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8th International Conference on Information and Communication Technology for Competitive Strategies, ICTCS 2023

作者： Ravindran, Rahulkrishnan Abhishek, S. Anjali, T. Shenoi, Ashwin Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Amritapuri India CRED Bangalore India

ISBN: (纸本)9789819712595

This SQL injection and cross-site scripting (XSS) extension is a Google chrome-based software program that is designed to detect and prevent SQLi and XSS attacks on web applications. These types of injections or attacks are among the most common and dangerous threats to web applications, as they can allow hackers a loophole to access and avail sensitive data or take control of a website, SQLi, and XSS extension typically works by analyzing incoming data and queries for suspicious patterns and characters, such as SQL commands or HTML code. An SQL based injection and a cross-site scripting XSS extension is an essential tool for developers, security analysts, and administrators who want to ensure the security and integrity of their web applications, prevent data breaches, and protect their users from potential harm. Web applications require rigorous security measures to protect them from various malicious attacks or injections and prevent data breaches. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Sensitive data

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A Deep Echo State Network With Scaling Factor Activation Functions for Fault Diagnosis of electrical Drive Systems

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IEEE Transactions on Transportation Electrification 2025年第3期11卷 7874-7884页

作者： Gong, Yuanpeng Jiang, Yulian Cheng, Chao Chen, Hongtian Wang, Shenquan Changchun University of Technology College of Electrical and Electronic Engineering Changchun130012 China Changchun University of Technology School of Computer Science and Engineering Changchun130012 China Shanghai Jiao Tong University Department of Automation Shanghai200240 China

Deep echo state networks (Deep-ESNs) play an important role in fault diagnosis. However, due to its limitation in the iterative process of dealing with nonlinear data, the accuracy of fault diagnosis is relatively low. In order to improve the fault diagnosis accuracy of electrical drive systems, this article proposes a novel Deep-ESN based on the synergistic effect of golden jackal optimization (GJO), variational mode decomposition (VMD), and scaling factor activation function, called GVSD-ESN. The main work of this study contains: 1) the novel scaling factor activation function is proposed to solve the gradient vanishing problem in the Deep-ESN model;2) GJO is used to solve high-dimensional optimization problems of VMD;3) the power spiral curve is proposed to optimize the position update equation of GJO, which solves the problem of falling into the local optimal;and 4) adding a sparse regularization layer between reservoirs can enhance the class definition of GVSD-ESN. Finally, the effectiveness of the proposed method is verified in electrical drive systems. © 2015 IEEE.

关键词： Variational mode decomposition

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Impedance Emulation Control of Wave Energy Converters 50

Impedance Emulation Control of Wave Energy Converters

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Chandran, Pranav Kim, InYong Brekken, Ted Johnson, B. Chandra Family Department of Electrical and Computer Engineering University of Texas at Austin AustinTX78701 United States School of Electrical Engineering and Computer Science CorvallisOR97331 United States

ISBN: (纸本)9781665464543

Modeling and control of wave energy conversion (WEC) systems for maximum power extraction is challenging due to complex multiphysics that include fluids, mechanics, and machine drives. To uncover an intuitive model that clearly depicts WEC system operation, we utilize a force-current equivalent circuit framework which then enables us to design an impedance emulation control strategy. To provide context for our framework, we focus on a standard reference model-3 (RM3) point absorber device coupled to a permanent magnet synchronous generator. After the proposed extremum seeking controller is computed, we experimentally validate its performance on a platform that consists of two back-to-back connected inverters that emulate the WEC system. © 2024 IEEE.

关键词： Wave energy conversion

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Adversarial Modality Alignment Network for Cross-Modal Molecule Retrieval

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第1期5卷 278-289页

作者： Zhao, Wenyu Zhou, Dong Cao, Buqing Zhang, Kai Chen, Jinjun Hunan University of Science and Technology School of Computer Science and Engineering Xiangtan425100 China Swinburne University of Technology Department of Computing Technologies MelbourneVIC3122 Australia Guangdong University of Foreign Studies School of Information Science and Technology Guangzhou510420 China

The cross-modal molecule retrieval (Text2Mol) task aims to bridge the semantic gap between molecules and natural language descriptions. A solution to this nontrivial problem relies on a graph convolutional network (GCN) and cross-modal attention with contrastive learning for reasonable results. However, there exist the following issues. First, the cross-modal attention mechanism is only in favor of text representations and cannot provide helpful information for molecule representations. Second, the GCN-based molecule encoder ignores edge features and the importance of various substructures of a molecule. Finally, the retrieval learning loss function is rather simplistic. This article further investigates the Text2Mol problem and proposes a novel adversarial modality alignment network (AMAN) based method to sufficiently learn both description and molecule information. Our method utilizes a SciBERT as a text encoder and a graph transformer network as a molecule encoder to generate multimodal representations. Then, an adversarial network is used to align these modalities interactively. Meanwhile, a triplet loss function is leveraged to perform retrieval learning and further enhance the modality alignment. Experiments on the ChEBI-20 dataset show the effectiveness of our AMAN method compared with baselines. © 2020 IEEE.

关键词： Semantics

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Soil Analysis Using Deep Learning for Precision Agriculture 1

Soil Analysis Using Deep Learning for Precision Agriculture

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1st International Conference on Pioneering Developments in computer science and Digital Technologies, IC2SDT 2024

作者： Fotabong, Thierry Forsack Muhammad, Abdullahi Keisham, Murphy Mehrotra, Tushar Singh, Rajneesh Kumar Singh, S. Pratap Agrawal, Arun Prakash Sharda School of Engineering and Technology Sharda University Department of Computer Science and Applications Greater Noida India School of Computing Science and Engineering Galgotias University Department of Computer Science and Engineering Greater Noida India Symbiosis Institute of Technology Nagpur Campus Deemed University Pune India

ISBN: (纸本)9798350365016

This research explores the application of deep learning techniques for soil analysis in precision agriculture, focusing on the classification of soil types using convolutional neural networks (CNNs). The study addresses the limitations of traditional soil classification methods, which are often labor-intensive and reliant on expert judgment. The proposed approach involves collecting soil image data, preprocessing it using techniques such as Gabor filtering, and classifying the images with a CNN model. The methodology includes data acquisition, feature extraction, and model training, aiming to accurately predict soil parameters using diverse input data sources like sensor readings and satellite imagery. The potential benefits of this approach include real-time monitoring, optimal fertilizer application, and enhanced crop management, which can contribute to sustainable agricultural practices and food security. © 2024 IEEE.

关键词： Convolutional neural networks

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Evaluation of Different Network Coding Algorithm Strategies for Wireless Systems 5th

Evaluation of Different Network Coding Algorithm Strategies ...

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5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Parameswaran, Murali Savita Kannagi, A. Panwar, Rahul School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bangalore India Department of Electrical Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India

ISBN: (纸本)9789819780426

These research objectives are to evaluate and compare distinct community coding algorithms that can be applied in wireless networks to maximize network efficiency, throughput, and facts switch velocity. Special procedures are taken, such as coding in any respect of nodes within the community or sure nodes, which includes area nodes or routers. One-of-a-kind coding algorithm techniques might be tested in this study, including threshold coding and coded pooling. The chosen method will depend on the type of community, the scale, the traffic charge, and the favored performance goals, which include latency or bandwidth. Through leveraging network coding, packets can be transmitted and retransmitted without re-encoding. Studies have been carried out to evaluate the overall performance of diverse network coding algorithms for wireless networks inclusive of flooding, random linear network coding (RLNC), most distance separable codes (MDSC), directional network coding (DANC) and layered community coding (LNC). At the same time, MDSC and directional network coding have been proven more potent in factor-to-factor conversation eventualities. LNC is the most efficient average in many instances because of its ability to modify in real-time to changing link conditions. All of those algorithms provide a couple of advantages for wireless networks. This abstract affords an overview of the unique algorithm techniques, evaluates their effectiveness in numerous scenarios, and highlights their blessings for wireless networks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Network coding

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IMPACT ASSESSMENT OF THE ORDER TYPES MIX IN THE GREEK DAY-AHEAD ELECTRICITY MARKET 14

IMPACT ASSESSMENT OF THE ORDER TYPES MIX IN THE GREEK DAY-AH...

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14th Mediterranean Conference on Power Generation Transmission, Distribution and Energy Conversion, MEDPOWER 2024

作者： Moustakas, Konstantinos Papazoglou, Georgios K. Bakirtzis, Emmanouil A. Karangelos, Efthymios Papavasiliou, Anthony Hellenic Energy Exchange S A Athens Greece School of Electrical and Computer Engineering Aristotle University of Thessaloniki Thessaloniki Greece School of Electrical and Computer Engineering National Technical University of Athens Athens Greece Department of Electrical Engineering and Computer Science Universite de Liege Liege Belgium

ISBN: (纸本)9781837242689

The Greek Day-Ahead Electricity Market facilitates a diverse array of order types and offers participants a plethora of choices. While Block Orders are theoretically supported, their accessibility is confined to a subset of market participants so as to ensure the Market Clearing Price formation and the technical feasibility of the resulting Market Schedules. This paper presents a quantitative analysis of the implications of lifting the currently applicable restrictions on the availability of Block Orders in the Greek Day-Ahead Electricity Market, based on past historical data. Clustering techniques are used to convert anonymized past Hourly Hybrid Orders into plausible Block Orders A market clearing simulator is then used to derive the outcome of the market given the created plausible Block Orders. Simulations are conducted under Coupling and Isolated conditions for three Indicative weeks in 2022 and while exploring various scenarios for the specifications of the new Block Orders and the categories of participants who could use them. Assessment metrics encompass Marginal Clearing Price (MCP) statistics, instances of Paradoxically Rejected Block Orders, and Lost Opportunity Cost, shedding light on whether restrictions should be upheld or mitigated. © The Institution of engineering & Technology 2024.

关键词： Costs

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Enhancing the Performance of Wireless Ad-Hoc Network: Through TCP/IP Protocols

Enhancing the Performance of Wireless Ad-Hoc Network: Throug...

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2024 International Conference on Smart Devices, ICSD 2024

作者： Chaudhary, Lalitesh Sharma, Sushil Kumar Kumar, Santosh Institute of Technology and Management Department of Computer Science Aligarh India Galgotias University School of Computing Science and Engineering Greater Noida India

ISBN: (纸本)9798350394412

Remote correspondence is quickly taking the place of wired correspondence, posing new difficulties for Transmission Control Protocol (TCP). TCP is enhanced in a few ways to detect this issue. This paper addresses the protocol and display upgrade model for remote, specially designated computers over TCP. TCP is essentially a transport protocol created for web applications that are wired. However, the TCP misinterprets some conditions, such obstructions that slow down transmission and taint presentation quality, resulting in decreased throughput. This is because remote specially designated systems are unstable and vulnerable to unforeseen faults associated to geography. Because of poor connections and high congestion, TCP must be modified in order to prevent package loss. Accordingly, the evaluation of the recommended TCP presentation for a remote specially defined system is managed by this study. © 2024 IEEE.

关键词： Transmission control protocol

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Non-planar dielectrics derived thermal and electrostatic field inhomogeneity for boosted weather-adaptive energy harvesting

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National science Review 2023年第9期10卷 248-257页

作者： Yi Zhou Tianpeng Ding Yin Cheng Yi Huang Wu Wang Jianmin Yang Lin Xie Ghim Wei Ho Jiaqing He Shenzhen Key Laboratory of Thermoelectric Materials and Department of Physics Southern University of Science and Technology Department of Electrical and Computer Engineering National University of Singapore School of Electronic Science and Engineering State Key Laboratory of Electronic Thin Film and Integrated Devices University of Electronic Science and Technology of China Department of Materials Science and Engineering National University of Singapore Institute of Materials Research and Engineering Agency for ScienceTechnology and Research (A*STAR) GuangdongHong Kong-Macao Joint Laboratory for Photonic-Thermal-Electrical Energy Materials and Devices Southern University of Science and Technology

Weather-adaptive energy harvesting of omnipresent waste heat and rain droplets,though promising in the field of environmental energy sustainability,is still far from practice due to its low electrical output owing to diele ctric structure irrationality and *** we present atypical upcycling of ambient heat and raindrop energy via an all-in-one non-planar energy harvester,simultaneously increasing solar pyroelectricity and droplet-based triboelectricity by two-fold,in contrast to conventional *** delivered non-planar dielectric with high transmittance confines the solar irradiance onto a focal hotspot,offering transverse thermal field propagation towards boosted inhomogeneous polarization with a generated power density of 6.1 mW m-2at 0.2 ***,the enlarged lateral surface area of curved architecture promotes droplet spreading/separation,thus travelling the electrostatic field towards increased *** enhanced pyroelectric and triboelectric outputs,upgraded with advanced manufacturing,demonstrate applicability in adaptive sustainable energy harvesting on sunny,cloudy,night,and rainy *** findings highlight a facile yet efficient strategy,not only for weather-adaptive environmental energy recovery but also in providing key insights for spatial thermal/electrostatic field manipulation in thermo electrics and ferroelectrics.

关键词： non-planar dielectrics heat manipulation pyroelectrics weather-adaptive energy harvesting

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Object Detection Using Deep Learning for Blind People with Voice Feedback

Object Detection Using Deep Learning for Blind People with V...

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2024 International Conference on System, Computation, Automation and Networking, ICSCAN 2024

作者： Pongiannan, R.K. Franklin, J. Richard Pravin, A. Maria, Marissa Mishra, Sarvottam Kumar Srm Institute of Science and Technology Department of Computing Technologies Kattankulathur India Srm Institute of Science and Technology Department of Electrical and Electronics Engineering Kattankulathur India Computer Science Engineering Srm Institute of Science and Technology Kattankulathur India

ISBN: (纸本)9798331510022

BlindSpace is an innovative application aimed at improving the lives of visually challenged individuals. Leveraging cutting-edge image captioning and object detection technologies, the app allows users to capture images using their smartphone's camera, providing detailed scene descriptions and audibly identifying objects within those images. This not only enhances users' understanding of their environment but also fosters independence and confidence. With voice commands and text-to-speech technology, the application offers a user-friendly experience and can be customized to individual preferences. Operating efficiently offline, BlindSpace stands as a significant leap in accessibility technology, bridging the gap between the visual and non-visual worlds for visually challenged individuals and promoting inclusivity and autonomy. © 2024 IEEE.

关键词： Smartphones

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