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作者： Chenlong Yin Weiheng Su Zheyong Lin Yuyang Xu School of Computer Science and Technology University of Science and Technology of China School of Informatics Computingand Cyber SystemsNorthern Arizona University School of Geodesy and Geomatics Wuhan University Division of General Studies University of Illinois at Urbana Champaign

We present a method that enhances the RATGAN using the idea of CycleGAN to prevent the model from *** generator with the proposed recurrent affine transformation for text-to-image synthesis and the fusion blocks are connected by an RNN during the generation of fake images to assure the global assignment of text *** transformation from the phony images to the text is then accomplished using a CNN and encoder with LSTM.A comparison of the generated text with the original text ensures the generator's *** order to achieve the state of the art,we evaluated both unconditional and conditional generation's effectiveness in relation to the accepted standards.

关键词： RAT-Gan Cycle Gan Text-to-Image

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Pose Estimation of Spacecraft Using Dual Transformers and Efficient Bayesian Hyperparameter Optimization

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International Journal of Advanced Computer Science and Applications 2025年第4期16卷 629-644页

作者： Raja, N. Kannaiya Ramesh, Janjhyam Venkata Naga El-Ebiary, Yousef A. Baker Muniyandy, Elangovan Reddy, N. Konda Kumar, Vanipenta Ravi Devarasetty, Prasad School of Computing Science and Engineering VIT Bhopal University Madhya Pradesh Bhopal466114 India Department of CSE Graphic Era Hill University Dehradun248002 India Department of CSE Graphic Era Deemed To Be University Uttarakhand Dehradun248002 India Faculty of Informatics and Computing UniSZA University Malaysia Department of Biosciences Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai602 105 India Applied Science Research Center Applied Science Private University Amman Jordan Department of Engineering Mathematics K L University Greenfields Guntur Dist Andhra Pradesh Vaddeswaram522302 India Department of Mathematics Annamacharya University New Boyanapalli Rajampet India Department of Computer Science and Engineering DVR & Dr HS MIC College of Technology Andhra Pradesh Kanchikacherla India

Spacecraft pose estimation is an essential contribution to facilitating central space mission activities like autonomous navigation, rendezvous, docking, and on-orbit servicing. Nonetheless, methods like Convolutional Neural Networks (CNNs), Simultaneous Localization and Mapping (SLAM), and Particle Filtering suffer significant drawbacks when implemented in space. Such techniques tend to have high computational complexity, low domain generalization capacity for varied or unknown conditions (domain generalization problem), and accuracy loss with noise from the space environment causes such as fluctuating lighting, sensor limitations, and background interference. In order to overcome these challenges, this study suggests a new solution through the combination of a Dual-Channel Transformer Network with Bayesian Optimization methods. The innovation is at the center with the utilization of EfficientNet, augmented with squeeze-and-excitation attention modules, to extract feature-rich representations without sacrificing computational efficiency. The dual-channel architecture dissects satellite pose estimation into two dedicated streams—translational data prediction and orientation estimation via quaternion-based activation functions for rotational precision. Activation maps are transformed into transformer-compatible sequences via 1×1 convolutions, allowing successful learning in the transformer's encoder-decoder system. To maximize model performance, Bayesian Optimization with Gaussian Process Regression and the Upper Confidence Bound (UCB) acquisition function makes the optimal hyperparameter selection with fewer queries, conserving time and resources. This entire framework, used here in Python and verified with the SLAB Satellite Pose Estimation Challenge dataset, had an outstanding Mean IOU of 0.9610, reflecting higher accuracy compared to standard models. In total, this research sets a new standard for spacecraft pose estimation, by marrying the versatility of deep le

关键词： Convolutional neural networks

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Obfuscated Malware Detection: Impacts on Detection Methods 15th

Obfuscated Malware Detection: Impacts on Detection Methods

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15th International scientific conferences on research and applications in the field of intelligent information and database systems, ACIIDS 2023

作者： Gorment, Nor Zakiah Selamat, Ali Krejcar, Ondrej Malaysia-Japan International Institute of Technology Universiti Teknologi Malaysia Jalan Sultan Yahya Petra Kuala Lumpur54100 Malaysia School of Computing Faculty of Engineering Universiti Teknologi Malaysia Johor Bahru Johor81310 Malaysia Universiti Teknologi Malaysia Johor Bahru Johor81310 Malaysia College of Computing and Informatics Universiti Tenaga Nasional Jalan IKRAM-UNITEN Selangor Kajang43000 Malaysia Center for Basic and Applied Research Faculty of Informatics and Management University of Hradec Kralove Hradec Kralove50003 Czech Republic

ISBN: (纸本)9783031424298

Obfuscated malware poses a challenge to traditional malware detection methods as it uses various techniques to disguise its behavior and evade detection. This paper focuses on the impacts of obfuscated malware detection techniques using a variety of detection methods. Furthermore, this paper discusses the current state of obfuscated malware, the methods used to detect it, and the limitations of those methods. The impact of obfuscation on the effectiveness of detection methods is also discussed. An approach for the creation of advanced detection techniques based on machine learning algorithms is offered, along with an empirical examination of malware detection performance assessment to battle obfuscated malware. Overall, this paper highlights the importance of staying ahead of the constantly evolving threat landscape to safeguard computer networks and systems. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Machine learning

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Classification of SEMG Signal Based Hand Movements by Using Support Vector Machine

Classification of SEMG Signal Based Hand Movements by Using ...

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IEEE Symposium on Computers & informatics (ISCI)

作者： Syeda Rabail Zahra Sadia Ismail Muhammad Danish Ali Muhammad Amir Khan Mohamad Yusof Darus Tahseen Mazhar Institute of Computing & Information Technology GOMAL University Dera Ismail Khan Pakistan Computer Science COMSATS University Islamabad Abbottabad Pakistan School of Computing Sciences College of Computing Informatics and Mathematics Universiti Teknologi MARA Shah Alam Selangor Malaysia Department of Computer Science Virtual University of Pakistan

ISBN: (数字)9798350353853

ISBN: (纸本)9798350353860

This paper explores the application of Surface Electromyography (SEMG) for hand movement classification using machine learning techniques. SEMG signals play a crucial role in sports medicine, rehabilitation, prosthesis control, and medical diagnosis. The study addresses a multi-class problem, extending the dataset with limited prior exploration. Nine features from SEMG signal's time domain are extracted, including Maximum Amplitude, Root Mean Square, Slope Sign Change, Variance, Simple Square Integral, Zero Crossing, Waveform Length, and Willison Amplitude. Linear Discriminant Analysis is employed for dimensionality reduction as a feature selection technique. The proposed algorithm achieves an overall classification accuracy of 72% for the classification of six different hand movements performed by five healthy subjects using Support Vector Machines. This research contributes to the advancement of SEMG-based hand movement classification in various practical applications.

关键词： Support vector machines Feature extraction Vectors Classification algorithms Medical diagnosis Time-domain analysis Root mean square

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A Steganographic Method for Color Images using the Salp Swarm Algorithm and Chaotic Maps

A Steganographic Method for Color Images using the Salp Swar...

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Conference on Local Computer Networks (LCN)

作者： Aya Jaradat Moad Mowafi Eyad Taqieddin Network Engineering and Security Dept Jordan University of Science and Technology Irbid Jordan School of Computing and Informatics Al Hussein Technical University Amman Jordan

The availability of high resolution images allows for using steganography to hide the presence of secret information. An issue of importance is to guarantee that the hidden data neither affects the quality of the images nor is it visually perceived. Another factor to consider is the capacity of embedding in the cover images without detection. In this paper we employ the Discrete Cosine Transform compression with quantization for lossy compression. We use the Salp Swarm Algorithm in conjunction with chaotic maps to find optimal locations in the cover images for data embedding in the LSBs. When chaotic maps are inserted into the SSA algorithm environment, the proposed method has achieved satisfactory results with minimal impact on the PSNR.

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RiskQ: risk-sensitive multi-agent reinforcement learning value factorization 23

RiskQ: risk-sensitive multi-agent reinforcement learning val...

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Proceedings of the 37th International Conference on Neural Information Processing Systems

作者： Siqi Shen Chennan Ma Chao Li Weiquan Liu Yongquan Fu Songzhu Mei Xinwang Liu Cheng Wang Fujian Key Laboratory of Sensing and Computing for Smart Cities School of Informatics Xiamen University (XMU) China and Key Laboratory of Multimedia Trusted Perception and Efficient Computing XMU China School of Computer National University of Defense Technology China

Multi-agent systems are characterized by environmental uncertainty, varying policies of agents, and partial observability, which result in significant risks. In the context of Multi-Agent Reinforcement Learning (MARL), learning coordinated and decentralized policies that are sensitive to risk is challenging. To formulate the coordination requirements in risk-sensitive MARL, we introduce the Risk-sensitive Individual-Global-Max (RIGM) principle as a generalization of the Individual-Global-Max (IGM) and Distributional IGM (DIGM) principles. This principle requires that the collection of risk-sensitive action selections of each agent should be equivalent to the risk-sensitive action selection of the central policy. Current MARL value factorization methods do not satisfy the RIGM principle for common risk metrics such as the Value at Risk (VaR) metric or distorted risk measurements. Therefore, we propose RiskQ to address this limitation, which models the joint return distribution by modeling quantiles of it as weighted quantile mixtures of per-agent return distribution utilities. RiskQ satisfies the RIGM principle for the VaR and distorted risk metrics. We show that RiskQ can obtain promising performance through extensive experiments. The source code of RiskQ is available in https://***/xmu-rl-3dv/RiskQ.

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Blockchain-enabled Device Authentication and Authorisation for Internet of Things

Blockchain-enabled Device Authentication and Authorisation f...

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Advanced Innovations in Smart Cities (ICAISC), International Conference on

作者： Raman Singh Sean Sturley Bhisham Sharma Imed Ben Dhaou School of Computing Engineering and Physical Sciences University of the West of Scotland United Kingdom Chitkara University Institute of Engineering and Technology Chitkara University Punjab India School of Engineering Computing and Informatics Dar Al-Hekma University Saudi Arabia

The Internet of Things (IoT) is the network of multiple devices known as “things” which includes sensors, security cameras, smart lights, smart TV, traffic lights etc. in the smart home or industrial environment. In many applications, these IoT devices are installed in open areas for example traffic lights/ security cameras in a smart city. Strong authentication and authorisation for these devices need to be deployed to ensure trust among IoT networks. IoT devices produce and forward security-sensitive data and hence confidentiality, authentication and proper authorisation should be the primary priority of an IoT system. Implementing Certificate Authority-based digital certificate solutions is costly because of the number of devices involved in IoT networks. Blockchain is a decentralized ledger-based technology which can help to provide seamless yet cost-effective solutions for confidentiality, authentication, and authorisation for IoT environments. A blockchain-based system for device registration, authentication, authorisation, and data confidentiality is proposed. The paper shows the methodological and procedural details of the proposed security scheme.

关键词： Authorization Technological innovation Smart cities Supply chains Authentication Cameras Blockchains

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Real-Time and Intelligent Flood Forecasting Using UAV-Assisted Wireless Sensor Network

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Computers, Materials & Continua 2022年第1期70卷 715-738页

作者： Shidrokh Goudarzi Seyed Ahmad Soleymani Mohammad Hossein Anisi Domenico Ciuonzo Nazri Kama Salwani Abdullah Mohammad Abdollahi Azgomi Zenon Chaczko Azri Azmi Centre for Artificial Intelligent(CAIT) Universiti Kebangsaan MalaysiaBangi43600Malaysia School of Computer Engineering Iran University of Science and TechnologyResalat Sq.16846-13114TehranIran School of Computing Faculty of Engineering Universiti Teknologi MalaysiaJohorMalaysia School of Computer Science and Electronic Engineering University of EssexColchester CO43SQUnited Kingdom Department of Electrical Engineering and Information Technologies University of Naples“Federico II”Naples80125Italy Razak Faculty of Technology and Informatics Universiti Teknologi MalaysiaKuala Lumpur54100Malaysia School of Electrical and Data Engineering University of Technology SydneyUltimoNSWAustralia

The Wireless Sensor Network(WSN)is a promising technology that could be used to monitor rivers’water levels for early warning flood detection in the 5G ***,during a flood,sensor nodes may be washed up or become faulty,which seriously affects network *** address this issue,Unmanned Aerial Vehicles(UAVs)could be integrated with WSN as routers or data mules to provide reliable data collection and flood *** light of this,we propose a fault-tolerant multi-level framework comprised of a WSN and a UAV to monitor river *** framework is capable to provide seamless data collection by handling the disconnections caused by the failed nodes during a ***,an algorithm hybridized with Group Method Data Handling(GMDH)and Particle Swarm Optimization(PSO)is proposed to predict forthcoming floods in an intelligent collaborative *** proposed water-level prediction model is trained based on the real dataset obtained fromthe Selangor River *** performance of the work in comparison with other models has been also evaluated and numerical results based on different metrics such as coefficient of determination(R2),correlation coefficient(R),RootMean Square Error(RMSE),Mean Absolute Percentage Error(MAPE),and BIAS are provided.

关键词： Unmanned aerial vehicles wireless sensor networks group method data handling particle swarm optimization river flow prediction

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MixLight: Borrowing the Best of both Spherical Harmonics and Gaussian Models

arXiv

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arXiv 2024年

作者： Ji, Xinlong Zhan, Fangneng Lu, Shijian Huang, Shi-Sheng Huang, Hua The School of Computing Science & Technology Beijing Institute of Technology Beijing100081 China The Max Planck Institute for Informatics Saarbrücken66123 Germany The School of Computer Science and Engineering Nanyang Technological University 639798 Singapore The School of ArtificialIntelligence Beijing Normal University Beijing100875 China

Accurately estimating scene lighting is critical for applications such as mixed reality. Existing works estimate illumination by generating illumination maps or regressing illumination parameters. However, the method of generating illumination maps has poor generalization performance and parametric models such as Spherical Harmonic (SH) and Spherical Gaussian (SG) fall short in capturing high-frequency or low-frequency components. This paper presents MixLight, a joint model that utilizes the complementary characteristics of SH and SG to achieve a more complete illumination representation, which uses SH and SG to capture low-frequency ambient and high-frequency light sources respectively. In addition, a special spherical light source sparsemax (SLSparsemax) module that refers to the position and brightness relationship between spherical light sources is designed to improve their sparsity, which is significant but omitted by prior works. Extensive experiments demonstrate that MixLight surpasses state-of-the-art (SOTA) methods on multiple metrics. In addition, experiments on Web Dataset also show that MixLight as a parametric method has better generalization performance than non-parametric methods. Copyright © 2024, The Authors. All rights reserved.

关键词： Light sources

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Integrated Energy-Efficient Distributed Link Stability Algorithm for UAV Networks

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Computers, Materials & Continua 2024年第11期81卷 2357-2394页

作者： Altaf Hussain Shuaiyong Li Tariq Hussain Razaz Waheeb Attar Farman Ali Ahmed Alhomoud Babar Shah School of Computer Science and Technology Chongqing University of Posts and TelecommunicationsChongqing400065China Key Laboratory of Industrial Internet of Things and Networked Control Ministry of EducationChongqing University of Posts and TelecommunicationsChongqing400065China School of Computer Science and Information Engineering Zhejiang Gongshang UniversityHangzhou310018China Management Department College of Business AdministrationPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Applied AI School of ConvergenceCollege of Computing and InformaticsSungkyunkwan UniversitySeoul03063Republic of Korea Department of Computer Science College of ScienceNorthern Border UniversityArar91431Saudi Arabia College of Technological Innovation Zayed UniversityDubai19282United Arab Emirates

Ad hoc networks offer promising applications due to their ease of use,installation,and deployment,as they do not require a centralized control *** these networks,nodes function as senders,receivers,and *** such network is the Flying Ad hoc Network(FANET),where nodes operate in three dimensions(3D)using Unmanned Aerial Vehicles(UAVs)that are remotely *** the integration of the Internet of Things(IoT),these nodes form an IoT-enabled network called the Internet of UAVs(IoU).However,the airborne nodes in FANET consume high energy due to their payloads and low-power *** optimal routing approach for communication is essential to address the problem of energy consumption and ensure energy-efficient data transmission in *** paper proposes a novel energy-efficient routing protocol named the Integrated Energy-Efficient Distributed Link Stability Algorithm(IEE-DLSA),featuring a relay mechanism to provide optimal routing with energy efficiency in *** energy efficiency of IEE-DLSA is enhanced using the Red-Black(R-B)tree to ensure the fairness of advanced energy-efficient *** link stability,transmission loss avoidance,delay awareness with defined threshold metrics,and improving the overall performance of the proposed protocol are the core functionalities of *** simulations demonstrate that the proposed protocol performs well compared to traditional FANET routing *** evaluation metrics considered in this study include network delay,packet delivery ratio,network throughput,transmission loss,network stability,and energy consumption.

关键词： FANET UAV internet of UAVs relay mechanism energy consumption routing IEE-DLSA

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