334 results on '"Uçan, Osman Nuri"'
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2. Modeling and Simulation of a Hybrid Electrical Grid for Reliability and Power Quality Enchantment
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AL-Mashhadani, Yahya Mohammed Jasim, Uçan, Osman Nuri, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Rasheed, Jawad, editor, Abu-Mahfouz, Adnan M., editor, and Fahim, Muhammad, editor
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- 2024
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3. Online Estimation of Resource Overload Risk in 5G Multi-Tenancy Network
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Hamad, Yasameen Shihab, Han, Bin, and ucan, Osman Nuri
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Computer Science - Networking and Internet Architecture ,Electrical Engineering and Systems Science - Signal Processing - Abstract
The technology of network slicing, as the most characteristic feature of the fifth generation (5G) wireless networks, manages the resources and network functions in heterogeneous and logically isolated slices on the top of a shared physical infrastructure, where every slice can be independently customized to fulfill the specific requirements of its devoted service type. It enables a new paradigm of multi-tenancy networking, where the network slices can be leased by the mobile network operator (MNO) to tenants in form of public cloud computing service, known as Slice-asa- Service (SlaaS). Similar to classical cloud computing scenarios, SlaaS benefits from overbooking its resources to numerous tenants, taking advantage of the resource elasticity and diversity, at a price of risking overloading network resources and violating the service-level agreements (SLAs), which stipulate the quality of service (QoS) that shall be guaranteed to the network slices. Thus, it becomes a critical challenge to the MNOs, accurately estimating the resource overload risk - especially under the sophisticated network dynamics - for monitoring and enhancing the reliability of SlaaS business., Comment: To appear at ESREL 2021
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- 2021
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4. Classification of the Level of Alzheimer's Disease Using Anatomical Magnetic Resonance Images Based on a Novel Deep Learning Structure
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Al-Jumaili, Saif, primary, Al-Azzawi, Athar, additional, Uçan, Osman Nuri, additional, and Duru, Adil Deniz, additional
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- 2023
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5. Secure banking and international trade digitization using blockchain
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Alsalim, Mohammed Sabah Hameed and Ucan, Osman Nuri
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- 2023
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6. Novel semi-supervised learning approach for descriptor generation using artificial neural networks
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Alwindawi, Alla Fikrat, Uçan, Osman Nuri, Ibrahim, Abdullahi A., and Yusuf, Aminu
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- 2022
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7. Utilizing Multivariate Clustering and Spatial Analysis for Selecting Suitable sites for Sustainable Wind Energy
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Khalaf, Oras Fadhil, primary, Uçan, Osman Nuri, additional, and Alsamarai, Naseem Adnan, additional
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- 2024
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8. Semi-Supervised Learning with Ensemble Deep Learning Networks for Descriptor Generation
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Alwindawi, Alla Fikrat, Uçan, Osman Nuri, Ibrahim, Abdullahi A., and Abbas, Sharafaldeen Abdulkadhum
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- 2022
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9. Schizophrenia diagnosis based on diverse epoch size resting-state EEG using machine learning.
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Alazzawı, Athar, Aljumaili, Saif, Duru, Adil Deniz, Uçan, Osman Nuri, Bayat, Oğuz, Coelho, Paulo Jorge, and Pires, Ivan Miguel
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ADDITIVE white Gaussian noise ,UNCERTAINTY (Information theory) ,FAST Fourier transforms ,SUPPORT vector machines ,K-nearest neighbor classification - Abstract
Schizophrenia is a severe mental disorder that impairs a person's mental, social, and emotional faculties gradually. Detection in the early stages with an accurate diagnosis is crucial to remedying the patients. This study proposed a new method to classify schizophrenia disease in the rest state based on neurologic signals achieved from the brain by electroencephalography (EEG). The datasets used consisted of 28 subjects, 14 for each group, which are schizophrenia and healthy control. The data was collected from the scalps with 19 EEG channels using a 250 Hz frequency. Due to the brain signal variation, we have decomposed the EEG signals into five sub-bands using a band-pass filter, ensuring the best signal clarity and eliminating artifacts. This work was performed with several scenarios: First, traditional techniques were applied. Secondly, augmented data (additive white Gaussian noise and stretched signals) were utilized. Additionally, we assessed Minimum Redundancy Maximum Relevance (MRMR) as the features reduction method. All these data scenarios are applied with three different window sizes (epochs): 1, 2, and 5 s, utilizing six algorithms to extract features: Fast Fourier Transform (FFT), Approximate Entropy (ApEn), Log Energy entropy (LogEn), Shannon Entropy (ShnEn), and kurtosis. The L2-normalization method was applied to the derived features, positively affecting the results. In terms of classification, we applied four algorithms: K-nearest neighbor (KNN), support vector machine (SVM), quadratic discriminant analysis (QDA), and ensemble classifier (EC). From all the scenarios, our evaluation showed that SVM had remarkable results in all evaluation metrics with LogEn features utilizing a 1-s window size, impacting the diagnosis of Schizophrenia disease. This indicates that an accurate diagnosis of schizophrenia can be achieved through the right features and classification model selection. Finally, we contrasted our results to recently published works using the same and a different dataset, where our method showed a notable improvement. [ABSTRACT FROM AUTHOR]
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- 2024
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10. Renewable energy utilization in demand-side energy management system based on linear programming optimization algorithm.
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Almashhadani, Muna Kamel, Cevik, Mesut, Al-Jumaili, Saif, Alhanaf, Ahmed Sami, Al-Bhadely, Faraj Khlaf, and Uçan, Osman Nuri
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OPTIMIZATION algorithms ,ENERGY management ,ENERGY consumption ,ENERGY demand management ,RENEWABLE energy sources ,GRIDS (Cartography) - Abstract
Demand-side management (DSM) is an effectual approach by coordinating utility management and routinely tracking energy usage, the intelligent grid assists in controlling energy demand and promotes its efficiency. However, the paper aims to utilize Linear programming optimization algorithms as an effective tool for managing energy demand and maximizing the use of renewable energy sources. These algorithms are able to estimate which is the best utilization of what resources are accessible and reduce consumption by describing the energy system as a collection of linear equations. The optimization system makes assumptions about the various energy costs when it will be high or low and modifies energy use accordingly. We applied different scenarios to assess the resiliency of the system. The simulation took into account a number of variables, including the weather, energy usage, and pricing fluctuations. MATLAB R2023a and Simulink provide an integrated platform with data analytics to build the proposed system and optimization model to minimize cost in MATLAB. Compared to other methods using various optimization algorithms as the binary orientation search algorithm (BOSA), cockroach swarm optimization (CSO), and the sparrow search algorithm (SSA) were applied to DSM methodology for a residential community with a primary focus on decreasing peak energy consumption results as in previous study was, BOSA has a lower standard deviation (0.8) compared to the other algorithms (1.7 for SSA and 1.3 for CSOA), making it more robust and superior, in addition to minimizing cost (5438.98 cents of USD (mean value) and 16.3% savings), the suggested approach is used for lowering electrical energy costs in a micro-grid system while maintaining their regular load and operating hours. [ABSTRACT FROM AUTHOR]
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- 2024
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11. Low Noise and Complexity Deep Learning Decoder for MIMO in image transmission for health System
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MOHAMMED, WALEED MAJEED, primary and UÇAN, Osman Nuri, additional
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- 2024
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12. Improved Performance and Cost Algorithm for Scheduling IoT Tasks in Fog–Cloud Environment Using Gray Wolf Optimization Algorithm
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Alsamarai, Naseem Adnan, primary and Uçan, Osman Nuri, additional
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- 2024
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13. Detection of Malicious SQL Injections Using SVM and KNN Algorithms
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Hacham, Sameer Abduljabbar Kadhim, primary and UÇan, Osman Nuri, additional
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- 2023
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14. Cyber Security Method for Phishing and Malicious Link Detection in Social Meda Using Data Mining Techniques
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Saadallah, Hadeel Basil, primary and Uçan, Osman Nuri, additional
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- 2023
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15. Fault Diagnosis in Overhead Power Line Using Deep Belief Network
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Abed, Qader Farhan, primary and UÇAn, Osman Nuri, additional
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- 2023
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16. Achieving Optical Fiber Transmission of Over 60 W of Electrical Power and Optical Data
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Al-Hadeethi, Alaa Tareq, primary, Uçan, Osman Nuri, additional, and Mohammed, Alaa Hamid, additional
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- 2023
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17. Pseudopapilledema Diagnosis Based on a Hybrid Approach Using Deep Transfer Learning
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Al-azzawi, Athar, primary, Al-jumaili, Saif, additional, Duru, Adil Deniz, additional, Bayat, Oguz, additional, Kurnaz, Sefer, additional, and Uçan, Osman Nuri, additional
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- 2023
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18. Preparation of ZnO Thin Film for Gas Sensors Using Spray Pyrolysis Technique
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Abdulhadi, Mithal O., primary, Al-Jumaili, Saif, additional, and Uçan, Osman Nuri, additional
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- 2023
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19. Evaluation of deep transfer learning methodologies on the covid-19 radiographic chest images
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Al-Azzawi, Athar, Al-Jumaili, Saif, Duru, Adil Deniz, Duru, Dilek Göksel, Uçan, Osman Nuri, Al-Azzawi A., Al-Jumaili S., DURU A. D., Duru D. G., Uçan O. N., Al-Azzawi, Athar, Al-Jumaili, Saif, and Uçan, Osman Nuri
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CT scan ,Sinyal İşleme ,Mühendislik ,ENGINEERING ,X-ray ,Deep Learning ,Information Systems, Communication and Control Engineering ,deep transfer learning ,CT Scan ,Electrical and Electronic Engineering ,Engineering, Computing & Technology (ENG) ,ENGINEERING, ELECTRICAL & ELECTRONIC ,Elektrik ve Elektronik Mühendisliği ,deep learning ,Mühendislik, Bilişim ve Teknoloji (ENG) ,Classification ,Deep Transfer Learning ,Fizik Bilimleri ,classification ,Signal Processing ,Physical Sciences ,X-Ray ,Engineering and Technology ,MÜHENDİSLİK, ELEKTRİK VE ELEKTRONİK ,Mühendislik ve Teknoloji ,Bilgi Sistemleri, Haberleşme ve Kontrol Mühendisliği ,CNN - Abstract
In 2019, the world had been attacked with a severe situation by the new version of the SARSCOV- 2 virus, which is later called COVID-19. One can use artificial intelligence techniques to reduce time consumption and find safe solutions that have the ability to handle huge amounts of data. However, in this article, we investigated the classification performance of eight deep transfer learning methodologies involved (GoogleNet, AlexNet, VGG16, MobileNet-V2, ResNet50, DenseNet201, ResNet18, and Xception). For this purpose, we applied two types of radiographs (X-ray and CT scan) datasets with two different classes: non-COVID and COVID-19. The models are assessed by using seven types of evaluation metrics, including accuracy, sensitivity, specificity, negative predictive value (NPV), F1- score, and Matthew\"s correlation coefficient (MCC). The accuracy achieved by the X-ray was 99.3%, and the evaluation metrics that were measured above were (98.8%, 99.6%, 99.6%, 99.0%, 99.2%, and 98.5%), respectively. Meanwhile, the CT scan model classified the images without error. Our results showed a remarkable achievement compared with the most recent papers published in the literature. To conclude, throughout this study, it has been shown that the perfect classification of the radiographic lung images affected by COVID- 19.
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- 2023
20. Investigation of epileptic seizure signatures classification in EEG using supervised machine learning algorithms
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Al-Jumaili, Saif, Duru, Adil Deniz, Ibrahim, Abdullahi Abdu, Uçan, Osman Nuri, Aljumaili S., Duru A. D., Ibrahim A. A., Uçan O. N., Al-Jumaili, Saif, Ibrahim, Abdullahi Abdu, and Uçan, Osman Nuri
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Fast Fourier Transform (FFT) ,K-Nearest Neighbor (KNN) ,electroencephalogram (EEG) ,classification epileptic seizure ,Mühendislik, Bilişim ve Teknoloji (ENG) ,Sağlık Bilimleri ,Electroencephalogram (EEG) ,Clinical Medicine (MED) ,K-nearest neighbor (KNN) ,Health Sciences ,Engineering and Technology ,Klinik Tıp (MED) ,support vector machine (SVM) ,Mühendislik ve Teknoloji ,Electrical and Electronic Engineering ,Engineering, Computing & Technology (ENG) ,Support Vector Machine (SVM) ,fast fourier transform (FFT) ,Classification Epileptic Seizure - Abstract
Epilepsy is one of the earnest neurological disorders that require further social attention. Based on the International League Against Epilepsy (ILAE), which classifies the epilepsy term as a number of several seizures that occur in the brain. Electroencephalography (EEG) is considered our brain window to the electrical activity. It is a significant device used for diagnosing multiple brain disorders such as Epilepsy. Moreover, this study used data from Temple University Hospital Seizure Corpus (TUH), which represents an accurate description of the clinical cases for five types of epileptic seizures. Initially, to extract information from EEG signals, three types of feature extraction have been used namely Fast Fourier Transform, Entropy, and Approximate Entropy. Due to the high degree of variance of EEG signals, we implemented a band-pass filter to divide the signals into sub-bands called delta rhythm (0.1 - 4Hz), theta rhythm (5 -9Hz), alpha rhythm (10 - 14Hz), beta rhythm (15- 31Hz), and gamma rhythm (32-100). The feature extraction outcome underwent normalization techniques and was used as input for the classifiers. Support Vector Machine (SVM), Decision Tree (DT), Naive Bayes (NB), and K-Nearest Neighbor (KNN) classifier have implemented in order to classify (1) second epoch length window. In the first scenario, we applied the FFT features to the classifiers, the results showed that SVM obtained the highest value compared to the other classifiers with 96% accuracy, whereas KNN was 92% and the DT and NB were 76% and 67%, respectively. The second scenario was applying entropy features to the classifiers, the results of classification were 91% for SVM and 88% for KNN, while the DT and NB were 76% and 67%, respectively. The last scenario was ApEn, which shows that SVM still gains the highest value, which was 83%, and 76% for KNN, where the DT and NB were 65% and 69%, respectively. From the aforementioned results, we deduced that SVM achieved the best accuracy when applied with the three feature extractions.
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- 2023
21. Evaluation of Deep Transfer Learning Methodologies on the COVID-19 Radiographic Chest Images
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Al-azzawi, Athar, primary, Al-jumaili, Saif, additional, Duru, Adil Deniz, additional, Duru, Dilek Göksel, additional, and Uçan, Osman Nuri, additional
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- 2023
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22. Investigation of Epileptic Seizure Signatures Classification in EEG Using Supervised Machine Learning Algorithms
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Al-jumaili, Saif, primary, Duru, Adil Deniz, additional, Ibrahim, Abdullahi Abdu, additional, and Uçan, Osman Nuri, additional
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- 2023
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23. Fully Automatic Liver and Tumor Segmentation from CT Image Using an AIM-Unet
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Özcan, Fırat, primary, Uçan, Osman Nuri, additional, Karaçam, Songül, additional, and Tunçman, Duygu, additional
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- 2023
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24. Dynamic Quota Calculation System (DQCS)
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Çelenk, Ulaş, primary, Ertuğrul, Duygu Çelik, additional, Zontul, Metin, additional, Elçi, Atilla, additional, and Uçan, Osman Nuri, additional
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- 2018
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25. Providing scalability and privacy for smart contract in the healthcare system
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Al-mutar, Firas H.N., Uçan, Osman Nuri, Ibrahim, Abdullahi Abdu, Al-mutar, Firas H.N., Uçan, Osman Nuri, and Ibrahim, Abdullahi Abdu
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Blockchain ,Smart Contract ,Healthcare ,Electrical and Electronic Engineering ,Hsms ,Atomic and Molecular Physics, and Optics ,Zokrates ,Electronic, Optical and Magnetic Materials - Abstract
As the healthcare industry evolved, it became an integral participant in providing services. In recent years, remote observation services have grown increasingly important for patients. In cases where patients are not physically present in clinics or hospitals, healthcare providers produce observations systems that diagnose and prescribe treatment. In/on patients' bodies, sensors are installed. Data can be exchanged wirelessly between healthcare systems. As a result of the implementation of blockchain-based characteristics (e.g. distributed ledger, decentralized storage, and authentication), healthcare systems can be enhanced. Accordingly, smart contracts are applied for the achievement of more authentication and sharing of records, and requirements for participants automatically. As the number of users or other components increases, blockchains and smart contracts should be able to provide quality service. Technically, smart contracts using blockchains have several challenges that are important, such as scalability, enhanced security, and optimal performance. There is still a question about the scalability of blockchain as there is a significant amount of computational power needed to scale up with a high number of participants in healthcare systems. In this paper, Hierarchical State Machines (HSMs) and ZoKrates are used to lower the consumption gas and the scalability of blockchain with smart contracts.
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- 2022
26. Classification of Covid-19 Effected CT Images using a Hybrid Approach Based on Deep Transfer Learning and Machine Learning
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Al-jumaili, Saif, primary, Duru, Dilek Göksel, additional, Ucan, Bengisu, additional, Uçan, Osman Nuri, additional, and Duru, Adil Deniz, additional
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- 2022
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27. Finite Tessellation in Digital Image: Comparison of Square and Tetrakis Square Forms
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SAN, Soner, ŞAHİNER, Hülya, UÇAN, Osman Nuri, and TEMEL, Baybora
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Social ,Digital Image ,Dijital Geometry ,Tessellation ,Tetrakis Square Tiling ,Sosyal ,Dijital Görüntü ,Dijital Geometri ,Mozaikleme ,Tetrakis Kare Dizilimi - Abstract
Tarihte sonlu geometrik dizilimle oluşturulan erken dönem görüntü örgüsü örnekleri; mozaik sanatı, yer karo döşemeleri ve dokuma tekniklerinde görülmektedir. Özellikle 19. yüzyılın ilk yarısında Joseph Marie Jacquard’ın dokuma tezgahlarında şablon kartları kullanması, bilgisayar teknolojilerinin sayısal altyapısını ve dijital görüntünün temelini oluşturmuştur. Günümüzde dijital görüntü; iki boyutlu düzlemde (x, y) kare forma sahip noktaların (pixel) sonlu dizilimi ile oluşturulmaktadır. Bu sonlu mozaikleme dijital geometride raster görüntüyü oluşturmakta ve düşük sayıdaki dizilimlerde (resolution) geometrik kırılmalara neden olarak görüntünün nesnel bütünlüğünü bozmaktadır.Bu bilgiler ışığında, dijital geometride kare form ile Öklidyen yarı düzenli mozaikler grubunda yer alan kesik kare dizilimin (truncated quadrille) çift-tekdüze türevi olan tetrakis kare (4.8.8) formun (kisquadrille) oluşturduğu görüntü örgüsünde nitel ve nicel farklılıkların karşılaştırılması bu araştırmanın konusunu oluşturmaktadır., Examples of early image weaves created with finite geometric sequences in history; It is seen in mosaic art, floor tiles and weaving techniques. Especially in the first half of the 19th century, Joseph Marie Jacquard's use of template cards in weaving looms formed the basis of the digital infrastructure and digital image of computer technologies. Today, digital image; It is formed by the finite array of square-shaped points (pixels) in the two-dimensional plane (x, y). This finite mosaicing creates a raster image in digital geometry and causes geometric breaks in low number of sequences (resolution) and disrupts the objective integrity of the image.In the light of this information; The subject of this research is to compare the qualitative and quantitative differences in the image pattern formed by the "truncated quadrille" double-uniform derivative of the square form and the "truncated quadrille" of the Euclidean semi-regular mosaics group in digital geometry, that is, the "kisquadrille" formed by the tetrakis square "4.8.8" form.
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- 2022
28. Bulanık mantık ve IOT kullanarak hibrit akıllı şebekeler için verimli izleme ve kontrol sistemi
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Alzubaidi, Teiseer, Uçan, Osman Nuri, Alzubaidi, Teiseer, and Uçan, Osman Nuri
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Fuzzy Logic ,Solar Energy ,PV ,Bulanık Mantık ,Akıllı Izgara ,Smart Grid ,Güneş Enerjisi - Abstract
Smart grids are electric grids that are composed of multiple power sources and devices connected to each other to provide better reliability in power generation and power management, modern developments of the smart grid aim at either improving the control of power sources and loads connected to the smart grid by developing a specialized software/hardware, or by improving the communication between the components of the smart grid and the central control. In this paper we aim at improving both sides of the smart grid system (communication and control), we propose a fuzzy logic based controller for renewable energy and fossil fuel sources in a smart grid and an internet of things based monitoring system which oversees the state of the smart grid, faults that occur in the smart grid , and how the fuzzy controller overcomes those faults, all in which provide an extra layer of support to the smart grid. Akıllı şebekeler, güç üretimi ve güç yönetiminde daha iyi güvenilirlik sağlamak için birbirine bağlı birden fazla güç kaynağı ve cihazdan oluşan elektrik şebekeleridir; akıllı şebekenin modern gelişmeleri, güç kaynaklarının kontrolünü ve akıllıya bağlı yükleri kontrol etmeyi amaçlamaktadır. özel bir yazılım / donanım geliştirerek veya akıllı şebekenin bileşenleri ile merkezi kontrol arasındaki iletişimi geliştirerek. Bu makalede akıllı şebeke sisteminin (iletişim ve kontrol) her iki tarafını da geliştirmeyi hedefliyoruz, akıllı bir şebekede yenilenebilir enerji ve fosil yakıt kaynakları ve devleti denetleyen şeylere dayalı bir izleme sistemi için bulanık mantık tabanlı bir kontrolör öneriyoruz akıllı şebekeye, akıllı şebekede meydana gelen arızalara ve bulanık denetleyicinin bu hataların üstesinden nasıl geldiği, bunların hepsi de akıllı şebekeye ekstra destek katmanı sağlar.
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- 2020
29. Sinir Ağları ile Desen Tanıma
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AHMED, ODAY, BAYAT, Oğuz, UÇAN, Osman Nuri, Uçan, Osman Nuri, and Bayat, Oğuz
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Computer Science, Artifical Intelligence ,Pattern recognition,Neural network,Kohonen,Self-Organized map,Classification ,Bilgisayar Bilimleri, Yapay Zeka ,Self-Organized Map ,Sinir Ağı ,Öz-Organize Harita ,Desen tanıma,Sinir ağı,Kohonen,Öz-Organize harita,Sınıflandırma ,Desen Tanıma ,Neural Network ,Sınıflandırma ,Pattern Recognition ,Classification ,Kohonen - Abstract
Due to its various applications, such as security systems, medical systems, entertainment, etc., facerecognition has also been identified as one of the main research topics. The preferred method of humanidentification is face recognition: natural, robust and non-intrusive. A wide range of systems require reliablepersonal identification schemes to either confirm or determine the identity of a requester. The purpose ofthese schemes is to ensure that only a legitimate user and no one else accesses the rendered services. Forexample, secure access to buildings, computer systems, laptops, mobile phone and ATMs is included. Thesesystems are vulnerable to an impostor’s will in the absence of robust personal recognition systems. This article hasdeveloped and shown the human face identification system using artificial neural networks, which reflects thatthe face recognition rate for 40 individuals shows results for 400 frames in the AT&T database at 85.5 percent, Güvenlik sistemleri, tıbbi sistemler, eğlence vb. Çeşitli uygulamaları nedeniyle yüz tanıma da ana araştırmakonularından biri olarak tanımlanmıştır. Tercih edilen insan tanımlama yöntemi yüz tanıma yöntemidir: doğal,sağlam ve müdahaleci olmayan. Çok çeşitli sistemler, talep edenin kimliğini onaylamak veya belirlemek içingüvenilir kişisel tanımlama şemaları gerektirir. Bu programların amacı, yalnızca meşru bir kullanıcının ve başkahiç kimsenin sunulan hizmetlere erişmemesini sağlamaktır. Örneğin, binalara, bilgisayar sistemlerine, dizüstübilgisayarlara, cep telefonuna ve ATM’lere güvenli erişim dahildir. Bu sistemler, sağlam kişisel tanıma sistemleriyokluğunda bir sahtekârın iradesine karşı savunmasızdır. Bu makale, yapay sinir ağları kullanan insan yüztanıma sistemini geliştirdi ve gösterdi; bu, 40 birey için yüz tanıma oranının, AT&T veritabanında yüzde 85,5 ile400 kare için sonuç gösterdiğini gösteriyor.
- Published
- 2020
30. Yapay zeka kullanarak karmaşık bir ortamda robotları hareket ettirme
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Yaseen, Omar Mahmood, Uçan, Osman Nuri, Bayat, Oğuz, Yaseen, Omar Mahmood, Uçan, Osman Nuri, and Bayat, Oğuz
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Light Detection and Ranging ,Takviye Öğrenimi ,Robotik ,Işık Tespiti Ve Değişimi ,Robotics ,Yapay Sinir Ağları ,Reinforcement Learning ,Artificial Neural Networks - Abstract
Robots are being used to automate several tasks in different environments. Some of these applications require the robots to be able to navigate in complex environments and avoid obstacles to reach their destinations. According to the dynamic nature of these environments, Artificial Intelligence (AI) is being used to allow robots handle continuously-changing environments. The existing techniques require intensive processing power and energy sources, which limits their employment is many applications. Thus, a new method is proposed in this study to take control of the robot when a collision is predicted. Different representations of the environment are used, so that, historical information can be provided efficiently. However, the results show that the use of the entire batch has better performance with similar complexity. The proposed method has been able to reduce the number of collision and increasing the speed of the robot during the navigation. Robotlar, farklı ortamlardaki çeşitli görevleri otomatikleştirmek için kullanılıyor. Bu uygulamalardan bazıları, robotların karmaşık ortamlarda gezinmesini ve hedeflerine ulaşmak için engellerden kaçınmasını gerektirir. Bu ortamların dinamik doğasına göre, robotların sürekli değişen ortamları işlemesine izin vermek için Yapay Zeka (AI) kullanılmaktadır. Mevcut teknikler yoğun işleme gücü ve enerji kaynakları gerektirir, bu da istihdamlarını sınırlayan birçok uygulamadır. Bu nedenle, bu çalışmada bir çarpışma tahmin edildiğinde robotun kontrolünü ele almak için yeni bir yöntem önerilmiştir. Çevrenin farklı gösterimleri kullanılır, böylece tarihsel bilgi verimli bir şekilde sağlanabilir. Ancak sonuçlar, tüm partinin kullanımının benzer karmaşıklıkla daha iyi performansa sahip olduğunu göstermektedir. Önerilen yöntem, navigasyon sırasında çarpışma sayısını azaltabilir ve robotun hızını artırabilir.
- Published
- 2020
31. Beyin epilepsi tespitini kullanarak doğruluk geliştirme makina öğrenme algoritmaları
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Al-Dahhan, Rand Natiq, Uçan, Osman Nuri, Al-Dahhan, Rand Natiq, and Uçan, Osman Nuri
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Naive Bayes ,Random Forest ,KNN ,Naïve Bays ,FFNN ,LSTM ,Rastgele Orman - Abstract
Data has gained vital role in science and engineering applications; the proper data analysis has made it possible to boost the economical worthiness of those applications. Machine learning tools are used to classify the big data in order to discover the hidden patterns in them. That may lead to noteworthy advantages that related to future prediction of the data. The resultant information can be used to enhance the practical systems in such way only the profitable thing can be come on then. In other way, it helps to prevent any unpleasant occurrence that may harm the company or the organization. A brain epilepsy disease prediction system is implemented using four different algorithms namely: Naive Bayes algorithm, K-Nearest Neighbours algorithm, Random Forest algorithm and Long Short Term Memory Neural Network. The performance metrics are also initiate in order to evaluate the difference in prediction performance of the four tools. The accuracy of prediction the disease was recorded more likely 33.035, 95, 61.195 and 96.79 for the Naïve Bays, Random Forest, K-Nearest Neighbour and Long Short Term Neural Network. Bilim ve mühendislik uygulamalarında veriler hayati bir rol oynamıştır; doğru veri analizi, bu uygulamaların ekonomik değerini artırır. Makine öğrenimi araçları büyük verileri sınıflandırmak için kullanılır ve veriler içindeki gizli kalıpların bulunmasını sağlar. Bu gelecek tahmini ile ilgili önemli avantajları sağlayabilir. Sonuçta elde edilen bilgiler pratik sistemleri sadece karlı olan şeyleri geliştirmek için de kullanılabilir. Başka bir şekilde bakıldığında, şirkete veya kuruluşa zarar verebilecek hoş olmayan olayların önlenmesine de yardımcı olur. Beyin epilepsi hastalığı tahmin sistemi dört farklı algoritma kullanılarak uygulanır: Naive Bayes algoritması, K-en yakın komşular algoritması, rastgele orman algoritması ve uzun kısa süreli bellek sinir ağı. Performans ölçümleri de dört aracın tahmin performansındaki farkı değerlendirmek için başlatılır. Tahmin doğruluğu, bu dört yöntem için sırasıyla 33,035, 95, 61,195 ve 96,79 olarak kaydedildi.
- Published
- 2020
32. Computational intelligence algorithms to handle dimensionality reduction for enhancing intrusion detection system
- Author
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Alsaadi, Husam Ibrahiem, Almuttairi, Rafah M., Bayat, Oğuz, Uçan, Osman Nuri, Uçan, Osman Nuri, Bayat, Oğuz, and Alsaadi, Husam Ibrahiem
- Subjects
Computational Intelligence Algorithm ,ComputingMethodologies_PATTERNRECOGNITION ,Support Vector Machine ,K-Nearest Neighbors ,Classification Algorithms ,Intrusion Detection System - Abstract
WOS:000523607200009 In this paper, propose to use computational intelligence models to improve intrusion detection system, the computational intelligence algorithms are used as preprocessing steps for selecting most significant features from network data. Two computational intelligence algorithms, namely Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) are implemented to generate subset of relevant features. The computational intelligence approaches have been applied to optimize the classification of algorithms. The most significant features obtained from computational intelligence is fed into the classification algorithm. Novelty of this presents research of use computational intelligence algorithms namely Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) for handling dimensionality reduction. The dimensionality reduction is obstructed time processing of classification algorithms. Three classification algorithms namely K-Nearest Neighbors (KNN), Support Vector Machine (SVM) and Naive Bayes (NB) are implemented for intrusion detection system. Benchmark datasets, namely, KDD cup and NSL-KDD datasets are used to demonstrate and validate the performance of the proposed model for intrusion detection. From the empirical results, it is observed that the classification algorithm has improved the intrusion detection system with using computational intelligence algorithms. A comparative result analysis between the proposed model and different existing models is presented. It is concluded that the proposed model has outperformed of conventional models.
- Published
- 2020
33. Laboratuvar lazer sistemi için düşük maliyetli yüksek hızlı veri toplama kartı
- Author
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Uçan, Osman Nuri, Bayat, Oğuz, Abdulhakeem, Bara Saad, Uçan, Osman Nuri, Bayat, Oğuz, and Abdulhakeem, Bara Saad
- Subjects
Data Acquisition ,Microcontroller ,Mikrokontrolör ,Lazer Sistemi Kontrolü ,Veri Toplama ,Arduino ,Laser System Controller ,DAQ - Abstract
The Data Acquisition (DAQ) is the process of taking a real-world signal, like a voltage, towards the computer, for analysis, processing, storing or other data manipulation. The Computer DAQ systems utilized in laboratory research, manufacturing automation and in measurement and test. This work is aiming to implement and develop an accurate compact, low-cost DAQ system for laser systems that can be run and controlled by using an interface board connected to Computer and the user interface program. The interfacing board is based on use a low-cost microcontroller where Arduino Uno has been used in that purpose and the GUI (graphic user interface) program has been developed by using LabVIEW. The proposed DAQ system can control and acquiring DATA from laboratory laser system, which offer several functions like controls the intensity of laser, control the number of pulses during period of time, etc. The testing result show that the proposed system can control and acquiring data easily and effectively that can be utilized to controls different laser systems with variety of applications. Veri Toplama (DAQ), bilgisayara voltaj gibi gerçek bir sinyali alma işlemidir ve analiz, işleme, depolama veya diğer veri işleme işlemleri için kullanılabilir. Laboratuvarda kullanılan Bilgisayar DAQ sistemleri; araştırma, üretim otomasyonu ve ölçüm ve testte kullanılabilir. Bu çalışma lazer sistemleri için hassas, kompakt, düşük maliyetli bir DAQ sistemi geliştirmek için geliştirilmiştir. Arayüz kartı, bilgisayara ve kullanıcı arayüz programına bağlıdır. Arduino Uno’nun bu amaçla kullanıldığı düşük maliyetli bir mikro denetleyici ve GUI (grafik kullanıcı arayüzü) programı LabVIEW kullanılarak geliştirilmiştir. Önerilen DAQ sistemi kontrol edebilir ve lazerin yoğunluğunu kontrol etmek gibi çeşitli işlevler sunan laboratuvar lazer sisteminden veri alınması, zaman aralığı vb. boyunca ölçebilir ve çeşitli uygulamalar için kullanılabilir.
- Published
- 2020
34. Decoding of quadrature partial response- trellis coded signals (QPR-TCM) in the presence of intersymbol interference and noise
- Author
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Uçan, Osman Nuri, Aygölü, Ümit, Panayirci, Erdal, Goos, Gerhard, editor, Hartmanis, Juris, editor, Mattson, Harold F., editor, Mora, Teo, editor, and Rao, T. R. N., editor
- Published
- 1991
- Full Text
- View/download PDF
35. Bulut doğrulama temelli yüz tanıma tekniği
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Alrahlawee, Anfal Thaer, Duru, Adil Deniz, Bayat, Oğuz, Uçan, Osman Nuri, Alrahlawee, Anfal Thaer, Bayat, Oğuz, and Uçan, Osman Nuri
- Subjects
Histogram Equalization ,Bulut Bilgi İşlem ,Histogram Eşitleme ,Viola Ve Jones Algoritması ,Doğrusal Diskriminant Analizi ,Face Detection ,Cloud Computing ,Linear Discriminant Analysis ,Viola And Jones Algorithm ,Yüz Algılama - Abstract
The recognition process for a single face can be completed in relatively less time. However, large scale implementation that involves recognition of several faces would make the procedure a lengthy one. Cloud computing service has been employed in this paper to provide a solution for scalability, where cloud computing increases the essential resources when larger data is to be processed. The programming and training of the developed system has been done in order to detect and recognize faces through cloud computing. Viola and Jones algorithm is employed for detecting faces that used integral image, cascaded classifiers, five sorts of Haar-like features, and Adaboost learning method. Face recognition has been done using Linear Discriminant Analysis (LDA), as it is more efficient compared to Principal Component Analysis (PCA) algorithm. Several MUCT database images have been used for assessing the performance of system. Tek bir yüz için tanıma süreci nispeten daha kısa sürede tamamlanabilir. Bununla birlikte, birkaç yüzün tanınmasını içeren büyük ölçekli uygulama, prosedürü uzun bir hale getirecektir. Bulut bilişim hizmeti, daha fazla veri işleneceği zaman bulut bilişimin temel kaynakları artırdığı bir ölçeklenebilirlik çözümü sağlaması için bu araştırmada kullanılmıştır. Geliştirilen sistemin programlanması ve eğitimi, bulut bilişim yoluyla yüzleri tespit etmek ve tanımak için yapılmıştır. İntegral görüntü, basamaklı sınıflandırıcılar, beş çeşit Haar benzeri özellikler ve Adaboost öğrenme yöntemi kullanılan yüzleri tespit etmek için Viola ve Jones algoritması kullanılır. Yüz tanıma, Temel Bileşen Analizi (PCA) algoritmasına göre daha verimli olduğu için Doğrusal Diskriminant Analizi (LDA) kullanılarak yapılmıştır. Sistemin performansını değerlendirmek için çeşitli MUCT veritabanı görüntüleri kullanılmıştır.
- Published
- 2019
36. 5 GHz Wi-Fi effects on Escherichia coli, Caenorhabditis Elegans and human neuroblastoma cells
- Author
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DİNÇ, Bircan, primary, ILYAS, Muhammad, additional, KAYGUSUZ, Hakan, additional, and UÇAN, Osman Nuri, additional
- Published
- 2021
- Full Text
- View/download PDF
37. An Expert System to Predict Eye Disorder Using Deep Convolutional Neural Network
- Author
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AHMED, Moahmmed Rashid, primary, AHMED, Saadaldeen Rashid, additional, DURU, Adil Deniz, additional, UÇAN, Osman Nuri, additional, and BAYAT, Oğuz, additional
- Published
- 2021
- Full Text
- View/download PDF
38. İletişim ağları üzerinden uyarlanabilir video iletimi
- Author
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Göse, Ersin, Uçan, Osman Nuri, Nafea, Ghaidq Nassr, Bayat, Oğuz, Nafea, Ghaidq Nassr, Uçan, Osman Nuri, and Bayat, Oğuz
- Subjects
HEVC ,AVC ,Kod Çözücü ,Bilgisayar Bilimleri, Donanım ve Mimari ,H264 ,Codec,Transcoder,AVC,HEVC,H.264 ,Computer Science, Hardware and Architecture ,Transcoder ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Kod çözücü,Kodlayıcı,AVC,HEVC,H.264 ,Data_CODINGANDINFORMATIONTHEORY ,Kodlayıcı ,Codec - Abstract
ÖzBu makalenin amacı video bithızını düşürme ve yüksek çözünürlüklü video dosyasının boyutunu uygun haldetutabilmektir. Bu işlem yeni nesil bir İleri Video Kodlayıcı ile yapılır. Bu tür bir işlem, tek düzeyli ya da çok düzeylikodlayıcılarla yapılabilir. Amaç, kod çevrimine ulaşılabilecek bir sürecin yürütülmesidir. Video sıkıştırması içinkullanılan kod çözücü H.264’tür. H.264 AVC’nin kodlanması için x264 kütüphanesi kullanılmıştır. Bithızı kontrolükodlayıcının içine yerleştirildiğinde, daha güvenilir ve iyileştirilmiş bir sisteme ulaşılır ve video kodlayıcınınçıkış oranı geçici bellekten sağlanan geri besleme ile sağlanır. QP, döngü uzunluğu gibi etkin parametreler,video kodlama sürecinde kullanılabilir. Deneme senaryolarında QCIF, CIF, HD gibi farklı biçimlerde videolarkullanılmıştır. Standartların uygulanması ve denenmesinde ise JM19 referans yazılımı kullanılmıştır., This paper is to minimize video bitrate and keeping the high resolution video file manageable. This processis achieved by using new generation of Advanced Video Coders (AVC). Such process can be done at onelevel encoder or multi levels of encoders by means of transcoding, where reformatting the content to bestreamed on channel is called transcoding. The goal is concerned of encoder processes that can be usedto achieve transcoding. The codec used for compression of video is H.264, a standard for providing highdefinition video at substantially low complicity and lower bit rates. The x264 Library is used for encodingH.264 AVC, undergirds some of the most profiles for broadcasting and streaming operations over wiredand wireless channels, including different applications. When a technique of bit-rate control is incorporatedwith the encoder, more reliable and qualified system for low bitrate video streaming over constant bit ratecommunication channel is achieved, where output rate of the video encoder is controlled by feedback basedon the buffer level. Where the most effective parameters such as skip frame, QP, cycle length (Gop), etc. areconfigured and it used as a rate control tools to test the streaming coded bit rate and the decoded videoquality. Testing scenarios use many different videos with QCIF, CIF, and HD formats encoded under mainprofile. JM19 reference software is used for implementing and testing the standards.
- Published
- 2018
39. Navigating Robots in a Complex Environment with Moving Objects Using Artificial Intelligence
- Author
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YASEEN, Omar, UÇAN, Osman Nuri, and BAYAT, Oğuz
- Subjects
Computer Science, Information System ,Bilgisayar Bilimleri, Bilgi Sistemleri ,Robotik,Yapay Sinir Ağları,Takviye Öğrenimi,Işık Tespiti ve Değişimi ,Robotics,Artificial Neural Networks,Reinforcement Learning,Light Detection and Ranging - Abstract
Robotlar, farklı ortamlardaki çeşitli görevleri otomatikleştirmek için kullanılıyor. Bu uygulamalardan bazıları, robotların karmaşık ortamlarda gezinmesini ve hedeflerine ulaşmak için engellerden kaçınmasını gerektirir. Bu ortamların dinamik doğasına göre, robotların sürekli değişen ortamları işlemesine izin vermek için Yapay Zeka (AI) kullanılmaktadır. Mevcut teknikler yoğun işleme gücü ve enerji kaynakları gerektirir, bu da istihdamlarını sınırlayan birçok uygulamadır. Bu nedenle, bu çalışmada bir çarpışma tahmin edildiğinde robotun kontrolünü ele almak için yeni bir yöntem önerilmiştir. Çevrenin farklı gösterimleri kullanılır, böylece tarihsel bilgi verimli bir şekilde sağlanabilir. Ancak sonuçlar, tüm partinin kullanımının benzer karmaşıklıkla daha iyi performansa sahip olduğunu göstermektedir. Önerilen yöntem, navigasyon sırasında çarpışma sayısını azaltabilir ve robotun hızını artırabilir., Robots are being used to automate several tasks in different environments. Some of these applications require the robots to be able to navigate in complex environments and avoid obstacles to reach their destinations. According to the dynamic nature of these environments, Artificial Intelligence (AI) is being used to allow robots handle continuously-changing environments. The existing techniques require intensive processing power and energy sources, which limits their employment is many applications. Thus, a new method is proposed in this study to take control of the robot when a collision is predicted. Different representations of the environment are used, so that, historical information can be provided efficiently. However, the results show that the use of the entire batch has better performance with similar complexity. The proposed method has been able to reduce the number of collision and increasing the speed of the robot during the navigation.
- Published
- 2020
40. Efficient Monitoring and Control System for Hybrid Smart Grids Using Fuzzy Logic and IOT
- Author
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ALZUBAİDİ, Teiseer and UÇAN, Osman Nuri
- Subjects
Engineering, Electrical and Electronic ,PV,solar energy,fuzzy logic,smart grid ,Mühendislik, Elektrik ve Elektronik - Abstract
Akıllı şebekeler, güç üretimi ve güç yönetiminde daha iyi güvenilirlik sağlamak için birbirine bağlı birden fazla güç kaynağı ve cihazdan oluşan elektrik şebekeleridir; akıllı şebekenin modern gelişmeleri, güç kaynaklarının kontrolünü ve akıllıya bağlı yükleri kontrol etmeyi amaçlamaktadır. özel bir yazılım / donanım geliştirerek veya akıllı şebekenin bileşenleri ile merkezi kontrol arasındaki iletişimi geliştirerek. Bu makalede akıllı şebeke sisteminin (iletişim ve kontrol) her iki tarafını da geliştirmeyi hedefliyoruz, akıllı bir şebekede yenilenebilir enerji ve fosil yakıt kaynakları ve devleti denetleyen şeylere dayalı bir izleme sistemi için bulanık mantık tabanlı bir kontrolör öneriyoruz akıllı şebekeye, akıllı şebekede meydana gelen arızalara ve bulanık denetleyicinin bu hataların üstesinden nasıl geldiği, bunların hepsi de akıllı şebekeye ekstra destek katmanı sağlar., Smart grids are electric grids that are composed of multiple power sources and devices connected to each other to provide better reliability in power generation and power management, modern developments of the smart grid aim at either improving the control of power sources and loads connected to the smart grid by developing a specialized software/hardware, or by improving the communication between the components of the smart grid and the central control. In this paper we aim at improving both sides of the smart grid system (communication and control), we propose a fuzzy logic based controller for renewable energy and fossil fuel sources in a smart grid and an internet of things based monitoring system which oversees the state of the smart grid, faults that occur in the smart grid , and how the fuzzy controller overcomes those faults, all in which provide an extra layer of support to the smart grid.
- Published
- 2020
41. Accuracy Enhancement of Brain Epilepsy Detection by Using of Machine Learning Algorithms
- Author
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AL-DAHHAN, Rand and UÇAN, Osman Nuri
- Subjects
Engineering, Electrical and Electronic ,LSTM,FFNN,Rastgele Orman,KNN,Naive Bayes ,LSTM,FFNN,Random Forest,KNN,Naïve Bays ,Mühendislik, Elektrik ve Elektronik - Abstract
Bilim ve mühendislik uygulamalarında veriler hayati bir rol oynamıştır; doğru veri analizi, bu uygulamaların ekonomik değerini artırır. Makine öğrenimi araçları büyük verileri sınıflandırmak için kullanılır ve veriler içindeki gizli kalıpların bulunmasını sağlar. Bu gelecek tahmini ile ilgili önemli avantajları sağlayabilir. Sonuçta elde edilen bilgiler pratik sistemleri sadece karlı olan şeyleri geliştirmek için de kullanılabilir. Başka bir şekilde bakıldığında, şirkete veya kuruluşa zarar verebilecek hoş olmayan olayların önlenmesine de yardımcı olur. Beyin epilepsi hastalığı tahmin sistemi dört farklı algoritma kullanılarak uygulanır: Naive Bayes algoritması, K-en yakın komşular algoritması, rastgele orman algoritması ve uzun kısa süreli bellek sinir ağı. Performans ölçümleri de dört aracın tahmin performansındaki farkı değerlendirmek için başlatılır. Tahmin doğruluğu, bu dört yöntem için sırasıyla 33,035, 95, 61,195 ve 96,79 olarak kaydedildi., Data has gained vital role in science and engineering applications; the proper data analysis has made it possible to boost the economical worthiness of those applications. Machine learning tools are used to classify the big data in order to discover the hidden patterns in them. That may lead to noteworthy advantages that related to future prediction of the data. The resultant information can be used to enhance the practical systems in such way only the profitable thing can be come on then. In other way, it helps to prevent any unpleasant occurrence that may harm the company or the organization. A brain epilepsy disease prediction system is implemented using four different algorithms namely: Naïve Bays algorithm, K-Nearest Neighbours algorithm, Random Forest algorithm and Long Short Term Memory Neural Network. The performance metrics are also initiate in order to evaluate the difference in prediction performance of the four tools. The accuracy of prediction the disease was recorded more likely 33.035, 95, 61.195 and 96.79 for the Naïve Bays, Random Forest, K-Nearest Neighbour and Long Short Term Neural Network.
- Published
- 2020
42. Wearable Detection Systems for Epileptic Seizure: A review
- Author
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Alwindawi, Alla Fikrat, primary, UÇAN, Osman Nuri, primary, and Morad, Ameer Hussein, primary
- Published
- 2020
- Full Text
- View/download PDF
43. A systematic mapping study on touch classification
- Author
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Fleh, Saad Q., Bayat, Oğuz, Al-Azawi, Saad, Uçan, Osman Nuri, Uçan, Osman Nuri, Bayat, Oğuz, and Fleh, Saad Q.
- Subjects
Systematic Mapping Studies ,Systematic Reviews ,Evidence Based on Human-Robot Interaction - Abstract
Al-Azawi, Saad/0000-0003-2475-3499 WOS:000432494400002 One of the basic interpersonal methods to communicate emotions is through touch. Social touch classification is one of the leading research which has great potential for more improvement. Social touch classification can be beneficial in the much scientific application such as robotics, human-robot interaction, etc.. Each person has the ability to interact with the environment and with other people via touch sensors that are speared over human soma. These touch sensors provide us with the important information about objects such as size, shape, position, surface and their movement. Therefore, the touch system plays the main role in human life from early days. The small gesture can express strong emotion, from the comforting experience of being touched by one's spouse, to the discomfort caused by a touch from a stranger. This paper presents and explains a systematic mapping study on social touch gesture recognition. From various digital libraries, 938 papers in total are collected. After applying three filters, 49 papers as primary studies related to the main topic are selected as listed in Appendix (A). The selected papers classified with respect to several facets. The results provide an overview of the existing relevant studies that are reported in the literature, highlight the focused areas and research gaps.
- Published
- 2018
44. Design and implementation of the pioneer-based bloot sharing system
- Author
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Çelik, Tayfun, Bayat, Oğuz, Duru, Adil Deniz, Uçan, Osman Nuri, Bayat, Oğuz, and Uçan, Osman Nuri
- Subjects
Kan Bağışı ,SPRING ,Kan Paylaşımı ,Blood Share ,Donör ,MySQL ,Donor ,Java ,AngularJS - Abstract
Bu tez çalışmasının amacı, kan ihtiyacı olan hasta ve sağlık kuruluşlarının kan gönüllüsü olan donörler ile aralarındaki haberleşmeyi bulut sunucular üzerinden sağlamaktır. En doğru ve hızlı şekilde gönüllülerin paylaştığı öncül bilgiler doğrultusunda onları yönlendirmektir. Uygulamanın bazı kısımları hali hazırda ürün olarak uygulama marketlerinde bulunmakta. Donör ve ihtiyaç sahiplerini eşleştiren mekanızmalar ve gönüllüyü teşvik eden oyunlaştırmalar mevcut. Bu proje kapsamında temel olarak gönüllüden mümkün oldukça bilgi edinilmeye çalışmak ve bağış sonrası takibinin yapılması da bir o kadar gönüllü motivasyonu için önemlidir. Bu iki odak noktası uygulamamızı benzer uygulamalardan farklı kılmaktadır. Uygulamanın geliştirmesinde en güncel ön yüz teknolojisi AngularJS ve en bilinen ve güvenli backend teknolojisi java programlama dili kullanılmıştır. Data yönetimi ise hem kullanımı kolay hemde güçlü olan MySQL database sunucusu kullanılmıştır. Uygulama çatısı olarak yönetimi kolay ve zengin modülü ile SPRING kullanıldı. The purpose of this thesis is to provide communication between donors who are blood donors of patients and health institutions who need blood through cloud servers. Directing them in the most accurate and fast way in the direction of the information that is shared by the volunteers. Some parts of the application are already present in the application markets as products. There are mechanisms to match the donor and the needy and volunteering games. Under the scope of this project, it is important for the volunteer to get as much information as possible and to follow up the donation for voluntary motivation. These two focal points make our application different from similar applications. The development of the application uses the most up-to-date front-end technology, AngularJS, and the wellknown and trusted backend technology java programming language. Data management is based on MySQL database server which is easy to use and powerful. SPRING is used as the management framework and it is rich and easy to manage.
- Published
- 2018
45. Çoklu yöntemlerle yenilenebilir enerjinin ekonomik dağıtım problemi
- Author
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Alfarras, Almuatasim M., Uçan, Osman Nuri, Bayat, Oğuz, Alfarras, Almuatasim M., Uçan, Osman Nuri, and Bayat, Oğuz
- Subjects
Optimization ,Optimizasyon ,Microgrid ,GOA ,Mikro şebeke ,Çekirge Optimizasyon Algoritması ,ELD. Algorithms ,Renewable Energy ,Planktonik Tunikap (Salp) sürü algoritması ,Ekonomik Yük Tevzi ,SSA ,Algoritmalar - Abstract
The successful design and operation of any power system is highly dependent on the economic load dispatch problem, therefore it can be considered as a major factor for any power system. Economic load dispatch (ELD) problem is the short-term determination of the best combination of generation while satisfying the demanded load with minimum cost under the system constrains. Generally, the cost function presented as quadratic function and solved by using different methods. For the past ten years, in order to solve (ELD) problems and to get the best possible results, many new methods have been developed such as meta-heuristic algorithms which are classified into two major classes (swarm intelligence and evolutionary) techniques. In this paper, two (swarm intelligence) optimization techniques are used, namely salp swarm algorithm (SSA) and grasshopper optimization algorithm (GOA) which are relatively new techniques. The (ELD) analytical method, simplified version of the analytical method and optimization techniques (SSA, GOA) applied to a microgrid considering the renewable energy sources (solar and wind) for different generation combination scenarios. At last, a comparison presented between the used methods in order to show the best result possible between them, in addition the result will show the effect of the renewable energy on the total generation cost. The proposed methods (analytical method, the simplified version of the analytical method and the salp swarm algorithm (SSA)) the same results for total average cost approximately (7292.64 $/h) but the execution time was better with the simplified version of the analytical method with time of (0.373 seconds), while the grasshopper optimization algorithm (GOA) showed a higher total cost average approximately (7292.94 $/h). Herhangi bir güç sisteminin başarılı bir şekilde tasarlanması ve çalıştırılması, büyük ölçüde ekonomik yük tevzi(dağıtım) problemine bağlıdır, bu nedenle herhangi bir güç sistemi için önemli bir faktör olarak düşünülebilir. Ekonomik yük tevzi(ELD) problemi, sistem sınırlaması altında istenen yükü en düşük maliyetle karşılarken, en iyi nesil/jenerasyon düzeninin kısa süreli olarak belirlenmesidir. Genel olarak, ikinci derece fonksiyon olarak belirtilen maliyet fonksiyonu, farklı yöntemler kullanılarak çözülmüştür. Geçtiğimiz on yıl boyunca, ekonomik yük tevzi sorunlarını çözmek ve en iyi sonuçları elde etmek için, iki ana kategoriye ayrılan (sürü zekâsı ve evrimsel) üst-sezgisel algoritmalar teknikleri gibi birçok yeni yöntem geliştirilmiştir. Bu çalışmada, yeni teknikler olan planktonik tunikap (salp) sürü algoritması (SSA) ve çekirge optimizasyon algoritması (GOA) olmak üzere iki (sürü zekası) optimizasyon teknikleri kullanılmıştır. Ekonomik Yük Tevzi (ELD) analitik yöntemi, farklı nesil kombinasyon/düzen senaryoları için yenilenebilir enerji kaynaklarını (güneş ve rüzgar) göz önünde bulundurarak bir mikro şebekeye uygulanan analitik yöntem ve optimizasyon tekniklerinin (SSA, GOA) basitleştirilmiş versiyonudur. Sonuç olarak, aralarındaki mümkün olan en iyi sonucu göstermek için kullanılan yöntemler arasında sunulan bir karşılaştırma, sonuca ek olarak, yenilenebilir enerjinin toplam üretim maliyetine etkisini de gösterecektir. Önerilen yöntemler (analitik yöntem, analitik yöntemin sadeleştirilmiş versiyonu ve salp sürüsü algoritması (SSA)) yaklaşık olarak ortalama toplam maliyet için aynı sonuçları (7292.64 $/h) ancak uygulama süresi analitik sadeleştirilmiş versiyonuyla daha iyi (0.373) ‘e dayanan yöntem, çekirge optimizasyon algoritması (GOA) yaklaşık olarak (7292.94 $ /h) daha yüksek bir toplam maliyet göstermiştir.
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- 2018
46. Formation control and obstacle avoidance in swarm robots
- Author
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Shallal, Abidaoun Hamdan, Uçan, Osman Nuri, Bayat, Oğuz, Bayat, Oğuz, Uçan, Osman Nuri, and Shallal, Abidaoun Hamdan
- Subjects
Intelligent Robots ,Swarm Robots ,Autonomy ,Navigation - Abstract
Alfarji, Abidaoun/0000-0003-0838-4240; WOS:000432494400017 This paper presents an approach for formation control and obstacle avoidance of a swarm robot (SR). Swarm robots are significant with their various tasks and range of applications, and also because they can identify and describe the challenges that need to be resolved in the real world. This work proposes a new formation control and an obstacle avoidance method for the dynamic region of swarm robot systems in order to prove SRs' ability to manage their formation by scaling and rotating while moving. Here, the Gradient Descent formula is adopted to update the range and the robot orientation vector of the SRs systems. Simulink MATLAB is also used to simulate the formation controller performance and the obstacle avoidance. The distributed formation control and the switching formation strategy for obstacle avoidance are illustrated in order to show the effectiveness of our proposed algorithm. We conclude that our method is easy to implement and achieve, not only the required distributed formation control and Obstacle Avoidance, but also to contribute to the usage in the tracking method.
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- 2018
47. Farklı sınıflandırma algoritmalarının uygulamaları
- Author
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Aburas, Amna Mohaned M., Mazher, Wamidh, Uçan, Osman Nuri, Bayat, Oğuz, Aburas, Amna Mohaned M., Mazher, Wamidh, Uçan, Osman Nuri, and Bayat, Oğuz
- Subjects
Spectral Method ,K-Ortalama ,Spektral Metod ,Eigenvector ,GUI ,Laplace ,K-Means ,Özdeğer Vektör ,Sınıflandırma ,Clustering - Abstract
Spectral clustering is developed for both normalized and unnormalized methods. However, selecting between the two methods is not established in the GUI (Graphical User Interface) yet . In this paper , we implement different clustering algorithms using GUI-MATLAB, then, the clustering by these three methods, is compared for similar pairs of datasets. Our model is employing such three different clustering methods which are spectral, hierarchical and density based methods, then employing different geometrical, multi-range, and multi-level similar datasets pairs of graph for clustering. As result, the above three clustering algorithms are experimented for different environments which are (geometrical, multi-range and multi-level). The simulation result shows the clustering of these pairs of geometrical datasets which are: Concentric circles, Semi-circles, and Aggregation. Accordingly, the spectral algorithm has superior clustering in case of big datasets more than 2000 pairs points and range more than 500 levels among datasets. Spektral kümeleme hem normalize hem de normalize edilmemiş yöntemler için geliştirilmiştir. Bununla birlikte, iki yöntem arasında seçim yapmak henüz GUI’de (Grafik Kullanıcı Arayüzü) kurulmamıştır. Bu yazıda, GUI-MATLAB kullanarak farklı kümeleme algoritmaları uyguluyoruz, daha sonra bu üç yöntemle kümeleme, benzer veri kümeleri çiftleri için karşılaştırılıyor. Modelimiz, spektral, hiyerarşik ve yoğunluk temelli yöntemler gibi üç farklı kümeleme yöntemini kullanmaktadır, daha sonra kümeleme için farklı geometrik, çok aralıklı ve çok düzeyli benzer veri kümeleri grafikler kullanmaktadır. Sonuç olarak, yukarıdaki üç kümeleme algoritması, (geometrik, çok menzilli ve çok seviyeli) farklı ortamlar için denenmiştir. Benzetim sonucu, bu çift geometrik veri kümelerinin kümelenmesini göstermektedir: Eş merkezli daireler, yarı daireler ve toplama. Buna göre, spektral algoritma, veri kümeleri arasında 2000’den fazla çift nokta ve 500’den fazla veri kümesindeki üstün kümeleme özelliklerine sahiptir.
- Published
- 2018
48. Gezgin satıcı probleminin çözümü için karınca koloni ve genetik algoritmalarının karşılaştırılması
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Alashheb, Waled Milad Abulsasem, Duru, Adil Deniz, Uçan, Osman Nuri, Bayat, Oğuz, Alashheb, Waled Milad Abulsasem, Uçan, Osman Nuri, and Bayat, Oğuz
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Optimization ,Problem Of Traveling Salesman ,Genetic Algorithm ,Optimization Of Ant Colony ,Eniyileştirme ,Genetik Algoritma ,Karınca Kolonisi Eniyileştirme ,Gezgin Satıcı Problem - Abstract
The Theory of computational complexity is an essential branch of study in the science of theoretical computing and mathematics. The resolution of Polynomial and Non Polynomial problems is one of the main problems that have open solutions, for which no famous efficient algorithm exist. The Problem of Traveling Salesman (TSP) is an example of these problems. Such a problem include, a count of specified cities must be visited by a traveling salesman where both start and end points will be the same city and getting a tour of all cities so that the complete distance or time is minimized will be the aim. The application of Optimization algorithms is one of the famous methods of the solution regarding to the TSP. These algorithms usually simulate the occurring phenomena in nature. Currently there exist several of such algorithms; for example, Genetic Algorithm (GA) and Optimization of Ant Colony (ACO). This paper aimed to compare two approaches, GA and ACO for solution of TSP. The results obtained from our experiments showed that the ACO is better than GA since it requires less execution time for solving the same problem. Polinom zamanda çözülebilecek (P) ve polinom zamanda doğrulanabilecek (NP) problemlerin bilinen etkin bir algoritmasının olmaması, hesaplamadaki karmaşıklık teorisinin teorik hesaplama ve matematiğin gerekli bir bilimsel çalışma kolu olmasını sağlamıştır. Gezgin satıcı problemi (GSP) bu tür problemlere örnektir. Bu problemde, satıcı tarafından belli sayıda şehirin ziyaret edilmesi istenir. Başlangıç ve bitiş şehri olarak aynı şehir ele alınır. GSP’nin amacı bir turu en az mesafe ve zamanda bitirmesidir. Evrimsel algoritmalar, GSP çözümü için kullanılan popüler yöntemlerdendir. Bu algoritmalar genelde doğada oluşan olayların benzeşimini temel almaktadır. Günümüzde, karınca kolonisi eniyileştirmesi (KKE) ve genetik algoritma (GA) bu tür algoritmalara örnektir. Bu tez kapsamında, GSP çözümü KKE ve GA ile gerçekleştirilerek sonuçları karşılaştırılmıştır. Deneyler sonucu elde edilen sonuçlar, KKE nun GA dan daha başarılı sonuç verdiği ve aynı problemin çözümü için daha az zaman kullandığı görülmüştür.
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- 2018
49. Reaktif güç kullanarak gerilim düzenlemesinde PV penetrasyon etkisi
- Author
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Noor, Ali Majid, Uçan, Osman Nuri, Bayat, Oğuz, Noor, Ali Majid, Uçan, Osman Nuri, and Bayat, Oğuz
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Reaktif Güç ,Yenilenebilir Enerji ,PSO ,Reactive Power ,Pends ,PV ,Renewable Energy ,Gerilim Regülasyonu ,Voltage Regulation - Abstract
Power Networks have two major aspects one is the Safety of the network and the other is its economic, reactive power is the very important element to serve these two aspects. To avoid unwanted power quality and high transmission loss we should locate reactive power in reasonable way in power network. Currently, in order to keep the network voltage in acceptable range and the real power loss as minimum we use dispatch of reactive power in traditional way. Since the reactive power has inequality constrains and quality constrains, so we can consider it as a nonlinear problem. In my thesis, I will use MATPOWER 5.1 toolbox, PSO algorithm and matlab program and applied it to find the optimum reactive power dispatch allocation. The algorithm PSO is a comprehensive optimization algorithm that is equipped with the best searching ability. Advantage (major ones) of the PSO is that when the function of the object is more complex the efficiency of PSO does not effect. Because MATLAB toolbox is a global program and our work focus on power flow so we will use MATPOWER 5.1 as open source to solve the problem. Since MATPOWER Toolbox is a power source so when any one use it, it will help him and the code will be very easy. Also we will use OpenDSS program via MATLAB COM to see PV effect. Then we will discuss the effect of PV residential penetration via MATLAB simulation using 24 house examples with PV and without PV penetrations. Our goal is to minimize power loss in transmission lines and to allocate the reactive power in optimal placement. IEEE 24 bus system is used to calculate the performance. Reaktif güç, güvenlik ağızlarının ve ekonomik yüzlerin güç şebekelerinin çalışması için kritik öneme sahiptir. Reaktif gücün mantıksız dağılımı, güç şebekelerinin güç kalitesini ciddi şekilde etkiler ve iletim kaybını arttırır. Halihazırda, reel güç kaybını en aza indirgemenin en ekonomik ve pratik yaklaşımı, reaktif güç dağıtım yöntemi kullanılarak kalmaktadır. Reaktif güç dağıtımı problemi doğrusal değildir ve eşitlik kısıtlamaları ve eşitsizlik kısıtlamaları vardır. Bu tezde, reaktif güç dağıtımı problemini çözmek için PSO algoritması ve MATPOWER 5.1 uygulanmıştır. PSO mükemmel arama yeteneği ile donatılmış küresel bir optimizasyon tekniğidir. PSO’nun en büyük avantajı, PSO’nun verimliliğinin nesnel işlevin karmaşıklığına daha az duyarlı olmasıdır. MATPOWER 5.1, güç akışı problemlerini çözmeye odaklanan açık kaynak MATLAB kodudur. MATPOWER’ın faydası, kodunun kolayca kullanılması ve değiştirilebilmesidir
- Published
- 2018
50. Evaluation of face recognition techniques using 2nd order derivative and new feature extraction method based on linear regression slope
- Author
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Alazzawi, Abdulbasit, Uçan, Osman Nuri, Bayat, Oğuz, Uçan, Osman Nuri, Bayat, Oğuz, and Alazzawi, Abdulbasit
- Subjects
PCA ,ComputingMethodologies_PATTERNRECOGNITION ,Computer Science::Computer Vision and Pattern Recognition ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Neural Network ,SLP ,ANN ,Face Recognition - Abstract
WOS:000432494400023 Face recognition system has been widely utilized for various sensitive applications such as Airport gates, special monitoring, and tracking system. The performance of most face recognition systems would significantly decrease if there were several variations in the illumination of dataset images. In this paper the proposed a new algorithm based on a combination of edge detection operators, features extractors and artificial neural network ANN as a classifier. The Second based on Laplacian comprise Zero cross, Laplacian of gaussian LOG, and Canny edge detection filters. A segmentation process is used to segment each image to equaled size blocks treats face edge pixels precisely. A new features extractor technique based on Linear Regression Slope SLP with discrete wavelet transformation (DWT) and principle components analysis PCA used for features extraction. ANN used for the data set classification and all results obtained evaluated. We tried a combination of various techniques like (Zero cross, DWT, SLP-PCA, ANN),(LOG, DWT, SLP-PCA, ANN),(Canny, DWT, SLP-PCA, ANN). The proposed method is examined and evaluated with different face datasets using ANN classifier. The experimental results were displaying the superiority of the proposed algorithm over the algorithms that used the state-of-art techniques where the combinations (Zero cross, SLP, ANN) gained the best results and could outperform all the other algorithms.
- Published
- 2018
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