Author: "Abubakar Abdulkarim" - Searchworks@Jio Institute Digital Library Search Results

81 results on '"Abubakar Abdulkarim"'

1. Energy management controllers: strategies, coordination, and applications

Author: Mutiu Shola Bakare, Abubakar Abdulkarim, Aliyu Nuhu Shuaibu, and Mundu Mustafa Muhamad
Subjects: Energy management controllers, Control strategies, Coordination mechanisms, Architectures, Real-world applications, Energy optimization, Energy industries. Energy policy. Fuel trade, HD9502-9502.5
Abstract: Abstract Energy management controllers (EMCs) are pivotal for optimizing energy consumption and ensuring operational efficiency across diverse systems. This review paper delves into the various control strategies utilized by energy management controllers and explores their coordination mechanisms. Additionally, it examines the architectures of energy management controllers and their real-world implementations. The paper surveys a spectrum of EMCs, including conventional-based, rule-based, optimization-based, hybrid methods, and commercial software-based approaches, highlighting their respective advantages and drawbacks. It investigates how these controllers are coordinated within complex energy systems to achieve optimal performance and adaptability. Furthermore, the review outlines different architectures of energy management controllers, ranging from centralized to decentralized designs, discussing their suitability for various applications and their impact on system performance. Real-world applications of energy management controllers in sectors such as smart grids, buildings, industrial processes, and transportation systems are examined. Case studies and examples demonstrate the efficacy of different control strategies and architectures in addressing specific energy management challenges and achieving desired outcomes. Overall, this review provides valuable insights into the current landscape of energy management controller design and implementation, offering direction for future research and development in the pursuit of energy optimization and sustainability.
Published: 2024
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2. Predictive energy control for grid-connected industrial PV-battery systems using GEP-ANFIS

Author: Mutiu Shola Bakare, Abubakar Abdulkarim, Aliyu Nuhu Shuaibu, and Mundu Mustafa Muhamad
Subjects: Predictive energy control, Gene expression programming, ANFIS, Solar PV-battery systems, Time of use pricing, Energy management, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract: Rising energy costs in Uganda's industrial sector have significantly increased manufacturing expenses and led to the closure of potential enterprises, underscoring the urgent need for efficient energy management solutions. The study presents an optimization-based predictive energy control model that integrates Gene Expression Programming (GEP) and Adaptive Network-based Fuzzy Inference Systems (ANFIS) for grid-connected solar PV-battery systems. The hybrid GEP-ANFIS model leverages GEP's strength in complex pattern recognition and ANFIS's adaptive learning capability to manage nonlinear data, resulting in more accurate and reliable energy predictions. The model utilizes historical load patterns, grid data, and solar PV/battery inputs to forecast load demand and solar power generation, optimizing energy usage based on Time of Use (TOU) pricing. The approach addresses the limitations of existing energy management techniques by enhancing predictive accuracy and ensuring seamless integration with industrial applications. The present work demonstrates that the proposed GEP-ANFIS double diode model consistently outperforms its counterparts, achieving a mean absolute percentage error (MAPE) of 7.25 %, a mean absolute deviation (MAD) of 2.95 %, and a root mean square error (RMSE) of 8.42 %. Moreover, the model exhibits superior accuracy in predicting short-term load demand, with a MAPE of 2.24 %, a MAD of 0.13 %, and an RMSE of 0.18 %. Additionally, the model results in an average energy cost reduction of 6.7 % for hybrid grid-connected solar PV/battery configurations, highlighting its economic benefits. The study's key contributions include the creation of a novel hybrid predictive model, significant cost savings, improved load prediction accuracy, and the integration of renewable energy sources into industrial energy management. The model's inferences can effectively address the challenges of rising energy costs, providing a robust framework for sustainable and efficient energy management in industrial settings.
Published: 2024
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3. Maximum power point tracking of a partially shaded solar photovoltaic system using a modified firefly algorithm-based controller

Author: Idoko Sunday John, Abubakar Abdulkarim, and Gbenga A. Olarinoye
Subjects: Photovoltaic system (PV) system, Maximum power point tracking (MPPT), Partial shading conditions (PSC), Firefly algorithm (FA), Flying squirrel search optimization (FSSO), Electrical engineering. Electronics. Nuclear engineering, TK1-9971, Information technology, T58.5-58.64
Abstract: Abstract Solar photovoltaic (PV) system is one of the most promising power systems based on renewable energy sources, with several advantages compared to others. However, solar PV systems have a challenge of low conversion efficiency because most of the irradiances of the sun, which are channelled to the PV panels, are not fully utilized for power consumption. A more challenging situation of the system occurs when some of its panels are obstructed from full reception of the solar irradiance, a case referred to as partial shading conditions (PSC) in solar PV systems. This leads to the generation of multiple, unequal power peaks in the system, from which the one with the highest power must be tracked for optimum utilization of the system. To this regard, this work presents a modified firefly algorithm-based controller, tied operationally with a DC–DC boost converter. A model was developed and simulated on MATLAB, for tracking the maximum power point of the system, both at constant solar irradiance and at PSC.
Published: 2023
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4. A comprehensive overview on demand side energy management towards smart grids: challenges, solutions, and future direction

Author: Mutiu Shola Bakare, Abubakar Abdulkarim, Mohammad Zeeshan, and Aliyu Nuhu Shuaibu
Subjects: Demand side management, Smart grid, Demand response, Optimization techniques, Machine language, Energy industries. Energy policy. Fuel trade, HD9502-9502.5
Abstract: Abstract Demand-side management, a new development in smart grid technology, has enabled communication between energy suppliers and consumers. Demand side energy management (DSM) reduces the cost of energy acquisition and the associated penalties by continuously monitoring energy use and managing appliance schedules. Demand response (DR), distributed energy resources (DER), and energy efficiency (EE) are three categories of DSM activities that are growing in popularity as a result of technological advancements in smart grids. During the last century, the energy demand has grown significantly in tandem with the increase in the global population. This is related to the expansion of business, industry, agriculture, and the increasing use of electric vehicles. Because of the sharp increase in global energy consumption, it is currently extremely difficult to manage problems such as the characterization of home appliances, integration of intermittent renewable energy sources, load categorization, various constraints, dynamic pricing, and consumer categorization. To address these issues, it is critical to examine demand-side management (DSM), which has the potential to be a practical solution in all energy demand sectors, including residential, commercial, industrial, and agricultural. This paper has provided a detailed analysis of the different challenges associated with DSM, including technical, economic, and regulatory challenges, and has proposed a range of potential solutions to overcome these challenges. The PRISMA reviewing methodology is adopted based on relevant literature to focus on the issues identified as barriers to improving DSM functioning. The optimization techniques used in the literature to address the problem of energy management were discussed, and the hybrid techniques have shown a better performance due to their faster convergence speed. Gaps in future research and prospective paths have been briefly discussed to provide a comprehensive understanding of the current DSM implementation and the potential benefits it can offer for an energy management system. This comprehensive review of DSM will assist all researchers in this field in improving energy management strategies and reducing the effects of system uncertainties, variances, and restrictions.
Published: 2023
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5. A review of dust-induced electromagnetic waves scattering theories and models for 5G and beyond wireless communication systems

Author: Emmanuel Alozie, Abdulwaheed Musa, Nasir Faruk, Agbotiname Lucky Imoize, Abubakar Abdulkarim, Aliyu D. Usman, Yusuf Olayinka Imam-Fulani, Kayode S. Adewole, Abdulkarim A. Oloyede, Olugbenga A. Sowande, Salisu Garba, Bashir Abdullahi Baba, Yinusa A. Adediran, and Lawan S. Taura
Subjects: Scattering, Electromagnetic wave, Attenuation, Cross-polarization, Dust storms, Science
Abstract: Dust particles and sand storms can cause attenuation and cross-polarization of electromagnetic wave propagation, especially at high frequencies above 10 GHz. Dust attenuation has been the focus of many research works, mainly with the deployment of a 5G wireless network in the FR-2 band (mmWave band, 23–53 GHz with TDD). This has led to the development of novel models to accurately predict and estimate attenuation. However, the existing review works have not adequately provided extensive taxonomies for these models to show the state-of-art and future research directions. This paper aims to bridge this gap by providing a comprehensive review of all electromagnetic scattering models in terms of their strengths, weaknesses, and applications. Lessons learned from the detailed survey have been stated and discussed extensively. Key findings from this review indicate that all the models developed were limited to the region where they were developed, with frequency and visibility levels as the two main parameters. The survey across regions showed no model was developed for Region 2, including the Americas, Greenland, and some of the eastern Pacific Islands. Among the dry regions of the globe, where dust and sand storms can occur either occasionally or frequently, it can be seen that only a few parts of these desert regions of Africa (Region 1) and Asia (Region 3) have been considered by authors for the development of prediction models for attenuation due to dust storms. Thus, this also shows the limitations of the overall deterministic models and presents the crucial need to develop new models or modify existing models to accurately predict dust attenuation in other regions, particularly in Africa.
Published: 2023
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6. Large scale survey for radio propagation in developing machine learning model for path losses in communication systems

Author: Haruna Chiroma, Ponman Nickolas, Nasir Faruk, Emmanuel Alozie, Imam-Fulani Yusuf Olayinka, Kayode S. Adewole, Abubakar Abdulkarim, Abdulkarim A. Oloyede, Olugbenga A. Sowande, Salisu Garba, Aliyu D. Usman, Lawan S. Taura, and Yinusa A. Adediran
Subjects: Path loss modeling, 5G wireless communication systems, Deep learning, Artificial neural network, Feature engineering, Machine learning, Science
Abstract: Several orthodox approaches, such as empirical methods and deterministic methods, had earlier been used for the prediction of path loss in wireless communication systems. These approaches are either inefficient or complex. Robustness and performance motivated the adoption of machine learning for modeling path loss in wireless communication systems in place of traditional modeling schemes. Surveys on modeling path loss in communication systems exist in the literature; however, emerging deep learning architectures in-depth analysis, machine learning taxonomies related to path loss, and in-depth analysis on feature engineering in modeling path loss are missing in the already published surveys. To fill this existing gap, a survey of machine learning modeling for path loss in wireless communication systems is conducted to resolve the outlined issues, hence making this survey unique. Synthesis and analysis of deep learning architectures to solve path loss problems in communication systems are hereby presented. New taxonomy – deep learning, nature-inspired meta-heuristic algorithms, and shallow algorithms approach to path loss modeling have been created. Analysis of feature engineering in path loss modeling is exploited. Lastly, challenges militating against the full potential of modeling path loss based on machine learning are highlighted and discussed. Alternative approaches for resolving the outlined challenges are also presented in the survey to help in designing more practical applications in the future.
Published: 2023
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7. ANN-based model for multiband path loss prediction in built-up environments

Author: Nasir Faruk, Quadri Ramon Adebowale, Imam-Fulani Yusuf Olayinka, Kayode S. Adewole, Abubakar Abdulkarim, Abdulkarim A. Oloyede, Haruna Chiroma, Olugbenga A. Sowande, Lukman A. Olawoyin, Salisu Garba, Aliyu D. Usman, Yinusa A. Adediran, and Lawan S. Taura
Subjects: Artificial neural networks, Path loss, Radio wave propagation, Multi-frequency band, Nigeria, Science
Abstract: Path loss propagation models are critically needed for optimum planning and deployment of wireless communication networks. However, the complexity exhibited by the propagated signals makes the prediction of the received losses difficult in built-up environments. There is however a new paradigm shift towards the application of computational methodologies, such as the Artificial Neural Networks (ANN), for multi-band path loss prediction. In this paper, we have developed a new ANN-based model for path loss prediction. The model was developed using large scale path loss data collected across 485 base stations in 6 urban cities of Nigeria, West Africa. The data collection, which spanned a period of 9 years, were taken over open areas, sub urban and urban environments, and the bands considered were 89.3 MHz, 103.5 MHz, 203.25MHz, 429.25 MHz, 529.25MHz, 615.25MHz, 629.25MHz, 900MHz, 1800 MHz and 2100MHz. The developed model was validated using independent path loss data across different frequencies, environments; and, distances and the results were compared with the popular empirical models such as Hata, COST 231 and Egli models, and to previously published ANN-based multi-frequency models. The global performance of 4.81 dB was obtained in terms of RMSE value with an R-value of 0.96, thus outperforming the existing ANN-based path loss models that were developed for multiple frequencies. Based on these findings, the proposed model can be deployed across all categories since the average RMSE values are all within the acceptable thresholds. Furthermore, the model is multi-frequency, thus will be suitable for multiple and complex environments, and usable for both short- and long-range wireless communication networks
Published: 2022
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8. Secure transmission in an unfriendly environment

Author: Lukman A. Olawoyin, Nasir Faruk, Abdulkarim A. Oloyede, Segun I. Popoola, Temitayo C. Adeniran, Nazmat T. Surajudeen-Bakinde, and Abubakar Abdulkarim
Subjects: Artificial noise, Full-duplex, Secure transmission, Average secrecy capacity, Secure outage probability, Information technology, T58.5-58.64
Abstract: This work investigates and show the performance of destination assisted node in ensuring secure communication in a dual-hop broadcast system. The information transmission occurs between the transmitters which are assumed to be equipped with single antenna through a number of intermediate untrusted relays to the receiver in the presence of multiple passive eavesdroppers. This work assumes that there is no direct link between the transmitter and the receiver and hence, the relay node, receives either the information or noise signal at every transmission processes. Since the transmission occurs in a two-phase, the legitimate receiver is contributing a degrading noise to both the eavesdropper and relay node channels during the first phase while it receives information from the transmitter through the relay during the second phase. Simulation results are used to illustrate the performance of the proposed scheme.
Published: 2020
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9. Expert System and Decision Support System for Electrocardiogram Interpretation and Diagnosis: Review, Challenges and Research Directions

Author: Kayode S. Adewole, Hammed A. Mojeed, James A. Ogunmodede, Lubna A. Gabralla, Nasir Faruk, Abubakar Abdulkarim, Emmanuel Ifada, Yusuf Y. Folawiyo, Abdukareem A. Oloyede, Lukman A. Olawoyin, Ismaeel A. Sikiru, Musa Nehemiah, Abdulsalam Ya’u Gital, and Haruna Chiroma
Subjects: electrocardiogram, ECG, cardiovascular disease, expert system, decision support system, heartbeat, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999
Abstract: Electrocardiography (ECG) is one of the most widely used recordings in clinical medicine. ECG deals with the recording of electrical activity that is generated by the heart through the surface of the body. The electrical activity generated by the heart is measured using electrodes that are attached to the body surface. The use of ECG in the diagnosis and management of cardiovascular disease (CVD) has been in existence for over a decade, and research in this domain has recently attracted large attention. Along this line, an expert system (ES) and decision support system (DSS) have been developed for ECG interpretation and diagnosis. However, despite the availability of a lot of literature, access to recent and more comprehensive review papers on this subject is still a challenge. This paper presents a comprehensive review of the application of ES and DSS for ECG interpretation and diagnosis. Researchers have proposed a number of features and methods for ES and DSS development that can be used to monitor a patient’s health condition through ECG recordings. In this paper, a taxonomy of the features and methods for ECG interpretation and diagnosis were presented. The significance of the features and methods, as well as their limitations, were analyzed. This review further presents interesting theoretical concepts in this domain, as well as identifies challenges and open research issues on ES and DSS development for ECG interpretation and diagnosis that require substantial research effort. In conclusion, this paper identifies important future research areas with the purpose of advancing the development of ES and DSS for ECG interpretation and diagnosis.
Published: 2022
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10. Large-scale radio propagation path loss measurements and predictions in the VHF and UHF bands

Author: Nasir Faruk, I.Y. Abdulrasheed, N.T. Surajudeen-Bakinde, Emmanuel Adetiba, A.A. Oloyede, Abubakar Abdulkarim, Olugbenga Sowande, Ayodele H. Ifijeh, and Aderemi A. Atayero
Subjects: Path loss measurement, Kriging Interpolation Method, Prediction model, Radio propagation, Science (General), Q1-390, Social sciences (General), H1-99
Abstract: For decades now, a lot of radio wave path loss propagation models have been developed for predictions across different environmental terrains. Amongst these models, empirical models are practically the most popular due to their ease of application. However, their prediction accuracies are not as high as required. Therefore, extensive path loss measurement data are needed to develop novel measurement-oriented path loss models with suitable correction factors for varied frequency, capturing both local terrain and clutter information, this have been found to be relatively expensive. In this paper, a large-scale radio propagation path loss measurement campaign was conducted across the VHF and UHF frequencies. A multi-transmitter propagation set-up was employed to measure the strengths of radio signals from seven broadcasting transmitters (operating at 89.30, 103.5, 203.25, 479.25, 615.25, 559.25 and 695.25 MHz respectively) at various locations covering a distance of 145.5 km within Nigerian urban environments. The measurement procedure deployed ensured that the data obtained strictly reflect the shadowing effects on radio signal propagation by filtering out the small-scale fading components. The paper also, examines the feasibilities of applying Kriging method to predict distanced-based path losses in the VHF and UHF bands. This method was introduced to minimize the cost of measurements, analysis and predictions of path losses in built-up propagation environments.
Published: 2021
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11. Path Loss Predictions in the VHF and UHF Bands Within Urban Environments: Experimental Investigation of Empirical, Heuristics and Geospatial Models

Author: Nasir Faruk, Segun I. Popoola, Nazmat T. Surajudeen-Bakinde, Abdulkarim A. Oloyede, Abubakar Abdulkarim, Lukman A. Olawoyin, Maaruf Ali, Carlos T. Calafate, and Aderemi A. Atayero
Subjects: ANFIS, artificial neural networks, backpropagation, path loss, Kriging, radio propagation, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract: Deep knowledge of how radio waves behave in a practical wireless channel is required for effective planning and deployment of radio access networks in urban environments. Empirical propagation models are popular for their simplicity, but they are prone to introduce high prediction errors. Different heuristic methods and geospatial approaches have been developed to further reduce path loss prediction error. However, the efficacy of these new techniques in built-up areas should be experimentally verified. In this paper, the efficiencies of empirical, heuristic, and geospatial methods for signal fading predictions in the very high frequency (VHF) and ultra-high frequency (UHF) bands in typical urban environments are evaluated and analyzed. Electromagnetic field strength measurements are performed at different test locations within four selected cities in Nigeria. The data collected are used to develop path loss models based on artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), and Kriging techniques. The prediction results of the developed models are compared with those of selected empirical models and field measured data. Apart from Egli and ECC-33, the root mean squared error (RMSE) produced by all other models under investigation are considered acceptable. Specifically, the ANN and ANFIS models yielded the lowest prediction errors. However, the empirical models have the lowest standard deviation errors across all the bands. The findings of this study will help radio network engineers to achieve efficient radio coverage estimation; determine the optimal base station location; make a proper frequency allocation; select the most suitable antenna; and perform interference feasibility studies.
Published: 2019
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12. Utilizing Machine Learning for Sensor Fault Detection in Wireless Sensor Networks.

Author: Abubakar Abdulkarim, Israel Ehile Ehile, and Refik çaglar Kizilirmak
Published: 2024
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13. Access to and quality of elective care: a prospective cohort study using hernia surgery as a tracer condition in 83 countries

Author: Dönmez, A Eylül, Goswami, Aakansha Giri, Raheja, Aashna, Bhadani, Aayush, El Kady, Abd Elrahman Safwat, Alniemi, Abdalaziz, Awad, Abdalkarim, Aladl, Abdalla, Younis, Abdalla, Alwali, Abdallah, Khalil, Abdallah, Mansour, Abdallah, Elkhouly, Abdallah Mohamed, Rashad Temerik, Abdallah, Hasan, Abdallatef, Chied, Abdelhafid, Abdraba, Abdelhamid, Hrora, Abdelmalek, Abdelshafi, Abdelrahman, Alwali, Abdelrahman, Maraqa, Abdelrahman, Ghaffar, Abdul, Chekfa, Abdul Jabar, Al Balushi, Abdul Majeed, Quddus, Abdul, Hammadieh, Abdul Rahman, Muntaka, Abdul-Jalilu Mohammed, Asekun, Abdulazeez, Alshahrani, Abdulaziz, Jowharji, Abdulaziz, Alshukre, Abdulbaset, Khair Etareig, Abdulhafid, Abubakar Abdulkarim, Abdulhafiz, Ashiru, Abdulhafiz, Alailesh, Abdulhamid, Al-Mallah, Abdullah, Baydoun, Abdullah, Chaudhry, Abdullah, Askin, Abdullah Emre, Almutairi, Abdulmjeed, Belkhair, Abdulmunem, Abdllah, Abdulrahman, Alhammali, Abdulrahman, Basalim, Abdulrahman, Abouelnagah, Abdulrahman Galal Mohamed Mostafa, Ghazal, Abdulrahman, Mohammed, Abdulrahman, Qasem, Abdulrahman, Anadani, Abdulrazak, Jimoh, Abdulrazaq, Lawal, Abdulrazzaq Oluwagbemiga, Khaity, Abdulrhman, Lawal, Abdulwahab, Elzoubi, Abdurrahim Esseid, Sheshe, Abdurrahman Abba, Cetişli, Abdurrahman Furkan, Oyedele, Abeeb, Aljahdali, Abeer, Aboelnasr, Abeer Gamal Elsyed, Demessie, Abel, Bhargava, Abhilasha, Sonkar, Abhinav Arun, Bavaharan, Abhirame, Khan, Abid, Campbell, Abigail, Oyelekan, Abimbola Adeola Akintunde, Okunlola, Abiodun Idowu, Ojewuyi, Abiodun, Ekerin, Abiola, Saleh, Abobakr, Khairy, Abouelatta, Muthunayagam, Abraham Benjamin, Botha, Abraham, Teshome Sahilemariam, Abraham, Nawawi, Abrar, Muhammad, Abubakar Bala, Dahiru, Abubakar, Yahaya, Abubakar, Abdelmalik, Abubaker, Anuar, Abul Akmal Arif, Ousseini, Adakal, Leon -Del- Angel, Adalberto, Frankel, Adam, Gyedu, Adam, Lim, Adam, Lukáč, Adam, Peckham-Cooper, Adam, Sabbah, Adam, Varga, Adam, Sanou, Adama, Issaka, Adamu, Ningi, Adamu, Yeshitila, Addis, Yingess, Addisu, Olugbami, Adebayo, Moses, Damola-Okesiji, Adebola, Lawal, Adedayo, Ojo, Adedoyin, Hashmi, Adeel, Fakoya, Adegbolahan, Ishola, Adegoke, Abiodun, Adekunle, Ajayi, Adekunle, Mouffokes, Adel, Bonelli, Adele, Adekoya, Adeleke, Akeem Aderogba, Adeleke, Özcan, Adem, Ayoade, Ademidun, Adeyeye, Ademola, Agbaje, Ademola, Talabi, Ademola, Ademuyiwa, Adesoji, Adewumiya, Adesoji, Ademuyiwa, Adesoji O, Aderounmu, Adewale, Adisa, Adewale, Oke, Adewale, Ragab, Adham, Alzadjali, Adil, Baksi, Aditya, Jayapalan, Aditya, Md Yunos, Adnan, Pisanu, Adolfo, Salazar, Adolfo, Salinas Barragan, Adrian Alberto, Fox, Adrian, Stollberg, Adrian, Franco, Adriana, Neves, Adriana, Vricheva, Adriana, Hodonou, Adrien Montcho, Aghayeva, Afag, Liaquat, Affifa, Alsultan, Afnan, Morad, Afnan, Kalidis, Afroditi Angella, Gkouniaroudi, Agathi, Karakosta, Agathi, Lovi, Agbenya, Yevide, Agossou Barthélémy, Duro, Agustin, Rodriguez Gonzalez, Agustin, Tariq, Ahbala, Abaidalla, Ahmad, Abuhammad, Ahmad, Abuhantash, Ahmad, Mansour, Ahmad Adel, Ahmad Zaidi, Ahmad Al Hafeez, Alahmad Alismael, Ahmad, Alayed, Ahmad, Alfarwan, Ahmad, Alhaj, Ahmad, Ali, Ahmad, Alroobi, Ahmad, Alsheikh, Ahmad, Alusef, Ahmad, Alzu'Bi, Ahmad, Kayali, Ahmad Amir, Bouhuwaish, Ahmad, Doghaim, Ahmad, El-Sherbiney, Ahmad, Ghazal, Ahmad, Ramly, Ahmad Nasir, Raza, Ahmad, Qureshi, Ahmad Uzair, Arnaout, Ahmad Yamen, Abdelhamid, Ahmed, Abuthaher, Ahmed, Adel, Ahmed, Ahmayda, Ahmed, Al-Mouahhed, Ahmed, Alagha, Ahmed, Albalawi, Ahmed, Albhaisi, Ahmed, Alrifaee, Ahmed, Azam, Ahmed, Barakat, Ahmed, Al-Hajjaj, Ahmed Basim Abed, Dawoud, Ahmed, El Shamarka, Ahmed, El-Bastwesy, Ahmed, Elghrieb, Ahmed, Elkhalifa, Ahmed, Elmosalamy, Ahmed, Elshazli Mahmoud, Ahmed, Montaser, Ahmed G., Gbeadese, Ahmed, Haty, Ahmed, K. Ali, Ahmed, Awad, Ahmed K., Kedwany, Ahmed, Khalleefah, Ahmed, Abbas, Ahmed M., Allam, Ahmed M., Maher, Ahmed, Elsayed, Ahmed Mohamed, Mohamed Ibrahim Mohamed, Ahmed, Mostafa, Ahmed, Nabil, Ahmed, Nada, Ahmed, Ragheb, Ahmed, Abdelrahman, Ahmed Saber Mohamed, Sabry, Ahmed, Sakr, Ahmed, Elkhodary, Ahmed Salah, Shaheen, Ahmed, Ammar, Ahmed Siddique, Hameed, Ahmer, Akmercan, Ahmet, Aslan, Ahmet, Barcin, Ahmet, Ciftci, Ahmet Burak, Bozkurt, Ahmet Çağlar, Sarı, Ahmet Can, Yaşar, Ahmet Can, Develioğlu, Ahmet, Öztürk, Ahmet Mücteba, Sanli, Ahmet Necati, Rencuzogullari, Ahmet, Yildiz, Ahmet, Kaan, Ahmet Zahit, Toi, Ahouefa Chourika Sakinath, Aljamoudi, Aida, Cheung, Aiden Chak Kei, Gkoutoula, Aikaterini, Kalogeropoulou, Aikaterini, Sarafi, Aikaterini, Abo Al Shamat, Aiman, Sanon, Aimé Serge Titianma, Sanon, Aimée Florence, Hiller, Aimée, Costas-Chavarri, Ainhoa, Lombardero, Ainhoa, Fraile, Ainoa, Bojazyah, Aisha, Kamal, Aisha, Gill, Aisling, Hada, Aïssatou, Gulla, Aiste, Mačiulaitytė, Aistė, 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N, Felix, Alahmad, Feras, Alnimri, Feras, Haddad, Feras, Gool, Ferhana, Castro, Fernanda, Diaz, Fernanda, Lucero, Fernanda, Vovola, Fernanda, Mahnic, Fernando, Mercado Sanchez, Fernando, Prieto La Noire, Fernando, Soggiu, Fiammetta, Tsige, Fikreab, Brzeszczyński, Filip, Rudisch, Filip, Valente Costa Pinto, Filipa, Ramalho De Almeida, Filipe, Banchini, Filippo, Palomino Escalante, Fiorella, Fadzlullah, Fitri, Terefe, Fitsum, Sulo, Fjorenta, Ciccarone, Flavia, Tirelli, Flavio, Krämer, Florian, Grama, Florin, Spanos, Foivos, Solimene, Folco, Akinwande, Foluso, Osman, Forzia, Stefou, Foteini, Kyramargios, Fotios, Stavratis, Fotios, Alassani, Fousseni, Ascari, Francesca, Cammelli, Francesca, D'Agostino, Francesca, Tropeano, Francesca Paola, Peters, Francesca, Ré, Francesca, Brucchi, Francesco, Casti, Francesco, Coratti, Francesco, Ferrara, Francesco, Floris, Francesco, Izzo, Francesco, Maffei, Francesco, Palmieri, Francesco, Pata, Francesco, Porcelli, Francesco, Selvaggi, Francesco, 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Judy, Mühlhäusser, Julia, Sidorovskaia, Julia, Carrizo, Julian, Napoli, Juliana, Pereira-Macedo, Juliana, Ribeiro, Juliana, De Deken, Julie, Nnoli, Juliet, Paredes, Julieta, Zevallos-Quiroz, Julio Cesar, Gonzalez Garcia, Julio, Adjei, Julius, Olaogun, Julius, Kutkevičius, Juozas, Metzger, Jürg, Košir, Jurij Aleš, Kosir, Jurij, Seyi-Olajide, Justina, Zajac, Justyna Karolina, Dhima, Jyoti, Dhiman, Jyoti, Shreyas, K, Türker, Kadir Yağız, Lee, Kai, Khutsishvili, Kakhi, Yu, Kam Keung Auston, Das, Kamala, Özdoğan, Kamil, Reddy, Kamireddy Madana Raghava, Kabulov, Kamran, Nahar, Kamrun, Rajaratnam, Kanapathippillai, Wijesinghe, Kanchana, Sevnaran, Kapil, Khalil, Karam, Singh, Karanbir, Fayed, Kareem, Booyse, Karien, Geiger-Timm, Karin, Maharaj, Karl, Bhutia, Karma, Richter, Karolina, Komorowska, Katarzyna, Urbańska, Katarzyna, Waddell, Kate, Kambouri, Katerina, Tata, Katerina, Richetti, Katharina, Griffin, Katherine, McKenzie, Katherine, Tambudze, Katherine, Hall, Katheryn, Chu, Kathryn, Theodoropoulou, Katina, Kröning, Katrin, Bozada-Gutiérrez, Katya, Raghuwanshi, Kaustubh, J B, Kavitha, Ahmed Ibrahim, Kefah, Bwala, Kefas John, Iles, Kelly, Jasso García, Kelvin, Oğur, Kemal, Fretwell, Kenneth, Oluchukwu, Kenneth, Onyekachi, Kenneth, Voon, Kenneth, Oderoha, Kevin Ewomazino, Nieto Yrigoin, Kevin, Quispe De La Roca, Kewin, Anaam, Khadega, Bensmain, Khadija, Shwail, Khadija, Akter, Khadiza, Sawaftah, Khaled Ahmad, Shamiyah, Khalid Adnan, Bhatti, Khalid, Mohammed, Khalid Miftah Ghuraybeel, Ayyoub, Khalil, Cholah, Khalil, Rahman, Khandakar Rezwanur, Abdulrahman, Khawla, Al-Shami, Khayry, Hayat, Khizar, Al Hinai, Khulood, Taghavi, Kiarash, Shodunke, Kikelomo, Abo Zaal, Kinaz, Ewool, Kingsley, Gaikwad, Kiran, Shemyatovsky, Kirill, Dey, Kirsty Elaine, Mishra, Kirti Kumar, Rathod, Kirtikumar J, Senanayake, Kithsiri Janakantha, Noguchi, Kiyonari, Kordeni, Kleoniki C., Dembele, Klétigui Samuel, Spassov, Kolyo, Khalid, Komal, Petrenko, Konstantin, Bekiaridou, Konstantina, Rekouna, Konstantina, Athanassiou, Konstantinos, Avgerinos, Konstantinos, Bouchagier, Konstantinos, Bouliaris, Konstantinos, Bramis, Konstantinos, Iliakopoulos, Konstantinos, Kontzoglou, Konstantinos, Ntatsis, Konstantinos, Pavlopoulos, Konstantinos, Perivoliotis, Konstantinos, Polychronopoulos, Konstantinos, Giannakopoulos, Konstantinos S., Zakkas, Konstantinos, Zapsalis, Konstantinos, Koumarelas, Konstantinos-Eleftherios, Mori, Krinal, Ooi, Krisada, Ascencio Diaz, Kriscia Vanessa, Jasaitis, Kristijonas, Nieuwenhuys, Kristin, Atherton, Kristy, Smith, Kristy, Sharma, Kruti, Jaffry, Kumail, Lehmann, Kuno, Ayad, Kusay, Luthra, Kush Kumar, Nanayakkara, Kushan, Agbedinu, Kwabena, Oduro-Boateng, Kwaku Boakye, Boakye-Acheampong, Kwame, Sim, Kwang Kiat, Yalley, Kwekuma, Collins, Kyeremeh, Muscat, Kyle, Hofmann, Kyra, Lambri, Kyriaki, Bananis, Kyriakos, Nassim, Kyrillos, Allan, Lachlan, Codina Corrons, Laia, Hijazein, Laith, Moolla, Laith, Sweidan, Laith, Rai, Lajpat, Devi, Lakshmi, Fountoulis, Lampros, Andreski, Lara, Bonello, Lara, Rodrigues Madeira, Lara, Tafesh, Lara, Yasin, Lara, Martinez, Laura, Fortuna, Laura, Peña Balboa, Laura Gabriela, García-Zambrano, Laura, Bolaños, Laura Isabela, Jiménez, Laura, Lely, Laura, Ortega Lechuga, Laura, Rossi, Laura, Rubin, Laura, Ruiz-Villa, Laura, Sequi, Laura, Sahan, Laura-Ann, Johnstone, Lauren, Monteiro, Lauren, Abdullahi, Lawal Barau, Jovcheski, Lazo, Siragusa, Leandro, Kang, Leannedra, Elgebaly, Leenah, Mansour, Lefteris, Robine-Durnell, Lélia, Bray, Lemuel Davies, Mohammed, Lena, Licari, Leo, Onyebulu, Leonard, Chieng, Leonard Ron, Solaini, Leonardo, Chardalias, Leonidas, Fountarlis, Leonidas Ilias, Van Den Hil, Leontine, Tapia Moral, Leopoldo, Petashvili, Leri, Heeren, Letícia, Laface, Letizia, Niyidukunda, Lewis, Barnard, Liam, Torres Bavestrello, Lidice Veronica, Hasan, Lilav, Dyab, Lima, Venclauskas, Linas, Beukes, Linda, Gabellini, Linda, Liepa, Linda, Zeng, Lingjuan, Dubs, Linus, Rampersad, Lisa, Catozzi, Livio, Castro, Lizeth, Milic, Ljiljana, Shawesh, Lobna, Anyanwu, Lofty-John, Khalifa, Lojina, Cheng, Lok Pong, Manoj Joshua, Lokavarapu, Shammas, Lora, Fuentes Rivera Lau, Lorena, Rodríguez Gómez, Lorena, Capello, Lorenzo, Epis, Lorenzo, Fatucchi, Lorenzo Maria, Rende, Lorenzo, Ripamonti, Lorenzo, Ackam, Louis, Moniz, Lourenço, Bains, Lovenish, Alriyami, Lubna, Alokshi, Lubnah, Martinek, Lubomir, Tulinsky, Lubomir, Samison, Luc, Lo Piccolo, Luca Benedetto, Cardinali, Luca, Nespoli, Luca Carlo, Casingena, Luca, Degrate, Luca, Bonomo, Luca Domenico, Morelli, Luca, Ottaviani, Luca, Resca, Luca, Scaravilli, Luca, Schiavone, Luca, Theuil, Luca, Casalduero, Lucas, Lee, Lucas D., Granero, Lucas, Caram, Lucas Jose, Barni, Lucia, Cidade Costa, Luciana, Paredes, Luciana, Poggi, Luciano, Marquez, Lucila, Garciandia, Lucio, Taglietti, Lucio, Pramod, Ludiya, Stella, Ludovica, Carbone, Ludovico, Bracciano, Luigi, Cobellis, Luigi, Conti, Luigi, Fedele, Luigi, Ragazzini, Luigi, Simonelli, Luigi, Verre, Luigi, Flores Chávez, Luis Adrián, Rea Bocanegra, Luis Alberto, Pelayo Orozco, Luis Ángel, Asensio Gomez, Luis, Bravo, Luis, Flores Chávez, Luis Manuel, Poggi, Luis, Cabezudo, Luis Ramón, Sante Serna, Luis, Tallon-Aguilar, Luis, Talé-Rosales, Luis-Fernando, Chantada, Luisa, Moreira, Luísa, Hasan, Lujain, M Mheidat, Lujain, Eisner, Lukas, Gantner, Lukas, Havranek, Lukas, Majerčák, Lukáš, Pánči, Lukáš, Nawacki, Łukasz, Adagrah Aniakwo, Luke, Bromley, Luke, Green, Luke, Paterson, Luke, Peters, Luke, Abdur-Rahman, Lukman, Omomeji, Lukman, Amosu, Lukmon, Kolongi, Lungushinga Christopher, Bin Aizan, Luqman Naim, Imchen, Lurong, Chang, Lydia, Mukamazera, Lydie, Katsiaras, Lykoyrgos, Al-Boukhari, Lynn, Chong, Lynn, Karydakis, Lysandros, Peris, M. Roosindu, Cancelas, Mª Dolores, Kariem, Maahir, Amoako-Boateng, Mabel, Alshamikh, Mabroukah, Ishak, Mabruok, Narayanan, Machingal, Matyja, Maciej, Walędziak, Maciej, Zounon, Mack-Arthur, Trindade, Madalena, Shahid, Madeeha, Kelly, Madeleine, Bajwa, Madiha, Bowles, Madison, Roussos, Madison, Sampaio-Alves, Mafalda, Manfredini, Magda, Kołomańska, Magdalena, Redynk, Magdalena, Farooq, Maham, Ali, Mahamudu Ayamba, Rodha, Mahaveer Singh, Alsalawi, Mahdi, Lodha, Mahendra, Sethi, Mahesh Kumar, Khalil, Mahfoud, Singh, Mahima, Abdualqader, Mahmmoud yehia, Abdelhafez, Mahmood, Sersarah, Mahmood, Abdelreheem, Mahmoud, Abu Al Amrain, Mahmoud, Barbarawi, Mahmoud, Diab, Mahmoud, Eissa, Mahmoud, ElFiky, Mahmoud, Elmesalmi, Mahmoud, Elmousili, Mahmoud, Fahmy, Mahmoud, Faisal, Mahmoud, Jabal, Mahmoud, Saad, Mahmoud M., Mahafdah, Mahmoud, Marei, Mahmoud Marei Abdelaziz, Mostafa, Mahmoud, Reda, Mahmoud, Zahran, Mahmoud, Suleman, Mahmowd, Genç, Mahmut Salih, Haghighat Ghahfarokhi, Mahta, Abubakar, Maimuna, Haimona, Mairarangi, Camuera, Maite, H. Oweidat, Majd, Mansour, Majd, Kalabić, Majda, MohammedAli, Majdeddin, Abu Daoud, Majdi, Almahjoub, Majdolin, Bilfaqirah, Majed, Yigah, Makafui, Akkawe, Malak, Dery, Malcolm, West, Malcolm, Rius, Malena, Nandasena, Malith, Aljarawn, Mallak, Masaaod, Mallak, Manangi, Mallikarjuna, Windsouri, Mamadou, Battili, Mamata, Rakotonaivo, Mamisoa Judicaël, Benghazi, Manaji, Al-Dhaheri, Manal, Almaqrahi, Manal, Katif, Manal, Alshami, Manar, Ibrahim, Manar, Ramazanov, Manas, Kaur, Mandeep, Agrawal, Manish Kumar, Pathak, Manish, Aggarwal, Manisha, Chandrasegaram, Manju, Anandan, Manoj, K S D, Manoj Kishan Lal, Kumar, Manoj, Sarda, Manoj, K B, Manojkumar, Jokubauskas, Mantas, Moreno Gonzales, Manuel Arturo, Cruz, Manuel, Diez Alonso, Manuel, Garcia, Manuel, Perez, Manuel, Mosquera Paz, Manuel Santiago, Cammelli, Manuela, Mercurio, Manuela, Singh, Manvinder, Taamreh, Manwa, Canals Sin, Mªpilar, Carbonell Pradas, Mar, Nunes, Mara, Sawaftah, Marah Ahmad, Khalil, Maram, Schneider, Marcel André, Steffani, Marcella, Pisano, Marcello, Doniquian, Marcelo Alejandro, Martínez Bareiro, Marcelo Nicolás, Pagani, Marcelo, Scortechini, Marcelo, Carvalho, Márcia, Sánchez Audelo, Marco Antonio, Brizzolari, Marco, Ceresoli, Marco, De Prizio, Marco, Amisano, Marco Francesco, Gramellini, Marco, Marcianò, Marco, Mariani, Marco, Milone, Marco, Montagna, Marco, Piccino, Marco, Santos, Marco, Dyer, Marcus, Kang, Marcus, Mahadi, Mardhiana, Zawadzki, Marek, Yinusa, Margaret, Bernardo, Margarida, Nunes Luís, Margarida, Gambelli, Margherita, Flint, Margot, Aggelidou, Maria, Bequis, Maria Agustina, Sotiriou, Maria Aikaterini, Ñañez, Maria Alejandra, Tahir, Maria Ambreen, Gascón Domínguez, María Ángeles, Asimakidou, Maria, Mourato, Maria Beatriz, Blanco, Maria, Christou, Maria, Coronas Soucheiron, Maria, Pignanelli, Maria Costanza, Kalaydjian, María Cristina, Martí-Ejarque, Maria del Mar, Olmedo Reinoso, María Del Mar, Cebollero, María Del Pilar, Derattani, Maria, Gama Caldeira, Maria Do Carmo, Drogouti, Maria, Gonzalez-Gonzalez, Maria Elena, Muñoz Fernández, María Elena, Muriel, María Emilia, Duran, María Eugenia, Zarate Casas, María Fernanda, Florou, Maria, Piacentini, Maria Gaia, Seixo, Maria Inês, Bellini, Maria Irene, Peña Soria, Maria Jesús, Martínez, María José, Medina, Maria José, Rueda Medécigo, María José, Karakeke, Maria, Kausar, Maria, Kyriazi, Maria, Marqueta De Salas, Maria, Modolo, Maria Marta, Mateu, Maria, Mavri, Maria, El Ghoul Miliotou, Maria Melina, Moreno Gijon, Maria, Papadoliopoulou, Maria, Proclamà, Maria Pia, Picciochi, Maria, Reis, Maria, Rennis, Maria, D'Anna, Maria Rosa, Ruffoli, Maria, Ruiz Soriano, María, Sánchez Ramirez, Maria, Sánchez-Rubio, María, Schüler, Maria, Sotiropoulou, Maria, Barrio Renteria, Maria Teresa, Tsopozidi, Maria, Vasconcelos, Maria, Facchino, Maria Vittoria, Wikar, Maria, Aguilera-Arevalo, Maria-Lorena, Abdu, Mariam, Asarbakhsh, Mariam, Elmiesiry, Mariam, Ashong, Marian Esi, Gomes, Mariana, Capuano, Marianna, Lill, Marianne, Nieto Galvan, Mariano, Osso, Mariasara, Olivos, Maricarmen, Sacdalan, Marie Dione, Weber, Marie-Christin, Gonzalez, Marijose De Cristo, Ferreira, Marília, Infantes Ormad, Marina, Kouliou, Marina Nektaria, Ransome, Marina, Vicario Bravo, Marina, Cuesta Argos, Mario, Faletar, Mario, Giuffrida, Mario, Lainez Escribano, Mario, Pacilli, Mario, Pannullo, Mario, Rodriguez-Lopez, Mario, Trejo-Avila, Mario, Merrakos, Marios, Tello Jimenez, Marisol, Kalisvaart, Marit, Quaunine, Marium, Perera, Mariyan, Harris, Mark, Youssef, Mark Melad Thabet, Peter, Mark, Philipp, Mark, Portelli, Mark, Jesudason, Mark Ranjan, Sammut, Mark, Tomlinson, Mark, Zammit Vincenti, Mark, Despotidis, Markos, Albertsmeier, Markus, Quante, Markus, Löffler, Markus W., Gurung, Markush, Gumsheimer, Marlena, Benamrouche, Maroua, Chaccour, Maroun, Ahmed, Marriam, Farooqui, Marryam Riaz, Angelini, Marta, Ortega Escudero, Marta, Martin Gimenez, Marta Pilar, Reia, Marta, Scricciolo, Marta, Caramantin Obando, Martha Maria, Gosselink, Martijn, Bertrand, Martin, Dum, Martin, Kajic, Martin, Karamanliev, Martin, Kyereh, Martin, Lucchini, Martin, Schön, Martin, Morna, Martin Tangnaa, Binda, Martina, Ceolin, Martina, Martorana, Martina, Zambon, Martina, Shams, Marvi, Alansary, Marwa, Alnuwayli, Marwa, Khalifa, Marwa, Bahnacy, Marwan, Iqreewi, Marway, Nnabagulanyi, Mary, Saleem, Marya, Alhimyar, Maryam, Kamal, Maryam, Masood, Maryam, Razaq, Maryam, Siddique, Maryam, Lazo Ramírez, Maryzela, Edeeb, Masaoud, Solkar, Maseera, Adetoyi, Mashood, Adeniyi, Caccetta, Massimiliano, Casati, Massimiliano, Veroux, Massimiliano, Dugo, Massimo, Bevanda, Mateo, Santillan, Mateo, Mietła, Mateusz, Pryt, Mateusz, Muir, Mathew, Bei, Matilda, McGuinness, Matt, Aulicino, Matteo, Castrovillari, Matteo, Filardo, Matteo, Palmeri, Matteo, Pisano, Matteo, Rottoli, Matteo, Gjoka, Mattheus, Binks, Matthew, Corcos, Matthew, Kwon, Matthew, Maybury, Matthew, Sammut, Matthew, Tutton, Matthew, Watson, Matthew, Biebl, Matthias, Janda, Matthias, Maak, Matthias, Wichmann, Matthias, Berselli, Mattia, Gritti, Mattia, Molteni, Mattia, Pacilli, Maurizio, Favoriti, Mauro, Garino, Mauro, Podda, Mauro, Santarelli, Mauro, Alfaid, Mawada, Albert, Mawadri Jimmy Isaac, Oyortey, Mawuenyo Attawa, Enßlin, Max, Berlet, Maximilian, Brunner, Maximilian, Kießler, Maximilian, Scheiterle, Maximilian, Sohn, Maximilian, Busch, Maximiliane, Perkins, Maya, Sabboh, Maya, Badkur, Mayank, Okudero, Mayowa, Mohamedshafee, Maysoon, Al-Juaifari, Maytham Aqeel, Elesseily, Mazen, Mohammad, Mazen, Nikberg, Maziar, Jean Claude, Mbonicura, Şermet, Medeni, Chisthi, Meer, Luthra, Meera, Sulciner, Megan, Kaple, Meghali, Bhat, Meghana, Koç, Mehmet Ali, Avci, Mehmet Alperen, Kizilkaya, Mehmet Celal, Kara, Mehmet Emin, Ozcelik, Mehmet Faik, Ozsoy, Mehmet Sait, Zaigham, Mehreen, Mesfin, Mekdelawit, Kalender, Mekselina, Mellado Tellez, Mel Paul, González De Miguel, Melania, Farrugia, Melanie, Theodoridou, Melanie, Barcelona, Melden Darrell, Aktas, Melik Kagan, Fernández Zurita, Melissa Andrea, Bautista, Melissa, Park, Melissa, Rodríguez-Ordoñez, Melissa-Zohemia, Yashar, Meltem, Worku, Mengistu, Al-Fraijat, Meran, Estaire Gómez, Mercedes, Shoshkova, Meri Danailova, Kruščica, Merima, Tanal, Mert, Çuhadar, Merve, Tokocin, Merve, Agyapong, Meshach Manu, Erkaya, Metincan, Okechukwu, Mgbako, Adinku, Michael, Bickford, Michael, Ediale, Michael, Issa, Michael, Konstantinidis, Michael K., Lie, Michael, M. Nathan, Michael, Maclean, Michael, Nortey, Michael, Pellen, Michael, Pham, Michael, Pitiakoudis, Michael, Singh, Michael Prodip, Spartalis, Michael, Van Der Colf, Michael, Wilson, Michael, Billis, Michail, Karanikas, Michail, Papamichail, Michail, Vailas, Michail, Kisielewski, Michał, Kusiński, Michał, Nycz, Michał, Święch, Michał, Fagbayimu, Micheal, Adamina, Michel, Fiogbe, Michel, Prudhomme, Michel, Angelucci, Michela, Campanelli, Michela, Cricrì, Michele, Grande, Michele, Manigrasso, Michele, Scopelliti, Michele, George, Michelle, Mozel, Michelle, Galasyuk, Mick, Chevallay, Mickael, Giuliano, Micol, Dobón Rascón, Miguel Ángel, Fernandez Romero, Miguel Angel, García Ureña, Miguel Ángel, Zaragoza Mendieta, Miguel Ángel, Bejarano Serrano, Miguel, Brito, Miguel, Calderon, Miguel, Jurado Román, Miguel, Palas, Miguel, Li Valencia, Miguel Roberto, Sebastián-Mendoza, Miguel-Julián, Muresan, Mihai-Stefan, Slavchev, Mihail, Agapov, Mikhail, Milentijević, Milica, Catterall, Millie, Stjepanovic, Milos, Doss, Mina, Natey, Mina, Aikins, Minas, Mattis, Minca, Ekanayake, Minoli Tharushika, Tora, Mir Mehrab Sharmin, Alsharayri, Mira, Shalaby, Mira, Boras, Miran, Riba Martínez, Mireia, Mogiatti, Mirella, Salibašić, Mirhan, Biancu, Miriam, Cappiello, Miriam, Koschke, Miriam Luise, Sadek, Mirna, Szura, Miroslaw, Horga, Miruna, Dason, Mishael, Tayyab, Mishal, Imirski, Mitko, Pejović, Mladen, Tabaza, Mo'Ath, Alneasan, Moaaz, Shalkamy, Moamen, Issa, Moammad Issa, Erfan, Moatasem, Ewedah, Moataz, Srour, Moayad, Beletachew, Moges, Abbas, Mohamad, Farho, Mohamad Ali, Marawy, Mohamad Kher, Klib, Mohamad, Morjan, Mohamad, Sawas, Mohamad Nabhan, Elghriani, Mohamed Abdelbaset Masoud, Abdelmaboud, Mohamed, Abdelmaksoud, Mohamed, Abdullahi, Mohamed, Abo Abdo, Mohamed, Ahmed, Mohamed, Ahmoud, Mohamed, Al Sayed, Mohamed, Suliman, Mohamed Almouafaq, Alsori, Mohamed, Altajouri, Mohamed, Assalhi, Mohamed, Berrakkouch, Mohamed, Elnour, Mohamed, Abdelsalam, Mohamed Elsayed Elaraby Abdelrahim, Elsayed Metwally, Mohamed, Hajalamin, Mohamed, Kamal Matter, Mohamed, Khaled, Mohamed, Kouta, Mohamed, Masoud, Mohamed, Almihashhish, Mohamed Miftah, Mokhtar, Mohamed, Mostafa, Mohamed, Yassin, Mohamed Musa, Bouhafs, Mohamed Nedjmeddine, Herdan, Mohamed Omar, Omer, Mohamed, Osman, Mohamed, Zaazou, Mohamed, Zahed Abdalla, Mohamed, Melouane, Mohamed-Sami, Abed, Mohammad, Sawaftah, Mohammad Ahmad Mohammad, Al-Masri, Mohammad, Al-Qannas, Mohammad, Ali-Hassanzadeh, Mohammad, Yunus, Mohammad Alif, Aloulou, Mohammad, Alrantisi, Mohammad, Araydah, Mohammad, Bani Hani, Mohammad, Barakat, Mohammad, Durrani, Mohammad, Khan, Mohammad Faisal, Dwikat, Mohammad Fuad, Hasan, Mohammad, Nabhan, Mohammad Hassan, Hijazi, Mohammad, Abu Albahrain, Mohammad Karam, Barakat, Mohammad Mounzer, Mubarak, Mohammad, Omar, Mohammad, Pourfridoni, Mohammad, Mslmani, Mohammad Rabee, Salah, Mohammad, Tanashat, Mohammad, Yahmad, Mohammad, Elmujtaba, Mohammed, Abd Al-Fattah, Mohammed, Abdelkabir, Mohammed, Abosedra, Mohammed, Sarker, Mohammed Abu Kawsar, Abudabbous, Mohammed, Abuwarda, Mohammed, Elgak, Mohammed Ahmed, Al Hinai, Mohammed, Al Zebda, Mohammed, Al-Shehari, Mohammed, Alharthi, Mohammed, Ali, Mohammed, Ismael Alamin, Mohammed Ali, Alqadasi, Mohammed, Alshanwani, Mohammed, Alshehri, Mohammed, Asaad, Mohammed, Bashir, Mohammed, Bohlala, Mohammed, Meghaizerou, Mohammed El Amine, Albanna, Mohammed Emad Hashem, Ghunaim, Mohammed, Goga, Mohammed, Hajhamad, Mohammed, Hamada Takrouney, Mohammed, Hammoda, Mohammed, Hamoud Almahly, Mohammed, Muragi, Mohammed, Mohammed, Mohammed Mustafa Hassan, Obaid, Mohammed, Omar, Mohammed, Said, Mohammed, Salah, Mohammed, Saleh Khatab, Mohammed, Aliyu, Mohammed Salele, Shakhshir, Mohammed, Sheriff, Mohammed, Tageldin, Mohammed, Abdelfattah, Mohanad, Daher, Mohanad, Lotfy, Mohanad, Alqedrh, Mohannad, Nasani, Mohannad, Mohd Shah, Mohd Shahrulsalam, Madany, Mohie El-Din Mostafa, Mobolaji-Ojibara, Mojisola, Nkogatse, Moleseng, Alazabi, Mona, Gupta, Money, Bogdan, Monica, Guerrero, Monica, Noguez Castillo, Monica, Gureh, Monika, Kacem, Montasser Jamaleddine, Tarar, Moosa Feroze, Seto, Morel, Steinruecke, Moritz, Edena, Morrison, Abdulsalam, Moruf, Abdelhadi Suliman Adam, Mosab, Saleh, Mosab, Anati, Mosaikah, Dokurugu, Moses Abdulai, Agunloye, Moses, Ibadin, Moses, Momoh, Moses, Abdelkarim, Mostafa, Kamar, Mostafa, Kotb, Mostafa, Mahran, Mostafa, Mohamad Amin, Mostafa, Shalaby, Mostafa, Waseem, Mostafa, Almaletti, Motasem, Saifi, Motaz, Tsuruta, Motohisa, Agbadebo, Mouhamed, Arnaout, Moumen, Ojo, Moyosoluwa, Sharma, Mrthyunjayani, Azzuz, Muad Mohamed Ramadan, Haj Hussein, Mudar, Ameen, Muftiat Omolola, Nkoronko, Mugisha, Fitri, Muhamad, Abdullah, Muhammad, Bashir, Muhammad Ahmad, Sadiq, Muhammad Ahmad, Ahmed, Muhammad, Ali, Muhammad, Al-Yusuf, Muhammad Ali, Haider, Muhammad Aliyan, Alshaar, Muhammad, Mirza, Muhammad Bilal, Che Yaacob, Muhammad, Daniyan, Muhammad, Elzayat, Muhammad, Butt, Muhammad Faizan, Sadiq, Muhammad Hamza, Chishti, Muhammad Haris, Ismail, Muhammad Izzat Shufphi, Kashif, Muhammad, Khalid, Muhammad, Mansoor Iqbal, Muhammad, Bin Khalid, Muhammad Moaz, Rafique, Muhammad Nouman, Raheem, Muhammad, Khalid, Muhammad Saud, Usama, Muhammad, Usman Malik, Muhammad, Saqib, Muhammad Waleed, Elhadi, Muhammed, Ateş, Muhammed Ikbal, Demirpolat, Muhammed Taha, Ergenç, Muhammer, Bello, Muideen, Kulimbet, Mukhtar, Nyirenda, Mulinda, Taeme, Mulugeta, Denini, Muna, Aziz, Munazzah, Yahaya, Mundashiru, Eugene, Muneza, Amadu, Munira, Chauhan, Munish, Acar, Murat, Teressa, Murti, Dauphin, Muryango, Arafat, Musa, Althomali, Musab, Rayzah, Musaed, Husain, Musharraf, Tolani, Musliu Adetola, Abu Jayyab, Mustafa, Al-Attraqchi, Mustafa, Kara, Mustafa Alper, Seker, Mustafa Ege, Gün, Mustafa, Hamed, Mustafa, Mehanny, Mustafa, Oncel, Mustafa, Sabri Massadi, Mustafa, Uyanik, Mustafa Safa, Uzunoglu, Mustafa Yener, Abdullahi, Mustapha, Saidani, Mustapha, Nofal, Mutaz, San, Myat, Ishak, Myrna, Keramida, Myrto D., Nik Burhanuddin, N.M. Syahrin, Talat, Nabila, Shehata, Nada, Alasbahi, Nadeen, Marcos, Nádia, Al Amri, Nadiah, Absy, Nadine, Parker, Naeelah, Lindi, Naeimah, Omer, Nafisa, Papadogianni, Nafsika, Rawal, Nagendra, Ismaiel, Nahar, Ben Hasan, Najat, Albahloul, Najla, Gokhare Viswanath, Nakul, Srinivas, Namitha, Christian, Nana Ama, Obuobi, Nana Kwame Asare, Beharry, Naomi, Yousefzadeh Kandevani, Naser, Alnamari, Nashwan, Oyelowo, Nasir, Oloko, Nasirudeen, Alzerwi, Nasser, Mosbah, Nasser, Shulman, Nastassia, Andrade, Natacha, Boumas, Natacha, Cobeño Tamayo, Natalia, Barrera Lopez, Natalia Guadalupe, Palamara, Natalia, Blencowe, Natalie, Marzouqa, Natalie, Blencowe, Natalie S, Salgadoe, Natalie, Techapongsatorn, Nathakorn, Paez, Nathaly, Ekwo, Nathan, Saini, Navdeep, Malik, Naveed Akhtar, Sharma, Naveen, Kumar, Navin, Chaudhry, Navneet Kumar, Karimbocus, Nawaaz, Rasool, Nazeerah, Lodhi, Nazia, Kavak, Nazli, Ildephonse, Ndayiragije, Diomede, Nduwimana, Bayleyegn, Nebiyou S., S.Bayleyegn, Nebiyou, Jović, Nediljko, Mosleh, Neebal, Aruldas, Neerav, Kapur, Neeti, Paul Sigamony, Negine Paul, Karthikeyan, Neha, Tabatabaian, Nelia, Affram, Nelson, Agboadoh, Nelson, Tran, Nelson, Lalovic, Nenad, Agugua-Obianyo, Nene, Kullab, Nermen, Lahmer, Nesrin, Raiq, Neven, Soldo, Neven, Spiteri, Neville, Chen, Nevin, Al Rabadi, Nezar, Christian, Ngarambe, Cabrel, Ngongang Ngansop, Leonelle Lore, Nguefack Noudem, Furbetta, Niccolò, Ensor, Nicholas, Tsantikos, Nick, Seeger, Nico, Cillara, Nicola, Eardley, Nicola, Petrarota, Nicola, Tartaglia, Nicola, Feijoo, Nicolas, Finocchiaro, Nicole, Koter, Nicole, De Santis, Nicolò, Fabbri, Nicolò, Schiavon, Nicolò, Tamini, Nicolò, Sharma, Nidhi, Sánchez Fuentes, Nieves, Solomon, Nigus, Bugdayci, Nihat, Lekiashvili, Nika, Gupta, Nikhil, Narain, Nikhil, Uttam, Nikita, Kłos, Nikola, Ververidis, Nikolaos Adrianos, Arkadopoulos, Nikolaos, Dimitrokallis, Nikolaos, Garmpis, Nikolaos, Gouvas, Nikolaos, Kalampokis, Nikolaos, Kopanakis, Nikolaos, Kydonakis, Nikolaos, Machairas, Nikolaos, Memos, Nikolaos, Michalopoulos, Nikolaos, Mathioudakis, Nikolaos Nestor, Roukounakis, Nikolaos, Stamos, Nikolaos, Tasis, Nikolaos, Tsakiridis, Nikolaos, Vlachakos, Nikolaos, Zampitis, Nikolaos, Kouzakos, Nikolas, Börner, Nikolaus, Dimitriou, Nikoletta, Dafnios, Nikos, Banerjee, Niladri, Klammer, Nils, Maharjan, Nima, Rabai, Nimah, Oscar, Nimpaye, Harrison, Nina, Kheyrbek, Nina, Kansakar, Nirajan, Bhat, Nisar, Krishnappa, Nischal, Pahuja, Nisha, Paul Ambrose, Nitin, Renovat, Niyongabo, Musawa, Nizar, Nwanne, Njideka, Steve, Nkurunziza, Chidumije, Nnaemeka, Nwafulume, Nnaemeka, Celestine, Nnamani, Duru, Nnamdi, López Bernal, Noelia Esthela, Laquatra, Noemi, Pasqua, Noemi, Awwad, Noor Al-Deen, Ali, Nora, Hielscher, Nora, Trabulsi, Nora, Hüser, Norbert, Muñoz Montes, Norberto, Eshak, Norma-Sol, Rajab, Nosaiba, Lahnaoui, Nouhaila, Ouachou, Nouhaila, Ali, Nour, Dadoush, Nour, Fazili, Noureen, Theophile, Ntahompagaze, Ntanzi, Ntuthuko, Bibila, Nubia Samuel, Alwaer, Nuhay, Naabo, Nuhu, Jiagge, Nuna, Freitas Oliveira, Nuno Miguel, Pratas, Nuno, Morricone, Nunzia, Franco, Nunzio Francesco, Binti Yusri, Nur Aima, Ramli, Nur Natasya, Abd Ghani, Nur Suriyana, Umar, Nura, Aly, Nuran Khaled, Lakhanov, Nurgali, Al-Hroub, Nurhan, Kiziltoprak, Nurhilal, Chavarrias, Nuria, Maulenov, Nurlan, Akinbami, Nurudeen, Abdulraheem, Nurudeen Toyin, Karunaratne, Nuwanthika, Jeannette, Nyiransabiyera, Altobaishat, Obieda, Egwuonwu, Ochonma Amobi, Enciu, Octavian, Cohen-Arazi, Oded, Pheiffer, Odette, Okoye, Odili Aloysius, Omoike, Ofure, čančar, Ognjen, Ekwunife, Okechukwu Hyginus, Emuze, Okundayo, Eljizoly, Ola Abdallah, Al Hamdani, Ola, Emadeldeen, Ola, Morgan, Ola, Olajumoke, Oladapo, Popoola, Olakunle, Ajiboye, Olalekan, Olasehinde, Olalekan, Jolayemi, Olamide, Babatunde, Olanrewaju, Balogun, Olanrewaju, Olajide, Olawumi, Lisin, Oleg, Bellou, Olga, Jurić, Oliver, Ladlow, Oliver, Whitehurst, Oliver, Camilleri, Olivia, Montaño Angeles, Olivia, Pryer, Olivia, Ray, Olivia, Gabom, Olivier, Ndizeye, Olivier, Ojewuyi, Olufemi, Oluyemi, Olukayode, Elebute, Olumide, Ogunsua, Oluseyi, Fasiku, Olushola Kayode, Fasoro, Olusola, Fatudimu, Oluwafemi, Osunlusi, Oluwafemi, Owolanke, Oluwagbenga, Oso, Oluwarotimi, Alaba, Oluwaseun, Ojo, Oluwaseun, Oluseye, Oluwaseun, Oyinloye, Oluwaseun, Al Alyani, Omaima, Okrah, Omane, Agha, Omar, Al-Fahel, Omar, Almomani, Omar, Alruwaili, Omar, Ibarra, Omar, Ibrahim, Omar, Khalil, Omar, Kouli, Omar, Lima Azurdia, Omar, Mansour, Omar, Mohamed Mokbel, Omar, Omar, Omar, Bedak, Omer, Ozkan, Omer Faruk, Yalkın, Omer, Mohamed, Omnia, Ayandipo, Omobolaji, Faboya, Omolara, Williams, Omolara Modupe, Irowa, Omorodion, Attawodi, Onuche, Salako, Opeyemi, Ioannidis, Orestis, Agcaoglu, Orhan, Martin Sole, Oriol, Webster, Orla, Abouhiekal, Osama, Al Shaqran, Osama, Bahsas-Zaky, Osama, Nubi, Osama Gamal, Hany, Osama, Matar, Osama, Mahafdah, Osama R., Sarhan, Osama, Osagie, Osasumwen, Soublett Rivas, Óscar Alexander, Gülcicek, Osman Bilgin, Cuenca Torres, Osmar Manuel, Carpineto Samorani, Osvaldo, Arsalan, Othman, Coyoy-Gaitán, Otto, Nouhail, Oumaima, Boujidi, Oumama, Dicko, Ousmane A A, Ahmad, Owais, Christianah, Oyegbola, Küpçüoğlu, Özge, Zanbak Mutlu, Özgecan Pırıl, Chadha, P, Prabhu, P Santosh, Carmignani, Pablo, Arteaga Asensio, Pablo Cesar, Del Val Ruiz, Pablo, Royo Dachary, Pablo, Sancho Pardo, Pablo, Vásquez, Pablo, Sukhvibul, Pakkapol, Assouto, Pamphile, Evangelou, Panagiota, Dorovinis, Panagiotis, Kapsampelis, Panagiotis, Kokoropoulos, Panagiotis, Kostoglou, Panagiotis, Manikis, Panagiotis, Sakarellos, Panagiotis, Lykoudis, Panagis, Kumar, Pankaj, Patel, Panna, Paraskeva, Panoraia, Vassiliu, Panteleimon, Antonakis, Pantelis, De Nardi, Paola, Marongiu, Paola, Kamenova, Paolina, Venturelli, Paolina, Belotti, Paolo, Ubiali, Paolo, Grivas, Paraskevas, Stamopoulos, Paraskevas, Chatzikomnitsa, Paraskevi, Trakosari, Paraskevi, Tekam Wadje, Parfait Stéphane, Manjunath, Parikshith, Gupta, Pariza, Dhamija, Parth, Haque, Parvez, Haque, Parvez David, Haque, Parwez Waseemul, Nze Obiang, Pascal Christian, Probst, Pascal, Chiacchio, Pasquale, Cianci, Pasquale, Favoriti, Pasqualino, Koggoh, Patience, Bernardo, Patrícia, Omwansa, Patricia, Serrano Méndez, Patricia, Owens, Patrick, Tang, Patrick, Walker, Patrick, Chimezie Andrew, Paul, Trinity, Paul, Wilson, Paul, George, Paul Yohan, Artigot, Paula, Devlin, Paula, Vladova, Paulina, Cabrera Rivera, Paulo Andrés, Arunachalam, Pavai, Glushkov, Pavel, Levíček, Pavel, Lal, Pawanindra, Panahi, Pedram, David Santos, Pedro, Laranjo, Pedro, Palazon Bellver, Pedro, Rego Ponte, Pedro, Salas Núñez, Pedro, Sornoza, Pedro, Chloropoulou, Pelagia, Correia, Penélope, Limani, Perparim, Agbonrofo, Peter, Boateng, Peter Agyekum, Elemile, Peter, Francúz, Peter, Riedl, Peter, Tschann, Peter, Yuide, Peter, Hudáč, Petr, Ostruszka, Petr, Zimmermann, Petra, Nambala, Petrus, Shimbulu, Petrus, Thomas, Phebey A, Kumassah, Philemon, Alexander, Philip, Mensah, Philip, Taah-Amoako, Philip, Horvath, Philipp, Garcia-Dubus, Philippe, Holt, Phillip, Lapolla, Pierfrancesco, Cicerchia, Pierfranco Maria, Palumbo, Piergaspare, Anoldo, Pietro, Calò, Pietro Giorgio, Grondona, Pietro, Masseria, Pietro, Riva, Pietro, Milewski, Piotr Jan, Kowalewski, Piotr, Kasetsermwiriya, Pohpdham, Patel, Poojan, Leungon, Poramet, Kaur, Prabhjot, Arya, Prafull Kumar, Shivashankar, Pranav, Kothari, Prashant, Dummala, Prashanth, Shukla, Prateek, John, Pravin, Adebayo, Precious, Andrejevic, Predrag, Thambi, Prem, Anandan, Premkumar, Idjerhe, Prince, Boateng, Prince Kwame, Ntem, Prince, Waghchoure, Prince, Yeboah Owusu, Prince, Moodley, Priyanka, Suresh, Priyanka, Kanavidis, Prodromos, Odigie, Vincent, Christodoulou, Prokopis, Nashidengo, Pueya Rashid, Patel, Puja, Dolatzay, Qayom Khan, Mashlah, Qusai, Sabbah, Qutaiba, Sethi, R, Robitsek, R. Jonathan, Jubran, Ra'Ed, Raheem Attallah Al-obaidy, Raad, Michael, Rabha, Abela, Rachel, Colbran, Rachel, Geow, Rachel, Titcombe, Rachel, Soglonou, Rachelle, Ait Ben Addi, Rachid, Jayakrishnan, Radhakrishnan, Acharya, Radhika, Salim, Radhwan, Guzmán Lambert, Radisnay, Donchev, Radoslav, Drasovean, Radu, Andreou, Rafael, Perez-Soto, Rafael Humberto, Santana Ortiz, Rafael, Villalobos Mori, Rafael, Sokratous, Rafailia, Smolinski Kurek, Rafal Ludwik, Solecki, Rafal, Basile, Raffaele, Abd Elkareem, Raghad, Yousef Yassin, Raghad, Faisal, Raghdah, Abd Alkareem, Rahaf, Hegy, Rahma, Jaba'Teh, Rahmah, Sharma, Rahul Deo, Gupta, Rahul, Saxena, Rahul, Sinha, Rahul, Varshney, Rahul, Ripoll I Palmés, Raimon, Lunevicius, Raimundas, Raghunath, Rajat, Redkar, Rajeev, Sharma, Rajeev, Philip Sridhar, Rajeevan, Krishna Raj, Rajesh, Nathani, Rajesh, Kottayasamy Seenivasagam, Rajkumar, Ahmed, Rakesh, Handa, Rakesh, Vakil, Rakesh, Armah, Ralph, Attaf, Ram, Elazary, Ram, Alkhatib, Rama, Alzu'Bi, Rama, Raddad, Rama, Kaur, Ramanjot, Kaur, Ramanpreet, Nataraja, Ramesh, Hussam Yacoub Hattar, Ramez, Ben Hmida, Rami, Chaudhary, Ramkaran, Ramirez Calas, Ramon Andres, Soliva Domínguez, Ramón, Ghaleb, Ramzi, Batir, Rana, Haddad, Rana, Sugair, Rana, Suleiman, Rand, Perera, Ranga, Altayargh, Rania, Joumaa, Ranim, Ellawala, Ranjith, Elaifia, Rany, Eloka, Raphael, Hernandez Rodriguez, Raquel Angelica, Diaz, Raquel, Lalanda, Raquel, Rodríguez-Uria, Raquel, Olatunji, Rasheed, Wani, Rauf, Díaz Pedrero, Raúl, Ubiñas, Raul, Lertnamvongwan, Raunika, Hiary, Rawan, Almahadin, Rawan Khalid Za'al, Radwan, Rawan, Issa, Rawand, Dar, Rayees Ahmad, Nyirenda, Raymond, Eghonghon, Raymond Atah, Oppong, Raymond, Govindaraju, Rayshini, Kalouk, Razan, Abad, Rebeca, Akankoatuesi Apatewen, Rebecca, Bradley, Rebecca, Enejo, Rebecca Eboshogwe, Hauwa Sani, Rebecca, Jurdon, Rebecca, Sönmez, Recep Erçin, Belouz, Reda, Abhinaya, Reddy, Abu Salah, Reem, Alatawi, Reem, Alqahtani, Reem, Sayad, Reem, Adel Diab, Rehab, Függer, Reinhold, Madi, Reman, Pajtak, Renata, Barradas, Renato, Díaz-Ruiz, Renato, Patrone, Renato, Palacios Huatuco, René M., Casma Bustamante, Renzo, Ranadive, Reuben Rajappa, Askari, Reza, Sulce, Rezart, Liang, Rhea, Tummon, Rhea, Roberts, Rhianna, Mcclen, Rhys, Duvenage, Riaan, Kattini, Ribal, Alvarado Hurtado, Ricardo, Tenfen Carneiro, Ricardo Augusto, Castro Lara, Ricardo Jesús, Silva Borges, Ricardo, Souto, Ricardo, Vaz Pereira, Ricardo, Barone, Riccardo, Fratarcangeli, Riccardo, Guercio, Riccardo, Magarini, Riccardo, Malatesti, Riccardo, Tripathi, Richa, Crawford, Richard, Kpangkpari, Richard, Marlin, Richard, McGee, Richard, Nesco, Richard, Spence, Richard, Akpaka, Richfield, Alinde, Rigobert, Khalid, Rija, Sato, Rikiya, Kitamura, Riley, Baldan, Rino, Agyei Boakye, Rita, Branquinho, Rita, Hleyhel, Rita, Miranda Pera, Rita, Pinheiro Duque, Rita, Ribeiro Dias, Rita, Bhatia, Riya, Rabah, Rnad, Damseh, Ro'Ya, Alzughayyar, Roa, Daradkeh, Roa'A, Bassam, Roaa, Refaie, Roaa, Bethune, Rob, Elshennawy, Roba, Cachia, Robert, Franz, Robert, Grützmann, Robert, Kibuuka, Robert, Laskowski, Robert, Mazurkiewicz, Robert, Munyaneza, Robert, Parker, Robert, Sagoe, Robert, Sucher, Robert, Granata, Roberta, Ruccella, Roberta, Tutino, Roberta, Badra, Roberto, Mares País, Roberto, Sampietro, Roberto, Scola, Roberto, Mackay, Robyn, Tumolo, Rocco, Figueroa, Rodrigo, Doamba, Rodrigue, Habib, Rohan, Gujjuri, Rohan R, Anjum T Siddeek, Rohik, Mittal, Rohin, Kumar, Rohit, Goudou, Roland, Rüdrich, Roland, Senin, Roman, Moukarzel, Romika, Ferlini, Romina Lorena, Ribeiro, Rómulo, Schmidt-Branden, Romy, Zerna Encalada, Ronald, Ferreira Acosta, Rosa, Lopatriello, Rosanna, Perez, Rosario, Hall, Rosie, Alloni, Rossana, Arena, Rossella, Gioco, Rossella, Polo, Roxy, Shen, Ru, Doherty, Ruairi, Rivas, Ruben, Oppong-Amoah, Ruby, Ooi, Rucira, Radojković, Rudolf, Herrera, Rudy, Bernardino, Rui, Ediru, Rukevwe, Al Shehhi, Ruqaiya, Masri, Ruqaya, Hodgson, Russell, Azimov, Rustam, Martínez Díaz, Rut, Santos Pereira, Rute, Naidoo, Ruvashni, Noor, Ruzaimie, Campbell, Ryan, Khalil, Ryta, Chigblo, S. 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Sharitha, Laura, Sharon, Shanker, Shashwat, Ababneh, Shatha, Gilbert, Shaun, Kenworthy, Shaunna, Ng, Shawn Hong Ming, Mackenzie, Shawn, Salindera, Shehnarz, Khattak, Shehrbano, Loke, Sheih Nee, Manzoor, Sheikh Viqar, Alwardi, Sheikha, Allam, Shereen, Tawfik, Sherifa, Francis, Shikha, Cai, Shirley, Dindyal, Shiva, Pandya, Shivangi, Chopra, Shreya, Ingley, Shreya, Kulkarni, Shrirang, Kosna, Shuba, Nayak, Shubhalaxmi, Ahuja, Shubham, Hariharan, Shubhang, Karuppusamy Krishnasamy, Shyam, Khare, Siddhant, Handa, Siddhartha, Amin Omar Alsiddig, Siddig, Alqurashi, Siddiga, Al-Tahayneh, Sief-Addeen, Sibiya, Silindokuhle, Perretta, Silvana, Ibarra Camargo, Silvia Alejandra, Montisci, Silvia, Mungo, Silvia, Puddu, Silvia, Severi, Silvia, Agudelo Mendoza, Silvia Valentina, Makkai-Popa, Silviu Tiberiu, Boyes, Simon, Monkhouse, Simon, Stock, simon, Alberti, Simona, Meneghini, Simona, Giudici, Simone, Guadagni, Simone, Birolo, Simone Lorenzo, Novello, Simone, Oliveira, Simone, Gumede, Simphiwe, Dhole, Simran, Budhwani, Simran Saleem, Ramjit, Sinead, Yumurtacilar, Sinem, Mahendra, Sirigi Naga, Abeykoon, Sithira, Moh Pauzi, Siti Farhan, Rajendra, Sittampalam, Sundararajan, Siva, Gananadha, Sivakumar, Kamarajah, Sivesh K, Marawu, Siyasanga, Basu, Sk, Hassan, Sleman, Reddy, Snigdha Mettu, Anaya Sanchez, Sofia, Gaspar Reis, Sofia, Gomez, Sofía, Gamba, Sofia Lucia, Pimentel Morais, Sofia, Ashry, Soha, Abdullateef, Sohaila, Bandyopadhyay, Soham, Samadi, Soheil, Pathan, Sohilkhan R., Lakew, Solomon, Basu, Somprakas, Ohri, Sonali, Alonso Marcos, Sonia, Amoza Pais, Sonia, Fortuna Martins, Sónia, Gill, Sonia, Matthiess, Sonia, Sabbatini, Sonia, Soto Schütte, Sonia, Engel, Sophie, Eam, Sothseyhakmonique, Botaitis, Sotirios, Lawani, Souliath, Jamil, Soumaya, Kondpan, Sourav, Oum, Sovannarith, Govender, Sovishnee, Christodoulou, Spyridon, Davakis, Spyridon, Vernadakis, Spyridon, Gkogkos, Spyros, Gobishangar, Sreekanthan, Suresh, Sreelakshmi, Vembar, Sridhar, M, Srikanth, Abdelrasoul Elnour Ismail, Srraa, Zourntou, Stamatina-Emmanouela, Nwabuoku, Stanley Emeka, Ideh, Stanley, Charitonos, Stavria, Liapis, Stavros Chrysovalantis, Faber, Stefan, Piccioni, Stefania Angela, Romano, Stefania, Silvestre, Stefania, Jarmusch, Stefanie, Soelling, Stefanie, Cardelli, Stefano, Chaifouroosh Mamagany, Stefano, Corso, Stefano, Basso, Stefano Maria Massimiliano, Megna, Stefano, Bitsianis, Stefanos, Tsatsos, Stefanos, Morales, Steffanía, Gerdes, Stephan, Göller, Stephanie, Hanna, Stephanie, Tabiri, Stephen, Agana, Stephen, Theivendran, Stephen Arthur, Kache, Stephen, Knight, Stephen R, Smith, Stephen, Stonelake, Stephen, Wrenn, Stephen, Gopaul, Steven, Vederaki, Styliani, Kapiris, Stylianos, Kykalos, Stylianos, Hlaing, Su Su, Chia, Su Yin Denise, Abu Khousa, Suad, M. Udwan, Suad, Raul, Subrat, Chase, Suchita, Nair, Sudharrshan, Joseph, Sudhir, Singh, Sudhir Kumar, Singh, Sudhir, Timmalah, Suhaylah, Alsuwiyah, Suhir, Thalgaspitiya, Sujeewa Priyantha Bandara, Sellahewa, Sujeewa, Neogi, Sujoy, Burger, Sule, Polat, Süleyman, Alkadi, Sulman, Asiri, Sultan, Otho, Sumaira, Mewa Kinoo, Suman, Ebrahim, Sumayyah, Tontus, Sumeyya, Midya, Sumit, Thuraisamy Sarma, Sundaramoorthy Iyer, Payyanur Thotan, Sundeep, Kumar Venkatappa, Sunil, Techapongsatorn, Suphakarn, Kaur, Supreet, Jp, Supritha, Tan, Suqi, Djote, Surafel Mulatu, Surendran, Suraj, Singh, Surendra, Chilaka, Suresh, Lee, Susan, Henriques, Susana, Giridaran, Suseendirarajah, Achugatla, Sushma, Kumar, Suvam, Brincat, Svetlana, Deshpande, Swati, Batista, Sylvia, Akharaekpanya, Tachporn, Moges, Tadesse Girma, Türkmen, Taha Berkay, Alhaj Hasan, Taima, Alshawabkeh, Taima', Majed, Taima', Lawal, Taiwo Akeem, Ibiyeye, Taiye Taibat, Rashid, Tajamul, Košir Božič, Tajda, Mohammed, Tajudeen, Khewater, Talal, Abelman, Talia, Al Barhi, Tamadher, Mogne, Tamiris, Salazar-Lorenzana, Tania Abril, Akter, Tania, Gómez Sanz, Tania, Motiwala, Tanmay, Valizadeh Elizeh, Tanya, Almahdi, Tanzeel, Albushary, Tanzel Alrahman, Abdulrahman, Taofeeq, Finlay, Tara, Chouari, Tarak, Awad, Tarek, Sabra, Tarek, M. Abubasheer, Tareq, Alhusban, Tariq, Yılmaz, Tarık Emre, Aloqaili, Tasneem, Aldirawi, Tayef, Karahasanoğlu, Tayfun, Gülşen, Taygun, Jemal, Tebarek, Nadeem, Tehmina, Singh, Tejinder Paul, Alinger, Temsula, Longkumer, Temsutoshi, Lo, Terence, Gimenez Maurel, Teresa, Uprak, Tevfik Kıvılcım, Petropoulou, Thalia, Rawther, Thampi, Techapongsatorn, Thawin, Manickam, Thendral, Padioti, Theodora, Kozonis, Theodoros, Sidiropoulos, Theodoros, Tsirlis, Theodoros, Theodosopoulos, Theodosios, Hessou, Thierry Kinnongni, Uiyapat, Thitapon, Agyen, Thomas, Harris, Thomas, Hugh, Thomas J, Jorgensen, Thomas W., Theivendrampillai, Thrshegan, Pham, Thuy Vy, Branco, Tiago, Nagwamutse, Tijjani Nasiru, Tony V, Tina, Devabalan Koil, Titus, Pilia, Tiziana, Abdulmola, Tmador Mahmed Ali, Oyeyemi, Tobiloba, Kebede, Tolera, Ibarra-Hurtado, Tomás Ramón, Reichelt, Tomas, Gach, Tomasz, Stefura, Tomasz, Wojewoda, Tomasz, Soric, Tomislav, Risteski, Toni, Tridip, Tridip Dutta Baruah, Yotsov, Tsanko, Doma Bhutia, Tshering, Girma, Tsion, Kwan, Tsun Yu, Ivanov, Tsvetomir, Iahmo, TT, Ashkar, Tuleen, Mabogoane, Tumi, Olobatoke, Tunde, Sholadoye, Tunde T., Mishra, Tushar Subhadarshan, Parker, Tyla, Ezomike, Uchechukwu, Dilibe, Uchenna, Kumbhar, Uday, Una, Uduak-Abasi, Grossi, Ugo, Ezidiegwu, Ugochukwu, Edith, Ugwuoke, Daspal, Ujjwal, Kalu, Ukoha Agwu, Dietz, Ulrich, Ronellenfitsch, Ulrich, Wirth, Ulrich, Abdullah, Umar, Rivolta, Umberto, Jayarajah, Umesh, Kanyan Kassim, Umu-Hera, Govindan, Unnikrishnan, Fernandes, Urânia, Akram, Usman, Mohammed Bello, Usman, Omara, Usra, Naidoo, Uvarasen, Mahendravarman, Vaishnaivy, Negoita, Valentina Madalina, Mariottini, Valentina, Murzi, Valentina, Zucchini, Valentina, Agbakwuru, Valentine, Armenta Tapia, Valeria Estefania, Gentilino, Valerio, Borgogni, Vanessa, Ng, Vanessa, Wolfschluckner, Vanessa, Silvestri, Vania, Žufić, Vanja, Gunasaegaram, Varman, Kamalathevan, Vasan, Pillay, Vasanthan, Neykov, Vasil, Kalles, Vasileios, Mousafeiris, Vasileios, Papadopoulos, Vasileios, Tsaousis, Vasileios, Tselepidis, Vasileios, Vougas, Vasileios, Georgilaki, Vasiliki, Nikolaou, Vasiliki, Themelidi, Vasiliki, Manchev, Vassil, Ioannou, Veatriki, Jha, Vedant Shekhar, Dragisic, Vedran, Sutharshan, Vengadasalam, Alonso, Veronica, Brocco, Veronica, Ongil Rodríguez, Verónica, Schirinzi, Veronica, Budyakova, Veronika, Naunova, Vesna, Panduro-Correa, Vicky, Ruiz López, Víctor Andrés, Bill, Victor, Dassah, Victor, Gonzabay, Víctor Eduardo, Etwire, Victor, Modekwe, Victor, Serna-Alarcon, Victor, De Donato, Victor Ugo, Duque Mallén, Victoria, Liu, Victoria, Sharma, Vidushi, Kumar, Vijaya, Muralidharan, Vijayaragavan, Kakotkin, Viktor, Enemuo, Vincent, Kudoh, Vincent, Osoka, Vincent, Siepaal, Vincent, Granata, Vincenza, Dinuzzi, Vincenza Paola, Lizzi, Vincenzo, Ricchiuti, Vincenzo, Mosca, Vinicio, Kanna D, Vinoth, Nair, Vipin Venugopal, Ledda, Virginia, Michael, Vishal, Singh, Vishavdeep, Govindasamy, Vishendran, Kollengode, Viswanathan V, Giordano, Vittoria, Morinelli, Vittoria, Lin, Vivian, Cuk, Vladica, Cijan, Vladimir, Çalik, Volkan, Bakshi, Vrushank, Ten, Vyacheslav, Ratheesh, Vysakh, Alsado, Wael, Mayo, Wafik, Yang, Wah, Rehman, Wajeeh Ur, Abbas, Walaa, Al-Khyatt, Waleed, Mabood, Waleed, Santucci, Walter, Yew, Wan Ting, Tahir, Warda, De Silva, Warusha Dhammika Dulantha, Wijenayake, Wasantha, Almadhoun, Waseem J.N., Alhroub, Wasef, Ebrahim, Wesam, Jabłoński, Wiktor, Krawczyk, Wiktor, Bhatti, William, Lai, William Kwan Ho, Petrushnko, Wilson, Afedo, Wisdom, Kasetsermwiriya, Wisit, Serednicki, Wojciech, Wysocki, Wojciech, Zerefa, Wondwossen Amtataw, Vagena, Xanthoula, Tarrado, Xavier, Papazarkadas, Xenofon, Po, Xiang Yuen, Ouadi, Yacine, Myla, Yacob, Haido, Yacoub, Hasan, Yafea, Karataş, Yağmur, Carpio Colmenares, Yahaira, Galvañ Félix, Yaiza, Balogun, Yakub Lekan, Maktabi, Yaman, Nerabani, Yaman, Fulgence, Yamuremye, De Silva, Yannick, Asar, Yara, Samer Morsy, Yara, Ghaleb, Yasameen Saif Saeed Mohammed, Vashishth, Yash, M S, Yashas, Manickchund, Yashoda, Sakaray, Yashwant, Kara, Yasin, Tosun, Yasin, Zwain, Yasir, Farag, Yasmeen, Jedidi, Yasmine, Seada, Yasmine, Aldebasi, Yasser, Ashour, Yasser, Badr, Yassin, Sarpong, Yaw, Alawneh, Yazan, Aung, Yee Lay, Orabi, Yehia, Lam, Yick Ho, Şen, Yigit Kaan, Koyluoglu, Yilmaz Onat, Huang, Yining, Mintz, Yoav, Perez, Yocarli, Chamara, Yohan, Melkamu, Yohannes, Maestre González, Yolanda, Dean, Yomna, Metaferia, Yonas Yilma, Malki, Yosra, Mohamed, Younis, A. Omar, Yousef, Alhammoud, Yousef, Allaoua, Yousef, Tanas, Yousef, El Okazy, Youssef, Kerolous, Youssef, Mohamed, Youssef, Al-Junaidi, Youssuf, Lakdawala, Yousuf, Lu, Yuann, Asano, Yukio, Altinel, Yuksel, Aktimur, Yunus Emre, Fishman, Yuri, Kudryavcev, Yurii, Tandoğan, Yusuf Iskender, Razafimandimby, Yves Michaël, Adofo-Asamoah, Yvonne, Şenol, Zafer, Odeh, Zahra, Benamrouche, Zahra Rayane, Alkhaier, Zahraa, Al-Sheikh Ali, Zaid, Zaher, Zain Aldin, Alnajjar, Zaina, Al-Balushi, Zainab, Alkhuzaie, Zainab, Khraim, Zakaria, Toutounji, Zakaria, Djama, Zakarya, Farraj, Zamil, Shah, Zamir Ahmad, Khan, Zara, Khan, Zarnigar, Abo Alarous, Zayn Alabden, Asaad, Zaynab, Demetrashvili, Zaza, Lorenc, Zbigniew, Brekalo, Zdrinko, Hannouneh, Zein Alabdin, Robertson, Zelda, Bady, Zeyad, Durna, Zeynep, Wong, Zhen Yu, Fozo, Zien Alabdin, Klib, Zienab, Chin, Ziling, Tamou, Zime Farid, Johnson, Zina, Shabello, Ziyad, Orzeszko, Zofia, Aljalabi, Zohal, Al-Azher El-Hamel, Zohour, Karampotaki, Zoi Rafaila, Valera Sanchez, Zoraida, Matkovic, Zoran, Azhar, Zubair, Qureshi, Zubaria, Correa López, Zulema Margarita, Balciscueta, Zutoia, Musilová, Zuzana, Katusic, Zvonimir, Osama, Zyad, and Dauksa, Zygimantas
Published: 2024
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14. A systematic review and Meta-data analysis on the applications of Deep Learning in Electrocardiogram.

Author: Nehemiah Musa, Abdulsalam Ya'u Gital, Nahla Aljojo, Haruna Chiroma, Kayode S. Adewole, Hammed Adeleke Mojeed, Nasir Faruk, Abubakar Abdulkarim, Ifada Emmanuel, Yusuf Y. Folawiyo, James A. Ogunmodede, Abdulkarim Ayopo Oloyede, Lukman A. Olawoyin, Ismaeel Abiodun Sikiru, and Ibrahim Katb
Published: 2023
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15. Physical layer security using boundary technique for emerging wireless communication systems.

Author: Ismaeel Abiodun Sikiru, Lukman Abiodun Olawoyin, Nasir Faruk, Abdulkarim Ayopo Oloyede, Abubakar Abdulkarim, Imam-Fulani Yusuf Olayinka, Olugbenga A. Sowande, Salisu Garba, and Agbotiname Lucky Imoize
Published: 2023
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16. Application of Computational Intelligence Algorithms in Radio Propagation: A Systematic Review and Metadata Analysis.

Author: Adebowale Q. Ramon, Nasir Faruk, Kayode S. Adewole, Abubakar Abdulkarim, Lukman Abiodun Olawoyin, Abdulkarim Ayopo Oloyede, Haruna Chiroma, Aliyu D. Usman, and Carlos T. Calafate
Published: 2021
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17. EFFECT OF MOISTURE CONTENT ON SOME SELECTED MECHANICAL PROPERTIES OF FARO 44 AND 57 VARIETY OF RICE (PADDY AND DEHUSKED).

Author: Mazza, Moses, Abubakar, Lawan Garba, Muhammad, M. Hamisu, Akangbe, OlaosebikanLayi, Jahun, Bala Gambo, Aminu, Mohammed, Jilima, Abubakar Abdulkarim, Usman, Danlad Drambi, and Haruna, Suleiman
Subjects: RICE, SLIDING friction, INTERNAL friction, MOISTURE, RICE milling, PADDY fields
Abstract: The mechanical properties of rice are among the most important parameters for designing and development of a rice milling machine, destoning machine as well as materials handling. The objective of the study was to determine the mechanical (angle of sliding and internal frictions) properties of (FARO 44 and FARO 57) paddy and dehusked at three different moisture content (5, 10 and 15%) moisture content dry basis. These properties were determined using Funnel and Baker technique and shear box apparatus respectively. The results showed that, angles of internal friction were at least 15.2°, on the average within the moisture ranges tested however, 35° angles were also obtained. Angles of sliding friction ranged between 40° - 50°. This study concludes that moisture content and variety affect the engineering property; angle of internal friction is useful in the determination of lateral and horizontal stress in the silo for grain storage. [ABSTRACT FROM AUTHOR]
Published: 2024
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18. Rural Healthcare Delivery in Sub-Saharan Africa: An ICT-Driven Approach.

Author: Nasir Faruk, N. T. Surajudeen-Bakinde, Abubakar Abdulkarim, Abdulkarim Ayopo Oloyede, Lukman Abiodun Olawoyin, Olayiwola Bello, Segun I. Popoola, and Thierry Oscar Edoh
Published: 2020
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19. Assessing the spatial pattern of public primary schools in Moro Local Government Area of Kwara State, Nigeria

Author: Abubakar, Abdulkarim, primary, Daukere, Bitrus Eniyekenimi, additional, Jamilu, Idris, additional, and Yahaya, Ishaya Kuku, additional
Published: 2023
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20. Minimization of Electric Power Losses on 132 kV and 220 kV Uganda Electricity Transmission Lines

Author: Ounyesiga Living, Stephen Ndubuisi Nnamchi, Kelechi John Ukagwu, Abubakar Abdulkarim, and Zaid Oluwadurotimi Jagun
Subjects: General Medicine
Published: 2023

21. A Deep-Learning Approach to Load Modeling in Modern Power Distribution System

Author: Abubakar Abdulkarim and MUSA MOHAMMED
Subjects: General Medicine
Abstract: Modern Power Distribution Networks (MPDNs) are no longer passive because Distributed Generations (DGs) are integrated with them to enhance system reliability and power quality. For this reason, load modeling has to be updated to capture the new dynamics of active DNs. This paper presents a composite load modeling for a grid-connected photovoltaic (PV) distribution network using the Levenberg-Marquardt algorithm in the deep learning feed-forward neural network approach. Load modeling is constructing a relationship between input excitation(s) and output response(s); it can be used for simulation studies, stability analysis, and control/protection design. A grid-connected PV distribution network was modeled in Matlab/Simulink and generates data for training and model estimation. The estimated model was tested and validated using a laboratory experimental test bed. Results of the model exhibit a good fitness of 99.8% and 97.2% in active and reactive power models respectively during training. While 97.84% and 94.65% respectively were obtained during testing. The estimation errors were found to be 0.0025 and 0.0049 for active and reactive powers respectively with 0.0473 and 0.0701 corresponding errors in testing.
Published: 2022

22. Cost Effective Tri-Band Mobile Phone Jammer for Hospitals Applications.

Author: Abdulkarim Ayopo Oloyede, Adeniyi Shamsudeen, Nasir Faruk, Lukman Abiodun Olawoyin, Segun I. Popoola, and Abubakar Abdulkarim
Published: 2018

23. Spectrum Survey and Coexistence Studies in the TV, WLAN, ISM and Radar Bands for Wireless Broadband Services.

Author: Nasir Faruk, Adebowale Q. Ramon, Segun I. Popoola, Abdulkarim Ayopo Oloyede, Lukman Abiodun Olawoyin, Nazmat Surajudeen-Bakinde, Abubakar Abdulkarim, and Yinusa A. Adediran
Published: 2018

24. EFFECTS OF MOISTURE CONTENT ON PHYSICAL PROPERTIES OF PADDY AND DEHUSKED RICE.

Author: Mazza, Moses, Abubakar, Lawan Garba, Muhammad, M. Hamisu, Akangbe, OlaosebikanLayi, Jahun, Bala Gambo, Aminu, Mohammed, and Jilima, Abubakar Abdulkarim
Subjects: MOISTURE, RICE products, AGRICULTURAL equipment, RICE, PADDY fields, RICE processing, SAMPLING (Process)
Abstract: The physical properties of rice are among the most important parameters for design of agricultural machine and other equipment for handling, planting, harvesting, processing, packaging and storing. This work is aimed at the determination of some of the physical properties of two varieties of rice at varying moisture content that are important in designing rice handling machine. The physical properties of two most popular produced rice varieties in Nigeria (FARO 44 and FARO 57) both paddy and dehusked at three different moisture content (5, 10 and 15%) were determined. Laboratory studies were carried out to determined physical properties of the two varieties of rice ((FARO 44 and FARO 57) important properties for the laboratory work includes: bulk density, unit density, roundness, axial dimensions, sphericity, projected areas, unit volume, unit weight, apparent density, were determined based on different moisture content and random sampling techniques. The results showed that minimum lengths of dehusked rice ranged from 4.57 - 5.29 mm while maximum lengths were between 8.21 - 8.25 mm. For paddy these lengths were minimally 7.65 - 8.78 mm and maximum lengths were 11.39 mm. The least range of minor diameters of dehusked rice was 4.57 - 5.29 mm and maximally these were 8.21 - 8.25 mm. Intermediate diameters were minimally 1.43 mm and maximally in the range of 2.71 - 2.78 mm for dehusked rice; for paddy these were 1.65 - 1.76 mm and 2.46 - 2.78 mm, respectively. Geometric mean diameters ranged between 3.31 - 4.05 mm. For paddy, projected area obtained within the range of 11.71 - 29.75 mm². For dehusked rice, projected area obtained in the range of 8.79 - 21.19 mm². Estimates of roundness were not higher than 33.6% for paddy or 54% for some grains of dehusked rice. The grains appeared more spherical than they were round since paddy were 35.3 - 48.3% spherical while dehusked grains were 39.8 - 59.4% spherical. Bulk densities ranged between 531.0 - 553.8 kg/m³ and 839.6 - 852.7 kg/m³ for dehusked forms of Faro 44 and Faro 57, respectively. True density was in the range of 1071.6 - 1566.2 kg/m³. This study concludes that moisture content and variety affect the engineering property and is useful in the design, development of machine for processing and handling of rice products. [ABSTRACT FROM AUTHOR]
Published: 2023
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25. STUDY OF CONVEXITY IN SETS AND FUZZY SETS

Author: null Abubakar Abdulkarim and I. F. Mukaila
Subjects: Mathematics::General Mathematics
Abstract: In this paper, we present an overview of both classical and fuzzy convexity, particularly, in conjunction with continuity5 and some topological concepts, and provide proofs of some of their algebraic properties along with suitable illustrations. We have extended the work of (Ammar E. E., 1999) by proving that if and are two convex fuzzy sets, then , , , and are also convex fuzzy sets. We have also shown that the convexity of a fuzzy set implies semistrict quasi-convexity
Published: 2022

26. A Review on Optimal Siting and Sizing of DSTATCOM

Author: Dansarki Nanly Wesley, Abubakar Abdulkarim, P.U. Okorie, Adamu Halilu Jabire, Sani Saminu, Nasir Faruk, I.S. Madugu, A. U. Lawan, and Iswadi Hasyim Rosma
Abstract: The continuous demand for electrical energy by industries and domestic users have stressed the electricity consumption to a high level. Because most components of domestic and industrial systems are made of power electronics devices in their designs. In addition, modern electrical power distribution networks (DNs) are subjected to major disturbances. Consequently, today’s power system is laden with power quality problems such as excessive energy losses, voltage deviations, poor power factor (PF), voltage instability and reliability issues to mentioned just a few. To forestall these disturbances, Distribution Engineers have introduced the use of Custom Power Devices (CPDs) in order to reduce power losses so as improve power quality. Amongst CPDs, Distribution Static Compensator (D-STATCOM) proves most promising in minimizing power quality issues because it generates minimal harmonics, waste less power, has small size, high regulatory capability and cost effective. Researchers in recent years have focused on methodologies required for identifying the most suitable location and rating of D- STATCOM device based on divergent views. However, to date, only one author has so far reviewed a paper on this aspect of study. This paper discusses the latest study on appropriate installation and rating of D-STATCOM techniques for balanced and unbalanced radial distribution networks (UBRDNs). The paper has also provided a comprehensive literature study on the location of DSTATCOM in RDNs for power loss reduction and power quality enhancement. Comparative analyses of various techniques for development of DSTATCOM Objective functions and constraints; Merits and Demerits are presented.
Published: 2022

27. Physical layer security using boundary technique for emerging wireless communication systems

Author: Ismaeel Abiodun Sikiru, Lukman Abiodun Olawoyin, Nasir Faruk, Abdulkarim Ayopo Oloyede, Abubakar Abdulkarim, Imam‐Fulani Yusuf Olayinka, Olugbenga Akinkunmi Sowande, Salisu Garba, and Agbotiname Lucky Imoize
Subjects: General Engineering
Published: 2022

28. Application of Machine Learning Algorithms to Path Loss Modeling: A Review

Author: Abubakar Abdulkarim, Nasir Faruk, Emmanuel Alozie, Olugbenga. A. Sowande, Imam-Fulani Yusuf Olayinka, Aliyu D. Usman, Kayode S. Adewole, Abdulkarim A. Oloyede, Haruna Chiroma, Salisu Garba, Agbotiname Lucky Imoize, Abdulwaheed Musa, and Lawan S. Taura
Published: 2022

29. Stray Animal Population Control: Methods, Public Health Concern, Ethics, and Animal Welfare Issues

Author: M. A. K. G. Khan, Erkihun Aklilu, and Abubakar Abdulkarim
Subjects: medicine.medical_specialty, General Veterinary, Public economics, Animal Welfare (journal), Public health, parasitic diseases, medicine, Business, Population control
Abstract: Stray animal overpopulation has become one of the most serious global problems with many negative impacts on the community, environment, and public health. Most of the stray animals do not depend on humans for food and shelter, and therefore, can reproduce uncontrollably. The uncontrolled reproduction of stray animals increases their population that leads to a higher chance of predation, road traffic accidents, transmission of zoonotic diseases, and therefore, becoming vectors for some diseases. There are several methods for stray animal population control depending on the situation and the nature of the stray animals. These methods include contraceptives, trap-neuter-return, poisoning, euthanasia, and gun shooting among others. Each of the outlined methods has its advantages and disadvantages as to their practicality, ease of conducting, cost, effectiveness, ethics, and animal welfare issues. In conclusion, to achieve successful control measures of the stray animal population and the problem they create, the concerned authorities need to design and enact animal rights laws, provide medical care (treatment and vaccination), feeding, shelter for the animals, and control their reproduction. Public health and environmental agencies may improve the services by regulating personal and environmental hygiene, prevention, and control of zoonotic and transmissible diseases that can be transmitted from stray animals to the public and other livestock respectively.
Published: 2021

30. Electroencephalogram (EEG) Based Imagined Speech Decoding and Recognition

Author: Zhang Shuai, Abd El Kader Isselmou, Adamu Halilu Jabire, Isah Salim Ahmad, Guizhi Xu, Ibrahim Abdullahi Karaye, Abubakar Abdulkarim, and Sani Saminu
Subjects: medicine.diagnostic_test, Computer science, Brain activity and meditation, Imagined speech, Speech recognition, 0206 medical engineering, 02 engineering and technology, Electroencephalography, 020601 biomedical engineering, Task (project management), 03 medical and health sciences, 0302 clinical medicine, Neuroimaging, SAFER, medicine, 030217 neurology & neurosurgery, Decoding methods, Brain–computer interface
Abstract: The recent investigations and advances in imagined speech decoding and recognition has tremendously improved the decoding of speech directly from brain activity with the help of several neuroimaging techniques that assist us in exploring the neurological processes of imagined speech. This development leads to assist people with disabilities to benefit from neuroprosthetic devices that improve the life of those suffering from neurological disorders. This paper presents the summary of recent progress in decoding imagined speech using Electroenceplography (EEG) signal, as this neuroimaging method enable us to monitor brain activity with high temporal resolution, it is very portable, low cost, and safer as compared to other methods. Therefore, it is a good candidate in investigating an imagined speech decoding from the human cortex which remains a challenging task. The paper also reviews some recent techniques, challenges, future recommendations and possible solutions to improve prosthetic devices and the development of brain computer interface system (BCI).
Published: 2021

31. A comprehensive survey on low-cost ECG acquisition systems: Advances on design specifications, challenges and future direction

Author: I A Katibi, Yusuf Y. Folawiyo, Kayode S. Adewole, Abdukareem A. Oloyede, Hammed A. Mojeed, J.A. Ogunmodede, Abubakar Abdulkarim, Nasir Faruk, Abdulsalam Ya'u Gital, Musa Nehemiah, Ifada Emmanuel, Ismaeel A. Sikiru, Haruna Chiroma, Lukman A. Olawoyin, and Mubarak Almutairi
Subjects: Computer science, business.industry, 0206 medical engineering, Biomedical Engineering, 02 engineering and technology, 020601 biomedical engineering, Critical infrastructure, Financial instability, Diagnostic modalities, Open research, Risk analysis (engineering), Health care, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Use case, business, Reliability (statistics), Efficient energy use
Abstract: Availability of low-cost, reliable, and portable Electrocardiography (ECG) devices is still very important in the medical world today. Despite the tremendous technological advancement, Cardiovascular Diseases (CVDs) remain a serious health burden claiming millions of lives on an annual basis globally. This is more prevalent in Low and Middle-Income Countries (LMICs) where there are huge financial instability and lack of critical infrastructure and support services for the health care system. Efforts aimed at reducing the prevalence of CVDs are confounded by late diagnosis, frequently, caused by lack of access to or non-availability of basic diagnostic modalities such as the ECG. Hence effective mitigation of the effect of CVDs in LMICs depend on the development of such devices at low-cost with reliability, accuracy and energy efficiency. This paper therefore, was developed to understand the state of the art of low-cost ECG acquisition systems with respect to design features and system capabilities for different use cases. In addition, different design options and taxonomies of available low-cost ECG devices, case studies reports of efficacy tests have been provided. The paper proposes a generalised ECG framework and provides implementation challenges and open research directions that should be considered when developing such devices for proper management of CVDs.
Published: 2021

32. Development of a Low-Cost Wireless Environmental Monitoring System

Author: Abdulkarim. A. Oloyede, Nasir Faruk, Abubakar Abdulkarim, Adetola Sogbesan, Salisu Garba, and Lukman A. Olawoyin
Published: 2022

33. Proactive Fuzzy-Based Backup Channel Selection Scheme for Spectrum Handoff in Cognitive Radio Networks

Author: Emmanuel Alozie, Nasir Faruk, Abdulkarim. A. Oloyede, Olugbenga. A. Sowande, Agbotiname Lucky Imoize, and Abubakar Abdulkarim
Published: 2022

34. Efficacy of some Unpopular PathLoss Propagation Models in the VHF and UHF Bands

Author: Lagodo Hafis Olajuwon, Nasir Faruk, Abdulkarim A. Oloyede, Olugbenga. A. Sowande, Abubakar Abdulkarim, Lukman A. Olawoyin, and Yinusa A. Adediran
Published: 2022

35. Effect of Training Algorithms and Network Architecture on the Performance of Multi-Band ANN-Based Path Loss Prediction Model

Author: Quadri Ramon Adebowale, Nasir Faruk, Kayode S. Adewole, Abubakar Abdulkarim, Abdulkarim A. Oloyede, Haruna Chiroma, Olugbenga. A. Sowande, Aliyu D. Usman, Imam-Fulani Yusuf Olayinka, Abduljalal Yusharu Kassim, and Lawan S. Taura
Published: 2022

36. 5G Frequency Standardization, Technologies, Channel Models, and Network Deployment: Advances, Challenges, and Future Directions

Author: Yusuf Olayinka Imam-Fulani, Nasir Faruk, Olugbenga A. Sowande, Abubakar Abdulkarim, Emmanuel Alozie, Aliyu D. Usman, Kayode S. Adewole, Abdulkarim A. Oloyede, Haruna Chiroma, Salisu Garba, Agbotiname Lucky Imoize, Bashir Abdullahi Baba, Abdulwaheed Musa, Yinusa A. Adediran, and Lawan S. Taura
Subjects: Renewable Energy, Sustainability and the Environment, Geography, Planning and Development, Building and Construction, Management, Monitoring, Policy and Law
Abstract: The rapid increase in data traffic caused by the proliferation of smart devices has spurred the demand for extremely large-capacity wireless networks. Thus, faster data transmission rates and greater spectral efficiency have become critical requirements in modern-day networks. The ubiquitous 5G is an end-to-end network capable of accommodating billions of linked devices and offering high-performance broadcast services due to its several enabling technologies. However, the existing review works on 5G wireless systems examined only a subset of these enabling technologies by providing a limited coverage of the system model, performance analysis, technology advancements, and critical design issues, thus requiring further research directions. In order to fill this gap and fully grasp the potential of 5G, this study comprehensively examines various aspects of 5G technology. Specifically, a systematic and all-encompassing evaluation of the candidate 5G enabling technologies was conducted. The evolution of 5G, the progression of wireless mobile networks, potential use cases, channel models, applications, frequency standardization, key research issues, and prospects are discussed extensively. Key findings from the elaborate review reveal that these enabling technologies are critical to developing robust, flexible, dependable, and scalable 5G and future wireless communication systems. Overall, this review is useful as a resource for wireless communication researchers and specialists.
Published: 2023

37. Rural Healthcare Delivery in Sub-Saharan Africa

Author: Abubakar Abdulkarim, Abdulkarim A. Oloyede, Lukman A. Olawoyin, Thierry Oscar Edoh, Olayiwola W. Bello, Segun I. Popoola, Nasir Faruk, and N. T. Surajudeen-Bakinde
Subjects: 03 medical and health sciences, Economic growth, 0302 clinical medicine, Information Systems and Management, Sub saharan, Healthcare delivery, 030220 oncology & carcinogenesis, parasitic diseases, Medicine (miscellaneous), 030212 general & internal medicine, Business, Information Systems
Abstract: Access to quality healthcare is a major problem in Sub-Saharan Africa with a doctor-to-patient ratio as high as 1:50,000, which is far above the recommended ratio by the World Health Organization (WHO) which is 1:600. This has been aggravated by the lack of access to critical infrastructures such as the health care facilities, roads, electricity, and many other factors. Even if these infrastructures are provided, the number of medical practitioners to cater for the growing population of these countries is not sufficient. In this article, how information and communication technology (ICT) can be used to drive a sustainable health care delivery system through the introduction and promotion of Virtual Clinics and various health information systems such as mobile health and electronic health record systems into the healthcare industry in Sub-Saharan Africa is presented. Furthermore, the article suggests ways of attaining successful implementation of telemedicine applications /services and remote health care facilities in Africa.
Published: 2020

38. Secure transmission in an unfriendly environment

Author: Abubakar Abdulkarim, Segun I. Popoola, Temitayo C. Adeniran, N. T. Surajudeen-Bakinde, Lukman A. Olawoyin, Abdulkarim A. Oloyede, and Nasir Faruk
Subjects: Computer Networks and Communications, Computer science, 02 engineering and technology, Data_CODINGANDINFORMATIONTHEORY, law.invention, Secure communication, Artificial Intelligence, Relay, law, 0202 electrical engineering, electronic engineering, information engineering, Computer Science::Networking and Internet Architecture, Full-duplex, Secure transmission, Computer Science::Information Theory, lcsh:T58.5-58.64, business.industry, Noise (signal processing), lcsh:Information technology, Node (networking), 020208 electrical & electronic engineering, Transmitter, ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS, 020206 networking & telecommunications, Average secrecy capacity, Secure outage probability, Artificial noise, Transmission (telecommunications), Hardware and Architecture, Antenna (radio), business, Software, Information Systems, Computer network
Abstract: This work investigates and show the performance of destination assisted node in ensuring secure communication in a dual-hop broadcast system. The information transmission occurs between the transmitters which are assumed to be equipped with single antenna through a number of intermediate untrusted relays to the receiver in the presence of multiple passive eavesdroppers. This work assumes that there is no direct link between the transmitter and the receiver and hence, the relay node, receives either the information or noise signal at every transmission processes. Since the transmission occurs in a two-phase, the legitimate receiver is contributing a degrading noise to both the eavesdropper and relay node channels during the first phase while it receives information from the transmitter through the relay during the second phase. Simulation results are used to illustrate the performance of the proposed scheme.
Published: 2020

39. Load modeling techniques in distribution networks: a review

Author: A. S. Abubakar, Abubakar Abdulkarim, Y. Jibril, Abdullahi Bala Kunya, and Musa Mohammed
Subjects: 0209 industrial biotechnology, Distribution networks, Computer science, business.industry, Load modeling, Control engineering, 02 engineering and technology, Renewable energy, Distribution system, Electric power system, 020901 industrial engineering & automation, 0202 electrical engineering, electronic engineering, information engineering, State of art, Smart network, 020201 artificial intelligence & image processing, Electronics, business
Abstract: Power system operation and control required models of generators, lines and loads to be accurately estimated, this is to enable operators make a reliable decision on the system. Generators and lines models are so far considered accurate, while load models are considered perplexing due to invention of new types of loads, distribution system are transforming from passive to active. Future distribution systems are desired to be smart and for a network to be smart the system as to be fully and accurately represented. Penetration of renewable energy and application of power electronic devices as well as participation of active customers in distribution systems make traditional methods of load modeling absolute. Accurate load modeling is required to address the new challenges evolving in the task of power system operation, control and stability studies. It is also an interest of power system researchers globally to realize Smart Networks (SNs), in which accurate load models are required. This work described a review of techniques and approaches for load modeling from traditional methods to the state of art in the area. In addition, gaps in the literature as well as research directions are also pointed out.
Published: 2020

40. Detection of Staphylococcus pseudintermedius in Dogs and Cats in Selangor, Malaysia

Author: Abdinasir Yusuf Osman, Muhammad Luqman Nordin, Siti Khairani Bejo, G. K. Dhaliwal, Mohammed Dauda Goni, Rumaizi Shaari, Mohamed Abdelrahman Mohamed, Sharifo Ali Elmi, Abubakar Abdulkarim Kanamma, and Saleha Abd Aziz
Subjects: Nasal cavity, Veterinary medicine, CATS, Staphylococcus pseudintermedius, General Veterinary, Animal health, biology, business.industry, Rectum, biology.organism_classification, medicine.anatomical_structure, Stray cats, Research studies, medicine, Animal Science and Zoology, Coagulase, business
Abstract: Staphylococcus pseudintermedius is an emerging coagulase gram-positive staphylococci in dogs and cats. It has now become a threat to animal health due to its multidrug resistance leading to very limited therapeutic options particularly in the treatment of small animals and therefore, requires urgent action to control its spread. The organism is currently recognised as a significant pathogen in veterinary medicine causing skin, ear and wound infections in dogs and cats. So far, there is limited coverage in relation to research studies concerning on S. pseudintermedius in dogs and cats in Malaysia. Therefore, this study was conducted to determine the presence of S. pseudintermedius in dogs and cats as well as to evaluate the best site for isolation of the organism. A total of two hundred dogs (n = 100) and cats (n = 100) were randomly sampled. Swab samples were taken from the nasal cavity, buccal cavity, rectum and perineal skin aseptically from both pet and stray dogs and cats. The samples were cultured and isolates were identified by biochemical tests and confirmed using a species-specific PCR assay. Our results revealed that the proportion of detection of S. pseudintermedius was higher in stray dogs and cats than pet animals. Staphylococcus pseudintermedius was detected in 6.5% (13/200) stray dogs, 6% (12/200) stray cats, 1.5% (3/200) pet dogs and 0% in pet cats. Our findings also demonstrated that nasal cavity was the ideal site for isolation of the organism (5.5%), followed by buccal cavity (3.5%), skin (2.5%) and rectum (2.5%), but statistically, the difference was not significant (p = 0.174). In conclusion, this study provided an empirical evidence in relation to the detection of S. pseudintermedius in stray and pet dogs and cats in Selangor, Malaysia. Future research is urgently needed to better understand the epidemiology of S. pseudintermedius in field settings.
Published: 2020

41. Effect of Membership Functions and Data Size on the Performance of ANFIS-Based Model for Predicting Path Losses in the VHF and UHF Bands

Author: Emmanuel Adetiba, Nasir Faruk, Abubakar Abdulkarim, Lukman A. Olawoyin, Abdulkarim A. Oloyede, N. T. Surajudeen-Bakinde, Segun I. Popoola, and O.A. Sowande
Subjects: Reduction (complexity), Adaptive neuro fuzzy inference system, symbols.namesake, Ultra high frequency, Mean squared error, Computational complexity theory, Computer science, Gaussian, General Engineering, symbols, Path loss, Algorithm, Membership function
Abstract: Today, the world is technology-driven and so of these technologies are driven using wireless systems. Signal coverage and quality of service are pertinent for network providers and path loss prediction is very important in the design and planning of these systems. However, the inefficiency of conventional propagation models, such as empirical, deterministic and theoretical models has been established in previous research works. The machine learning methods have recently been applied for prediction of path losses. The Adaptive Neuro-Fuzzy Inference System (ANFIS) technique is one of the machine learning techniques that has been successfully employed to predict path losses in different environments. However, the performance of the ANFIS-based models in terms of the computational complexity and accuracy depends on the selection of the appropriate system parameters. This paper, therefore, investigates the effect of number and shape of membership function (MF), and training data size on the performance of ANFIS model for predicting path losses in the VHF and UHF bands in built-up environments. Path loss propagation measurements were conducted in four cities of Nigeria over the cellular and broadcasting frequencies. A total of 17 broadcast transmission and cellular base stations were utilized for this study. From the results obtained, it can be concluded for the broadcasting bands that the generalized bell MF shows better performance with an average RMSE of 3.00 dB across all the routes, followed by gaussian, Pi, trapezoid and triangular MFs in that other with average RMSE values of 3.09 dB, 3.11 dB, 3.16 dB and 3.23 dB respectively. For the cellular systems, Triangular MF outperformed other MFs with the lowest average RMSE. The generalized bell MF was found to be suited for WCDMA band while triangular MF is most suited for GSM band. Furthermore, it can also be concluded that the higher the number of membership functions, the lower the RMSE, whereas, a decrease in the data size leads to a reduction in the RMSE values. The findings of this study would help researchers and network planners to make a more informed decision on choosing appropriate system parameters when modelling ANFIS models for path loss prediction.
Published: 2021

42. A Review on Rain Signal Attenuation Modeling, Analysis and Validation Techniques: Advances, Challenges and Future Direction

Author: Emmanuel Alozie, Abubakar Abdulkarim, Ibrahim Abdullahi, Aliyu D. Usman, Nasir Faruk, Imam-Fulani Yusuf Olayinka, Kayode S. Adewole, Abdulkarim A. Oloyede, Haruna Chiroma, Olugbenga A. Sowande, Lukman A. Olawoyin, Salisu Garba, Agbotiname Lucky Imoize, Abdulwaheed Musa, Yinusa A. Adediran, and Lawan S. Taura
Subjects: Renewable Energy, Sustainability and the Environment, Geography, Planning and Development, Building and Construction, Management, Monitoring, Policy and Law
Abstract: Radio waves are attenuated by atmospheric phenomena such as snow, rain, dust, clouds, and ice, which absorb radio signals. Signal attenuation becomes more severe at extremely high frequencies, usually above 10 GHz. In typical equatorial and tropical locations, rain attenuation is more prevalent. Some established research works have attempted to provide state-of-the-art reviews on modeling and analysis of rain attenuation in the context of extremely high frequencies. However, the existing review works conducted over three decades (1990 to 2022), have not adequately provided comprehensive taxonomies for each method of rain attenuation modeling to expose the trends and possible future research directions. Also, taxonomies of the methods of model validation and regional developmental efforts on rain attenuation modeling have not been explicitly highlighted in the literature. To address these gaps, this paper conducted an extensive literature survey on rain attenuation modeling, methods of analyses, and model validation techniques, leveraging the ITU-R regional categorizations. Specifically, taxonomies in different rain attenuation modeling and analysis areas are extensively discussed. Key findings from the detailed survey have shown that many open research questions, challenges, and applications could open up new research frontiers, leading to novel findings in rain attenuation. Finally, this study is expected to be reference material for the design and analysis of rain attenuation.
Published: 2022

43. Large-scale radio propagation path loss measurements and predictions in the VHF and UHF bands

Author: Aderemi A. Atayero, O.A. Sowande, Nasir Faruk, I. Y. Abdulrasheed, Ayodele H. Ifijeh, N. T. Surajudeen-Bakinde, Abdulkarim A. Oloyede, Emmanuel Adetiba, and Abubakar Abdulkarim
Subjects: 0301 basic medicine, Science (General), Computer science, Measure (physics), Broadcasting, Kriging Interpolation Method, Radio propagation, Q1-390, 03 medical and health sciences, 0302 clinical medicine, Prediction model, Path loss, Fading, Path loss measurement, Remote sensing, H1-99, Multidisciplinary, business.industry, Social sciences (General), 030104 developmental biology, Ultra high frequency, Clutter, business, 030217 neurology & neurosurgery, Radio wave, Research Article
Abstract: For decades now, a lot of radio wave path loss propagation models have been developed for predictions across different environmental terrains. Amongst these models, empirical models are practically the most popular due to their ease of application. However, their prediction accuracies are not as high as required. Therefore, extensive path loss measurement data are needed to develop novel measurement-oriented path loss models with suitable correction factors for varied frequency, capturing both local terrain and clutter information, this have been found to be relatively expensive. In this paper, a large-scale radio propagation path loss measurement campaign was conducted across the VHF and UHF frequencies. A multi-transmitter propagation set-up was employed to measure the strengths of radio signals from seven broadcasting transmitters (operating at 89.30, 103.5, 203.25, 479.25, 615.25, 559.25 and 695.25 MHz respectively) at various locations covering a distance of 145.5 km within Nigerian urban environments. The measurement procedure deployed ensured that the data obtained strictly reflect the shadowing effects on radio signal propagation by filtering out the small-scale fading components. The paper also, examines the feasibilities of applying Kriging method to predict distanced-based path losses in the VHF and UHF bands. This method was introduced to minimize the cost of measurements, analysis and predictions of path losses in built-up propagation environments., Path loss measurement, Kriging Interpolation Method, prediction model, radio propagation
Published: 2021

44. Performance Evaluation of Different Membership Function in Fuzzy Logic Based Short-Term Load Forecasting

Author: Mutiu Shola Bakare, Abdulrahman Okino Otuoze, Ibrahim S. Madugu, Waheed Olaide Owonikoko, Abubakar Abdulkarim, Oladimeji Ibrahim, Mubarak A. Afolayan, and Kayode Elijah Adedayo
Subjects: Mathematical optimization, Computer science, 020209 energy, Load forecasting, 020208 electrical & electronic engineering, 0202 electrical engineering, electronic engineering, information engineering, General Engineering, 02 engineering and technology, Fuzzy logic, Membership function, Term (time)
Abstract: A mismatch between utility-scale electricity generation and demand often results in resources and energy wastage that needed to be minimized. Therefore, the utility company needs to be able to accurately forecast load demand as a guide for the planned generation. Short-term load forecast assists the utility company in projecting the future energy demand. The predicted load demand is used to plan ahead for the power to be generated, transmitted, and distributed and which is crucial to power system reliability and economics. Recently, various methods from statistical, artificial intelligence, and hybrid methods have been widely used for load forecasts with each having their merits and drawbacks. This paper investigates the application of the fuzzy logic technique for short-term load forecast of a day ahead load. The developed fuzzy logic model used time, temperature, and historical load data to forecast 24 hours load demand. The fuzzy models were based on both the trapezoidal and triangular membership function (MF) to investigate their accuracy and effectiveness for the load forecast. The obtained low Mean Absolute Percentage Error (MAPE), Mean Forecast Error (MFE), and Mean Absolute Deviation (MAD) values from the forecasted load results showed that both models are suitable for short-term load forecasting, however the trapezoidal MF showed better performance than the triangular MF.
Published: 2021

45. Parametric Model Based Approach for Consumer Load Prediction

Author: A.I. Abdullateef, Mudathir Folohunso Akorede, Abubakar Abdulkarim, and Momoh-Jimoh Eyiomika Salami
Subjects: Consumption (economics), Data point, Autoregressive model, Estimation theory, Computer science, Parametric model, Work (physics), Statistics, Autoregressive–moving-average model, Energy consumption
Abstract: Various load prediction techniques have been proposed to predict consumer load which represents the activities of the consumer on the distribution network. Usually, these techniques use cumulative energy consumption data of the consumers connected to the power network to predict consumer load. However, this data fails to reveal and monitor the activities of individual consumers represented by consumer load consumption pattern. A new approach of predicting individual consumer load based on autoregressive moving average model (ARMA) is proposed in this study. Sub- optimal technique of parameter estimation based on Prony method was used to determine the model order of the ARMA models ARMA (10, 8), ARMA (8, 6) and ARMA (6, 4). ARMA (6, 4) was found to be appropriate for consumer load prediction with an average mean square error of 0.00006986 and 0.0000685 for weekday and weekend loads respectively. The energy consumption data acquired from consumer load prototype for one week, with 288 data points per day used in our previous work, was used and 5-minute step ahead load prediction is achieved. Furthermore, a comparison between autoregressive AR (20) and ARMA (6, 4) was carried out and ARMA (6, 4) was found to be appropriate for consumer load prediction. This facilitates the monitoring of individual consumer activities connected on the power network.
Published: 2019

46. ANFIS Model for Path Loss Prediction in the GSM and WCDMA Bands in Urban Area

Author: Abubakar Abdulkarim, N. T. Surajudeen-Bakinde, A. Abdulkarim, Aderemi A. Atayero, Segun I. Popoola, Lukman A. Olawoyin, and Nasir Faruk
Subjects: Adaptive neuro fuzzy inference system, geography, geography.geographical_feature_category, Mean squared error, Computer science, computer.software_genre, Urban area, GSM, Path loss, Wireless systems, Data mining, Mobile communication systems, computer, UMTS frequency bands
Abstract: Path loss propagation is a vital concern when designing and planning networks in mobile communication systems. Propagation models such as the empirical, deterministic and theoretical models, which possess complex, inconsistent, time-consuming and non-adaptable features, have proven to be inefficient in designing of wireless systems, thereby resulting in the need for a more reliable model. Artificial Intelligence methods seem to overcome the drawbacks of the propagation models for predicting path loss. In this paper, the ANFIS approach to path loss prediction in the GSM and WCDMA bands is presented for selected urban areas in Nigeria. Furthermore, the effects of the number of Membership Functions (MFs) are investigated. The prediction results indicated that the ANFIS model outperformed the Hata, Cost-231, Egli and ECC-33 models in both Kano and Abuja urban areas. In addition, an increase in the number of MFs conceded an improved RMSE result for the generalized bell-shaped MF. The general performance and outcome of this research work show the efficiency and usefulness of the ANFIS model in improving prediction accuracy over propagation models
Published: 2019

47. State of the Art in Research on Optimum Design, Reliability and Control of Renewable Energy Microgrids

Author: Lukman A. Olawoyin, Y. Jibril, Yinusa A. Adediran, Segun I. Popoola, Oladimeji Ibrahim, Abubakar Abdulkarim, A. O. Oloyode, Sobhy M. Abdelkader, N. T. Surajudeen-Bakinde, John Morrow, Nasir Faruk, and A.I. Abdullateef
Subjects: Electric power system, Wind power, Work (electrical), business.industry, Computer science, Control (management), Microgrid, Environmental economics, business, Solar energy, Reliability (statistics), Renewable energy
Abstract: This paper has presented a comprehensive review in the area of microgrid from the design to implementation. The aim is to evaluate the current status, problems and research efforts toward realising functional microgrids in the power system. The expectations about microgrid are many; therefore the study is divided into three main sections. Recent advancements in the wind energy, solar energy and their future prediction are summarised. States of arts in optimum design of renewable energy microgrid are also investigated. In addition, critical literature review in the reliability analysis of microgrids consisting of renewable energy sources is also reported. Control of microgrids consisting renewable energy sources have been presented. Some examples of existing microgrids across the globe are critically reviewed. The work therefore recommends that energy planners and all stakeholders should consider environmental and regional difference in microgrids planning. Finally, future research areas and directions in these areas are highlighted.
Published: 2018

48. A Review on Unmanned Aerial Vehicle Energy Sources and Management

Author: Sulaiman Haruna Sulaiman, Abubakar Abdulkarim, Ahmad Bala Alhassan, Ibrahim Abdullahi Shehu, and Musa Mohammed
Subjects: Energy management system, Battery (electricity), Internal combustion engine, business.industry, Payload, Computer science, ComputerApplications_COMPUTERSINOTHERSYSTEMS, Wireless power transfer, business, Energy source, Automotive engineering, Energy (signal processing), Renewable energy
Abstract: Unmanned Aerial vehicle (UAV) systems have an insufficient amount of onboard energy which is being shared for mobility, transmission, data processing, control and payload related applications. Different energy sources have been investigated and applied to solve unmanned aerial vehicle energy limitations. These energy sources were either used as single sources or hybrid for the reason of UAV weight budget or miniaturization. To achieve the aforementioned designed criteria, researchers around the globe are continuously investigating different energy sources and hybridization techniques while others focus on the Energy Management System (EMS) such to achieve optimal energy sources utilization. Such energy sources and supplying techniques are battery swapping, wireless Power Transfer (WPT), tethering methods, Fuel Cells (FC), and SuperCapacitors (SC). While, the hybridization technique is based on the combination of single energy source with either renewable energy sources, Internal Combustion Engine (ICE) to save fuel or WPT. Example of such hybridization techniques are solar and battery storage, Fuel Cell (FC) and Battery Storage (BS) etc. This article presents an in-depth review of UAV energy sources, hybridization techniques and EMS. Their challenges and methods adopted by researchers to mitigate such UAV energy challenges.
Published: 2021

49. Application of Computational Intelligence Algorithms in Radio Propagation: A Systematic Review and Metadata Analysis

Author: Abdulkarim A. Oloyede, Haruna Chiroma, Kayode S. Adewole, Quadri Ramon Adebowale, Aliyu D. Usman, Nasir Faruk, Abubakar Abdulkarim, Lukman A. Olawoyin, and Carlos T. Calafate
Subjects: Article Subject, Artificial neural network, Computer Networks and Communications, Computer science, business.industry, 020302 automobile design & engineering, 020206 networking & telecommunications, Computational intelligence, TK5101-6720, 02 engineering and technology, computer.software_genre, Swarm intelligence, Computer Science Applications, ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES, Radio propagation, Open research, 0203 mechanical engineering, Telecommunication, 0202 electrical engineering, electronic engineering, information engineering, Wireless, Path loss, Data mining, business, computer, Communication channel
Abstract: [EN] The importance of wireless path loss prediction and interference minimization studies in various environments cannot be over-emphasized. In fact, numerous researchers have done massive work on scrutinizing the effectiveness of existing path loss models for channel modeling. The difficulties experienced by the researchers determining or having the detailed information about the propagating environment prompted for the use of computational intelligence (CI) methods in the prediction of path loss. This paper presents a comprehensive and systematic literature review on the application of nature-inspired computational approaches in radio propagation analysis. In particular, we cover artificial neural networks (ANNs), fuzzy inference systems (FISs), swarm intelligence (SI), and other computational techniques. The main research trends and a general overview of the different research areas, open research issues, and future research directions are also presented in this paper. This review paper will serve as reference material for researchers in the field of channel modeling or radio propagation and in particular for research in path loss prediction., This work was funded by the Federal Ministry of Education, Federal Government of Nigeria, Tertiary Education Trust Fund (TETFUND), Institutional Based Research (IBR) Fund, 2018.
Published: 2021

50. An Investigative Study on Impact of Frequency Dynamics in Load Modeling

Author: Abdullahi Bala Kunya, Musa Mohammed, Abubakar Abdulkarim, Ibrahim Abdullahi Shehu Bashir Musa Umar, and Adamu Sa’du Abubakar
Subjects: Computer science, Control theory, Load modeling, Dynamics (mechanics)
Abstract: Load modeling plays a significant impact in assessing power system stability margin, control, and protection. Frequency in the power system is desired to be kept constant, but in a real sense, it is not constant as loads continually change with time. In much literature, frequency dynamics are ignored in the formulation of load models for the basic assumption that it does not affect the models. In this paper, the composite load model was formulated with Voltage-Frequency Dependency (V-FD) on real and reactive powers and applied to estimate the load model. 2- Area network 4- machines Kundur test network was used for testing the developed model. The model was trained with measurements from a low voltage distribution network supplying the Electrical Engineering department at Ahmadu Bello University, Zaria. Both training and testing data were captured under normal system operation (dynamics). To evaluate the V-FD model performance, Voltage-Dependent (VD) model was examined on the same measured data. The work makes use of the Feed Forward Neural Network (FFNN) as a nonlinear estimator. Results obtained indicate that including frequency dynamics in modeling active power reduces the accuracy of the model. While in modeling reactive power the model performance improves. Hence, it can be said that including frequency dynamics in load modeling depends on the intended application of the model.
Published: 2020

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