检索结果-内蒙古大学图书馆

IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)

作者： R K Pongiannan S. Nikkath Bushra Syed Ismail Abdul Lathif Saahil Pradhan R Brindha J Franklin Department of Computing Technologies SRM Institute of Science and Technology Kattankulathur India Data science and business systems School of computing SRM Institute of Science and Technology Kattankulathur India Department of Computational Intelligence SRM Institute of Science and Technology Kattankulathur India Department of Electrical and Electronics Engineering SRM Institute of Science and Technology Kattankulathur India

Health care has become an essential part of present human life. The preliminary requirement to select the basic information about medical facilities through a mobile app will serve the needs of the common people. This paper presents an integrated mobile app developed using JAVA. This app is user-friendly in terms of login, registration, and bookings. This caters to the facility to select information regarding doctors, medical lab facilities, pharmacy details, and health articles. This app will provide communication.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Micro-Objects Classification for Microplastic Pollution Detection using Holographic Images

Micro-Objects Classification for Microplastic Pollution Dete...

引用

Advances in computing, Communication and Applied Informatics (ACCAI), International Conference on

作者： Naga Sai Munagala Vibhaw Kumar S. Srividhya G. Usha R. Jeyalakshmi Department of Data Science and Business Systems SRM Institute of Science and Technology Kattankulathur Chennai India Department of Computing Technology SRM Institute of Science and Technology Kattankulathur Chennai India Department of Chemistry SRM Institute of Science and Technology Kattankulathur Chennai India

ISBN: (数字)9798350389449

ISBN: (纸本)9798350389456

Microplastic pollution poses a significant environmental threat, necessitating advanced methods for effective control and mitigation. This paper focuses on the development of a novel approach for micro-objects classification, specifically targeting microplastics, utilizing holographic images. Holography provides a three-dimensional representation of microscopic particles, enhancing the accuracy and efficiency of classification algorithms. In this paper, initially the acquisition of holographic images of water samples containing micro-objects, with a particular emphasis on microplastics are collected. State-of-the-art image processing and machine learning techniques are employed to develop a robust classification system capable of distinguishing between various micro-objects with high precision. Next, the Key objectives include the design and implementation of classification algorithm, leveraging holographic data to differentiate microplastics from other particles. The proposed work aims to enhance the efficiency of microplastic identification, enabling more effective monitoring and control of pollution in aquatic *** outcomes of this paper hold promise for advancing microplastic pollution research and environmental monitoring practices. The integration of holographic images into the classification process offers a unique perspective, providing valuable insights into the characteristics and distribution of microplastics. Ultimately, this research contributes to the development of innovative solutions for addressing the pervasive issue of microplastic pollution.

关键词： Training Accuracy Pollution Image processing Computational modeling Prevention and mitigation Microscopy

来源：评论

学校读者我要写书评

暂无评论

IoT-based trusted wireless communication framework by machine learning approach

引用

Measurement: Sensors 2024年 34卷

作者： Chakaravarthi, S. Saravanan, S. Jagadeesh, M. Nandhini, S. Department of Artificial Intelligence and Data Science Panimalar Engineering College India Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Tamilnadu Chennai India Department of Computing Technologies SRM Institute of Science and Technology Tamilnadu Kattankulathur603203 India Department of Data Science and Business Systems SRM Institute of Science and Technology Tamilnadu Kattankulathur603203 India

The traditional Radio-Frequency systems (RFS) authentication methods, designed to ensure secure data transmission on the web, may not always effectively prevent adversaries from gaining access to concealed IDs or asymmetric cryptography through infiltrative, side-channel, training, and computer attacks. In contrast, Unaccounted Information (UAI) has the potential to exploit irregularities in production systems to automatically identify microchips, offering a highly robust and cost-effective security solution. This approach introduces RFS-UAI, a deep neural network-based system that efficiently manages wireless node identification by leveraging synthetic RFS characteristics of remote controls (Tx) learned through supervised methods in Wireless Sensor Networks (WSN). Unlike traditional methods that require the development of specialized transistors for UAI or semantic segmentation, this approach utilizes the existing asymmetrical RFS communication networks. Similar to the way the human brain processes information, Rx handles the entire device identification process at the gateway. According to test results, which include assessing process capability at a specified 65 nm threshold voltage and characteristics such as Local Oscillator (LO) misalignment and I-Q disparity using a probabilistic model with 52 hidden units, the system can distinguish up to 4800 transmitters with a remarkable 99.9 % accuracy under various channel conditions, all without the need for regular preambles. This recommended method can serve as a standalone security measure or be integrated into a biometric identification system. © 2024 The Authors

关键词： Authentication

来源：评论

学校读者我要写书评

暂无评论

A Review of the Effectiveness of Management Information System in Decision Making 1

A Review of the Effectiveness of Management Information Syst...

引用

1st International Conference on Computer science and Emerging Technologies, CSET 2023

作者： Zeidan Al-Kaseasbeh, Hazem Mohammad Wahsheh, Firas Rashed Mohamad, Fatma Susilawati Jusoh, Julaily Aida Farea, Mazen Mohammed Archana, V.K. Irbid National University Faculty of Business and Financial Science MIS Bi and Data Analysis Department Irbid Jordan Ajloun National University Faculty of Business Department of Management Information Systems Ajloun Jordan UniSZA Faculty of Informatics and Computing Malaysia Al-Madinah International University Faculty of Finance & Administrative Sciences Malaysia Jain Deemed to Be University Bangalore India

ISBN: (纸本)9798350341737

The rapid advancement of technology has revolutionized the way organizations operate, resulting in the widespread adoption of Management Information systems (MIS) as a crucial tool in decision-making processes. This research paper presents a comprehensive review of the effectiveness of Management Information systems in facilitating decision-making within various organizational contexts. The paper begins with an exploration of the fundamental role of MIS in collecting, processing, and presenting relevant data to decision-makers. Emphasis is placed on understanding how MIS enables the integration of data from diverse sources and transforms it into actionable insights, empowering managers to make informed and timely decisions. Furthermore, this review delves into the different types of Management Information systems, including Executive Information systems (EIS), Decision Support systems (DSS), and Transaction Processing systems (TPS). By analyzing case studies and real-world examples, the paper highlights the specific applications and benefits of each system type in enhancing decision-making efficiency and accuracy. To assess the effectiveness of MIS in decision-making, the review examines key performance indicators, such as the speed and accuracy of decision-making processes, resource optimization, and overall organizational performance. The role of MIS in improving strategic planning, risk management, and competitive advantage is also thoroughly investigated. Additionally, the review explores potential challenges and limitations associated with the implementation and utilization of MIS in decision-making. Factors such as data security, system reliability, user training, and resistance to change are addressed, offering insights into strategies for mitigating these obstacles. The paper concludes with a synthesized analysis of the existing literature and identifies gaps for future research in the field of Management Information systems and decision-making effectiveness

关键词： Decision support systems

来源：评论

学校读者我要写书评

暂无评论

Strengthening Authentication: The Role of Multi-Level Hashing in OSPA Protocol 5

Strengthening Authentication: The Role of Multi-Level Hashin...

引用

5th International Conference on IoT Based Control Networks and Intelligent systems, ICICNIS 2024

作者： Hariharasudhan, S. Varghese, Vineetha Malarvizhi, K. Santhoshkumar, S.P. Nalini, T. Vikram, D. Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Computer Science and Engineering Chennai Avadi India Rathinam Technical Campus Department of Computer Science and Engineering Coimbatore India Jct College of Engineering and Technology Department of Computer Science Al Business Systems Coimbatore India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology School of Computing Department of Computer Science and Engineering Chennai Avadi India Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Saveetha University Department of Computer Science and Engineering Chennai India Rathinam Technical Campus Department of Artificial Intelligence Data Science Coimbatore India

ISBN: (纸本)9798331518097

Authentication is a crucial step in the cyber security process that confirms user identities. Even though they are widely used, traditional password based techniques are frequently vulnerable to attacks like guessing and password theft. This study presents the Optimal Strong Password Authentication (OSPA) protocol, which uses USB sticks to provide safe user authentication in order to address these issues. The Multi-Level Hashing Algorithm (MLHA), which dynamically picks hash functions during authentication to generate many layers of hashed passwords, is a key component of OSPA's effectiveness. By preventing eavesdropping efforts and reducing the possibility of unwanted access through guessing attacks, this method strengthens security. This protocol provides strong authentication procedures, protecting confidential data and improving overall cyber security posture by integrating MLHA into the OSPA architecture. © 2024 IEEE.

关键词： Authentication Protocol

来源：评论

学校读者我要写书评

暂无评论

Experimental Evaluation of AI Powered Vehicle Toll Collection System Based on RFID and Internet of Things (IoT) Assistance

Experimental Evaluation of AI Powered Vehicle Toll Collectio...

引用

2024 International Conference on Innovative computing, Intelligent Communication and Smart Electrical systems, ICSES 2024

作者： Pulikanti, Jyothi Jayaraj, R. Purushotham, S. Devi, V. Saranya Antony, A.Santhi Mary Chitra, M.P. Qis College of Engineering and Technology Department of Aimlds Andhra Pradesh Ongole India School of Computing Srm Institute of Science and Technology Department of Data Science and Buisness Systems Kattankulathur Chennai India Sona College of Technology Department of Eee Salem India Qis College of Engineering and Technology Department of Ece AndhraPradesh Ongole India Loyola-ICAM College of Engineering and Technology Department of Eee Nungambakkam Loyola Campus Chennai India Panimalar Engineering College Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798331543617

This paper presents the experimental evaluation of an AI-powered vehicle toll collection system, utilizing RFID technology and IoT integration. The system was designed to automate toll collection, reducing transaction time and improving accuracy while minimizing human intervention. The methodology involved RFID-based vehicle identification, real-time data transfer via IoT, and automatic toll deductions from prepaid accounts. The system was evaluated based on transaction speed, accuracy, user satisfaction, and system reliability. Results show that the automated system significantly reduced average transaction times from 32.5 seconds (manual) to 10 seconds (automated) during peak hours. Additionally, the system demonstrated a 100% accuracy rate in detecting unregistered vehicles and low-balance scenarios. User satisfaction was high, with an average rating of 4.6 out of 5. System reliability was also excellent, achieving an average uptime of 99.5% across multiple toll booth locations. The AI-powered toll collection system proved to be highly efficient in automating toll processes, reducing congestion, and improving the user experience. These findings suggest that such systems can effectively modernize toll management, contributing to time savings, reduced operational costs, and enhanced security. © 2024 IEEE.

关键词： Radio frequency identification (RFID)

来源：评论

学校读者我要写书评

暂无评论

Blockchain-Enabled Quality Assurance and Traceability in the Indian Confectionery Market

Blockchain-Enabled Quality Assurance and Traceability in the...

引用

Innovative computing, Intelligent Communication and Smart Electrical systems (ICSES), International Conference on

作者： B. Subashini P. Shanthi K. Venkatesh Department of Data Science and Business Systems School of Computing SRM Institute of Science and Technology kattankulathur Tamilnadu India Department of Information Technology St. Joseph's Institute of Technology OMR Chennai Department of Networking and Communications School of Computing SRM Institute of Science and Technology kattankulathur Tamilnadu India

ISBN: (数字)9798331543624

ISBN: (纸本)9798331543631

India, whose population growth is its greatest asset cannot afford to let its people eat confectionery that is either tainted or somehow polluted, since this would lead to extensive malnutrition. Traditional food supply chains are characterized by centralization and the problems associated with it such as having a single point of failure and producing inconsistent products while compromising the quality, along with data loss. With the need for daily reports in all regions of India regarding food fraud, contamination, and adulteration, a clearly advanced decentralized model is sought after for the creation of a supply chain. This paper introduces the supply chain network for the Indian confectionery market based on blockchain to better address quality claims, contamination, and transparency. This enables real-time traceability within the ecosystem, by using IoT strategies along with the Ethereum blockchain leading to better product authentication and resulting in higher consumer confidence. Blockchain creates a secure data tracking function, while smart contracts can be used to define the process - such as IoT monitoring of temperature. The united method enables verified data to be available to the consumer, energy efficiency, and trust across the supply chain.

关键词： Temperature sensors Temperature measurement Temperature distribution Quality assurance Supply chains Smart contracts Real-time systems Blockchains Contamination Monitoring

来源：评论

学校读者我要写书评

暂无评论

Enabling Protection for Critical Infrastructure through Security and Privacy in the Industrial Internet of Things 9

Enabling Protection for Critical Infrastructure through Secu...

引用

9th International Conference on Communication and Electronics systems, ICCES 2024

作者： Yasotha, B. Vijayanandh, T. Thirumoorthy, P. Priya, M.Sangeetha Sasidaran, S. Prakalya, S.B. Srmist Department of Data Science and Business Systems Kattankulathur India School of Computing Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science & Engineering Avadi Tamil Nadu Chennai India Dhanalakshmi College of Engineering Department of Electrical and Electronics Engineering Chennai India Chennai India Panimalar Engineering College Department of Information Technology Chennai600123 India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798350377972

Industrial Internet of Things can improve critical infrastructure in energy, transportation, and manufacturing. However, IIoT device and system integration opened security weaknesses that bad actors may exploit, causing huge disruptions and financial losses. IoT network security and privacy must be prioritized to protect key infrastructure. IIoT security issues and solutions are examined in this research. First, we take a look at the state of security and the unique risks that industrial IoT devices are up against, including hacking, illegal access, and cyber-physical assaults. Then, to lessen the impact of these dangers, we investigate cutting-edge security solutions, such as authentication, encryption, and access control systems. Building a robust security architecture specifically for IIoT applications is one of the main goals of the project. To improve safety and anonymity, this system uses cutting-edge innovation like blockchain, AI, and edge computing. We also talk about how privacy-preserving methods like differential privacy and anonymization are important for keeping sensitive information safe while allowing data sharing for analysis and operations. We assess the efficacy of the suggested security protocols and procedures using a battery of case studies and simulations. Reducing the attack surface and improving the resilience of IIoT systems can be achieved by a multi-layered security approach that includes effective privacy protections. We conclude by outlining our research's larger implications, which include the importance of standardization, regulatory compliance, and stakeholder collaboration in ensuring the safe and privacy-protecting deployment of IIoT technologies in vital infrastructure. Protecting vital infrastructure from cyber threats is our ultimate goal, and our work helps build IIoT systems that are more secure and dependable. © 2024 IEEE.

关键词： Industrial internet of things (IIoT)

来源：评论

学校读者我要写书评

暂无评论

Intelligent traffic prediction system using hybrid convolutional neural networks for smart cities

引用

Multimedia Tools and Applications 2024年 1-19页

作者： J, Jeba Sonia G, Arun Kumar kumar, ERajesh Raju, K. Narasimha Sudha, V. Kshirsagar, Pravin R. Tirth, Vineet Rajaram, A. Department of Data Science and Business Systems School of Computing College of Engineering and Technology SRM Institute of Science and Technology Tamil Nadu Chennai603203 India Department of Electronics and Communication Engineering JSS Academy of Technical Education Uttar Pradesh Noida201301 India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram522302 India Andhra Pradesh Visakhapatnam530048 India Department of Electronics and Communication Engineering Sona College of Technology Tamil Nadu Salem636005 India Department of Electronics & amp Telecommunication Engineering J D College of Engineering & ampManagement Maharashtra Nagpur India Mechanical Engineering Department Centre for Engineering and Technology Innovations College of Engineering King Khalid University Asir Abha61421 Saudi Arabia Department of Electronics and Communication Engineering EGS Pillay Engineering College Nagapattinam India

Intelligent Traffic Management systems (ITMS) play a crucial role in advancing smart city applications by addressing the rapid increase in road traffic due to the growing number of vehicles. Effective real-time traffic prediction is essential to avoid congestion, yet existing systems often struggle with high delays and insufficient accuracy. This paper introduces an innovative ITMS based on a Hybrid Convolutional Neural Network (HCNN) to overcome these challenges. The proposed system integrates numerous smart devices, including smart vehicles, with an edge computing framework where the HCNN model is deployed. The HCNN combines Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks to enhance prediction accuracy and reduce latency. Experimental results demonstrate that the HCNN model achieves up to 95% prediction accuracy while reducing delays by up to 50% compared to conventional methods. These improvements are significant for smart city applications, ensuring timely and precise traffic management. The study validates the effectiveness of the HCNN model in improving traffic prediction and proposes its potential for broader smart city implementation. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Asymptotic Bayesian Generalization Error in Latent Dirichlet Allocation and Stochastic Matrix Factorization

引用

SN Computer science 2020年第2期1卷 1-22页

作者： Hayashi, Naoki Watanabe, Sumio Simulation & Mining Division NTT DATA Mathematical Systems Inc. 1F Shinano-machi-Renga-kan Shinano-machi 35 Tokyo Shinjuku-Ku 160-0016 Japan Department of Mathematical and Computing Science Tokyo Institute of Technology W8-42 Tokyo 2-12-1 Oookayama Meguro-ku 152-8552 Japan

Latent Dirichlet allocation (LDA) is useful in document analysis, image processing, and many information systems;however, its generalization performance has been left unknown because it is a singular learning machine to which regular statistical theory can not be applied. Stochastic matrix factorization (SMF) is a restricted matrix factorization in which matrix factors are stochastic;the column of the matrix is in a simplex. SMF is being applied to image recognition and text mining. We can understand SMF as a statistical model by which a stochastic matrix of given data is represented by a product of two stochastic matrices, whose generalization performance has also been left unknown because of non-regularity. In this paper, using an algebraic and geometric method, we show the analytic equivalence of LDA and SMF, both of which have the same real log canonical threshold (RLCT), resulting in that they asymptotically have the same Bayesian generalization error and the same log marginal likelihood. Moreover, we derive the upper bound of the RLCT and prove that it is smaller than the dimension of the parameter divided by two, hence the Bayesian generalization errors of them are smaller than those of regular statistical models. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Algebraic geometry Bayesian learning Latent Dirichlet allocation Matrix factorization Singular model Topic model

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：