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Articles 31 - 60 of 564

Full-Text Articles in Electrical and Computer Engineering

Biogeography Based Optimization With Salp Swarm Optimizer Inspired Operator For Solving Non-Linear Continuous Optimization Problems, Vanita Garg, Kusum Deep, Khalid Abdulaziz Alnowibet, Hossam Zawbaa, Ali Wagdy Mohamed Jan 2023

Biogeography Based Optimization With Salp Swarm Optimizer Inspired Operator For Solving Non-Linear Continuous Optimization Problems, Vanita Garg, Kusum Deep, Khalid Abdulaziz Alnowibet, Hossam Zawbaa, Ali Wagdy Mohamed

Articles

In this paper, a novel attempt is made to incorporate the two effective algorithm strategies, where BBO has a strong exploration and Salp Swarm Algorithm (SSA) is used for exploitation of the search space. The proposed algorithm is tested on IEEE CEC 2014 and statistical, convergence graphs are given. The proposed algorithm is also applied to 10 real life problems and compared with its counterpart algorithm. Results obtained by above experiments have demonstrated the outperformance of the hybrid version of BBO over other algorithms.

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A Multi–Objective Gaining–Sharing Knowledge-Based Optimization Algorithm For Solving Engineering Problems, Nour Elhouda Chalabi, Abdelouahab Attia, Khalid Abdulaziz Alnowibet, Hossam Zawbaa, Hatem Masri, Ali Wagdy Mohamed Jan 2023

A Multi–Objective Gaining–Sharing Knowledge-Based Optimization Algorithm For Solving Engineering Problems, Nour Elhouda Chalabi, Abdelouahab Attia, Khalid Abdulaziz Alnowibet, Hossam Zawbaa, Hatem Masri, Ali Wagdy Mohamed

Articles

Metaheuristics in recent years has proven its effectiveness; however, robust algorithms that can solve real-world problems are always needed. In this paper, we suggest the first extended version of the recently introduced gaining–sharing knowledge optimization (GSK) algorithm, named multiobjective gaining–sharing knowledge optimization (MOGSK), to deal with multiobjective optimization problems (MOPs). MOGSK employs an external archive population to store the nondominated solutions generated thus far, with the aim of guiding the solutions during the exploration process. Furthermore, fast nondominated sorting with crowding distance was incorporated to sustain the diversity of the solutions and ensure the convergence towards the Pareto optimal set, …

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Opportunities Of Iot In Fog Computing For High Fault Tolerance And Sustainable Energy Optimization, A. Reyana, Sandeep Kautish, Khalid Abdulaziz Alnowibet, Hossam Zawbaa, Ali Wagdy Mohamed Jan 2023

Opportunities Of Iot In Fog Computing For High Fault Tolerance And Sustainable Energy Optimization, A. Reyana, Sandeep Kautish, Khalid Abdulaziz Alnowibet, Hossam Zawbaa, Ali Wagdy Mohamed

Articles

Today, the importance of enhanced quality of service and energy optimization has promoted research into sensor applications such as pervasive health monitoring, distributed computing, etc. In general, the resulting sensor data are stored on the cloud server for future processing. For this purpose, recently, the use of fog computing from a real-world perspective has emerged, utilizing end-user nodes and neighboring edge devices to perform computation and communication. This paper aims to develop a quality-of-service-based energy optimization (QoS-EO) scheme for the wireless sensor environments deployed in fog computing. The fog nodes deployed in specific geographical areas cover the sensor activity performed …

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Swarm Electrification: A Comprehensive Literature Review, Stephen Sheridan, Keith Sunderland, Jane Courtney Jan 2023

Swarm Electrification: A Comprehensive Literature Review, Stephen Sheridan, Keith Sunderland, Jane Courtney

Articles

In the global North, the need to decarbonize power generation is well documented and the challenges faced are endemic to the design of the electrical grids. With networks relying on centralized generation, it can be difficult to replace fossil-fuel power plants with renewable energy sources as generation may be intermittent causing grid instability when there is no ‘spinning reserve’ [1]. In parts of the global south, however, many under-electrified nations have high levels of solar irradiance. This, combined with falling prices for solar panels, is allowing for alternative paths to electrification from costly grid extensions and has resulted in grids …

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Adaptive Fuzzy Supplementary Controller For Ssr Damping In A Series-Compensated Dfig-Based Wind Farm, Mohamed Abdeen, Sayed Hosny Ahmed El-Banna, Sara Elgohary, Hend Mostafa, Nora Ghaly, Nourhan Adel, Zeinab Elkhwas, Mohamed Alahmady, Hossam Zawbaa, Salah Kamel Jan 2023

Adaptive Fuzzy Supplementary Controller For Ssr Damping In A Series-Compensated Dfig-Based Wind Farm, Mohamed Abdeen, Sayed Hosny Ahmed El-Banna, Sara Elgohary, Hend Mostafa, Nora Ghaly, Nourhan Adel, Zeinab Elkhwas, Mohamed Alahmady, Hossam Zawbaa, Salah Kamel

Articles

Although using a series compensation technique in a long transmission line effectively increases the transmittable power; it may cause a sub-synchronous resonance (SSR) phenomenon. Gate-controlled series capacitor (GCSC) is an effective method for SSR damping by controlling the turn-off angle. In the previous studies, a constant supplementary damping controller (SDC) was used for controlling the turn-off angle, which can mitigate the SSR phenomenon. However, these methods can not capture the maximum transmittable power at different operating points. In this paper, a fuzzy logic controller (FLC) is proposed to compute the gain of SDC based on the wind speed and the …

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An Adaptive Vector Control Method For Inverter-Based Stand-Alone Microgrids Considering Voltage Reduction And Load Shedding Schemes, Sumit Kumar Jha, Deepak Kumar, Prabhat Ranjan Tripathi, Bhargav Appasani, Hossam Zawbaa, Salah Kamel Jan 2023

An Adaptive Vector Control Method For Inverter-Based Stand-Alone Microgrids Considering Voltage Reduction And Load Shedding Schemes, Sumit Kumar Jha, Deepak Kumar, Prabhat Ranjan Tripathi, Bhargav Appasani, Hossam Zawbaa, Salah Kamel

Articles

The droop mechanism is widely utilized in a stand-alone microgrid (MG) to regulate power-sharing among distributed generators (DG). However, over the years, the droop phenomena are continually modified to lessen the deviation in voltage and frequency parameters caused due to classical droop. This study suggests computing the droop coefficient for voltage–current (V–I) droop to take into account for proportional power distribution among DGs. In grid utility networks, the conservation voltage reduction (CVR) strategy is widely used to curtail the use of energy. Hence, this paper investigates the CVR's performance for stand-alone MG by performing the adaptive vector control scheme in …

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Wind Energy Harvesting And Conversion Systems: A Technical Review, Sinhara M. H. D. Perera, Ghanim Putrus, Michael Conlon, Mahinsasa Narayana, Keith Sunderland Jan 2023

Wind Energy Harvesting And Conversion Systems: A Technical Review, Sinhara M. H. D. Perera, Ghanim Putrus, Michael Conlon, Mahinsasa Narayana, Keith Sunderland

Articles

Wind energy harvesting for electricity generation has a significant role in overcoming the challenges involved with climate change and the energy resource implications involved with population growth and political unrest. Indeed, there has been significant growth in wind energy capacity worldwide with turbine capacity growing significantly over the last two decades. This confidence is echoed in the wind power market and global wind energy statistics. However, wind energy capture and utilisation has always been challenging. Appreciation of the wind as a resource makes for difficulties in modelling and the sensitivities of how the wind resource maps to energy production results …

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Impact Of Distributed Energy Resources In Smart Homes And Community-Based Electricity Market, Aziz Saif, Shafi K. Khadem, Michael Conlon, Brian Norton Jan 2023

Impact Of Distributed Energy Resources In Smart Homes And Community-Based Electricity Market, Aziz Saif, Shafi K. Khadem, Michael Conlon, Brian Norton

Articles

Toward the achievement of decarbonised European smart grid network by 2050, the European Commission (EC) has given high importance to its “Clean Energy for all Europeans Package (CEP)” by empowering individuals and groups of consumers to participate in this energy transition. Such energy transition demands residential households to transform the energy-positive smart homes into energy-active smart homes, thus building a smart community. This transformation will expedite if the residential customers are provided with a better choice of supply, access to reliable energy prices, possibility to produce and sell their own electricity with increased transparency and better regulation for more involvement …

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Spontaneous Mirror Symmetry Breaking And Chiral Segregation In The Achiral Ferronematic Compound Dio, Neelam Yadav, Yuri Panarin, Wanhe Jiang, Georg H. Mehl, Jagdish K. Vij Jan 2023

Spontaneous Mirror Symmetry Breaking And Chiral Segregation In The Achiral Ferronematic Compound Dio, Neelam Yadav, Yuri Panarin, Wanhe Jiang, Georg H. Mehl, Jagdish K. Vij

Articles

An achiral compound, DIO, known to exhibit three nematic phases namely N, NX and NF, is studied by polarizing microscopy and electro-optics for different surface conditions in confinement. The high temperature N phase assigned initially as a conventional nematic phase, shows two additional unusual features: the optical activity and the linear electro-optic response related to the polar nature of this phase. An appearance of chiral domains is explained by the spontaneous symmetry breaking arising from the saddle-splay elasticity and followed by the formation of helical domains of the opposite chirality. This is the first example of helical segregation observed in …

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Embedded Ai For Wheat Yellow Rust Infection Type Classification, Uferah Shafi, Rafia Mumtaz, Muhammad Deedahwar Mazhar Qureshi, Zahid Mahmood, Sikander Khan Tanveer, Ihsan Ul Haq, Syed Mohammad Hassan Zaidi Jan 2023

Embedded Ai For Wheat Yellow Rust Infection Type Classification, Uferah Shafi, Rafia Mumtaz, Muhammad Deedahwar Mazhar Qureshi, Zahid Mahmood, Sikander Khan Tanveer, Ihsan Ul Haq, Syed Mohammad Hassan Zaidi

Articles

Wheat is the most important and dominating crop in Pakistan in terms of production and acreage, which is grown on 37% of the cultivated area, accounting for 70% of the total production. However, wheat yield is highly affected by stripe rust, which is considered the most devastating fungal disease, causing 5.5 million tonnes of loss per year globally. In order to minimize this loss, the accurate and timely detection of rust disease is crucial instead of manual inspection. Towards this end, we propose a system to detect wheat rust disease and classify its infection types into four classes, including healthy, …

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Control And Protection Of Mmc-Based Hvdc Systems: A Review, Rashid Hussain Chandio, Faheem Akhtar Chachar, Jahangeer Badar Soomro, Jamshed Ahmed Ansari, Mudassir Munir Mudassir Munir, Hossam Zawbaa, Salah Kamel Salah Kamel Jan 2023

Control And Protection Of Mmc-Based Hvdc Systems: A Review, Rashid Hussain Chandio, Faheem Akhtar Chachar, Jahangeer Badar Soomro, Jamshed Ahmed Ansari, Mudassir Munir Mudassir Munir, Hossam Zawbaa, Salah Kamel Salah Kamel

Articles

The voltage source converter (VSC) based HVDC (high voltage direct current system) offers the possibility to integrate other renewable energy sources (RES) into the electrical grid, and allows power flow reversal capability. These appealing features of VSC technology led to the further development of multi-terminal direct current (MTDC) systems. MTDC grids provide the possibility of interconnection between conventional power systems and other large-scale offshore sources like wind and solar systems. The modular multilevel converter (MMC) has become a popular technology in the development of the VSC-MTDC system due to its salient features such as modularity and scalability. Although, the employment …

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Design And Implementation Of A New Adaptive Mppt Controller For Solar Pv Systems, Saibal Manna, Deepak Kumar Singh, Ashok Kumar Akella, Hossam Kotb, Kareem M. Aboras, Hossam Zawbaa, Salah Kamel Jan 2023

Design And Implementation Of A New Adaptive Mppt Controller For Solar Pv Systems, Saibal Manna, Deepak Kumar Singh, Ashok Kumar Akella, Hossam Kotb, Kareem M. Aboras, Hossam Zawbaa, Salah Kamel

Articles

This research provides an adaptive control design in a photovoltaic system (PV) for maximum power point tracking (MPPT). In the PV system, MPPT strategies are used to deliver the maximum available power to the load under solar radiation and atmospheric temperature changes. This article presents a new adaptive control framework to enhance the performance of MPPT, which will minimize the complexity in system control and efficiently manage uncertainties and disruptions in the environment and PV system. Here, the MPPT algorithm is decoupled with model reference adaptive control (MRAC) techniques, and the system gains MPPT with overall system stability. The simulation …

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Distributed Intermittent Fault Diagnosis In Wireless Sensor Network Using Likelihood Ratio Test, Bhabani Sankar Gouda, Meenakshi Panda, Trilochan Panigrahi, Sudhakar Das, Bhargav Appasani, Omprakash Acharya, Hossam Zawbaa, Salah Kamel Jan 2023

Distributed Intermittent Fault Diagnosis In Wireless Sensor Network Using Likelihood Ratio Test, Bhabani Sankar Gouda, Meenakshi Panda, Trilochan Panigrahi, Sudhakar Das, Bhargav Appasani, Omprakash Acharya, Hossam Zawbaa, Salah Kamel

Articles

In current days, sensor nodes are deployed in hostile environments for various military and commercial applications. Sensor nodes are becoming faulty and having adverse effects in the network if they are not diagnosed and inform the fault status to other nodes. Fault diagnosis is difficult when the nodes behave faulty some times and provide good data at other times. The intermittent disturbances may be random or kind of spikes either in regular or irregular intervals. In literature, the fault diagnosis algorithms are based on statistical methods using repeated testing or machine learning. To avoid more complex and time consuming repeated …

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Metaheuristic Optimization Techniques Used In Controlling Of An Active Magnetic Bearing System For High-Speed Machining Application, Suraj Suraj, Pabitra Kumar Biswas Pabitra Kumar Biswas, Sukanta Debnath, Anumoy Ghosh, Thanikanti Sudhakar Babu, Hossam Zawbaa, Salah Kemal Jan 2023

Metaheuristic Optimization Techniques Used In Controlling Of An Active Magnetic Bearing System For High-Speed Machining Application, Suraj Suraj, Pabitra Kumar Biswas Pabitra Kumar Biswas, Sukanta Debnath, Anumoy Ghosh, Thanikanti Sudhakar Babu, Hossam Zawbaa, Salah Kemal

Articles

Smart control tactics, wider stability region, rapid reaction time, and high-speed performance are essential requirements for any controller to provide a smooth, vibrationless, and efficient performance of an in-house fabricated active magnetic bearing (AMB) system. In this manuscript, three pre-eminent population-based metaheuristic optimization techniques: Genetic algorithm (GA), Particle swarm optimization (PSO), and Cuckoo search algorithm (CSA) are implemented one by one, to calculate optimized gain parameters of PID controller for the proposed closed-loop active magnetic bearing (AMB) system. Performance indices or, objective functions on which these optimization techniques are executed are integral absolute error (IAE), integral square error (ISE), integral …

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Performance Improvement Of Hybrid System Based Dfig-Wind/Pv/Batteries Connected To Dc And Ac Grid By Applying Intelligent Control, Younes Sahri, Salah Tamalouzt, Sofia Lalouni Belaid, Mohit Bajaj, Sherif S.M. Ghoneim, Hossam Zawbaa, Salah Kamel Jan 2023

Performance Improvement Of Hybrid System Based Dfig-Wind/Pv/Batteries Connected To Dc And Ac Grid By Applying Intelligent Control, Younes Sahri, Salah Tamalouzt, Sofia Lalouni Belaid, Mohit Bajaj, Sherif S.M. Ghoneim, Hossam Zawbaa, Salah Kamel

Articles

One of the main causes of CO2 emissions is the production of electrical energy. Therefore, many researchers goal’s is to develop renewable power systems. This paper proposes a new intelligent control development of hybrid PV–Wind-Batteries. Neuro-Fuzzy Direct Power Control (NF-DPC) is invested in order to enhance system performance and generated currents quality. An improved MPPT algorithm based on Fuzzy Controller (FC) is invested for PV power optimization. In addition, a new Modified Fuzzy Direct Power Control (MF-DPC) is developed and applied to the grid side converter to control the active and reactive power by monitoring the involved active power flow …

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Local Electricity Market Operation In Presence Of Residential Energy Storage In Low Voltage Distribution Network: Role Of Retail Market Pricing, Aziz Saif, Shafi K. Khadem Shafi K. Khadem, Michael Conlon, Brian Norton Jan 2023

Local Electricity Market Operation In Presence Of Residential Energy Storage In Low Voltage Distribution Network: Role Of Retail Market Pricing, Aziz Saif, Shafi K. Khadem Shafi K. Khadem, Michael Conlon, Brian Norton

Articles

Local Electricity Market (LEM) appears as a promising consumer-centric market-based approach that extends the self-consumption method, widely implemented in residential households, to collective self-consumption in the local energy communities, enabled through peer-to-peer (P2P) transactions. To facilitate the integration of LEM in the wholesale electricity market (WEM), it is paramount to comprehend the synergy of retail electricity pricing on the LEM operation hosted in the low-voltage distribution network (LVDN). The paper presents a co-simulation framework consisting of a local electricity market model coupled with a three-phase distribution network simulator to perform a holistic case study for a smart energy community in …

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Nipuna: A Novel Optimizer Activation Function For Deep Neural Networks, Golla Madhu, Sandeep Kautish, Khalid Abdulaziz Alnowibet, Hossam Zawbaa, Ali Wagdy Mohamed Jan 2023

Nipuna: A Novel Optimizer Activation Function For Deep Neural Networks, Golla Madhu, Sandeep Kautish, Khalid Abdulaziz Alnowibet, Hossam Zawbaa, Ali Wagdy Mohamed

Articles

In recent years, various deep neural networks with different learning paradigms have been widely employed in various applications, including medical diagnosis, image analysis, self-driving vehicles and others. The activation functions employed in deep neural networks have a huge impact on the training model and the reliability of the model. The Rectified Linear Unit (ReLU) has recently emerged as the most popular and extensively utilized activation function. ReLU has some flaws, such as the fact that it is only active when the units are positive during back-propagation and zero otherwise. This causes neurons to die (dying ReLU) and a shift in …

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Interpreting Energy Utilisation With Shapley Additive Explanations By Defining A Synthetic Data Generator For Plausible Charging Sessions Of Electric Vehicles, Prasant Kumar Mohanty, Gayadhar Panda, Malabika Basu, Diptendu Sinha Roy Jan 2023

Interpreting Energy Utilisation With Shapley Additive Explanations By Defining A Synthetic Data Generator For Plausible Charging Sessions Of Electric Vehicles, Prasant Kumar Mohanty, Gayadhar Panda, Malabika Basu, Diptendu Sinha Roy

Articles

Electric vehicles (EVs) are an effective solution for reducing reliance on non-renewable energy sources. However, the lack of charging infrastructure and concerns over their range are some of the biggest hurdles to adopting EVs. Charging infrastructure for EVs is, however, on the rise. Proper planning of charging stations vis-`a-vis road networks and related points of interest such as transportation hubs, schools, shopping centres, etc., alongside such roads become vital to laying out a plan for such infrastructure, particularly for developing countries like India where EV adoption is relatively in a nascent stage. Synthetic datasets can help overcome these hurdles and …

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Lightnet: A Novel Lightweight Convolutional Network For Brain Tumor Segmentation In Healthcare, Dongyuan Wu, Junyi Tao, Zhen Qin, Rao Asad Mumtaz, Jin Qin, Linfang Yu, Jane Courtney Jan 2023

Lightnet: A Novel Lightweight Convolutional Network For Brain Tumor Segmentation In Healthcare, Dongyuan Wu, Junyi Tao, Zhen Qin, Rao Asad Mumtaz, Jin Qin, Linfang Yu, Jane Courtney

Articles

Diagnosis, treatment planning, surveillance, and the monitoring of clinical trials for brain diseases all benefit greatly from neuroimaging-based tumor segmentation. Recently, Convolutional Neural Networks (CNNs) have demonstrated promising results in enhancing the efficiency of image-based brain tumor segmentation. Most current work on CNNs, however, is devoted to creating increasingly complicated convolution modules to improve performance, which in turn raises the computing cost of the model. This work proposes a simple and effective feed-forward CNN, LightNet (Light Network). Based on multi-path and multi-level, it replaces traditional convolutional methods with light operations, which reduces network parameters and redundant feature maps. In the …

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Schizo-Net: A Novel Schizophrenia Diagnosis Framework Using Late Fusion Multimodal Deep Learning On Electroencephalogram-Based Brain Connectivity Indices, Nitin Grover, Aviral Chharia, Rahul Upadhyay, Luca Longo Jan 2023

Schizo-Net: A Novel Schizophrenia Diagnosis Framework Using Late Fusion Multimodal Deep Learning On Electroencephalogram-Based Brain Connectivity Indices, Nitin Grover, Aviral Chharia, Rahul Upadhyay, Luca Longo

Articles

Schizophrenia (SCZ) is a serious mental condition that causes hallucinations, delusions, and disordered thinking. Traditionally, SCZ diagnosis involves the subject’s interview by a skilled psychiatrist. The process needs time and is bound to human errors and bias. Recently, brain connectivity indices have been used in a few pattern recognition methods to discriminate neuro-psychiatric patients from healthy subjects. The study presents Schizo-Net , a novel, highly accurate, and reliable SCZ diagnosis model based on a late multimodal fusion of estimated brain connectivity indices from EEG activity. First, the raw EEG activity is pre-processed exhaustively to remove unwanted artifacts. Next, six brain …

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Do Games Reduce Math Anxiety? A Meta-Analysis, Pierpaolo Dondio, Viacheslav Filonenko, Mariana Rocha Jan 2023

Do Games Reduce Math Anxiety? A Meta-Analysis, Pierpaolo Dondio, Viacheslav Filonenko, Mariana Rocha

Articles

In this paper, we meta-analyse the empirical evidence about the effectiveness of game-based interventions to reduce students' level of math anxiety. After performing a search for randomised controlled studies relevant to game-based intervention for math anxiety, 16 experimental studies with a total of 686 participants described in 11 peer-review articles met the selection criteria.A random-effects meta-analysis indicated a small and non-significant reduction of math anxiety (mean effect size ES=-0.32, CI=[-0.64,0.01]). The results were moderated by several factors: non-digital games were more effective, while digital games had a negligible mean effect size of $ES=-0.13$, $CI=[-0.33,0.08]$. The effect size was moderated also …

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Gated Deep Reinforcement Learning With Red Deer Optimization For Medical Image Classification, Narayanan Ganesh, Sambandan Jayalakshmi, Rama Chandran Narayanan, Miroslav Mahdal, Hossam Zawbaa, Ali Wagdy Mohamed Jan 2023

Gated Deep Reinforcement Learning With Red Deer Optimization For Medical Image Classification, Narayanan Ganesh, Sambandan Jayalakshmi, Rama Chandran Narayanan, Miroslav Mahdal, Hossam Zawbaa, Ali Wagdy Mohamed

Articles

The brain is one of the most important and complex organs in the body, consisting of billions of individual cells. Uncontrolled growth and expansion of aberrant cell populations within or around the brain are the main causes of brain tumors. These cells have the potential to harm healthy cells and impair brain function [1]. Tumors can be detected using medical imaging techniques, which are considered the most popular and accurate way to classify different types of cancer, and this procedure is even more crucial as it is noninvasive [2]. Magnetic resonance imaging (MRI) is one such medical imaging technique that …

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Rate Of Change Of Direct-Axis Current Component Protection Scheme For Inverter-Based Islanded Microgrids, Abdolhamid Farshadi, Behzad Keyvani Eydi, Hamed Nafisi, Hossein Askarian-Abyaneh, Arash Beiranvand Jan 2023

Rate Of Change Of Direct-Axis Current Component Protection Scheme For Inverter-Based Islanded Microgrids, Abdolhamid Farshadi, Behzad Keyvani Eydi, Hamed Nafisi, Hossein Askarian-Abyaneh, Arash Beiranvand

Articles

Rapid growth in the utilization of the inverter-interfaced distributed energy resources (IIDERs) in microgrids has brought new challenges in the network protection area. Microgrid protection specifically becomes a concern during operation in the islanded mode. There is a considerable reduction in fault current levels in this mode compared to when the microgrid is connected to the grid, which makes conventional algorithms operate with significant delay or, in many cases, not even pick up the fault. This paper proposes a protection algorithm based on the rate of change of direct-axis current component ( id ) to protect inverter-based microgrids (IBMGs). The …

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Pattern And Polarization Diversity Multisector Annular Antenna For Iot Applications, Abel Zandamela, Nicola Marchetti, Max Ammann, Adam Narbudowicz Jan 2023

Pattern And Polarization Diversity Multisector Annular Antenna For Iot Applications, Abel Zandamela, Nicola Marchetti, Max Ammann, Adam Narbudowicz

Articles

This work proposes a small pattern and polarization diversity multisector annular antenna with electrical size and profile of ka = 1.2 and 0.018λ, respectively. The antenna is planar and comprises annular sectors that are fed using different ports to enable digital beamforming techniques, with efficiency and gain of up to 78% and 4.62 dBi, respectively. The cavity model analysis is used to describe the design concept and the antenna diversity. The proposed method can produce different polarization states (e.g., linearly and circularly polarized patterns) and pattern diversity characteristics covering the elevation plane. Owing to its small electrical size, low-profile and …

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An Investigation Of 3.5 Μm Emission In Er3+-Doped Fluorozirconate Glasses Under 638 Nm Laser Excitation, Haiyan Zhao, Ke Tian, Xin Wang, Dejun Liu, Shunbin Wang, Gerald Farrell, Pengfei Wang Jan 2023

An Investigation Of 3.5 Μm Emission In Er3+-Doped Fluorozirconate Glasses Under 638 Nm Laser Excitation, Haiyan Zhao, Ke Tian, Xin Wang, Dejun Liu, Shunbin Wang, Gerald Farrell, Pengfei Wang

Articles

Intense 3.5 μm mid-infrared emission has been achieved in Er3+-doped ZBYA glasses, which is ascribed to the Er3+: 4F9/2→4I9/2 transition. Based on the absorption spectrum of Er3+ ions, a 638 nm laser was utilized to directly pump the upper level (Er3+: 4F9/2) to achieve 3.5 μm emission with enhanced quantum efficiency. Spectroscopic parameters were predicted by Judd-Ofelt theory. The maximum emission cross-section of the Er3+-doped ZBYA glass was estimated to be 5.5×10-22 cm2 at 3496 nm. Additionally, the fluorescence spectra and energy level lifetimes of ZBYA glass samples with different Er3+ ions doping concentrations were also measured. The theoretical and …

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Survey Of Routing Techniques-Based Optimization Of Energy Consumption In Sd-Dcn, Mohammed Nsaif, Gergely Kovásznai, Ali Malik, Ruairí De Fréin Jan 2023

Survey Of Routing Techniques-Based Optimization Of Energy Consumption In Sd-Dcn, Mohammed Nsaif, Gergely Kovásznai, Ali Malik, Ruairí De Fréin

Articles

The increasing power consumption of Data Center Networks (DCN) is becoming a major concern for network operators. The object of this paper is to provide a survey of state-of-the-art methods for reducing energy consumption via (1) enhanced scheduling and (2) enhanced aggregation of traffic flows using Software-Defined Networks (SDN), focusing on the advantages and disadvantages of these approaches. We tackle a gap in the literature for a review of SDN-based energy saving techniques and discuss the limitations of multi-controller solutions in terms of constraints on their performance. The main finding of this survey paper is that the two classes of …

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Evaluating Large Delay Estimation Techniques For Assisted Living Environments, Swarnadeep Bagchi, Ruairí De Fréin Sep 2022

Evaluating Large Delay Estimation Techniques For Assisted Living Environments, Swarnadeep Bagchi, Ruairí De Fréin

Articles

Abstract Phase wraparound due to large inter-sensor spacings in multi-channel demixing limits the range of relative delays that many time–frequency relative delay estimators can estimate. The performance of a large relative delay estimation method, called the elevatogram, is evaluated in the presence of significant phase wraparound. This paper compares the elevatogram with the popular relative delay estimator used in DUET and the brute-force approach in D-AdRess and analyses its computational efficiency. The elevatogram can accurately estimate relative delays of speech signals of up to 800 samples, whereas DUET and D-AdRess were limited to delays of 7 and 35 samples, given …

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An Empirical Comparison Of The Security And Performance Characteristics Of Topology Formation Algorithms For Bitcoin Networks, Muntadher Sallal, Ruairí De Fréin, Ali Malik, Benjamin Aziz Sep 2022

An Empirical Comparison Of The Security And Performance Characteristics Of Topology Formation Algorithms For Bitcoin Networks, Muntadher Sallal, Ruairí De Fréin, Ali Malik, Benjamin Aziz

Articles

There is an increasing demand for digital crypto-currencies to be more secure and robust to meet the following business requirements: (1) low transaction fees and (2) the privacy of users. Nowadays, Bitcoin is gaining traction and wide adoption. Many well-known businesses have begun accepting bitcoins as a means of making financial payments. However, the susceptibility of Bitcoin networks to information propagation delay, increases the vulnerability to attack of the Bitcoin network, and decreases its throughput performance. This paper introduces and critically analyses new network clustering methods, named Locality Based Clustering (LBC), Ping Time Based Approach (PTBC), Super Node Based Clustering …

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A Computational Approach To Evaluating Curricular Alignment To The United Nations Sustainable Development Goals, Philippe Lemarchand, Mick Mckeever, Cormac Macmahon, Philip Owende Aug 2022

A Computational Approach To Evaluating Curricular Alignment To The United Nations Sustainable Development Goals, Philippe Lemarchand, Mick Mckeever, Cormac Macmahon, Philip Owende

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The United Nations (UN) considers universities to be key actors in the pursuit of the Sustainable Development Goals (SDGs). Yet, efforts to evaluate the embeddedness of the SDGs in university curricula tend to rely on manual analyses of curriculum documents for keywords contained in sustainability lexica, with little consideration for the diverse contexts of such keywords. The efficacy of these efforts, relying on expert co-elicitation in both subject-matter contexts and sustainability, suffers from drawbacks associated with keyword searches, such as limited coverage of key concepts, difficulty in extracting intended meaning and potential for greenwashing through “keyword stuffing.” This paper presents …

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A Physical Layer Security (Pls) Approach Through Address Fed Mapping Crest Factor Reduction Applicable For 5g/6g Signals, Somayeh Mohammady, David Malone Prof. Aug 2022

A Physical Layer Security (Pls) Approach Through Address Fed Mapping Crest Factor Reduction Applicable For 5g/6g Signals, Somayeh Mohammady, David Malone Prof.

Articles

The privacy and security of 5G/6G infrastructures are receiving great attention together with power consumption and efficiency. Here, Physical Layer Security (PLS) is considered and a technique named Address Fed Mapping (AFM) is proposed which not only enhances the physical layer security, but also reduces the effect of high Peak to Average Power Ratio (PAPR), which results in efficiency improvement in OFDM based signals used in beyond 5G and 6G. The AFM is designed based on the idea of randomly generated signals, modifying the original signal to reduce PAPR. Instead of a typical randomization algorithm, a unique key is generated …

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