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E-Governance Systems: A Case Study of the Development of a Small-Scale Farmer Database 电子政务系统:以小农数据库开发为例

Zambia ICT Journal Pub Date : 2018-06-29 DOI: 10.33260/ZICTJOURNAL.V2I1.41

Alinani Simukanga, J. Phiri, Mayumbo Nyirenda, Monica Kalumbilo-Kabemba

引用次数: 6

Forecasting Seasonal Rainfall in Zambia – An Artificial Neural Network Approach 预测赞比亚的季节性降雨——一种人工神经网络方法

Zambia ICT Journal Pub Date : 2018-06-29 DOI: 10.33260/ZICTJOURNAL.V2I1.46

Lillian Mzyece, Mayumbo Nyirenda, Monde K. Kabemba, Grey Chibawe

{"title":"Forecasting Seasonal Rainfall in Zambia – An Artificial Neural Network Approach","authors":"Lillian Mzyece, Mayumbo Nyirenda, Monde K. Kabemba, Grey Chibawe","doi":"10.33260/ZICTJOURNAL.V2I1.46","DOIUrl":"https://doi.org/10.33260/ZICTJOURNAL.V2I1.46","url":null,"abstract":"Weather forecasting is an ever-challenging area of investigation for scientists. It is the application of science and technology in order to predict the state of the atmosphere for a given time and location. Rainfall is one of the weather parameters whose accurate forecasting has significant implications for agriculture and water resource management. In Zambia, agriculture plays a key role in terms of employment and food security. Rainfall forecasting is one of the most complicated and demanding operational responsibilities carried out by meteorological services all over the world. Long-term rainfall prediction is even more a challenging task. It is mainly done by experts who have gained sufficient experience in the use of appropriate forecasting techniques like modelling. It is mainly done by experts who have gained sufficient experience in the use of appropriate forecasting techniques like modelling. In this paper, a rainfall forecasting model using Artificial Neural Network is proposed as a model that that can be 'trained' to mimic the knowledge of rainfall forecasting experts. This makes it possible for researchers to adapt different techniques for different stages in the forecasting process. We begin by noting the five main stages in the seasonal rainfall forecasting process. We then apply artificial neural networks at each step. Initial results show that the artificial neural networks can successfully replace the currently used processes together with the expert knowledge. We further propose the use of these neural networks for teaching such forecasting processes, as they make documentation of the forecasting process easier and hence making the educational process of teaching to forecast seasonal rainfall easier as well. Artificial Neural Networks are reliable, handle more data at one time by virtual of being computer based, are less tedious and less dependent on user experience.","PeriodicalId":206279,"journal":{"name":"Zambia ICT Journal","volume":"18 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132898499","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

Gaps in the Management and Use of Biometric Data: A Case of Zambian Public and Private Institutions 生物识别数据管理和使用的差距:赞比亚公共和私人机构的案例

Zambia ICT Journal Pub Date : 2018-06-29 DOI: 10.33260/ZICTJOURNAL.V2I1.49

Melissa K. Chinyemba, J. Phiri

{"title":"Gaps in the Management and Use of Biometric Data: A Case of Zambian Public and Private Institutions","authors":"Melissa K. Chinyemba, J. Phiri","doi":"10.33260/ZICTJOURNAL.V2I1.49","DOIUrl":"https://doi.org/10.33260/ZICTJOURNAL.V2I1.49","url":null,"abstract":"The current physical and cybersecurity systems rely on traditional three-factor authentication to mitigate the threats posed by insider attacks. Key is the use of biometric information. Biometrics are a unique measurement and analysis of the unique physiological special traits such as voice, eye structure and others that can be used in the discipline of varying person identification. Biometry, which is the analysis of these biometrics is a complex process but guarantees identification and non-repudiation. If used to identify humans then several issues such as where is the biometric data stored? Who has access to it? And how does one ensure that such data satisfies the principle of availability. To achieve availability, secure transportation arises. To achieve transportation, non-repudiation, confidentiality and authentication, integrity arise. A storage and transport system is recommended to these challenges. In this paper, we explore the gaps into how public and private institution store and manage biometrics information. We benchmarked each organization again the ISO 30107 and ISO 24745. Our results show that while most companies are adopting and using biometrics systems, few have adopted the ISO biometrics standards that govern the storage and management of biometric information and hence creating security risk.","PeriodicalId":206279,"journal":{"name":"Zambia ICT Journal","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116804618","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

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