检索结果-内蒙古大学图书馆

2023 International Conference on computer communication and Informatics, ICCCI 2023

作者： Chinnasamy, P. Elumalai, Anupriya Ayyasamy, Ramesh Kumar Kavya, S.P. Dhanasekaran, S. Kiran, Ajmeera MLR Institute of Technology Department of Computer Science and Engineering Hyderabad India VIT - AP University School of Computer Science and Engineering India Faculty of Information and Communication Technology Kampar Malaysia KPR Institute of Engineering and Technology Department of Artificial Intelligence and Data Science Coimbatore India Deemed to Be University Kalasalingam Academy of Research and Education Department of Information Technology Tamilnadu Srivilliputtur India

ISBN: (纸本)9798350348217

By exploiting wireless operators, contemporary bookcrossing allows people to share books conveniently and hastens the spread of knowledge. Nevertheless, the widespread use of smartphone bookcrossing has been seriously hampered by the lack of tracking, resulting in missing and disappearance of textbooks, additionally, it leads to organizational inefficiency. Hence, we suggest using the emerging blockchain technology to exploit the advantages of its immutability and encrypted smart contract in order to overcome these difficulties. In this research, we propose a BookChain, a blockchain-based intra-campus book-sharing system that is verifiable and effective. BookChain securely records all of the book's interacting entities on blockchain because every consumer could retrace the book's renting activity, hence lowering the risk of a book being misplaced. Additionally, BookChain promotes the use of smart contracts to streamline the distribution of books with very little human interference, maximizing productivity. The experimental findings demonstrate the efficiency and affordability of the suggested system even with a large number of concurrent participants. © 2023 IEEE.

关键词： Smart contract

来源：评论

学校读者我要写书评

暂无评论

Surface Sampling, Vertex Manipulation and Surface Generation Based on WebGL Technologies 7

Surface Sampling, Vertex Manipulation and Surface Generation...

引用

7th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2023

作者： Runchevski, Danail Rechkoska-Shikoska, Ustijana Salkoski, Rasim University for Information Science and Technology 'St. Paul the Apostle' Faculty of Communication Networks and Security Resen Macedonia University for Information Science and Technology 'St. Paul the Apostle' Faculty of Computer Science and Engineering Ohrid Macedonia University for Information Science and Technology 'St. Paul the Apostle' Faculty of Information Systems Visualisation Multimedia and Animation Ohrid Macedonia

ISBN: (纸本)9798350342154

Surface sampling is a powerful technique used in computer graphics and visualization to gather data from 3D surfaces. Surface sampling is a process of collecting visual and tactile information from real world surfaces to serve as references for artistic creations. It allows artists to study and analyze the intricate details of surfaces, such as the roughness of tree bark, the smoothness of a pebble, or the subtle variations in fabric patterns. By examining surfaces up close, artists gain insights into the nuances that make each surface visually and texturally distinct. The solution we've developed operates seamlessly on both desktop and mobile devices, utilizing the functionalities of widely used web browsers. It eliminates the need for any software installations. Our achievement is founded on fully open-source solutions, allowing users to explore 3D models without any barriers. © 2023 IEEE.

关键词： Web browsers

来源：评论

学校读者我要写书评

暂无评论

Text Analysis on Early Reactions to ChatGPT as a Tool for Academic Progress or Exploitation

引用

SN computer science 2024年第4期5卷 1-23页

作者： Bukar, Umar Ali Sayeed, Md Shohel Razak, Siti Fatimah Abdul Yogarayan, Sumendra Amodu, Oluwatosin Ahmed Raja Mahmood, Raja Azlina Centre for Intelligent Cloud Computing (CICC) Faculty of Information Science & amp Technology Multimedia University Jalan Ayer Keroh Lama Bukit Beruang Melaka 75450 Malaysia Department of Electrical Electronics & amp Systems Engineering Universiti Kebangsaan Malaysia (UKM) Selangor Bangi 43600 Malaysia Information and Communication Engineering Department Elizade University Ondo State Ilara-Mokin Nigeria Department of Communication Technology and Network Faculty of Computer Science and Information Technology Universiti Putra Malaysia Selangor Darul Ehsan Serdang 43400 Malaysia

Large language models (LLMs) have garnered significant attention lately, and one particular implementation that has captivated users is ChatGPT, a first-of-its kind innovation that sparks intense debates among professionals regarding its ethical boundaries, especially after it was released for public use. Some of the debates are ongoing, with several people getting more used to this tool and some losing touch with several ethical concerns. Thus, it is crucial to explore the early professional’s perspectives surrounding ChatGPT to comprehend its potential impact on the educational sector and, in particular, society in general. This research aims to address this knowledge gap by employing data mining techniques on LinkedIn to analyze ChatGPT-related discussions and provide a comprehensive textual examination. The dataset for this investigation consists of 166 records written in English by LinkedIn users discussing ChatGPT in its early stage. The study utilized VOSviewer software to clean, analyze, mine, and visualize the data. Among the sample, it was observed that 49% of the users are PhD holders, predominantly with experience in scientific research and data science fields. Hence, the findings reveal that issues such as plagiarism, references, citations, manuscripts, papers, and literature reviews stand out as the major concerns. These results suggest that while ChatGPT can contribute to academic progress by fostering new knowledge, thoughts, and ideas, it can also facilitate academic misconduct, including plagiarism and inaccurate information dissemination. Therefore, this paper also provides discussions on the implications and ethical issues of ChatGPT. In particular, it is imperative to establish clear ethical boundaries and guidelines for the appropriate use of LLMs in academic settings. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd 2024.

关键词： Academic ChatGPT Ethics LinkedIn LLMs Text analysis Visualization VOSviewer

来源：评论

学校读者我要写书评

暂无评论

Decision Transformer-Powered Traffic Control System 11

Decision Transformer-Powered Traffic Control System

引用

11th International Japan-Africa Conference on Electronics, communications, and Computations, JAC-ECC 2023

作者： Nawar, Mahmoud Saad, Abdallah Elhalawany, Basem M. Fares, Ahmed Kuwait College of Science and Technology Doha District93004 Kuwait Benha University Faculty of Engineering at Shoubra Cairo Egypt The School of Electronics E-JUST University Communication and Computer Engineering New Borg El-Arab City Egypt

ISBN: (纸本)9798350369328

Today, traffic congestion presents a real challenge in urban areas, with consequences beyond affecting commuters by increasing travel times and causing frustrating experiences. There has been consistent research using reinforcement learning methods to approach this issue. This manuscript considers a shift in this direction and proposes a novel intelligent controller based on a GPT-based decision transformer. Using transformer models will open significant opportunities for exploiting the available pre-trained transformer models. This paper prepared an offline dataset using the DQN agent and published it online, followed by training a decision transformer. The evaluation results show that the proposed method outperforms the DQN agent used for gathering the dataset;this manifests that transformers are promising in revealing knowledge that reinforcement learning agents cannot discover during their interaction with the environment. © 2023 IEEE.

关键词： Traffic congestion

来源：评论

学校读者我要写书评

暂无评论

Cephalopods Classification Using Fine Tuned Lightweight Transfer Learning Models

引用

Intelligent Automation & Soft Computing 2023年第3期35卷 3065-3079页

作者： P.Anantha Prabha G.Suchitra R.Saravanan Department of Computer Science&Engineering Sri Krishna College of TechnologyCoimbatore641042Tamil NaduIndia Department of Electronics and Communication Engineering Government College of TechnologyCoimbatore641013Tamil NaduIndia Department of Marine Pharmacology Faculty of Allied Health SciencesChettinad Academy of Research and EducationKelambakkamChengalpattu603103Tamil NaduIndia

Cephalopods identiﬁcation is a formidable task that involves hand inspection and close observation by a *** observation and iden-tiﬁcation take time and are always contingent on the involvement of experts.A system is proposed to alleviate this challenge that uses transfer learning techni-ques to classify the cephalopods *** the proposed method,only the Lightweight pre-trained networks are chosen to enable IoT in the task of cephalopod ***,the efﬁciency of the chosen models is determined by evaluating their performance and comparing theﬁ***,the models areﬁne-tuned by adding dense layers and tweaking hyperparameters to improve the classiﬁcation of *** models also employ a well-tuned Rectiﬁed Adam optimizer to increase the accuracy ***,Adam with Gradient Cen-tralisation(RAdamGC)is proposed and used inﬁne-tuned models to reduce the training *** framework enables an Internet of Things(IoT)or embedded device to perform the classiﬁcation tasks by embedding a suitable lightweight pre-trained ***ﬁne-tuned models,MobileNetV2,InceptionV3,and NASNet Mobile have achieved a classiﬁcation accuracy of 89.74%,87.12%,and 89.74%,***ﬁndings have indicated that theﬁne-tuned models can classify different kinds of *** results have also demonstrated that there is a signiﬁcant reduction in the training time with RAdamGC.

关键词： Cephalopods transfer learning lightweight models classiﬁcation deep learning ﬁsh IoT

来源：评论

学校读者我要写书评

暂无评论

An Enhanced Packet Delivery Ratio Improvement Protocol Design over 5G Assisted Wireless Sensor Network Environment 2

An Enhanced Packet Delivery Ratio Improvement Protocol Desig...

引用

2nd IEEE Global Conference on communications and Information Technologies, GCCIT 2024

作者： Balaji, T.S. Charaan, R.M.Dilip Rajalakshmi, J. Samuthira Pandi, V. Shobana, D. Priya, J. Lakshmi Srm Institute of Science and Technology Faculty of Engineering and Technology Department of Electronics and Communication Engineering Tamilnadu Chennai India Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai India S.A.Engineering College Department of Cse Tamilnadu Chennai India Chennai Institute of Technology Centre for Advanced Wireless Integrated Technology Tamil Nadu Chennai India Rajalakshmi Engineering College Department of Mechatronics Engineering Tamil Nadu Chennai India Saveetha Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350388916

Sensors are pervasive in modern life, and Wireless Sensor Networks (WSNs) will play an increasingly important role in the years to come. Broadband, energy, coverage, and route optimization resource shortages are WSN's main drawbacks. Optimizing the packet delivery ratio is a crucial aspect of wireless sensor network (WSN) architecture. In order to enhance WSNs over the long term, previous approaches used a secure zone-based routing mechanism. For packet transmission, a new criterion was developed in multi-hop communication. It was built into the routing metric to protect against flooding, message manipulation, and dropping attacks. Congestion in WSN increases and reduces packet delivery ratio, even while energy conservation and attack resilience are accomplished. Our proposed solution, Advanced Path Selection with Traffic Estimation (APSTE), is a new way of routing data packets that takes flow differentiation into account. This should help increase the packet delivery ratio and solve this issue. In order to determine how effective, the suggested method is, it is cross-validated using the standard routing model known as Link Consistency with Path Evaluation (LCPE). In order to improve the WSN's QoS parameters and extend the network's lifespan, the APSTE approach reduces the energy consumption of sensor nodes while maintaining or improving their logical throughput and packet acquisition rates. © 2024 IEEE.

关键词： 5G mobile communication systems

来源：评论

学校读者我要写书评

暂无评论

Graph Neural Networks for Resource Allocation Optimization in Healthcare Industry 2

Graph Neural Networks for Resource Allocation Optimization i...

引用

2nd International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2024

作者： Manivannan, S.K. Kavididevi, Venkatesh Muthukumaran, D. Nandhini, R. Vakula, V. Srinivasan, C. Srm Institute of Science and Technology Faculty of Management Kattankulathur Tamil Nadu Chennai India Vardhaman College of Engineering Department of Information Technology Telangana Hyderabad India Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India Rajalakshmi Institute of Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India Sri Sai Ranganathan Engineering College Department of Electronics and Communication Engineering Tamil Nadu Coimbatore India Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350368413

Optimizing the allocation of healthcare resources has never been easier than with the help of Graph Neural Networks (GNNs). In healthcare systems, where complications abound, GNNs may help with the allocation of resources in a way that improves both patient outcomes and operational efficiency. The goal is to use GNNs' graph-modelling capabilities to describe healthcare networks, with hospitals, doctors, and other medical resources acting as nodes and potential transfers of patients or shared resources as edges. Using both past and present data, the goal is to optimize resource allocation by forecasting the most effective distribution patterns. The decision-making process is improved by using important methods including attention mechanisms, message-passing algorithms, and node embeddings. The accuracy and scalability of healthcare resource management are both enhanced by GNNs, which capture spatial and temporal dynamics. The general efficacy of healthcare delivery systems is improved by this method, which permits more precise forecasts and efficient use of resources. The results highlight how GNNs can change healthcare resource allocation models. From GitHub repository data the short interfering RNAs (siRNAs) and microRNAs (miRNAs) data with efficacy is calculated. Out of the 8 data collected as samples for various siRNAs the efficacy minimum value is 0.07 and the maximum value is 0.946 and in other data samples collected it is 0.386 and 0.777. For miRNAs it is 0.934 and 0.394 and in other data sample collected it is 0.738 and 0.432. © 2024 IEEE.

关键词： Graph neural networks

来源：评论

学校读者我要写书评

暂无评论

Physics-based fuid simulation in computer graphics: Survey, research trends, and challenges

引用

Computational Visual Media 2024年第5期10卷 803-858页

作者： Xiaokun Wang Yanrui Xu Sinuo Liu Bo Ren Jiri Kosinka Alexandru C.Telea Jiamin Wang Chongming Song Jian Chang Chenfeng Li Jian Jun Zhang Xiaojuan Ban Beijing Advanced Innovation Center for Materials Genome Engineering and School of Intelligence Science and Technologyand Shunde Innovation School University of Science and Technology BeijingBeijing 100083China National Center for Computer Animation Faculty of Media and CommunicationBournemouth UniversityPoole BH125BBUK. Bernoulli Institute University of GroningenGroningen 9700 AKthe Netherlands School of Computer Science Peking UniversityBeijing 100871China. TMCC College of Computer ScienceNankai UniversityTianjin 300350China Department of Information and Computing Sciences Utrecht UniversityUtrecht 3584 CCthe Netherlands. Zienkiewicz Institute for Modelling Data and AISwansea UniversitySwansea SA18ENUK. Institute of Materials Intelligent Technology Liaoning Academy of MaterialsShenyang 110004China.

Physics-based fluid simulation has played an increasingly important role in the computer graphics *** methods in this area have greatly improved the generation of complex visual effects and its computational *** techniques have emerged to deal with complex boundaries,multiphase fluids,gas-liquid interfaces,and fine *** parallel use of machine learning,image processing,and fluid control technologies has brought many interesting and novel research *** this survey,we provide an introduction to theoretical concepts underpinning physics-based fuid simulation and their practical implementation,with the aim for it to serve as a guide for both newcomers and seasoned researchers to explore the field of physics-based fuid simulation,with a focus on developments in the last *** by the distribution of recent publications in the field,we structure our survey to cover physical background;discretization approaches;computational methods that address scalability;fuid interactions with other materials and interfaces;and methods for expressive aspects of surface detail and *** a practical perspective,we give an overview of existing implementations available for the above methods.

关键词： computer graphics physical simulation fluid simulation fluid coupling

来源：评论

学校读者我要写书评

暂无评论

Surveillance and Intruder Detection using Pyramid Vision Transformer You Only Look Once Enhanced with Gradient Weighted Class Activation Mapping 4

Surveillance and Intruder Detection using Pyramid Vision Tra...

引用

4th IEEE International Conference on Mobile Networks and Wireless communications, ICMNWC 2024

作者： Arunachalam, Sripriya Almusawi, Muntather Rafikiran, Shaik. Sivagami, S. Praveena, Hirald Dwaraka Srm Institute of Science and Technology Faculty of Science and Humanities Department of Computer Science and Applications Vadapalani City Campus Chennai India College of Technical Engineering The Islamic University of Al Diwaniyah Department of Computers Techniques Engineering Al Diwaniyah Iraq Sri Venkateswara College of Engineering Department of Electrical & Electronics Engineering Tirupati India New Prince Shri Bhavani College of Engineering and Technology Department of Chemistry Chennai India Department of Electronics and Communication Engineering Tirupati India

ISBN: (纸本)9798350352931

In this era, wireless networks are economically feasible and flexible to establish in healthcare, defense, surveillance, and traffic monitoring, fire detection. Effective intruder detection systems utilize advanced technologies like Artificial Intelligence (AI), sensors, and cameras. Traditional approaches for surveillance and intruder detection had faced several challenges which include false alarms, high costs, privacy concerns, and vulnerabilities. To overcome these challenges, a Gradient-weighted Class Activation Mapping (Grad CAM) with Pyramid Vision Transformer-You Only Look Once Enhanced (PViT-YOLOE) namely GRADCAM-PViT-YOLOE is proposed to detect intruders in public places using images and videos. For preprocessing, noise reduction, image resizing, and image segmentation are considered to reduce false positives, enhance memory efficiency, and to reduce complexity. Then, PViT-YOLOE is considered for feature extraction to enhance detection of small objects, enhance robustness to variations. At last, Grad CAM is employed as classifier to detect intruders in public places with improved interpretability, robustness to noise, and flexibility. The results demonstrate the efficacy of the proposed GRADCAM-PViT-YOLOE in terms of accuracy (99.25%), precision (96.75%) recall (89.82%) and F1-Score (87.92%) when compared to the existing method like Faster Regions Convolutional Neural Networks (FR-CNN). © 2024 IEEE.

关键词： Noise abatement

来源：评论

学校读者我要写书评

暂无评论

An Innovative IoT-Driven Smart Streetlight Management System Design 2

An Innovative IoT-Driven Smart Streetlight Management System...

引用

2nd International Conference Computational and Characterization Techniques in engineering and sciences, IC3TES 2024

作者： Shermina Justin, Shekaina Thenmozhi, P. George, Jissy Ann Kumar, T. Ananth Ananth, Christo Muscat College Department of Computing Oman Princess Nourah Bint Abdulrahman University Electrical Engineering Department Saudi Arabia Dept. of Electronics and Communication Engineering Chennai600119 India British University of Bahrain College of Ict Bahrain Ifet College of Engineering Computer Science and Engineering Viluppuram India Samarkand State University Uzbekistan Adjunct Faculty Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Chennai India

ISBN: (纸本)9798350364699

This research introduces a cutting-edge approach to optimizing the management of streetlight systems through automation by using IoT. Traditional methods often suffer from inefficiencies, leading to unnecessary energy consumption and maintenance costs. In this study, we propose a novel automated streetlight management system that leverages advanced technologies such as IoT sensors, machine learning algorithms, and smart scheduling mechanisms. By dynamically adjusting lighting levels based on real-time factors such as traffic density, weather conditions, and time of day, our system aims to achieve significant energy savings while ensuring optimal illumination for pedestrians and vehicles. We present the design architecture of our system, along with experimental results demonstrating its effectiveness in various urban environments. Our findings highlight the potential of automated streetlight management systems to enhance sustainability, improve safety, and reduce operational expenses for municipalities and urban planners. © 2024 IEEE.

关键词： Energy utilization

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：