2020 2nd International Multidisciplinary Information Technology and Engineering Conference (IMITEC)最新文献

A Model for Wireless Signal Path Loss using Radiosity Technique 基于辐射度技术的无线信号路径损耗模型

2020 2nd International Multidisciplinary Information Technology and Engineering Conference (IMITEC) Pub Date : 2020-11-25 DOI: 10.1109/IMITEC50163.2020.9334133

Lindani Moyo, K. Sibanda, Nyashadzashe Tamuka

{"title":"A Model for Wireless Signal Path Loss using Radiosity Technique","authors":"Lindani Moyo, K. Sibanda, Nyashadzashe Tamuka","doi":"10.1109/IMITEC50163.2020.9334133","DOIUrl":"https://doi.org/10.1109/IMITEC50163.2020.9334133","url":null,"abstract":"There has been an explosion in the number of wireless devices and deployment of wireless networks. Successful deployment of wireless networks depends on proper planning and design. One of the important aspects during the planning phase is to determine the extent at which diffraction (scatter) and reflection of propagated signals has an influence on path loss. The best way to do so, is to model the signal's path loss as it travels from the emitter to the receiver. In this work we propose a model to predict path loss for wireless networks based on the radiosity method commonly implemented in the quest for realism in representing images in the computer graphics field. We created the radiosity path loss model and used it to compute I signal strength and path loss values at a varying distances. We also validated the model using an experiment carried out using inSSIDer software. The experiment was repeated twice to ascertain the consistence of results. At 95% level of confidence and 58 degrees of freedom, a t-student test revealed that the difference between obtained values for both experiments was insignificant. Hence the study showed that all values that were captured during each experiment were stable and reliable. The results further showed that our model accurately predicted path loss. This was demonstrated through curve fitting of the model results and the experimental result, which proved to be a best fit.","PeriodicalId":349926,"journal":{"name":"2020 2nd International Multidisciplinary Information Technology and Engineering Conference (IMITEC)","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116885530","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 Conceptual Model to Identify Vulnerable Undergraduate Learners at Higher-Education Institutions 一种识别高校本科弱势学习者的概念模型

2020 2nd International Multidisciplinary Information Technology and Engineering Conference (IMITEC) Pub Date : 2020-11-25 DOI: 10.1109/IMITEC50163.2020.9334103

Noluthando Mngadi, Ritesh Ajoodha, Ashwini Jadhav

{"title":"A Conceptual Model to Identify Vulnerable Undergraduate Learners at Higher-Education Institutions","authors":"Noluthando Mngadi, Ritesh Ajoodha, Ashwini Jadhav","doi":"10.1109/IMITEC50163.2020.9334103","DOIUrl":"https://doi.org/10.1109/IMITEC50163.2020.9334103","url":null,"abstract":"There is a growing concern around student attrition worldwide, including South African universities. More often than not, the reasons for students not completing their degree in the allocated time frame include academic reasons, socio-pschyo factors, and lack of effective transition from the secondary education system to the tertiary education systems. To overcome these challenges, the tertiary educational institutions endeavor to implement interventions geared toward academic success. One of the challenges, however, is identifying the vulnerable students in a timely manner. This study therefore aims to predict student performance by using a learner attrition model so that the vulnerable students are identified early on in the academic year and are provided support through effective interventions, thereby impacting student success positively. Predictive machine learning methods, such as support vector machines, decision trees, and logistic regression, were trained to deduce the students into four risk-profiles. A random forest outperformed other classifiers in predicting at-risk student profiles with an accuracy of 85%, kappa statistic of 0.7, and an AUC of 0.95. This research argues for a more complex view of predicting vulnerable learners by including the student's background, individual, and schooling attributes.","PeriodicalId":349926,"journal":{"name":"2020 2nd International Multidisciplinary Information Technology and Engineering Conference (IMITEC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125398160","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: 4

The Effectiveness of Collaboration Using the Hackathon to Promote Computer Programming Skills 利用黑客马拉松提高计算机编程技能的协作效果

2020 2nd International Multidisciplinary Information Technology and Engineering Conference (IMITEC) Pub Date : 2020-11-25 DOI: 10.1109/IMITEC50163.2020.9334089

Sakhumuzi Mhlongo, K. Oyetade, T. Zuva

{"title":"The Effectiveness of Collaboration Using the Hackathon to Promote Computer Programming Skills","authors":"Sakhumuzi Mhlongo, K. Oyetade, T. Zuva","doi":"10.1109/IMITEC50163.2020.9334089","DOIUrl":"https://doi.org/10.1109/IMITEC50163.2020.9334089","url":null,"abstract":"A model learning environment for a 21st-century Information Technology (IT) graduate comprises of both technical and soft skills. New trends are emerging on how to develop this technical and soft skills. Collaborative learning and social cognitive theory were adopted as a theoretical foundation for this study as limited studies have been done to find out which frameworks has been consistent to determine students' computer programming experience using the Hackathon. This paper aim to evaluate the effectiveness of collaboration in a Hackathon environment to learn Computer Programming (CP) among IT students. The objectives of the study are: (i) to examine the influence of collaboration on students' CP skills (ii) to examine the influence of Hackathon on students' computer programming skills (iii) to study the statistical association between collaborative learning and Hackathon on students' CP skills. 80 students participated in this study through a survey method and the responses was analyzed using SPSS software. The results of the study indicate that students were satisfied with their collaborative learning experience and believed that the Hackathon approach will help them in developing computer programming technical and soft skill. This study develops a model and contributes to empirical studies on Hackathon as most studies in this field are based on anecdotal findings.","PeriodicalId":349926,"journal":{"name":"2020 2nd International Multidisciplinary Information Technology and Engineering Conference (IMITEC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129627660","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: 10

A Review of Motion Segmentation: Approaches and Major Challenges 运动分割综述:方法和主要挑战

2020 2nd International Multidisciplinary Information Technology and Engineering Conference (IMITEC) Pub Date : 2020-11-25 DOI: 10.1109/IMITEC50163.2020.9334076

Jana Mattheus, Hans Grobler, Adnan M. Abu-Mahfouzl

引用次数: 7

Private Blockchain Networks: A Solution for Data Privacy 私有区块链网络:数据隐私的解决方案

2020 2nd International Multidisciplinary Information Technology and Engineering Conference (IMITEC) Pub Date : 2020-11-25 DOI: 10.1109/IMITEC50163.2020.9334132

Tyron Ncube, N. Dlodlo, A. Terzoli

引用次数: 6

Assessing the Impact of Personal Mobile Device in Higher Educational Enviroment: The case of Sol Plaatjie University 个人移动设备在高等教育环境中的影响评估:以中山大学为例

2020 2nd International Multidisciplinary Information Technology and Engineering Conference (IMITEC) Pub Date : 2020-11-25 DOI: 10.1109/IMITEC50163.2020.9334101

Christopher Thabo Ezekiel Makhoere, Osden Jokonya, Koga Gorejena

{"title":"Assessing the Impact of Personal Mobile Device in Higher Educational Enviroment: The case of Sol Plaatjie University","authors":"Christopher Thabo Ezekiel Makhoere, Osden Jokonya, Koga Gorejena","doi":"10.1109/IMITEC50163.2020.9334101","DOIUrl":"https://doi.org/10.1109/IMITEC50163.2020.9334101","url":null,"abstract":"Portable Mobile Device(PMD‘s) have the potential to elevate higher educational institutions(HEI), by the way in which students and lectures communicate using these devices thus presenting the students with perceptions of learning using these devices and also taking advantage of other platforms of social media for collaboration and self-directed learning. According to research studies on social media for learning, it has been found that new opportunities are created for innovative ideas and at the same time generating students of 21st Century. The emergence on the use of social platforms encourages active interaction of internet usage amongst students. However, opportunities for online networking and communities to facilitate multi-directional communication and knowledge exchange are offered by social media. Theories of social learning informs the design of participatory social interaction to support learning. In addition, the collection of data for this study was intended to be done through student focus group interviews. This was however not possible due to the recent decision of changing traditional learning(face-to-face) to online learning this current academic year, although this study was intentionally done to evaluate how mobile device will benefit on-line learning. It is argued in the reviewed literature that youth of the 21st century might have a tendency to resist traditional methods of teaching and learning. The usage of social platforms like WhatsApp, Facebook, Slack and others allows for interaction and sharing of experiences and interests on the web and are valuable for collaborative learning through constant internet connectivity. The findings of this study will be used to guide lecturing staff at SPU to identify social networking resources and other emerging technologies for the delivery of learning content that are freely and instantaneously available to students.","PeriodicalId":349926,"journal":{"name":"2020 2nd International Multidisciplinary Information Technology and Engineering Conference (IMITEC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117297655","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

Malware Classification using Deep Learning Technique 基于深度学习技术的恶意软件分类

2020 2nd International Multidisciplinary Information Technology and Engineering Conference (IMITEC) Pub Date : 2020-11-25 DOI: 10.1109/IMITEC50163.2020.9334071

Olufikayo Olowoyo, P. Owolawi

引用次数: 4

Handling BigInteger Computations in the Implementation of the RSA Model 处理RSA模型实现中的大整数计算

2020 2nd International Multidisciplinary Information Technology and Engineering Conference (IMITEC) Pub Date : 2020-11-25 DOI: 10.1109/IMITEC50163.2020.9334094

Nemuramba Denzhe, C. Chibaya

{"title":"Handling BigInteger Computations in the Implementation of the RSA Model","authors":"Nemuramba Denzhe, C. Chibaya","doi":"10.1109/IMITEC50163.2020.9334094","DOIUrl":"https://doi.org/10.1109/IMITEC50163.2020.9334094","url":null,"abstract":"Developing systems that can handle very large integers is challenging, especially if we are trapped in using some of the well-known programming languages such as VB, C++, Delphi, or Java. Their numeric data types have defined finite ranges. Innovative methods are required to enable the handling of large integer over and above the ranges supported by available primitive data types. Implementation of the RSA model is a typical case where very large integers are used. This paper investigates incorporation of very large integers into the implementation of the RSA model. We precisely describe parts of the RSA algorithm where such innovations are sought and how the concept of the BigInteger class fits in. Our illustrations assume programming in Java. While the BigInteger class is available for use in mathematical procedures involving very large integral sums beyond the limits of the appropriate basic data type, developers either do not or rarely use the class due to lack of functional examples of where such libraries were used. This paper provides valuable insights into the potential advent of new data types. These insights provide basic insights into the potential need for new developments in programming languages, especially the need to invent even larger types of numerical data types in programming languages. In our views, this work in progress offers foundational views towards implementation of better siblings of the RSA model.","PeriodicalId":349926,"journal":{"name":"2020 2nd International Multidisciplinary Information Technology and Engineering Conference (IMITEC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127240674","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

Educational Data-mining to Determine Student Success at Higher Education Institutions 教育数据挖掘决定学生在高等教育机构的成功

2020 2nd International Multidisciplinary Information Technology and Engineering Conference (IMITEC) Pub Date : 2020-11-25 DOI: 10.1109/IMITEC50163.2020.9334139

Ndiatenda Ndou, Ritesh Ajoodha, Ashwini Jadhav

{"title":"Educational Data-mining to Determine Student Success at Higher Education Institutions","authors":"Ndiatenda Ndou, Ritesh Ajoodha, Ashwini Jadhav","doi":"10.1109/IMITEC50163.2020.9334139","DOIUrl":"https://doi.org/10.1109/IMITEC50163.2020.9334139","url":null,"abstract":"The expansion of enrolments in South African higher education institutions has not been accompanied by a proportional increase in the percentage of students who graduate. This is an ongoing problem faced by the Department of Higher Education and Training in South Africa (DHET). In their 2020 undergraduate cohort studies, DHET reported that the percentage of first time entering students graduating in minimum allocated time from 3 year degrees has remained low, ranging between 25.7% and 32.2%, for the academic years 2000 to 2017. This indicates students are struggling in higher education, as more than 60% of students being admitted by the system are consistently not completing their chosen field of study in the allotted time. In this study, we introduce an approach that involves prediction of student performance at each year of study until qualifying, for students at a South African higher education institution. The present study applies various classification techniques to a synthetic data-set, generated by a Bayesian network, with the aim to show that these classifiers can be used to predict student performance in advance with the aim to promote student success and avoid the negative consequences of students struggling to complete their studies or dropping-out altogether.","PeriodicalId":349926,"journal":{"name":"2020 2nd International Multidisciplinary Information Technology and Engineering Conference (IMITEC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132099389","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: 5

Support Vector Machine Prediction Model: Students' Protests in South Africa 支持向量机预测模型:南非学生抗议

2020 2nd International Multidisciplinary Information Technology and Engineering Conference (IMITEC) Pub Date : 2020-11-25 DOI: 10.1109/IMITEC50163.2020.9334074

Wandisa Mfenguza, K. Sibanda

{"title":"Support Vector Machine Prediction Model: Students' Protests in South Africa","authors":"Wandisa Mfenguza, K. Sibanda","doi":"10.1109/IMITEC50163.2020.9334074","DOIUrl":"https://doi.org/10.1109/IMITEC50163.2020.9334074","url":null,"abstract":"Higher Education has a role of developing the socioeconomic status of nations through human capital development, building and use of knowledge as well as research development. Since the inception of South African democracy, the vision of the South African government has been to realize ‘a better life for all’ through economic development by regenerating an entire social system through production of skilled graduates. This drive was accomplished by implementation of the Reconstruction and Development Program (RDP) introduced in 1994. Despite the government's efforts, it is however alarming to see the higher education sector in shambles due to student protests. The student protests result to destruction of university infrastructure and are affecting students' academic performance negatively. The protests do not only affect academic activities, but also impact the South African economy negatively due to the bad publicity that is presented by the protests. Developing models that would predict the students' protests would be a positive contribution towards prevention of such protests. Machine learning techniques are well known for producing accurate predictive models. This study therefore explored machine learning techniques to build a students' protests prediction model. The study used support vector machine technique for the implementation. Data collected from news articles and social media was used to train and test the prediction model. The accuracy of the prediction model was evaluated using split validation technique. The results of the study indicated that the proposed algorithm can accurately model the prediction of the students' strikes. The orchestrated experiments involved comparing the accuracy of two SVM kernels, viz, the RBF and the Linear kernels. The results have revealed that the RBF kernel remarkably outperforms the linear kernel.","PeriodicalId":349926,"journal":{"name":"2020 2nd International Multidisciplinary Information Technology and Engineering Conference (IMITEC)","volume":"170 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122571277","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