检索结果-内蒙古大学图书馆

A New Tree Structure for Local Diagnosis

Journal of information Science and Engineering 2024年第2期40卷 231-244页

作者： Chen, Meirun Li, Xiao-Yan Lin, Cheng-Kuan Pai, Kung-Jui School of Mathematics and Statistics Xiamen University of Technology Xiamen361024 China College of Computer and Data Science Fuzhou University Fuzhou350108 China Department of Computer Science National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Undergraduate Degree Program of Systems Engineering and Technology National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Computer Science and Information Engineering Chung Cheng Institute of Technology National Defense University Taoyuan30010 Taiwan Department of Industrial Engineering and Management Ming Chi University of Technology New Taipei City243303 Taiwan

Diagnosability is an important parameter to measure the fault tolerance of a multiprocessor system. If we only care about the state of a node, instead of doing the global diagnosis, Hsu and Tan proposed the idea of local diagnosis. Chiang and Tan provided an extended star structure to diagnose a node under comparison model. In this work, we evaluate the local diagnosability better by proposing a tree structure around this node. We provide the corresponding algorithm to diagnose the node. Simulation results are presented for different failure probability of a node in the tree and different percentage of faulty nodes in the tree, showing the performance of our algorithm. © 2024 Institute of information Science. All rights reserved.

关键词： comparison model diagnosis algorithm fault diagnosis local diagnosability tree

来源：评论

学校读者我要写书评

暂无评论

Systematic Analysis of Student Academic Performance Prediction: Prediction Model, Optimization, Data Augmentation, and Educational Policy Implications

Systematic Analysis of Student Academic Performance Predicti...

引用

International Conference on information technology systems and Innovation (ICITSI)

作者： Ismail Setiawan Rahmat Gernowo Budi Warsito Department of Information System Universitas Diponegoro Semarang Indonesia Bachelor of Information Systems and Technology Program Faculty of Science and Technology Universitas ‘Aisyiyah Surakarta Surakarta Indonesia Department of Statistics Universitas Diponegoro Semarang Indonesia

ISBN: (数字)9798331511470

ISBN: (纸本)9798331511487

Predicting student academic performance is a critical challenge in higher education that aims to improve the quality of learning and optimize support for students. The main issues faced are how to choose the right prediction model, utilize optimization methods, and improve prediction accuracy. This paper presents a systematic review of the literature related to various prediction models, ranging from traditional statistical models to machine learning and ensemble/hybrid models, and discusses optimization techniques such as evolutionary algorithms. In addition, determinants of academic performance such as motivation, student engagement, and institutional support are identified as important variables in predicting learning outcomes. The datasets used, model evaluation methods, and technologies and tools that support the analysis process are also discussed in detail. The results of this review show that a hybrid approach that combines machine learning and optimization techniques is able to provide more accurate predictions compared to traditional models. This paper also highlights existing limitations, including challenges in model generalization, and provides policy recommendations to improve the effectiveness of academic performance prediction and its implementation in educational practice.

关键词： Analytical models Technological innovation Accuracy Systematics Education Optimization methods Machine learning Predictive models Data models Systematic literature review

来源：评论

学校读者我要写书评

暂无评论

Mobile Application for Elderly Care 2

Mobile Application for Elderly Care

引用

2nd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2022

作者： Jose, Fernando Livaldo Mahardhika, Mozan Hafiz Sukiman, Nathanael Adolf Warnars, Harco Leslie Hendric Spits Ramadhan, Arief Utomo, Wiranto Herry Bina Nusantara University School of Information Systems Information Systems Department Jakarta11480 Indonesia Bina Nusantara Univerisity Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia President University Faculty of Computing Department of Magister Science of Information Technology West Java17530 Indonesia

ISBN: (纸本)9781665400527

This paper discusses the design and implementation process of mobile applications used by nurses to communicate with the elderly or with people appointed to represent the elderly in using this mobile application. This mobile application is expected to help caregivers or nurses monitor the health condition of the elderly, and this mobile application has several functions that make it complete. These functions include submitting weekly reports, communicating with others via forums, and providing relevant information about the elderly and how to deal with them, including news and government regulations on elderly care. This mobile application uses case diagrams to describe business processes and class diagrams to illustrate database design. As for the implementation, android studio and MySQL database are used for database storage. This paper is limited to 9 references for literature review previous similar research by searching for publication titles with the sentences 'mobile application'+elderly+care using quotation marks and without quotation marks for the words elderly and care for all years of publication. © 2022 IEEE.

关键词： Mobile computing

来源：评论

学校读者我要写书评

暂无评论

Optimal Synergic Deep Learning for COVID-19 Classification Using Chest X-Ray Images

引用

Computers, Materials & Continua 2023年第6期75卷 5255-5270页

作者： JoséEscorcia-Gutierrez Margarita Gamarra Roosvel Soto-Diaz Safa Alsafari Ayman Yafoz Romany F.Mansour Departament of Computational Science and Electronic Universidad de la CostaCUCBarranquilla080002Colombia Biomedical Engineering Program Universidad Simón BolívarBarranquilla080002Colombia Department of Computer Science and AI Faculty of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga72511Egypt

A chest radiology scan can significantly aid the early diagnosis and management of COVID-19 since the virus attacks the *** X-ray(CXR)gained much interest after the COVID-19 outbreak thanks to its rapid imaging time,widespread availability,low cost,and *** radiological investigations,computer-aided diagnostic tools are implemented to reduce intra-and inter-observer *** lately industrialized Artificial Intelligence(AI)algorithms and radiological techniques to diagnose and classify disease is *** current study develops an automatic identification and classification model for CXR pictures using Gaussian Fil-tering based Optimized Synergic Deep Learning using Remora Optimization Algorithm(GF-OSDL-ROA).This method is inclusive of preprocessing and classification based on *** data is preprocessed using Gaussian filtering(GF)to remove any extraneous noise from the image’s ***,the OSDL model is applied to classify the CXRs under different severity levels based on CXR *** learning rate of OSDL is optimized with the help of ROA for COVID-19 diagnosis showing the novelty of the *** model,applied in this study,was validated using the COVID-19 *** experiments were conducted upon the proposed OSDL model,which achieved a classification accuracy of 99.83%,while the current Convolutional Neural Network achieved less classification accuracy,i.e.,98.14%.

关键词： Artificial intelligence chest X-ray COVID-19 optimized synergic deep learning preprocessing public health

来源：评论

学校读者我要写书评

暂无评论

On a New Rough Clustering Based on Optimization

On a New Rough Clustering Based on Optimization

引用

International Symposium on Soft Computing and Intelligent systems (SCIS)

作者： Sakuya FURUTA Yasunori ENDO Master's Program in Risk and Resilience Engineering Degree Programs in Systems and Information Engineering Graduate School of Science annd Technology University of Tsukuba Ibaraki Japan Institute of Systems and Information Engineering University of Tsukuba Ibaraki Japan

ISBN: (数字)9798350373332

ISBN: (纸本)9798350373349

The purpose of this study is to develop and investigate a new rough clustering based on optimization. We propose a restructured algorithm using only one variable, instead of the algorithm described using two variables in existing methods. We also perform numerical examples using artificial data and the Iris and Wine datasets. This research has the potential to be used as a method for determining false negatives and false positives in cancer diagnosis.

关键词： Iris Accuracy Clustering algorithms Computational complexity Optimization Cancer

来源：评论

学校读者我要写书评

暂无评论

The Analysis of Online Order Mobile Application Using User Experience Questionnaire (A Case Study Approach) 7

The Analysis of Online Order Mobile Application Using User E...

引用

7th International Conference on information Management and technology, ICIMTech 2022

作者： Hartono, Sugiarto Shahudin, Faizah Widagdo, Hermawan Honggo Hendrawan, Tommy School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia School of Economics and Management Xiamen University Malaysia Selangor Malaysia Faculty of Science & Technology Information System Study Program Universitas Nasional Karangturi Semarang50227 Indonesia PT. Elgibor Solusi Digital Semarang50167 Indonesia

ISBN: (数字)9781665450904

ISBN: (纸本)9781665450904

ABC Application is owned by ABC Company which already has branches of more than 100 stores in 7 countries where Indonesia is one of the branches with 79 stores spread across several cities, especially Jabodetabek area. ABC has launched an application that has been operating for more than a year;because the ABC application is new to the food and beverage sector, the application has received several positive and negative responses from its users especially on its user experience. Based on this background, this research will more focus on user experience of ABC Application. ABC Application can find out the assessment of user experience and improve the results of any negative responses in the form of criticism or suggestions from users. The method used in this research is the User Experience Questionnaire (UEQ). From the research results that have been carried out, the novelty scale is the scale with the lowest attachment of all respondents. Therefore, improving and developing the ABC application through this scale is necessary. © 2022 IEEE.

关键词： Surveys

来源：评论

学校读者我要写书评

暂无评论

Deep-Learning-Based Magnetic Resonance Simultaneous Multislice Imaging Using Holographic Image Decoding

Deep-Learning-Based Magnetic Resonance Simultaneous Multisli...

引用

IEEE International Conference on Image Processing

作者： Satoshi Ito Yuki Sato Naoya Endo Shohei Ouchi Electrical and Electronic Systems Engineering Graduate Program in Information Utsunomiya University Department of Innovative Electrical and Electronic Engineering National Institute of Technology Oyama

ISBN: (数字)9798350349399

ISBN: (纸本)9798350349405

We propose a new magnetic resonance simultaneous multislice imaging (SMS) by developing our previously proposed imaging method based on the principle of holography. Different amplitude modulations for each slice are applied to separate the slice images. The slice image separation is performed using a data-driven science in which U-Nets separates the slice images using the given amplitude modulation as a cue. Simulation experiments using a real-valued and an phase-varied image model revealed the relationship between the coefficients of amplitude modulation, the number of simultaneously excited slices, and image quality. In addition, we performed image separation experiments on the holographic imaging method by approximating the excited volume region as five slice images with no gaps, and showed the feasibility of image separation. This method has the potential to be a new type of SMS.

关键词： Image quality Deep learning Phase modulation Neural networks Magnetic resonance Holography Amplitude modulation

来源：评论

学校读者我要写书评

暂无评论

Air Quality Prediction Based on Air Pollution Emissions in the City Environment Using XGBoost with SMOTE 4

Air Quality Prediction Based on Air Pollution Emissions in t...

引用

4th IEEE International Conference of Computer Science and information technology, ICOSNIKOM 2022

作者： Nababan, Adli A Sutarman Zarlis, Muhammad Nababan, Erna B Universitas Sumatera Utara Faculty of Computer Science and Information Technology Department of Computer Science Medan Indonesia Universitas Sumatera Utara Faculty of Mathematics and Natural Sciences Department of Mathematics Medan Indonesia Binus Graduate Program-Master of Information Systems Management Bina Nusantara University Department of Information Systems Management Jakarta Indonesia

ISBN: (纸本)9798350399073

Air pollution makes it worse in populated regions. Indonesia's major cities are also impacted by air pollution. Due to rising traffic, material consumption by vehicles, industrial growth, land burning, and garbage collection, air quality has altered significantly. Accurate measurement and classification of air quality are required. Results of accurate classification aid in forming governmental regulations. To reach the criteria for livable air quality, we intend to manage controls. Some of the characteristics of air pollution include particulate (PM10) or PM25, sulfides (in the form of SO2), carbon monoxide (CO), ozone (O3), and nitrites (NO2). Using the XGBoost algorithm and synthetic minority oversampling (SMOTE) methods based on the Air Pollution Standard Index (ISPU) category, this study seeks to uncover factors that affect air quality. XGBoost, an ensemble machine learning approach built on a decision tree and applying a gradient reinforcement framework, is the classification algorithm in use. Air quality categorization has been tested and shown to work with the XGBoost algorithm. The dataset used in this study is air quality in 2021 which was collected by the Jakarta Environmental Ministry The proposed classification model will be evaluated using the Repeated k-fold cross-validation method for objective results. The results of the study prove that SMOTE and XGBoost have better performance than using only the XGBoost method in predicting air quality, where the overall accuracy value of SMOTE with XGBoost is 99.60%, The overall precision value is 99.60%, the overall recall value is 99.60% and the overall f1-score is 99.60% and the overall ROC AUC value is 99.96%. The overall SMOTE method with the proposed XGBoost has given better performance in air pollution prediction. © 2022 IEEE.

关键词： Air quality

来源：评论

学校读者我要写书评

暂无评论

Urgency Detection of Events Through Twitter Post: A Research Overview

Urgency Detection of Events Through Twitter Post: A Research...

引用

International Conference on Electrical Engineering and Computer Science (ICECOS)

作者： Frederick William Edlim Gregorius Edo Rangga Kurnia Putra Wiratama Riyan Mahmudin Andi Solihin Amelia Devi Putri Ariyanto Diana Purwitasari Department of Informatics Institut Teknologi Sepuluh Nopember Surabaya Indonesia Information Technology and Systems Study Program Widya Husada University Semarang Indonesia

ISBN: (数字)9798350368253

ISBN: (纸本)9798350368260

Indonesia is located in volatile Pacific fire ring and stands as one of the most global disaster-prone areas. The government and public are in constant vigilance of the potential threats. Social media generates large amounts of data from its users and is one of the prime candidates to be used as a disaster monitoring and response system. Several studies have demonstrated the effectiveness of using such an approach for developing disaster monitoring systems. but due to the number of messages generated, filtering is needed to extract useful information from the message. Hence, it's needed to detect an urgency from a message. This review, which was carried out following the PRISMA model, focused on the detection of the urgency of Indonesian Twitter during crisis events. From studies selected, several recommendations are suggested for future endeavor in this topic. Future systems are advised to employ three or four class schemes rather than binary class to gain more nuanced insights into tweet urgency. On-Event training and testing approaches are suitable for frequently occurring events, whereas out-of-event approaches offer broader applicability for real-world scenarios. Both machine learning and deep learning methods, including multimodal approaches, have demonstrated efficacy in urgency detection. Addressing pre-processing challenges, such as abbreviations and slang, is critical, and ensuring consistency in manually annotated data is essential. Additionally, the selection of appropriate word embeddings, such as fastText, IndoBERT, or crisis-specific embeddings, is crucial for achieving optimal model performance.

关键词： Training Deep learning Support vector machines Social networking (online) Disasters Blogs Data mining Synchronization Monitoring Testing

来源：评论

学校读者我要写书评

暂无评论

Quality Analysis the E-PASTI System to Determine the Condition of the System and information Quality

Quality Analysis the E-PASTI System to Determine the Conditi...

引用

2019 International Conference of Science and information technology in Smart Administration, ICSINTeSA 2019

作者： Nugraha, Bayu Marleny, Finki Dona Sfenrianto, Sfenrianto Edwina, Cinthya Information System Program Faculty of Science and Technology Sari Mulia University South Kalimantan Banjarmasin Indonesia Information Systems Management Department BINUS Graduate Program-Master of Information Systems Management Bina Nusantara University Jakarta11480 Indonesia

The purpose of this study is to evaluate the quality of secretarial, financial and staffing information systems at the Directorate General of AHU, known as the E-PASTI system. There are two variables analysed, namely system quality and information quality. Data collection using questionnaires that distributed to 123 employees who used the E-PASTI system but returned 93 questionnaires. Data quality analyst uses descriptive quantitative method. The results of the study are several conditions related to the system and information quality of E-PASTI. The quality can be a reference for the AHU Directorate General to improve the quality of E-PASTI that suits the needs of employees. © Published under licence by IOP Publishing Ltd.

关键词： Personnel

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：