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As the corona virus can mutate and due to other scientific factor associated to it, experts believe that COVID-19 will remain with us for decades. Therefore, one has to keep social distancing measures. Accepting the pandemic situation, the paper presents a mechanism for detecting violations of social distancing using deep learning to estimate the distance between individuals to diminish the influence of COVID-19. The focus of this paper is to understand the effect of social distancing on the spread of COVID-19 by using YOLOv3 and Faster-RCNN and proposes IFRCNN (improved faster region – convolution neural network). The proposed method IFRCNN is checked on a live streaming video of pedestrians walking on the street. This paper keeps the live updates of the recorded video along with social distancing violation records on a location, so how many people in a location are maintaining social distancing. Updates will be stored in a cloud-based storage system and any organization or firm can get live updates of that location in their digital devices.

Healthcare analytics provide many benefits in healthcare dashboard systems. Healthcare datasets majorly contains categorical attributes. This paper proposed an optimized clustering for healthcare dataset named harmony search based categorical clustering (HSCC). The existing k-modes clustering algorithm is one of the well-known categorical data-clustering algorithm. Since the k-modes algorithm produces local optimal clusters. Generally, researchers use genetic algorithm (GA) based clustering algorithms to converge locally optimal solutions to global optimal solutions. GA has some deficiencies such as premature convergence with low speed. In this paper, harmony search (HS) optimization algorithm used to optimize clustering results. The result shows the proposed HSCC algorithm produced global optimized solution, unbiased and matured results. HSCC produces 98% accuracy for dental and 71% for lung cancer dataset. While GACC produces 95% and 65% accuracy for dental dataset and lung cancer dataset.

Microarray technology is a novel method to monitor the levels of expression of a huge number of genes simultaneously.this study aims at (1) identifying the most important genes in the molecular senescence of the hippocampus and retina, where both with accelerated neurological senescence (S10 and 8) models were obtainable. By using feature selection to reduce the size of high dimensional data. Hence, the process of gene selection is twofold; removing the irrelevant genes and selecting the informative genes, and (2) The determination of the study is to specify the association among these genes or pathways that would deliver insight into the mechanism for this phenotype which will be greater to the current imperfect state-of-the-art estimates. In this study, gene selection methods have been implemented, including Analysis of Variance (ANOVA). The results are showed that CNN model achieve 0.98 accuracy based on a subset of genes from ANOVA method. Thus, Genes subset selected is achieved a better accuracy at classification and a little time of processing.

ICMAS Conference Proceeding is the 3rd Edition of the College of Education, Mustansiriyah University Conferences. ICMAS involved Our Peer-Reviewed Papers that were reviewed and presented through the 3rd International Conference on Mathematics and Applied Sciences (ICMAS) held in the College of Education, Mustansiriyah University, Baghdad, Iraq, from 23 to 24 March 2022. ICMAS Aims to bring together all aspects and research works in a scientific platform to discuss the latest and new trends in topics covered under broad areas such as (but not limited to): Functional, Nodal, and Mathematical Analysis, Dynamic Systems, and Control Systems, Statistics and Operations Research, Numerical Analysis, Differential Equations and Optimization, Algebra, Topological Aspects, Plasma, and Theoretical Physics, Materials Physics, Materials Analysis, Characterization, Optics, Quantum Optics and Lasers, Mathematical Physics, Applied Physics, Statistical physics, Nonlinear systems, Networking, Communications, Image Processing, Data Security, Vacuum Science, Information Technology and Its Applications. The conference is co-published by Journal of Physics: Conference Series, ISSN: 1742-6588, 1742-6596. List of Conference Committees, Organizing Committee, Scientific Committee, International Committee, Conference Tracks, Invited Speakers, Organizing Institutions, Conference Proceeding of 1st Day (23 March 2022), Conference Sessions (Day 1: 23 March 2022), Conference Sessions (Day 2: 24 March 2022), Wishing to Participate with our Next Conference are available in the pdf

Ahmed J. Obaid1, Isam Asal Hasan2, Ali Taher Mohi2, Salah Albermany1, Souvik Pal3, Sandeep Kautish4 1 Faculty of Computer Science and Mathematics, University of Kufa, Najaf, Iraq. 2 College of Education, Mustansiriyah University, Baghdad, Iraq. 3 Global Institute of Management and Technology, West Bengal, India. 4 LBEF Campus Kathmandu Nepal (In collaboration with Asia Pacific university Malaysia). E-Mails: ahmedj.aljanaby@uokufa.edu.iq. ICPAS Conference Proceeding 2nd edition, Involved Our Peer Reviewed Papers that reviewed and presented through the 2nd International Conference on Physics and Applied Sciences (ICPAS) which held in College of Education, Mustansiriyah University, Baghdad, Iraq in 26-27 MAY, 2021. ICPAS Aims to bring together all aspects and research works in scientific platform to discussed the latest and new trends in topics covered under broad areas such as (but not limited to) Nuclear, plasma and theoretical physics, Materials physics, materials analysis and characterization, Optics, Quantum Optics and Lasers, Mathematical Physics, Applied Physics, Statistical physics and Nonlinear systems, Communications, Vacuum science, technology and applications. The conference is co-sponsored by Journal of Physics: Conference Series, ISSN: 1742-6588, 1742-6596. List of Conference Committees, all images are available in the pdf

One of the potential top-level goals for 5G heterogeneous networks may be intellectual and perfect network which modifies consumer preferences in a proactive manner in addition to needs of channel. Research provides an interdisciplinary approach to e-health, primarily concern BDA, and radio space management inside a various level fifth generation network in the company of massive data. The growing need for and usage of big data fuelled digital transformation. The research focuses on the effect of Big Data on digital technologies during the 5G era. To carry out digital transformation, three machine learning (ML) algorithms are identified. In addition to decision tree DT the other algorithms used for the classification are NB, LR. These algorithms run on the large data processing engine they work. These algorithms serve as an ensemble tool for examining old records of stroke outpatients (OPs) and body built IOT based sensors [19]. These readings are available as Big Data. In the model which has been proposed here, OP-Centric Network Optimization Framework was presented before evaluating the machine learning algorithm function and all appropriate steps to plan massive data. An ensemble method in the company of NB classification device, decision tree classification device, and logistic classification device was used in this analysis. These entire classification devices are highly controlled and managed classification device. This method is based on the OP data set and feeds the predicted stroke probabilities to an SV classifier.

Cloud infrastructure is a modern computing system in which pooled services are made available to users at various times depending on their demands. The process of distributing workload among computing system nodes is known as load balancing. Loads include things like CPU power; ram capacity, and network traffic. A well-balanced load avoids the situation when some nodes are fully loaded while others are inactive or not working. Where there are many tasks in a virtual machine (VM), these tasks are delegated to underutilize VMs in the same or a separate datacenter. Modified Round Robin and Modified Honey Bee Algorithms are proposed in this article for effective load balancing based on honey bee and Round Robin foraging activity to control load through VMs. Tasks taken from VMs that are crowded are viewed as honey bees. In the suggested method which is a circular ribbon, filled VMs are considered. In order to ensure a fast responding time and a minimum number of task migrations, the planned protocol also explores the aims of tasks in VM queues. The results of the test indicate that the quality of service has improved considerably (QoS).

Nowadays, most of the information science inquires about a spotlight on affiliation rule to decide explicit examples and rules from huge information. Affiliation guideline is worked by basic information duration device, for example, WEKA which incorporates arrangement, bunching, affiliation runs, etc. When all is said in done, the affiliation standard could be pertinent for enormous E-Learning datasets like they were pertinent towards the formless arrangement. Within this exam, the uses for affiliating rule after gathering under straight information for a considerable length of time from LMS have been explored. Intriguing quality measurements and other applicable understudy inclinations are caught in the wake of thinking about a few affiliation rule calculations. Some imagined introductions of rules and their applicable outcomes will be exhibited in wording reasonableness in eLearning conditions.

Identification of disease from therapeutic statistical evidences area single confronted task which can make a point of importance in the field of medical science. But according to the literature survey, it has been seen that still there are some chances that this challenging task can be fulfilled. In this research a feature ranking algorithm Random Forest is used for ranked the features of the attributes & later on four machine learning algorithm has been used i.e. Random forest, decision Tree, support Vector Machine & XG Boost classification algorithm to classify similar disease datasets like Jaundice, Malaria, Covid, Common cold, Typhoid, Dengue & Pneumonia. Comparison between the classifier is done on the basis of with ranking with feature selection & ranking without feature selection with the help of parameters of confusion matrix, Matthews’s correlation coefficient (MCC), area under the curve (AUC), Receiver Operating Characteristics Curve (ROC) & computational time. The results of the simulations shows the effectiveness of Covid like disease prediction is done by the feature selection ranking &classification algorithm.

Currently huge amount of data used to stored, extracted and transacted via various stand alone and internet based applications. These applications are extended towards the verticals like huge databases, data warehouses, cloud computing services and various client-server applications. In all these applications important data used to float day in day out. Therefore preserving user authentication & access control is extremely important aspect of information security. Here an attempt is made to generate an implicit authentication system using multi-share visual key cryptography which will generate strong password keys by using images. Initially various images will be fused to form a resultant image than on this fused visual key cryptography will be performed which will provide multiple shares, out of these one of the share is selected to generate strong password strings/keys to accomplish the task of access control or user authentications.

This article analyzes the access of population of Ukraine to food and the real financial opportunities of its citizens. Empirical coefficients of elastic demand for basic foodstuffs according to the average income of the population per household were determined. The average annual indicators of change in total income and food expenditure per household were calculated. These calculations showed that the indicator “Economic affordability of food” almost a third does not ensure food security of the population of Ukraine. Based on the methodology presented in this research, the necessary total income of the population to ensure food security by the indicator “Economic affordability of food” and scenarios for its provision by changing the structure of food costs, coefficients of elasticity of demand for household income and resources and other variables were determined.

Recommendation technology is an essential component of the Internet of Things (IoT) services that can help users get information at any time and from any place. Traditional recommendation algorithms, on the other hand, are unable to satisfy the IoT environment’s swift and reliable recommendation criteria. The use of mathematical and information discovery methods to overcome the relationship with target consumers in order to have desired items is known as a recommendation system. In this paper, a recommendation algorithm based on collaborative filtering is proposed. In this sense, the recommendation method (Recommender Systems) was developed; it is focused on the user’s characteristics, such as hobbies, and it is recommended to satisfy the object’s user specifications, also known as customized recommendation system (Personalized Recommender Systems), The majority of modern e-commerce recommender programs tend to recommend the best goods to a customer, believing that each product’s properties remain constant. Some properties, such as price discounts, can, however, be customized to respond to the preferences of each customer..

Deep Learning is a function of AI that duplicates the mechanisms of human thought in the processing of information and selection processes. The aim of this study is to apply a technology known as SVMHTMC to improve deep learning. The HTM Cortical Learning Approach and the Support Vector Machine have been combined in this suggested algorithm. The deep learning technique is based on the assumption that the mean absolute percentage error is reduced. Aside from the overlapping duty cycle, the high proportion of which shows the speed of the classifier’s processing function. The findings demonstrate that by halving the value, the suggested set of criteria minimizes the absolute proportion of mistakes. In addition, raise the percentage of overlapping duty cycles by 17%.

This paper presents a cryogenic analysis of Junction less Under lapped Nanowire MOSFETs in lower technology nodes. The temperature dependent analysis is carried out to extract the DC figure of merits (FOMs) of the proposed nanowire MOSFET. The analysis is carried out to investigate the drain current associated with the device at different temperature. Further the analysis is extended with underlap length variation from source, drain and both sides. As the trans conductance plays a vital role in device performance estimation, so the analysis is further extended to calculate the transconductance for all the temperature variation and underlap length variation. With the introduction of gate metal under lapping, the sub-threshold behaviour of the proposed structure under different temperature is carried out extensively.

IHICPAS Conference Proceeding volume contain the novel contributions that were reviewed and presented through the Ibn Al-Haitham International Conference for Pure and Applied Sciences (IHICPAS) will be held in College of Education for Pure Science (Ibn al-Haitham), University of Baghdad on 20 and 21 December, 2020., where the conference covers 6 tracks which includes (Trackl Chemistry, Track 2: Mathematics, Track3: Computer Science, Track 4: Biology Sciences, Track 5: Physics, and Track 6: Remote Sensing and GIS). IHICPAS aims to gathering together all the new trends, projects, technologies, and recent research works in many fields in pure and Applied Sciences. The received papers which passed the double-blind reviews which successfully passed the reviewers comments and editorial board decisions comes from various authors around the world, where the authors are either working in academics centers, universities, research institutes, corporations, industries, and other agencies or postgraduate students where the presented works refers to their novelty in their research works. IHICPAS Conference got very significant interesting from authors that comes from several countries like: UK, India, French, Morocco, Turkey, Nepal, Philippines, Indonesia, Australia, Egypt, Lebanon, Algeria, Iran, Pakistan, Malaysia, and Many other Countries where the authors are successfully presented their works and attend the sessions who managed by our scientific and organizing committee Members, and answered all the questions and dotes that directed by session chairs and attendances. We successfully held this conference within 2 days (20 and 21 December 2020), where in the first day we successfully listen to the keynote speakers’ presentations then the session started from 10:00 AM based on Iraq Standard Time till 10:00PM. We would like to express our thanks and appreciation to all our session chairs for their hard work and attend our (12) sessions through two days and more than 10 hours per day to deliver the presented works in successful manner. Venue of the Conference, The Reason(s) why IHICPAS Conference Held virtually:, Technology, Technical Difficulties and Drawbacks of Conference Virtually., The Main Technical Difficulties of Virtual Meetings can be summarizing as follow:, Conference Chairs, Conference Secretariat Chairs, International Program Chairs, Scientific Committee, Organizing Committee, Invited Speakers, Organizing Institutions, Special Thanks to Conference Partners:, Conference Flyers and Posters:, are available in the pdf

Web mining is the process of discovering important information and patterns in a weblog file. And contains loads of information. It consists of pages of various formats (HTML documents, images, etc.). And the data for this record is still increasing at a very high rate. So the process of retrieving information from it is a very difficult task. In order to obtain the required information from the network. This requires mining the weblog file. In this paper, the researcher conducted a review of previous studies and what researchers have dealt with in web prospecting. Explain web mining concepts. And how to obtain information and the visitors’ patterns through the techniques and algorithms used in Web usage mining.

Salah Albermany1, Ahmed J. Obaid2, Shubham Sharma3, Bassma H. Hamad4, Hiba A. Ahmed5 1, 2 Faculty of Computer Science and Mathematics, University of Kufa, Najaf, Iraq. 3 Advanced Materials Science and Energy, CSIR Institute, RCED, India. 4 Alkarkh University of Science, Iraq 5 Dept of Mathematics, Baghdad University, Iraq E-Mails: 1salah.albermany@uokufa.edu.iq, 2ahmedj.aljanaby@uokufa.edu.iq IICPS Conference Proceeding volume contain the novel contributions that were reviewed and presented through the first version of Iraqi Academic Syndicate International Conference for pure and Applied Sciences, where the conference covers 6 tracks which includes ( Track1 Physics and Astronomy, Track 2: Geology and Earth Science, Track3: Biology and Biotechnology, Track 4: Information Technology and Mathematics Sciences, Track 5: chemistry and Material Sciences, and Track 6: Remote Sensing and GIS). IICPS aims to gathering together all the new trends, projects, technologies, and recent research works in many fields in pure and Applied Sciences. The received papers which passed the double-blind reviews which successfully passed the reviewers comments and editorial board decisions comes from various authors around the world, where the authors are either working in academics centers, universities, research institutes, corporations, industries, and other agencies or postgraduate students where the presented works refers to their novelty in their research works. List of titles Conference Chairs, Conference Secretariat Chairs, International Program Chairs, Organizing Committee, Scientific Committee, Invited Speakers, Organizing Institutions, Special Thanks to, Conference Flyers and Posters, Screen Shoots of Day 1 and Day 2 Using (ZOOM) are available in this Pdf.

This primary study tries to explore the best machine learning model of hyperparameter tuning using single, multiple, and deep neural networks for predicting engineering student grade of Pokhara University Nepal in the year 2019. Generally, hyperparameter algorithms are adjusted from the data sets automatically when the model was designed. This is not a good idea for all sort of algorithm, with less flexibility of user choices. Therefore this article ties to meet the research gap between automatic calculation vs external model hyperparameter calculation on the same data sets applying comparison. The single neuron predicts 92 percent accuracy of the student’s A, B, C, D grade of university examination with correlation with their internal marks respectively. The five-neuron multilayer neural network produces 72 percent accuracy and deep neural network with drop-out layer (32, 64) examines, the most suitable hyperparameter determines to produce an accurate result of 50 percent accurate when 32 hidden levels were used over 64 hyperparameters produce quite less accuracy (44 percent) of their final score in constituent campus Pokhara. The main objective of this study is to examine the comparison between various neural networks for educational settings for optimization of model deployment accurately when categorical large data prediction of student grade. Therefore, this study compares three comparisons of the neural network model with the same data sets for best hypermeter prediction.

The ISCPS Proceedings volume contains the written versions of the contributions presented during the First International Conference for Pure and Applied Sciences (ISCPS), it had been held at Faculty of Science, University of Kufa, Najaf, Iraq(http://sci.uokufa.edu.iq/), at 13 and 14 July 2020, ISCPS also hosted a session from 3rd Creativity and Innovation Forum which it’s had been held at University of Babylon. The Conference provided a forum for discussion and sharing between lecturers, researchers, academics, practitioners, communities, and Information technology specialists, from universities, research institutes, corporations, industries, the government, and the general public in terms of Pure and Applied Sciences in the aspect of Biology, Chemistry, Geology, Physics, and Mathematics. The conference has been a great opportunity for participants coming from UK, Turkey, Egypt, Lebanon, Qatar, Algeria, Syria, Iran, India, Pakistan, Malaysia, Palestine, Senegal, Morocco, and Many other Countries to present and discuss topics in their respective research areas. List of Conference Chairs, Editorial Committee, Organizing Committee (Faculty of Science, University of Kufa), Scientific Committee (Faculty of Science, University of Kufa), Invited Speakers, Organizing Institutions and Sponsors are available in this pdf.

The use of CCTV is so widespread today that it is widely used in almost every part of the city, public places, homes, shops, passages and even roads outside the city. These cameras are used for specific purposes, but most of them have in common the use of the camera as a tool for continuous surveillance and recording of surrounding events for future use. However, each of them is an independent network. It has been seen and there is no common point and no joint exploitation of this huge investment From a macro perspective, it seems that the existence of continuous networks of CCTVs in the long run will not be cost effective for the economy and the initial investment cost and maintenance costs will be significant. It turns out that field surveys indicate that most of the large networks of CCTV are in government-affiliated institutions, of which their funding is required from public spending. One of the country’s major institutions, There are municipalities that have one of the largest CCTV networks in the country today The major use of this network is mainly for security purposes to secure and control public safety, as well as to monitor and control traffic and to commit possible offenses against offending drivers. Despite the large investment made on this network and a very good context Images are provided for transfer but no other operation.The purpose of this article is to create wealth and add value to the network of security CCTVs. It is clear, however, that surplus operations on the core task of the network should not disrupt the core mission of the network and, in addition, provide different access to the network. This network will also require compliance with network information security.

Nowadays, when executives talk about “knowledge management”, the discussion is usually prompted by the problem of big data and analytics. Of course, this is not surprising. Extraordinary amounts of complex, rich data on customers, operations, and staff are now available to most managers, but it is difficult to turn that data into useful knowledge. In today’s world, knowledge is regarded as one of the essential assets of any organization and organizations invest heavily in the acquisition, creation, storage, conversion and updating of knowledge. It is thought that if the right experts and the right tools are used for this volume of data, we will have tremendous strategic information. In fact, the ever-changing business environment has led organizations to increasingly strive to promote knowledge and make optimal use of organizational knowledge as a competitive advantage. In this regard, the knowledge management system and its infrastructure play a significant role in maintaining and updating the knowledge-based assets of the organization and valuable experiences of its role in the organization’s performance have been reported. However, investing and deploying a knowledge management system in an organization requires that the factors affecting its success in an organization be properly identified and appropriate programs are developed to foster it, especially given the different organizational culture of development. to be given. In the present article, the problem of identifying these factors was presented based on the experience of implementing a knowledge management system in the research community, namely Iranian companies. In this paper, the neural network was used as a reference for deciding on the importance of these factors due to its ability to discover the relationships between available data.

The primary motive of this research investigation is to explore out by enforcing the sun powered energy in the present hybrid electric vehicles, which signifies precipitous plummet in pollutants and harmful contaminants of environment. Solar powered coercing vehicles are environmental friendly however can’t attain to most reliable speed in certain specific time-interval. The operational functioning of two dissimilar fuels collectively may be one of the most advantageous aspects of this novel concept. CATIA V5R19 is appropriate podium for the design outlining of vehicles which this particular research study is aiming. After analyzing the blueprint layout, for computation or estimating of forces, load, internal resisting force and lateral strain performing at the front and rear collisions of structural body-on-frames, ANSYS 13.0 version platform was utilized for software primarily based modeling and simulation. Output statistics or facts figures are premeditated to determine the technical factors of solar powered hybrid vehicles. Solar hybrid electric vehicles have high competencies of an overall recital as its enormous arrangement of traditional fuel engine, possesses high powered electric-vehicle-battery & solar photo-voltaic panel modules.

Start your abstract here…olar irradiation and the temperature affects the output of photovoltaic modules in great extent. Environmental and electrical parameters affect the photovoltaic (PV) output power. Environmental parameters like solar radiance and temperatures has major contribution in PV output power. This research gives the precise algorithm for PV system simulation in Matlab. This research gives the simulation of current, voltage and power on different solar radiance level and temperature values. For allowing interaction with power converter, therefore this is mandatory to illustrate simulation that is based on circuit for PV cell. Simulation blocks are similar to PV module and they are compatible with various crusytalline modules and different types of PV arrays. Concentrated photovoltaic systems are being operated at higher temperature than fixed PV setup, and system efficiencies and material properties has been affected with higher temperature. Hence, thorough understating of high temperature are very important. Misalignment and optics tolerances causes decrement in cell efficiency. As direct sunlight is used by PV system, therefore proper system design can reduce sensitivity to errors.

This Conference Proceedings volume contains the written versions of the contributions presented during the Al-Kadhum International Conference for Modern Applications of Information & Communication Technology (MAICT-19), it had been held at Imam Al-Kadhum College (IKC) on Baghdad, Iraq in January 11-12, 2020. The Conference provided a forum for discussion and sharing between lecturers, researchers, academics, practitioners, communities, and Information technology specialists, from universities, research institutes, corporations, industries, the government, and the general public in terms of Information and Communication Technologies in the aspect of Computers systems, Security Systems, Communications and Networking technologies, Computing & Informatics Theory, modern application of IT, Mathematical Models and Innovation. The conference has been a great opportunity for participants coming from Iraq, United Kingdom, Turkey, Russia, Egypt, Lebanon, Iran, Pakistan, Malaysia, and India to present and discuss topics in their respective research areas. MAICT-19 conference included 4 plenary sessions and invited speakers, and also oral and poster presentations to allow as many as possible attendances to present their scientific results on the different fields. The manuscripts which have presented were published in the IoP Conference Series: Journal of Physics under the peer-reviewed process. We love to express our gratitude for all of the participants, keynote speakers, and guests of honor, for their effective contribution in our conference and these proceedings. We also, acknowledge The General Secretariat of Imam Al-Kadhum Holy Shrine for their hospitality and sponsoring the conference. Furthermore, would like to thank SICC Center for their supports. Our ongoing thankfulness is presented for our Guest editors and Speakers: • Prof. Dr. P. Nagaradjane and Shubham S. from India. • Dr. Sobirov B. from Uzbekistan. • Prof. Dr. Sara P. and Paulo P. from Portugal. • Prof. Ahmedi Y. and prof. K. Yeganegi from Iran. • Dr. Mushtaq T. and Dr. Noor T Sh. from Ukraine. • Dr.Bassma H.Hamad, from Alkarkh University of Science, Iraq. • Dr. Hiba A. Ahmed from Baghdad University, Iraq. Finally, we would love to express our gratefulness for all our sponsors, partners, and colleagues, we hope to collaborate with them in future activities. Thank you, Prof. Dr. Saleh Al-Karaawy, Director of MAICT Scientific Committee. Professor Dr. Ghani Al-Khakani, Head of IKC College. Asst. prof. Dr. Wesam A. Shehab, Director of TCIA Foundation. Dr. Ahmed J. Obaid, Conference Coordinator