2022 1st Zimbabwe Conference of Information and Communication Technologies (ZCICT)最新文献_第3页

An Assessment of the Independence Gap in the Zimbabwean ICT Regulatory Framework 津巴布韦ICT监管框架中独立性差距的评估

2022 1st Zimbabwe Conference of Information and Communication Technologies (ZCICT) Pub Date : 2022-11-09 DOI: 10.1109/ZCICT55726.2022.10045846

Casper Chigwedere, Sam Takavarasha, B. Chisaka

引用次数: 0

Understanding E-learning Adoption and Acceptance during the Covid 19 Pandemic: The Influence of Self Efficacy 新冠肺炎疫情期间在线学习的采用和接受:自我效能感的影响

2022 1st Zimbabwe Conference of Information and Communication Technologies (ZCICT) Pub Date : 2022-11-09 DOI: 10.1109/ZCICT55726.2022.10046037

Fine Masimba, Kudakwashe Maguraushe

{"title":"Understanding E-learning Adoption and Acceptance during the Covid 19 Pandemic: The Influence of Self Efficacy","authors":"Fine Masimba, Kudakwashe Maguraushe","doi":"10.1109/ZCICT55726.2022.10046037","DOIUrl":"https://doi.org/10.1109/ZCICT55726.2022.10046037","url":null,"abstract":"The world wide outbreak of the COVID-19 pandemic reconfigured various landscapes in higher education as various institutions, lecturers and students were forced to adopt e-learning. However, the successful adoption and acceptance of e-learning by both lecturers and students involved has not been discussed and measured. This study seeks to investigate the influence of both the lecturer and student self efficacy on behavoral intention to use e-learning during the pandemic in the context of the Technology Acceptance Model (TAM). Lecturer Self-Efficacy (LSE) and Student Self-Efficacy (SSE) were hypothesized to have a correlation with the perceived usefullness and perceived ease of use of e-learning systems as well as the attitude towards using those e-learning systems which resultantly influence the behavoural intention to use e-learning systems. A total of 362 questionnaires were received from both students and lecturers in Zimbabwe’s two universities and two polytechnics. Structural Equation Modelling was utilized to test the hypothesized conceptual model. Reliability and validity checks were done to the model instrument. Results indicated that both LSE and SSE have a positive influence on perceived ease of use but however, both LSE and SSE revealed a negative influence on perceived usefullness. Results also indicated that both LSE and SSE have a positive influence on attitude towards use of e-learning systems. The findings of the study contribute to the literature by highlighting the influence of LSE and SSE in the adoption and acceptance of e-learning systems in higher education.","PeriodicalId":125540,"journal":{"name":"2022 1st Zimbabwe Conference of Information and Communication Technologies (ZCICT)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121135139","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

ZCICT 2022 Cover Page ZCICT 2022封面

2022 1st Zimbabwe Conference of Information and Communication Technologies (ZCICT) Pub Date : 2022-11-09 DOI: 10.1109/zcict55726.2022.10045968

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Intrusion Detection System for IoT environments using Machine Learning Techniques 使用机器学习技术的物联网环境入侵检测系统

2022 1st Zimbabwe Conference of Information and Communication Technologies (ZCICT) Pub Date : 2022-11-09 DOI: 10.1109/ZCICT55726.2022.10045992

Shammah Chishakwe, Nesisa Moyo, Belinda Mutunhu Ndlovu, Sibusisiwe Dube

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Blended Learning Approach: Students’ versus Lecturers’ Views from a South African Rural University 混合式学习方法:来自南非农村大学的学生与教师的观点

2022 1st Zimbabwe Conference of Information and Communication Technologies (ZCICT) Pub Date : 2022-11-09 DOI: 10.1109/ZCICT55726.2022.10045969

Nosipho Mavuso, N. Jere

{"title":"Blended Learning Approach: Students’ versus Lecturers’ Views from a South African Rural University","authors":"Nosipho Mavuso, N. Jere","doi":"10.1109/ZCICT55726.2022.10045969","DOIUrl":"https://doi.org/10.1109/ZCICT55726.2022.10045969","url":null,"abstract":"There is a current paradigm shift within institutions of higher learning in terms of how teaching and learning take place. This radical transition has been forced globally as a result of the Covid-19 pandemic, which saw the higher education sector implementing drastic changes in terms of remote learning. It seems there is a misunderstanding of the term blended learning based on the students’ and lecturers’ views from a selected South African university. A mixed method approach was used to collect both qualitative and quantitative data. An online questionnaire was distributed to learners to get quantitative data. On the other hand, lecturers were engaged through interviews within a workshop. An experimental approach using the university’s learning management system known as WiseUp was used. Both traditional and online modes of deliverables are common within a case. Findings show different understanding of the term blended learning and the differences in preferred activities within the blended mode. The paper provides some examples of good applications of blended learning. As higher education institutions try to embrace blended learning techniques, there is a need to engage and improve awareness of the meaning of this approach.","PeriodicalId":125540,"journal":{"name":"2022 1st Zimbabwe Conference of Information and Communication Technologies (ZCICT)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134377409","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

Snake Identification System Using Convolutional Neural Networks 基于卷积神经网络的蛇识别系统

2022 1st Zimbabwe Conference of Information and Communication Technologies (ZCICT) Pub Date : 2022-11-09 DOI: 10.1109/ZCICT55726.2022.10046005

S. Dube, Admire Bhuru

{"title":"Snake Identification System Using Convolutional Neural Networks","authors":"S. Dube, Admire Bhuru","doi":"10.1109/ZCICT55726.2022.10046005","DOIUrl":"https://doi.org/10.1109/ZCICT55726.2022.10046005","url":null,"abstract":"Computer vision has recently been dominated by Convolutional Neural Networks (CNNs), these are a kind of Artificial Neural Networks (ANNs) mostly employed for image classification and object detection. Identifying a snake species is important when interacting with the species as well as when treating injuries due to envenoming. This task however proves to be a hurdle for the general public. This paper, therefore, sought to solve the problem of misidentification of snake species which often leads to envenoming, and mishandling of snake species by harnessing the power of CNNs together with the portability of mobile devices in developing a mobile application that identifies snake species from images almost in real-time. In implementing this system, the CNN model was trained in Google Collab on a custom-tailored dataset. The images in the dataset were sourced from the internet, and were divided into eight classes which represented eight different snake species. The images were annotated using MakeSense.ai, an online data annotation tool. After annotation the images were piped into the YOLOv5 CNN model on Google Collab for model training. The training process yielded an accuracy of 71% for all the eight classes. After training, the model was converted to a Tensorflow Lite model and exported to Android Studio IDE wherein the rest of the application was developed using Java programming language.","PeriodicalId":125540,"journal":{"name":"2022 1st Zimbabwe Conference of Information and Communication Technologies (ZCICT)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134419678","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

Queue Modelling and Jitter Control in Mobile Ad Hoc Networks 移动自组织网络中的队列建模与抖动控制

2022 1st Zimbabwe Conference of Information and Communication Technologies (ZCICT) Pub Date : 2022-11-09 DOI: 10.1109/ZCICT55726.2022.10046032

B. Nyambo, G. Janssens, Hillary Marufu, M. Munyaradzi, Bernard Mapako, Kaitano Dzinavatonga

{"title":"Queue Modelling and Jitter Control in Mobile Ad Hoc Networks","authors":"B. Nyambo, G. Janssens, Hillary Marufu, M. Munyaradzi, Bernard Mapako, Kaitano Dzinavatonga","doi":"10.1109/ZCICT55726.2022.10046032","DOIUrl":"https://doi.org/10.1109/ZCICT55726.2022.10046032","url":null,"abstract":"Jitter in multimedia traffic is mainly introduced by variations in network characteristics. Ifjitter is so significant in the application that is receiving, this can result in a degraded performance in real-time multimedia communications applications. Jitter causes inaudible audio or unclear video which can be undesirable and uncomfortable to the user. Buffers are often employed to temporarily to store arriving packets before playing them at equal intervals to curb and minimize jitter. Jitter for voice packets should not exceed 20-50 milliseconds within a given stream. This paper proposes a method to reducejitter in intermediate nodes is proposed, such that when the packets arrive at the receiving end, there would be little or nojitter to process in the de-jitter buffer. We analyze M/G/1 nonpreemptive and pre-emptive resume priority queuing in the intermediate node and analyze how these models will affect delay and jitter. We found out that preemptive priority queuing performs better but almost the same to non-preemptive priority queuing. Both Priority based queues performed much better than the First in First out queue.","PeriodicalId":125540,"journal":{"name":"2022 1st Zimbabwe Conference of Information and Communication Technologies (ZCICT)","volume":"253 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115415229","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

Virtual Technologies for Tourism Promotion in Zimbabwe 津巴布韦旅游推广的虚拟技术

2022 1st Zimbabwe Conference of Information and Communication Technologies (ZCICT) Pub Date : 2022-11-09 DOI: 10.1109/ZCICT55726.2022.10046006

Wellington Tatenda Gwavava, David I. Fadaraliki, Prudence Kadebu

引用次数: 0

A comparative analysis of the effectiveness of feature engineering techniques on thyroid disease prediction 特征工程技术在甲状腺疾病预测中的有效性对比分析

2022 1st Zimbabwe Conference of Information and Communication Technologies (ZCICT) Pub Date : 2022-11-09 DOI: 10.1109/ZCICT55726.2022.10045927

Aidah Mashonga, Leslie KudzaiNyandoro, Kudakwashe Zvarevashe

{"title":"A comparative analysis of the effectiveness of feature engineering techniques on thyroid disease prediction","authors":"Aidah Mashonga, Leslie KudzaiNyandoro, Kudakwashe Zvarevashe","doi":"10.1109/ZCICT55726.2022.10045927","DOIUrl":"https://doi.org/10.1109/ZCICT55726.2022.10045927","url":null,"abstract":"The thyroid gland’s edge experiences an abnormal proliferation of thyroid tissue, which causes thyroid illness. The two primary types of thyroid disorders are hypothyroidism and hyperthyroidism which typically result when this gland releases excessive amounts of hormones. To identify and diagnose thyroid disease, this study suggests employing effective classifiers and feature selection strategies that consider accuracy and other performance evaluation measures. This study offers a thorough examination of various classifiers that includes the support vector machine, logistic regression, and extreme gradient boosting algorithms. The algorithms use three feature removal strategies that is recursive feature elimination, Pearson’s correlation and chi-squared statistics. To determine thyroid illness, thyroid data from the Kaggle datasets were used. Numerous aspects of the experiment have been evaluated and analyzed, including accuracy, precision, and the receiver operating curve’s area under the curve. The outcome showed that classifiers that use feature selection have a greater overall accuracy(Xtreme Gradient Boost 98%and support vector machine 95%) compared to without feature selection technique (support vector machine 89%). Logistics regression performed better without at 95% than 94% with feature selection.","PeriodicalId":125540,"journal":{"name":"2022 1st Zimbabwe Conference of Information and Communication Technologies (ZCICT)","volume":"362 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122058587","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

Fake News Detection using 5L-CNN 使用5L-CNN进行假新闻检测

2022 1st Zimbabwe Conference of Information and Communication Technologies (ZCICT) Pub Date : 2022-11-09 DOI: 10.1109/ZCICT55726.2022.10045981

Demo Rangarirai Collen, Leslie Kudzai Nyandoro, Kudakwashe Zvarevashe

{"title":"Fake News Detection using 5L-CNN","authors":"Demo Rangarirai Collen, Leslie Kudzai Nyandoro, Kudakwashe Zvarevashe","doi":"10.1109/ZCICT55726.2022.10045981","DOIUrl":"https://doi.org/10.1109/ZCICT55726.2022.10045981","url":null,"abstract":"With the advent of websites and social media technologies, the internet has been a great method of transmitting news and information around the globe. However, due to lack of editorial scrutiny and monitoring by the media authorities, the news distribution has been seriously abused leading to the fast spreading of fake news. Fake news involves misleading broadcasting of information from sources that target to intentionally manipulate the way how people view some events or statements. This study seeks to develop a fake news detection model which will be able to analyze the title and text information attached to the news articles. From the researches done by previous scholars, it showed that the models did not perform very well because of the lack of sufficient feature extraction and fine tuning of the classification of the text. This research will therefore, articulate the gap by employing 5L-CNN deep learning model which will use inbuilt tokenizers for word embedding and will show better accuracy compared to the traditional machine learning models. In this paper, we compare machine learning algorithms (Decision trees, Random Forest, Logistic Regression & Naive Bayes) and deep learning algorithms (RNN, 5L-CNN & LSTM) to classify the authenticity of news articles. The model developed in this paper attained the best accuracy with 5L-CNN which had a result of 99.99%.","PeriodicalId":125540,"journal":{"name":"2022 1st Zimbabwe Conference of Information and Communication Technologies (ZCICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129194035","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