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Deep Learning with Backtracking Search Optimization Based Skin Lesion Diagnosis Model

computers, Materials & Continua 2022年第1期70卷 1297-1313页

作者： C.S.S.Anupama L.Natrayan E.Laxmi Lydia Abdul Rahaman Wahab Sait Jose Escorcia-Gutierrez Margarita Gamarra Romany F.Mansour Department of Electronics&Instrumentation Engineering V.R.Siddhartha Engineering CollegeVijayawada520007India Department of Mechanical Engineering Saveetha School of EngineeringSIMATSChennai602105India Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Archives and Communication King Faisal University31982Kingdom of Saudi Arabia Electronic and Telecommunicacions Program Universidad Autonoma del CaribeBarranquilla08001Colombia Department of Computational Science and Electronic Universidad de la CostaCUCBarranquilla08001Colombia Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga72511Egypt

Nowadays,quality improvement and increased accessibility to patient data,at a reasonable cost,are highly challenging tasks in healthcare *** of Things(IoT)and Cloud Computing(CC)architectures are utilized in the development of smart healthcare *** entities can support real-time applications by exploiting massive volumes of data,produced by wearable sensor *** advent of evolutionary computation algorithms andDeep Learning(DL)models has gained significant attention in healthcare diagnosis,especially in decision making *** cancer is the deadliest disease which affects people across the *** skin lesion classification model has a highly important application due to its fine-grained variability in the presence of skin *** current research article presents a new skin lesion diagnosis model i.e.,Deep Learning with Evolutionary Algorithm based Image Segmentation(DL-EAIS)for IoT and cloud-based smart healthcare ***,the dermoscopic images are captured using IoT devices,which are then transmitted to cloud servers for further ***,Backtracking Search optimization Algorithm(BSA)with Entropy-Based Thresholding(EBT)i.e.,BSA-EBT technique is applied in image *** by,Shallow Convolutional Neural Network(SCNN)model is utilized as a feature *** addition,Deep-Kernel Extreme LearningMachine(D-KELM)model is employed as a classification model to determine the class labels of dermoscopic *** extensive set of simulations was conducted to validate the performance of the presented method using benchmark *** experimental outcome infers that the proposed model demonstrated optimal performance over the compared techniques under diverse measures.

关键词： Intelligent models skin lesion dermoscopic images smart healthcare internet of things

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Next Generation Memristor Reservoir Computing

Next Generation Memristor Reservoir Computing

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Metrology for Extended Reality, Artificial Intelligence and Neural engineering (MetroXRAINE), IEEE International Conference on

作者： K. Nikiruy T. Ivanov M. Ziegler D. Rossetti F. Corinto A. Ascoli R. Tetzlaff A. S. Demirkol N. Schmitt Department of Electrical Engineering and Information Technology Micro-and Nanoelectronic Systems TU Ilmenau Ilmenau Germany Department of Electronics and Telecommunications (DET) Politecnico di Torino Turin Italy Faculty of Electrical and Computer Engineering Institute of Circuits and Systems TU Dresden Dresden Germany

ISBN: (数字)9798350378009

ISBN: (纸本)9798350378016

The nonlinear transformation used in reservoir computing can be effectively replaced by nonlinear vector autoregression (NVAR) for data prediction. In such a method, also known as next generation reservoir computing (NGRC), the input signal consists of a linear part, including several previous data points, and their nonlinear combinations. Here we show that the application of this method to a network with memristive weights (memristors) can be used to predict signals, depending on the nature of the nonlinear functions and the number of memristors. The network allows an accurate prediction of chaotic time series of Mackey-Glass and Duffing oscillators.

关键词： Performance evaluation Accuracy Time series analysis Memristors Reservoir computing Neural engineering Ordinary differential equations Vectors Next generation networking Oscillators

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A High-Band Compact Microstrip Patch Antenna for 5G Wireless Technologies 6

A High-Band Compact Microstrip Patch Antenna for 5G Wireless...

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6th International Conference on Contemporary Computing and Informatics, IC3I 2023

作者： Santhakumar, G. Muthukumar, R. Asa Jyothi, G. Balakumar, S. Maranan, Ramya Bonde, Roshan Sri Krishna College of Technology Department of Electronics and Communication Engineering Tamil Nadu Coimbatore India Erode Sengunthar Engineering College Department of EEE Tamil Nadu Erode India Malla Reddy Engineering College ECE Department Maisamma Guda Telangana Hyderabad India Arba Minch University Faculty of Electrical & Computer Engineering Arba MinchPin: 21 Ethiopia Saveetha School of Engineering Department of Research and Innovation SIMATS Tamil Nadu Chennai India Dr. Babasaheb Ambedkar Technological University Lonere Raigad India

ISBN: (纸本)9798350304480

This examination presents a High Increase, Overhauled Bandwidth Patch antenna for 5G Undertakings. Using an inset-took care of taking care of method for the microstrip patch antenna wave band, the double band is achieved. Two rectangular apertures are embedded on the patch's transmitting component to provide it a high increase. The anticipated antenna Consolidating three stages at the edge of the rectangular patch increases bandwidth. Fifth-generation (5G) networks clearly outperform 4G because to reduced idleness, more transmission speed, greater bandwidth, and a higher possibility of integrating with more notable various devices. For impending 5G association technologies, this paper studies and presents a microstrip patch antenna working at 28 GHz. The outcome of this reenactment is superior to the previous one. It typically acts as a dependable choice for 5G wireless innovation as a result. The performance of the suggested antenna is superior to that of earlier antennas spread in logical diaries. © 2023 IEEE.

关键词： 5g High-Band Microstrip Patch Antenna Wireless Technologies

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Oil Condition Assessment for Aged Transformers Based on Dissolved Gas Analysis

Oil Condition Assessment for Aged Transformers Based on Diss...

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International Middle-East Power System Conference, MEPCON

作者： Adel El-Faraskoury Sayed A. Ward Diaa-Eldin A. Mansour Shimaa A. Ibrahim Mohamed Badawi Extra High Voltage Research Centre Egyptian Electricity Holding Company Department of Electrical Engineering Faculty of Engineering at Shoubra Benha University Department of Electrical Engineering Faculty of Engineering Delta University for Science and Technology Egypt Electrical Power Engineering Department School of Electronics Communications and Computer Engineering Egypt-Japan University of Science and Technology Alexandria Egypt Electrical Power and Machines Engineering Department Faculty of Engineering Tanta University Tanta Egypt

One of the indispensable assets of the electrical systems and its most expensive components are power transformers. Condition assessment of power transformers is crucial and must be performed precisely to detect any abnormal conditions and prevent failures. Most transformer condition assessment relies on evaluating the insulating oil quality that achieves the cooling inside the transformer and the electrical insulation role. Hence, insulating oil performance is an important term for the reliable operation of power transformers. Under field aging, there is critical degradation in the chemical properties of the transformer oil, which may cause the occurrence of arcing, thermal, and partial discharge fault types. One of these chemical degradations caused by transformer aging is the generation of dissolved gases. Hence, dissolved gas analysis (DGA) is considered an in-service common and effective technique for detecting oil condition assessment under field aging. In addition, this technique can diagnose fault types. This paper studies the effect of oil aging on dissolved gas generation. For this purpose, it presents an analysis of the generation of dissolved gases for four old transformers of the same oil type (Diala B) and different ratings that exist in the Egyptian Electricity Transmission Company (EETC). This analysis of transformer oils was studied from 2010 to 2021.

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Retraction Note: Unlocking the power of recalling enhanced recurrent neural network: channel estimation and data analysis for 5G MIMO communication system

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Optical and Quantum electronics 2024年第11期56卷 1-2页

作者： Alqahtani, Abdullah Saleh Pathak, Pankaj Pandiaraj, Saravanan Indrapriyadarsini, H. Arun Kumar, U. Nataraju, Susheela Department of Self-Development Skills-IT CFY Deanship King Saud University Riyadh Saudi Arabia Symbiosis Institute of Digital and Telecom Management (SIDTM) Symbiosis International (Deemed University) Lavale Pune India Department of Electronics and Communication Engineering Karpagam Institute of Technology Coimbatore India Department of Electrical and Electronics Engineering Faculty of Engineering Karpagam Academy of Higher Education (Deemed to Be University) Coimbatore India Department of Computer Science Engineering G Madegowda Institute of Technology Bharathinagara (K M Doddi) India

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A Low-profile Broadband Dual-polarized Magneto-electric Dipole Antenna for 5G Applications

A Low-profile Broadband Dual-polarized Magneto-electric Dipo...

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World Congress on Computing and Communication Technologies (WCCCT)

作者： Yihuang Yang Botao Feng Xiao Ding Li Deng Wenzhe Gu Kwok L. Chung College of Electronics and Information Engineering Shenzhen University Shenzhen China Faculty of Humanities and Arts Macau University of Science and Technology Macau China College of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China School of Computer Science and Engineering Huizhou University Huizhou China School of Intelligent Manufacturing and Electrical Engineering Guangzhou Institute of Science and Technology Guangdong China

ISBN: (数字)9798331512620

ISBN: (纸本)9798331512637

This study proposes a compact wideband dual-polarized (DP) magneto-electric (ME) dipole antenna with cross-differential feeding, designed for 5G/6G millimeter-wave (mm-Wave) systems. The antenna features a geometrically symmetric configuration, integrating radiating elements and feeding networks into a single metallic layer, achieving a low-profile structure. By leveraging ME coupling mechanisms, the antenna supports dual-orthogonal polarization operation, offering a broad impedance bandwidth of 39.4% (26.3-39.1 GHz) under differential port excitation. Experimental results demonstrate excellent radiation performance, including highly symmetric radiation patterns, cross-polarization suppression below -30 dB, a gain range of 2.6-6.2 dBi, and an axial ratio (AR) below 2 dB across the operational band. The unified feed-radiator co-design effectively mitigates mm-Wave challenges such as narrow bandwidth and integration constraints commonly found in conventional dual-polarized antennas, which makes the proposed design a promising solution for compact MIMO arrays in the 28/39 GHz 5G NR bands.

关键词： Wireless communication Dipole antennas Magnetoelectric effects Microstrip antennas Directive antennas Antenna feeds Broadband communication Broadband antennas Wideband Gain

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CSI-GPT: Integrating Generative Pre-Trained Transformer with Federated-Tuning to Acquire Downlink Massive MIMO Channels

arXiv

引用

arXiv 2024年

作者： Zeng, Ye Qiao, Li Gao, Zhen Qin, Tong Wu, Zhonghuai Khalaf, Emad Chen, Sheng Guizani, Mohsen School of Information and Electronics Beijing Institute of Technology Beijing100081 China Electrical and Computer Engineering Department Faculty of Engineering King Abdulaziz University Jeddah21589 Saudi Arabia School of Electronics and Computer Science University of Southampton SouthamptonSO17 1BJ United Kingdom King Abdulaziz University Jeddah21589 Saudi Arabia United Arab Emirates

In massive multiple-input multiple-output (MIMO) systems, how to reliably acquire downlink channel state information (CSI) with low overhead is challenging. In this work, by integrating the generative pre-trained Transformer (GPT) with federated-tuning, we propose a CSI-GPT approach to realize efficient downlink CSI acquisition. Specifically, we first propose a Swin Transformer-based channel acquisition network (SWTCAN) to acquire downlink CSI, where pilot signals, downlink channel estimation, and uplink CSI feedback are jointly designed. Furthermore, to solve the problem of insufficient training data, we propose a variational auto-encoder-based channel sample generator (VAE-CSG), which can generate sufficient CSI samples based on a limited number of high-quality CSI data obtained from the current cell. The CSI dataset generated from VAE-CSG will be used for pre-training SWTCAN. To fine-tune the pre-trained SWTCAN for improved performance, we propose an online federated-tuning method, where only a small amount of SWTCAN parameters are unfrozen and updated using over-the-air computation, avoiding the high communication overhead caused by aggregating the complete CSI samples from user equipment (UEs) to the BS for centralized fine-tuning. Simulation results verify the advantages of the proposed SWTCAN and the communication efficiency of the proposed federated-tuning method. Our code is publicly available at https://***/ BIT-ZY/CSI-GPT Copyright © 2024, The Authors. All rights reserved.

关键词： Channel estimation

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Investigation of the Use of Renewable Energy in Microgrid Applications

Investigation of the Use of Renewable Energy in Microgrid Ap...

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International Conference on Science technology engineering and Management (ICONSTEM)

作者： Keerthi Kumar N Saravana Selvan G. Ravindra Seeniappan. Kallappan L. Natrayan Nadanakumar Vinayagam Department of Mechanical Engineering BMS Institute of Technology and Management Yelahanka Karnataka India Faculty of Engineering and Computer Technology AIMST University Malaysia India Department of Electrical and Electronics Engineering Sree Vidyanikethan Engineering College Tirupati Andhra Pradesh Department of Mechanical Engineering Velammal Institute of Technology Chennai Tamil Nadu India Department of Mechanical Engineering Saveetha School of Engineering SIMATS Chennai Tamil Nadu India Department of Automobile Engineering Hindustan Institute of Technology and Science Chennai Tamil Nadu India

ISBN: (数字)9798350365092

ISBN: (纸本)9798350365108

This research focuses on the primary aspects that influence the usage of renewable energy sources in microgrids. These aspects include energy demand, the amount of solar irradiation, and the capacity of the batteries. In addition to this, it exemplifies the relevance of these factors and the dynamic relationship between them in the operation of microgrid systems. A number of factors must be considered during the design and implementation of micro grids, as this study shows that renewable energy sources have a major impact on them. The paper highlights the benefits of microgrids, which include lower energy costs, increased energy autonomy, and fewer emissions of greenhouse gases. The findings of this research have the potential to make a contribution toward the overall goal of constructing a resilient and flexible energy infrastructure. This might be accomplished with the help of the findings of this study. This may be done by optimizing the construction of micro grids that display higher performance and effectiveness in capturing renewable energy resources using the insights gathered from the inquiry. These micro grids would be optimized to use the information gained from the investigation.

关键词： Renewable energy sources Radiation effects Costs Microgrids Mathematics Batteries Greenhouse gases

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Nucleus Segmentation Using Adaptive Thresholding for Analysis of Blood and Bone Marrow Smear Images 1

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11th International Conference on Frontiers of Intelligent Computing: Theory and Applications, FICTA 2023

作者： Bhateja, Vikrant Gupta, Sparshi Verma, Siddharth Singh, Sourabh Azar, Ahmad Taher Lay-Ekuakille, Aimé Lin, Jerry Chun-Wei Department of Electronics Engineering Faculty of Engineering and Technology Veer Bahadur Singh Purvanchal University Shahganj Road Uttar Pradesh Jaunpur222003 India Department of Electronics and Communication Engineering Shri Ramswaroop Memorial College of Engineering and Management Uttar Pradesh Lucknow India Vodafone Idea Limited Gomti Nagar Uttar Pradesh Lucknow India LTIMindtree Pune Hinjewadi Maharashtra Pune India College of Computer and Information Sciences Prince Sultan University Riyadh11586 Saudi Arabia Faculty of Computers and Artificial Intelligence Benha University Banha13518 Egypt Department of Innovation Engineering University of Salento Ed. "Corpo O" Via Monteroni Lecce73100 Italy Western Norway University of Applied Sciences Bergen Norway

ISBN: (数字)9789819967063

ISBN: (纸本)9789819967056

The analysis of blood and bone marrow smear pictures aids in the detection of hematological malignancies. The colour levels of the nucleus and its neighbours in these smear images aid in identifying cell malignancy. The primary goal of this project is to conduct colour-based segmentation on blood/bone marrow smear images. These photos are first treated to contrast stretching using the dark contrast algorithm (DCA). This enhancement boosts the contrast of the nucleus and its surrounding components. Using an adaptive thresholding approach, colour-based segmentation of enhanced microscopic pictures (blood/bone marrow smear images) was performed. The colour segmented image is then transformed to binary to create the binary mask, which is then evaluated using the overlap ratio (OR) to determine performance. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Color

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Packet Drop Reduction by Volunteer nodes in Mobile Wireless Sensor Networks

Packet Drop Reduction by Volunteer nodes in Mobile Wireless ...

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International Conference on Edge Computing and Applications (ICECAA)

作者： Nilamadhab Mishra P. Latha K. Sashi Rekha MuthuKumaran B School of Computer Science and Engineering VIT Bhopal University Bhopal Madhya Pradesh India Department of Electronics and Communication Engineering St.Joseph's College of Engineering Chennai Tamil Nadu India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University (SIMATS) Chennai Tamil Nadu India Department of Electronics and Communication Engineering Faculty of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Tamil Nadu India

In Mobile Wireless Sensor Networks (MWSN), minimizing packet drop is vital. Many strategies are proposed to manage the packet drops. Though, these strategies need to be more capable of handling the packet drops proficiently. This approach proposes a Packet Drop Reduction using Volunteer nodes (PDRV) in MWSN. Volunteer nodes aim to reduce packet drops and delays in the network. In this approach, the volunteer node listens to the discharge data packet and then allocates the transmitter node. These nodes are selected based on node linkage, energy, communication processing time, and bandwidth. In addition, PDRV verifies the hash signature with One Time Key (OTK) for transmitting secure data. Hence, it reduces both the packet drops and the delay. Here, the volunteer nodes are selected by the node ability. The node linkage. energy, communication processing time, and bandwidth evaluate node ability. Experimental outcomes illustrate that the PDRV mechanism has reduced the network delay and packet losses.

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