Background. University education in all countries of the world occupies an important placebecause... more Background. University education in all countries of the world occupies an important placebecause universities are the stronghold of enlightened thought, the center of enlightenment, and the home of constructive scientific research. Through our survey of the published papers, there was no statistical study examining the reasons for this gap. If the reasons are studied, the compatibility between the outputs of education and the labor market will be achieved. Objective. To identify factors that cause the gap between university education and the labor market, then expand the compatibility between learning outcomes in Saudi universities and market requirements in accordance with the Kingdom’s Vision 2030. Methods and Materials. Questionnaires were given to the general population of Saudi Arabia, using Google forms for data collection. The target group was 384 people answered. Results. The findings showed, Resolution IV with regression analysis gave the factors that caused the gap betwee...
International Journal of Wireless and Ad Hoc Communication
Localization is widely employed in wireless sensor networks (WSN) to detect the present position ... more Localization is widely employed in wireless sensor networks (WSN) to detect the present position of the nodes. Generally, WSN comprises numerous sensors, which makes the deployment of GPS in all nodes cost and fails to provide precise localization outcomes in several cases. The manual configuration of the position reference of the sensors is not feasible under dense networks. Therefore, the NL process can be treated as an NP-hard problem and solved by metaheuristic algorithms. In this aspect, this paper presents an improved group teaching optimization algorithm-based NL technique called IGTOA-NL for WSN. The IGTOA technique is derived by integrating the basic concepts of GTOA with the β-hill-climbing technique to improve the overall node localization process. The IGTOA-NL technique can effectually localize the nodes in WSN under varying anchor node count. To showcase the productive outcome of the IGTOA technique, a series of simulations take place under a diverse number of anchors. ...
Advances in Systems Analysis, Software Engineering, and High Performance Computing
Wireless sensor networks (WSNs) may be described as a self-configured wireless networks that can ... more Wireless sensor networks (WSNs) may be described as a self-configured wireless networks that can be used to track physical objects or monitor environmental features, such as temperature or motion. The sensed data is then passed across the network to the main location or sink node, where the data can be processed and analyzed. Sensor nodes in WSN are fundamentally resource-constrained: they have restricted processing power, computing, space, and transmission bandwidth. Object tracking is considered as one of the major applications. However, many of the recent articles focused on object localization. In this chapter, the authors suggest an effective approach for tracking objects in WSNs. The aim is to achieve both minimal energy consumption in reporting activity and balanced energy consumption across the WSN lifetime extension of sensor nodes. Furthermore, data reliability is considered in our model. The chapter starts by formulating the multi-object tracking problem using 0/1 Integer...
With the emergence of one of this century’s deadliest pandemics, coronavirus disease (COVID-19) h... more With the emergence of one of this century’s deadliest pandemics, coronavirus disease (COVID-19) has an enormous effect globally with a quick spread worldwide. This made the World Health Organization announce it as a pandemic. COVID-19 has pushed countries to follow new behaviors such as social distancing, hand washing, and remote work and to shut down organizations, businesses, and airports. At the same time, white hats are doing their best to accommodate the pandemic. However, while white hats are protecting people, black hats are taking advantage of the situation, which creates a cybersecurity pandemic on the other hand. This paper discusses the cybersecurity issues at this period due to finding information or finding another related research that had not been discussed before. This paper presents the cybersecurity attacks during the COVID-19 epidemic time. A lot of information has been collected from the World Health Organization (WHO), trusted organizations, news sources, offici...
Face recognition is one of the emergent technologies that has been used in many applications. It ... more Face recognition is one of the emergent technologies that has been used in many applications. It is a process of labeling pictures, especially those with human faces. One of the critical applications of face recognition is security monitoring, where captured images are compared to thousands, or even millions, of stored images. The problem occurs when different types of noise manipulate the captured images. This paper contributes to the body of knowledge by proposing an innovative framework for face recognition based on various descriptors, including the following: Color and Edge Directivity Descriptor (CEDD), Fuzzy Color and Texture Histogram Descriptor (FCTH), Color Histogram, Color Layout, Edge Histogram, Gabor, Hashing CEDD, Joint Composite Descriptor (JCD), Joint Histogram, Luminance Layout, Opponent Histogram, Pyramid of Gradient Histograms Descriptor (PHOG), Tamura. The proposed framework considers image set indexing and retrieval phases with multi-feature descriptors. The exa...
Virtual screening is the most critical process in drug discovery, and it relies on machine learni... more Virtual screening is the most critical process in drug discovery, and it relies on machine learning to facilitate the screening process. It enables the discovery of molecules that bind to a specific protein to form a drug. Despite its benefits, virtual screening generates enormous data and suffers from drawbacks such as high dimensions and imbalance. This paper tackles data imbalance and aims to improve virtual screening accuracy, especially for a minority dataset. For a dataset identified without considering the data’s imbalanced nature, most classification methods tend to have high predictive accuracy for the majority category. However, the accuracy was significantly poor for the minority category. The paper proposes a K-mean algorithm coupled with Synthetic Minority Oversampling Technique (SMOTE) to overcome the problem of imbalanced datasets. The proposed algorithm is named as KSMOTE. Using KSMOTE, minority data can be identified at high accuracy and can be detected at high prec...
In this work, an optimization of the InGaP/GaAs dual-junction (DJ) solar cell performance is pres... more In this work, an optimization of the InGaP/GaAs dual-junction (DJ) solar cell performance is presented. Firstly, a design for the DJ solar cell based on the GaAs tunnel diode is provided. Secondly, the used device simulator is calibrated with recent experimental results of an InGaP/GaAs DJ solar cell. After that, the optimization of the DJ solar cell performance is carried out for two different materials of the top window layer, AlGaAs and AlGaInP. For AlGaAs, the optimization is carried out for the following: aluminum (Al) mole fraction, top window thickness, top base thickness, and bottom BSF doping and thickness. The electrical performance parameters of the optimized cell are extracted: J SC = 18.23 mA / c m 2 , V OC = 2.33 V , FF = 86.42 % , and the conversion efficiency ( η c ) equals 36.71%. By using AlGaInP as a top cell window, the electrical performance parameters for the optimized cell are J SC = 19.84 mA / c m 2 , V OC = 2.32 V , FF = 83.9 % , and η c = 38.53 % . ...
Nowadays, IoT has been widely used in different applications to improve the quality of life. Howe... more Nowadays, IoT has been widely used in different applications to improve the quality of life. However, the IoT becomes increasingly an ideal target for unauthorized attacks due to its large number of objects, openness, and distributed nature. Therefore, to maintain the security of IoT systems, there is a need for an efficient Intrusion Detection System (IDS). IDS implements detectors that continuously monitor the network traffic. There are various IDs methods proposed in the literature for IoT security. However, the existing methods had the disadvantages in terms of detection accuracy and time overhead. To enhance the IDS detection accuracy and reduces the required time, this paper proposes a hybrid IDS system where a pre-processing phase is utilized to reduce the required time and feature selection as well as the classification is done in a separate stage. The feature selection process is done by using the Enhanced Shuffled Frog Leaping (ESFL) algorithm and the selected features are...
International Journal of System Dynamics Applications
With the advances of networks and sensing technologies, it is possible to benefit from the surrou... more With the advances of networks and sensing technologies, it is possible to benefit from the surrounding environment's data in enhancing peoples' life. Currently, we have different types of networks such as Wireless Sensor Networks (WSNs), Vehicle Ad Hoc Networks (VANETs), Cellular Networks (CNs), and Social Networks (SNs) along with underlying computing such as Cloud computing. These types of networks provide huge data about the surrounding environments including weather information, peoples' relations, peoples' interest, and location information. This paper examines the suitability of hierarchal fuzzy logic controller in classifying the IoT data. The paper also tries to answer “if-else “questions about the effect of each of the input parameters. The authors' test case in this paper is related to the disease spreading prediction problem. This test case is highly important to the health care organizations. Different case studies are generated to examine the efficie...
Background. University education in all countries of the world occupies an important placebecause... more Background. University education in all countries of the world occupies an important placebecause universities are the stronghold of enlightened thought, the center of enlightenment, and the home of constructive scientific research. Through our survey of the published papers, there was no statistical study examining the reasons for this gap. If the reasons are studied, the compatibility between the outputs of education and the labor market will be achieved. Objective. To identify factors that cause the gap between university education and the labor market, then expand the compatibility between learning outcomes in Saudi universities and market requirements in accordance with the Kingdom’s Vision 2030. Methods and Materials. Questionnaires were given to the general population of Saudi Arabia, using Google forms for data collection. The target group was 384 people answered. Results. The findings showed, Resolution IV with regression analysis gave the factors that caused the gap betwee...
International Journal of Wireless and Ad Hoc Communication
Localization is widely employed in wireless sensor networks (WSN) to detect the present position ... more Localization is widely employed in wireless sensor networks (WSN) to detect the present position of the nodes. Generally, WSN comprises numerous sensors, which makes the deployment of GPS in all nodes cost and fails to provide precise localization outcomes in several cases. The manual configuration of the position reference of the sensors is not feasible under dense networks. Therefore, the NL process can be treated as an NP-hard problem and solved by metaheuristic algorithms. In this aspect, this paper presents an improved group teaching optimization algorithm-based NL technique called IGTOA-NL for WSN. The IGTOA technique is derived by integrating the basic concepts of GTOA with the β-hill-climbing technique to improve the overall node localization process. The IGTOA-NL technique can effectually localize the nodes in WSN under varying anchor node count. To showcase the productive outcome of the IGTOA technique, a series of simulations take place under a diverse number of anchors. ...
Advances in Systems Analysis, Software Engineering, and High Performance Computing
Wireless sensor networks (WSNs) may be described as a self-configured wireless networks that can ... more Wireless sensor networks (WSNs) may be described as a self-configured wireless networks that can be used to track physical objects or monitor environmental features, such as temperature or motion. The sensed data is then passed across the network to the main location or sink node, where the data can be processed and analyzed. Sensor nodes in WSN are fundamentally resource-constrained: they have restricted processing power, computing, space, and transmission bandwidth. Object tracking is considered as one of the major applications. However, many of the recent articles focused on object localization. In this chapter, the authors suggest an effective approach for tracking objects in WSNs. The aim is to achieve both minimal energy consumption in reporting activity and balanced energy consumption across the WSN lifetime extension of sensor nodes. Furthermore, data reliability is considered in our model. The chapter starts by formulating the multi-object tracking problem using 0/1 Integer...
With the emergence of one of this century’s deadliest pandemics, coronavirus disease (COVID-19) h... more With the emergence of one of this century’s deadliest pandemics, coronavirus disease (COVID-19) has an enormous effect globally with a quick spread worldwide. This made the World Health Organization announce it as a pandemic. COVID-19 has pushed countries to follow new behaviors such as social distancing, hand washing, and remote work and to shut down organizations, businesses, and airports. At the same time, white hats are doing their best to accommodate the pandemic. However, while white hats are protecting people, black hats are taking advantage of the situation, which creates a cybersecurity pandemic on the other hand. This paper discusses the cybersecurity issues at this period due to finding information or finding another related research that had not been discussed before. This paper presents the cybersecurity attacks during the COVID-19 epidemic time. A lot of information has been collected from the World Health Organization (WHO), trusted organizations, news sources, offici...
Face recognition is one of the emergent technologies that has been used in many applications. It ... more Face recognition is one of the emergent technologies that has been used in many applications. It is a process of labeling pictures, especially those with human faces. One of the critical applications of face recognition is security monitoring, where captured images are compared to thousands, or even millions, of stored images. The problem occurs when different types of noise manipulate the captured images. This paper contributes to the body of knowledge by proposing an innovative framework for face recognition based on various descriptors, including the following: Color and Edge Directivity Descriptor (CEDD), Fuzzy Color and Texture Histogram Descriptor (FCTH), Color Histogram, Color Layout, Edge Histogram, Gabor, Hashing CEDD, Joint Composite Descriptor (JCD), Joint Histogram, Luminance Layout, Opponent Histogram, Pyramid of Gradient Histograms Descriptor (PHOG), Tamura. The proposed framework considers image set indexing and retrieval phases with multi-feature descriptors. The exa...
Virtual screening is the most critical process in drug discovery, and it relies on machine learni... more Virtual screening is the most critical process in drug discovery, and it relies on machine learning to facilitate the screening process. It enables the discovery of molecules that bind to a specific protein to form a drug. Despite its benefits, virtual screening generates enormous data and suffers from drawbacks such as high dimensions and imbalance. This paper tackles data imbalance and aims to improve virtual screening accuracy, especially for a minority dataset. For a dataset identified without considering the data’s imbalanced nature, most classification methods tend to have high predictive accuracy for the majority category. However, the accuracy was significantly poor for the minority category. The paper proposes a K-mean algorithm coupled with Synthetic Minority Oversampling Technique (SMOTE) to overcome the problem of imbalanced datasets. The proposed algorithm is named as KSMOTE. Using KSMOTE, minority data can be identified at high accuracy and can be detected at high prec...
In this work, an optimization of the InGaP/GaAs dual-junction (DJ) solar cell performance is pres... more In this work, an optimization of the InGaP/GaAs dual-junction (DJ) solar cell performance is presented. Firstly, a design for the DJ solar cell based on the GaAs tunnel diode is provided. Secondly, the used device simulator is calibrated with recent experimental results of an InGaP/GaAs DJ solar cell. After that, the optimization of the DJ solar cell performance is carried out for two different materials of the top window layer, AlGaAs and AlGaInP. For AlGaAs, the optimization is carried out for the following: aluminum (Al) mole fraction, top window thickness, top base thickness, and bottom BSF doping and thickness. The electrical performance parameters of the optimized cell are extracted: J SC = 18.23 mA / c m 2 , V OC = 2.33 V , FF = 86.42 % , and the conversion efficiency ( η c ) equals 36.71%. By using AlGaInP as a top cell window, the electrical performance parameters for the optimized cell are J SC = 19.84 mA / c m 2 , V OC = 2.32 V , FF = 83.9 % , and η c = 38.53 % . ...
Nowadays, IoT has been widely used in different applications to improve the quality of life. Howe... more Nowadays, IoT has been widely used in different applications to improve the quality of life. However, the IoT becomes increasingly an ideal target for unauthorized attacks due to its large number of objects, openness, and distributed nature. Therefore, to maintain the security of IoT systems, there is a need for an efficient Intrusion Detection System (IDS). IDS implements detectors that continuously monitor the network traffic. There are various IDs methods proposed in the literature for IoT security. However, the existing methods had the disadvantages in terms of detection accuracy and time overhead. To enhance the IDS detection accuracy and reduces the required time, this paper proposes a hybrid IDS system where a pre-processing phase is utilized to reduce the required time and feature selection as well as the classification is done in a separate stage. The feature selection process is done by using the Enhanced Shuffled Frog Leaping (ESFL) algorithm and the selected features are...
International Journal of System Dynamics Applications
With the advances of networks and sensing technologies, it is possible to benefit from the surrou... more With the advances of networks and sensing technologies, it is possible to benefit from the surrounding environment's data in enhancing peoples' life. Currently, we have different types of networks such as Wireless Sensor Networks (WSNs), Vehicle Ad Hoc Networks (VANETs), Cellular Networks (CNs), and Social Networks (SNs) along with underlying computing such as Cloud computing. These types of networks provide huge data about the surrounding environments including weather information, peoples' relations, peoples' interest, and location information. This paper examines the suitability of hierarchal fuzzy logic controller in classifying the IoT data. The paper also tries to answer “if-else “questions about the effect of each of the input parameters. The authors' test case in this paper is related to the disease spreading prediction problem. This test case is highly important to the health care organizations. Different case studies are generated to examine the efficie...
— Wireless Sensor Network (WSN) is a network of portable and lightweight sensors used to monitor ... more — Wireless Sensor Network (WSN) is a network of portable and lightweight sensors used to monitor a specific field and report the data they detect wirelessly to a sink node responsible for the analysis and decision making. WSNs have limited power as well as resources. More advanced sensors known as " multimodal sensors " can report more than one feature, which requires even more efficient utilization of the power. Clustering lessens the amount of power lost in WSN. Many clustering algorithms have been proposed for WSNs. However, up to our knowledge, this is the first work that considers multimodal WSNs. In this paper, we propose new techniques for efficient clustering in Multimodal WSN. Through an extensive set of experiments, our proposed algorithms applied to Fuzzy C-Means and K-Means , which are not designed for WSN, have showed an outperformance over LEACH-C, which is a clustering algorithm designed especially for WSN.
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