检索结果-内蒙古大学图书馆

13th IEEE Symposium on Computer Applications and Industrial Electronics, ISCAIE 2023

作者： Wandy, Wandy Adi, Kusworo Ayu, Media Anugerah Diponegoro University Doctoral Program of Information Systems School of Postgraduate Studies Semarang Indonesia Diponegoro University Faculty of Science and Mathematics Department of Physics Semarang Indonesia Sampoerna University Faculty of Engineering and Technology Department of Computer Science South Jakarta Indonesia

ISBN: (纸本)9798350347319

Sports Science is an interdisciplinary and multidisciplinary science that strives to increase athletic performance and endurance. Sport Science recognizes and prevents injuries. Sensors and statistics formalize Sports Science. Runners need coaches and teams to support them before, during, and after the run race. Coaches generate running training plans to boost performance. Running race performances may be impacted by air pollution exposure while training, so coaches should consider limiting air pollution exposure when training. One of the external factors is Particulate Matter (PM2.5 and PM10). Sensors connecting to the Internet can record external factors and produce csv data. The foundation of supervised machine learning is the labeling process. Labeling a set of data is one of the laborious and time-consuming phases in every machine-learning application because it requires verifying the accuracy of the labels and making any necessary revisions. This research aimed to find a solution to automatically label numerous air particulate matter raw data using a rule based on parameters to reduce manual work, human errors and faster processes. This labeled data will later be used for supervised machine learning classification to support the coach in generating training programs for the runners in a Sports information System. Based on Indonesia Air Quality index rule-based approach, labeled text data in csv has been generated and tested with PM2.5 and PM10 parameters in three scenarios with a 100% success rate. It was possible to automate the labeling process, and it explained how automation results in fast and accurate results. © 2023 IEEE.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

Application of text mining techniques to identify actual wrong-way driving (WWD) crashes in police reports

引用

International Journal of Transportation Science and Technology 2023年第4期12卷 1038-1051页

作者： Parisa Hosseini Seyedalireza Khoshsirat Mohammad Jalayer Subasish Das Huaguo Zhou Department of Civil and Environmental Engineering Center for Research and Education in Advanced Transportation Engineering Systems(CREATEs)Rowan University201 Mullica Hill RoadGlassboroNJ 08028USA Department of Computer&Information Sciences University of Delaware18 Amstel AveNewarkDE 19716USA Civil Engineering Program Ingram School of EngineeringTexas State UniversityRFM 5202601 University DriveSan MarcosTX 78666USA Harbert Center Department of Civil and Environmental EngineeringAuburn UniversityAuburnAL 36849USA

Wrong-way driving(WWD)has been a long-lasting issue for transportation agencies and law enforcement,since it causes pivotal threats to road *** being rare,crashes occurring due to WWD are more severe than other types of *** order to analyze WWD crashes,there is a need to obtain WWD incidents or crash ***,it is time-consuming to identify actual WWD crashes from potential WWD crashes in large crash *** often involves large man-hours to review hardcopy of crash narratives in the police ***,it may cause an overestimation or underestimation of WWD crash *** fill this gap,the present study,as the first-of-its-kind,aims at identifying actual WWD crashes from potential WWD crashes in police reports by using machine learning ***,Bidirectional Encoder Representations from Transformers(BERT)models have shown promising results in natural language *** this study,we implemented the BERT model as well as five conventional classification algorithms,including Naïve Bayes(NB),Support Vector Machine(SVM),Decision Tree(DT),Random Forest(RF),and Single Layer Perceptron(SLP)to classify crash report narratives as actual WWD and non-WWD ***-validation and different performance metrics were used to evaluate the performance of each classification *** indicated that the BERT model outperformed in identifying actual WWD crashes in comparison with other algorithms with an accuracy of 81.59%.The BERT classification algorithm can be implemented to reduce the time needed to identify actual WWD crashes from crash report narratives.

关键词： Wrong-Way Driving Crashes Crash Report Narratives Text Mining Text Classification

来源：评论

学校读者我要写书评

暂无评论

Metaverse for Public Welfare and the United Nations Sustainable Development Goals

Metaverse for Public Welfare and the United Nations Sustaina...

引用

Cloud Computing, Big Data and Internet of Things (3CBIT), International Conference on

作者： Amjad Umar Information Systems Engineering & Management Program Harrisburg University Harrisburg USA

ISBN: (纸本)9781665492263

Metaverse is extremely popular at present in the gaming industry but can it accelerate the advancement of public services as defined by the United Nations Sustainable Development Goals (UN SDGs)? In particular, can metaverse provide any value to developing nations and how can the challenges and risks introduced by the metaverse be addressed through govrnment regulations and policies? This paper presents a systematic analysis of metaverse and utilizes the United Nations SDGs as a metric to explore public welfare aspects of metaverse. A digital transformation Lab is presented for rapid deployment and experimentation with metaverse.

关键词： Measurement Industries Systematics Metaverse Digital transformation Urban areas Developing countries

来源：评论

学校读者我要写书评

暂无评论

Mean-variance and Safety-first Portfolio Selection Strategy for High-volume/High-value Traded Stocks in Philippine Stock Exchange (PSE)

Mean-variance and Safety-first Portfolio Selection Strategy ...

引用

2024 IEEE International Conference on Industrial engineering and engineering Management, IEEM 2024

作者： De Guzman, T.C. Young, M.N. Prasetyo, Y.T. Persada, S.F. Nadilfatin, R. School of Graduate Studies Mapua University Manila Philippines School of Industrial Engineering and Engineering Management Mapua University Manila Philippines Department of Industrial Engineering and Management Yuan Ze University Taoyuan City Taiwan International Bachelor Program in Engineering Yuan Ze University Taoyuan City Taiwan Entrepreneurship Business Creation Business School Binus University West Jakarta Indonesia Department of Information Systems Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (纸本)9798350386097

This research evaluates the effectiveness of Mean-Variance (MV) and Safety-First (SF) portfolio selection strategies for high-volume/high-value traded stocks on the Philippine Stock Exchange (PSE). Analyzing data from 288 stocks over 7,670 trading days (30 years), we estimated stock returns, assigned probability weights, and conducted optimization models. The results show that the Mean-Variance (MV0.5) strategy achieved the best balance between risk and return, boasting the highest mean and cumulative returns with moderate volatility. The Safety-First (SF) strategy, however, yielded negative cumulative returns, indicating potential issues. The Market strategy had the lowest mean return but also the least risk, appealing to risk-averse investors. The Portfolio Mean-Variance (PMV) strategy provided a reasonable balance of returns and risk. Statistical analysis revealed that only the MV0.5 strategy outperformed market returns. These findings offer crucial insights into risk assessment and portfolio management for investors evaluating these strategies against market performance. © 2024 IEEE.

关键词： Marketplaces

来源：评论

学校读者我要写书评

暂无评论

Developing an Expert System for Mobile-based Gastroenteritis Detection Using ESDLC and Best First Search Methods

Developing an Expert System for Mobile-based Gastroenteritis...

引用

International Conference on Informatics and Computing (ICIC)

作者： R. Rizal Isnanto Catur Edi Widodo Ike Pertiwi Windasari Misik Puspajati Saputri Information Systems Doctoral Program Diponegoro University Semarang Indonesia Computer Engineering Department Diponegoro University Semarang Indonesia

Gastroenteritis is a common gastrointestinal disorder with varying degrees of severity, including cases without dehydration, mild dehydration, moderate dehydration, and severe dehydration. This research focuses on the development of a mobile-based expert system for detecting gastroenteritis, capable of distinguishing between these different dehydration levels. The methodology employed integrates the Extreme Structure Development Life Cycle (ESDLC) and the Best First Search algorithm. The expert system is designed to provide swift and accurate responses to users inputting symptoms, categorizing gastroenteritis cases based on the severity of dehydration. The application of ESDLC ensures a structured and organized development process, while the Best First Search method enhances the efficiency of the diagnostic process, facilitating timely and precise recommendations. Accessible through mobile platforms, the system allows users to input symptoms conveniently and receive rapid recommendations. Rigorous testing and evaluation affirm the system's high accuracy in discerning dehydration levels in gastroenteritis patients. In conclusion, the developed mobile-based expert system exhibits promising potential for advancing diagnostic services, particularly in the categorization of dehydration levels in gastroenteritis cases. The successful implementation of ESDLC and Best First Search paves the way for similar solutions in other healthcare domains, contributing positively to early and accurate disease management efforts. This innovation marks a significant stride towards improving healthcare technology for enhanced decision support in gastroenteritis diagnosis.

关键词：

来源：评论

学校读者我要写书评

暂无评论

An Examination of the Possible Application of Artificial Intelligence Audit Process in Organizations 6

An Examination of the Possible Application of Artificial Int...

引用

6th International Conference on Cybernetics and Intelligent System, ICORIS 2024

作者： Sardjono, Wahyu Pranata, Dewi Sagita Isamesal, Muhammad Information Systems Management Department BINUS Graduate Program Bina Nusantara University Jakarta11480 Indonesia Cyber Security Studi Program Department of Informatics Faculty of Natural Mathematical & Engineering Sciences King’s College London West Minster WC2R 2LS United Kingdom Management Department Faculty of Economics and Busines Universitas of Airlangga Surabaya10430 Indonesia

ISBN: (纸本)9798331539603

This study investigates how artificial intelligence (AI) can transform audit processes, including how AI can be used in businesses to execute non-technical audit tasks and what effect this will have on those tasks. A qualitative case study methodology is used in the research design to give detailed insights into how AI is being adopted by businesses. This study aims to analyze the aspects that impact AI implementation from the viewpoints of managers, auditors, and other stakeholders. The findings show that artificial intelligence (AI) has a great deal of promise for non-technical audit procedures in businesses. AI can automate tedious jobs, evaluate large data sets to identify hazards and enhance teamwork and communication. These developments may lead to increased productivity, maybe better audit quality, and more effective processes. But there are still difficulties. Data quality is essential to the success of AI integration, and auditors may exhibit bias in favor of human professionals. Careful thought must also be given to ethical issues about transparency and possible job displacement. All things considered, this study adds significant knowledge to both the academic literature and real-world auditing applications. It improves our comprehension of the function of AI in the industry and provides useful information for people involved in information technology development, audit, and legislation. © 2024 IEEE.

关键词： Data quality

来源：评论

学校读者我要写书评

暂无评论

Preferences in Construction Workers Selection to a Project Team: A Conjoint Analysis Approach 24

Preferences in Construction Workers Selection to a Project T...

引用

6th International Conference on Management Science and Industrial engineering, MSIE 2024

作者： Bonete, Lorenz Ian B. Prasetyo, Yogi Tri Ahmed, Nagib Ismail Cahigas, Maela Madel L. Nadlifatin, Reny Ayuwati, Irene Dyah School of Industrial Engineering and Engineering Management Mapúa University Manila Philippines School of Graduate Studies Mapúa University Manila Philippines International Bachelor Program in Engineering Yuan Ze University Chung-Li Taiwan Department of Industrial Engineering and Management Yuan Ze University Chung-Li Taiwan Department of Information Systems Institut Teknologi Sepuluh Nopember Kampus ITS Sukolilo Surabaya60111 Indonesia University of Surabaya Surabaya60284 Indonesia

ISBN: (纸本)9798400717130

Construction teams are responsible for building complex projects within the allotted budget, time and expected quality. Thus, team members must be able to work with each other to avoid any complications during the construction process. As such, team supervisors must select from a pool of applicants or from their current roster of workers, which would be composed of different personalities and capabilities. This paper aims to identify the preferences of team supervisors when building up their team using conjoin analysis. The study found out that supervisors would like to have workers that respects and values their work and can work harmoniously with others. This study is beneficial for the human resource department of construction companies when recruiting workers, for the management when trying to develop their current personnel and for the workers who are trying to improve themselves. © 2024 ACM.

关键词： Supervisory personnel

来源：评论

学校读者我要写书评

暂无评论

Expert System for Diagnosis of Diphtheria Disease Using Fuzzy Logic

Expert System for Diagnosis of Diphtheria Disease Using Fuzz...

引用

International Seminar on Research of information Technology and Intelligent systems (ISRITI)

作者： R.Rizal Isnanto Mustafid Agung Budi Prasetijo Safira Isna Fitria Ali Information Systems Doctoral Program Diponegoro University Semarang Indonesia Computer Engineering Department Diponegoro University Semarang Indonesia

Diphtheria is an infectious disease that affects the upper respiratory system and throat, arising suddenly and caused by Corynebacterium diphtheriae. The symptoms of diphtheria such as fever, swollen neck and slimy nose are often interpreted as influenza or laryngitis. Diphtheria is a contagious and deadly disease that requires specialized and rapid treatment and care. In today's technological era, it can be overcome with a system that can diagnose diphtheria like a doctor's diagnosis ability commonly called an expert system. This study describes the application of an expert system to diagnose diphtheria disease. The research method used is the web-based Expert System Development Life Cycle (ESDLC). The method used to process input values is Forward Chaining. Fuzzy Tsukamoto to calculate the input value from the user. The research has been tested with Blackbox testing showing the results that the expert system works well and accuracy testing with 92% results. The results show effectiveness with a satisfactory level of accuracy in detecting diphtheria disease. This research contributes to the development of expert systems in the health sector with a focus on diagnosing diphtheria disease using a fuzzy logic approach.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Gastritis Diagnosis Expert System Using Android-Based Certainty Factor Method

Gastritis Diagnosis Expert System Using Android-Based Certai...

引用

International Seminar on Research of information Technology and Intelligent systems (ISRITI)

作者： R. Rizal Isnanto Purwanto Yudi Eko Windarto Annas Setiawan Information Systems Doctoral Program Diponegoro University Semarang Indonesia Computer Engineering Department Diponegoro University Semarang Indonesia

In the modern era, an increasing number of diseases are emerging because of human lifestyle choices and bacterial transmission. Gastritis, characterized by inflammation in the stomach lining leading to frequent abdominal pain, is one such ailment. Recognizing the significance of addressing these health issues, there is a need for an expert system application specifically designed for diagnosing gastritis. The primary objective is to disseminate information to the public regarding the early symptoms of gastritis, promoting awareness from a young age. The research method used is the web-based Expert System Development Life Cycle (ESDLC). The diagnostic process employs the Certainty Factor (CF) method to ensure accurate results. By utilizing symptom CF values chosen by the user, the Certainty Factor approach facilitates a diagnosis based on calculations established by medical specialists. The research culminates in the development of an expert system application capable of accurately diagnosing the disease Android based. The accuracy rates for the first, second, and third test cases are reported as 98.848%, 99.8464%, and 99.99115264%, respectively. System testing, conducted through black-box testing, validates the application's functionality, demonstrating a 100% success rate for each component.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Design of an Infusion Capacity Monitoring System for Patients Based on the Internet of Things in Hospitals

Design of an Infusion Capacity Monitoring System for Patient...

引用

International Conference on Business and Industrial Research (ICBIR)

作者： Vina Septiana Windyasari Silvia Ayunda Murad Syahriani Syam Maulia Mahardika Johan Budiman Diah Rahmawati Information Systems Study Program Islamic Syekh-Yusuf University Tangerang Indonesia Information System Department BINUS Online Learning Binus University Jakarta Indonesia Informatics Engineering Study Program Islamic Syekh-Yusuf University Tangerang Indonesia Civil Engineering Study Program Islamic Syekh-Yusuf University Tangerang Indonesia

ISBN: (数字)9798350383027

ISBN: (纸本)9798350383034

The patient's infusion fluid will only be changed if the nurse changes it or based on information from the patient's family. The research method used in terms of fluid volume utilizes the function of the Arduino microcontroller as the brain, the load cell sensor as an infusion fluid weight detector connected to the IoT, fuzzy logic calculations on the infusion volume weight measuring device in line with real-time decision-making when reading gram weight changes with sensors, and the system development method using a prototype model. The test results of three infusion bottles containing mineral water with a liquid volume of 500 ml and a load cell sensor as an infusion weight detector can be accepted by the Arduino Wemos D1 as a load cell sensor processing component. The infusion liquid weight data is uploaded to the MySQL database, and a notification is sent and displayed on the smartphone when the infusion volume reaches 12% of its weight. The results of this study indicate that the design of tools connected to applications on smartphones can work well and facilitate the process of monitoring infusions for patients in real-time

关键词： Weight measurement Fuzzy logic Solid modeling Liquids Databases Volume measurement Prototypes Detectors Real-time systems Monitoring

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：