检索结果-内蒙古大学图书馆

2nd International Conference on Computational Intelligence, Communication Technology and Networking, CICTN 2025

作者： Kulkarni, Soham Sunil Kumar, Anant Gakhar, Suket Sharma, Vipin Kumar Arora, Sneha Department of Computer Science University of California Irvine Irvine United States Department of Computer Science and Engineering Manipal Institute of Technology Manipal India Department of Computer Science and Engineering Kurukshetra University Kurukshetra India Department of Electronics and Communication Engineering Lovely Professional University Phagwara India

ISBN: (纸本)9798331530389

This paper introduces a secure authentication framework by applying Mutual Authentication Coupled with Optimised AES (Advanced Encryption Standard) Encryption to improve the security of the multi-server environment. By addressing inefficiencies in traditional mutual authentication protocols without encryption, this framework significantly improves both performance and resilience. Encryption time was reduced by 25% and authentication time by 16.67% while CPU (Central Processing Unit) usage was reduced by 23.08%, with a corresponding 21.43% improvement in memory efficiency. The proposed system demonstrates a 70% improvement in attack resistance. Dynamic revocation mechanisms mitigate unauthorized access and malicious activity in real time. The protocol is designed for resource-constrained environments to ensure secure, scalable, and efficient communication in multi-server architectures, further increasing system reliability and user trust in cloud-based services. © 2025 IEEE.

关键词： Authentication Protocol

来源：评论

学校读者我要写书评

暂无评论

Multi-model Ensemble Conformal Prediction in Dynamic Environments 38

Multi-model Ensemble Conformal Prediction in Dynamic Environ...

引用

38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Hajihashemi, Erfan Shen, Yanning Department of Electrical Engineering & Computer Science University of California Irvine United States

Conformal prediction is an uncertainty quantification method that constructs a prediction set for a previously unseen datum, ensuring the true label is included with a predetermined coverage probability. Adaptive conformal prediction has been developed to address data distribution shifts in dynamic environments. However, the efficiency of prediction sets varies depending on the learning model used. Employing a single fixed model may not consistently offer the best performance in dynamic environments with unknown data distribution shifts. To address this issue, we introduce a novel adaptive conformal prediction framework, where the model used for creating prediction sets is selected 'on the fly' from multiple candidate models. The proposed algorithm is proven to achieve strongly adaptive regret over all intervals while maintaining valid coverage. Experiments on real and synthetic datasets corroborate that the proposed approach consistently yields more efficient prediction sets while maintaining valid coverage, outperforming alternative methods. © 2024 Neural information processing systems foundation. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Komorebi: Enhancing Mental Wellness with Sentiment Analysis and Cognitive Behavior Therapy 4

Komorebi: Enhancing Mental Wellness with Sentiment Analysis ...

引用

4th International Conference on Electrical, computer, Communications and Mechatronics engineering, ICECCME 2024

作者： Lee, Priyanka Sood, Kanika California State University Fullerton Department of Computer Science Fullerton United States

ISBN: (纸本)9798350391183

In recent years, the rapid advancements in human and computer interaction have been reshaped by artificial intelligence (AI) and natural language processing (NLP). Chatbots have been among the most prominent use cases of NLP and have provided transformative technological applications which have been integral to our digital landscape. One of the most promising applications of chatbot utilization is in the medical industry, specifically mental health. NLP is at the heart of this AI capability and has revolutionized how chatbots interact with users, allowing the computer to generate, understand, and analyze human language interactions. This research presents the development and evaluation of a GPT-powered mental health chatbot for a mental wellness website with a foundation built on sentiment analysis techniques. The chatbot aims to provide personalized support and leverage evidence-based strategies for coping with and improving mental health issues prescribed using cognitive behavior therapy (CBT) interventions. Through the implementation of a combination of machine learning models and rule-based algorithms, the website features an activities module which categorizes user sentiments into positive, neutral, and negative emotions and prescribes a personalized CBT intervention to users. The system fosters an empathetic and supportive conversational environment between users and the virtual assistant to build rapport and trust. The effectiveness of this chatbot is measured through a mixed-methods approach that includes functional testing, user feedback, and ethical evaluation. © 2024 IEEE.

关键词： mHealth

来源：评论

学校读者我要写书评

暂无评论

WiFi Received Signal Strength (RSS) Based Automated Attendance System for Educational Institutions 24

WiFi Received Signal Strength (RSS) Based Automated Attendan...

引用

11th International Conference on Networking, Systems and Security, NSysS 2024

作者： Khan, Sidratul Muntaha Maliha, Mehreen Tabassum Haque, Md Shahedul Rahman, Ashikur Department of Computer Science and Engineering Bangladesh University of Engineering and Technology Dhaka Bangladesh Department of Computer Science Virginia Polytechnic Institute State University Arlington United States

ISBN: (纸本)9798400711589

Smartphones are becoming part of people’s day-to-day activities now-a-days. Globally, almost 90% of cellular phones are smartphones. "Personnel tracking" is a viable usage of smartphones. Automated attendance system, an application of personnel tracking, is efficient and essential for enhancing productivity and streamlining operations in modern workplaces and educational institutions. While traditional methods of attendance tracking are prone to inaccuracies and inefficiencies, smartphone-based systems offer a smoother approach. In this paper, we present a smartphone-based attendance system that leverages Wi-Fi signal strength for indoor localization. Instead of requiring precise positioning, we propose a system with zone-based localization approach. We divide the whole area into distinct smaller zones and determine the users’ location within these zones. Through real-world deployment, we demonstrate that our novel approach reduces the complexity of exact positioning while still achieving high accuracy in identifying a user’s presence within specific areas, which are often enclosed by boundaries. Comparative evaluations with implementing an algorithm show the superiority of our proposed method in terms of accuracy and practicality, making it suitable for deployment in large-scale organizational settings. © 2024 Copyright held by the owner/author(s).

关键词： Wi-Fi

来源：评论

学校读者我要写书评

暂无评论

Visual Studio Code in Introductory computer science Course: An Experience Report

Visual Studio Code in Introductory Computer Science Course: ...

引用

2024 ASEE Annual Conference and Exposition

作者： Tan, Jialiang Chen, Yu Jiao, Shuyin Department of Computer Science and Engineering Lehigh University United States Department of Computer Science North Carolina State University United States

Involving integrated development environments (IDEs) in introductory-level (CS1) programming courses is critical. However, it is difficult for instructors to find a suitable IDE that is beginner-friendly and offers robust functionality. In this paper, we share our experience of implementing Visual Studio Code (VS Code) in a CS1 programming course. We describe our motivation for selecting VS Code and our approach to introducing it to engineering students. To assist students with diverse programming backgrounds, we provide comprehensive guidance with hierarchical indexing. By seamlessly integrating VS Code, known as a rich text editor, with a selection of extensions, our aim is to streamline the learning process for students by enabling it to function as an IDE. We perform an experimental evaluation of students' programming experience of using VS Code and validate the VS Code together with guidance as a promising solution for CS1 programming courses. © American Society for engineering Education, 2024.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Adaptive Solution Space in Particle Swarm Optimization

Adaptive Solution Space in Particle Swarm Optimization

引用

2024 United states National Committee of URSI National Radio science Meeting, USNC-URSI NRSM 2024

作者： Bagherkhani, Sahar Rahmat-Samii, Yahya De Flaviis, Franco Department of Electrical Engineering and Computer Science University of California Irvine CA United States Department of Electrical and Computer Engineering University of California Los Angeles CA United States

ISBN: (纸本)9781946815194

Particle swarm optimization (PSO) is a well-known optimization technique in electromagnetics. To ensure particles remain within the designated solution space throughout the optimization procedure, various boundary conditions are employed in PSO algorithms. However, there are instances when the global optimum is not present within the specified solution space. Consequently, regardless of how extensively the particles search, they cannot achieve the desired fitness value. This paper introduces an adaptive solution space method that efficiently expands the solution space to attain the desired fitness goals. The performance of the adaptive solution space method is tested using both mathematical benchmark functions and a real-world electromagnetic problem. Simulation results confirm the efficiency and effectiveness of the proposed adaptive solution space method. © 2024 IEEE. All rights reserved.

关键词： adaptive solution space antenna design Particle swarm optimization (PSO) patch antenna Rastigrin function

来源：评论

学校读者我要写书评

暂无评论

Accurate threat hunting in industrial internet of things edge devices

引用

Digital Communications and Networks 2023年第5期9卷 1123-1130页

作者： Abbas Yazdinejad Behrouz Zolfaghari Ali Dehghantanha Hadis Karimipour Gautam Srivastava Reza M.Parizi Cyber Science Lab School of Computer ScienceUniversity of GuelphOntarioCanada Department of Electrical and Software Engineering University of CalgaryAlbertaCanada Department of Mathematics and Computer Science Brandon UniversityBrandonCanada College of Computing and Software Engineering Kennesaw State UniversityGAUSA Research Center for Interneural Computing China Medical UniversityTaichungTaiwanChina Department of Computer Science and Mathematics Lebanese American UniversityBeirut1102Lebanon

Industrial Internet of Things(IIoT)systems depend on a growing number of edge devices such as sensors,controllers,and robots for data collection,transmission,storage,and *** kind of malicious or abnormal function by each of these devices can jeopardize the security of the entire ***,they can allow malicious software installed on end nodes to penetrate the *** paper presents a parallel ensemble model for threat hunting based on anomalies in the behavior of IIoT edge *** proposed model is flexible enough to use several state-of-the-art classifiers as the basic learner and efficiently classifies multi-class anomalies using the Multi-class AdaBoost and majority *** evaluations using a dataset consisting of multi-source normal records and multi-class anomalies demonstrate that our model outperforms existing approaches in terms of accuracy,F1 score,recall,and precision.

关键词： IIoT Threat hunting Edge devices Multi-class anomalies Ensemble methods

来源：评论

学校读者我要写书评

暂无评论

A Comprehensive Ensemble-Based Approach for Heart Disease Prediction with Feature Selection and Model Analysis 5

A Comprehensive Ensemble-Based Approach for Heart Disease Pr...

引用

5th International Conference on Advanced Research in Computing, ICARC 2025

作者： Tahosin, Mst. Sazia Hossain Pranto, Ismail Uddin Chowdhury, Mohamamd Muid Barua Emon, Sonet Alam, Md Ashraful Khan, Chonchal Daffodil International University Department of Computer Science and Engineering Dhaka Bangladesh American International University-Bangladesh Department of Computer Science and Engineering Dhaka Bangladesh Chittagong University of Engineering and Technology Department of Electronics and Telecommunication Engineering Chattogram Bangladesh Noakhali Science and Technology University Department of Computer Science and Telecommunication Engineering Noakhali Bangladesh Colorado State University Department of Computer Science CO United States

ISBN: (纸本)9798331530983

Heart disease is a leading global cause of mortality, emphasizing the urgent need for early and accurate diagnostic methods. However, traditional diagnostic tools often lack the scalability and precision to meet diverse healthcare demands. We propose a robust ensemble-based machine learning framework for heart disease prediction that combines advanced data preprocessing, feature selection, and model optimization techniques to address this. This study utilized a consolidated dataset of 1,888 records from five heart health databases. First, systematic preprocessing addressed missing values and standardized features. Next, a hybrid feature selection strategy, integrating Univariate Selection, Correlation Coefficient Analysis, and Mutual Information, reduced the feature set from 14 to 11 key indicators. Subsequently, we evaluated 12 machine learning models on all and reduced feature sets. Finally, our ensemble model, combining Random Forest, Decision Trees, XGBoost, CatBoost, and Extra Trees, achieved an outstanding accuracy of 98.12±1.20. Thus, our results demonstrate that integrating multiple classifiers with optimized feature selection significantly enhances predictive accuracy and model reliability. This scalable framework can transform early heart disease detection, improving outcomes across diverse healthcare settings. © 2025 IEEE.

关键词： Cardiology

来源：评论

学校读者我要写书评

暂无评论

Exploring Efficient Implementation of Delay-based PUF Design on FPGA

Exploring Efficient Implementation of Delay-based PUF Design...

引用

2023 International Conference on Intelligent Computing, Communication, Networking and Services, ICCNS 2023

作者： Rajput, Shailesh Dofe, Jaya Sood, Kanika California State University Department of Electrical and Computer Engineering FullertonCA United States California State University Department of Computer Science FullertonCA United States

ISBN: (纸本)9798350339291

The Internet of Things (IoT) presents unique challenges for security due to resource limitations. Physically unclonable function (PUF) technology offers a promising solution for cost-effective hardware identification and authentication. PUFs leverage process variations in integrated circuits to produce unique and unreplicable responses. They generate a significant number of challenge-response pairs (CRPs) for authentication. In IoT applications, Arbiter PUF (APUF) and its variants are considered the most appropriate lightweight security primitives. However, implementing a high-quality version of APUF on Field Programmable Gate Arrays (FPGA) has been challenging. This work proposes a practical implementation of APUF and XOR PUF on FPGA, improving flexibility and simplifying implementation. Our experimental analysis shows that APUF and XOR PUF demonstrate a remarkable reliability rate of 98%. Additionally, the distribution of 1s and 0s in the response bit is almost uniform, indicating a randomness of 46.81%. Furthermore, we conduct machine learning modeling attacks to assess the efficacy of the APUF and XOR PUF implementation. © 2023 IEEE.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

A Spectral Approach to Approximately Counting Independent Sets in Dense Bipartite Graphs 51

A Spectral Approach to Approximately Counting Independent Se...

引用

51st International Colloquium on Automata, Languages, and Programming, ICALP 2024

作者： Carlson, Charlie Davies, Ewan Kolla, Alexandra Potukuchi, Aditya Department of Computer Science University of California Santa BarbaraCA United States Department of Computer Science Colorado State University Fort CollinsCO United States University of California Santa CruzCA United States Department of Electrical Engineering and Computer Science York University Toronto Canada

ISBN: (纸本)9783959773225

We give a randomized algorithm that approximates the number of independent sets in a dense, regular bipartite graph – in the language of approximate counting, we give an FPRAS for #BIS on the class of dense, regular bipartite graphs. Efficient counting algorithms typically apply to "high-temperature" problems on bounded-degree graphs, and our contribution is a notable exception as it applies to dense graphs in a low-temperature setting. Our methods give a counting-focused complement to the long line of work in combinatorial optimization showing that CSPs such as Max-Cut and Unique Games are easy on dense graphs via spectral arguments. Our contributions include a novel extension of the method of graph containers that differs considerably from other recent low-temperature algorithms. The additional key insights come from spectral graph theory and have previously been successful in approximation algorithms. As a result, we can overcome some limitations that seem inherent to the aforementioned class of algorithms. In particular, we exploit the fact that dense, regular graphs exhibit a kind of small-set expansion (i.e., bounded threshold rank), which, via subspace enumeration, lets us enumerate small cuts efficiently. © Charlie Carlson, Ewan Davies, Alexandra Kolla, and Aditya Potukuchi.

关键词： Containers

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：