检索结果-内蒙古大学图书馆

14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Dutta, Sangita Chakraborty, Susanta Indian Institute of Engineering Science and Technology Department of Computer Science and Technology Howrah India

ISBN: (纸本)9798350335095

Multiple features of the complex network are exhibited among the nodes in time-varying social networks. Community detection has numerous approaches, but the majority of methods are restricted to disjoint community situations. Solutions to disjoint community situations do not reflect well on real-world social networks. An innovative heuristic method has been proposed to recognize community structure in real-world networks and to identify the most influential node within each community. The proposed concept on a recognized community network has been tested in order to validate it. This work introduced one new network metric, the Dependency factor which computes the influence of a node. Our results are compared with other existing approaches using real-life datasets. We have compared the dependency factor with other network centralities. The computational case study is done over a well-known Bengali novel, namely Chaar Adhyay written by Nobel laureate Rabindranath Tagore. The analytical results are more accurate than the state-of-the-art approaches. © 2023 IEEE.

关键词： Heuristic methods

来源：评论

学校读者我要写书评

暂无评论

Sorted Range Selection and Range Minima Queries 2nd

Sorted Range Selection and Range Minima Queries

引用

2nd International Conference on Applied Algorithms, ICAA 2025

作者： Akram, Waseem Saxena, Sanjeev Department of Computer Science and Engineering Indian Institute of Technology Kanpur208016 India

ISBN: (纸本)9783031845420

Given an array A[1 : n] of n elements drawn from an ordered set, the sorted range selection problem is to build a data structure that can be used to answer following queries: Given a pair of indices i, j(1≤i≤j≤n), and a positive integer k, report the k smallest elements from the sub-array A[i : j] in sorted order. Brodal et al. (Brodal, G. S., Fagerberg, R., Greve, M., and López-Ortiz, A., Online sorted range reporting. Algorithms and Computation (2009) pp. 173–182) introduced the problem and gave a solution that can answer a query in O(k) time. The preprocessing takes O(nlogn) time and O(n) space. In this paper, we propose the only other possible optimal trade-off for the problem. After preprocessing using O(n) time and space, we can answer a range selection query in O(klogk) time. Moreover, the proposed algorithm reports the output elements individually in non-decreasing order. Our solution is simple and practical. We also study the problem in a dynamic setting. We also describe an extremely simple method for the range minima queries (most of whose parts are known), which takes almost (but not exactly) linear time. We believe that this method may be, in practice, faster and easier to implement in most cases. Moreover, we also give a simple dynamic solution to the range minimum problem. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Optimization

来源：评论

学校读者我要写书评

暂无评论

Behavioral insights into compression: a study of Move-to-Front-or-Middle deterministic online algorithm through sequence classification and characterization

引用

International Journal of information technology (Singapore) 2025年第1期17卷 189-203页

作者： Baisakh Mohapatra, Hitesh Guru, Abhishek Department of Computer Science and Engineering Sambalpur University Institute of Information Technology Sambalpur India Computer Science and Engineering GMR Institute of Technology Andhra Pradesh Rajam India School of Computer Engineering KIIT Deemed to Be University Bhubanseswar India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram India

Since the list update problem was applied to data compression as an effective encoding technique, numerous deterministic algorithms have been studied and analyzed. A powerful strategy, Move-to-Front (MTF), involves moving an accessed item to the front of the list immediately. Theoretical analysis has demonstrated MTF’s potential, showing it to be 2-competitive through competitive analysis. This success has inspired researchers to develop various intriguing MTF variants and assess their performance both theoretically and experimentally. One such variant, Move-to-Front-or-Middle (MFM), has been experimentally shown that MFM performed better than the classic MTF on Calgary and Cantebury Datasets. However, the experimental performance alone does not provide sufficient insight into the internal behavior of the algorithm or explain why its performance surpasses MTF on certain datasets. Therefore, in this paper, we conduct a detailed behavioral study of MFM through sequence classification and characterization to gain deeper understanding of the algorithm and aims to reconcile the disparity between theoretical and experimental outcomes. This paper also by classifying and characterizing MFM’s performance across various request sequences, considering both the presence and absence of locality of reference. © Bharati Vidyapeeth's institute of computer Applications and Management 2024.

关键词： Competitive analysis Deterministic list update algorithm List update problem Sequence classification

来源：评论

学校读者我要写书评

暂无评论

LASKV: Lightweight Authenticated Session Key Agreement for Video Surveillance System 5th

LASKV: Lightweight Authenticated Session Key Agreement for V...

引用

5th International Symposium on Signal and Image Processing, ISSIP 2024

作者： Kumar, Pramod Pal, Arup Kumar Islam, SK Hafizul Jharkhand Dhanbad India Department of Computer Science and Engineering Indian Institute of Information Technology Kalyani West Bengal Kanchrapara India

ISBN: (纸本)9789819795147

The video surveillance system (VSS) is an integral part of the modern society. The surveillance camera captures the video of its designated areas and subsequently stores the video data in the server for future needs. In this situation, the VSS should send the captured video to the server securely;later, according to the demand, legitimate users can access the video data securely. This chapter suggests a secure VSS where the camera transmits the surveillance video data (SVD) to the server once both entities are mutually authenticated and generates the session key. Further, a legitimate user can access the SVD from the server once both parties are mutually authenticated and ensure a session key for secure data transmission. This chapter proposes a lightweight authenticated session key agreement for VSS based on the ASCON, strengthening access control and safeguarding private data. We call the proposed scheme LASKV. The LASKV scheme is lightweight and upholds security against various cryptographic attacks. In this regard, the informal security analysis and the Scyther simulation endorse the security of the LASKV scheme. Overall, the LASKV scheme effectively stores and accesses the SVD safely within an organization. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Authentication

来源：评论

学校读者我要写书评

暂无评论

A Bilateral Assessment of Human Activities Using PSO-Based Feature Optimization and Non-linear Multi-task Least Squares Twin Support Vector Machine

引用

SN computer science 2024年第3期5卷 1-18页

作者： Thakur, Ujwala Vidyarthi, Ankit Prajapati, Amarjeet Department of Computer Science Engineering and Information Technology Jaypee Institute of Information Technology Noida Sector-62 Uttar Pradesh Noida 201309 India

Human activity recognition (HAR) is an essential part of many applications, including smart surroundings, sports analysis, and healthcare. Accurately categorizing intricate actions from sensor data is still difficult, though. This method infers an individual’s actions using a variety of sensor data, including magnetometers, gyroscopes, and accelerometers. This work suggests a unique method for classifying human activities by combining a non-linear multi-task least squares twin support vector machine (NMtLSSVM) with particle swarm optimization (PSO) for feature optimization. Utilizing the advantages of both approaches, the suggested strategy achieves excellent resilience and accuracy in activity identification. The suggested method reduces dimensionality and computing costs while maintaining pertinent information using PSO to extract the most important features from the raw sensor data. On the other hand, NMtLSSVM is used to construct a multi-task learning framework that learns several related tasks at the same time and shares information among them. As a result, generalization and resilience can be enhanced beyond single-task models. Two datasets that are available to the public, WISDM, and UCI-HAR, were used to assess the suggested method. The testing findings show that the suggested approach works noticeably better than the most advanced techniques already in use. Overall activities, the outcome achieves an average classification accuracy of 97.8% (UCI-HAR dataset) and 98.5% (WISDM dataset). Furthermore, the PSO-based feature optimization decreased the feature count by 60% without sacrificing efficiency. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd 2024.

关键词： Human action recognition Intelligent computing Machine learning classification Performance comparison Sensory data analysis

来源：评论

学校读者我要写书评

暂无评论

Hybrid dense matching features for cloud-based face recognition

引用

International Journal of Cloud Computing 2023年第2-4期12卷 399-423页

作者： Shreekumar, T. Karunakara, K. Faculty of Computer Science and Engineering Mangalore Institute of Technology and Engineering Mijar Moodabidre India Faculty of Information Science and Engineering Sri Siddartha Institute of Technology Sri Siddhartha Academy of Higher Education Tumakuru India

Cloud computing is a computing service done not on a local device but an internet connection to a data centre infrastructure. The cloud computing system also provides a scalability solution where cloud computing can increase the resources needed when doing larger data processing. In recent years, face bio-metric plays an important role in biometric authentication, where security is the primary concern. The two major difficulties to be addressed in face recognition are illumination and pose variation. This work proposes a cloud computing-based face recognition technique by consolidating four-patch LBP and the local landmark features to the acquired feature vector. After that, the SVM is utilised to recognise the individual. The feature set used for training and testing is also made available in the cloud. At some stage in the training phase, the kernel parameters of SVM are optimised with GWO to improve the recognition performance. This method yields a maximum recognition accuracy of 99.00% with LFW and 98.0% accuracy with YTF. Copyright © 2023 Inderscience Enterprises Ltd.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Secured and Privacy-Preserving GPU-Based Machine Learning Inference in Trusted Execution Environment: A Comprehensive Survey 17

Secured and Privacy-Preserving GPU-Based Machine Learning In...

引用

17th International Conference on COMmunication Systems and NETworkS, COMSNETS 2025

作者： Chaudhuri, Arunava Shukla, Shubhi Bhattacharya, Sarani Mukhopadhyay, Debdeep Indian Institute of Technology Kharagpur Department of Computer Science and Engineering Kharagpur India Indian Institute of Technology Kharagpur Centre for Computational and Data Sciences Kharagpur India

ISBN: (纸本)9798331531195

With the rapid advancement of machine learning (ML) models and their widespread application across various sectors such as intrusion detection, medical diagnosis, natural language processing, and autonomous driving, these technologies have achieved remarkable success. However, this progress has also raised significant concerns about ensuring the security of ML models and protecting both private training data and model outputs from getting exposed in a shared cloud environment. To address these challenges, researchers have proposed various methodologies to create privacy-preserving, secure, and trustworthy model execution environments to prevent adversarial attacks. This study provides a comprehensive review of Trusted Execution Environment (TEE) implementations across different hardware accelerators. It also offers an overview of modern techniques for preserving privacy and security in execution environments, while identifying critical research gaps that require attention. In essence, this survey is an important resource for researchers, providing insights into recent methodologies and guiding them to focus on pressing research challenges. © 2025 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

BESIEC: An Adaptive Optimized Model for Task Scheduling & Offloading

引用

SN computer science 2024年第8期5卷 1-12页

作者： Mohanty, Jayashree Sobhanayak, Srichandan Department of Computer Science and Engineering International Institute of Information Technology (IIIT) Odisha Bhubaneswar 751003 India

The rapid change in computational strategy and delay-sensitive applications require intense power sources of computational resources. This creates a challenge of precise latency requirements in 5G network services. Task scheduling and offloading can be promising solutions to achieve high-performance optimized output with heterogeneity, handling of tasks, conservation of energy, and reliable latency factor. Blockchain (BC), Software defined networks (SDN) and the Internet of Things(IoT) are the most promising significant technologies researched in this article, and the fusion of the three has the potential to reinvent the relationship of trust in the networks and promote the integration of confidentiality and reliability in the respective use cases. Cloud infrastructure is used to provide clients with powerful computing and storage environments. A kind of expansion of cloud computing architecture, edge computing, has been trending. Now, it is used to build distributed secure architecture to promote the safety and integrity of data throughout its lifetime and bring much-needed efficiency to IoT data processing. This paper considers a Blockchain-Enabled Software-defined network-based IoT Edge Cloud(BESIEC) scenario for data integrity during task scheduling and offloading processes while achieving optimal computational resources and minimizing end-to-end delays. The strategy shows that it is better to implement the BESIEC model than the Traditional Floodlight implementation. The BESIEC model shows better time consumption performance regarding the number of tasks completed compared to local processing, cloud offloading, and edge offloading. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： BESIEC Blockchain Cloud IoT edge SDN Signature-based approach

来源：评论

学校读者我要写书评

暂无评论

Crafting Captivating Narratives: Enhancing Image Captioning Through Encoder-Decoder Architectures 2

Crafting Captivating Narratives: Enhancing Image Captioning ...

引用

2nd IEEE International Conference on Data science and Network Security, ICDSNS 2024

作者： Sahaaya Arul Mary, S.A. Pandey, Adamya Kumar Jha, Aadarsh Sharma, Kartikay Shohel, Mohmad Natarajan, B. School of Computer Science and Engineering Vellore Institute of Technology Vellore India School of Information Technology Vellore Institute of Technology Vellore India School of Computer Science and Engineering Vellore Institute of Technology Chennai India

ISBN: (纸本)9798350373110

This research work aims to develop an image captioning system utilizing deep learning techniques. The pre-trained VGG-16 model is employed to extract image features, while an innovative encoder-decoder architecture is used to generate descriptive captions. To ensure compatibility with the model, pre-processing techniques are applied to the dataset, which comprises images and their corresponding descriptions. Tokenization, vocabulary generation, and effectively utilizing a data generator are integral parts of the training process, facilitating the handling vast datasets. Multiple training epochs are employed to optimize the model's ability to associate captions with specific picture attributes. The model's performance is evaluated using BLEU-1 and BLEU-2 scores on a designated test set, providing quantitative insights into the quality of the generated captions. Additionally, this work includes a visualization component enabling users to input names of specific images, generating captions in real-time for comparative analysis with actual captions. This comprehensive approach integrates methodologies from computer vision and natural language processing, showcasing how deep learning can enhance the interpretability and comprehension of images akin to human perception. BLEU is a widely used, automated metric for evaluating image captioning models, offering objective and quantitative comparisons. © 2024 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

WCM-WTrA: A Cross-Project Defect Prediction Method Based on Feature Selection and Distance-Weight Transfer Learning

引用

Chinese Journal of Electronics 2022年第2期31卷 354-366页

作者： LEI Tianwei XUE Jingfeng WANG Yong NIU Zequn SHI Zhiwei ZHANG Yu School of Computer Science and Technology Beijing Institute of Technology China Information Technology Security Evaluation Center School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture

Cross-project defect prediction is a hot topic in the field of defect prediction. How to reduce the difference between projects and make the model have better accuracy is the core problem. This paper starts from two perspectives: feature selection and distance-weight instance transfer. We reduce the differences between projects from the perspective of feature engineering and introduce the transfer learning technology to construct a cross-project defect prediction model WCM-WTrA and multi-source model Multi-WCM-WTrA. We have tested on AEEEM and ReLink datasets, and the results show that our method has an average improvement of 23%compared with TCA+ algorithm on AEEEM datasets,and an average improvement of 5% on ReLink datasets.

关键词： feature engineering cross-project defect prediction software defect prediction project management feature selection learning (artificial intelligence) software maintenance WCM-WTrA distance-weight transfer learning software quality distance-weight instance transfer multisource model MultiWCM-WTrA

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：