检索结果-内蒙古大学图书馆

Design of an Efficient and Provable Secure Key Exchange Protocol for HTTP Cookies

computers, Materials & Continua 2024年第7期80卷 263-280页

作者： Waseem Akram Khalid Mahmood Hafiz Burhan ul Haq Muhammad Asif Shehzad Ashraf Chaudhry Taeshik Shon Graduate School of Engineering Science and Technology National Yunlin University of Science and TechnologyYunlin64002TaiwanChina Future Technology Research Center National Yunlin University of Science and TechnologyYunlin64002TaiwanChina Department of Computer Science Lahore Garrison UniversityLahore54920Pakistan Department of Computer Science and Information Technology College of EngineeringAbu Dhabi UniversityAbu Dhabi69911United Arab Emirates Department of Software Engineering Faculty of Engineering and ArchitectureNisantasi UniversityIstanbul34398Turkey Department of Cybersecurity Ajou UniversitySuwon16499Republic of Korea

Cookies are considered a fundamental means of web application services for authenticating various Hypertext Transfer Protocol(HTTP)requests andmaintains the states of clients’information over the *** cookies are exploited to carry client patterns observed by a *** client patterns facilitate the particular client’s future visit to the corresponding ***,security and privacy are the primary concerns owing to the value of information over public channels and the storage of client information on the *** protocols have been introduced that maintain HTTP cookies,but many of those fail to achieve the required security,or require a lot of resource *** this article,we have introduced a lightweight Elliptic Curve Cryptographic(ECC)based protocol for authenticating client and server transactions to maintain the privacy and security of HTTP *** proposed protocol uses a secret key embedded within a *** proposed protocol ismore efficient and lightweight than related protocols because of its reduced computation,storage,and communication ***,the analysis presented in this paper confirms that proposed protocol resists various known attacks.

关键词： Cookies authentication protocol impersonation attack ECC

来源：评论

学校读者我要写书评

暂无评论

Pilot study of the emotion cognition based on visual experience: A case study of roadside buildings in the Orio-Hibikino area

引用

Frontiers of Architectural Research 2024年第5期13卷 1113-1126页

作者： Satrio Agung Perwira Bart Dewancker Dimas Herjuno Faculty of Environmental Engineering The University of KitakyushuKitakyushuJapan Department of Architecture The University of KitakyushuKitakyushuJapan Graduate School of Life Science and Systems Engineering Kyushu Institute of TechnologyKitakyushuJapan

The purpose of this research is to explore how the design of buildings and spaces affects our *** study examines how our visual surroundings and emotional responses are *** hypothesis is that people’s emotions are influenced by what they see in the buildings,spaces,and furniture around *** personality type may have a unique emotional response to their *** study has three main goals:to analyze the built environment,to assess psychological well-being,and to conduct neuroscience *** built environment analysis is divided into two groups:architecture design analysis and street view design *** psychological well-being analysis identifies three key *** neuroscience analysis shows that rectangular shapes combined with linear ornamentation and calming colors create the most comforting building *** most comfortable street view includes an abundance of greenery with sun-shading *** conclusion,the study confirms that architecture affects our *** factors that contribute to our comfort are stored in our mind and body over *** mood and emotional state are influenced by what we see in our *** questionnaire and experiment results support these conclusions.

关键词： Architectural design Visual experience Person’s cognition Person’s emotion Roadside building

来源：评论

学校读者我要写书评

暂无评论

Deep Learning Approaches for Pneumonia Classification in Healthcare 3

Deep Learning Approaches for Pneumonia Classification in Hea...

引用

3rd International Conference on Innovative Practices in Technology and Management, ICIPTM 2023

作者： Sriram, G.K. Karunasagar, A. Sudharsan, R. Malini, A. Thiagarajar College of Engineering Department of Computer Science and Business Systems Madurai India

ISBN: (纸本)9798350336238

In the past two decades, there has been a sharp rise in the use of deep learning for medical image processing and analysis. Recent challenges, for instance, the most well-known ImageNet computer Vision competition, have almost entirely incorporated deep learning approaches for providing the best result. The concept of Image classification was later extended to Image Segmentation and Object Detection which proved to perform extremely well using state-of-the-art classification algorithms as their backbone architecture. The accuracy of the algorithm and approach has a significant impact on the medical field as there is a constant need for accurate and computationally efficient models. The existing object detection and segmentation approaches need large data for providing accurate results, unlike classification algorithms in which accuracy can be achieved with a relatively smaller amount of data. Hence, for the overall increase of model accuracy, there is a need for image augmentation to be incorporated. In this paper, several deep learning methodologies such as classification, object detection, ensemble, and segmentation for pneumonia classification and detection have been reviewed and an ensemble-based approach for the classification of Pneumonia using chest X-rays has been proposed. © 2023 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Layer-Wise External Attention by Well-Localized Attention Map for Efficient Deep Anomaly Detection

引用

SN computer science 2024年第5期5卷 592页

作者： Nakanishi, Keiichi Shiroma, Ryo Hayakawa, Tokihisa Katafuchi, Ryoya Tokunaga, Terumasa Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology 680-4 Kawazu Fukuoka-ken Iizuka-shi 820-8502 Japan Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology 680-4 Kawazu Fukuoka-ken Iizuka-shi 820-8502 Japan

The external attention mechanism offers a promising approach to enhance image anomaly detection (Hayakawa et al., in: IMPROVE, pp. 100-–110, 2023). Nevertheless, the effectiveness of this method is contingent upon the judicious selection of an intermediate layer with external attention. In this study, we performed a comprehensive series of experiments to clarify the mechanisms through which external attention improves detection performance. We assessed the performance of the LEA-Net (Hayakawa et al., in: IMPROVE, pp. 100–110, 2023), which implements layer-wise external attention, using MVTec AD and Plant Village datasets. The detection performances of the LEA-Net were compared with that of the baseline model under different anomaly maps generated by three unsupervised approaches. In addition, we investigated the relationship between the detection performance of LEA-Net and the selection of an attention point, which means an intermediate layer where external attention is applied. The findings reveal that the synergy between the dataset and the generated anomaly map influenced the effectiveness of the LEA-Net. For poorly localized anomaly maps, the selection of the attention point becomes a pivotal factor in determining detection efficiency. At shallow attention points, a well-localized attention map successfully notably improves the detection performance. For deeper attention points, the overall intensity of the attention map is essential;this intensity can be substantially amplified by layer-wise external attention, even for a low-intensity anomaly map. Overall, the results suggest that for layer-wise external attention, the positional attributes of anomalies hold greater significance than the overall intensity or visual appearance of the anomaly map. © The Author(s) 2024.

关键词： Anomaly detection Deep learning MVTec AD Plant science Self-attention Visual attention mechanism Visual inspection AI

来源：评论

学校读者我要写书评

暂无评论

An Unsupervised Machine Learning Approach for Heart Disease Prediction 5

An Unsupervised Machine Learning Approach for Heart Disease ...

引用

5th International Conference on Artificial Intelligence and Data sciences, AiDAS 2024

作者： Loh, Wing Son Lim, Yu Jiun Ling, Lloyd Chin, Ren Jie Lee, Chen Kang Lee, Ming Jie Universiti Tunku Abdul Rahman Department of Mathematical and Engineering Sciences Lee Kong Chian Faculty of Engineering and Science Kajang43000 Malaysia Lee Kong Chian Faculty of Engineering and Science Universiti Tunku Abdul Rahman Department of Civil Engineering Kajang43000 Malaysia Lee Kong Chian Faculty of Engineering and Science Universiti Tunku Abdul Rahman Department of Internet Engineering and Computer Science Kajang43000 Malaysia

ISBN: (纸本)9798331528553

Cardiovascular diseases (CVDs) persist as a primary cause of mortality on a global scale, necessitating effective prediction methods. This study presents a novel modelling approach utilizing the Self-Organizing Map (SOM), an unsupervised machine learning approach, for CVD prediction. The SOM model employed to analyze and cluster patient data based on intrinsic patterns without predefined labels, enabling the identification of high-risk individuals. Results demonstrated that the SOM model effectively differentiates between healthy and at-risk patients, offering a robust approach for early detection. The SOM presented to be the best predictive model for the CVD data prediction with the highest accuracy (84.44%);precision (89.13%);recall (82.00%);F1-score (85.42%). The U-Matrix of SOM as a visualization tool provided insightful representations that highlighted two discernible clusters, effectively illustrating the health status of individuals with similar health conditions concerning CVD. This facilitates a better understanding and management of CVD. The research findings suggested the potential of integrating SOM into clinical workflows, offering a potent tool for healthcare professionals in the fight against CVD. © 2024 IEEE.

关键词： Prediction models

来源：评论

学校读者我要写书评

暂无评论

Diabetes Prediction Using Machine Learning Techniques: A Case Study from Jordan 25

Diabetes Prediction Using Machine Learning Techniques: A Cas...

引用

25th International Arab Conference on Information Technology, ACIT 2024

作者： Alazaidah, Raed Batyha, Radwan Samara, Ghassan Al Henawi, Esraa Al-Safarini, Maram Y. Samhan, Ahmad A. Elrashidi, Ali Alluwaici, Mo'Ath Al-Omari, Deana It Zarqa University Department of Data Science Ai Faculty Zarqa Jordan Private University Department of Computer Science Faculty of It Applied Science Amman Jordan Zarqa University Department of Computer Science Faculty of It Zarqa Jordan Zarqa University Department of Software Engineering Faculty of It Zarqa Jordan University of Business and Technology Department of Electrical Engineering Jeddah21432 Saudi Arabia

ISBN: (纸本)9798331540012

Diabetes is one of the most common diseases in Jordan. It is the main reason of death among Jordanian adult citizens. Worldwide, 48% of all deaths are due to Diabetes occurred before the age of 70 years. Hence, this research is interested in the early prediction of this disease among Jordanian people. To achieve this main objective, Machine Learning (ML) is utilized through a large number of classification models and considering five well-known evaluation metrics. These classification models have been trained on a primary dataset that has been collected for the purpose of the research. The results revealed that BayesNet and NaiveBayes are the best classification models to handle the task of the early prediction of Diabetes in Jordan © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Latest Innovations in Intelligent Network-on-Chip Architectures: A Systematic Review 17

Latest Innovations in Intelligent Network-on-Chip Architectu...

引用

17th IEEE/ACM International Workshop on Network on Chip Architectures, NoCArc 2024

作者： Kakoulli, Elena Neapolis University Pafos Intelligent Systems Laboratory Department of Computer Science Pafos Cyprus Cyprus University of Technology Electrical Engineering and Computer Engineering and Informatics Limassol Cyprus

ISBN: (纸本)9798331506421

This review investigates the latest advancements in intelligent Network-on-Chip (NoC) architectures, focusing on innovations from 2022 to 2024. The integration of Artificial Intelligence (AI) and Machine Learning (ML) into NoC designs has driven significant improvements in performance, scalability, energy efficiency, and security. Key contributions include AI/ML-driven techniques to optimize routing, reduce latency, manage power consumption, and enhancing security against emerging threats. Despite these advancements, challenges such as computational overhead and integration complexities remain. This review consolidates these findings, addresses existing challenges, and proposes future research directions to further leverage AI and ML for developing robust and adaptable NoC architectures. © 2024 IEEE.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

The Emergence of Artificial Intelligence in Education and its Impact on Individual Literacy in Higher Education 7

The Emergence of Artificial Intelligence in Education and it...

引用

7th IEEE International Conference and Workshop Obuda on Electrical and Power engineering, CANDO-EPE 2024

作者： Farkas, Imre Kovari, Attila Rajcsanyi-Molnar, Monika Institute of Computer Engineering University of Dunaujvaros Department of Computer Systems and Control Technology Dunaujvaros Hungary Eszterházy Károly Catholic University Institute of Digital Technology Faculty of Computer Science Eger Hungary Institute of Electronics and Communication Systems Kandó Kalmán Faculty of Electrical Engineering Obuda University Budapest Hungary John Von Neumann University GAMF Faculty of Engineering and Computer Science Kecskemét Hungary Institute of Social Sciences University of Dunaujvaros Department of Economics and Management Dunaujvaros Hungary

ISBN: (纸本)9798331531119

In the last three years, a new partner has emerged for teachers and educators in the field of education. The mushrooming of applications based on large language models has greatly shaped the educational development fields of the present era. The use of various AI applications has become commonplace among students and teachers alike. Many questions are being raised by researchers in this field. What does the rapid development of AI applications bring to the field of pedagogy? Should the products of such applications be compared with human performance? The form presented in this thesis seeks to answer similar questions. What is the impact of frequent use of these applications on the literacy level of individuals? In which areas do students tend to use these applications? The results indicate that half of the students believe their literacy levels will decrease with the mass emergence of AI applications, while 36% feel it will not change. However, 88 % of students have already dealt with AI-based applications, with 64 % using them several times or more, suggesting a high level of integration into their educational processes. © 2024 IEEE.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Improved Beluga Whale Optimizer-Based Cluster Head Selection in FANET 3

Improved Beluga Whale Optimizer-Based Cluster Head Selection...

引用

3rd IEEE International Conference on Mobile Networks and Wireless Communications, ICMNWC 2023

作者： Venkatasubramanian, S. Saranathan College of Engineering Department of Computer Science and Business Systems Trichy India

ISBN: (纸本)9798350317022

Important issues have arisen for the reliability of communications in FANETs as of the high-speed mobility of unmanned aerial vehicles (UAVs). One of the more recent Meta-heuristic (MH) methods, makes use of the Beluga Whale optimizer (BWO) to optimize network parameters in FANET. However, BWO may get stuck in local optima and converge too quickly because of its lack of diversity. This paper provides two steps to improve the original BWO procedure. Opposition-based learning (OBL), also known as OBWO's first stage, helps to speed up the search procedure and improve the learning procedure so that a higher quality generation of candidate keys for the basic BWO can be selected. In addition, a powerful cluster maintenance algorithm for continually updating UAV clusters is proposed. The simulation findings show that the projected OBWO scheme outperforms state-of-the-art clustering techniques by a wide margin in terms of packet delivery ratio, network lifetime to cluster head altering ratio, and energy usage. © 2023 IEEE.

关键词： Beluga Whale Optimization Cluster Head Selection Energy Ratio Flying ad hoc network Opposition-Based Learning Packet delivery ratio

来源：评论

学校读者我要写书评

暂无评论

The Basics of Neutrosophic Simulation for Converting Random Numbers Associated with a Uniform Probability Distribution into Random Variables Follow an Exponential Distribution

引用

Neutrosophic Sets and systems 2023年 53卷 358-366页

作者： Jdid, Maissam Alhabib, Rafif Salama, A.A. Faculty of Informatics Engineering Al-Sham Private University Damascus Syria Department of Mathematical Statistics Faculty of Science Albaath University Homs Syria Department of Mathematics and Computer Science Faculty of Science Port Said University Port Said Egypt

When performing the simulation process, we encounter many systems that do not follow by their nature the uniform distribution adopted in the process of generating the random numbers necessary for the simulation process. Therefore, it was necessary to find a mechanism to convert the random numbers that follow the regular distribution over the period [0, 1] to random variables that follow the probability distribution that works on the system to be simulated. In classical logic, we use many techniques in the transformation process that results in random variables that follow irregular probability distributions. In this research, we used the inverse transformation technique, which is one of the most widely used techniques, especially for the probability distributions for which the inverse function of the cumulative distribution function can found. We applied this technique to generate neutrosophic random variables that follow an exponential distribution or a neutrosophic exponential distribution. This based on classical or neutrosophic random numbers that follow a regular distribution. We distinguished three cases according to the logic that each of the random numbers or the exponential distribution follows. We arrived at neutrosophic random variables that, when we use them in systems that operate according to an exponential distribution, such as queues and others, will provide us with a high degree of accuracy of results, and the reason for this is due to the indeterminacy provided by neutrosophic logic © 2023, Neutrosophic Sets and *** Rights Reserved.

关键词： Random variables

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：