检索结果-内蒙古大学图书馆

7th International Symposium on Innovative Approaches in Smart Technologies, ISAS 2023

作者： Gupta, Keshav Dev Cengiz, Korhan Awasthi, Charu Ramini, Siva Akash Chatterjee, Shyamapriya Pavithra, M. Poornima College of Engineering Department of Computer Science Engineering Jaipur India University of Fujairah College of Information Technology United Arab Emirates Istinye University Department of Computer Engineering Istanbul Turkey University of Hradec Kralove Faculty of Informatics and Management Department of Information Technologies Hradec Kralove500 03 Czech Republic JSS Academy of Technical Education Department of Information Technology Noida India Andhra Pradesh Amaravati India Narula Institute of Technology Department of Information Technology West Bengal Kolkata India Jansons Institute of Technology Karumathampatti Department of Computer Science and Engineering Coimbatore641659 India

ISBN: (纸本)9798350383065

The proliferation of the Internet of Things (IoT) has ushered in a transformative era of connected devices, emphasizing the critical need for effective resource management. This study introduces an innovative approach that harnesses Evolutionary and Swarm Intelligence algorithms for IoT Task Scheduling, addressing resource optimization challenges. The approach offers superior resource utilization through advanced optimization techniques, reducing energy consumption and enhancing efficiency. Furthermore, it significantly reduces task scheduling execution time, enabling prompt decision-making in dynamic IoT environments. This results in improved task allocation quality, meeting application-specific requirements, and prioritizing critical tasks. Notably, the approach excels in minimizing completion time, making it particularly advantageous for real-time IoT applications. This research contributes to the advancement of IoT resource management, offering an adaptive, efficient, and intelligent solution with broad applicability. In the evolving landscape of IoT, the findings presented here lay a solid foundation for future research and practical implementations, ultimately promoting more responsive, sustainable, and intelligent IoT ecosystems. © 2023 IEEE.

关键词： Swarm intelligence

来源：评论

学校读者我要写书评

暂无评论

Tackling Non-IID for Federated Learning with Components Alignment 1

引用

5th International Conference on Machine Learning for Cyber Security, ML4CS 2023

作者： Xue, Baolu Zhang, Jiale Chen, Bing Li, Wenjuan School of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing211106 China School of Information Engineering Yangzhou University Yangzhou225009 China The Education University of Hong Kong 999077 Hong Kong

ISBN: (数字)9789819724581

ISBN: (纸本)9789819724574

Federated Learning (FL) is a privacy-preserving framework used to perform machine learning tasks with distributed data. One of the key challenges is heterogeneous data distributions among clients, which results in client-drift, leading to the oscillatory and low-accuracy global model. Although lots of work has been proposed to mitigate client-drift, we find there are drawbacks associated with the two common methods: feature alignment and classifier tuning. For the former, the great bias in classifiers still holds in local models and degrades global model performance. For the latter, it’s hard to obtain suitable global features to introduce external knowledge to locals. To address the above drawbacks, in this paper, we propose a privacy-preserving and effective method, named FCA, to tackle client-drift issues in Non-IID federated learning via aligning models’ components. Specifically, FCA enhances similarity among the local models’ components, i.e. feature extractors and classifiers, by utilizing the estimated global feature representations. Experimental results demonstrate that FCA achieves better performance with fewer rounds. Compared with vanilla, our method achieves from 0.4% to 7.5% performance improvement on three popular datasets with four different Non-IID scenarios. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Privacy-preserving techniques

来源：评论

学校读者我要写书评

暂无评论

Joint Optimization of Power Allocation and Beamforming for UAV-RIS Communication System

引用

IEEE Wireless Communications Letters 2025年第6期14卷 1733-1737页

作者： Guo, Xinying Liu, Longfei Zhang, Jiankang Chen, Sheng Henan University of Technology Key Laboratory of Grain Information Processing and Control Ministry of Education College of Information Science and Engineering Zhengzhou450001 China Bournemouth University Department of Computing and Informatics PooleBH12 5BB United Kingdom University of Southampton School of Electronics and Computer Science SouthamptonSO17 1BJ United Kingdom

This letter considers the communication system assisted by a fixed-trajector uncrewed aerial vehicle (UAV), which is equipped with a reconfigurable intelligent surface (RIS). For this UAV-RIS assisted system, we jointly optimize the power allocation and active beamforming at the base station (BS) and the passive beamforming at the RIS, by a novel phase block coordinate descent algorithm framework aimed at maximizing the system sum-rate. Specifically, the joint optimization problem is decomposed into two phases, and we propose two optimization algorithms: one for BS power allocation using fractional programming (FP) and the other for jointly optimizing active and passive beamforming using FP-manifold, which alternately optimize two phases. Simulation results not only highlight the rapid convergence and evident superiority of our proposed framework but also reveal that the optimal UAV-RIS placement is related to the flight height. © 2012 IEEE.

关键词： Unmanned aerial vehicles (UAV)

来源：评论

学校读者我要写书评

暂无评论

An Extended Deep Learning based Solution for Screening COVID-19 CT-Scans 9

An Extended Deep Learning based Solution for Screening COVID...

引用

9th International Conference on Computing for Sustainable Global Development, INDIACom 2022

作者： Pandey, Dhiraj Pandey, Kavita Jss Academy of Technical Education Noida Dept. of Information Technology Noida India Jaypee Institute of Information Technology Noida Dept. of Computer Science Engineering and Information Technology Noida India

ISBN: (纸本)9789380544441

Due to immense pressure on the medical sector, there is a huge chance of human error in diagnosing the report of COVID-19 patients. For the detection of COVID-19, many Artificial Intelligence-based methodologies have been proposed. This work offers an ideal approach by a fusion of deep learning classifiers and medical images to provide a speedy and accurate identification of the COVID-19 virus by analyzing the user's CT-Scan images of the lungs. In this work, an adjusted rendition of ResNet101V2 that is improved by a Feature Pyramid Network for classifying the CT scan images into the categories: normal or COVID-19 positive, has been implemented. An accuracy of marginally significant has been obtained by ResNet101V2 with Feature Pyramid Network. The proposed FPN, using the deep learning technique, assured a satisfactory performance in terms of detecting COVID-19 in CT scan and gives a testing accuracy of 97.79%. The predicted results on test-cases are highly accurate using FPN and can assist the medical professionals in making a proper judgment. © 2022 Bharati Vidyapeeth, New Delhi.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

Intelligent Energy Utilization Analysis Using IUA-SMD Model Based Optimization Technique for Smart Metering Data

引用

Journal of Harbin Institute of technology(New Series) 2024年第1期31卷 90-98页

作者： K.Rama Devi V.Srinivasan G.Clara Barathi Priyadharshini J.Gokulapriya Department of Information Technology Panimalar Engineering CollegeChennaiTamil Nadu 600029India Department of Computer Applications Dayananda Sagar College of EngineeringBengaluru 560078KarnatakaIndia Department of Computer Appliations Karpagam Academy of Higher EducationCoimbatoreTamil Nadu 641021India Department of Computer Science Rathinam College of Arts and ScienceCoimbatoreTamil Nadu 641021India

Smart metering has gained considerable attention as a research focus due to its reliability and energy-efficient nature compared to traditional electromechanical metering systems. Existing methods primarily focus on data management,rather than emphasizing efficiency. Accurate prediction of electricity consumption is crucial for enabling intelligent grid operations,including resource planning and demandsupply balancing. Smart metering solutions offer users the benefits of effectively interpreting their energy utilization and optimizing costs. Motivated by this,this paper presents an Intelligent Energy Utilization Analysis using Smart Metering Data(IUA-SMD)model to determine energy consumption patterns. The proposed IUA-SMD model comprises three major processes:data Pre-processing,feature extraction,and classification,with parameter optimization. We employ the extreme learning machine(ELM)based classification approach within the IUA-SMD model to derive optimal energy utilization labels. Additionally,we apply the shell game optimization(SGO)algorithm to enhance the classification efficiency of the ELM by optimizing its parameters. The effectiveness of the IUA-SMD model is evaluated using an extensive dataset of smart metering data,and the results are analyzed in terms of accuracy and mean square error(MSE). The proposed model demonstrates superior performance,achieving a maximum accuracy of65.917% and a minimum MSE of0.096. These results highlight the potential of the IUA-SMD model for enabling efficient energy utilization through intelligent analysis of smart metering data.

关键词： electricity consumption predictive model data analytics smart metering machine learning

来源：评论

学校读者我要写书评

暂无评论

Wind Driven Optimization-Based Medical Image Encryption for Blockchain-Enabled Internet of Things Environment

引用

computers, Materials & Continua 2022年第11期73卷 3219-3233页

作者： C.S.S.Anupama Raed Alsini N.Supriya E.Laxmi Lydia Seifedine Kadry Sang-Soo Yeo Yongsung Kim Department of Electronics&Instrumentation Engineering V.R.Siddhartha Engineering CollegeVijayawada520007India Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Computer Science and Engineering Malla Reddy Engineering College(A)Hyderabad500100India Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Applied Data Science Noroff University College4612KristiansandNorway Department of Computer Engineering Mokwon UniversityDaejeon35349Korea Department of Technology Education Chungnam National University 99Daehak-roYuseong-guDaejeon34134Korea

Internet of Things(IoT)and blockchain receive significant interest owing to their applicability in different application areas such as healthcare,finance,transportation,*** image security and privacy become a critical part of the healthcare sector where digital images and related patient details are communicated over the public *** paper presents a new wind driven optimization algorithm based medical image encryption(WDOA-MIE)technique for blockchain enabled IoT *** WDOA-MIE model involves three major processes namely data collection,image encryption,optimal key generation,and data ***,the medical images were captured from the patient using IoT ***,the captured images are encrypted using signcryption *** addition,for improving the performance of the signcryption technique,the optimal key generation procedure was applied by WDOA *** goal of the WDOA-MIE algorithm is to derive a fitness function dependent upon peak signal to noise ratio(PSNR).Upon successful encryption of images,the IoT devices transmit to the closest server for storing it in the blockchain *** performance of the presented method was analyzed utilizing the benchmark medical image *** security and the performance analysis determine that the presented technique offers better security with maximum PSNR of 60.7036 dB.

关键词： Internet of things image security medical images encryption optimal key generation blockchain

来源：评论

学校读者我要写书评

暂无评论

Continuous Integration, Testing Deployment and Delivery in Devops

Continuous Integration, Testing Deployment and Delivery in D...

引用

2024 International Conference on Knowledge engineering and Communication Systems, ICKECS 2024

作者： Naresh, E. Murthy, S.V.N. Sreenivasa, N. Merikapudi, Seshaiah Rakhi Krishna, C.R. Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Department of Information Technology Manipal India SJC Institute of Technology Department of Cse Chikkaballapur India Nitte Meenakshi Institute of Technology Department of Computer Science and Engineering Bangalore Yelahanka India Bgsit Department of Cse India

ISBN: (纸本)9798350359688

The proposed research article focuses on Continuous Integration, Testing, Delivery and Deployment in terms of DevOps environment. DevOps is a combination of development and operations. In a usual work environment, both development and operations of that company work entirely differently where mutual interaction is said to be minimum. Thus, to overcome that, DevOps was introduced, where both development and operations must work together in the same environment. In this article we will discuss what each of these terms means, how they work, why they are important in today's software development life cycle (SDLC), what tools are used for each of them, etc. We will consider a few scenarios where the above-mentioned topics are better than the traditional or the most widely used SDLC methodologies. © 2024 IEEE.

关键词： Integration testing

来源：评论

学校读者我要写书评

暂无评论

Aspect-Based Sentiment Analysis Based on Knowledge Enhancement and Pre-trained Language Model

Journal of Network Intelligence

引用

Journal of Network Intelligence 2025年第2期10卷 1168-1181页

作者： Ye, Lizhu Johar, Md Gapar Md Alkawaz, Mohammed Hazim School of Information Technology and Engineering Guangzhou College of Commerce Guangzhou511363 China School of Graduate Studies Management and Science University Selangor Shah Alam40100 Malaysia Software Engineering and Digital Innovation Center Management and Science University Selangor Shah Alam40100 Malaysia Department of Computer Science College of Education for Pure Science University of Mosul Mosul41002 Iraq

Aspect-Based Sentiment Analysis (ABSA) is a significant task in the field of natural language processing, and the existing ABSA models not only lack the mining of sentiment knowledge, but also ignore the semantic feature representation of text. To address the above issues, this article designs an ABSA method relied on knowledge enhancement and Pre-trained Language Model (PLM). Firstly, a syntactic dependency graph is constructed based on the sentiment knowledge of the text to integrate the syntactic and sentiment information in the sentence. On this basis, PLM is utilized to encode words and sentences in the text context to enrich the semantic feature representation of the text. Secondly, the dependency graph of the sentence is enhanced by using emotional knowledge and the dependency types between words, and the node features are modeled by graph convolutional network to get the specific aspectual representation enhanced by emotional knowledge;meanwhile, the conceptual graph is enhanced by using conceptual graph for the aspectual word concepts and then fused with the specific aspectual representation to get the aspectual representation enhanced by multi-source knowledge. Then designing a dual interaction attention mechanism to realize the fusion of context and aspect features. Finally, the fused characteristic information is adopted as the input of the fully connected layer, and the softmax function is used to output the final sentiment polarity classification. The experimental outcome indicates that the suggested method outperforms the comparison model on the Restaurant and Twitter datasets, and better experimental outcome are obtained. © 2025 ISSN.

关键词： Emotion Recognition

来源：评论

学校读者我要写书评

暂无评论

All-optical logic gates based on hierarchical photonic crystal modulated photoluminescence of perovskite nanocrystals

引用

Science China(Technological Sciences) 2023年第9期66卷 2735-2742页

作者： WANG Yun ZHA YanFang YANG YunYi LIU CiHui DI YunSong CAO GuiYuan WEI ShiBiao CHEN ZhiHui GAN ZhiXing Center for Future Optoelectronic Functional Materials School of Computer and Electronic InformationSchool of Artificial IntelligenceNanjing Normal UniversityNanjing 210023China Centre for Translational Atomaterials School of ScienceSwinburne University of TechnologyHawthorn VIC 3122Australia Nanophotonics Research Center Shenzhen Key Laboratory of Micro-Scale Optical Information TechnologyShenzhen UniversityShenzhen 518060China Key Laboratory of Advanced Transducers and Intelligent Control Systems Ministry of Education and Shanxi ProvinceCollege of Electronic Information and Optical EngineeringTaiyuan University of TechnologyTaiyuan 030024China

Halide perovskites exhibit high performance in all sorts of optoelectronic and photonic areas, suggesting their huge potential in integrated photonic devices. However, until now, all optical logic gates based on perovskites are still rarely explored, hindering the development of all-optical networks and computing. Herein, a new concept of all-optical logic gates is proposed based on the modulation of photoluminescence(PL) from perovskite nanocrystals(PNCs). A hierarchical photonic crystal(Hie PhC) is developed by self-assembling polystyrene(PS) and SiO2nanoparticles, which exhibit a higher PL enhancement than that of a monolayer PhC. Moreover, the light-controlled PL is realized by taking advantage of the high thermal response of the PL from PNCs/Hie PhC on polyethylene(PE) substrate, assisted by a graphene layer for light-heat conversion. Consequently, optical diode and triode are achieved based on the modulated PL, which exhibit contrast ratios(CR) of 24.7 and 74.0 dB, ***-optical logic gates, including “AND”, “OR” and “NOT”, are realized based on the optical diode and triode.

关键词： perovskite nanocrystals photonic crystals all-optical logic gates modulation of photoluminescence

来源：评论

学校读者我要写书评

暂无评论

Optimized Task Scheduling in Diverse Distributed Systems with a Hybrid Genetic Algorithm Approach 3rd

Optimized Task Scheduling in Diverse Distributed Systems wit...

引用

3rd International Conference on Intelligent Systems and Sustainable Computing, ICISSC 2023

作者： Muthusamy, Ramesh Kumar Kadu, Swati Ayyasamy, Karthikeyan Pichuka Veera Venkata Satya, Srinivas Arumugam, Ramachandran Ammasai, Viswanathan Sengan, Sudhakar Department of Information Technology V.S.B. College of Engineering Technical Campus Tamil Nadu Coimbatore642109 India Department of AI&DS AISSMS IOIT Pune411001 India Department of Computer Science and Engineering Panimalar Engineering College Tamil Nadu Chennai600123 India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram522502 India Department of Computer Science and Engineering Saveetha Engineering College Tamil Nadu Chennai602105 India School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Vellore632014 India Department of Computer Science and Engineering PSN College of Engineering and Technology Tamil Nadu Tirunelveli627012 India

ISBN: (纸本)9789819783540

In Heterogeneous Distributed Systems (HDS), efficient task scheduling (TS) across diverse resources remains a pressing challenge. This paper introduces a Hybrid Genetic Algorithm (HGA) as a solution, blending heuristic techniques with the evolutionary strengths of Genetic Algorithms (GAs) to optimize Task Scheduling (TS). Traditional algorithms often fall short in balancing computational speed with solution quality, especially in large-scale environments. This proposed HGA addresses this by leveraging domain-specific heuristics to provide a promising starting point for the GA's optimization process. The TS dilemma has been successfully defined by an all-encompassing logical system, which ensures the accuracy of the design of algorithms. In comparison tests, the HGA frequently comes out on top, demonstrating less makespan and a more excellent distribution of tasks among the resources available. Also, resources with more efficient processing capabilities will be provided priority in this recommended heuristic method, which focuses on tasks with higher computational demands. The findings of the present investigation demonstrate that the HGA may transform TS approaches by providing high-quality solutions while increasing performance. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Scheduling algorithms

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：