2019 International Conference on Computing, Computational Modelling and Applications (ICCMA)最新文献_第3页

Comparative Evaluation of Asymmetric Price Transmission Linear Models Using rMDL, eMDL, nMDL, gMDL, AIC and BIC Across Varying Sample Sizes 不同样本量下rMDL、eMDL、nMDL、gMDL、AIC和BIC的非对称价格传导线性模型比较评价

2019 International Conference on Computing, Computational Modelling and Applications (ICCMA) Pub Date : 2019-03-01 DOI: 10.1109/ICCMA.2019.00030

I. K. Amponsah, H. Acquah, Nathaniel K. Howard

{"title":"Comparative Evaluation of Asymmetric Price Transmission Linear Models Using rMDL, eMDL, nMDL, gMDL, AIC and BIC Across Varying Sample Sizes","authors":"I. K. Amponsah, H. Acquah, Nathaniel K. Howard","doi":"10.1109/ICCMA.2019.00030","DOIUrl":"https://doi.org/10.1109/ICCMA.2019.00030","url":null,"abstract":"The Minimum Description Length (MDL), a less known criterion, is making great strides in model selection as compared to the widely known and used information criteria (AIC, BIC, etc). This study developed the MDL criterion using R-functions to evaluate Asymmetric Price Transmission (APT) models (Complex, Standard and Houck’s) for the first time ever. All six criteria’s ability to recover the true DGP was assessed under the condition of varying sample size. A 1000 Monte Carlo simulation procedure revealed that the MDL criteria on the average points to the true DGP and are comparable (if not better) to both AIC and BIC under study condition. Generally, the performances of all model selection criteria (rMDL, nMDL, gMDL, eMDL, AIC and BIC) improved with increasing sample size in their ability to recover the true DGP for both standard and complex models. This study recommends the use of MDL criterion in model selection and in the light of constraint (financial, time and inadequate resources), a sample size of 150 is sufficient in making sound decisions on asymmetric price models.","PeriodicalId":413965,"journal":{"name":"2019 International Conference on Computing, Computational Modelling and Applications (ICCMA)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132076869","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: 3

Using Decision Tree Classification Algorithm to Predict Learner Typologies for Project-Based Learning 基于项目的学习中使用决策树分类算法预测学习者类型

2019 International Conference on Computing, Computational Modelling and Applications (ICCMA) Pub Date : 2019-03-01 DOI: 10.1109/ICCMA.2019.00029

E. Gyimah, D. K. Dake

{"title":"Using Decision Tree Classification Algorithm to Predict Learner Typologies for Project-Based Learning","authors":"E. Gyimah, D. K. Dake","doi":"10.1109/ICCMA.2019.00029","DOIUrl":"https://doi.org/10.1109/ICCMA.2019.00029","url":null,"abstract":"As educational data in tertiary institutions are becoming huge, it is important to deploy Data Mining algorithms in discovering knowledge and improving academic quality. One fast course delivery approach or trend, constructivism in higher education is based on Learner prioritization in the learning process where a learner transforms information, constructs hypothesis and makes decisions using mental models. Similar learner groupings for project-based learning through hidden patterns extraction can aid Active Learning and Instructor Monitoring. In our previous paper, K-means clustering algorithm was used to group learners with similar scores in three assessments. In this paper, we built a classifier model using the J48 Decision Tree Algorithm for predicting learner groupings after getting class labels through the K-means clustering algorithm. This classifier will help in predicting future groupings of learners for the same course and attributes. The weka simulation for the classifier model gave a 99.9% ROC Area curve, which indicates a general performance of the model and a 96.19% of correctly classified instances. The Confusion Matrix has 80% of the members correctly classified. The classification model has an extremely low FP Rate of 2%, another indication of a high performance predictive classifier.","PeriodicalId":413965,"journal":{"name":"2019 International Conference on Computing, Computational Modelling and Applications (ICCMA)","volume":"255 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133618212","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

Investigating the Actual usage of Learning Management System: From Perspectives of University Students 学习管理系统的实际使用情况调查:以大学生为视角

2019 International Conference on Computing, Computational Modelling and Applications (ICCMA) Pub Date : 2019-03-01 DOI: 10.1109/ICCMA.2019.00008

Charles Buabeng-Andoh, Charles Baah

{"title":"Investigating the Actual usage of Learning Management System: From Perspectives of University Students","authors":"Charles Buabeng-Andoh, Charles Baah","doi":"10.1109/ICCMA.2019.00008","DOIUrl":"https://doi.org/10.1109/ICCMA.2019.00008","url":null,"abstract":"This study investigated university students' actual use of learning management system using Unified Theory of Acceptance and Use of Technology (UTAUT) model. Quantitative and qualitative research strategies were adopted using close-ended and open-ended questionnaire to collect data from 149 students who were learning management system (LMS) users. Random sampling approach was used to select the students. The quantitative data were analyzed using structural equation model and the qualitative data were analyzed using thematic analysis. The results from quantitative analysis showed that performance expectancy, effort expectancy and institutional support influenced students' actual use of LMS while social influence and infrastructure support did not influence students' actual use. But, the results from qualitative analysis found lack of training, unavailability of internet connection and poor electricity supply as major concerns that affect students' actual usage of LMS. This study contributed to the current discussion on use of UTAUT to explain students' actual use of technology in developing countries. Implications, limitations and future studies were discussed.","PeriodicalId":413965,"journal":{"name":"2019 International Conference on Computing, Computational Modelling and Applications (ICCMA)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122879449","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: 3

Nodal Authentication of IoT Data Using Blockchain 使用区块链的物联网数据节点认证

2019 International Conference on Computing, Computational Modelling and Applications (ICCMA) Pub Date : 2019-03-01 DOI: 10.1109/ICCMA.2019.00028

B. Asare, Kester Quist-Aphetsi, Laurent Nana

引用次数: 6

A Decentralized Cryptographic Blockchain Approach for Health Information System 健康信息系统的去中心化加密区块链方法

2019 International Conference on Computing, Computational Modelling and Applications (ICCMA) Pub Date : 2019-03-01 DOI: 10.1109/ICCMA.2019.00027

Rexford Nii Ayitey Sosu, Kester Quist-Aphetsi, Laurent Nana

引用次数: 9