Sameer Alsharif - Academia.edu (original) (raw)
Papers by Sameer Alsharif
Journal of Energy Storage
International Journal of Photoenergy
As a freely available energy source for managing long-term issues in energy crisis, solar energy ... more As a freely available energy source for managing long-term issues in energy crisis, solar energy (SE) will have to grow more to meet world’s energy demands. Maghreb countries have launched international tenders for large-scale solar power projects, confirming north African countries’ goals to become green-power leaders, by enforcing renewable energy development policies. This work is aimed at simulating and designing a SE cooler to safely store quality and tasty dates. By optimizing the storage parameters and cooling gas with less energy consumption, R152a has been confirmed as a reliable refrigerant to own high critical temperature, sufficient specific heat capacity, and potential cost-effectiveness of compression. Safe packaging in Tolga-Algeria-Dates food company can be achieved by safe cooling systems that is aimed at wide variation of energy storage and delivery requirements of the manufacturing process. The performance ratio ( P R ) and energy losses have been analyzed by usin...
Combustion-chamber is a critical component of the propulsion engine, which is widelyused in the s... more Combustion-chamber is a critical component of the propulsion engine, which is widelyused in the space industry and aeronautics. The goal of this article is to perform a numericalanalysis on the combustion process using a liquid-type propellant. The steps that must be followeduntil total combustion is achieved are emphasized. It concerns the fuel feeding phase, its injectionand the combustion operation. The amount of combustion products and the energy generated areevaluated. It has been shown that the liquid propellant may present an efficient alternative fuelthan the kerosene. In addition, the temperature of combustion does not exceed a certain limit toavoid structural problems in the chamber. The parametric survey allowed determining the range ofthe most influence factors, including the pressure, mixture richness, velocity and flow rates ofinjection for the fuel and oxidizer. The number and type of injectors revealed a considerableinfluence on the velocity and flow rates of injecti...
Intelligent Automation & Soft Computing
Non-orthogonal multiple access (NOMA) is one of the promising 5G technologies to improve spectral... more Non-orthogonal multiple access (NOMA) is one of the promising 5G technologies to improve spectral efficiency massive connectivity and cell-edge throughput. The performance of NOMA systems mainly depends on the efficiency of the subcarrier allocation algorithm. This paper aims to jointly optimize spectral efficiency (SE), outage probability, and fairness among users with respect to the subcarrier allocation for downlink NOMA systems. We propose a low-complexity greedy-based subcarrier allocation algorithm based on the lowest-opportunities user's first precept. This precept is based on computing the number of opportunities for each user to select a subcarrier with good channel gain by counting the number of available subcarriers with channel gains higher than a particular threshold value. So, the proposed algorithm allows the users with low opportunities to select their desired subcarriers first and hence improves their achieved data rates. Simulation results demonstrate that compared to orthogonal multiple access (OMA), and traditional NOMA algorithms, the proposed subcarrier allocation algorithm attains significantly superior spectral efficiency, fairness performance, user data rate, and outage probability. In addition, the proposed algorithm's performance metrics improve as the number of users in the system increases, contrary to traditional NOMA algorithms.
Computers, Materials & Continua
Due to the difficulties of brain tumor segmentation, this paper proposes a strategy for extractin... more Due to the difficulties of brain tumor segmentation, this paper proposes a strategy for extracting brain tumors from three-dimensional Magnetic Resonance Image (MRI) and Computed Tomography (CT) scans utilizing 3D U-Net Design and ResNet50, taken after by conventional classification strategies. In this inquire, the ResNet50 picked up accuracy with 98.96%, and the 3D U-Net scored 97.99% among the different methods of deep learning. It is to be mentioned that traditional Convolutional Neural Network (CNN) gives 97.90% accuracy on top of the 3D MRI. In expansion, the image fusion approach combines the multimodal images and makes a fused image to extricate more highlights from the medical images. Other than that, we have identified the loss function by utilizing several dice measurements approach and received Dice Result on top of a specific test case. The average mean score of dice coefficient and soft dice loss for three test cases was 0.0980. At the same time, for two test cases, the sensitivity and specification were recorded to be 0.0211 and 0.5867 using patch level predictions. On the other hand, a software integration pipeline was integrated to deploy the concentrated model into the webserver for accessing it from the software system using the Representational state transfer (REST) API. Eventually, the suggested models were validated through the Area Under the Curve-Receiver Characteristic Operator (AUC-ROC) curve and Confusion Matrix and compared with the existing research articles to understand the underlying problem. Through Comparative Analysis, we have extracted meaningful insights regarding brain tumour segmentation and figured out potential gaps. Nevertheless, the proposed model can be adjustable in daily life and the healthcare domain to 4510 CMC, 2022, vol.72, no.3 identify the infected regions and cancer of the brain through various imaging modalities.
Wireless Personal Communications, 2021
Computers, Materials & Continua, 2022
Internet of Things (IoT) defines a network of devices connected to the internet and sharing a mas... more Internet of Things (IoT) defines a network of devices connected to the internet and sharing a massive amount of data between each other and a central location. These IoT devices are connected to a network therefore prone to attacks. Various management tasks and network operations such as security, intrusion detection, Quality-of-Service provisioning, performance monitoring, resource provisioning, and traffic engineering require traffic classification. Due to the ineffectiveness of traditional classification schemes, such as port-based and payload-based methods, researchers proposed machine learning-based traffic classification systems based on shallow neural networks. Furthermore, machine learning-based models incline to misclassify internet traffic due to improper feature selection. In this research, an efficient multilayer deep learning based classification system is presented to overcome these challenges that can classify internet traffic. To examine the performance of the proposed technique, Moore-dataset is used for training the classifier. The proposed scheme takes the pre-processed data and extracts the flow features using a deep neural network (DNN). In particular, the maximum entropy classifier is used to classify the internet traffic. The experimental results show that the proposed hybrid deep learning algorithm is effective and achieved high accuracy for internet traffic classification, i.e., 99.23%. Furthermore, the proposed algorithm achieved the highest accuracy compared to the support vector machine (SVM) based classification technique and k-nearest neighbours (KNNs) based classification technique.
IEEE Access, 2022
This paper proposes triangular region representations based on keypoints detected in images with ... more This paper proposes triangular region representations based on keypoints detected in images with viewpoint changes. The strongest keypoints in the reference and query images are allocated individually using a previously published contourlet-based approach to determine the keypoints. These selected keypoints serve as vertices of the triangular regions to be transformed into rectangular representations as simple numeric matrices. The suggested representation methods used to form rectangular matrices are full triangle representation (FTR) and a lighter representation called triangle medians and sides representation (TMSR). For the former, the intensity values along the lines connecting the anchor keypoint to the points between the other two triangular vertices form the rows of the representation matrix. These two triangle vertices are located in an allotted window around the anchor keypoint from the nearby keypoints. For the latter, the intensity values on the six triangular lines, medians, and sides formed the resulting rectangular matrix. The proposed representations are validated for image-matching applications using a descriptor-less matching method. Moreover, the performances of these algorithms are compared with those of traditional algorithms. The results confirmed the superiority of the proposed method over these algorithms. INDEX TERMS Affine transformation, image matching, keypoints, triangular region representation. IBRAHIM EL RUBE' (Senior Member, IEEE) received the B.Eng. degree from the Department of Computer and Electronics Engineering, in 1992, the M.Sc. degree in electronics and communications engineering from the Arab Academy for Science and Technology, Egypt, in 1999, and the Ph.D. degree in systems design engineering from the
2013 IEEE Energytech, 2013
Computers, Materials & Continua
The rapid development in the information technology field has introduced digital watermark techno... more The rapid development in the information technology field has introduced digital watermark technologies as a solution to prevent unauthorized copying and redistribution of data. This article introduces a self-embedded image verification and integrity scheme. The images are firstly split into dedicated segments of the same block sizes. Then, different Analytic Beta-Wavelet (ABW) orthogonal filters are utilized for embedding a self-segment watermark for image segment using a predefined method. ABW orthogonal filter coefficients are estimated to improve image reconstruction under different block sizes. We conduct a comparative study comparing the watermarked images using three kinds of ABW filters for block sizes 64 × 64, 128 × 128, and 256 × 256. We embed the watermark using the ABW-based image watermarking method in the 2-level middle frequency sub-bands of the ABW digital image coefficients. The imperceptibility and robustness of the ABW-based image watermarking method image is evaluated based on the Peak Signal to Noise Ratio (PSNR) and Correlation coefficient values. From the implementation results, we came to know that this ABW-based image watermarking method can withstand many image manipulations compared to other existing methods.
Wireless Personal Communications
Intelligent Automation & Soft Computing
This paper proposes a new cross-layer communication system for the provision of Internet services... more This paper proposes a new cross-layer communication system for the provision of Internet services and applications to mitigate the negative impacts of COVID-19, due to which the massive online demands are affecting the current communication systems' infrastructures and capabilities. The system requirements and model are investigated where it utilizes high-altitude platform (HAP) for fast and efficient connectivity provision to bridge the communication infrastructure gap in the current pandemic. The HAP is linked to the main server or gateway station located on ground and can provide communication narrow beams towards isolated areas which suffer from poor terrestrial radio coverage or lack of communication infrastructure. The vital e-learning applications using Internet services provision from the proposed HAP system are described and modelled including system adaptation parameters such as the application and physical layers to control the data rates of different e-learning applications and the overall cell data rate. On the other hand, the provision of high-speed Internet services from the proposed system is supported by using adaptive antenna arrays onboard HAP which provides high-gain beams to achieve the required high-quality transmission data rates at the student premises and provides the capability of coverage cell area adaptation for load balancing. The concentric circular antenna arrays with tapered feeding are proposed in this adaptive antenna system to control the cell mainlobe gain and reduce the out-of-coverage radiation as well. In addition, the system feasibility has been proved in two coverage scenarios including single-beam and multibeam HAP communications.
2021 National Computing Colleges Conference (NCCC)
IEEE Access
This paper proposes a novel optimization-based power sharing control strategy to moderate PV powe... more This paper proposes a novel optimization-based power sharing control strategy to moderate PV power intermittency and increase its penetration. Such a control strategy aims to minimize the total PV power sensitivity to the light change by redistributing the demand power among available PV units such that the demanding power is met with minimal variation. PV plant is coupled with the grid utility, and it should maintain a specific amount of power determined by the grid operator. However, due to the PV power sensitivity to the light, the delivered power at the coupling point fluctuates and leads to undesirable responses such as grid frequency excursion, stability problems, and unoptimized power generation. To address such issues, we formulate an optimization problem to reduce the total PV power sensitivity by selecting the optimal reference voltage for each PV panel. We define the power sensitivity as the rate of power change to light fluctuation to be the objective function of the proposed optimization problem, and the selected reference voltages for all PV panels are the decision variables. Compared to other conventional powersharing techniques such as the same utilization level, droop control, and lookup table, MATLAB simulation results verify the contribution of the proposed algorithm's performance superiority in PV power sensitivity reduction, grid stability assurance, and power generation enhancement. Moreover, when there is insufficient PV power to meet the grid operator's demand, the proposed algorithm automatically sets the entire PV plant to work at its MPP without switching circuits.
Journal of Energy Storage
International Journal of Photoenergy
As a freely available energy source for managing long-term issues in energy crisis, solar energy ... more As a freely available energy source for managing long-term issues in energy crisis, solar energy (SE) will have to grow more to meet world’s energy demands. Maghreb countries have launched international tenders for large-scale solar power projects, confirming north African countries’ goals to become green-power leaders, by enforcing renewable energy development policies. This work is aimed at simulating and designing a SE cooler to safely store quality and tasty dates. By optimizing the storage parameters and cooling gas with less energy consumption, R152a has been confirmed as a reliable refrigerant to own high critical temperature, sufficient specific heat capacity, and potential cost-effectiveness of compression. Safe packaging in Tolga-Algeria-Dates food company can be achieved by safe cooling systems that is aimed at wide variation of energy storage and delivery requirements of the manufacturing process. The performance ratio ( P R ) and energy losses have been analyzed by usin...
Combustion-chamber is a critical component of the propulsion engine, which is widelyused in the s... more Combustion-chamber is a critical component of the propulsion engine, which is widelyused in the space industry and aeronautics. The goal of this article is to perform a numericalanalysis on the combustion process using a liquid-type propellant. The steps that must be followeduntil total combustion is achieved are emphasized. It concerns the fuel feeding phase, its injectionand the combustion operation. The amount of combustion products and the energy generated areevaluated. It has been shown that the liquid propellant may present an efficient alternative fuelthan the kerosene. In addition, the temperature of combustion does not exceed a certain limit toavoid structural problems in the chamber. The parametric survey allowed determining the range ofthe most influence factors, including the pressure, mixture richness, velocity and flow rates ofinjection for the fuel and oxidizer. The number and type of injectors revealed a considerableinfluence on the velocity and flow rates of injecti...
Intelligent Automation & Soft Computing
Non-orthogonal multiple access (NOMA) is one of the promising 5G technologies to improve spectral... more Non-orthogonal multiple access (NOMA) is one of the promising 5G technologies to improve spectral efficiency massive connectivity and cell-edge throughput. The performance of NOMA systems mainly depends on the efficiency of the subcarrier allocation algorithm. This paper aims to jointly optimize spectral efficiency (SE), outage probability, and fairness among users with respect to the subcarrier allocation for downlink NOMA systems. We propose a low-complexity greedy-based subcarrier allocation algorithm based on the lowest-opportunities user's first precept. This precept is based on computing the number of opportunities for each user to select a subcarrier with good channel gain by counting the number of available subcarriers with channel gains higher than a particular threshold value. So, the proposed algorithm allows the users with low opportunities to select their desired subcarriers first and hence improves their achieved data rates. Simulation results demonstrate that compared to orthogonal multiple access (OMA), and traditional NOMA algorithms, the proposed subcarrier allocation algorithm attains significantly superior spectral efficiency, fairness performance, user data rate, and outage probability. In addition, the proposed algorithm's performance metrics improve as the number of users in the system increases, contrary to traditional NOMA algorithms.
Computers, Materials & Continua
Due to the difficulties of brain tumor segmentation, this paper proposes a strategy for extractin... more Due to the difficulties of brain tumor segmentation, this paper proposes a strategy for extracting brain tumors from three-dimensional Magnetic Resonance Image (MRI) and Computed Tomography (CT) scans utilizing 3D U-Net Design and ResNet50, taken after by conventional classification strategies. In this inquire, the ResNet50 picked up accuracy with 98.96%, and the 3D U-Net scored 97.99% among the different methods of deep learning. It is to be mentioned that traditional Convolutional Neural Network (CNN) gives 97.90% accuracy on top of the 3D MRI. In expansion, the image fusion approach combines the multimodal images and makes a fused image to extricate more highlights from the medical images. Other than that, we have identified the loss function by utilizing several dice measurements approach and received Dice Result on top of a specific test case. The average mean score of dice coefficient and soft dice loss for three test cases was 0.0980. At the same time, for two test cases, the sensitivity and specification were recorded to be 0.0211 and 0.5867 using patch level predictions. On the other hand, a software integration pipeline was integrated to deploy the concentrated model into the webserver for accessing it from the software system using the Representational state transfer (REST) API. Eventually, the suggested models were validated through the Area Under the Curve-Receiver Characteristic Operator (AUC-ROC) curve and Confusion Matrix and compared with the existing research articles to understand the underlying problem. Through Comparative Analysis, we have extracted meaningful insights regarding brain tumour segmentation and figured out potential gaps. Nevertheless, the proposed model can be adjustable in daily life and the healthcare domain to 4510 CMC, 2022, vol.72, no.3 identify the infected regions and cancer of the brain through various imaging modalities.
Wireless Personal Communications, 2021
Computers, Materials & Continua, 2022
Internet of Things (IoT) defines a network of devices connected to the internet and sharing a mas... more Internet of Things (IoT) defines a network of devices connected to the internet and sharing a massive amount of data between each other and a central location. These IoT devices are connected to a network therefore prone to attacks. Various management tasks and network operations such as security, intrusion detection, Quality-of-Service provisioning, performance monitoring, resource provisioning, and traffic engineering require traffic classification. Due to the ineffectiveness of traditional classification schemes, such as port-based and payload-based methods, researchers proposed machine learning-based traffic classification systems based on shallow neural networks. Furthermore, machine learning-based models incline to misclassify internet traffic due to improper feature selection. In this research, an efficient multilayer deep learning based classification system is presented to overcome these challenges that can classify internet traffic. To examine the performance of the proposed technique, Moore-dataset is used for training the classifier. The proposed scheme takes the pre-processed data and extracts the flow features using a deep neural network (DNN). In particular, the maximum entropy classifier is used to classify the internet traffic. The experimental results show that the proposed hybrid deep learning algorithm is effective and achieved high accuracy for internet traffic classification, i.e., 99.23%. Furthermore, the proposed algorithm achieved the highest accuracy compared to the support vector machine (SVM) based classification technique and k-nearest neighbours (KNNs) based classification technique.
IEEE Access, 2022
This paper proposes triangular region representations based on keypoints detected in images with ... more This paper proposes triangular region representations based on keypoints detected in images with viewpoint changes. The strongest keypoints in the reference and query images are allocated individually using a previously published contourlet-based approach to determine the keypoints. These selected keypoints serve as vertices of the triangular regions to be transformed into rectangular representations as simple numeric matrices. The suggested representation methods used to form rectangular matrices are full triangle representation (FTR) and a lighter representation called triangle medians and sides representation (TMSR). For the former, the intensity values along the lines connecting the anchor keypoint to the points between the other two triangular vertices form the rows of the representation matrix. These two triangle vertices are located in an allotted window around the anchor keypoint from the nearby keypoints. For the latter, the intensity values on the six triangular lines, medians, and sides formed the resulting rectangular matrix. The proposed representations are validated for image-matching applications using a descriptor-less matching method. Moreover, the performances of these algorithms are compared with those of traditional algorithms. The results confirmed the superiority of the proposed method over these algorithms. INDEX TERMS Affine transformation, image matching, keypoints, triangular region representation. IBRAHIM EL RUBE' (Senior Member, IEEE) received the B.Eng. degree from the Department of Computer and Electronics Engineering, in 1992, the M.Sc. degree in electronics and communications engineering from the Arab Academy for Science and Technology, Egypt, in 1999, and the Ph.D. degree in systems design engineering from the
2013 IEEE Energytech, 2013
Computers, Materials & Continua
The rapid development in the information technology field has introduced digital watermark techno... more The rapid development in the information technology field has introduced digital watermark technologies as a solution to prevent unauthorized copying and redistribution of data. This article introduces a self-embedded image verification and integrity scheme. The images are firstly split into dedicated segments of the same block sizes. Then, different Analytic Beta-Wavelet (ABW) orthogonal filters are utilized for embedding a self-segment watermark for image segment using a predefined method. ABW orthogonal filter coefficients are estimated to improve image reconstruction under different block sizes. We conduct a comparative study comparing the watermarked images using three kinds of ABW filters for block sizes 64 × 64, 128 × 128, and 256 × 256. We embed the watermark using the ABW-based image watermarking method in the 2-level middle frequency sub-bands of the ABW digital image coefficients. The imperceptibility and robustness of the ABW-based image watermarking method image is evaluated based on the Peak Signal to Noise Ratio (PSNR) and Correlation coefficient values. From the implementation results, we came to know that this ABW-based image watermarking method can withstand many image manipulations compared to other existing methods.
Wireless Personal Communications
Intelligent Automation & Soft Computing
This paper proposes a new cross-layer communication system for the provision of Internet services... more This paper proposes a new cross-layer communication system for the provision of Internet services and applications to mitigate the negative impacts of COVID-19, due to which the massive online demands are affecting the current communication systems' infrastructures and capabilities. The system requirements and model are investigated where it utilizes high-altitude platform (HAP) for fast and efficient connectivity provision to bridge the communication infrastructure gap in the current pandemic. The HAP is linked to the main server or gateway station located on ground and can provide communication narrow beams towards isolated areas which suffer from poor terrestrial radio coverage or lack of communication infrastructure. The vital e-learning applications using Internet services provision from the proposed HAP system are described and modelled including system adaptation parameters such as the application and physical layers to control the data rates of different e-learning applications and the overall cell data rate. On the other hand, the provision of high-speed Internet services from the proposed system is supported by using adaptive antenna arrays onboard HAP which provides high-gain beams to achieve the required high-quality transmission data rates at the student premises and provides the capability of coverage cell area adaptation for load balancing. The concentric circular antenna arrays with tapered feeding are proposed in this adaptive antenna system to control the cell mainlobe gain and reduce the out-of-coverage radiation as well. In addition, the system feasibility has been proved in two coverage scenarios including single-beam and multibeam HAP communications.
2021 National Computing Colleges Conference (NCCC)
IEEE Access
This paper proposes a novel optimization-based power sharing control strategy to moderate PV powe... more This paper proposes a novel optimization-based power sharing control strategy to moderate PV power intermittency and increase its penetration. Such a control strategy aims to minimize the total PV power sensitivity to the light change by redistributing the demand power among available PV units such that the demanding power is met with minimal variation. PV plant is coupled with the grid utility, and it should maintain a specific amount of power determined by the grid operator. However, due to the PV power sensitivity to the light, the delivered power at the coupling point fluctuates and leads to undesirable responses such as grid frequency excursion, stability problems, and unoptimized power generation. To address such issues, we formulate an optimization problem to reduce the total PV power sensitivity by selecting the optimal reference voltage for each PV panel. We define the power sensitivity as the rate of power change to light fluctuation to be the objective function of the proposed optimization problem, and the selected reference voltages for all PV panels are the decision variables. Compared to other conventional powersharing techniques such as the same utilization level, droop control, and lookup table, MATLAB simulation results verify the contribution of the proposed algorithm's performance superiority in PV power sensitivity reduction, grid stability assurance, and power generation enhancement. Moreover, when there is insufficient PV power to meet the grid operator's demand, the proposed algorithm automatically sets the entire PV plant to work at its MPP without switching circuits.