2022 7th International Conference on Business and Industrial Research (ICBIR)最新文献_第4页

Mobile Banking Adoption for Digital Financial Inclusion 采用移动银行实现数字普惠金融

2022 7th International Conference on Business and Industrial Research (ICBIR) Pub Date : 2022-05-19 DOI: 10.1109/ICBIR54589.2022.9786477

P. Jain, B. Sharma, Rachit Jain, Anand Kumar Pandey, S. Khare

引用次数: 0

Evaluation of Hybrid Collaborative Filtering Approach with Context-Sensitive Recommendation System 基于上下文敏感推荐系统的混合协同过滤方法评价

2022 7th International Conference on Business and Industrial Research (ICBIR) Pub Date : 2022-05-19 DOI: 10.1109/ICBIR54589.2022.9786506

D. F. Murad, Rosilah Hassan, B. Wijanarko, Riyan Leandros, S. A. Murad

{"title":"Evaluation of Hybrid Collaborative Filtering Approach with Context-Sensitive Recommendation System","authors":"D. F. Murad, Rosilah Hassan, B. Wijanarko, Riyan Leandros, S. A. Murad","doi":"10.1109/ICBIR54589.2022.9786506","DOIUrl":"https://doi.org/10.1109/ICBIR54589.2022.9786506","url":null,"abstract":"This study aims to evaluate the recommendation system we have implemented. The test was carried out using student profile data with (1) adding contextual information and (2) without contextual information. The evaluation was carried out using three predictive methods, user collaborative filtering, item collaborative filtering, and hybrid. We use the correlation coefficient to determine which method has the best correlation coefficient between the predicted and actual values. In this experiment, the best method for predicting the actual value is to use a user-based collaborative filtering method. A low correlation coefficient indicates that a machine learning model is needed to learn the predictive formula of the predictor features and their actual values. The test results using these three methods show that the correlation coefficient between the actual value and the predicted value using user-based collaborative filtering is the highest. Meanwhile, the lowest correlation coefficient between the actual value and predicted values using item collaborative filtering is the lowest. The results of this study prove that contextual information as an additional feature of student profiles increases the correlation coefficient between actual and predicted scores using a user collaborative filter.","PeriodicalId":216904,"journal":{"name":"2022 7th International Conference on Business and Industrial Research (ICBIR)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133674971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Collaborative Collection of Multilingual Pronoun Substitutes and Address Terms 多语代词代称和称呼用语的协同收集

2022 7th International Conference on Business and Industrial Research (ICBIR) Pub Date : 2022-05-19 DOI: 10.1109/ICBIR54589.2022.9786494

Virach Sornlertlamvanich, Hiroki Nomoto, Sunisa Wittayapanyanon Saito, Atsushi Kasuga, Kenji Okano, Wataru Okubo, Yunjin Nam, Yoshimi Miyake, Thuzar Hlaing, Ryuko Taniguchi, Sri Budi Lestari

引用次数: 2

Static Properties of Laser Welded Ultra-High-Strength Stainless Steel Tube 激光焊接超高强度不锈钢管的静态性能

2022 7th International Conference on Business and Industrial Research (ICBIR) Pub Date : 2022-05-19 DOI: 10.1109/ICBIR54589.2022.9786395

M. Hietala, M. Keskitalo, A. Järvenpää

{"title":"Static Properties of Laser Welded Ultra-High-Strength Stainless Steel Tube","authors":"M. Hietala, M. Keskitalo, A. Järvenpää","doi":"10.1109/ICBIR54589.2022.9786395","DOIUrl":"https://doi.org/10.1109/ICBIR54589.2022.9786395","url":null,"abstract":"This paper investigates static properties of laser welded ultra-high-strength (UHS) stainless steel tube. The material of the tube was cold-hardened ultra-high-strength austenitic stainless steel (AISI 301 2H) with a tensile strength of 1.55 GPa. The AISI 301 steel tubes were manufactured by laser welding from two U-shaped parts. For comparison, low strength stainless steel (AISI 304) tubes were also examined in the experiments. The microstructure of the welded joints was studied by optical microscopy. The hardness of the laser weld joint was determined. The strength of the tubes was studied by three-point bending and compression tests. It was observed that the hardness at the HAZ of the AISI 301 joint was 51% lower than that of the base material. HAZ showed new fine grains of austenite phase structure due to the reversion transformation from martensite to austenite. Result showed that the AISI 304 weld had the same hardness as the base material. Three-point bending experiments revealed that the bending strength of the UHS (AISI 301) steel tube was approximately 60% higher than that of low strength AISI 304 steel tube. The location of the weld relative to the direction of the compressive force had a significant effect on the compressive strength of the UHS (AISI 301) steel tube.","PeriodicalId":216904,"journal":{"name":"2022 7th International Conference on Business and Industrial Research (ICBIR)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117056992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Automated Data Analytics and Overall Equipment Effectiveness Visualization Technique for Assembly Line on Continuous Manufacturing System using Power BI 基于Power BI的连续制造系统装配线自动化数据分析与整体设备效率可视化技术

2022 7th International Conference on Business and Industrial Research (ICBIR) Pub Date : 2022-05-19 DOI: 10.1109/ICBIR54589.2022.9786497

P. Vejjanugraha, Kanda Tiwatthanont, Napaphat Vichaidis, Tanasin Yatsungnoen, Patsama Charoenpong, Sared Wansopa, Adisak Suasaming, P. Boonsieng

{"title":"An Automated Data Analytics and Overall Equipment Effectiveness Visualization Technique for Assembly Line on Continuous Manufacturing System using Power BI","authors":"P. Vejjanugraha, Kanda Tiwatthanont, Napaphat Vichaidis, Tanasin Yatsungnoen, Patsama Charoenpong, Sared Wansopa, Adisak Suasaming, P. Boonsieng","doi":"10.1109/ICBIR54589.2022.9786497","DOIUrl":"https://doi.org/10.1109/ICBIR54589.2022.9786497","url":null,"abstract":"Thailand 4.0 model is established to develop a smart city with human-machine interaction to communicate to every station in the manufacturing process using sensor and visualization techniques. The automated approach for analyzing and visualizing the Overall Equipment Effectiveness (OEE) of the assembly line on the continuous manufacturing system using Power BI is introduced. The data cleansing and data transform process was applied to prepare the input data, and the Data Analysis Expressions (DAX) measurement is used to calculate the key features from timestamp and output table such as time duration of ‘RED’, ‘GREEN’, and ‘YELLOW’, count ‘NG’ status, and count ‘FG’ status. Once OEE and OEE Loss are calculated from the prepared data, the visualization of Modules I, II, and III are generated to demonstrate the cycle time, progress amount, and OEE and OEE loss. The visualization shows the relation between OEE and OEE loss and their components. The losses and abnormality signals can be detected from the graph and eliminated losses by the Kaizen process. It showed that the Performance Loss from the minor stop could be reduced by decreasing the waiting time from 2 Standard Cycle Time (StdCT) to 1 StdCT, the OEE is improved from 53.11% to 57.05%, and Performance is changed from 78.55% to 84.38%.","PeriodicalId":216904,"journal":{"name":"2022 7th International Conference on Business and Industrial Research (ICBIR)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116158106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

ICBIR 2022 All Tracks Presentation Schedule ICBIR 2022所有曲目展示时间表

2022 7th International Conference on Business and Industrial Research (ICBIR) Pub Date : 2022-05-19 DOI: 10.1109/icbir54589.2022.9786463

引用次数: 0

Mobile Payments Adoption in Small and Medium Retail Enterprises: An Exploratory Study in Manila, Philippines 移动支付在中小型零售企业的应用:在菲律宾马尼拉的探索性研究

2022 7th International Conference on Business and Industrial Research (ICBIR) Pub Date : 2022-05-19 DOI: 10.1109/ICBIR54589.2022.9786389

Alexander A. Hernandez, Ronaldo Juanatas, Victor James C. Escolano, Ma. Divina E. Elvambuena

引用次数: 1

The Software Development for Job Shop Production Planning and Inventory Control on Spreadsheet 基于电子表格的作业车间生产计划与库存控制软件开发

2022 7th International Conference on Business and Industrial Research (ICBIR) Pub Date : 2022-05-19 DOI: 10.1109/ICBIR54589.2022.9786430

Punyapat Trethepvijit, Anchalee Supithak

引用次数: 1

Digital Skills and Job Performance in Remote Work 远程工作中的数字技能和工作绩效

2022 7th International Conference on Business and Industrial Research (ICBIR) Pub Date : 2022-05-19 DOI: 10.1109/ICBIR54589.2022.9786486

García-Salirrosas Elizabeth Emperatriz, Millones-Liza Dany Yudet

引用次数: 1

Study on the Different Types of Accounting Fraud and Tools to Detect and Prevent Fraud 不同类型的会计舞弊及舞弊检测和预防工具研究

2022 7th International Conference on Business and Industrial Research (ICBIR) Pub Date : 2022-05-19 DOI: 10.1109/ICBIR54589.2022.9786440

Hasyimah Isa, Mohammad Erwindie Abdul Rahim, Nur Aizzah Mohammad Ariffin, Ratne Azera Embran, Syazana Han Mohammad Ridzuan Han, Ulaganathan Subramanian, F. Kawi, Norazillah Abdullah

引用次数: 0