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An Optimization Approach for Convolutional Neural Network Using Non-Dominated Sorted Genetic Algorithm-Ⅱ

Computers, Materials & Continua 2023年第3期74卷 5641-5661页

作者： Afia Zafar Muhammad Aamir Nazri Mohd Nawi Ali Arshad Saman Riaz Abdulrahman Alruban Ashit Kumar Dutta Badr Almutairi Sultan Almotairi Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn MalaysiaMalaysia School of Electronics Computing and MathematicsUniversity of DerbyUK Department of Computer Science National University of TechnologyIslamabadPakistan Department of Information Technology College of Computer and Information SciencesMajmaah UniversityAl Majmaah11952Saudi Arabia Department of Computer Science and Information Systems College of Applied SciencesAlMaarefa UniversityRiyadh13713Kingdom of Saudi Arabia Department of Information Technology College of Computer Sciences and Information Technology CollegeMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Natural and Applied Sciences Faculty of Community CollegeMajmaah UniversityMajmaah11952Saudi Arabia Department of Information Systems Faculty of Computer and Information SciencesIslamic University of MadinahMadinah42351Saudi Arabia

In computer vision,convolutional neural networks have a wide range of *** representmost of today’s data,so it’s important to know how to handle these large amounts of data *** neural networks have been shown to solve image processing problems ***,when designing the network structure for a particular problem,you need to adjust the hyperparameters for higher *** technique is time consuming and requires a lot of work and domain *** a convolutional neural network architecture is a classic NP-hard optimization *** the other hand,different datasets require different combinations of models or hyperparameters,which can be time consuming and *** approaches have been proposed to overcome this problem,such as grid search limited to low-dimensional space and queuing by random *** address this issue,we propose an evolutionary algorithm-based approach that dynamically enhances the structure of Convolution Neural Networks(CNNs)using optimized *** study proposes a method using Non-dominated sorted genetic algorithms(NSGA)to improve the hyperparameters of the CNN *** addition,different types and parameter ranges of existing genetic algorithms are *** study was conducted with various state-of-the-art methodologies and *** have shown that our proposed approach is superior to previous methods in terms of classification accuracy,and the results are published in modern computing literature.

关键词： Non-dominated sorted genetic algorithm convolutional neural network hyper-parameter optimization

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A Secure Communication Protocol for Unmanned Aerial Vehicles

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Computers, Materials & Continua 2022年第1期70卷 601-618页

作者： Navid Ali Khan N.Z.Jhanjhi Sarfraz Nawaz Brohi Abdulwahab Ali Almazroi Abdulaleem Ali Almazroi School of Computer Science and Engineering(SCE) Taylor’s University Lake-side CampusSubang Jaya47500Malaysia School of Information and Technology Monash UniversityMalaysia University of Jeddah College of Computing and Information Technology at KhulaisDepartment of Information TechnologyJeddahSaudi Arabia Department of Computer Science Rafha Community CollegeNorthern Border UniversityArar91431Saudi Arabia

Mavlink is a lightweight and most widely used open-source communication protocol used for Unmanned Aerial *** UAVs and autopilot systems support it,and it provides bi-directional communication between the UAV and Ground Control *** communications contain critical information about the UAV status and basic control commands sent from GCS to UAV and UAV to *** order to increase the transfer speed and efficiency,the Mavlink does not encrypt the *** a result,the protocol is vulnerable to various security attacks such as Eavesdropping,GPS Spoofing,and *** this study,we tackle the problem and secure the Mavlink communication *** leveraging the Mavlink packet’s vulnerabilities,this research work introduces an experiment in which,first,the Mavlink packets are compromised in terms of security requirements based on our threat *** results show that the protocol is insecure and the attacks carried out are *** overcomeMavlink security,an additional security layer is added to encrypt and secure the *** encryption technique is proposed that makes the communication between the UAV and GCS *** results show that the Mavlink packets are encrypted using our technique without affecting the performance and *** results are validated in terms of transfer speed,performance,and efficiency compared to the literature solutions such as MAVSec and benchmarked with the original Mavlink *** achieved results have significant improvement over the literature and Mavlink in terms of security.

关键词： Unmanned aerial vehicles mavlink protocol drones security UAVs communication

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'User AR' - Leveraging AI Based Augmented Reality for User Manuals 15

'User AR' - Leveraging AI Based Augmented Reality for User M...

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15th International Conference on computing Communication and Networking Technologies, ICCCNT 2024

作者： Shanmugam, Thirumurugan Chandrashekar, Chirag Bhati, Vipin Subburaj, Maheswari Sivaraman, Arun Kumar Sultana, Ajmery University of Technology and Applied Sciences College of Computing and Information Sciences Suhar Oman Vellore Institute of Technology School of Computer Science and Engineering Chennai India Photon Interactive Inc Digital Engineering Solution Center TorontoON Canada Algoma University School of Computer Science and Technology BramptonON Canada

ISBN: (纸本)9798350370249

The objective of this research is to propose an AI based novel augmented reality (AR) software to assist users in operating a wide range of technical and non-technical devices. The project's aim is to make this AR application, which provides detailed explanations of all the device's functions, more widely used than traditional user manuals. Augmented reality, which overlays digital information onto the real world, can be employed to develop an AR-based user manual for products or devices. Mobile applications that use a camera to recognize a product or device and display dynamic graphics, such as 3 D models, animations, or text, are one example of AR user manuals. These augmented reality user manuals enable consumers to quickly and easily learn how to operate, assemble, repair, or troubleshoot their purchased products. Experiments show that the proposed algorithm was able to recognize the object accurately with a percentage of 95.2%. © 2024 IEEE.

关键词： Artificial Intelligence Augmented reality (AR) Object Recognition

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GIRP: Energy-Efficient QoS-Oriented Microservice Resource Provisioning via Multi-Objective Multi-Task Reinforcement Learning

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IEEE Transactions on Mobile computing 2025年第7期24卷 5793-5807页

作者： Yuan, Honggang Wang, Ting Fu, Min Shi, Yuanming East China Normal University MoE Engineering Research Center of Software/Hardware Co-design Technology and Application Shanghai Key Laboratory of Trustworthy Computing Shanghai200062 China National University of Singapore Department of Electrical and Computer Engineering 117583 Singapore ShanghaiTech University School of Information Science and Technology Shanghai201210 China

Microservice architecture has revolutionized web service development by facilitating loosely coupled and independently developable components distributed as containers or virtual machines. While existing studies emphasize end-to-end latency, this paper investigates energy-efficient quality-of-service (QoS)-oriented microservice provisioning, focusing on both QoS satisfaction and power consumption (PC) conservation. We propose the Green and Intelligent Resource Provision (GIRP) architecture, integrating a data-driven energy-latency-aware resource allocation and scheduling manager to balance latency and PC. To reconcile the trade-offs involved, a dual-objective optimization problem is formulated to minimize latency and energy use by selecting proper servers, allocating CPU cores, and determining service replicas. To address challenges with discrete variables, dual objectives, and implicit mappings, we leverage a model-free deep deterministic policy gradient-based reinforcement learning algorithm. Specifically, we develop a multi-task agent via the Multi-gate Mixture-of-Experts model to simultaneously make two separate actions regarding CPU core numbers and service replica numbers, followed by a single-task agent to determine service scheduling. Extensive experiments on the DeathStarBenchmark testbed validate GIRP's effectiveness, demonstrating approximately 52% resource savings and a 43% reduction in PC compared to leading methods like Sinan, Firm, and heuristic-based algorithms. These results highlight GIRP's capability to optimize microservice orchestration by balancing end-to-end latency and power efficiency. © 2025 IEEE. All rights reserved.

关键词： Quality of service

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An embedded vertical‐federated feature selection algorithm based on particle swarm optimisation

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CAAI Transactions on Intelligence technology 2023年第3期8卷 734-754页

作者： Yong Zhang Ying Hu Xiaozhi Gao Dunwei Gong Yinan Guo Kaizhou Gao Wanqiu Zhang School of Information and Control Engineering China University of Mining and TechnologyXuzhouChina The Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin UniversityChangchunChina School of Computing University of Eastern FinlandKuopioFinland The Macao Institute of Systems Engineering Macao University of Science and TechnologyTaipaChina

In real life,a large amount of data describing the same learning task may be stored in different institutions(called participants),and these data cannot be shared among par-ticipants due to privacy *** case that different attributes/features of the same instance are stored in different institutions is called vertically distributed *** pur-pose of vertical‐federated feature selection(FS)is to reduce the feature dimension of vertical distributed data jointly without sharing local original data so that the feature subset obtained has the same or better performance as the original feature *** solve this problem,in the paper,an embedded vertical‐federated FS algorithm based on particle swarm optimisation(PSO‐EVFFS)is proposed by incorporating evolutionary FS into the SecureBoost framework for the first *** optimising both hyper‐parameters of the XGBoost model and feature subsets,PSO‐EVFFS can obtain a feature subset,which makes the XGBoost model more *** the same time,since different participants only share insensitive parameters such as model loss function,PSO‐EVFFS can effec-tively ensure the privacy of participants'***,an ensemble ranking strategy of feature importance based on the XGBoost tree model is developed to effectively remove irrelevant features on each ***,the proposed algorithm is applied to 10 test datasets and compared with three typical vertical‐federated learning frameworks and two variants of the proposed algorithm with different initialisation ***-mental results show that the proposed algorithm can significantly improve the classifi-cation performance of selected feature subsets while fully protecting the data privacy of all participants.

关键词： Evolutionary optimization feature selection privacy protection vertical‐federated learning

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Automatic Feature Extraction from Satellite Imagery for Remote Sensing 7

Automatic Feature Extraction from Satellite Imagery for Remo...

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7th International Conference on Trends in Electronics and Informatics, ICOEI 2023

作者： Mary, D Diya Nair, Nandana S. Mohana Revathy, S. Gladence, L. Mary Bernatin, T. Sathyabama Institute of Science and Technology Department of Information Technology Chennai India Centre for Remote Sensing and Geoinformatics Sathyabama Institute of Science and Technology Chennai India School of Computing Sathyabama Institute of Science and Technology Chennai India Sathyabama Institute of Science and Technology Department of Ece Chennai India

ISBN: (纸本)9798350397284

Feature extraction from satellite images has steadily but progressively grown in recent years. Numerous feature extraction techniques have been created as a result of the increase. The loss of certain features is one of the various obstacles that must be overcome while selecting the best path for feature extraction. This study suggests utilizing a Convolutional Neural Network (CNN) approach to tackle these issues and extract attributes from satellite images supplied by an open source dataset called MLRSNet. Images with labels explaining each image's characteristics are displayed in the output. This makes it simpler to recognize and understand different components in satellite images. © 2023 IEEE.

关键词： Feature extraction

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FedHKD: A Hierarchical Federated Learning Approach Integrating Clustering and Knowledge Distillation for Non-IID Data 1

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2nd International Conference on Artificial Intelligence Security and Privacy, AIS and P 2024

作者： Hu, Shiwen Wang, Changji Li, Yuan Liu, Zhen Liu, Ning Gan, Qingqing School of Information Science and Technology Guangdong University of Foreign Studies Guangzhou China Guangdong Engineering Research Center of Data Security Governance and Privacy Computing Guangzhou China

ISBN: (数字)9789819611485

ISBN: (纸本)9789819611478

Federated learning allows decentralized model training while preserving data privacy. However, Non-IID data poses significant challenges, leading to performance degradation and increased communication overhead. This paper introduces FedHKD, a hierarchical FL algorithm that integrates client clustering and knowledge distillation to address Non-IID challenges. By clustering clients with similar data distributions and transferring knowledge across clusters, FedHKD improves model accuracy while reducing communication costs. Experimental results on Fashion-MNIST and CIFAR-10 datasets demonstrate up to 14.24% improvement in accuracy and a substantial reduction in communication overhead, proving its effectiveness in Non-IID environments. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Federated learning

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An Efficient and Privacy-Preserving Load Monitoring and Billing Scheme in Smart Grid 9

An Efficient and Privacy-Preserving Load Monitoring and Bill...

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9th IEEE International Conference on Data science in Cyberspace, DSC 2024

作者： Ding, Yong Yuan, Enchang Yang, Changsong Liang, Hai Wang, Huiyong Peng, Xinyong Guilin University of Electronic Technology Laboratory of Cryptography and Information Security School of Computer Science and Information Security Guilin541004 China Guangxi Zhuang Autonomous Region Information Center Guangxi Key Laboratory of Digital Infrastructure Nanning530000 China Guilin University of Electronic Technology School of Mathematics and Computing Science Guilin541004 China

ISBN: (纸本)9798350391367

The smart grid is widely recognized as a highly efficient solution for mitigating carbon emissions and addressing energy crises. Within this framework, the collection of metering data from users is crucial for improving energy efficiency. However, the frequent collection of real-time metering data presents substantial challenges in terms of data privacy and communication overhead. In this paper, we propose an efficient and secure scheme that enables the system operator to monitor load and compute bills while preserving the users' privacy. During the load monitoring phase, our scheme uses certificateless ring signatures and unique random identifiers to ensure the security of electricity data. Additionally, the proposed scheme uses improved function encryption for electricity data in a ciphertext state to protect users' privacy during dynamic billing. Detailed security analysis demonstrates that our scheme meets the security requirements of the smart grid. Furthermore, we compare our scheme with existing schemes to demonstrate the effectiveness of our proposed scheme in terms of low computational complexity and communication overhead. © 2024 IEEE.

关键词： billing blockchain data aggregation privacy preservation smart grid

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Maximizing Area Coverage in Privacy-Preserving Worker Recruitment: A Prior Knowledge-Enhanced Geo-Indistinguishable Approach

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IEEE Transactions on information Forensics and Security 2025年 20卷 5138-5151页

作者： Zhang, Pengfei Cheng, Xiang Zhang, Zhikun Zhu, Youwen Zhang, Ji Yunnan University of Finance and Economics Yunnan Key Laboratory of Service Computing Yunnan Kunming650221 China Key Laboratory of Computing Power Network and Information Security Ministry of Education Jinan250316 China Ministry of Education Key Laboratory of Equipment Data Security and Guarantee Technology Guilin541004 China Beijing University of Posts and Telecommunications Beijing100876 China Zhejiang University School of Computer Science and Technology Hangzhou310027 China Nanjing University of Aeronautics and Astronautics School of Computer Science and Technology Nanjing210016 China University of Southern Queensland School of Mathematics Physics and Computing ToowoombaQLD4350 Australia

Worker recruitment for area coverage maximization, typically requires participants to upload location information, which can deter potential participation without proper protection. While existing studies resort to geo-indistinguishability to address this concern, they primarily focus on either specific task locations (Target Coverage) or operate under pre-defined recruitment quotas for an interested region (Area Coverage). These focuses not only yield suboptimal area coverage when scaled but also fail to leverage valuable prior knowledge in the form of participants' noisy historical registered locations, to enhance both location obfuscation and worker identification processes. To address these limitations, we present WILTON, which optimizes area coverage under geo-indistinguishability by recruiting the minimum number of participants through the strategic utilization of noisy prior knowledge. In WILTON, to generate obfuscated locations, we propose a probabilistic and weight-aware input perturbation mechanism, which groups and weights prior locations rather than using only personal prior locations. To privately identify the recruited workers, we design a grid-based worker identification method, which provides a worst-case performance guarantee of ratio 1 -1/e to the optimum. We provide a theoretical analysis of the privacy, utility, and complexity guarantees of WILTON. Experimental results over two real-world datasets and one synthetic dataset show that WILTON surpasses the state-of-the-arts by at least 8% in area coverage improvement. © 2005-2012 IEEE.

关键词： Knowledge acquisition

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Visual simulation of bone cement blending and dynamic flow

Visual simulation of bone cement blending and dynamic flow

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Shen, Long Zhang, Yalan Frey, Steffen Telea, Alex Kosinka, Jiri Wang, Xiaokun Ban, Xiaojuan University of Science and Technology Beijing School of Intelligence Science and Technology Beijing China University of Groningen Bernoulli Institute Groningen Netherlands Utrecht University Department of Information and Computing Sciences Utrecht Netherlands University of Science and Technology Beijing Beijing Key Laboratory of Knowledge Engineeringfor Materials Science Beijing China

ISBN: (纸本)9798350386226

Bone cement filling is an important method for preventing osteoporosis and treating fractures. In bone cement filling surgery, the preparation and dosage of the cement usually depend on specific product manuals and the doctor's experience. If bone cement is not used properly, it may cause additional damage. For teaching and auxiliary medical purposes, for example, assisting doctors to observe the possible flow of bone cement, this paper proposes a multiphase non-Newtonian fluid simulation method to simulate and visualize the flow behavior during the wet sand phase of bone cement blending and polymerization. Our method enables showing intuitively the application process of bone cement under different scene settings to obtain dynamic bone cement effects with high stability and performance. Compared with other methods, our method can simulate highly viscous mixed fluids efficiently and robustly, which supports our method's usage in the aforementioned training and experimentation scenarios. © 2024 IEEE.

关键词： Non Newtonian flow

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