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Drying-Mediated Self-Assembly of Graphene for Inkjet Printing of High-Rate Micro-supercapacitors

Nano-Micro Letters 2020年第3期12卷 155-168页

作者： Szymon Sollami Delekta Mika‑Matti Laurila Matti Mantysalo Jiantong Li School of Electrical Engineering and Computer Science KTH Royal Institute of TechnologyElectrum 22916440 KistaSweden Laboratory for Future Electronics Faculty of Information Technology and Communication SciencesTampere University33720 TampereFinland

Scalable fabrication of high-rate micro-supercapacitors(MSCs)is highly desired for on-chip integration of energy storage *** virtue of the special self-assembly behavior of 2D materials during drying thin films of their liquid dispersion,a new inkjet printing technique of passivated graphene micro-flakes is developed to directly print MSCs with 3D networked porous *** presence of macroscale through-thickness pores provides fast ion transport pathways and improves the rate capability of the devices even with solid-state *** multiple-pass printing,the porous microstructure effectively absorbs the successively printed inks,allowing full printing of 3D structured MSCs comprising multiple vertically stacked cycles of current collectors,electrodes,and sold-state *** all-solid-state heterogeneous 3D MSCs exhibit excellent vertical scalability and high areal energy density and power density,evidently outperforming the MSCs fabricated through general printing techniques.

关键词： High-rate micro-supercapacitor 3D micro-supercapacitor Drying-mediated self-assembly Graphene Inkjet printing

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A Single Switch Non-Isolated Ultra High Step-Up DC-DC Converter with Semiconductors Low Voltage Stress

A Single Switch Non-Isolated Ultra High Step-Up DC-DC Conver...

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International Smart Grid Workshop and Certificate Program (ISGWCP)

作者： Hossein Gholizadeh Mohammadfazel Dehghan Gevork B. Gharehpetian Navid Bayati School of Electrical and Computer Eng. University of Tehran Tehran Iran Electrical Engineering Faculty Shahid Beheshti University Tehran Iran Electrical Engineering Department Amirkabir University of Technology Tehran Iran Centre for Industrial Electronics University of Southern Denmark Sønderborg Denmark

ISBN: (数字)9798350361612

ISBN: (纸本)9798350361629

Non-isolated DC-DC converters are suitable for most of applications. Moreover, isolated converters suffer from electromagnetic interference (EMI), discontinuity of the input current, high voltage stress of semiconductors, and leakage inductances. This study proposes a non-isolated DC-DC converter with ultra-high voltage gain value. Moreover, the input current is continuous, and the input filter capacitor experiences a low current stress. Besides the high voltage gain, the converter switch is lower than the output voltage. Notably, the common ground of input source and load is present. The proposed topology is discussed in both ideal /non-ideal modes. Finally, experimental results are presented. This converter is proposed for high-voltage applications. The output voltage, the input voltage, and the output power are 1440 V, 10 V, and 80 W, respectively.

关键词： Low voltage Electromagnetic interference Voltage High-voltage techniques DC-DC power converters Switches Topology

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Data poisoning: issues, challenges, and needs

Data poisoning: issues, challenges, and needs

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7th IET Smart Cities Symposium (SCS 2023)

作者： Mohammad Aljanabi Alaa Hamza Omran Maad M Mijwil Mostafa Abotaleb El-Sayed M. El-kenawy Sahar Yousif Mohammed Abdelhameed Ibrahim Department of computer College of Education Aliarqai university Baghdad Iraq University of information technology and communications Baghdad Iraq Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt Computer Science Department Computer Science & Information Technology College Anbar University Anbar Iraq Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

Data poisoning attacks, where adversaries manipulate training data to degrade model performance, are an emerging threat as machine learning becomes widely deployed in sensitive applications. This paper provides a comprehensive overview of data poisoning including attack techniques, adversary incentives, impacts on security and reliability, detection methods, defenses, and key research gaps. We examine label flipping, instance injection, backdoors, and other attack categories that enable malicious outcomes ranging from IP theft to accidents in autonomous systems. Promising detection approaches include statistical tests, robust learning, and forensics. However, significant challenges remain in translating academic defenses like adversarial training and sanitization into practical tools ready for operational use. With safety and trustworthiness at stake, more research on benchmarking evaluations, adaptive attacks, fundamental tradeoffs, and real-world deployment of defenses is urgently needed. Understanding vulnerabilities and developing resilient machine learning pipelines will only grow in importance as data integrity is fundamental to developing safe artificial intelligence.

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Solid-state non-volatile memories based on vdW heterostructure-based vertical-transport ferroelectric field-effect transistors

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Science China(Information Sciences) 2024年第6期67卷 198-206页

作者： Qiyu YANG Zheng-Dong LUO Fei XIAO Junpeng ZHANG Dawei ZHANG Dongxin TAN Xuetao GAN Yan LIU Zhufei CHU Yinshui XIA Genquan HAN Hangzhou Institute of Technology Xidian University State Key Discipline Laboratory of Wide Band Gap Semiconductor Technology School of MicroelectronicsXidian University School of Artificial Intelligence Xidian University School of Materials Science and Engineering University of New South Wales (UNSW) Sydney ARC Centre of Excellence in Future Low-Energy Electronics Technologies (FLEET) University of New South Wales (UNSW) Sydney Key Laboratory of Light Field Manipulation and Information Acquisition Ministry of Industry and Information Technologyand Shaanxi Key Laboratory of Optical Information TechnologySchool of Physical Science and TechnologyNorthwestern Polytechnical University Faculty of Electrical Engineering and Computer Science Ningbo University

Driven by the explosive development of data-centric computation applications, it is becoming urgent to develop in-memory computing devices that are beyond the von Neumann architecture with an arrangement of separated logic and memory components. The transistor-type solid-state non-volatile memories,such as ferroelectric field-effect transistors(Fe FETs), have long been regarded as a competitive candidate for future in-memory computing architectures. However, the density scaling towards high-density arrays would require advanced Fe FETs with reduced footprints, which remains a great challenge so far. Here, a vertical-transport(VT) Fe FET that flips the charge transport channel perpendicular to the substrate plane is proposed, in which a ferroelectric gate and a van der Waals(vd W) heterojunction channel are vertically integrated, effectively reducing the device footprints. The proposed VT-Fe FET shows not only the robust binary non-volatile memory states but also several key synaptic functionalities at the device level. An artificial neural network with supervised learning was simulated based on the device conductance switching properties,showing excellent classification accuracy for the MNIST handwritten digits. These findings suggest that the proposed VT-Fe FET could offer a new solution for future non-volatile memories as well as more advanced neuromorphic systems.

关键词： vdW heterostructure non-volatile memory vertical-transport transistor ferroelectric field-effect transistor memristive devices

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Application of Modified MPPT Algorithms: A Comparative Study between Different Types of Solar Cells

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Applied Solar Energy (English translation of Geliotekhnika) 2020年第5期56卷 309-323页

作者： Khodair, D. Salem, M.S. Shaker, A. El Munim, H. E. Abd Abouelatta, M. Department of Electronics and Electrical Communications Faculty of Engineering Ain Shams University Cairo11517 Egypt Department of Engineering Physics Faculty of Engineering and Technology Future University Cairo Egypt Department of Computer Engineering Computer Science and Engineering College University of Ha’il Ha’il Saudi Arabia Department of Electrical Communication and Electronics Systems Engineering Faculty of Engineering Modern Science and Arts University Cairo Egypt Department of Engineering Physics and Mathematics Faculty of Engineering Ain Shams University Cairo11517 Egypt Department of Computer and Systems Engineering Faculty of Engineering Ain Shams University Cairo11517 Egypt

Abstract: Due to the broad needs for energy as market demands, searching on how to improve the efficiency of the PV systems is an essential concern for researchers to worry about. So, it is crucial to force the PV system to work at its peak power point in order to get the maximum available power from the photovoltaic panel. This paper presents a comprehensive comparison between four Maximum Power Point Tracking (MPPT) Algorithms;Perturb and Observe (P&O), Incremental Conductance (INC), Modified Variable Step Size Perturb and Observe (M-VSS-P&O) and Modified Variable Step Size Incremental Conductance (M-VSS-INC) by using of the DC-DC boost converter for three different kinds of solar cells. These cells are polycrystalline KC200GT cell, monocrystalline shell SQ85 cell and thin film shell ST40 cell. Simulations have been performed using MATLAB-SIMULINK for the three types of solar cells to investigate their performance under both standard test conditions (STC) and slowly varying and sudden changes in solar irradiance. The study has considered the response time, output power efficiency and steady-state-oscillations. The simulation results of the modified algorithms show an improvement in the cell performance in steady state conditions, tracking time and boost converter efficiency as well as an enhancement in the dynamic response in tracking the maximum power point (MPP) in varying climatic conditions over conventional algorithms. © 2020, Allerton Press, Inc.

关键词： Thin films

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A Hybrid Approach to Optimal Power Allocation in MIMO-NOMA: Integrating DGNN and Tyrannosaurus Optimization

A Hybrid Approach to Optimal Power Allocation in MIMO-NOMA: ...

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Sustainable Expert Systems (ICSES), International Conference on

作者： Anurag Vijay Agrawal A. Anuradha Kranti D Patil Vilaskumar Patil K. Karthikumar S V V Satyanarayana Tallapragada Department of Electronics and Communication Engineering Bhagwant Institute of Technology Muzaffarnagar Uttar Pradesh India Department of Computer Science Sri Aditya Degree College Bhimavaram Andhra Pradesh India Department of E & TC Trinity Academy of Engineering GHRCEM Pune Maharashtra India Department of Electronics and Communication Engineering Faculty of Engineering and Technology Sharnbasva University Kalaburagi Karnataka India Department of Electrical and Electronic Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi Chennai Tamil Nadu India Department of Electronics and Communication Engineering School of Engineering Mohan Babu University Tirupati Andhra Pradesh India

ISBN: (数字)9798331540364

ISBN: (纸本)9798331540371

One of the primary technologies necessary for the upcoming sixth generation of communication networks (6G) is massive multi-input multi-output, or MIMO. However, enormous MIMO presents a challenge in reducing energy use and the sum rate demand due to the power use of the several radio frequencies (RF) links in 6G technology. Therefore, this research presented a novel Deformable Graph Neural Network (DGNN) with Tyrannosaurus optimization for the optimal power distribution that maximized the sum rate and energy efficiency of the MIMO NOMA system. The adaptive mechanism of DGNN enables more accurate and efficient power allocation decisions. The integrated Tyrannosaurus optimization ensures the model converging on optimal power allocation strategies that maximize both sum rate and energy efficiency. The efficiency of the recommended model is compared in regarding sum rate and Energy Efficiency (EE) with the some of the recent approaches. The proposed method gained the greater sum rate and EE outperforming all other compared models.

关键词： 6G mobile communication Radio frequency NOMA Adaptation models Simulation Energy efficiency Hybrid power systems Resource management Optimization Signal to noise ratio

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Success History Adaptive Competitive Swarm Optimizer with Linear Population Reduction: Performance benchmarking and application in eye disease detection

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computers in Biology and Medicine 2025年 186卷 109587-109587页

作者： Zhong, Rui Wang, Zhongmin Hussien, Abdelazim G. Houssein, Essam H. Al-Shourbaji, Ibrahim Elseify, Mohamed A. Yu, Jun Information Initiative Center Hokkaido University Sapporo Japan College of Tropical Crops Yunnan Agricultural University Yunnan China Department of Computer and Information Science Linköping University Linköping Sweden Faculty of Science Fayoum University Faiyum Egypt Faculty of Computers and Information Minia University Minia Egypt Department of Electrical and Electronics Engineering Jazan Jazan University Jazan Saudi Arabia Department of Computer Science University of Hertfordshire Hatfield United Kingdom Department of Electrical Engineering Faculty of Engineering Al-Azhar University Qena Egypt Institute of Science and Technology Niigata University Niigata Japan

Eye disease detection has achieved significant advancements thanks to artificial intelligence (AI) techniques. However, the construction of high-accuracy predictive models still faces challenges, and one reason is the deficiency of the optimizer. This paper presents an efficient optimizer named Success History Adaptive Competitive Swarm Optimizer with Linear Population Reduction (L-SHACSO). Inspired by the effective success history adaptation scheme and linear population reduction strategy in Differential Evolution (DE), we introduce these techniques into CSO to enable the automatic and intelligent adjustment of hyper-parameters during optimization thereby balancing exploration and exploitation across different phases. To thoroughly investigate the performance of L-SHACSO, we conduct extensive numerical experiments on CEC2017, CEC2020, CEC2022, and eight engineering problems. State-of-the-art optimizers including jSO and L-SHADE-cnEpSin and recently proposed metaheuristic algorithms (MAs) such as RIME and the Parrot Optimizer (PO) are employed as competitors. Experimental results confirm the superiority of L-SHACSO across various optimization tasks. Furthermore, we integrate L-SHACSO into DenseNet and Extreme Learning Machine (ELM) and propose DenseNet-L-SHACSO-ELM for eye disease detection, where the features extracted by the pre-trained DenseNet are fed into L-SHACSO-optimized ELM for classification. Experiments on public datasets confirm the feasibility and effectiveness of our proposed model, which has great potential in real-world scenarios. The source code of this research is available at https://***/RuiZhong961230/L-SHACSO. © 2024 Elsevier Ltd

关键词： Swarm intelligence

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Utilizing Cooperative Spectrum Sharing for High Speed Wireless Networks

Utilizing Cooperative Spectrum Sharing for High Speed Wirele...

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Smart Generation Computing, Communication and Networking (SMART GENCON), International Conference on

作者： Dharmesh Dhabliya Vikash Kumar Kharbas Amritpal Sidhu Shweta Singh Gowrishankar J Jaisudha J Department of Information Technology Vishwakarma Institute of Information Technology Pune Maharashtra India Department of Computer Science & Engineering Vivekananda Global University Jaipur India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and technology Chitkara University Punjab India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Department of Computer Science Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Ramnagar Karnataka India Department of Electronics and Communication Engineering Prince Shri Venkateshwara Padmavathy Engineering College Chennai

Cooperative spectrum sharing is a method to allocate the radio spectrum amongst users for high-velocity wireless networks. It entails multiple unbiased customers that cooperate to percentage their respective spectra to maximize the records fee and the practical spectrum usage. The cooperative spectrum sharing technique lets non-overlapping frequency bands be utilized by multiple customers supplying a high statistics fee with minimum interference. It affords a green way of handling the radio spectrum, permitting multiple customers to share the to-be-had spectrum sources rather than having an unmarried consumer monopolize an upbeat frequency band. Cooperative spectrum sharing is likewise tremendous because of its low implementation cost and occasional power intake. Furthermore, it could be fast deployed to numerous areas to meet the increasing demand for excessive-speed Wi-Fi networks.

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High gain dual polarized antenna using a narrow pulse model in minkowski fractal patch 18

High gain dual polarized antenna using a narrow pulse model ...

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18th International Conference on Electrical engineering/electronics, computer, Telecommunications and Information technology, ECTI-CON 2021

作者： Wongsin, Norakamon Suangun, Thanakarn Mahatthanajatuphat, Chatree Akkaraekthalin, Prayoot Torrungrueng, Danai Rakluea, Paitoon Rajamangala University of Technology Thanyaburi Faculty of Engineering Department of Electronics and Telecommunications Pathum Thani Thailand University of Phayao Faculty of Engineering Department of Electrical Engineering Phayao Thailand King Mongkut's University of Technology North Bangkok Department of Electrical and Computer Engineering Bangkok Thailand King Mongkut's University of Technology North Bangkok Department of Teacher Training in Electrical Engineering Bangkok Thailand

ISBN: (纸本)9780738111278

High Gain Dual Polarized Antenna using narrow pulse model in Minkowski fractal Patch (MFP) is presented. This design consists of dual fed by two transmission line feed connectors placed onto the lower substrate as the feeding system, square patch antenna with a dimension of 60 mm × 60 mm, and dual-polarized MFP putting on the upper substrate. The simulated result shows that the antenna has a resonant frequency at 3.48 GHz, by the distance between MFP and square patch antenna is 10 mm. However, the radiation pattern between vertical and horizontal feed for standalone square patch antenna provides a similar gain of 2 dBi. The 2D Radiation patterns on the X-Z plane at phi-angle 45 and -45 degrees are dual-polarization. Moreover, the proposed antenna with MFS improves the gain of 5.6 dBi at 0 degrees on the X-Z plane at phi-angle 45 degrees and -45 degrees with HPBW of 71.7 degrees and 80.4 degrees, respectively. © 2021 IEEE.

关键词： Fractals

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An Enhanced Deep Neural Network Enabled with Cuckoo Search Algorithm for Intrusion Detection in Wide Area Networks 5

An Enhanced Deep Neural Network Enabled with Cuckoo Search A...

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5th International Conference on Information technology for Education and Development, ITED 2022

作者： Jimoh, Rasheed Gbenga Imoize, Agbotiname Lucky Awotunde, Joseph Bamidele Ojo, Stephen Akanbi, Mulikat Bola Bamigbaye, Jesufemi Ayotomide Faruk, Nasir University of Ilorin Faculty of Communication and Information Sciences Department of Computer Science Ilorin Nigeria University of Lagos Department of Electrical and Electronics Engineering Nigeria Institute of Digital Communication Ruhr University Department of Electrical Engineering and Information Technology Bochum44801 Germany Anderson University Department of Electrical and Computer Engineering AndersonSC29621 United States Kwara State Polytechnic Department of Computer Science Ilorin Nigeria Sule Lamido University Department of Physics Nigeria SLU Directorate of ICT Nigeria

ISBN: (纸本)9781509064229

A diversity of harmful software has been created as a result of the dramatic increase in internet usage, posing major risks to computer security. There is a great probability that the numerous computing operations performed through the network will be interfered with or altered, and as a result, effective intrusion detection systems are imperative. In addition, the attacks on the network are unpredictable, something that emphasizes the value of creating effective classification and prediction models. Machine learning (ML) and Deep Learning techniques have been used to evaluate datasets for intrusion detection systems (IDS). The employment of the DL-based approach enabled by feature selection helps to address challenges with data quality, handling high-dimensional data, and other related issues. Therefore, due to the large nature and volume of the IDS datasets, and the ability of DL-based models to learn categories incrementally through their hidden layer architecture to produce more accurate results in big data, this study proposes a Long-Short-Term-Memory (LSTM) model, and to further enhance the classification capacity of the projected DL method, the cuckoo search algorithm was introduced to select optimal features from the wireframe. The accuracy and subsequent detection of the suggested model positive and negative rates were evaluated. The experimental results show that the LSTM outperformed some other existing models with the highest classification accuracy of 99.7% and an error rate of 0.006. © 2022 IEEE.

关键词： Long short-term memory

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