检索结果-内蒙古大学图书馆

International Conference on Communications (COMM)

作者： Răzvan-Sebastian Neculai Ioana-Corina Bogdan Marian Alexandru Dan-Nicolae Robu Department of Cybersecurity Faculty of Electrical Engineering and Computer Science Transilvania University of Brasov & Eviden Braşov Romania Department of Electronics and Computers Faculty of Electrical Engineering and Computer Science Transilvania University of Brasov Braşov Romania

ISBN: (数字)9798350355956

ISBN: (纸本)9798350355963

This paper aims to implement and use the Spring Security framework to secure and authenticate the connection between a web application and the ESP32 device. In the context of a web application, by analyzing the integration of the Spring Security framework, it investigates the ways in which it manages the complex process of authentication and authorization, thus providing a secure and protected connection to an IoT device. Additionally, this study investigates the integration and use of the RTOS operating system to manage physical access in an IoT environment, in particular by implementing the opening of a door using tags. The mechanism described above leads to an additional level of security and control over physical access in an IoT ecosystem.

关键词： Operating systems System performance Authentication Solids Real-time systems Internet of Things Reliability Springs Monitoring Radiofrequency identification

来源：评论

学校读者我要写书评

暂无评论

Early Fault Detection in Rolling Element Bearings Using Signal Processing Techniques 21

Early Fault Detection in Rolling Element Bearings Using Sign...

引用

21st IEEE International Conference on Smart Communities: Improving Quality of Life using AI, Robotics and IoT, HONET 2024

作者： Saeed, Ali Akram, M. Usman Khan, Muazzam A. Afsar, M. Belal Quaid-i-Azam University ICESCO Big Data Analytics and Edge Computing Department of Computer Science Islamabad Pakistan National University of Sciences and Technology Department of Computer and Software Engineering Islamabad Pakistan Otto-von-Guericke University Faculty of Electrical Engineering and Information Technology Maddeburg Germany

ISBN: (纸本)9798350378078

Many studies show that bearings are the most vulnerable components in low-voltage motors. While advanced bearing diagnostic systems exist, their cost can be a barrier for non-critical machinery due to the potential wait time to see a return on investment. This research explores the feasibility of using basic signal processing techniques on vibration data for bearing condition monitoring. The primary goal is to analyze benchmark data from the Case Western Reserve University (CWRU) dataset and establish a baseline performance for this data-driven approach. The results suggest that, with appropriate signal processing, it's possible to achieve early detection of bearing faults, leading to more efficient time-To-fault identification with higher detection accuracies ranging from 83 % to 100 % for each method. © 2024 IEEE.

关键词： Signal modulation

来源：评论

学校读者我要写书评

暂无评论

Use of digital platforms for enhancing academic performance. Systematic Review 7

Use of digital platforms for enhancing academic performance....

引用

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

作者： Costescu, Cristina Anamaria Şogor, Mǎlina Pǎlimariu, Sabina Katona, Jozsef Tufar, Ioana Avram, Carla Maria Babe-Bolyai University Special Education Department Cluj-Napoca Romania Institute of Computer Engineering University of Dunaujvaros Department of Software Development and Application Dunaujvaros Hungary John Von Neumann University GAMF Faculty of Engineering and Computer Science Kecskemet Hungary Budapest Business University Faculty of Finance and Accountancy Department of Applied Quantitative Methods Budapest Hungary

ISBN: (纸本)9798331531119

The purpose of this study was to determine the effect of technology-based interventions on academic performance. To achieve this purpose a systematic review was conducted. Within the scope of this study EBSCO, Springer, ProQuest, science Direct, Wiley Online Library, Taylor and Francis Online, databases were scanned, and 18 studies were included in the review. Our results show that the iPad is the most preferred digital device for enhancing math and reading skills and significant results can be seen when used. Similar positive effects were observed with other technological devices, reinforcing the effectiveness of technology as a tool for supporting academic performance. This evidence underscores the value of incorporating digital devices in educational strategies, particularly for improving key academic skills. © 2024 IEEE.

关键词： academic performance children digital devices

来源：评论

学校读者我要写书评

暂无评论

A novel graph convolutional networks model for an intelligent network traffic analysis and classification

引用

International Journal of Information Technology (Singapore) 2024年 1-13页

作者： Olabanjo, Olusola Wusu, Ashiribo Aigbokhan, Edwin Olabanjo, Olufemi Afisi, Oseni Akinnuwesi, Boluwaji Department of Mathematics Morgan State University Baltimore MD United States Department of Computer Science Lagos State University Ojo Lagos Nigeria Department of Mathematics Lagos State University Ojo Lagos Nigeria Department of Computer Technology Yaba College of Technology Yaba Lagos Nigeria Department of Cybersecurity University of Derby Derby United Kingdom Department of Philosophy Lagos State University Ojo Lagos Nigeria Department of Computer Science Faculty of Science and Engineering University of Eswatini Kwaluseni Swaziland

Network security in the midst of evolving and complex cyber-attacks is a growing concern. As the complexity of network architectures grows, so does the need for advanced methods in network traffic analysis and classification. This study explores the application of a novel Graph Convolutional Networks (GCNs) to address the challenges associated with intelligent network traffic analysis. The network interactions are modeled as a graph, where nodes represent devices or IP addresses, and edges capture the communication channels between them. In this work, dataset which contains packet information of some network devices was obtained from an online repository. The data was preprocessed, normalized and label-encoded. Seven baseline models, including Feed Forward Network (FFN) were developed as reference to the proposed GCN. The parameters were tuned to optimize the performance and the dataset was split into average train-test to avoid overfitting. Two convolutional fully-connected layers were used also as more could cause oversmoothing. Performance of the novel GCN was compared with the reference models. The improved GCN model gave classification accuracy of 94.3% compared to classical GCN with 92.5% and FFN with 88%. Results also showed that the enhanced GCN proposed in this study outperformed the classical GCN and FFN in precision, recall, F1 score and area under curve metrics. Through the utilization of a GCN architecture and proposed enhancements, the proposed model demonstrates notable effectiveness in accurately classifying diverse types of network traffic. This research showed the efficacy of GCNs in intelligent network traffic analysis, offering a promising approach to augmenting cybersecurity efforts in an evolving digital landscape. © Bharati Vidyapeeth's Institute of computer Applications and Management 2024.

关键词： cybersecurity Graph convolutional networks (gcns) Intelligent classification Machine learning Network data processing Network traffic analysis

来源：评论

学校读者我要写书评

暂无评论

Arabic Sentiment Analysis of Mobile Banking Services Reviews 10

Arabic Sentiment Analysis of Mobile Banking Services Reviews

引用

10th International Conference on Social Networks Analysis, Management and Security, SNAMS 2023

作者： Khabour, Safaa M. Mustafa, Dheya Althebyan, Qutaibah Yarmouk University Faculty of Information Technology and Computer Sciences Dept. of Information Systems Irbid21163 Jordan The Hashemite University Faculty of Engineering Dept. of Computer Engineering Zarqa13133 Jordan Al Ain University Dept. of Cybersecurity Al Ain United Arab Emirates Jordan University of Science and Technology Irbid Jordan

ISBN: (纸本)9798350318906

Online customer reviews have developed into a significant source of information about a business's performance. Due to shifting consumer expectations and growing internet penetration, the Middle East, especially Jordan, is seeing an increase in the usage of online banking. This propensity toward digital transition has been accelerated by the COVID-19 pandemic. Mobile banking service companies aim to effectively use customers' feedback to identify areas for improvement in customer satisfaction. Although Arabic is becoming one of the most widely used languages on the Internet, only a few studies have focused on Arabic sentiment analysis to date. The present study conducts an extensive emotion mining and sentiment analysis on mobile banking reviews in Arabic, exploiting machine learning, natural language processing, and resampling methods to obtain subjective feedback, determine polarity, and identify customers' feelings in the banking domain. This work walks the reader through detailed steps of cleaning and preprocessing a manually annotated dataset of online banking reviews in Arabic, followed by features extraction and modeling, dataset splitting, and balancing training data. Finally, we examined classification algorithms including Decision Tree (DT), Support Vector Machine (SVM), Logistic Regression (LR), Naïve Bayes (NB), K-Nearest Neighbors (KNN), and Random Forest (RF). Ensemble hard and soft voting ML methods were also evaluated. We achieved a maximum accuracy of about 94% using the LR classifier and a maximum precision of 94% using the LR and hard voting methods. Our methodology will enable banks to acquire insights on how to develop their online presence and meet the demands of customers and stakeholders. © 2023 IEEE.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

Mobile Medical Assistant System for Laboratory Report Analysis and Medical Drug Identification 4

Mobile Medical Assistant System for Laboratory Report Analys...

引用

4th International Conference on Advancements in Computing, ICAC 2022

作者： Warnakulasuriya, Deshani Dewangi, Tharushi Sewwandi, Navodya Rathnayake, Minoli Kodagoda, Nuwan Suriyawansha, Kushanra Department of Computer Science and Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350398090

It is quite common for medical drugs and prescriptions to be misidentified by hospitals and after drugs are being dispensed to the patients. Misidentification of medical drugs is more common among elderly and visually impaired patients. In hospital organizations, the leading medical error is adverse drug events. Another most common issue patients face is keeping track of medical lab reports. Our proposed mobile medical assistant system uses image processing to identify drugs with or without packaging, identifying prescription and medical lab reports. Furthermore, the mobile application will identify the trends of medical lab reports and predict next month's results of the medical lab report of the patient using machine learning. © 2022 IEEE.

关键词： Hospitals

来源：评论

学校读者我要写书评

暂无评论

Enhancing Content-Based Histopathology Image Retrieval Using QR Code Representation

Enhancing Content-Based Histopathology Image Retrieval Using...

引用

2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023

作者： Rouzegar, Hamidreza Rahnamayan, Shahryar Bidgoli, Azam Asilian Makrehchi, Masoud Ontario Tech University Department of Electrical Computer and Software Engineering OshawaON Canada Brock University Engineering Department St. CatharinesON Canada Laurier University Faculty of Science Wilfrid WaterlooON Canada

ISBN: (纸本)9781665430654

The growing field of Content-Based Medical Image Retrieval (CBMIR) plays an integral role in the diagnosis and treatment plan of numerous diseases, including cancer. However, the effective representation of gigapixel medical images via a large number of extracted features remains a challenging task, crucially influencing other processes in a digital workflow. In this paper, we propose a novel QR code representation strategy to enhance retrieval performance. Unlike the traditional one-dimensional binary representation methods (i.e., barcodes), this 2D approach captures more intricate and informative patterns from the features by differentiating each pair of features resulting in a 2D binary vector. We delve into three distinct QR code generation strategies, namely, the Thresholding QR, the MinMax QR, and the Hybrid QR, each offering unique strengths. Our experiments on representing whole slide images of the Cancer Genome Atlas (TCGA) dataset reveal that while the Hybrid QR tends to provide balanced performance, there are instances where the other two methods outshine. Even though this approach requires more memory usage, the considerable enhancement in accuracy justifies this trade-off;obviously, in medical applications, accuracy holds the highest priority. Hence, the findings indicate that QR codes can effectively improve the performance of CBMIR systems by not only accelerating the retrieval process but also increasing the accuracy of image retrieval, leading to potentially more accurate diagnoses and treatment planning. © 2023 IEEE.

关键词： Barcode Content-Based Image Retrieval Histopathology Images Medical Image Analysis QR Code

来源：评论

学校读者我要写书评

暂无评论

Image Reconstruction Improvement of Variable Coded Aperture using Deep Learning Method for Gamma and Lensless Imaging Applications

Image Reconstruction Improvement of Variable Coded Aperture ...

引用

2023 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2023

作者： Schwarz, Ariel Shemer, Amir Danan, Eliezer Cohen, Noa E. Danan, Yossef Department of Electrical and Electronics Engineering Azrieli College of Engineering Jerusalem9103501 Israel Faculty of Engineering Bar-Ilan University Ramat-Gan5290002 Israel School of Software Engineering and Computer Science Azrieli College of Engineering Jerusalem9103501 Israel

ISBN: (纸本)9798350345995

In gamma ray imaging for nuclear medicine, coded aperture is used to improve sensitivity. one of the main reconstructing methods is inverse filtering (deconvolution), where the recorded image is cross-correlated with periodic inverse filter of coded array. The reconstruction is free of coding noise for arbitrary array. However, amplification of quantum noise affect the reconstructed image. Although it is improved by Wiener filtering, the major problem is small terms in the spectral distribution of coded masks. Statistically and experimentally pinhole arrays have at least one term which is zero, resulting unacceptably noisy reconstruction. In our previous research we presented new approach of variable coded aperture (VCA) design for far and near field imaging applications [1-4]. The imaging system is based on time multiplexing method using variable multi pinhole array. The unique variable design enables to overcome the spatial frequencies cutoff and small terms in the Fourier transform exists in static multi pinhole array. The overall pinholes positions are designed to avoid spatial frequencies loss. However, traces of duplications can still be detected in reconstruction using Wiener filtering. Furthermore, since coded aperture blocks most of the photons that enter the detector, the dynamic range of the image is limited, thus leading to low contrast image and inadequate colors gamut. © 2023 IEEE.

关键词： Quantum noise

来源：评论

学校读者我要写书评

暂无评论

Compact NSGA-II for Multi-objective Feature Selection

Compact NSGA-II for Multi-objective Feature Selection

引用

2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Miyandoab, Sevil Zanjani Rahnamayan, Shahryar Bidgoli, Azam Asilian Ontario Tech University Department of Electrical Computer and Software Engineering OshawaON Canada Brock University Department of Engineering St. CatharinesON Canada Wilfrid Laurier University Faculty of Science WaterlooON Canada

ISBN: (纸本)9798350337020

Feature selection is an expensive challenging task in machine learning and data mining aimed at removing irrelevant and redundant features. This contributes to an improvement in classification accuracy, as well as the budget and memory requirements for classification, or any other post-processing task conducted after feature selection. In this regard, we define feature selection as a multi-objective binary optimization task with the objectives of maximizing classification accuracy and minimizing the number of selected features. In order to select optimal features, we have proposed a binary Compact NSGA-II (CNSGA-II) algorithm. Compactness represents the population as a probability distribution to enhance evolutionary algorithms not only to be more memory-efficient but also to reduce the number of fitness evaluations. Instead of holding two populations during the optimization process, our proposed method uses several Probability Vectors (PVs) to generate new individuals. Each PV efficiently explores a region of the search space to find non-dominated solutions instead of generating candidate solutions from a small population as is the common approach in most evolutionary algorithms. To the best of our knowledge, this is the first compact multi-objective algorithm proposed for feature selection. The reported results for expensive optimization cases with a limited budget on five datasets show that the CNSGA-II performs more efficiently than the well-known NSGA-II method in terms of the hypervolume (HV) performance metric requiring less memory. The proposed method and experimental results are explained and analyzed in detail. © 2023 IEEE.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Expert Phishing Detection System

Expert Phishing Detection System

引用

2024 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology, IAICT 2024

作者： Alsarhan, Ayoub Al-Aiash, Issa Al-Fraihat, Dimah Aljaidi, Mohammad Abu Laila, Dena Abd Al Hakem Department of Information Technology Faculty of Prince Al-Hussein Bin Abdallah II for Information Technology The Hashemite University Zarqa13133 Jordan Department of Cybersecurity Faculty of Prince Al-Hussein Bin Abdallah II for Information Technology The Hashemite University Zarqa13133 Jordan Department of Software Engineering Faculty of Information Technology Isra University Amman11622 Jordan Department of Computer Science Faculty of Information Technology Zarqa University Zarqa13110 Jordan Department of Cyber Security Faculty of Information Technology Zarqa Technical Intermediate College Zarqa Jordan

ISBN: (纸本)9798350353464

Phishing attacks are a threat that continuously emphasizes the need for effective detection methods. This paper presents a machine learning detection method that employs a random forest classifier, which is an adaptable algorithm that can handle a variety of feature sets. The dataset used in this work offers a range of features extracted from various URLs, addressing elements such as URL length, domain structure, and keyword presence. We deployed a computational approach for feature engineering. The random forest classifier is employed for both prediction and to assess feature importance, guiding an automated feature selection process. By doing this, the model’s performance is optimized, and the most important features are utilized. The findings of this study show the effectiveness of our method with an impressive accuracy of 98.45% on a test set. The classifier exhibits balanced precision and recall for both phishing and legitimate instances. Moreover, the automated feature selection process improves the interpretation of the model, emphasizing key indicators of phishing attacks. The proposed approach not only produces outstanding outcomes but also offers a flexible and scalable approach to address the dynamically evolving threat landscape of phishing attempts. ©2024 IEEE.

关键词： Cyber-security Phishing attacks Phishing URLs

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：