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Two-Phase Bidirectional Dual-Relay Selection Strategy for Wireless Relay Networks

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Computers, Materials & Continua 2021年第10期69卷 539-553页

作者： Samer Alabed issam maaz Mohammad Al-Rabayah College of Engineering and Technology American University of the Middle EastKuwait

In this article,we introduce a new bi-directional dual-relay selection strategy with its bit error rate(BER)performance analysis.During the first step of the proposed strategy,two relays out of a set of N relay-nodes are selected in a way to optimize the system performance in terms of BER,based on the suggested algorithm which checks if the selected relays using the maxmin criterion are the best ones.In the second step,the chosen relay-nodes perform an orthogonal space-time coding scheme using the two-phase relaying protocol to establish a bi-directional communication between the communicating terminals,leading to a significant improvement in the achievable coding and diversity gain.To further improve the overall system performance,the selected relay-nodes apply also a digital network coding scheme.Furthermore,this paper discusses the analytical approximation of the BER performance of the proposed strategy,where we prove that the analytical results match almost perfectly the simulated ones.Finally,our simulation results show that the proposed strategy outperforms the current state-of-the-art ones.

关键词： Two-way wireless relay networks cooperative diversity techniques distributed space-time coding relay selection strategies network coding schemes

An Improved Reactive Power Sharing in an Isolated Microgrid with a Local Load Detection

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中国电气工程学报(英文) 2023年第2期9卷 14-26页

作者： issam A.Smadi Luay I.Shehadeh Department of Electrical Engineering Jordan University of Science and TechnologyIrbid 22110Jordan

Accurate reactive power sharing is one of the main issues in isolated microgrids to avoid circulating currents and overloading small distributed generation(DG)units.A simple and enhanced method for improving reactive power sharing among parallel-connected DG systems in an isolated microgrid was proposed.The proposed method uses a compensator term with an integral action to minimize the reactive power-sharing error internally without any need for communication or information shared among the DG units.Moreover,a small disturbance carrying part of the reactive power-sharing error is injected into the active power-droop controller,maintaining the essential system parameters within their allowable limits.Consequently,a simple compensation trigger system is proposed to effectively detect any local load change in the network and provide compensation gains to activate the proposed control method.The stability of the proposed method was verified and analyzed using a detailed small-signal model.Moreover,the effectiveness and robustness of the proposed method were validated through comprehensive simulation studies and comparisons with other related techniques.

关键词： Adaptive droop distributed generation(DG) droop control microgrid power management reactive power-sharing

DC offset rejection in a frequency-fixed second-order generalized integrator-based phase-locked loop for single-phase grid-connected applications

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Protection and Control of Modern Power Systems 2022年第1期7卷 1-13页

作者： issam A.Smadi Bayan H.Bany Fawaz Electrical Engineering Department Jordan University of Science and TechnologyIrbid 22110Jordan

Fast and accurate monitoring of the phase,amplitude,and frequency of the grid voltage is essential for single-phase grid-connected converters.The presence of DC offset in the grid voltage is detrimental to not only grid synchronization but also the closed-loop stability of the grid-connected converters.In this paper,a new synchronization method to mitigate the effect of DC offset is presented using arbitrarily delayed signal cancelation(ADSC)in a second-order generalized integrator(SOGI)phase-locked loop(PLL).A frequency-fixed SOGI-based PLL(FFSOGI-PLL)is adopted to ensure better stability and to reduce the complexity compared with other SOGI-based PLLs.A small-signal model of the proposed PLL is derived for the systematic design of proportional-integral(PI)controller gains.The effects of frequency variation and ADSC on the proposed PLL are considered,and correction methods are adopted to accurately estimate grid information.The simulation results are presented,along with comparisons to other single-phase PLLs in terms of settling time,peak frequency,and phase error to validate the proposed PLL.The dynamic performance of the proposed PLL is also experimentally validated.Overall,the proposed PLL has the fastest transient response and better dynamic performance than the other PLLs for almost all performance indices,offering an improved solution for precise grid synchronization in single-phase applications.

关键词： Grid integration Virtual microgrid DC offset mitigation Grid synchronization Phase-locked loop Second-order generalized integrator

Fast and Accurate Thoracic SPECT Image Reconstruction

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Computer Modeling in Engineering & Sciences 2022年第5期131卷 881-904页

作者： Afef Houimli issam Ben Mhamed Bechir Letaief Dorra Ben-Sellem University of Tunis El Manar Higher Institute of Medical Technologies of TunisResearch Laboratory in Biophysics and Medical Technologies LR13ES07Tunis1006Tunisia University of Tunis Higher National School of Engineers of TunisSignal Image and Energy Management Laboratory:LR13 ES03 SIMEENSITMontfleury1008Tunisia Faculty of Medicine of Tunis University of Tunis El ManarTunis1007Tunisia Nuclear Medicine Department Salah AZAIEZ InstituteTunis1006Tunisia

In Single-Photon Emission Computed Tomography(SPECT),the reconstructed image has insufficient contrast,poor resolution and inaccurate volume of the tumor size due to physical degradation factors.Generally,nonstationary filtering of the projection or the slice is one of the strategies for correcting the resolution and therefore improving the quality of the reconstructed SPECT images.This paper presents a new 3D algorithm that enhances the quality of reconstructed thoracic SPECT images and reduces the noise level with the best degree of accuracy.The suggested algorithm is composed of three steps.The first one consists of denoising the acquired projections using the benefits of the complementary properties of both the Curvelet transformand theWavelet transforms to provide the best noise reduction.The second step is a simultaneous reconstruction of the axial slices using the 3D Ordered Subset Expectation Maximization(OSEM)algorithm.The last step is post-processing of the reconstructed axial slices using one of the newest anisotropic diffusion models named Partial Differential Equation(PDE).The method is tested on two digital phantoms and clinical bone SPECT images.A comparative study with four algorithms reviewed on state of the art proves the significance of the proposed method.In simulated data,experimental results show that the plot profile of the proposed model keeps close to the original one compared to the other algorithms.Furthermore,it presents a notable gain in terms of contrast to noise ratio(CNR)and execution time.The proposed model shows better results in the computation of contrast metric with a value of 0.68±7.2 and the highest signal to noise ratio(SNR)with a value of 78.56±6.4 in real data.The experimental results prove that the proposed algorithm is more accurate and robust in reconstructing SPECT images than the other algorithms.It could be considered a valuable candidate to correct the resolution of bone in the SPECT images.

关键词： SPECT image resolution correction thoracic SPECT images wavelet transform curvelet transforms 3D-OSEM PDE

A Hybrid Heuristic Algorithm for Solving COVID-19’s Social Distancing at Universities Campus

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Computer Systems Science & Engineering 2022年第6期41卷 933-944页

作者： Hassan Al-Tarawneh Khalid Al-Kaabneh Aysh Alhroob Hazem Migdady issam Alhadid Department of Data sciences and Artificial Intelligence Al-Ahlyyia Amman UniversityAmmanJordan Department of Software Engineering Isra UniversityAmmanJordan Department of CSMIS Oman college of management and technologyMuscatOman Faculty of Information Technology and Systems University of JordanAqabaJordan

Social distancing during COVID-19 has become one of the most important measures in reducing the risks of the spread of the virus. Implementing thesemeasures at universities is crucial and directly related to the physical attendance ofthe populations of students, professors, employees, and other members on campus. This research proposes an automated scheduling approach that can help universities and schools comply with the social distancing regulations by providingassistance in avoiding huge assemblages of people. Furthermore, this paper proposes a novel course timetable-scheduling scheme based on four main constraints.First, a distance of two meters must be maintained between each student inside theclassroom. Second, no classrooms should contain more than 20% of their regularcapacity. Third, there would be no back-to-back classes. Lastly, no lectures shouldbe held simultaneously in adjacent classrooms. The proposed approach wasimplemented using a variable neighborhood search (VNS) approach with an adaptive neighborhood structure (AD-NS) to resolve the problem of scheduling coursetimetables at Al-Ahlyyia Amman University. However, the experimental resultsshow that the proposed techniques outperformed the standard VNS tested on university course timetabling benchmark dataset ITC2007-Track3. Meanwhile, theapproach was tested using datasets collected from the faculty of information technology at Al-Ahlyyia Amman University (Jordan). Where the results showed that,the proposed technique could help educational institutes to resume their regularoperations while complying with the social distancing guidelines.

关键词： COVID-19 social distance variable neighborhood search adaptive neighborhood structure university course timetable

Modeling Palestinian COVID-19 Cumulative Confirmed Cases:A Comparative Study

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Infectious Disease Modelling 2020年第1期5卷 748-754页

作者： issam Dawoud Department of Mathematics Al-Aqsa UniversityGazaPalestine

COVID-19 is still a major pandemic threatening all the world.In Palestine,there were 26,764 COVID-19 cumulative confirmed cases as of 27th August 2020.In this paper,two statistical approaches,autoregressive integrated moving average(ARIMA)and k-th moving averages-ARIMA models are used for modeling the COVID-19 cumulative confirmed cases in Palestine.The data was taken from World Health Organization(WHO)website for one hundred seventy-six(176)days,from March 5,2020 through August 27,2020.We identified the best models for the above mentioned approaches that are ARIMA(1,2,4)and 5-th Exponential Weighted Moving Average e ARIMA(2,2,3).Consequently,we recommended to use the 5-th Exponential Weighted Moving Average e ARIMA(2,2,3)model in order to forecast new values of the daily cumulative confirmed cases in Palestine.The forecast values are alarming,and giving the Palestinian government a good picture about the next number of COVID-19 cumulative confirmed cases to review her activities and interventions and to provide some robust structures and measures to avoid these challenges.

关键词： COVID-19 Pandemic ARIMA models Forecasting Moving average models

Higher-Level Hardware Synthesis of the KASUMI Algorithm

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Journal of Computer Science & Technology 2007年第1期22卷 60-70页

作者： issam W. Damaj Electrical and Computer Engineering Department Dhofar University P.O. Box 2509 Salalah 211 Oman

Programmable Logic Devices （PLDs） continue to grow in size and currently contain several millions of gates. At the same time, research effort is going into higher-level hardware synthesis methodologies for reconfigurable computing that can exploit PLD technology. In this paper, we explore the effectiveness and extend one such formal methodology in the design of massively parallel algorithms. We take a step-wise refinement approach to the development of correct reconfigurable hardware circuits from formal specifications. A functional programming notation is used for specifying algorithms and for reasoning about them. The specifications are realised through the use of a combination of function decomposition strategies, data refinement techniques, and off-the-shelf refinements based upon higher-order functions. The off-the-shelf refinements are inspired by the operators of Communicating Sequential Processes （CSP） and map easily to programs in Handel-C （a hardware description language）. The Handel-C descriptions are directly compiled into reconfigurable hardware. The practical realisation of this methodology is evidenced by a case studying the third generation mobile communication security algorithms. The investigated algorithm is the KASUMI block cipher. In this paper, we obtain several hardware implementations with different performance characteristics by applying different refinements to the algorithm. The developed designs are compiled and tested under Celoxica＇s RC-1000 reconfigurable computer with its 2 million gates Virtex-E FPGA. Performance analysis and evaluation of these implementations are included.

关键词： data encryption formal models gate array methodology parallel algorithms

Optimized Convolutional Neural Network for Automatic Detection of COVID-19

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Computers, Materials & Continua 2022年第1期70卷 1159-1175页

作者： K.Muthumayil M.Buvana K.R.Sekar Adnen El Amraoui issam Nouaouri Romany F.Mansour Department of Information Technology PSNA College of Engineering and TechnologyDindigul624622TamilnaduIndia Department of Computer Science&Engineering PSNA College of Engineering and TechnologyDindigul624622India School of Computing SASTRA Deemed UniversityThanjavur613401India Univ.Artois U.R.3926Laboratoire de Génie Informatique et d’Automatique de l’Artois(LGI2A)F-62400BéthuneFrance Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga72511Egypt

The outbreak of COVID-19 affected global nations and is posing serious challenges to healthcare systems across the globe.Radiologists use X-Rays or Computed Tomography(CT)images to confirm the presence of COVID-19.So,image processing techniques play an important role in diagnostic procedures and it helps the healthcare professionals during critical times.The current research work introduces Multi-objective Black Widow Optimization(MBWO)-based Convolutional Neural Network i.e.,MBWOCNN technique for diagnosis and classification of COVID-19.MBWOCNN model involves four steps such as preprocessing,feature extraction,parameter tuning,and classification.In the beginning,the input images undergo preprocessing followed by CNN-based feature extraction.Then,Multi-objective Black Widow Optimization(MBWO)technique is applied to fine tune the hyperparameters of CNN.Finally,Extreme Learning Machine with autoencoder(ELM-AE)is applied as a classifier to confirm the presence of COVID-19 and classify the disease under different class labels.The proposed MBWO-CNN model was validated experimentally and the results obtained were compared with the results achieved by existing techniques.The experimental results ensured the superior results of the ELM-AE model by attaining maximum classification performance with the accuracy of 96.43%.The effectiveness of the technique is proved through promising results and the model can be applied in diagnosis and classification of COVID-19.

关键词： COVID-19 classification CNN hyperparameter tuning black widow optimization

Facial expression recognition using threestage support vector machines

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Visual Computing for Industry,Biomedicine,and Art 2019年第1期2卷 236-244页

作者： issam Dagher Elio Dahdah Morshed Al Shakik Computer Engineering Department University of BalamandTripoli P.O.BOX 100Lebanon

Herein,a three-stage support vector machine(SVM)for facial expression recognition is proposed.The first stage comprises 21 SVMs,which are all the binary combinations of seven expressions.If one expression is dominant,then the first stage will suffice;if two are dominant,then the second stage is used;and,if three are dominant,the third stage is used.These multilevel stages help reduce the possibility of experiencing an error as much as possible.Different image preprocessing stages are used to ensure that the features attained from the face detected have a meaningful and proper contribution to the classification stage.Facial expressions are created as a result of muscle movements on the face.These subtle movements are detected by the histogram-oriented gradient feature,because it is sensitive to the shapes of objects.The features attained are then used to train the three-stage SVM.Two different validation methods were used:the leave-one-out and K-fold tests.Experimental results on three databases(Japanese Female Facial Expression,Extended Cohn-Kanade Dataset,and Radboud Faces Database)show that the proposed system is competitive and has better performance compared with other works.

关键词： Facial expression recognition Support vector machine Histogram of oriented gradients Viola-Jones Validation