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A Cloud Based Electronic Office Framework for Ethiopian Public Universities (CBEOFEPU)
Gizatie Desalegn,
Mesfin Abebe,
Fisha Haileslassie,
Melese Kalayu
Issue:
Volume 6, Issue 1, March 2020
Pages:
1-9
Received:
11 December 2019
Accepted:
23 December 2019
Published:
6 January 2020
Abstract: An effective cloud-based electronic office management system plays a crucial role in delivering services in a better way. The main goal of this research is to create a smart environment, a digital workplace solution, good communication, and collaboration between employers and Ethiopian higher education institutions and to add some cloud computing capabilities to the electronic office. The proposed system is intended to better drive the effective development of Smart society and to advance a step into an era of the paperless, replace the previous manual handling of documents with an efficient electronic system. The study uses questionnaire, Interview, and observation data collection techniques and the developed prototype and proposed framework evaluate by different users, experts in software engineering and related fields. This study proposes a private cloud platform architecture for electronic office in Ethiopian public universities Software as a Service. The Cloud-Based Electronic Office Framework (CBEOF) adapts the IBM Cloud Reference Architecture (IBMCRA), the NIST Cloud Reference Architecture, and the Microsoft Web Application Architecture to take advantage of all the considerations and capabilities of a cloud-based software architecture.
Abstract: An effective cloud-based electronic office management system plays a crucial role in delivering services in a better way. The main goal of this research is to create a smart environment, a digital workplace solution, good communication, and collaboration between employers and Ethiopian higher education institutions and to add some cloud computing c...
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Data Analysis: Types, Process, Methods, Techniques and Tools
Issue:
Volume 6, Issue 1, March 2020
Pages:
10-15
Received:
11 December 2019
Accepted:
25 December 2019
Published:
6 January 2020
Abstract: The process of evaluating data using analytical and logical reasoning to examine each component of the data provided. This form of analysis is just one of the many steps that must be completed when conducting a research experiment. Data from various sources is gathered, reviewed, and then analyzed to form some sort of finding or conclusion. There are a variety of specific data analysis method, some of which include data mining, text analytics, business intelligence, and data visualizations. Data analysis is defined as a process of cleaning, transforming, and modeling data to discover useful information for business decision-making. The purpose of Data Analysis is to extract useful information from data and taking the decision based upon the data analysis. whenever we take any decision in our day-to-day life is by thinking about what happened last time or what will happen by choosing that particular decision. This is nothing but analyzing our past or future and making decisions based on it. For that, we gather memories of our past or dreams of our future. So that is nothing but data analysis. Now same thing analyst does for business purposes, is called Data Analysis. This research article based on data analysis, it’s types, process, methods, techniques & tools.
Abstract: The process of evaluating data using analytical and logical reasoning to examine each component of the data provided. This form of analysis is just one of the many steps that must be completed when conducting a research experiment. Data from various sources is gathered, reviewed, and then analyzed to form some sort of finding or conclusion. There a...
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On Modelling of Infant Mortality Rate in Nigeria with Exponentiated Cubic Transmuted Exponential Distribution
Issue:
Volume 6, Issue 1, March 2020
Pages:
16-22
Received:
11 December 2019
Accepted:
25 December 2019
Published:
6 January 2020
Abstract: The idea of introducing extra parameters into the existing model in enhancing more flexibility is a giant stride in research. Transmutation map technique is one of the recent methods of introducing additional properties such as skewness, kurtosis and bimodality into the baseline distribution. In this article, a new exponentiated exponential distribution is developed using transmutation map. This model is referred to as exponentiated cubic transmuted exponential distribution (ECTED). The mathematical properties of the model which include survival function, hazard function, central and non- central moments, moment generating function and order statistics are established. The inherent parameters in the model are estimated using method of maximum likelihood estimation (MLE). The system of equations obtained is non-linear in parameters therefore non-linear optimization algorithms are implemented in R package. The distribution is used to model data on infant mortality rate in Nigeria. The performance of the subject model is compared with its baseline exponential distribution (ED), transmuted exponential distribution (TED), exponentiated transmuted exponential distribution (ETED) and cubic transmuted exponential distribution (CTED) using Akaike Information criterion (AIC), Corrected Akaike Information criterion (AICC) and Bayesian Information criterion (BIC). It is hope that this will serve as an alternative distribution in modelling complex real life data arising from various fields of human endeavors.
Abstract: The idea of introducing extra parameters into the existing model in enhancing more flexibility is a giant stride in research. Transmutation map technique is one of the recent methods of introducing additional properties such as skewness, kurtosis and bimodality into the baseline distribution. In this article, a new exponentiated exponential distrib...
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Detection Mechanism for Malicious Messages on KSU Student Social Network
Rawan Almutlaq,
Alaaeldin Hafez
Issue:
Volume 6, Issue 1, March 2020
Pages:
23-36
Received:
8 December 2019
Accepted:
26 December 2019
Published:
8 January 2020
Abstract: The internet has a considerable effect on social relations and connections among people. Social networking platforms have been an enormous medium for establishing relations and connections among different people all over the world. People, organizations and companies use these platforms to communicate and interact with their communities and audience. These platforms have made it easy for people to share information, create content, and communicate and connect with others online; however, online interaction and communication among people have resulted in the creation of many problems. Malicious contents can easily be shared and populated to reach a wider audience than by using the traditional sharing methods. Detection mechanism is a growing area of research that can detect any inappropriateness of data that is more sensitive to malicious behavior. The detection mechanism needs to be involved in the analysis of the abusing messages posted on the Twitter account of King Saud University (KSU). Text mining is one approach that can be used to detect such malicious or abusing messages. Text mining techniques provide the means to perform data classification where messages can be classified into malicious and non-malicious messages. In addition, Sentiment Analysis is used to identify user tendencies, trends, and opinions by classifying a text into positive, negative and neutral. In this paper, we aim to provide a literature review to investigate the current techniques. The study also addresses the detection of malicious messages which identifies the behavior of malicious and abusive messages. Based on the extensive review of the current techniques, our focus is on the analysis of Arabic and English tweets on KSU’s Twitter account. First, data was collected from Twitter. This was followed by the preprocessing phase. Then, a corpus was produced applying a machine learning based approach by using Naive Bayes and Random Forest Classifier algorithms. Subsequently, the study focused on comparing the accuracy and performance of the Naive Bayes classifier with Random Forest Classifier algorithms in analyzing Arabic and English texts. In order to ensure reaching accurate results, Arabic and English tweets were analyzed.
Abstract: The internet has a considerable effect on social relations and connections among people. Social networking platforms have been an enormous medium for establishing relations and connections among different people all over the world. People, organizations and companies use these platforms to communicate and interact with their communities and audienc...
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Determinants of School Choice: Understanding How Parents’ Choose Primary School for Their Children in Arba Minch, Southern Ethiopia
Tilahun Bedaso Merga,
Belay Shobisso Sofamo
Issue:
Volume 6, Issue 1, March 2020
Pages:
37-43
Received:
11 December 2019
Accepted:
25 December 2019
Published:
8 January 2020
Abstract: Almost all parents want to educate their children in the best possible educational environment. Their decision to invest in children depends on a number of social, economic and cultural factors. Education in Ethiopia is offering by both public and private sector educational institutions. It is free of cost in public schools whereas in private schools, the parents have to bear the financial burden. For the last two decades private sector is emerging as an important source of imparting education in Ethiopia particularly in the study area. Many aspects regarding the education system of Ethiopia have been discussed in various studies so far. However, the factors which motivate the parents to make a decision about private sector are yet to be explored. The present study was conducted in Arba Minch town to scrutinize the factors which motivate the parents to educate their children in private schools. Primary data was collected for this purpose from 119 parents of elementary school students. The results were derived by using descriptive as well as inferential analysis. The logistic regression analysis suggests that parents’ perceptions play an important role in the school-choice decision. In particular, perceptions of school quality, cost of school, and teacher performance emerge as key determinants of private school choice. Additionally, age of the child, monthly income of household, distance from home to school, and numbers of children in family have a significant impact on parents’ probability of choosing a private school for their child. In the context of Ethiopia, we can therefore conclude that the school-choice decision is a combination of child, household and school characteristics. Moreover, these findings are important in unraveling the factors based on which parents decide which type of school to send their children.
Abstract: Almost all parents want to educate their children in the best possible educational environment. Their decision to invest in children depends on a number of social, economic and cultural factors. Education in Ethiopia is offering by both public and private sector educational institutions. It is free of cost in public schools whereas in private schoo...
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Application of Bayesian Approach Survival Analysis of Under-five Pneumonia Patients in Tercha General Hospital, South West Ethiopia
Lema Abate,
Megersa Tadesse
Issue:
Volume 6, Issue 1, March 2020
Pages:
44-52
Received:
9 December 2019
Accepted:
25 December 2019
Published:
16 January 2020
Abstract: Pneumonia is among the major killer diseases in under-five children in the world. In developing countries 3 million children die each year due to pneumonia. Ethiopia is one of the 15 pneumonia high burden countries. The aim of this study was to examine the risk factors of the survival time of under-five pneumonia patients using Bayesian approach analysis. Total of 281 under-five pneumonia patients included in this study. The parametric survival models such as Weibull, Lognormal and Log-logistic baseline distributions were used to fit the datasets by introducing prior distributions. The DIC value was used to compare the baseline distributions, and based on the DIC value the Weibull baseline distribution was selected as good model to fit under-five pneumonia dataset well. The results obtained from the Weibull survival model showed that patients from urban residence and patients who were admitted during patient nurse ratio (PNR) was small; were prolong timing death of under-five pneumonia patients, while patients who admitted during Spring and summer season, patients who suffer comorbidity and severe acute malnutrition (SAM) were shorten timing of death of under-five pneumonia patients. Factors such as sex, residence, Season of Diagnosis, Comorbidity, Severe Acute Malnutrition (SAM), Patient refer status and Patient to Nurse Ratio (PNR) were associated with the survival time of under-five pneumonia in this study. The concerned body should give attention for the factors identified in these study to prevent the mortality of under-five children due to pneumonia.
Abstract: Pneumonia is among the major killer diseases in under-five children in the world. In developing countries 3 million children die each year due to pneumonia. Ethiopia is one of the 15 pneumonia high burden countries. The aim of this study was to examine the risk factors of the survival time of under-five pneumonia patients using Bayesian approach an...
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