检索结果-内蒙古大学图书馆

15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Roy, Sourabarna Debbarma, Tina Pal, Tannistha Duraisamy, Prakash National Institute of Technology Agartala Dept. of Computer Science and Engineering Agartala India University of Wisconsin- Green Bay Dept. of Computer Science and Engineering WI54311 United States

ISBN: (纸本)9798350370249

To detect Parkinson's disease, we compare the effectiveness of K-Nearest Neighbors (KNN), Logistic Regression (LR), Support Vector Machines (SVM), and Random Forest (RF) algorithms. Utilizing a dataset with clinical and biomedical features, we preprocess the data to handle missing values and standardize the features. Subsequently, we train each algorithm with the preprocessed data and evaluate their performance using metrics like accuracy, precision, recall, and F1-score. Our results indicate that all four algorithms achieve excellent accuracy in diagnosing Parkinson's disease, with KNN slightly outperforming the others. However, the selection of the algorithm may depend on specific needs such as interpretability and computational efficiency. Additionally, we conduct a feature importance analysis to identify the most relevant features for Parkinson's disease identification, offering insights that can aid in early diagnosis and disease management. © 2024 IEEE.

关键词： Logistic regression

来源：评论

学校读者我要写书评

暂无评论

Analysis of Arabs Publications In the Field of computer Networks 14

Analysis of Arabs Publications In the Field of Computer Netw...

引用

14th International Conference on information and Communication Systems, ICICS 2023

作者： El-Bashabsheh, Emran Younes, Mutaz Shatnawi, Mohammed Jordan University of Science and Technology Dept. of Computer Information Systems Irbid Jordan Jordan University of Science and Technology Dept. of Computer Science Irbid Jordan

ISBN: (纸本)9798350307870

Increasing technology led to increasing collaboration between the countries in general, especially the Arabic world. In recent years, many impacts affect the growth of research work in different Arabic countries. In this research, we show the growth of research work and its quality between Arabs and the rest of the world. We collected over 2500 publications and used it to create a new table that contains the intersection between each Arab country and each co-author's continent to show the relationship between each Arabic country with the rest of the world. We divided the data into two periods, before and after 2015, then we used Hue to apply our analysis on the data. We focused on the number of publications and the number of citation for each Arabic country. We noticed the rapid growth in the last period in some Arabic countries such as Jordan, Qatar, United Arab Emirates, and Saudi Arabia. In contrast, the rest of the countries had slow or decreasing growth. © 2023 IEEE.

关键词： Big data

来源：评论

学校读者我要写书评

暂无评论

EXAMSENTRY: Secure, Verify, Excel 7

EXAMSENTRY: Secure, Verify, Excel

引用

7th IEEE International Conference on Emerging Smart Computing and Informatics, ESCI 2025

作者： Bhalgat, Kushal Bawdekar, Jaee Siroya, Chirag Mandlecha, Sanjana Girme, Shital Dept. of Computer Engineering Pune Institute of Computer Technology Pune India

ISBN: (纸本)9798331515683

In today's digital world, online assessments are essential for companies to evaluate candidates effectively. However, they face challenges like malpractice and test integrity. We aim to create a scalable, secure platform that ensures fairness and reliability in online evaluations. The platform monitors the test environment by blocking browser extensions and media interference while verifying participants' identities using advanced methods. Eye tracking will ensure that candidates stay focused on the screen, while the system checks the stability of their internet connection and browser settings. Artificial intelligence will detect suspicious behavior during the exam, and cloud infrastructure will manage high user traffic for smooth performance under heavy loads. Results will be automatically generated and securely delivered to companies, providing a comprehensive solution for large-scale assessments. © 2025 IEEE.

关键词： application development in the education domain cloud-based solutions distributed systems Online assessments remote examinations scalable testing environments secure testing platforms security test proctoring

来源：评论

学校读者我要写书评

暂无评论

A Proposed Model for Machine Learning-Based Early Chronic Kidney Disease Detection 3

A Proposed Model for Machine Learning-Based Early Chronic Ki...

引用

3rd International Conference for Advancement in technology, ICONAT 2024

作者： Bhandurge, Sonam Sambrekar, Kuldeep Allagi, Shridhar Rajpurohit, Vijay S. Sannakki, Sanjeev Angadi Institute of Technology and Management Visvesvaraya Technological University Belagavi Dept. Computer Science and Engineering Karnataka Belagavi India Gogte Institute of Technology Visvesvaraya Technological University Belagavi Dept. Computer Science and Engineering Karnataka Belagavi India Kle Institute of Technology Hubli Visvesvaraya Technological University Belagavi Dept. Computer Science and Engineering India

ISBN: (纸本)9798350354171

Chronic kidney disease (CKD) is a sluggish and cumulative decline of kidney characteristics over the years. Early detection of CKD is essential when you consider that delayed detection and hospital treatment of the situation might eventually bring about the final stage of CKD and the patient's death. The prediction of diseases has grown to be appreciably impacted by means of the utilization of machine learning (ML) in healthcare. Thus, ML methods are the simplest in CKD prediction. The major goal is to use distinct supervised ML techniques, such as Support Vector Machine, Random Forest, Artificial Neural Network, and Logistic Regression, to examine and verify how correct they may be at detecting CKD. The proposed model provides various strategies for detecting CKD using medical facts which incorporates data preprocessing, strategies for handling missing values, and data reduction. It is noted that the clinical data has been classified with an overall accuracy of 100% by the Random Forest algorithm. The suggested ML model will help doctors identify chronic kidney ailments early on, which will be an effective manner of preventing the illness. © 2024 IEEE.

关键词： Support vector regression

来源：评论

学校读者我要写书评

暂无评论

Classifying wireless IOT ICU traffic with machine learning models 19

Classifying wireless IOT ICU traffic with machine learning m...

引用

19th International Conference on Future Networks and Communications, FNC 2024 / 21st International Conference on Mobile Systems and Pervasive Computing, MobiSPC 2024 / 14th International Conference on Sustainable Energy information technology, SEIT 2024

作者： Sibai, Fadi N. Sibai, Ahmad Electrical & Computer Engineering Dept. Gulf University for Science and Technology Mishref Kuwait Computer Science & Engineering Dept. University of South Florida TampaFL33620 United States

In this work, we classified the wireless internet of things (IoT) traffic of the IoT Health intensive care unit (IHI) dataset which belongs to three general classes: patient monitoring, environment monitoring, and network attack. We trained and tested 7 machine learning (ML) models with Orange 3 including kNN, Decision Tree (tree), SVM, Random Forest (RF), Neural Network (NN), Gradient Boosting (GB), and AdaBoost (AB). With the original dataset, 5 ML models performed perfect classification. After pruning the dataset columns by keeping the features with the highest correlations with the label in the dataset, good classifications were obtained with only 4 TCP/IP features by the Gradient Boosting, kNN, and RF models with MSEs in the range 0.008-0.011, and R2s in the range 0.978-0.984. With only 6 MQTT features, Gradient Boosting, RF, Tree, and NN were the top classifiers with MSEs in the range 0.073-0.074, and R2s in the range 0.856-0.859. This work demonstrates the effectiveness of guiding the feature pruning process by the values of the correlation coefficients in order to minimize the long training times of ML models while achieving good accuracies. © 2024 The Authors. Published by Elsevier B.V.

关键词： correlation coefficient feature pruning Internet of things IOT health intensive care unit dataset machine learning network security

来源：评论

学校读者我要写书评

暂无评论

Microstrip Patch Antenna for Single Resonant Frequency Using Various Types of Slots

Microstrip Patch Antenna for Single Resonant Frequency Using...

引用

2023 International Conference on Electrical, computer, Communications and Mechatronics engineering, ICECCME 2023

作者： Islam, Md Amirul Stea, Giovanni Uddin, Md Ashraf Mahmud, Sultan Rahma, Kh. Mustafizur University of Pisa Dept. of Information Engineering Pisa Italy Jagannath University Dept. of Computer Science & Engineering Dhaka Bangladesh World University of Bangladesh Dept. of Computer Science & Engineering Dhaka Bangladesh

ISBN: (纸本)9798350322972

Microstrip patch antennas are widely utilized in WLAN applications, and body-centric wireless communication relies on multiple network links to get messages through. But the existing antenna size is big with less bandwidth, which increases the cost. This paper has taken a rigorous approach to design an antenna that will provide a single resonant frequency at the targeted bandwidth (2.45GHz). The patch size in the proposed antenna is 28mm by 27mm and energized by a 50 ohm microstrip feed line with dimensions 3.137mm by 18.35mm. The dielectric substrate of permittivity Er = 4.3 is used in the fabrication process. The optimal size and other antenna characteristics are found by finite difference time domain method based CST Studio Suite. Other parameters like return loss, input impedance, and bandwidth of the microstrip patch antennas are calculated using VNA and WATS software to verify the proposed work. Finally, the proposed slot-loaded antenna attains an improved bandwidth and gain while providing a single resonant frequency. © 2023 IEEE.

关键词： Bandwidth

来源：评论

学校读者我要写书评

暂无评论

Challenges in AI-supported Process Analysis in the Italian Judicial System: what After Digitalization?

引用

Digital Government: Research and Practice 2024年第1期5卷 1-10页

作者： Bianchini, Devis Bono, Carlo Campi, Alessandro Cappiello, Cinzia Ceri, Stefano De Luzi, Francesca Mecella, Massimo Pernici, Barbara Plebani, Pierluigi Dept. of Computer Science University of Brescia Via Branze 38 Brescia25123 Italy Dept. of Electronics Information and Bioengineering Politecnico di Milano Piazza Leonardo da Vinci 32 Milan20133 Italy Dept. of Computer Control and Management Engineering Sapienza Universitá di Roma Via Ariosto 25 Roma00185 Italy

In this commentary article, we outline research challenges and possible directions for the potential applications of AI in the judicial domain by specifically considering process analysis in the Italian context. Applying AI to process analysis poses several challenges, including information extraction from legacy information systems and analysis of legal documents, process modeling with a particular emphasis on temporal analysis, real-time process monitoring, conformance and compliance checking, predictive techniques for accurate predictions, and analysis of judges' workload. Solutions to these challenges include methods and tools for data identification and collection, innovative approaches to process modeling, reactive techniques for real-time monitoring, conformance checking with explainability, language models adapted to specific domains, and the identification of suitable indicators for the analysis of case handling efficiency and case classification. Copyright © 2024 held by the owner/author(s).

关键词： Process monitoring

来源：评论

学校读者我要写书评

暂无评论

Court Ledger-Decentralized and Tamper-Proof Solution for Storing Evidence

Court Ledger-Decentralized and Tamper-Proof Solution for Sto...

引用

2023 International Conference on Recent Advances in Electrical, Electronics, Ubiquitous Communication, and Computational Intelligence, RAEEUCCI 2023

作者： Benitha Chritinal, J. Tharun Kumar, T. Yogesh, Y. Hemnath, V. Panimalar Engineering College Dept. of Information Technology Chennai India

ISBN: (纸本)9798350337426

Court Ledger is an open-source blockchain application created to modernize and protect the administration of court data. The blockchain's immutability and invulnerability are put to use here to keep court documents incorruptible and easily accessible to legitimate users. Court Ledger eliminates the need for time-consuming and prone-to-error manual record-keeping by keeping track of and updating court records in real time. Furthermore, the system protects sensitive information while allowing authorized users access to court documents. Court Ledger has the ability to completely change the way courts handle their case files by providing a streamlined, easy-to-use platform for doing so. © 2023 IEEE.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

Machine Learning Techniques for Detecting DDOS Attacks 3

Machine Learning Techniques for Detecting DDOS Attacks

引用

3rd International Conference on Emerging Smart Technologies and Applications, eSmarTA 2023

作者： Saeed, Mamoon M. Rashad Mohammed, Husam Nedhal Hazaea Gazem, Othman Abdulkafi Saeed, Rashid A. Ahmed Morei, Hossam Mohammed Thabet Eidah, Aimen Ebdulkreem Gaid, AbdulGuddoos S.A. Ameen Saif Al-Uosfi, Ameen Sami Qasem Al-Madhagi, Mohamed Galal Faculty of Engineering Department of Communications and Electronics Engineering Yemen College of Computers and Information Technology Taif University Department of Computer Engineering Taif21944 Saudi Arabia Taiz University Faculty of Engineering & Information Technology Dept. of Communication & Computer Engineering Taiz Yemen

ISBN: (纸本)9798350305333

The development witnessed by the world of science and technology and the emergence of the Internet, where cybersecurity has become one of the most important areas that are growing rapidly every day, and one of its goals is to maintain access to users at any time. Where it is noted that the biggest enemy for the availability is Distributed Denial of Service (DDoS) attack, which works to prevent access to the service and slow down the service. Through this paper, machine learning will be used to discover the DDoS attack and know its type to be aware of it and take the necessary measures for that. Where the CICDDoS2019 dataset will be used. After it is studied, analyzed, cleaned and the best algorithm was selected. Five classification algorithms (Random Forest, Decision Tree, SVM, Naive Bayes, and xgboost) were used to train and test the data from the datasets, and it can be said that of the five, Random Forest algorithms had the highest level of accuracy (99.95426%). © 2023 IEEE.

关键词： Denial-of-service attack

来源：评论

学校读者我要写书评

暂无评论

Source Localization Using a Single Array of Sensors in Nearfield Configuration, and Application to Active Noise Cancellation

Source Localization Using a Single Array of Sensors in Nearf...

引用

2024 Intermountain engineering, technology and Computing, IETC 2024

作者： Moon, Todd K. Shekaramiz, Mohammad Gunther, Jacob H. Utah State University Information Dynamics Laboratory Electrical and Computer Engineering Dept. LoganUT United States Utah State University Electrical and Computer Engineering Dept. LoganUT United States

ISBN: (纸本)9798350373073

In this paper we demonstrate by computed examples that an array of sensors in nearfield configuration can provide source localization in both x and y, going beyond the usual directional localization provided by a 1-dimensional array. This ability to localize a source opens new application areas. An application presented here is the possibility of doing active noise cancellation of the sound of a snorer. © 2024 IEEE.

关键词： Spurious signal noise

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：