检索结果-内蒙古大学图书馆

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

作者： Murala, Praveena Sivaraman, K. Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350359688

The complexity and size of biological datasets have led to an exponential increase in the demand for advanced data analysis tools in biological research. Traditional statistical methods and machine learning algorithms usually fail to capture complicated patterns in these datasets. The paper fills that gap by proposing a novel deep learning-based method for mining biological data. The suggested method overcomes the constraints of existing systems by utilizing Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) to extract hierarchical features and temporal correlations, respectively. Preprocessing techniques, supervised learning, transfer learning, and ensemble procedures are utilized to boost the system's accuracy (0.95), precision (0.94), recall (0.96), and F1score (0.95) when compared to other systems. The results indicate significant gains in accuracy across a variety of datasets, with the proposed system displaying computational efficiency, training in 8 hours and inference in 1 second, versus 15 hours and 5 seconds for conventional systems. The study underlines the critical need for new approaches in the field, as well as the transformational potential of the suggested system to accelerate medical, genetic, and biotechnology discoveries. © 2024 IEEE.

关键词： Data accuracy

来源：评论

学校读者我要写书评

暂无评论

Evolving Approaches in Epilepsy Management: Harnessing Internet of Things and Deep Learning 6th

Evolving Approaches in Epilepsy Management: Harnessing Inter...

引用

6th International conference on communication and computational technologies, ICCCT 2024

作者： Assim, Ola Marwan Mahmood, Ahlam Fadhil Department of Computer Science Engineering University of Mosul Mosul Iraq

ISBN: (纸本)9789819774227

For efficient treatment and management of epilepsy, which is characterized by repeated, abrupt, and excessive electrical discharges in the brain, early detection and exact diagnosis are required. The use of the Internet of Things (IoT) and deep learning algorithms for identifying and monitoring epileptic seizures has increased dramatically in recent years. IoT devices, which collect data from various sources like video cameras, wearable sensors, and electroencephalogram (EEG) equipment, collaborate with deep learning algorithms to deliver real-time insights about a patient's status. This in-depth examination examines the most recent breakthroughs in IoT and deep learning technology for identifying and tracking epileptic episodes. The review delves into the field's existing issues and potential future directions. This review begins by discussing the intricacies of diagnosing and monitoring epilepsy and subsequently delving into IoT and deep learning techniques for seizure detection, classification, and prediction. Finally, we shed light on intriguing research avenues and discuss the barriers and prospects in this dynamic domain. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Electroencephalography

来源：评论

学校读者我要写书评

暂无评论

Qualitative and Quantitative Analysis of Modifications in Playfair Cipher 5th

Qualitative and Quantitative Analysis of Modifications in...

引用

5th International Conference on Computational Intelligence in Communications and Business Analytics, CICBA 2023

作者： Ray, Anubhab Singh, Kartikeya Harsh, Aditya Thorat, Shubham Kar, Nirmalya Department of Computer Science and Engineering NIT Agartala Agartala India

ISBN: (纸本)9783031488788

Security in digital world has become a paramount issue, even more so in the post pandemic world when the digital footprint of the world has increased. Multiple encryption techniques are used to ensure the same. Certain famous classical ciphers which were in prevalent use during ancient times are now not robust enough to keep up with security requirements of modern world. This paper analyses the different modifications proposed to one such cipher i.e., Playfair Cipher and how these modifications enhance it’s performance thus making it usable in modern world. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Cryptography

来源：评论

学校读者我要写书评

暂无评论

Blockchain-Enabled Secure Communication for Autonomous Vehicles 8

Blockchain-Enabled Secure Communication for Autonomous Vehic...

引用

8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Khanpara, Pimal Kathiria, Preeti Patel, Usha Athreya, Deekshita Nirma University Department of Computer Science and Engineering Ahmedabad India

ISBN: (纸本)9798350376425

This research study introduces an innovative Vehicle-to-Everything (V2X) communication system utilizing Ethereum blockchain and Solidity smart contracts. The proposed approach transcends conventional vehicular communication systems by integrating the inherent security and transparency of blockchain technology. This integration aims to revolutionize V2X interactions, encompassing vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications, ensuring enhanced security, reliability, and immutability of data exchanged in urban traffic environments. The foundation of our system is a strong Solidity smart contract deployed on the Ethereum blockchain. This contract orchestrates the V2X communication, providing a decentralized and tamper-proof platform for transmitting and receiving data across various urban traffic entities. The practical application of this system is demonstrated through simulations in an urban environment created in Netedit, with various traffic scenarios evaluated using the Simulation of Urban Mobility (SUMO) software. © 2024 IEEE.

关键词： Ethereum

来源：评论

学校读者我要写书评

暂无评论

Revisiting Under-Represented Knowledge of Latin American Literature in Large Language Models 27

Revisiting Under-Represented Knowledge of Latin American Lit...

引用

27th European Conference on Artificial Intelligence, ECAI 2024

作者： Kim, Jinsung Koo, Seonmin Lim, Heuiseok Korea University Department of Computer Science and Engineering Korea Republic of

ISBN: (纸本)9781643685489

With the advent of large language models (LLMs), concerns about knowledge bias have recently increased. Previously, prevalent research has focused on detecting the bias of model knowledge by providing explicit social terms, such as race, gender, and age, into inputs. However, revealing the subtle and implicit bias of the model knowledge requires verification utilizing language expressed in a more implied form, such as literary works. This is because literature implicitly contains subjective filters of individuals and their living regional culture. Accordingly, this study aims to probe a research question of whether LLMs have a knowledge under-representation problem between two different regions using the same language, Spain and Spanish-speaking countries in Latin America. To this end, we design an under-representation verification task, REGion and Literary Author prediction (REGLA) and dataset based on Spanish-written literary works. Inspired by the knowledge shortcut concept from a previous study, REGLA consists of two tasks to figure out meta-information of poems, i.e., region and author. Moreover, we explore various prompting methods that can unleash the knowledge observed to be under-represented within the verification process. According to the verification and prompt engineering results, knowledge about the literary works of Latin American countries appears to be more under-represented compared to those of Spain in LLMs. It is also observed that the task decomposition prompting method effectively lets under-represented knowledge be generated. © 2024 The Authors.

关键词： Knowledge representation

来源：评论

学校读者我要写书评

暂无评论

EMRChain: Electronic Medical Records Management System using Blockchain 3

EMRChain: Electronic Medical Records Management System using...

引用

3rd IEEE International Conference on Blockchain and Distributed Systems Security, ICBDS 2024

作者： Rajasekharan, Arjun Koshy, Rani College of Engineering Trivandrum Dept. of Computer Science and Engineering Kerala Thiruvananthapuram India College of Engineering Trivandrum Department of Computer Science and Engineering Kerala Thiruvananthapuram India

ISBN: (纸本)9798350354348

Electronic Medical Records (EMRs) are traditionally managed by central authorities, posing significant security risks such as data breaches, limited interoperability, and restricted patient control. This system leverages blockchain technology to address these issues, ensuring data remains immutable, transparent, and highly secure. Utilizing the Ethereum network and IPFS technology, our system provides a decentralized framework for storing and sharing medical records. Healthcare professionals, patients, and authorized parties can seamlessly exchange and access records through Ethereum's decentralized structure and smart contracts, enabling automated and auditable interactions. To enhance confidentiality, all data uploaded to IPFS undergoes AES 256-bit encryption, with the encrypted Content Identifier (CID) stored on the blockchain. This ensures that intercepted CIDs cannot be accessed without the decryption key. IPFS technology facilitates decentralized storage and retrieval, eliminating the need for a centralized server and improving scalability and resilience. Patients retain full control over their health information, granting or revoking access as necessary. This system ensures secure patient identification, precise access management, and data confidentiality while allowing authorized parties to track and trace record access and modifications. Our blockchain-based EMR management system addresses the inherent risks of traditional centralized systems by providing a secure, transparent, and decentralized solution. By leveraging Ethereum and IPFS, it enhances data security, patient control, and interoperability, thus paving the way for more robust and patient-centric healthcare information management. This approach ensures that healthcare data remains secure, patients maintain control over their information, and authorized parties can effectively manage and access the records. © 2024 IEEE.

关键词： Ethereum

来源：评论

学校读者我要写书评

暂无评论

A New Profiling-Based Side-Channel Attack on Graphics Processing Units

引用

Journal of Computing science and engineering 2023年第1期17卷 30-40页

作者： Wang, Xin Zhang, Wei Department of Electrical and Computer Engineering Virginia Commonwealth University RichmondVA United States Department of Computer Science and Engineering University of Louisville LouisvilleKY United States

Graphics processing units (GPUs) have been increasingly used to solve a range of compute-intensive and data-parallel scientific computing problems that can be perfectly parallelized for performance speedups. Particularly, GPUs have recently become popular to host the encryption/decryption algorithms due to its high-throughput computing capability. However, the security issues of moving the cryptographic algorithms onto GPUs have not been studied adequately. Consequently, with absence of any protection strategy, the potential vulnerabilities of GPUs to side-channel attacks (SCAs) may expose the confidential information with high risk. In this paper, we proposed a new profiling-assisted correlationbased side-channel attack (pacSCA) to demonstrate that ignoring security issues and naively moving security services onto GPUs can offer adversaries fatal vulnerabilities to thieve critical information. The results showed that the proposed SCA can rebuild the secure key of the AES-128 algorithm in less than 6 seconds, revealing the urgency of protecting GPUs against side-channel threats. © Copyright 2023. The Korean Institute of Information Scientists and Engineers

关键词： Graphics processing unit

来源：评论

学校读者我要写书评

暂无评论

Harris Hawk Optimized CLAHE and Novel Score Level Fusion of Lightweight CNNs for Multimodal Biometric Recognition 6

Harris Hawk Optimized CLAHE and Novel Score Level Fusion of ...

引用

6th International Conference on Pattern Analysis and Intelligent Systems, PAIS 2024

作者： Singh, Indu Singh, Tanvi Luthra, Sunaina Khatri, Shruti Delhi Technological University Department of Computer Science And Engineering India

ISBN: (纸本)9798350350265

Biometric authentication is critical for secure access in diverse domains, emphasizing the need for high accuracy to prevent security breaches. Multimodal biometrics fuse traits to fortify security, vital across diverse domains, surpassing unimodal systems' vulnerability. This paper introduces a novel approach that combines Contrast Limited Adaptive Histogram Equalization (CLAHE) and Harris Hawk Optimization(HHO) (CLAHE-HHO) for image preprocessing. It is followed by an innovative score-level fusion designed for the classification of Iris and Palm-print Biometric Modalities, using Transfer Learning based Lightweight ShuffleNet and MobileNetV3 Architecture. Initially, the Iris and Palmprint images undergo preprocessing using CLAHE, with the clip limit optimized through Harris Hawk Optimization. After preprocessing, Iris images are classified using ShuffleNet, while Palmprint images undergo classification using MobileNetV3. Scores from Palmprint and Iris modalities are fused using Weighted sum Score-level Fusion, with fusion weights determined via the novel Cauchy Search-based Golden Ratio Optimization (CGRO) technique. The performance of the system is evaluated on accuracy, Detection Error Tradeoff (DET) Curve, Equal Error Rate (EER), Total Training time. The proposed methodology proves that the multimodal authentication outperformed unimodal identification with a recognition accuracy of 100 % surpassing results obtained from individual iris and palmprint modalities. © 2024 IEEE.

关键词： Biometrics

来源：评论

学校读者我要写书评

暂无评论

Real-time Air Quality Monitoring and Context-aware Alert System 17

Real-time Air Quality Monitoring and Context-aware Alert Sys...

引用

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

作者： Kakde, Anuj Pagoti, Yashwant Krishna Nikumbh, Sarthak Karmakar, Prasenjit Chakraborty, Sandip Indian Institute of Technology Department of Computer Science and Engineering Kharagpur India

ISBN: (纸本)9798331531195

Air quality monitoring is gaining increasing importance as awareness about the health impacts of air pollution continues to grow. These monitors typically track air pollutants to give users a clearer picture of their environment. Accurate and real-time monitoring increases our understanding of the surrounding air we breathe and allows us to improve it. The proposed system helps users minimize their exposure to harmful pollutants by providing real-time data on the concentration of various gases. The system triggers alerts directly to the subscribed user's mobile phones in case of any hazardous situations so that the user can take appropriate actions immediately to resolve the issue. Our extensive data collection and evaluation with off-the-shelf machine learning models indicated an overall F1-score of 99.54 (±0.5)% with a simple random forest model in classifying burning, cooking, occupancy in a closed room, using aerosol products, based on the sensor's readings. © 2025 IEEE.

关键词： Indoor air pollution

来源：评论

学校读者我要写书评

暂无评论

Display and View—NSDN—Image Caption Generator and Headcount 8th

Display and View—NSDN—Image Caption Generator and Headcoun...

引用

8th International Conference on Information System Design and Intelligent Applications, ISDIA 2024

作者： Nahar, Shreya Jain, Tanishka R. Shah, Mihir Dilip, Golda Department of Computer Science and Engineering SRMIST Vadapalani Chennai India

ISBN: (纸本)9789819748914

The automatic description of the content of an image is a challenge that combines computer vision with natural language processing in the field of artificial intelligence. Most existing models have limitations in accurately identifying subtle elements of an image and counting the number of people present. To address this challenge, we introduce the natural-language scene description network (NSDN), which incorporates recent developments in computer vision and machine translation to generate descriptive phrases that effectively depict images. This technology has the potential to improve the efficiency, capacity, reliability, and safety of crowd management tasks, particularly in diverse and adaptive crowd situations. Despite challenges such as clutter, occlusion, non-uniform object scale, and irregular object distribution, YOLO shows promise for intelligent crowd counting and analysis in images. This article reviews, categorizes, analyzes distinguishing features, and extensively assesses the effectiveness of crowd-counting methods that rely on convolutional neural networks and provides a detailed analysis of their performance. © The Author(s).

关键词： Convolutional neural networks

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：