With 25 years of experience in academics and research, Professor Jabar boasts a commendable research record and extensive experience that makes him an asset for advancing scientific knowledge and fostering innovation in his field. He has published over 90 high-impact research papers and 15 books/chapters. Dr Jabar is one of Oman's top scientists who is interested in researching artificial intelligence, cloud computing, soft computing, natural language processing, renewable energy modelling, simulation and optimization, and virtual reality. Dr. Jabar is a Professor at the Faculty of Computing and Information Technology at Sohar University. He completed his postdoctoral in computer graphics VR/AR UKM-Malaysia. He earned a Ph.D. in AI and NLP from the Faculty of Information Science and Technology, UKM. He holds an M.Sc. and a B.Sc. in computer sci. He is a distinguished editor and reviewer affiliated with reputable professional organizations, including Elsevier, Springer, Wiley, MDPI, and IEEE. Address: Sohar University- Oman
The statistics of the World Health Organization (WHO) indicate that outdoor air pollution in 2016... more The statistics of the World Health Organization (WHO) indicate that outdoor air pollution in 2016 is a significant cause of premature mortality, with an average of 4.2 million death cases. This mortality is due to exposure to PM2.5 particulate matter, which causes many diseases such as respiratory, cardiovascular, and cancers. The concentration of particulate matter (PM) is the most popular air pollutant that affects short term and long term health. The paper aims to study and investigate the concentration dispersion of particulates (PM 2.5 and PM10) and its impact on human health in Oman. The study suggested a hybrid neural and mathematical approaches for analyzing the effect rate of particulate matter (PM2.5 and PM10). The paper implements a comparative study to analyze the proposed neural and mathematical models, which predict the future levels of pollutants in a fast, cheap, and safe way. The Linear regression models achieve fewer results of R², MSE, RMSE (0.7604, 0.0673, 0.2595), respectively. However, the non-linear regression polynomial prediction model obtained excellent results based on the coefficient of determination (R²) value of 0.9394 and mean square error (MSE) rate of 0.0209, and root mean square error (RMSE) value of 0.1447. Moreover, the Neural SOM model obtained the highest results in predicting the experimental data that achieved an MSE value of 0.0064, correlation rate (R) value of 0.994, NMSE value of 0.01392, and MAE value of 0.0467. All the results were correctly verified based on suitable mathematical methods.
In recent years, Neural networks are increasingly deployed in various fields to learn complex pat... more In recent years, Neural networks are increasingly deployed in various fields to learn complex patterns and make accurate predictions. However, designing an effective neural network model is a challenging task that requires careful consideration of various factors, including architecture, optimization method, and regularization technique. This paper aims to comprehensively overview the state-of-the-art artificial neural network (ANN) generation and highlight key challenges and opportunities in machine learning applications. It provides a critical analysis of current neural network model design methodologies, focusing on the strengths and weaknesses of different approaches. Also, it explores the use of different learning approaches, including convolutional neural networks (CNN), deep neural networks (DNN), and recurrent neural networks (RNN) in image recognition, natural language processing, and time series analysis. Besides, it discusses the benefits of choosing the ideal values for ...
Journal of Internet Services and Information Security
Detecting fake faces has become a crucial endeavour within the realm of computer vision. The wide... more Detecting fake faces has become a crucial endeavour within the realm of computer vision. The widespread availability of digital media has facilitated the creation and dissemination of deceptive and misleading content. A prominent strategy for identifying counterfeit faces employs advanced deep-learning methodologies that scrutinise both colour and textural attributes. This investigation is geared towards devising a method for discerning fake faces by leveraging the capabilities of convolutional neural networks (CNNs). These networks are trained to discriminate between authentic and forged images by discerning nuances in their colour characteristics. To achieve this, the MSU MFSD dataset will be harnessed, allowing for exploring colour textures and extracting facial traits across diverse colour channels, including RGB, HSV, and YCbCr.The proposed framework marks a notable stride in the realm of computer vision research, particularly given the prevalent employment of digital media, wh...
Artificial Intelligence & Robotics Development Journal
AQI (Air Quality Index) is the standard degree that guides us to measure air pollution levels suc... more AQI (Air Quality Index) is the standard degree that guides us to measure air pollution levels such as PM2.5, O3, NO2, and SO2 to show the state of air quality. Polluted gas causes much damage and problems to people, plants, and the environment because of its negative impact. Data mining successfully examines an enormous cluster of data to recognize associations, determine relations between variables, and predict future values. In this paper, an experimental study was performed on analyzing the previous dataset of (PM2.5 and O3) for accurately predicting AQI using deep learning Feedforward Neural network techniques. The deep learning (Feedforward Neural Network (FFNN) predicting models are employed to evaluate based on R, R², MSE, MAE, and RMSE criteria using historical data from (the Ministry of Environment-Oman). Different epochs and a different number of hidden layers are deployed to improve and boost performance. In FFNN, the epochs number increase by 50,100 and 500 while the hid...
Artificial Intelligence & Robotics Development Journal
Modern technologies in virtual reality (VR) and augmented reality (AR) provide unique features th... more Modern technologies in virtual reality (VR) and augmented reality (AR) provide unique features that can be used to facilitate tasks in everyday life. Several courses can be built using augmented reality, such as engine maintenance, computer maintenance, chemistry lab, etc. Augmented reality technologies provide dynamic and interactive instructions to resolve a problem or present required concepts. Building an educational system based on augmented reality is not an easy task due to some difficulties and challenges, such as the cost of augmented reality tools and other hardware and software required. Also, training students with engineering concepts and precise parts involves a lot of analysis and practice to know problems and then design solutions. The paper aims to develop a virtual educational environment for training students in engineering sectors in practical laboratory sessions based on AR/VR techniques. The proposed system provides a safe and low-cost environment to train the ...
The notable developments in renewable energy facilities and resources help reduce the cost of pro... more The notable developments in renewable energy facilities and resources help reduce the cost of production and increase production capacity. Therefore, developers in renewable energy evaluate the overall performance of the various equipment, methods, and structure and then determine the optimal variables for the design of energy production systems. Variables include equipment characteristics and quality, geographical location, and climatic variables such as solar irradiance, temperature, humidity, dust, etc. This paper investigated and reviewed the current big data methods and tools in solar energy production. It discusses the comprehensive two-stage design and evaluation for examining the optimal structure for renewable energy systems. In the design stage, technical and economic aspects are discussed based on a robust analysis of all input/output variables for determining the highest performance. Next, assess and evaluate the effectiveness of each method under different circumstances...
Social media applications have been increasingly gaining significant attention from online educat... more Social media applications have been increasingly gaining significant attention from online education and training platforms. Social networking tools provide multiple advantages for communicating, exchanging opinions, and discussing specific issues. Social media also helps to improve the processes of teaching and learning through sharing educational programs. In this study, we used a quantitative research technique based on the partial least-squares (PLS) linear regression method to determine the influence of using social media as an online discussion and communication platform for academic purposes by assessing the relationships among the skills obtained through social media, the usage of social media, and the purpose of social media. A total of 200 students participated in this study (88% female and 12% males), and a purposive sampling technique was used to select a suitable population for the study. The results show that 61.5% of the participants use the web daily for more than fi...
The statistics of the World Health Organization (WHO) indicate that outdoor air pollution in 2016... more The statistics of the World Health Organization (WHO) indicate that outdoor air pollution in 2016 is a significant cause of premature mortality, with an average of 4.2 million death cases. This mortality is due to exposure to PM2.5 particulate matter, which causes many diseases such as respiratory, cardiovascular, and cancers. The concentration of particulate matter (PM) is the most popular air pollutant that affects short term and long term health. The paper aims to study and investigate the concentration dispersion of particulates (PM 2.5 and PM10) and its impact on human health in Oman. The study suggested a hybrid neural and mathematical approaches for analyzing the effect rate of particulate matter (PM2.5 and PM10). The paper implements a comparative study to analyze the proposed neural and mathematical models, which predict the future levels of pollutants in a fast, cheap, and safe way. The Linear regression models achieve fewer results of R², MSE, RMSE (0.7604, 0.0673, 0.2595), respectively. However, the non-linear regression polynomial prediction model obtained excellent results based on the coefficient of determination (R²) value of 0.9394 and mean square error (MSE) rate of 0.0209, and root mean square error (RMSE) value of 0.1447. Moreover, the Neural SOM model obtained the highest results in predicting the experimental data that achieved an MSE value of 0.0064, correlation rate (R) value of 0.994, NMSE value of 0.01392, and MAE value of 0.0467. All the results were correctly verified based on suitable mathematical methods.
In recent years, Neural networks are increasingly deployed in various fields to learn complex pat... more In recent years, Neural networks are increasingly deployed in various fields to learn complex patterns and make accurate predictions. However, designing an effective neural network model is a challenging task that requires careful consideration of various factors, including architecture, optimization method, and regularization technique. This paper aims to comprehensively overview the state-of-the-art artificial neural network (ANN) generation and highlight key challenges and opportunities in machine learning applications. It provides a critical analysis of current neural network model design methodologies, focusing on the strengths and weaknesses of different approaches. Also, it explores the use of different learning approaches, including convolutional neural networks (CNN), deep neural networks (DNN), and recurrent neural networks (RNN) in image recognition, natural language processing, and time series analysis. Besides, it discusses the benefits of choosing the ideal values for ...
Journal of Internet Services and Information Security
Detecting fake faces has become a crucial endeavour within the realm of computer vision. The wide... more Detecting fake faces has become a crucial endeavour within the realm of computer vision. The widespread availability of digital media has facilitated the creation and dissemination of deceptive and misleading content. A prominent strategy for identifying counterfeit faces employs advanced deep-learning methodologies that scrutinise both colour and textural attributes. This investigation is geared towards devising a method for discerning fake faces by leveraging the capabilities of convolutional neural networks (CNNs). These networks are trained to discriminate between authentic and forged images by discerning nuances in their colour characteristics. To achieve this, the MSU MFSD dataset will be harnessed, allowing for exploring colour textures and extracting facial traits across diverse colour channels, including RGB, HSV, and YCbCr.The proposed framework marks a notable stride in the realm of computer vision research, particularly given the prevalent employment of digital media, wh...
Artificial Intelligence & Robotics Development Journal
AQI (Air Quality Index) is the standard degree that guides us to measure air pollution levels suc... more AQI (Air Quality Index) is the standard degree that guides us to measure air pollution levels such as PM2.5, O3, NO2, and SO2 to show the state of air quality. Polluted gas causes much damage and problems to people, plants, and the environment because of its negative impact. Data mining successfully examines an enormous cluster of data to recognize associations, determine relations between variables, and predict future values. In this paper, an experimental study was performed on analyzing the previous dataset of (PM2.5 and O3) for accurately predicting AQI using deep learning Feedforward Neural network techniques. The deep learning (Feedforward Neural Network (FFNN) predicting models are employed to evaluate based on R, R², MSE, MAE, and RMSE criteria using historical data from (the Ministry of Environment-Oman). Different epochs and a different number of hidden layers are deployed to improve and boost performance. In FFNN, the epochs number increase by 50,100 and 500 while the hid...
Artificial Intelligence & Robotics Development Journal
Modern technologies in virtual reality (VR) and augmented reality (AR) provide unique features th... more Modern technologies in virtual reality (VR) and augmented reality (AR) provide unique features that can be used to facilitate tasks in everyday life. Several courses can be built using augmented reality, such as engine maintenance, computer maintenance, chemistry lab, etc. Augmented reality technologies provide dynamic and interactive instructions to resolve a problem or present required concepts. Building an educational system based on augmented reality is not an easy task due to some difficulties and challenges, such as the cost of augmented reality tools and other hardware and software required. Also, training students with engineering concepts and precise parts involves a lot of analysis and practice to know problems and then design solutions. The paper aims to develop a virtual educational environment for training students in engineering sectors in practical laboratory sessions based on AR/VR techniques. The proposed system provides a safe and low-cost environment to train the ...
The notable developments in renewable energy facilities and resources help reduce the cost of pro... more The notable developments in renewable energy facilities and resources help reduce the cost of production and increase production capacity. Therefore, developers in renewable energy evaluate the overall performance of the various equipment, methods, and structure and then determine the optimal variables for the design of energy production systems. Variables include equipment characteristics and quality, geographical location, and climatic variables such as solar irradiance, temperature, humidity, dust, etc. This paper investigated and reviewed the current big data methods and tools in solar energy production. It discusses the comprehensive two-stage design and evaluation for examining the optimal structure for renewable energy systems. In the design stage, technical and economic aspects are discussed based on a robust analysis of all input/output variables for determining the highest performance. Next, assess and evaluate the effectiveness of each method under different circumstances...
Social media applications have been increasingly gaining significant attention from online educat... more Social media applications have been increasingly gaining significant attention from online education and training platforms. Social networking tools provide multiple advantages for communicating, exchanging opinions, and discussing specific issues. Social media also helps to improve the processes of teaching and learning through sharing educational programs. In this study, we used a quantitative research technique based on the partial least-squares (PLS) linear regression method to determine the influence of using social media as an online discussion and communication platform for academic purposes by assessing the relationships among the skills obtained through social media, the usage of social media, and the purpose of social media. A total of 200 students participated in this study (88% female and 12% males), and a purposive sampling technique was used to select a suitable population for the study. The results show that 61.5% of the participants use the web daily for more than fi...
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Papers by Jabar H. Yousif