2022 IEEE International Conference on Computing (ICOCO)最新文献_第7页

Prediction of FTSE Bursa Malaysia KLCI Stock Market using LSTM Recurrent Neural Network 基于LSTM递归神经网络的马来西亚富时证券KLCI市场预测

2022 IEEE International Conference on Computing (ICOCO) Pub Date : 2022-11-14 DOI: 10.1109/ICOCO56118.2022.10031901

T. M. Busu, Saadi Ahmad Kamarudin, N. Ahad, Norazlina Mamat

{"title":"Prediction of FTSE Bursa Malaysia KLCI Stock Market using LSTM Recurrent Neural Network","authors":"T. M. Busu, Saadi Ahmad Kamarudin, N. Ahad, Norazlina Mamat","doi":"10.1109/ICOCO56118.2022.10031901","DOIUrl":"https://doi.org/10.1109/ICOCO56118.2022.10031901","url":null,"abstract":"Stock market prediction is vital in the financial world. Investors and people interested in investing would be interested in the future value of the stock market before they invest in it. By using the method of time series, this research gives a contribution to forecast and modelling the FTSE Bursa Malaysia KLCI (FBM KLCI) stock market. In this research, the stock market is forecasted to identify the stock market trend in the future. The FBM KLCI closing prices data was utilized to build Long Short-Term Memory (LSTM) models to predict the stock market. The performance of the model has been evaluated using the root mean squared error (RMSE) and the mean absolute error (MAE) in order to choose the best model. The researcher used the Bursa Malaysia data to forecast the stock market for five years, from October 20, 2016, to October 20, 2021, which has been scrapped from the Yahoo Finance website. The data is analyzed by running Python coding in Google Colab. The result proves that the accuration of the LSTM model by using Recurrent Neural Network (RNN) approach is accurate and the predicted value of the stock market at the date 2021-10-05 is increased by 1.87%. It can be used to predict the future closing stock prices in stock market prediction in FBM KLCI stock market. The results are expected to provide an accurate prediction for a better profit. Thus, prediction in stock market investment can support long-term economic growth, or in other words, it can help economic sustainability.","PeriodicalId":319652,"journal":{"name":"2022 IEEE International Conference on Computing (ICOCO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129378508","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

Answering Why? An Overview of Immersive Data Visualization Applications Using Multi-Level Typology of Visualization Task 回答为什么?基于多层次可视化任务类型的沉浸式数据可视化应用综述

2022 IEEE International Conference on Computing (ICOCO) Pub Date : 2022-11-14 DOI: 10.1109/ICOCO56118.2022.10031696

Najwa Ayuni Jamaludin, Farhan Mohamed, M. Sunar, A. Selamat, O. Krejcar

引用次数: 0

Performance Evaluation of Multi-Channel for 10×10 Mesh Wireless Network-on-Chip Architecture 10×10 Mesh无线片上网络多通道性能评价

2022 IEEE International Conference on Computing (ICOCO) Pub Date : 2022-11-14 DOI: 10.1109/ICOCO56118.2022.10031710

A. Lit, Popoola Oluwaseun Lydia, S. Suhaili, R. Sapawi, K. Kipli, D. N. S. Dharmiza

{"title":"Performance Evaluation of Multi-Channel for 10×10 Mesh Wireless Network-on-Chip Architecture","authors":"A. Lit, Popoola Oluwaseun Lydia, S. Suhaili, R. Sapawi, K. Kipli, D. N. S. Dharmiza","doi":"10.1109/ICOCO56118.2022.10031710","DOIUrl":"https://doi.org/10.1109/ICOCO56118.2022.10031710","url":null,"abstract":"Wireless Network-on-Chip (NoC) is envisioned as complementary to the conventional NoC due to its CMOS compatibility and architectural flexibility, which is advantageous as no wiring infrastructure is required for wireless transmission. On-chip wireless channels are used to actually minimize the communication latency between the distant processing cores because of its ability to communicate with long-distance communication processing cores in a single-hop. This paper investigates the effect of the single-, dual-, and triple-channels on the mesh-WiNoC architecture. Additionally, four and nine radio hubs are evenly distributed throughout the mesh-WiNoC topological structure to evaluate its global transmission latency, network throughput, and energy characteristics. The investigated architectures under test are simulated on the cycle-accurate systemC based Noxim simulator under a random traffic workload scenario for WiNoC performance evaluation. This study’s contribution is that it looks into the best number of wireless channels to use in a 10 × 10 mesh WiNoC architecture for 4 and 9 radio hub scenarios to get the best performance in transmission latency and energy consumption. Experimental results show that for both investigated number of radio hub on mesh-WiNoC architecture demonstrates nearly identical system performance in terms of transmission latency and throughput. However, the meshWiNoC architecture with 4 radio hub demonstrates better energy characteristics, saving 9.63% and 13.60% of energy, respectively, when compared to the architecture with 6 and 9 radio hub.","PeriodicalId":319652,"journal":{"name":"2022 IEEE International Conference on Computing (ICOCO)","volume":"314 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122966221","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: 1

Analysis of Articles that Correct Other Posts on Social Media Aimed at Promoting the Experience in Examining Fakes 社交媒体上纠正他人帖子的文章分析，旨在提升审假经验

2022 IEEE International Conference on Computing (ICOCO) Pub Date : 2022-11-14 DOI: 10.1109/ICOCO56118.2022.10031731

R. Onuma, H. Kaminaga, H. Nakayama, Y. Miyadera, Keito Suzuki, Shoichi Nakamura

{"title":"Analysis of Articles that Correct Other Posts on Social Media Aimed at Promoting the Experience in Examining Fakes","authors":"R. Onuma, H. Kaminaga, H. Nakayama, Y. Miyadera, Keito Suzuki, Shoichi Nakamura","doi":"10.1109/ICOCO56118.2022.10031731","DOIUrl":"https://doi.org/10.1109/ICOCO56118.2022.10031731","url":null,"abstract":"Social media is increasingly being used as a tool to gather a wide variety of information. However, there are fake articles on social networking services mixed in with useful posts. It is desirable for users to use social networking services while determining the truth or falsity of articles. However, such judgement is difficult for inexperienced users since the skills to determine the authenticity of articles should be obtained by a stacking of experiences. In this research, we aim to develop methods for gaining experience with examining fake articles by suggesting noteworthy articles on the basis of an analysis of others’ responses to the articles. This paper describes methods for extracting articles that correct other posts on the basis of the characteristics of people’s responses to articles on social networking services and for extracting candidates for fake articles by analyzing such articles. Finally, we describe an experiment using a prototype system and discuss the effectiveness of our system as based on its results.","PeriodicalId":319652,"journal":{"name":"2022 IEEE International Conference on Computing (ICOCO)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132791689","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

Data Conversion Process Framework to Generate Individual-Level Nutrition Data from Household-Level Grocery Data 从家庭层面食品杂货数据生成个人层面营养数据的数据转换过程框架

2022 IEEE International Conference on Computing (ICOCO) Pub Date : 2022-11-14 DOI: 10.1109/ICOCO56118.2022.10031274

Nuraina Daud, Nurulhuda Noordin, N. Teng

{"title":"Data Conversion Process Framework to Generate Individual-Level Nutrition Data from Household-Level Grocery Data","authors":"Nuraina Daud, Nurulhuda Noordin, N. Teng","doi":"10.1109/ICOCO56118.2022.10031274","DOIUrl":"https://doi.org/10.1109/ICOCO56118.2022.10031274","url":null,"abstract":"This paper presents a data conversion process involving household grocery data. The household grocery data were gathered from the primary source which is directly from 50 selected household in Shah Alam for 5 consecutive months. The data transformation was done to convert the grocery data into the nutrition data. The converted nutrition data will be tested using data mining classification algorithms, and the patterns generated from it will be explored for obesity prediction purposes. In the data transformation process, the raw grocery data has undergone several data pre-processing and conversion methods. These processes have been done by the nutritionists as the knowledge on nutrition field are needed in performing this task. The processes involved are calorie conversion, macronutrient grouping, food pyramid grouping, and food categorization. There were five methods have been conducted to perform the conversion task which are food composition database, offline and online market survey, food pyramid and knowledge theory on nutrition. The conversion process has been gathered to form Data Conversion Process Framework. This paper also introduced the use of estimation formula using BMI weightage as a method to generate the individual-level nutrition data. The nutrition data generated from the grocery data processing and the conversion process using the BMI weightage highlight the significance of the study. The output from this study (nutrition data) will be used in the later stage of the study as the input data in the development of obesity prediction modelling.","PeriodicalId":319652,"journal":{"name":"2022 IEEE International Conference on Computing (ICOCO)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131366245","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

ARventure: Edutainment Meets Science Mobile Application ARventure:寓教于乐满足科学移动应用

2022 IEEE International Conference on Computing (ICOCO) Pub Date : 2022-11-14 DOI: 10.1109/ICOCO56118.2022.10031868

Nurul Nabilah Izzati Binti Ridzuan, Nurfauza Binti Jali, S. K. Jali, Mohamad Imran Bandan, Adrus Bin Mohamad Tazuddin, Lim Phei Chin

{"title":"ARventure: Edutainment Meets Science Mobile Application","authors":"Nurul Nabilah Izzati Binti Ridzuan, Nurfauza Binti Jali, S. K. Jali, Mohamad Imran Bandan, Adrus Bin Mohamad Tazuddin, Lim Phei Chin","doi":"10.1109/ICOCO56118.2022.10031868","DOIUrl":"https://doi.org/10.1109/ICOCO56118.2022.10031868","url":null,"abstract":"Despite continuous growth in STEM-associated industries, the number of students pursuing Science, Technology, Engineering, and Mathematics (STEM) related subjects is declining. The implementation of Augmented Reality (AR) in education has the potential to improve not just the students’ conceptual comprehension and knowledge but also critical abilities like problem-solving, cooperation, and communication. This study intends to demonstrate how a mobile application embedded with AR that uses an educational scrapbook as its AR marker platform can improve the learning experience of secondary Malaysian secondary school students studying Science. 30 students across Malaysia were recruited. Their responses were analysed to determine whether the notion of employing a mobile application and scrapbook was feasible. Overall, the System Usability Scale (SUS) results were encouraging (mean=69.83, SD=13.36, n=30), suggesting the possibility of integrating AR as part of the learning medium that could improve the learning experience in Science subjects.","PeriodicalId":319652,"journal":{"name":"2022 IEEE International Conference on Computing (ICOCO)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123497878","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

Industry Recommendation for Undergraduate Internship using Decision Tree 基于决策树的大学生实习行业推荐

2022 IEEE International Conference on Computing (ICOCO) Pub Date : 2022-11-14 DOI: 10.1109/ICOCO56118.2022.10031980

Intan Norsyafiqa Kamalbahrin, H. M. Hanum, N. Abdullah, Noor Latiffah Adam, N. Kamal, Z. Bakar

{"title":"Industry Recommendation for Undergraduate Internship using Decision Tree","authors":"Intan Norsyafiqa Kamalbahrin, H. M. Hanum, N. Abdullah, Noor Latiffah Adam, N. Kamal, Z. Bakar","doi":"10.1109/ICOCO56118.2022.10031980","DOIUrl":"https://doi.org/10.1109/ICOCO56118.2022.10031980","url":null,"abstract":"The process of matching student profiles to industry profiles is critical to ensuring that students are placed in industries that are a good fit for their program. Therefore, to solve this problem, a system is presented that will give suggestions on suitable industrial types and internship placement from companies in the suggested industry for undergraduate students. This project maps student profiles from seven computer science programs and seven industrial types. There are 284 sample profiles collected from undergraduate students of Universiti Teknologi MARA. The profiles are gathered from previous records of placement for internship training. A decision tree model is constructed based on the sample profiles. The student’s Cumulative Grade Point Average (CGPA) and registered program are used as the main feature of industry recommendation. As a result, a web-based system for mapping students’ profiles to industries’ profiles has been developed. The application stores students’ and industries’ profiles and recommends suitable industries for each student’s profile.","PeriodicalId":319652,"journal":{"name":"2022 IEEE International Conference on Computing (ICOCO)","volume":"547 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116376108","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

A Comparative Study of Monolithic and Microservices Architectures in Machine Learning Scenarios 机器学习场景中单片和微服务架构的比较研究

2022 IEEE International Conference on Computing (ICOCO) Pub Date : 2022-11-14 DOI: 10.1109/ICOCO56118.2022.10031648

S. Kleftakis, Argyro Mavrogiorgou, N. Zafeiropoulos, Konstantinos Mavrogiorgos, Athanasios Kiourtis, D. Kyriazis

{"title":"A Comparative Study of Monolithic and Microservices Architectures in Machine Learning Scenarios","authors":"S. Kleftakis, Argyro Mavrogiorgou, N. Zafeiropoulos, Konstantinos Mavrogiorgos, Athanasios Kiourtis, D. Kyriazis","doi":"10.1109/ICOCO56118.2022.10031648","DOIUrl":"https://doi.org/10.1109/ICOCO56118.2022.10031648","url":null,"abstract":"Choosing the most suitable architecture for applications is not an easy decision. While the software giants have almost all put in place the microservices architecture, on smaller platforms such decision it is not so obvious. In the healthcare domain and specifically when accomplishing Machine Learning (ML) tasks in this domain, considering its special characteristics, the decision should be made based on specific metrics. In the context of the beHEALTHIER platform, a platform that is able to handle heterogeneous healthcare data towards their successful management and analysis by applying various ML tasks, such research gap was fully investigated. There has been conducted an experiment by installing the platform in three (3) different architectural ways, referring to the monolithic architecture, the clustered microservices architecture exploiting docker compose, and the microservices architecture exploiting Kubernetes cluster. For these three (3) environments, time-based measurements were made for each Application Programming Interface (API) of the diverse platform’s functionalities (i.e., components) and useful conclusions were drawn towards the adoption of the most suitable software architecture.","PeriodicalId":319652,"journal":{"name":"2022 IEEE International Conference on Computing (ICOCO)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114150868","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

ICOCO2022 Organizing Committees ICOCO2022组委会

2022 IEEE International Conference on Computing (ICOCO) Pub Date : 2022-11-14 DOI: 10.1109/icoco56118.2022.10031855

引用次数: 0

Experimental Analysis of U-Net and Mask R-CNN for Segmentation of Synthetic Liquid Spray U-Net和掩模R-CNN用于合成液体喷雾分割的实验分析

2022 IEEE International Conference on Computing (ICOCO) Pub Date : 2022-11-14 DOI: 10.1109/ICOCO56118.2022.10031951

Refat Khan Pathan, Wei Lun Lim, Sian Lun Lau, C. Ho, P. Khare, R. Koneru

引用次数: 1