检索结果-内蒙古大学图书馆

3rd international conference on Electrical, Electronics, and information Engineering, EEIE 2024

作者： Feng, Wenhui He, Qing Wang, Tingli Wang, Shixin School of Instrument Science and Opto-Electronics Engineering Beijing Information Science and Technology University Beijing100192 China

ISBN: (纸本)9781510688179

As the public pays more and more attention to fire, the importance of fire prevention is becoming increasingly prominent. This paper focuses on the realization of fire alarm software that can alarm in real time. Through in-depth research on sensor technology, cloud computing technology, mobile application development framework and real-time data processing algorithm, the accurate monitoring of smoke concentration and timely alarm function are realized. Through cloud server communication technology, the software can be stably connected with the supporting hardware equipment to complete the alarm notification in real time. At the same time, by continuously querying the server data at a frequency of once per second, it ensures that the alarm notification is issued to the user as soon as the server alarm data is updated. In addition, the software has a simple user interface, which is convenient for users to set up and view historical data, and fully considers the convenience of use. After rigorous testing, this software has excellent performance in accuracy, real-time and stability, providing a convenient and efficient solution for improving fire prevention capabilities, and has broad market prospects for its application in fire protection. © The Authors.

关键词： Fire alarm systems

来源：评论

学校读者我要写书评

暂无评论

The Symphony of Style: An Extensive Examination of Determination Mechanisms in Deep Learning-Inspired Outfit Suggestions 2

The Symphony of Style: An Extensive Examination of Determina...

引用

2nd international conference on Computational Intelligence, communication technology and Networking, CICTN 2025

作者： Guru Prasad, M.S. Bhosagi, Ravatappa A. Madhusudhana, K. Prithviraj Chandrappa, S. Kumar, Vikash Dehradun India School of Computing and Information Technology Reva University Bengaluru India Dept. of Electronics & Communication Engineering SDM Institute of Technology Ujire India NMAMIT Mangalore India Bengaluru India Department of Computer Application Graphic Era Deemed University Dehradun India

ISBN: (纸本)9798331530389

In the field of the fashion industry, the introduction of deep learning technology has taken an innovative revolution by providing assistance in the construction of intellectual systems that are intelligent to deliver personalized ensemble recommendations. In this research work, an innovative ensemble recommendation structure called Deep Learning VGG16 (Visual Geometry Group 16) recommender is presented. The proposed method allows a deep learning model VGG16 to understand complex patterns and developments resulting from a vast group of fashion images. In order to increase the user experience and greater participation in the well-established fashion industry, the system offers personalized ensemble ideas. The important, core and fundamental component of the system is VGG16, consisting of 13 convolutional layers and 3 fully connected layers, which is used to support the analysis of fashion images. A cutting-edge convolutional neural network (CNN) model is improved over a large and diverse collection of fashion images. Model will extract advanced high-level information and statistics with the capability to distinguish particulars in colour patterns, clothing combinations, and stylistic elements. Using this process of development, the system becomes better at identifying user preferences and fashion trends. © 2025 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Rapidly Deployed Cyber Attack Bait Based on Software Defined Network Corresponding to Artificial Intelligence Strategy 27

Rapidly Deployed Cyber Attack Bait Based on Software Defined...

引用

27th international conference on Advanced communications technology, ICACT 2025

作者： Jian, Ming-Shen Lee, Bo-Yi Liu, Xing-En Cai, Rui-Lun Cai, Zhong-Wei Liao, Pei-Cen Chou, Ta-Yuan Huang, Wun-Yuan CCIS Lab. Dept. of CSIE National Formosa University Yunlin County632 Taiwan 2National Center for High-Performance Computing Taiwan

ISBN: (纸本)9791188428137

To protect the services and data of the main servers, Rapidly Deployed Cyber Attack Bait is proposed for the unpredictable cybersecurity attack in this research. Based on Software Defined Network, the data packet and operation of cybersecurity attack could be redirected to the on demand deployed bait container. By suitable artificial intelligence strategy, the idle bait containers corresponding to the type of cybersecurity attack can be on demand deployed automatically and rapidly. Verification shows the feasibility of the virtualized bait container could be about 1.16 times to 2 times enough for the future coming attacker and also record the all operations of the cybersecurity attack individually. © 2025 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.

关键词： Cyber attacks

来源：评论

学校读者我要写书评

暂无评论

Wearable Assistive Device for Enhanced Navigation in Visually Impaired Individuals Using YOLO-Based Object Detection 5

Wearable Assistive Device for Enhanced Navigation in Visuall...

引用

5th IEEE international conference on advances in Electrical, computing, communication and Sustainable Technologies, ICAECT 2025

作者： Rao, Abhishek S. Poojary, Ramaprasad Karthik Pai, B.H. Rohan Arya, A.R. Utkarsh Kumar, Harsh Darshan, S. Shenoy, H. Nagesh Nmam Institute of Technology Department of Information Science and Engineering India School of Engineering and It Manipal Academy of Higher Education Dubai Campus PO Box no 345050 Dubai United Arab Emirates Canara Engineering College Department of Computer Science and Engineering Benjanapadavu India

ISBN: (纸本)9798350356236

The proposed study addresses the pressing challenge of enabling visually impaired individuals to navigate their surroundings with enhanced safety and autonomy. To this end, we propose a wearable assistive device designed to improve spatial awareness and facilitate environmental interaction. The primary objectives include developing an accurate object detection system, integrating real-time distance measurement capabilities, and incorporating situational awareness through weather data integration. The study methodology employs cutting-edge computer vision and machine learning techniques, with a YOLO-based object detection model at its core. This model ensures robust identification of objects, achieving an impressive 97% precision and recall. To support safe navigation, real-time distance measurement functionality was implemented. Additionally, the device incorporates real-time weather data via the Open Weather API, delivering comprehensive updates on temperature, precipitation, and wind conditions to assist in user decision-making. Design considerations focused on user-centric aspects such as battery life, portability, and cost-effectiveness to ensure practicality and accessibility. Evaluation results demonstrated an average mAP of 98.34% at IoU 0.5 across all object classes, with some reaching up to 99.50%. User testing validated the system's efficacy, achieving a 95% success rate in object identification and spatial guidance. These findings underscore the device's potential to enhance independence, safety, and quality of life for visually impaired users, promoting inclusivity through advanced assistive technology. © 2025 IEEE.

关键词： Distance measurement

来源：评论

学校读者我要写书评

暂无评论

Remote State Estimation and Blum–Shub–Smale Machines—A Computability Analysis With Applications to Virtual Twinning

引用

IEEE Transactions on Automatic Control 2025年第5期70卷 3165-3180页

作者： Boche, Holger Bock, Yannik Deppe, Christian Fitzek, Frank H. P. Technical University of Munich Chair of Theoretical Information Technology MunichD-80290 Germany BMBF Research Hub 6G-Life D-80333 Munich Germany MunichD-80799 Germany MunichD-80807 Germany Technische Universität Braunschweig Institute for Communications Technology BraunschweigD-38106 Germany 5G Lab Germany DresdenD-01062 Germany

This article analyzes aspects of the problem of remote state estimation (RSE) via noisy communication channels for their Blum–Shub–Smale (BSS) computability, motivated by an exemplary application to a formal model of virtual twinning subject to stringent integrity requirements. Computability theory provides a unique framework for the formal and mathematically rigorous analysis of algorithms and computing machines. Therefore, computability theory is essential in the domain of safety- and life-critical technology, where the formal verification of automated systems is necessary. Based on the RSE problem, we establish a simple mathematical model of virtual-twin systems that entails a formal notion of integrity (i.e., a state where the virtual entity accurately mirrors its physical counterpart). The model's notion of integrity is related to the question of whether the system under consideration is capable of computing the communication channel's zero-error capacity and corresponding zero-error codes. While this task is known to exceed the theoretical capabilities of Turing computers, we prove its formal feasibility within the model BSS machines. As different authors have proposed BSS machines as potential model of some forms of analog computing, this article serves as a proof-of-concept for a theoretical analog supremacy of unconventional information-processing hardware. Considering recent advances in the development of such hardware, forms of analog supremacy will likely become relevant in the future of cyber-physical systems and information technology. © 1963-2012 IEEE.

关键词： Computability and decidability

来源：评论

学校读者我要写书评

暂无评论

Dynamic Spectrum Allocation with Service Priority in C+L-Band Elastic Optical Networks 4

Dynamic Spectrum Allocation with Service Priority in C+L-Ban...

引用

4th international Computational Imaging conference, CITA 2024

作者： Yang, Huijie Zheng, Nianying Dang, Jian Wang, Xiaoling Chen, Hong Chen, Bowen School of Electronic and Information Engineering Soochow University Suzhou China School of Information and Communication Guilin University of Electronic Technology Guangxi Guilin541004 China

ISBN: (纸本)9781510688834

With the rapid development of cloud computing, video, smart home, and Internet of things (IoT), the bandwidth requirements of communication networks are also greatly increasing. This paper investigates dynamic spectrum allocation for both immediate and advance reservations in C+L-band elastic optical networks. We propose a dynamic spectrum allocation approach with service priority (DSA-SP) by considering the tolerable delay time. We consider the service importance when allocating the spectrum resources in C+L-band elastic optical networks. We discuss two types of the connection requests that include both immediate reservation and advance reservation based on the maximum tolerable delay time. The simulation results demonstrate that the proposed dynamic spectrum allocation approach achieves the low blocking probability, the high spectrum efficiency, and high average optical signal-to-noise ratio (SNR). © 2025 SPIE.

关键词： Signal to noise ratio

来源：评论

学校读者我要写书评

暂无评论

Revolutionizing Forensic Odontology with Artificial Intelligence: A Systematic Review 2

Revolutionizing Forensic Odontology with Artificial Intellig...

引用

2nd international conference on Computational Intelligence, communication technology and Networking, CICTN 2025

作者： Singh, Nitendra Singh, Kuldeep Sehrawat, Ruchi Singh, Amit Prakash Augustine, Jeyaseelan Verma, Mahesh University School of Information Communication and Technology Guru Gobind Singh Indraprastha University Sector 16C Dwarka New Delhi India Maulana Azad Institute of Dental Sciences New Delhi India Guru Gobind Singh Indraprastha University Sector 16C Dwarka New Delhi India

ISBN: (纸本)9798331530389

Forensic odontology is the branch of dentistry that deals with the proper collection, handling, and presentation of dental evidence to the court of law. It requires the expertise of a forensic odontologist. It can be time-consuming and strenuous in case of mass disasters. This has led many professionals to use automation. AI is revolutionizing healthcare;it is changing the practice of medicine (including dentistry), science, and policy. Dentistry and forensic odontology have been utilizing advances in diagnosis and treatment planning through the use of various AI-driven software and applications. AI applications in forensic science promise notable gains in efficiency and accuracy, particularly for disaster victim identification. The use of artificial intelligence (AI) in forensic odontology is discussed in this article along with the most recent findings and suggestions on ongoing translational advancements in intelligence. © 2025 IEEE.

关键词： Dentistry

来源：评论

学校读者我要写书评

暂无评论

8th international conference on information Science, communication and computing, ISCC 2024

8th International Conference on Information Science, Communi...

引用

8th international conference on information Science, communication and computing, ISCC 2024

The proceedings contain 24 papers. The special focus in this conference is on information Science, communication and computing. The topics include: The AIoT Ward Management and Health Monitori...

ISBN: (纸本)9789819617807

The proceedings contain 24 papers. The special focus in this conference is on information Science, communication and computing. The topics include: The AIoT Ward Management and Health Monitoring System based on Aliyun IoT Platform;blockchain-Based Verifiable Multi-Keyword Ciphertext Retrieval Scheme;a Secure and Efficient Signcryption Scheme Applying in IoT Scenarios;a Distraction Mining Network for Polyp Segmentation;ORLQ: A Link Quality-Based Routing Protocol for UWSN;A Method for Lightweight DDoS Attack Detection Based on LightGBM;smart Contract Vulnerability Detection Method Based on Node Feature Augmentation Graph Convolutional Network;smart Contract Vulnerability Detection Method Based on Edge-Deactivation Graph Convolutional Network;an Exhaustive Survey on the Methods and Applications of Graph Neural Networks;assessment of Forecast Algorithms of Aircraft Icing in Southwestern China;Research on Topic Mining Based on LDA Model;from Text to Emotion: Applying Fine-Tuning Techniques to Large Language Models for Sentiment Analysis of Children’s Reading;fine-Grained Sketch-Based Image Retrieval Using a Contrastive Learning Framework;radiometric Difference Measurement Method Based on Infrared Thermal Imager;automatic Measurement of Knee Joint Space Width on Anteroposterior X-ray Images Based on U2-Net;detection of Hip-Knee-Ankle Angle in Lower Limb X-rays Based on Multi-Classification U2-Net (Angles to Angle);target Association of Heterogeneous Sensors Based on Attribute-Position Fusion;verification and Testing of Chinese information technology Application Innovation Network Security for the Tobacco Industry;Fine-Grained Image Classification Based on BAM Attention Mechanism and PPM Pyramid Enhancement Methodological Studies;multimodal Machine Translation Based on Text-Image Aggregation;adaptive Multi-scale Fusion Transformer for Image Super-Resolution.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Advanced Facial Recognition with Behavioural Analysis for Intelligent Security Monitoring 5

Advanced Facial Recognition with Behavioural Analysis for In...

引用

5th IEEE international conference on advances in Electrical, computing, communication and Sustainable Technologies, ICAECT 2025

作者： Changala, Ravindra Yasaswi, K. RaviKiran Farooq, Mansoor Khan, Shamim Ahmad Kiran, Ajmeera Muthuperumal, S. Department of Cse Guru Nanak Institutions Technical Campus Hyderabad India Jntuk Department of Master of Business Administration Andhra Pradesh India American University of Bahrain Department of Cybersecurity Bahrain Glocal School of Science & Technology Glocal University Department of Ece Uttar Pradesh India Mlr Institute of Technology Dept. of Cse Telangana Hyderabad India K. Ramakrishnan College of Engineering Department of Mathematics Trichy India

ISBN: (纸本)9798350356236

Facial recognition systems has been adopted widely now in security systems of today's world but the drawbacks methodologies lack capability to identify suspicious activities. Other approaches, including CNNs applied to face recognition and hybrid CNN-LSTM models for behavior recognition, have some issues with recognizing efficient features of human appearance based on sequence-to-sequence temporal analysis, as well as the long-term dependencies inherent to the data. In this research, a new advanced hybrid ViT-LSTM model is developed to improve facial recognition and behavior anomaly detection to support smart security surveillance. The Vision Transformer (ViT) acquires the high-dimensional facial features with better accuracy as well as it gains the global spatial information which CNNs failed to do in large-scale scenarios. These features are processed by LSTM networks over time to identify behavioral patterns, in order to provide for a sound temporal handling of human activities. The mixed structure connects both components with the fusion layer so that multitask classification can be achieved for identity authentication and anomaly identification. The proposed model efficacy is demonstrated by training it and validating it on the benchmark dataset, which establishes increased face recognition and higher precision of behavioral anomaly detection as compared to the conventional CNN-LSTM models. Third, the system has less latency and high real-time performance to be implemented in security critical areas. This novel hybrid approach therefore presents a scalable, accurate and efficient solution for next-generation security monitoring systems. © 2025 IEEE.

关键词： Network security

来源：评论

学校读者我要写书评

暂无评论

An Automatic Machine Learning Based Customer Segmentation Model with RFM Analysis 3rd

An Automatic Machine Learning Based Customer Segmentation Mo...

引用

3rd international conference on advances in information and communication technology, ICTA 2024

作者： Xuan, Tran Thi Hoc, Nguyen Thai Thai Nguyen University of Information and Communication Technology Thai Nguyen Viet Nam

ISBN: (纸本)9783031809422

Big Data analysis has played a great role in extracting valuable insights from a vast amount of data, which can help companies make better business decisions and gain significant benefits. This paper investigates a Big Data based solution which applies the K-means clustering algorithm integrated with RFM analysis in a Spark processing pipeline for customer segmentation. Spark plays as a primary tool to deploy the entire experimentation process into a pipeline for automation, reusability, scalability, and enhanced computational power and speed for large datasets. The experimental results indicate the algorithm’s effectiveness in consumer segmentation with the proposed Big Data based model. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： K-means clustering

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：