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...
Journal of Agricultural Chemistry and Biotechnology, 2014
Six diverse wheat cultivars (Triticum aestivum L.) were used in a partial-diallel crosses to prod... more Six diverse wheat cultivars (Triticum aestivum L.) were used in a partial-diallel crosses to produce 15 F1, hybrids. Genetical analysis and heritability, was estimated for days to heading, days to maturity, grain filling period, plant height, spike length, number of spikes /plant, 1000-grain weight, number of kernels per spike, grain yield/ plant and grain protein content. Mather and Jinks (1971) and Hayman(1954 a and b) methods were used to estimate the genetic parameters for studied characters. Significant mean squares were obtained for genotypes, parents and crosses for all traits studied under the three nitrogen levels. Thus, the parental cultivars displayed enough of genetic variability. The significant of mean squares for parents vs. crosses provide evidence for heterosis. Moreover, nitrogen mean squares were significant indicating that these characters behaved differently from one nitrogen level to another. The local wheat cultivar Shandaweel1 (P3) was superior for giving higher number of grains/spike, 1000-grain weight and grain protein content % while Gemmeiza9(P4) was the best for giving more number of spikes/plant and grain yield. Meanwhile the cross combination (Shandaweel1×Gemmeiza9 gave the heaviest 1000-grain weight ant the maximum value of number of grains/spike and grain yield /plant was obtained by the cross (P1×P5). These results hold true under the three nitrogen levels. The additive genetic variances (D) were significant for most of studied traits under three nitrogen fertilization levels. Significant values for the dominance components (H1) were obtained for all traits under three nitrogen fertilizer levels. Values of (H1) were larger in magnitude than their respective (D) ones for all traits under three nitrogen levels. Values of H2 were found to be smaller than H1 for all traits under the three nitrogen levels. Studies on degree of dominance revealed the presence of over dominance for days to maturity, grain filling period, plant height, spike length, number of grains per spike, grain yield per plant and grain protein content at the three nitrogen level. The average degree of dominance (H1/D) 1/2 were found to be nearly equal unity for days to heading and 1000 grain weight at low nitrogen fertilization indicating that these characters were controlled by compelet dominance. The proportion of genes with positive and negative effects in the parents as indicated by H2/4H1 were lese than its maximum value (0.25) at the three nitrogen fertilization levels for days to heading, grain filling period, plant height, number of spikes/plant and grain protein content% suggesting asymmetrical distribution of positive and negative alleles among the parental population. While, it was near to its maximum value (0.25) for 1000-grain weight and grain yield/plant at low and medium N fertilization levels, days to maturity and number of grains/spike at 75kg.N./fad. indicating equal distribution of positive and negative alleles. Estimates of the ratio of dominant to recessive alleles in the parents KD/KR were more than unity for most of the studied characters revealing more frequency of dominant alleles. The heritability estimates ranged from 7.9 % for grain filling period at medium N fertilization to 69.5% for 1000-grain weight in the third nitrogen level. Low heritability estimates were detected for grain filling period, main spike length, grain yield/plant and grain protein content% at the three nitrogen levels Gebrel,E.M.A.H. et al. 202 indicating that most of the genetic variance may be due to non-additive genetic effect and was a fleeted by environmental factors, hereby selection should be delayed to later generations.
Rule-based systems generate many of the redundant rules; such rules are expensive especially in o... more Rule-based systems generate many of the redundant rules; such rules are expensive especially in online systems. Currently, there are many of the available rule minimization techniques; however, they still suffer from high complexity and lack of efficiency. In this paper, we introduce a novel method (QMR) based on Quine-McCluskey (Q-M) algorithm. The novelty of our algorithm is in the adaptation of Q-M that is used in reducing Boolean expressions to the rule minimization. Our minimization method is very simple and supports many items (variables). In addition, we propose an encoding method that reduces the size of any given data set. This encoding utilizes the usage of binary numbers which fits Q-M simplification method. The encoding is very simple to be automated as well as Q-M algorithm. This research shows a proof of concept examples as well as rule minimization test cases. We compare our algorithm to ID3 which is one of the most used algorithms in rule based systems; especially in networks. However, ID3 does not support more than two states output in contrast to our QMR algorithm which support as many as output states. Therefore, our comparison with ID3 will be limited to the two state output test cases; another test case will be conducted to show the applicability of our approach to more than two states output.
This paper proposes a Billiards algorithm for two sensor deployment problems, random and determin... more This paper proposes a Billiards algorithm for two sensor deployment problems, random and deterministic deployment. The deployment considers both homogenous and heterogeneous sensors. The algorithm aims to maximize the coverage of a given monitored field with obstacles. The coverage is maximized by avoiding sensors overlapping and minimizing the uncovered areas. By adjusting the expansion ratio, the algorithm was able to find the best sensing ranges that maximize the field coverage. The conducted experiments point out the effect of expansion ratio, iterations between expansions, number of collisions, and mobility, on the overall coverage. At the same time, Billiards algorithm shows significant improvement in the coverage performance from the initial field's coverage.
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...
Sentiment analysis using stemmed Twitter data from various languages is an emerging research topi... more Sentiment analysis using stemmed Twitter data from various languages is an emerging research topic. In this paper, we address three data augmentation techniques namely Shift, Shuffle, and Hybrid to increase the size of the training data; and then we use three key types of deep learning (DL) models namely recurrent neural network (RNN), convolution neural network (CNN), and hierarchical attention network (HAN) to classify the stemmed Turkish Twitter data for sentiment analysis. The performance of these DL models has been compared with the existing traditional machine learning (TML) models. The performance of TML models has been affected negatively by the stemmed data, but the performance of DL models has been improved greatly with the utilization of the augmentation techniques. Based on the simulation, experimental, and statistical results analysis deeming identical datasets, it has been concluded that the TML models outperform the DL models with respect to both training-time (TTM) and runtime (RTM) complexities of the algorithms; but the DL models outperform the TML models with respect to the most important performance factors as well as the average performance rankings.
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 % . ...
In this paper, an analytical model of a proposed low-cost high efficiency NPN silicon-based solar... more In this paper, an analytical model of a proposed low-cost high efficiency NPN silicon-based solar cell structure is presented. The structure is based on using low cost heavily doped commercially available silicon wafers and proposed to be fabricated by the same steps as the conventional solar cells except an extra deep trench etch step. Moreover, the cell has been engineered to react to the UV spectrum, resulting in a greater conversion performance. The presented analytical model takes the electrical and optical characteristics into account. Thus, the influence of both physical and technological parameters on the structure performance could be easily examined. Consequently, the optimization of the structure performance becomes visible. To inspect the validity of the analytical model, a comparison of the main performance parameters resulting from the model results with TCAD simulations is carried out, showing good agreement. INDEX TERMS Low cost, high efficiency, high-doped wafers, solar cell, analytical model.
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...
Wireless Sensor Networks (WSNs) is the base for many critical applications where a large number o... more Wireless Sensor Networks (WSNs) is the base for many critical applications where a large number of nodes are deployed in the monitored field. Those nodes suffer from limited processing capabilities as well as energy. They are also required to live for a long time; sensors send their data to the sink node through multi-hop routing. The sink node is responsible for making the appropriate decision based on the received data. This shows how critical the information fusion process at the sink node. Such fusion is affected by the quality of the collected information from the deployed sensors. In addition, information handling in the WSN is also affected by environmental conditions, sensors energy, and data reliability, which play important roles in the eminence of information fusion. This paper introduces an efficient environment-aware fusionbased reliable routing algorithm named E3AF. The algorithm takes different parameters into consideration, including environmental metrics, energy consumption balance among sensor nodes, and network and data reliability. The algorithm models the environment to allow the routing algorithm to avoid going through areas marked dangerous. The paper formulates the problem into an optimization problem, which is structured as an Integer Linear programming (ILP) to help grasp and obtain the optimum solution. Furthermore, the paper presents swarm intelligence as a heuristic algorithm when the optimal solution is not possible. In comparison to EFMRP, some of the used equations were corrected, and more realistic conditions and constraints were added. With extensive experiments, the proposed algorithm is evaluated and proved its efficiency.
Many industrial wireless sensor network (IWSN) applications require real-time communications in w... more Many industrial wireless sensor network (IWSN) applications require real-time communications in which bounded delay requirements need to be satisfied. IWSN lossy links and limited resources of sensor nodes pose significant challenges for supporting real-time applications. Many IWSN routing algorithms focus on being energy efficient to extend the network lifetime, but the delay wasn't the main concern. However, these algorithms are unable to deal with real-time applications in which data packets need to be delivered to the sink node within a predefined real-time information. On the other hand, the most existing real-time routing schemes are often based on the desired deadline time (required delivery time) and end-to-end distance in the selection of forwarding node while the reliability of on-time data delivery, the effects of a collision, energy balance, and a number of a hop count to the sink node have largely been ignored. These issues can dramatically impact real-time performance. Therefore, the paper proposes a routing algorithm that achieves a balance between energy efficiency and reliability while being suitable for real-time applications as well. In addition, it reduces the effects of congestion by sufficiently utilizing the underloaded nodes to improve network throughput. Finally, the hop count to the sink is considered. This paper formulates the real-time routing problem into 0/1 Integer Linear Programming (ILP) problem and then proposes a Real-time Energy-Efficient Traffic-Aware approach (RTERTA) to solve the optimization problem for a large-scale IWSN. From the obtained simulation results, the proposed solution has proved to be able to enhance the network performance in terms of packets miss ratio, average end-to-end delay, packets delivery rate, as well as network lifetime.
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...
Journal of Agricultural Chemistry and Biotechnology, 2014
Six diverse wheat cultivars (Triticum aestivum L.) were used in a partial-diallel crosses to prod... more Six diverse wheat cultivars (Triticum aestivum L.) were used in a partial-diallel crosses to produce 15 F1, hybrids. Genetical analysis and heritability, was estimated for days to heading, days to maturity, grain filling period, plant height, spike length, number of spikes /plant, 1000-grain weight, number of kernels per spike, grain yield/ plant and grain protein content. Mather and Jinks (1971) and Hayman(1954 a and b) methods were used to estimate the genetic parameters for studied characters. Significant mean squares were obtained for genotypes, parents and crosses for all traits studied under the three nitrogen levels. Thus, the parental cultivars displayed enough of genetic variability. The significant of mean squares for parents vs. crosses provide evidence for heterosis. Moreover, nitrogen mean squares were significant indicating that these characters behaved differently from one nitrogen level to another. The local wheat cultivar Shandaweel1 (P3) was superior for giving higher number of grains/spike, 1000-grain weight and grain protein content % while Gemmeiza9(P4) was the best for giving more number of spikes/plant and grain yield. Meanwhile the cross combination (Shandaweel1×Gemmeiza9 gave the heaviest 1000-grain weight ant the maximum value of number of grains/spike and grain yield /plant was obtained by the cross (P1×P5). These results hold true under the three nitrogen levels. The additive genetic variances (D) were significant for most of studied traits under three nitrogen fertilization levels. Significant values for the dominance components (H1) were obtained for all traits under three nitrogen fertilizer levels. Values of (H1) were larger in magnitude than their respective (D) ones for all traits under three nitrogen levels. Values of H2 were found to be smaller than H1 for all traits under the three nitrogen levels. Studies on degree of dominance revealed the presence of over dominance for days to maturity, grain filling period, plant height, spike length, number of grains per spike, grain yield per plant and grain protein content at the three nitrogen level. The average degree of dominance (H1/D) 1/2 were found to be nearly equal unity for days to heading and 1000 grain weight at low nitrogen fertilization indicating that these characters were controlled by compelet dominance. The proportion of genes with positive and negative effects in the parents as indicated by H2/4H1 were lese than its maximum value (0.25) at the three nitrogen fertilization levels for days to heading, grain filling period, plant height, number of spikes/plant and grain protein content% suggesting asymmetrical distribution of positive and negative alleles among the parental population. While, it was near to its maximum value (0.25) for 1000-grain weight and grain yield/plant at low and medium N fertilization levels, days to maturity and number of grains/spike at 75kg.N./fad. indicating equal distribution of positive and negative alleles. Estimates of the ratio of dominant to recessive alleles in the parents KD/KR were more than unity for most of the studied characters revealing more frequency of dominant alleles. The heritability estimates ranged from 7.9 % for grain filling period at medium N fertilization to 69.5% for 1000-grain weight in the third nitrogen level. Low heritability estimates were detected for grain filling period, main spike length, grain yield/plant and grain protein content% at the three nitrogen levels Gebrel,E.M.A.H. et al. 202 indicating that most of the genetic variance may be due to non-additive genetic effect and was a fleeted by environmental factors, hereby selection should be delayed to later generations.
Rule-based systems generate many of the redundant rules; such rules are expensive especially in o... more Rule-based systems generate many of the redundant rules; such rules are expensive especially in online systems. Currently, there are many of the available rule minimization techniques; however, they still suffer from high complexity and lack of efficiency. In this paper, we introduce a novel method (QMR) based on Quine-McCluskey (Q-M) algorithm. The novelty of our algorithm is in the adaptation of Q-M that is used in reducing Boolean expressions to the rule minimization. Our minimization method is very simple and supports many items (variables). In addition, we propose an encoding method that reduces the size of any given data set. This encoding utilizes the usage of binary numbers which fits Q-M simplification method. The encoding is very simple to be automated as well as Q-M algorithm. This research shows a proof of concept examples as well as rule minimization test cases. We compare our algorithm to ID3 which is one of the most used algorithms in rule based systems; especially in networks. However, ID3 does not support more than two states output in contrast to our QMR algorithm which support as many as output states. Therefore, our comparison with ID3 will be limited to the two state output test cases; another test case will be conducted to show the applicability of our approach to more than two states output.
This paper proposes a Billiards algorithm for two sensor deployment problems, random and determin... more This paper proposes a Billiards algorithm for two sensor deployment problems, random and deterministic deployment. The deployment considers both homogenous and heterogeneous sensors. The algorithm aims to maximize the coverage of a given monitored field with obstacles. The coverage is maximized by avoiding sensors overlapping and minimizing the uncovered areas. By adjusting the expansion ratio, the algorithm was able to find the best sensing ranges that maximize the field coverage. The conducted experiments point out the effect of expansion ratio, iterations between expansions, number of collisions, and mobility, on the overall coverage. At the same time, Billiards algorithm shows significant improvement in the coverage performance from the initial field's coverage.
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...
Sentiment analysis using stemmed Twitter data from various languages is an emerging research topi... more Sentiment analysis using stemmed Twitter data from various languages is an emerging research topic. In this paper, we address three data augmentation techniques namely Shift, Shuffle, and Hybrid to increase the size of the training data; and then we use three key types of deep learning (DL) models namely recurrent neural network (RNN), convolution neural network (CNN), and hierarchical attention network (HAN) to classify the stemmed Turkish Twitter data for sentiment analysis. The performance of these DL models has been compared with the existing traditional machine learning (TML) models. The performance of TML models has been affected negatively by the stemmed data, but the performance of DL models has been improved greatly with the utilization of the augmentation techniques. Based on the simulation, experimental, and statistical results analysis deeming identical datasets, it has been concluded that the TML models outperform the DL models with respect to both training-time (TTM) and runtime (RTM) complexities of the algorithms; but the DL models outperform the TML models with respect to the most important performance factors as well as the average performance rankings.
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 % . ...
In this paper, an analytical model of a proposed low-cost high efficiency NPN silicon-based solar... more In this paper, an analytical model of a proposed low-cost high efficiency NPN silicon-based solar cell structure is presented. The structure is based on using low cost heavily doped commercially available silicon wafers and proposed to be fabricated by the same steps as the conventional solar cells except an extra deep trench etch step. Moreover, the cell has been engineered to react to the UV spectrum, resulting in a greater conversion performance. The presented analytical model takes the electrical and optical characteristics into account. Thus, the influence of both physical and technological parameters on the structure performance could be easily examined. Consequently, the optimization of the structure performance becomes visible. To inspect the validity of the analytical model, a comparison of the main performance parameters resulting from the model results with TCAD simulations is carried out, showing good agreement. INDEX TERMS Low cost, high efficiency, high-doped wafers, solar cell, analytical model.
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...
Wireless Sensor Networks (WSNs) is the base for many critical applications where a large number o... more Wireless Sensor Networks (WSNs) is the base for many critical applications where a large number of nodes are deployed in the monitored field. Those nodes suffer from limited processing capabilities as well as energy. They are also required to live for a long time; sensors send their data to the sink node through multi-hop routing. The sink node is responsible for making the appropriate decision based on the received data. This shows how critical the information fusion process at the sink node. Such fusion is affected by the quality of the collected information from the deployed sensors. In addition, information handling in the WSN is also affected by environmental conditions, sensors energy, and data reliability, which play important roles in the eminence of information fusion. This paper introduces an efficient environment-aware fusionbased reliable routing algorithm named E3AF. The algorithm takes different parameters into consideration, including environmental metrics, energy consumption balance among sensor nodes, and network and data reliability. The algorithm models the environment to allow the routing algorithm to avoid going through areas marked dangerous. The paper formulates the problem into an optimization problem, which is structured as an Integer Linear programming (ILP) to help grasp and obtain the optimum solution. Furthermore, the paper presents swarm intelligence as a heuristic algorithm when the optimal solution is not possible. In comparison to EFMRP, some of the used equations were corrected, and more realistic conditions and constraints were added. With extensive experiments, the proposed algorithm is evaluated and proved its efficiency.
Many industrial wireless sensor network (IWSN) applications require real-time communications in w... more Many industrial wireless sensor network (IWSN) applications require real-time communications in which bounded delay requirements need to be satisfied. IWSN lossy links and limited resources of sensor nodes pose significant challenges for supporting real-time applications. Many IWSN routing algorithms focus on being energy efficient to extend the network lifetime, but the delay wasn't the main concern. However, these algorithms are unable to deal with real-time applications in which data packets need to be delivered to the sink node within a predefined real-time information. On the other hand, the most existing real-time routing schemes are often based on the desired deadline time (required delivery time) and end-to-end distance in the selection of forwarding node while the reliability of on-time data delivery, the effects of a collision, energy balance, and a number of a hop count to the sink node have largely been ignored. These issues can dramatically impact real-time performance. Therefore, the paper proposes a routing algorithm that achieves a balance between energy efficiency and reliability while being suitable for real-time applications as well. In addition, it reduces the effects of congestion by sufficiently utilizing the underloaded nodes to improve network throughput. Finally, the hop count to the sink is considered. This paper formulates the real-time routing problem into 0/1 Integer Linear Programming (ILP) problem and then proposes a Real-time Energy-Efficient Traffic-Aware approach (RTERTA) to solve the optimization problem for a large-scale IWSN. From the obtained simulation results, the proposed solution has proved to be able to enhance the network performance in terms of packets miss ratio, average end-to-end delay, packets delivery rate, as well as network lifetime.
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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