{"title":"Designing Automated Batch-Processing Production Planning for Manufacturing based on Asset-Oriented Modelling","authors":"Chen Fai Chin, Yee Mei Lim, Wah Pheng Lee","doi":"10.56453/icdxa.2020.1015","DOIUrl":"https://doi.org/10.56453/icdxa.2020.1015","url":null,"abstract":"Value-based assets in manufacturing such as machines and production planning are critical to productivity and operational success. This paper proposes the implementation design of an intelligent system that produces flexible production planning based on asset-oriented modelling for batch-processing-oriented design. The research aims to reduce the machine changeover time and enables flexibility in production scheduling. The challenge of having such an automated production planning system is that it must be able to handle real-time customer orders, any ad hoc interruptions and unexpected downtime in any production lines. It is important to design an automated production planning system that can produce optimized scheduling that satisfies all hard-constraints in the system. Keywords: intelligent scheduling, manufacturing, production planning, manufacturing asset.","PeriodicalId":216696,"journal":{"name":"Conference Proceedings: International Conference on Digital Transformation and Applications (ICDXA 2020)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123166882","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}
Rustamov Zahiriddin, Jaloliddin Rustamov, J. Tan, Harrsimran Kaur Atar Singh, Kien Sin Aw
{"title":"A Usability Evaluation of TARCApp Mobile Application","authors":"Rustamov Zahiriddin, Jaloliddin Rustamov, J. Tan, Harrsimran Kaur Atar Singh, Kien Sin Aw","doi":"10.56453/icdxa.2020.1022","DOIUrl":"https://doi.org/10.56453/icdxa.2020.1022","url":null,"abstract":"TARCApp mobile application is an application used by Tunku Abdul Rahman University College students on a daily basis to access necessary resources. Therefore, this study attempts to evaluate the usability of the application by comparing with the Concordia mobile application from the aspects of effectiveness, efficiency and satisfaction. Instruments such as Test Task, Single Ease Question (SEQ) and Software Usability Scale (SUS) questionnaires have been used to measure the usability of these mobile applications. Results indicate that the TARCApp mobile application had a high degree of effectiveness and efficiency. However, the satisfaction was poor, and some usability issues have been discovered during this study. Keywords: usability, mobile application, effectiveness, efficiency, satisfaction","PeriodicalId":216696,"journal":{"name":"Conference Proceedings: International Conference on Digital Transformation and Applications (ICDXA 2020)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128793184","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}
{"title":"Scanner-Based Digital Image Correlation Method for Mechanical Characterization of Rubber","authors":"Ching Pang Goh, M. Ratnam","doi":"10.56453/icdxa.2020.1009","DOIUrl":"https://doi.org/10.56453/icdxa.2020.1009","url":null,"abstract":"The digital image correlation (DIC) method coupled with a moveable camera has been widely used for large in-plane displacement measurement in elastomeric materials. However, this method has the limitation due to the limited field-of-view (FOV) of the camera. In this paper, a novel scanner based digital image correlation (SBDIC) method which enables acquisition of a large FOV of speckle pattern image on the specimen has been developed. The entire information of the deformation was obtained and analyzed up to 350% strain. The correlation between the images at successive stages was computed using incremental cross correlation (CC) tracking algorithm. The Young’s modulus and Poisson’s ratio of vulcanized natural rubber (VNR) up to 350% axial strain were determined simultaneously using the same set of data. Tangent and secant modulus of the rubber at axial strains of 50% to 350% in 50% increments obtained from the scanner-based DIC method was compared with those obtained from a universal tensile test machine (UTM). In addition, the Poisson’s ratios show that the experimental data fitted well with the theoretical result up to an axial stretch ratio of 2.0. The SBDIC method was found to be a potential tool for low cost measurement of mechanical characteristics of polymeric materials. Keywords: DIC, large deformation, cross-correlation, axial strain, Poisson ratio","PeriodicalId":216696,"journal":{"name":"Conference Proceedings: International Conference on Digital Transformation and Applications (ICDXA 2020)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128607985","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}
{"title":"A Survey on Multi-View and 3D High Efficiency Video Coding on Real Time Streaming","authors":"Yik Siang Pang, Y. Tew","doi":"10.56453/icdxa.2020.1013","DOIUrl":"https://doi.org/10.56453/icdxa.2020.1013","url":null,"abstract":"In the past few years, the demand of multi-view was increased rapidly and there was a lot of research works to improve the technique and fulfil its needs. High Efficiency Video Coding (HEVC) compression standard has been implemented in this work. HEVC is a compression standard designed to reduce bitrate and remain the same quality compared to the previous compression standard Advanced Video Coding (H.264). It will provide a better compression to higher resolution video such as Ultra High Definition (UHD). In this paper presents a preliminary study on Multi-view with depth by using HEVC compression on a real-time streaming protocol. The study of proposed work may help the industry to enhance the viewing experience by multiple camera capture and also resolve the data traffic issue to transmit UHD video. Keywords: High Efficiency Video Coding, 3DHEVC, Multi-view, real-time streaming, Ultra High Definition","PeriodicalId":216696,"journal":{"name":"Conference Proceedings: International Conference on Digital Transformation and Applications (ICDXA 2020)","volume":"2015 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132421839","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}
{"title":"Crack Segmentation using DeepLab","authors":"Zhen Cheng Voon, J. Chaw","doi":"10.56453/icdxa.2020.1011","DOIUrl":"https://doi.org/10.56453/icdxa.2020.1011","url":null,"abstract":"Crack detection on road or building surface is normally inspected manually by specialist. It consumes a lot of time and the inspection result might be different depending on the specialist experience and knowledge. In this paper, an automated crack segmentation model built using DeepLab model is proposed where transfer learning is being utilized. The model is trained on the dataset from DeepCrack which consists of 300 training images and 237 testing images. 3 models are trained with different value of training step and training rate. The models are then evaluated using the mean intersection-over-union metrics and managed to achieve value around 0.75 for mean intersection-over-union. 10 images also chosen and the precision and recall value for each of the images are calculated and plotted on a graph. The segmentation result of the DeepLab model was used to compare with the segmentation result of Otsu’s method in detecting cracks. Keywords: crack segmentation, DeepLab, transfer learning","PeriodicalId":216696,"journal":{"name":"Conference Proceedings: International Conference on Digital Transformation and Applications (ICDXA 2020)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114894019","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}
{"title":"Applying TRIZ to Solve Electricity Maximum Demand Problem","authors":"K. H. Yiauw, Jay Son Teo","doi":"10.56453/icdxa.2020.1014","DOIUrl":"https://doi.org/10.56453/icdxa.2020.1014","url":null,"abstract":"This paper aims to provide a systematic approach by applying TRIZ to reduce the maximum demand of the targeted plant, and nonetheless, it does not demote the working quality and environment. TRIZ tools such as engineering system defining, function analysis, cause and effect chain analysis, and engineering contradiction are applied according to achieve a suitable solution to alleviate the problem. From the finding shows that the root cause of high maximum demand (MD) in the plant is due to the company does not have a proper standard on energy savings, using large demand machinery and old aged appliance which are unable to control. The root cause and contradiction are resolved by applying TRIZ tools. Hence, it can be concluded that TRIZ is an innovative and systematic tool in problem-solving. Keywords: Demand-side Management, Industrial, Maximum Demand, TRIZ","PeriodicalId":216696,"journal":{"name":"Conference Proceedings: International Conference on Digital Transformation and Applications (ICDXA 2020)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117148431","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}
{"title":"A Study on Multi-View Camera Casting Framework using Internet of Things Technology","authors":"Y. Tew, Yoonku Lee","doi":"10.56453/icdxa.2020.1021","DOIUrl":"https://doi.org/10.56453/icdxa.2020.1021","url":null,"abstract":"With the advanced video streaming technology, smartphone users can share and stream real-time camera to any video subscriber with a high network transmission speed. On the other side, subscriber able to select their favorite video sources can create multiple screen (i.e., Multi-View features) display. In this paper, a video casting framework for displaying multiple video sources is proposed. This framework potentially leads to an object modelling when multiple cameras point to the same object with different angle of view. In addition, the multiview feature provides additional flexibility on a well-designed production line monitoring system in an Industrial IoT framework. With the existence of multiview content, earlier error detection and prevention can be performed to facilitate cyber-physical system, as an important element in Industrial IoT. Keywords: multi-view, Industry 4.0, Internet of Things, Real-Time Streaming Protocol, video casting","PeriodicalId":216696,"journal":{"name":"Conference Proceedings: International Conference on Digital Transformation and Applications (ICDXA 2020)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127376023","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}
{"title":"A Comparative Study on the Time Series Models for Forecasting Facebook Reactions","authors":"Yong Poh Yu, Khai Lone Lim, T. Lim","doi":"10.56453/icdxa.2020.1012","DOIUrl":"https://doi.org/10.56453/icdxa.2020.1012","url":null,"abstract":"The Facebook reactions were used over 300 billion times during their first year of existence. Research on reaction activity is essential especially for the digital marketing purpose. The market needs to understand how Facebook reactions fluctuate to forecast the best period to post advertisements on Facebook that yields the highest number of reactions. In this study, several time-series models are used to forecast the number of Facebook reactions over a certain period for different domains. A comparative study is done to evaluate the performance of each model, in terms of strengths and weaknesses. Keywords: Forecasting, Facebook reactions, time series model, ARIMA, SARIMA","PeriodicalId":216696,"journal":{"name":"Conference Proceedings: International Conference on Digital Transformation and Applications (ICDXA 2020)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126142216","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}
{"title":"A Critical Review on Impression Rate and Pattern on Social Media Sites","authors":"Kwai Mui Choon, T. Lim","doi":"10.56453/icdxa.2020.1003","DOIUrl":"https://doi.org/10.56453/icdxa.2020.1003","url":null,"abstract":"Social media interaction continues affecting consumer opinion of a product, so social media marketing has become the most accessible marketing channel for brands to reach their business’ target market, product promotion, make a sale or spread brand awareness. This paper is to critically review past research works on the impact of impressions on social media marketing and highlight gaps found. There are limited studies available on the impact of the impression rate on brand awareness through social media marketing/advertising. By using a systematic literature review, this paper contributes to social media adoption by investigating consumers’ brand awareness towards social media advertising, the relationship between impressions rate and brand awareness and social media measurement practices in various industries. Keywords: social media, impressions, reach, brand awareness","PeriodicalId":216696,"journal":{"name":"Conference Proceedings: International Conference on Digital Transformation and Applications (ICDXA 2020)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126427384","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}
{"title":"A Review on Sentiment Analysis for Code-Mix Chinese and English Text on Social Media","authors":"Kong Hua Lim, T. Lim","doi":"10.56453/icdxa.2020.1001","DOIUrl":"https://doi.org/10.56453/icdxa.2020.1001","url":null,"abstract":"Social media is rich with opinions. Millions of people shared their thoughts on products, services and events on Social Media Sites (SMS). Digital marketers extract and analyse content from SMS so that they know how best to promote their products or services to potential buyers. Government can get feedback from citizens about policies they have implemented. Works here reviews numerous sentiment analysis research works that study code-mix posts and comments that were expressed in formal and informal languages with a code-mix of Chinese and English or English and Hindi. Research in code-mix English and Hindi sentiment analysis are reviewed to provide some insights for application in code-mix Chinese and English. Raw data collected will be pre-processed into structured representation. Works here will discuss sentiment analysis that adopts lexicon approach, machine learning and combination of both. Works here will highlight translation and non-translation approaches used to analyse code-mix text. Discussion about propose solution for further exploration is discussion in a section. Critical remarks and a concluding section will be presented at the end of the paper. Keywords: code-mix, machine learning, lexicon","PeriodicalId":216696,"journal":{"name":"Conference Proceedings: International Conference on Digital Transformation and Applications (ICDXA 2020)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130811283","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}