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International Conference on Power Electronic Drives

作者： Vikash Kumar Saini Ameena S. Al-Sumaiti Rajesh Kumar Smart OR Lab Advanced Power and Energy Center Khalifa University Abu Dhabi UAE Department of Human Anatomy and Physiology Faculty of Health Sciences University of Johannesburg Johannesburg South Africa Department of Electrical Engineering RAMAN Lab Malaviya National Institute of Technology Jaipur India

ISBN: (数字)9798350372472

ISBN: (纸本)9798350372489

smart grid networks are gradually participating in highly efficient and advanced intelligent cyber-physical systems with high renewable energy penetration and information technologies. The reliable operation of the grid depends on forecasting methods widely used in the industrial, commercial, and residential sectors. The forecast's accuracy depends upon the data's quality, which is vulnerable to cyberattacks. False data attacks in training data pose a significant threat to forecasting accuracy. This study introduces a data-driven, explainable artificial intelligence (XAI) data poisoning technique that effectively compromises the forecasting model, even in the presence of outlier identification. This work investigated the impact of poisoning attacks on short-term solar forecasting with outlier identification. The XAI and t-SNE models are used for feature extraction and reduction, respectively. The various forecasting models are utilised, and performance results show that CNN-LSTM-Attentation is the most effective for forecasting compared to others. The obtained performance matrices MAE, MSE, RMSE, R2 score with the proposed model are 0.089, 0.026, 0.161, and 99.69%, respectively.

关键词： Deep learning Accuracy Explainable AI Training data Predictive models Feature extraction Data models smart grids Forecasting Computer crime

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A Silicon Monoxide Lithium-Ion Battery Anode with Ultrahigh Areal Capacity

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Nano-Micro Letters 2022年第3期14卷 229-243页

作者： Jiang Zhong Tao Wang Lei Wang Lele Peng Shubin Fu Meng Zhang Jinhui Cao Xiang Xu Junfei Liang Huilong Fei Xidong Duan Bingan Lu Yiliu Wang Jian Zhu Xiangfeng Duan State Key Laboratory for Chemo/Biosensing and Chemometrics College of Chemistry and Chemical EngineeringSchool of Physics and ElectronicsHunan Key Laboratory of Two‑Dimensional MaterialsEngineering Research Center of Advanced Catalysis of the Ministry of EducationHunan UniversityChangsha 410082People’s Republic of China International Graduate School at Shenzhen Tsinghua UniversityShenzhen 518057People’s Republic of China Key Laboratory of Structures Dynamic Behavior and Control of the Ministry of Education Key Laboratory of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information TechnologyHarbin Institute of TechnologyHarbin 150090People’s Republic of China School of Energy and Power Engineering North University of ChinaTaiyuan 030051People’s Republic of China Department of Chemistry and Biochemistry University of CaliforniaLos AngelesCA 90095USA

Silicon monoxide(SiO)is an attractive anode material for next-generation lithium-ion batteries for its ultra-high theoretical capacity of 2680 mAh g−*** studies to date have been limited to electrodes with a rela-tively low mass loading(<3.5 mg cm^(−2)),which has seriously restricted the areal capacity and its potential in practical *** areal capacity with such high-capacity materials is critical for capitalizing their potential in practi-cal ***,we report a monolithic three-dimensional(3D)large-sheet holey gra-phene framework/SiO(LHGF/SiO)composite for high-mass-loading *** specifically using large-sheet holey graphene building blocks,we construct LHGF with super-elasticity and exceptional mechanical robustness,which is essential for accommodating the large volume change of SiO and ensuring the structure integrity even at ultrahigh mass ***,the 3D porous graphene network structure in LHGF ensures excellent electron and ion *** systematically tailoring microstructure design,we show the LHGF/SiO anode with a mass loading of 44 mg cm^(−2)delivers a high areal capacity of 35.4 mAh cm^(−2)at a current of 8.8 mA cm^(−2)and retains a capacity of 10.6 mAh cm^(−2)at 17.6 mA cm^(−2),greatly exceeding those of the state-of-the-art commercial or research ***,we show an LHGF/SiO anode with an ultra-high mass loading of 94 mg cm^(−2)delivers an unprecedented areal capacity up to 140.8 mAh cm^(−2).The achievement of such high areal capacities marks a critical step toward realizing the full potential of high-capacity alloy-type electrode materials in practical lithium-ion batteries.

关键词： Silicon monoxide Large-sheet holey graphene Lithium-ion batteries High mass loading Ultra-high areal capacity

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Sustainable biogas production via anaerobic digestion with focus on CSTR technology: A review

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Journal of the Taiwan Institute of Chemical Engineers 2024年 162卷

作者： Shah, Sonal Vilas Yadav Lamba, Bhawna Tiwari, Avanish K. Chen, Wei-Hsin School of Advanced Engineering UPES Dehradun248007 India UPES Dehradun248007 India New Delhi110029 India Department of Aeronautics and Astronautics National Cheng Kung University Tainan701 Taiwan Research Center for Smart Sustainable Circular Economy Tunghai University Taichung407 Taiwan Department of Mechanical Engineering National Chin-Yi University of Technology Taichung411 Taiwan

Background: Waste pollution can negatively impact the ecosystem directly or indirectly. Utilizing waste as a resource to produce value-added products, like biofuels, is one option to address this problem. This would create a circular economy, which is in line with the Sustainable Development Goals (SDGs) 5, 7, 8, and 9 of the United Nations (UN). Anaerobic digestion (AD) is a technology that humans have extensively used to generate renewable energy. However, a great deal of research is required to optimize biogas production under diverse conditions. Several factors have been considered pertaining to the design and operation of digesters to ensure cost-effective and efficient digestion. Method: This article summarizes the underlying AD processes and the operating parameters used to enhance process efficiency. Considering older research and recent developments, a comprehensive summary of the theory of continuous stirred tank reactor (CSTR) technology for AD has been presented. The novelty of this review article lies in the emphasis on advanced intensification strategies to stabilize the AD process in CSTR for enhanced biogas/biomethane production. Furthermore, energy balance calculations of CSTR for biogas production are reviewed to promote the practical application of the technology on a global scale. Significant Findings: While pretreatment enhances the substrate's surface area, eliminates lignin, and decreases the crystallinity of cellulose to stimulate microbial uptake, co-digestion provides feedstock accessibility to the microorganisms and improves CH4 yield. Energy balance studies of CSTR revealed that the majority of the energy consumed is used during heating, mixing, and feedstock transportation. In addition, the use of digestate enhances the energy recovery efficiency of the CSTR system. With proper process optimizations, AD for biogas production can help the country overcome current energy issues. © 2024

关键词： Anaerobic digestion

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Tunable valley polarization and magnetic coupling by ferroelectric substrate in a VSe2/AgBiP2Se6 heterostructure

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Physical Review Applied 2024年第5期22卷 054064-054064页

作者： Bingwen Zhang Xiang Chen Guang Song Fenglin Deng Jun Wang Fujian Key Laboratory of Functional Marine Sensing Materials Center for Advanced Marine Materials and Smart Sensors College of Material and Chemical Engineering Minjiang University Fuzhou 350108 People’s Republic of China Department of Physics Huaiyin Institute of Technology Huaian 223003 China Key Laboratory of Magnetic Materials and Devices and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo 315201 People’s Republic of China

Valleytronics, exploring the valley degree of freedom in crystals akin to the charge in electronics and spin in spintronics, holds tremendous potential for information processing and computing in next-generation devices. We investigated the spin and valley manipulation of a 2H-VSe2 monolayer by stacking a ferroelectric substrate, AgBiP2Se6, to form a van der Waals heterostructure, VSe2/AgBiP2Se6, whose lattice mismatch is only 0.44%. Because the band alignment between VSe2 and AgBiP2Se6 is type I, the valley property at both the valence band and conduction band is well maintained, and the heterostructure exhibits an anomalous valley Hall effect. By switching the ferroelectric polarization direction, valley polarization can be effectively tuned, and the manipulation is nonvolatile because the heterostructure holds the ferroelectric bistability property. When the ferroelectric polarization points to VSe2, interlayer sliding can give rise to obvious valley polarization changes with a small sliding potential, and by interlayer charge transfer, the exchange coupling of V atoms can be obviously tuned, and therefore the Curie temperature is enhanced from 680 K to 975 K.

关键词： Magnetic phase transitions Multiferroics Valleytronics Ferroelectrics Heterostructures Janus materials Transition metal dichalcogenides Van der Waals systems

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MMR-Mamba: Multi-Modal MRI Reconstruction with Mamba and Spatial-Frequency Information Fusion

arXiv

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arXiv 2024年

作者： Zou, Jing Liu, Lanqing Chen, Qi Wang, Shujun Hu, Zhanli Xing, Xiaohan Qin, Jing Center for Smart Health The Hong Kong Polytechnic University Hong Kong The Department of Electronic Engineering and Information Science University of Science and Technology of China Anhui China The Department of Biomedical Engineering The Hong Kong Polytechnic University Hong Kong Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China The Department of Radiation Oncology Stanford University StanfordCA94305 United States

Multi-modal MRI offers valuable complementary information for diagnosis and treatment;however, its utility is limited by prolonged scanning times. To accelerate the acquisition process, a practical approach is to reconstruct images of the target modality, which requires longer scanning times, from under-sampled k-space data using the fully-sampled reference modality with shorter scanning times as guidance. The primary challenge of this task is comprehensively and efficiently integrating complementary information from different modalities to achieve high-quality reconstruction. Existing methods struggle with this: 1) convolution-based models fail to capture long-range dependencies;2) transformer-based models, while excelling in global feature modeling, struggle with quadratic computational complexity. To address this dilemma, we propose MMR-Mamba, a novel framework that thoroughly and efficiently integrates multimodal features for MRI reconstruction, leveraging Mamba’s capability to capture long-range dependencies with linear computational complexity while exploiting global properties of the Fourier domain. Specifically, we first design a Target modality-guided Cross Mamba (TCM) module in the spatial domain, which maximally restores the target modality information by selectively incorporating relevant information from the reference modality. Then, we introduce a Selective Frequency Fusion (SFF) module to efficiently integrate global information in the Fourier domain and recover high-frequency signals for the reconstruction of structural details. Furthermore, we devise an Adaptive Spatial-Frequency Fusion (ASFF) module, which mutually enhances the spatial and frequency domains by supplementing less informative channels from one domain with corresponding channels from the other. Extensive experiments on the BraTS and fastMRI knee datasets demonstrate the superiority of our MMR-Mamba over state-of-the-art reconstruction methods. Copyright © 2024, The Authors. All rights

关键词： Information fusion

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Effective Ambiguity Attack Against Passport-based DNN Intellectual Property Protection Schemes through Fully Connected Layer Substitution

arXiv

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arXiv 2023年

作者： Chen, Yiming Tian, Jinyu Chen, Xiangyu Zhou, Jiantao State Key Laboratory of Internet of Things for Smart City Department of Computer and Information Science University of Macau China Faculty of Innovation Engineering Macau University of Science and Technology China Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China

Since training a deep neural network (DNN) is costly, the well-trained deep models can be regarded as valuable intellectual property (IP) assets. The IP protection associated with deep models has been receiving increasing attentions in recent years. Passport-based method, which replaces normalization layers with passport layers, has been one of the few protection solutions that are claimed to be secure against advanced attacks. In this work, we tackle the issue of evaluating the security of passport-based IP protection methods. We propose a novel and effective ambiguity attack against passport-based method, capable of successfully forging multiple valid passports with a small training dataset. This is accomplished by inserting a specially designed accessory block ahead of the passport parameters. Using less than 10% of training data, with the forged passport, the model exhibits almost indistinguishable performance difference (less than 2%) compared with that of the authorized passport. In addition, it is shown that our attack strategy can be readily generalized to attack other IP protection methods based on watermark embedding. Directions for potential remedy solutions are also given. Copyright © 2023, The Authors. All rights reserved.

关键词： Deep neural networks

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Boosting flexible electronics with integration of two-dimensional materials

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InfoMat 2024年第7期6卷 1-50页

作者： Chongyang Hou Shuye Zhang Rui Liu Thomas Gemming Alicja Bachmatiuk Hongbin Zhao Hao Jia Shirong Huang Weijia Zhou Jian-Bin Xu Jinbo Pang Mark HRümmeli Jinshun Bi Hong Liu Gianaurelio Cuniberti Institute for Advanced Interdisciplinary Research(iAIR) University of JinanJinanthe People’s Republic of China State Key Laboratory of Advanced Welding and Joining Harbin Institute of TechnologyHarbinthe People’s Republic of China State Key Laboratory of Transducer Technology Shanghai Institute of Microsystem and Information TechnologyChinese Academy of SciencesShanghaithe People’s Republic of China Institute for Materials Chemistry Leibniz Institute for Solid State and Materials Research Dresden(IFW Dresden)DresdenGermany Lukasiewicz Research Network PORT Polish Center for Technology DevelopmentWroclawPoland State Key Laboratory of Advanced Materials for Smart Sensing GRINM Group Co.LtdBeijingthe People’s Republic of China Institute for Materials Science and Max Bergmann Center of Biomaterials TUD Dresden University of TechnologyDresdenGermany Department of Electronic Engineering The Chinese University of Hong KongHong Kong SARthe People’s Republic of China Institute of Environmental Technology VSB-Technical University of OstravaOstravaCzech Republic College of Energy Soochow Institute for Energy and Materials InnovationsSoochow UniversitySuzhouthe People’s Republic of China Key Laboratory of Advanced Carbon Materials and Wearable Energy Technologies of Jiangsu Province Soochow UniversitySuzhouthe People’s Republic of China Centre of Polymer and Carbon Materials Polish Academy of SciencesZabrzePoland School of Integrated Circuits University of Chinese Academy of SciencesBeijingthe People’s Republic of China Institute of Microelectronics of Tianjin Binhai New Area Tianjinthe People’s Republic of China Institute of Microelectronics Chinese Academy of SciencesBeijingthe People’s Republic of China State Key Laboratory of Crystal Materials Center of Bio and Micro/Nano Functional MaterialsShandong UniversityJinanthe People’s Republic of China

Flexible electronics has emerged as a continuously growing field of ***-dimensional(2D)materials often act as conductors and electrodes in elec-tronic devices,holding significant promise in the design of high-performance,flexible *** studies have focused on harnessing the potential of these materials for the development of such ***,to date,the incorporation of 2D materials in flexible electronics has rarely been summa-rized or ***,there is an urgent need to develop compre-hensive reviews for rapid updates on this evolving *** review covers progress in complex material architectures based on 2D materials,including interfaces,heterostructures,and 2D/polymer ***-ally,it explores flexible and wearable energy storage and conversion,display and touch technologies,and biomedical applications,together with integrated design *** the pursuit of high-performance and high-sensitivity instruments remains a primary objective,the integrated design of flexible electronics with 2D materials also warrants *** combin-ing multiple functionalities into a singular device,augmented by machine learning and algorithms,we can potentially surpass the performance of existing wearable ***,we briefly discuss the future trajectory of this burgeoning *** review discusses the recent advancements in flex-ible sensors made from 2D materials and their applications in integrated archi-tecture and device design.

关键词： 2D materials biomedical healthcare energy storage and conversion flexible electronics heterostructures sensors

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Highly Durable and Conductive Korea Traditional Paper (Hanji) Embedded with Ti3C2TX Mxene for Hanji-Based Paper Electronics

SSRN

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SSRN 2024年

作者： Jeong, Jaehoon Seok, Hae-Jun Shin, Hak Choi, Su Bin Kim, Jong-Woong Kim, Han-Ki School of Advanced Materials Science and Engineering Sungkyunkwan University Gyeonggi-do Suwon16419 Korea Republic of Department of Fine Arts Sungkyunkwan University Seoul03063 Korea Republic of Department of Smart Fab. Technology Sungkyunkwan University Gyeonggi-do Suwon16419 Korea Republic of

Lightweight, low-cost, eco-friendly, and mechanically flexible Ti3C2TX (MXene) electrodes require for paper electronics. We develop a highly durable and conductive traditional Korean paper (Hanji) covered with MXene for Hanji-based paper electronics. The effective networking of MXene on the cellulose structure of Hanji leads to a highly conductive and flexible Hanji which acts as a multi-functional paper for Hanji-based paper electronics. Owing to the synergetic combination of Hanji and MXene, the as-prepared Hanji/MXene exhibits a low sheet resistance of 0.62 Ohm square-1, and outstanding mechanical stability without breaking the Hanji fibers. To further evaluate the potential of our Hanji/MXene composite, its performance in electromagnetic interference (EMI) shielding, interconnectors, heaters, supercapacitors, and temperature sensor applications is investigated. Shielding and heater paper samples employing Hanji/MXene-based electrodes show an EMI shielding efficiency (EMI SE) of 43.3 dB and saturation temperature of 76 °C at a low voltage of 3 V. Moreover, the Hanji/MXene-based supercapacitors exhibit a capacitance of 139.6 mF cm-2 at a current density of 1 mA cm-2. Furthermore, the Hanji/MXene-based temperature sensors exhibit an effective sensing performance over a wide temperature range. Overall, the successful operation of Hanji-based EMI shielding devices, interconnectors, heaters, supercapacitors, and temperature sensors indicates that Hanji/MXene serves as a promising conductive paper substrate for multi-functional paper electronics. © 2024, The Authors. All rights reserved.

关键词： Supercapacitor

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Techno Economic Feasibility Analysis of Grid-Connected Microgrid by Using Solar PV for Residential Usage 9

Techno Economic Feasibility Analysis of Grid-Connected Micro...

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9th Edition of IEEE Region 10 Humanitarian technology Conference, R10-HTC 2021

作者： Mahmud, Dewan Mahnaaz Hasan, Sayeed Ahmed, S.M. Masum Zeyad, Mohammad Advanced Bioinformatics Computational Biology and Data Science Laboratory Bangladesh Energy and Technology Research Division Chattogram Bangladesh Erasmus+ Joint MSC In Smart Cities and Communities Faculty of Engineering Mons Belgium Erasmus+ Joint MSC In Smart Cities and Communities Department of Thermal Engineering Bilbao Spain

ISBN: (纸本)9781665432405

Renewable energy systems (RES) are becoming more prominent because of the depletion of natural resources. Optimum sizing of the hybrid RES is necessary to ensure that renewable energy sources penetrate. Improper sizing may result in higher initiating costs or an inability to meet load demand under various weather conditions. By analyzing with Hybrid Optimization Multiple Energy Resources (HOMER pro), this study shows the ideal hybrid energy system that provides the lowest cost of energy production, emissions, and so on. This study provides a grid-connected hybrid power system model based on metrological data collected from a residential building in Mohammadpur, Dhaka, Bangladesh. Solar energy is used as a sustainable energy source thus the cost of the system was decreased, which is also environmentally friendly. This renewable energy also helped to minimize the levelized cost of energy (COE). The conclusion estimates operational costs, production costs, net present cost, and energy cost for the two combinations evaluated for the proposed microgrid system. According to the simulation results, delivering power to the load via a microgrid would be a viable and cost-effective solution. © 2021 IEEE.

关键词： Battery storage

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Using Deep Reinforcement Learning in Optimal Energy Management for Residential House Aggregators with Uncertain User Behaviors

Using Deep Reinforcement Learning in Optimal Energy Manageme...

引用

IEEE Student Conference on Electric Machines and Systems

作者： Yujun Lin Linfang Yan Hongxun Hui Yin Chen Xia Chen Jinyu Wen State Key Laboratory of Advanced Electromagnetic Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan China State Grid (Suzhou) City & Energy Research Institute Suzhou China Department of Electrical and Computer Engineering State Key Laboratory of Internet of Things for Smart City University of Macau Macau China Department of Electronic and Electrical Engineering University of Strathclyde Glasgow U.K.

ISBN: (数字)9798350366945

ISBN: (纸本)9798350366952

In this study, the home energy management problem, which can be regarded as a high-dimensional optimization problem, for numerous residential houses, is addressed. The concept of the aggregator is utilized to reduce the state and action space and to handle the high dimensionality. A two-stage deep reinforcement learning (DRL)-based approach is proposed for the aggregators to track the schedule from a superior grid and guarantee the operation constraints. In the first stage, a DRL control agent is set to learn the optimal scheduling strategy interacting with the environment based on the soft-actor-critic framework and generate the aggregate control actions. In the second stage, the aggregate control actions are disaggregated to individual appliances considering the users' behaviors. The uncertainty of an electric vehicle's charging demand is quantitatively expressed based on the driver's experience. An aggregate anxiety concept is introduced to characterize the driver's anxiety on the electric vehicle's range and uncertain events. Finally, simulations are conducted to verify the effectiveness of the proposed approach under dynamic user behaviors, and comparisons show the superiority of the proposed approach over other benchmark methods.

关键词： Schedules Uncertainty Aggregates Anxiety disorders Optimal scheduling Deep reinforcement learning Electric vehicle charging Temperature control Vehicle dynamics Resistance heating

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