检索结果-内蒙古大学图书馆

8th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2024

作者： Kushnerov, Oleksandr Murr, Pierre Herasymov, Serhii Milevskyi, Stanislav Melnyk, Marharyta Golovashych, Sergii Sumy State University Department of Economic Cybernetics Sumy Ukraine International University of Science and Technology in Kuwait Computer Engineering Department Kuwait Kuwait 'Kharkiv polytechnic institute' Cybersecurity department National Technical University Kharkiv Ukraine Set University Department of Cyber Security and information protection Kyiv Ukraine National Technical University 'Kharkiv polytechnic institute' Department of Software Engineering and Management Intelligent Technologies Kharkiv Ukraine

ISBN: (纸本)9798350354423

Monitoring and analyzing network traffic are critically important tasks in the context of increasing cyber threats. Traditional data processing methods often struggle to handle the large volumes and complexity of modern network traffic, necessitating the use of advanced technologies such as neural networks and machine learning. This article demonstrates the application of neural networks for monitoring and analyzing network traffic, highlighting their ability to learn from large datasets to detect complex patterns and anomalies. Using TensorFlow, we developed a neural network model based on an autoencoder that effectively identifies and classifies anomalies in network traffic. The model's effectiveness was validated using a synthetic dataset from Kaggle, showing high accuracy on both training and testing data. Our approach significantly improves the efficiency and accuracy of threat detection compared to traditional methods, making it a valuable tool for enhancing cybersecurity. © 2024 IEEE.

关键词： Cyber attacks

来源：评论

学校读者我要写书评

暂无评论

CDNet: Cross-frequency Dual-branch Network for Face Anti-Spoofing

CDNet: Cross-frequency Dual-branch Network for Face Anti-Spo...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： Xiaobin Huang Qiufu Li Linlin Shen Xingwei Chen Computer Vision Institute School of Computer Science and Software Engineering. Shenzhen University Shenzhen Huafu Information Technology Co Ltd

Face anti-spoofing (FAS) defends the facial image recognition systems against the spoof attacks. While the imperceptible spoof cues in the facial images are usually represented in the images' high-frequency components, existing methods do not fully explore them. In this paper, we introduce wavelet into face anti-spoofing and propose a Cross-frequency Dual-branch network (CDNet), which mainly contains two frequency branches to explore spoof cues from the input facial images' high- and low-frequency components generated by wavelet transforms. In CDNet, we design Frequency Attention Module (FAM) to fuse different internal frequency features learned by two frequency branches, and propose a Complementary Learning Module (CLM) to aggregate the two final frequency features. In addition, we present a resolution-aware Binary Cross-Entropy Loss to balance the training samples with different resolutions. We conduct comprehensive experiments on four datasets, and the results shows that our CDNet performs better than the previous state-of-the-art methods on both intra- and inter-dataset testing.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Web Application to predict Skin Disease: An Approach Using Deep Learning Algorithm

Web Application to predict Skin Disease: An Approach Using D...

引用

Human-computer Interaction, Optimization and Robotic Applications (HORA), International Congress on

作者： Eelanila Thayalan Ayingaran Arumugavel Sharujan Ganeshan Makenthiran Dalaxshan Harinda Fernando Kaushalya Rajapakse Department of Information Technology Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Computer Systems Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Computer Science and Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (数字)9798350394634

ISBN: (纸本)9798350394641

The Disease Prediction System revolutionizes healthcare with advanced machine learning techniques for early detection of skin diseases, notably focusing on skin cancer. Through image processing and Transfer Learning, it excels in identifying potential malignancies, enabling timely interventions. Its capabilities extend to benign tumors and growth disorders, utilizing the ResNet50 Model for precise identification. Additionally, it predicts skin reactions associated with various dermatological conditions, such as Urticaria Hives and Warts, leveraging the efficientnetB0 Model. Integration of the VGG16 Model enhances diagnostic accuracy for inflammatory skin conditions. This holistic approach prioritizes patient-centric care, leveraging diverse datasets and intricate pattern recognition in medical images. The system’s proactive nature embodies personalized solutions for early detection, timely intervention, and improved patient outcomes. Its versatility and accuracy underscore itstransformative potential in healthcare delivery. By harnessing diverse datasets and recognizing intricate patterns within medical images, it heralds a new era of personalized healthcare solutions. In essence, the Disease Prediction System exemplifies the transformative potential of machine learning in healthcare, ensuring the highest standards of diagnostic accuracy and efficacy, while prioritizing patient well-being and quality oflife.

关键词： Transfer learning Medical services Skin Pattern recognition Medical diagnostic imaging Standards Robots

来源：评论

学校读者我要写书评

暂无评论

Smart Expiry Tracker and Product Recommender using Google ML Kit OCR Engine 2

Smart Expiry Tracker and Product Recommender using Google ML...

引用

2nd International Conference on Computational Intelligence and Network Systems, CINS 2024

作者： Krishanamurthy, Vallidevi Kurumthottam, Aleena Bosco Ali, Shireen Aliza Anandan, Paul Danny Kavitha, Muthu Subash Karthikeyan, K. Kumaresh, V. Manikandan, S. School of Computer Science and Engineering Vellore Institute of Technology Chennai India School of Mechanical Electrical and Manufacturing Engineering Loughborough University United Kingdom School of Information and Data Sciences Nagasaki University Japan Senior Data Analyst Ninjacart Bangalore India Software Development Engineer Vegrow Chennai India iOS App Developer Facilio Chennai India

ISBN: (纸本)9798331504106

Expiration dates play a crucial role in both personal and business contexts, influencing everything from health management to operational efficiency. Track Expiry Dates (TED) is a comprehensive mobile application designed to address two key needs: document management and expiry tracking. We designed a secure app which offers users to store personal documents such as driving licenses, passports, general documents, product warranty cards, and bills, ensuring that critical information is readily accessible and safeguarded against loss or damage. The proposed system provides a seamless and efficient solution for tracking expiry dates and storing essential documents such as Aadhar cards and PAN cards. It automatically sends reminders to users and their nominated family members prior to document expiration, ensuring timely renewals. From a business perspective, the platform enables companies to leverage data from uploaded documents to offer targeted, content-driven recommendations for products and brands. With its intuitive user interface and robust back-end infrastructure, the app delivers a comprehensive system for document management and expiry tracking, effectively meeting the diverse requirements of both individual users and businesses. ©2024 IEEE.

关键词： Driver licensing

来源：评论

学校读者我要写书评

暂无评论

AI Integration in the IT Professional Workplace: A Scoping Review and Interview Study with Implications for Education and Professional Competencies 2024

AI Integration in the IT Professional Workplace: A Scoping R...

引用

29th Working Group Reports on Innovation and Technology in computer science Education, ITiCSE WGR 2024

作者： Clear, Tony Cajander, Åsa Clear, Alison Mcdermott, Roger Daniels, Mats Divitini, Monica Forshaw, Matthew Humble, Niklas Kasinidou, Maria Kleanthous, Styliani Kultur, Can Parvini, Ghazaleh Polash, Mohammad Zhu, Tingting Department of Computer Science and Software Engineering Auckland University of Technology Auckland New Zealand Department of Information Technology Uppsala University Uppsala Sweden School of Business Eastern Institute of Technology Auckland New Zealand School of Computing Robert Gordon University Aberdeen United Kingdom Dpt. of Computer Science Norwegian University of Science and Technology Trondheim Norway The Alan Turing Institute Newcastle Upon Tyne United Kingdom Open University of Cyprus Nicosia Cyprus The Open University of Cyprus Nicosia Cyprus School of Computer Science Carnegie Mellon University PittsburghPA United States Manning College of Information and Computer Sciences University of Massachusetts Amherst Amherst United States School of Computer Science University of Sydney Sydney Australia Department of Geography Geomatics and Environment University of Toronto Mississauga Toronto Canada School of Computer Science Newcastle University Newcastle upon Tyne United Kingdom

ISBN: (纸本)9798400712081

As Artificial Intelligence (AI) continues transforming workplaces globally, particularly within the information Technology (IT) industry, understanding its impact on IT professionals and computing curricula is crucial. This research builds on joint work from two countries, addressing concerns about AI's increasing influence in IT sector workplaces and its implications for tertiary education. The study focuses on AI technologies such as generative AI (GenAI) and large language models (LLMs). It examines how they are perceived and adopted and their effects on workplace dynamics, task allocation, and human-system interaction. IT professionals, noted as early adopters of AI, offer valuable insights into the interplay between AI and work engagement, highlighting the significant competencies required for digital workplaces. This study employs a dual-method approach, combining a systematic and multi-vocal literature review and qualitative research methods. These included a thematic analysis of a set of 47 interviews conducted between March and May of 2024 with IT professionals in two countries (New Zealand and Sweden). The research aimed to understand the implications for computing students, education curricula, and the assessment of emerging professional competencies. The literature review found insufficient evidence addressing comprehensive AI practice methodologies, highlighting the need to both develop and regulate professional competencies for effective AI integration. Key interview findings revealed diverse levels of GenAI adoption, ranging from individual experimentation to institutional integration. Participants generally expressed positive attitudes toward the technology and were actively pursuing self-learning despite some concerns. The themes emerging from the interviews included AI's role in augmenting human tasks, privacy and security concerns, productivity enhancements, legal and ethical challenges, and the evolving need for new competencies in the workplace.

关键词： artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

Intelligent Gen: An Efficient On-Demand Access Protocol in MANETs using Network Simulator - 2 18

Intelligent Gen: An Efficient On-Demand Access Protocol in M...

引用

18th INDIAcom;11th International Conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Ganesan, T. Murali, N. Murugan, S. Palani Peter, M. Chandrakumar Raj, P. Anand Manikandan, S. E.G.S. Pillay Engineering College Department of Computer Science and Engineering Tamil Nadu Nagapattinam India E.G.S. Pillay Engineering College Department of Artificial Intelligence & Data Science Tamil Nadu Nagapattinam India Periyar Maniammai Institute of Science & Technology Department of Software Engineering Tamil Nadu Thanjavur India E.G.S. Pillay Engineering College Department of Computer Science and Business Systems Tamil Nadu Nagapattinam India E.G.S. Pillay Engineering College Department of Information Technology Tamil Nadu Nagapattinam India

ISBN: (纸本)9789380544519

Mobile Ad-Hoc network is a self-configuring and multi-hop collection of mobile devices for making successful communication. The wireless and mobile communication process are encountered based on bandwidth, process control and energy conception. Energy conception is considered and dynamically changed to rely on life time of batteries and power. The life time of battery get exhausted very quickly the nodes are moved and changed rapidly across the network. This paper noticed the problem of life time of power, batteries and energy consumption problem in various routing stages. The proposed Intelligent Gen Algorithm is used to get optimal solution for ensuring high robustness, flexibility and Energy consumption factor. It presents a common framework to balance various routing requirements in MANETs dynamically. The following are the main contributions includes, i. introducing Intelligent GEN Algorithms to classify the throughout bandwidth, delay, data ratio. ii. Various routing performance are evaluated and viewed by speed, packetize and simulation time. The comparison evaluated by select routing algorithm using NS-2. The simulation results are recorded and the performance is monitored by using on demand access protocl. The result clearly demonstrated the proposed Intelligent Gen algorithm used in self-organized manner by wireless channel. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： AOMDV Protocol Intelligent Gen Algorithm MANET Network Simulator NS-2

来源：评论

学校读者我要写书评

暂无评论

An LWE-Based Multi-Key Privacy-Preserving Distributed Deep Learning∗ 23

An LWE-Based Multi-Key Privacy-Preserving Distributed Deep L...

引用

23rd IEEE International Conference on High Performance Computing and Communications, 7th IEEE International Conference on Data science and Systems, 19th IEEE International Conference on Smart City and 7th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Antwi-Boasiako, Emmanuel Zhou, Shijie Liao, Yongjian Danso, Ebenezer Kwaku School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China Ghana Institute of Management and Public Administration Computer Science Department Accra Ghana China University for Development Studies Ghana

ISBN: (纸本)9781665494571

Privacy preservation in distributed deep learning (DDL) has received a lot of attention recently. One key approach to preserving privacy for DDL is the use of Homomorphic Encryption (HE), which allows computation on ciphertexts without decryption. Although current applications of HE provide some level of privacy to DDL, they are not post-quantum resistant and multi-key compliant. The use of same key by all participants could lead to collusion attacks and possible leakage of sensitive information from a participant's local dataset in the distributed deep learning setting. Furthermore, most of the privacy solutions provided for the DDL assume that all learning participants must be present before the start of the protocol. Hence, such solutions do not allow a new participant to benefit from the utility of the joint learning of other participants, for which it was not present. To address the above problems, we propose a new privacy preserving solution for DDL that uses an LWE-based Multi-key approach. Our proposed privacy preserving DDL solution is multi-key compliant, post-quantum resistant and has an additional property of allowing a new participant to benefit from the utility of an already trained collaborative deep learning system. We prove that our privacy-preserving distributed deep learning system is secured. We note that our proposed solution generally provides a robust privacy-preserving solution for the DDL and at the same time has great potential to reduce communication and computation costs associated with similar systems. © 2021 IEEE.

关键词： Deep learning Resistance Privacy Protocols Costs Collaboration Cryptography

来源：评论

学校读者我要写书评

暂无评论

Blockchain and PUF-based secure key establishment protocol for cross-domain digital twins in industrial Internet of Things architecture

引用

Journal of Advanced Research 2024年 62卷 155-163页

作者： Mahmood, Khalid Shamshad, Salman Saleem, Muhammad Asad Kharel, Rupak Das, Ashok Kumar Shetty, Sachin Rodrigues, Joel J.P.C. School of Psychology and Computer Science University of Central Lancashire Preston United Kingdom Graduate School of Intelligent Data Science National Yunlin University of Science and Technology Yunlin 64002 Taiwan Department of Software Engineering The University of Lahore Lahore 54590 Pakistan Department of Computer Science University of Sahiwal Punjab Sahiwal 57000 Pakistan Center for Security Theory and Algorithmic Research International Institute of Information Technology Hyderabad 500 032 India Department of Modeling Simulation and Visualization Engineering Virginia Modeling Analysis and Simulation Center and Center for Cybersecurity Education and Research Old Dominion University Suffolk 23435 VA United States COPELABS Lusófona University Campo Grande 376 Lisbon 1749-024 Portugal

Introduction: The Industrial Internet of Things (IIoT) is a technology that connects devices to collect data and conduct in-depth analysis to provide value-added services to industries. The integration of the physical and digital domains is crucial for unlocking the full potential of the IIoT, and digital twins can facilitate this integration by providing a virtual representation of real-world entities. Objectives: By combining digital twins with the IIoT, industries can simulate, predict, and control physical behaviors, enabling them to achieve broader value and support industry 4.0 and 5.0. Constituents of cooperative IIoT domains tend to interact and collaborate during their complicated operations. Methods: To secure such interaction and collaborations, we introduce a blockchain-based cross-domain authentication protocol for IIoT. The blockchain maintains only each domain's dynamic accumulator, which accumulates crucial materials derived from devices, decreasing the overhead. In addition, we use the on-chain accumulator to effectively validate the unlinkable identities of cross-domain IIoT devices. Results: The implementation of the concept reveals the fact that our protocol is efficient and reliable. This efficiency and reliability of our protocol is also substantiated through comparison with state-of-the-art literature. In contrast to related protocols, our protocol exhibits a minimum 22.67% increase in computation cost efficiency and a 16.35% rise in communication cost efficiency. Conclusion: The developed protocol guarantees data transfer security across the domain and thwarts IoT devices from potential physical attacks. Additionally, in order to protect privacy, anonymity and unlinkability are also guaranteed. © 2024

关键词： Digital twins Industrial Internet of Things (IIoT) Key agreement Mutual authentication Physically Unclonable Functions (PUFs)

来源：评论

学校读者我要写书评

暂无评论

A Real-time Cutting Model Based on Finite Element and Order Reduction

引用

computer Systems science & engineering 2022年第10期43卷 1-15页

作者： Xiaorui Zhang Wenzheng Zhang Wei Sun Hailun Wu Aiguo Song Sunil Kumar Jha Wuxi Research Institute Nanjing University of Information Science&TechnologyWuxi214100China Engineering Research Center of Digital Forensics Ministry of EducationJiangsu Engineering Center of Network MonitoringSchool of Computer and SoftwareNanjing University of Information Science&TechnologyNanjing210044China School of Automation Nanjing University of Information Science&TechnologyNanjing210044China State Key Laboratory of Bioelectronics Jiangsu Key Lab of Remote Measurement and ControlSchool of Instrument Science and EngineeringSoutheast UniversityNanjing210096China IT Fundamentals and Education Technologies Applications University of Information Technology and Management in RzeszowRzeszow Voivodeship100031Poland

Telemedicine plays an important role in Corona Virus Disease 2019(COVID-19).The virtual surgery simulation system,as a key component in telemedicine,requires to compute in ***,this paper proposes a realtime cutting model based on finite element and order reduction method,which improves the computational speed and ensure the real-time *** proposed model uses the finite element model to construct a deformation model of the virtual ***,a model order reduction method combining proper orthogonal decomposition and Galerkin projection is employed to reduce the amount of deformation *** addition,the cutting path is formed according to the collision intersection position of the surgical instrument and the lesion area of the virtual ***,the Bezier curve is adopted to draw the incision outline after the virtual lung has been ***,the simulation system is set up on the PHANTOM OMNI force haptic feedback device to realize the cutting simulation of the virtual *** results show that the proposed model can enhance the real-time performance of telemedicine,reduce the complexity of the cutting simulation and make the incision smoother and more natural.

关键词： Virtual surgery cutting model finite element model model order reduction Bezier curve

来源：评论

学校读者我要写书评

暂无评论

Energy Efficiency Optimization for UAV-Assisted Cellular Networks: A Periodic Clustering-Based MATD3 Approach

Energy Efficiency Optimization for UAV-Assisted Cellular Net...

引用

2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Liu, Fuhao Chen, Haoqiang Miao, Jiansong Zhang, Tao Zhang, Chuan Kang, Jiawen Niyato, Dusit Beijing University of Posts and Telecommunications School of Information and Communication Engineering Beijing China Beijing Smartchip Microelectronics Technology Company Limited Beijing China Beijing Jiaotong University School of Software Engineering Beijing China Beijing Institute of Technology School of Cyberspace Science and Technology Beijing China Guangdong University of Technology School of Automation Guangzhou China Nanyang Technological University School of Computer Science and Engineering Singapore Singapore

ISBN: (纸本)9798350351255

With the advancement of unmanned aerial vehicles (UAVs) technology, UAV-assisted cellular networks (UACNs) have emerged as a new communication paradigm aimed at enhancing the coverage and capacity of ground networks. Unfortunately, the limited energy capacity of UAVs significantly restricts their operational duration, so optimizing energy efficiency is of importance. However, existing optimization schemes often overlook the impact of ground user mobility on user association, lacking ability to achieve optimal energy efficiency. In this paper, the K-Means method is applied to optimize user association by periodically clustering users. Additionally, given the dynamic nature of the wireless channels, we utilize the Multi-Agent Twin Delayed Deep Deterministic Policy Gradient (MATD3) approach to jointly optimize 3D trajectory and power allocation. The objective is to maximize the sum energy efficiency while meeting the constraints included maximum power, minimum achievable data rate and spatial limitation. Simulation results demonstrate the effectiveness of the proposed algorithm compared with other benchmark algorithms. © 2024 IEEE.

关键词： Mobile telecommunication systems

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：