Scientific Research Journal, Volume VIII, Issue VII, July 2020 Edition

Scientific Research Journal

Scirj Volume VIII, Issue VII, July 2020 Edition
ISSN: 2201-2796

Publication starts: 25th July 2020
Full Paper available from: 25th July 2020

AN ASSESSMENT OF ROLE OF FAITH-BASED ORGANIZATIONS IN NIGERIA DEMOCRACY
EMMANUEL ADELEKAN OJEWUNMI

Abstract: : This paper addresses the relationship that exists between democratic governance and faith-based organizations in Nigeria. The paper addresses to a certain extent, the relationship between the two main religions in Nigeria and democratic governance since 1999, with an analysis of the mutual impact one has had on the other, particularly how Christian and Islamic missions have influenced governance. The paper, using a historical method and instrument for data collection, analyses the various ways religious organizations have contributed to the stability of the democracy and identifies areas where they have failed to address the major problems confronting the country. It concludes that the faiths played a major role in the political construct and policymaking of some of the administrations.

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Page 1-11

LINE-OF-SIGHT UNDERWATER WIRELESS COMMUNICATION SYSTEM
Suleman M. Ali Shaban, Fathi Mohmed Omer Amer, Giuma Saleh Isa Abudagel

Abstract: Underwater optical wireless communication (UOWC) has a number of potential applications ranging from deep oceans to coastal waters. However, the greatest challenge for UOWC originates from the fundamental characteristics of sea water or ocean; tackling these challenges requires a detailed understanding of complex physio-chemical biological systems. There are numerous similarities between UOWC and free space optical (FSO) communications, mainly because both are using optical wavelengths to transfer secure information between dedicated point-to - point connections.

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Page 12-30

Vector bionomics, potential vectors and insecticide efficacy in malaria endemic areas, Ye Township, Mon State Myanmar
Maung Maung Mya, Sein Thaung, Nyan Sint, Yee Yee Myint, Sai Zaw Min Oo, Pae Phyo Kyaw, Di Lone and Yan Naung Maung Maung

Abstract: Vector bionomic and evaluation of insecticide efficacy were carried out in Koe Mine, Man Aung and 14 Mine areas of Ye Township, Mon State from July 2018 to August 2019 for better understanding of the Anopheles species distribution current insecticide susceptibility status and potential vector of malaria. Mosquitoes were collected using cattle baited net and light traps and larval survey was conducted in water well using WHO dipper. Standard WHO insecticide susceptibility was employed using field collected specimens. Results revealed that all total of 684 and 89 Anopheles mosquitoes consisted of 9 and 5 specie were collected from Koe Mine and Man Aung villages. Main vector An. minimus (6.58% & 3.37%) and Secondary vector An. maculatus (52.34%&37.08%) was collected in high density, An. philippinensis and An. jamesii adult was observed low density in both areas. Other species of An. willmori, An. annularis, An. kochi and An. aconitus were collected in Koe Mine village. All collected Anopheles mosquitoes were found sporozoite negative.

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Page 31-43

Modeling Students Performance using Cox and Parametric Accelerated Failure Time Models
Azme Khamis, Che Azmeeza Che Hamat & Mohd Asrul Affendi Abdullah

Abstract: This study explored the use of survival analysis to investigate the Bachelor’s degree students’ performance based on GPA, entrance qualification, faculty, and course. The study considered the application of semi-parametric and parametric Accelerated Failure Time (AFT) models. The main objectives of the study are to identify the covariates that dominate students’ performance via the Cox model, to investigate the performance of the Cox model based on the Proportional Hazard (PH) assumption, and to compare the performance of parametric AFT models using Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and Corrected Akaike Information Criterion (AICc). Results revealed that the Cox model suggested the covariates of GPA, faculty, entrance qualification, and the course had affected student performance. PH assumption in the Cox model was violated. This analysis concluded that the Cox model provided a less accurate estimate of student performance and further study should be conducted with parametric AFT models. In parametric AFT models, the Log-normal AFT was chosen as the best model and can be used as an alternative model for estimating student performance at universities and other similar higher educational institutions.

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Page 44-49

Knowledge and Utilization of Electronic Health Record in Healthcare Delivery in Kwadaso S.D.A Hospital, Kumasi
Kennedy Addo, Pabbi Kwaku Agyepong

Abstract: Background: There has been a lot of development in the healthcare industry and this development has led to a change in the tools being used by healthcare professionals in their field of work. The traditional paper-based medical record has been replaced with the Electronic Health Record (EHR). Objective: The main purpose of the study was to assess the knowledge and utilization of electronic health record in healthcare delivery in Kwadaso S.D.A Hospital, Kumasi.

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Page 50-56

STOCK PRICE FORECASTING BASED ON BACK PROPAGATION NEURAL NETWORK AND MARKOV CHAIN
Azme Bin Khamis & Li Chee Guan

Abstract: This study focused on the stock price prediction of an oil and gas exploration company in Malaysia. An artificial neural network that trained by back propagation algorithm or back propagation neural network (BPNN) as well as a hybrid model that combining back propagation neural network and Markov chain are used in this study. The main objective of this study is to compare the forecasting performance of the hybrid model and the BPNN model. The sample data is taken from 1st October 2018 to 30th September 2019. The main interest in this study is daily closing price, and the attributes are opening price, highest price, lowest price, trading volume, Brent crude oil price and OPEC oil price. The hybrid model is built by initialized the forecasting using back propagation neural network, followed by Markov state division, transition probability matrix formulation and prediction computation. Accordingly, both predictive models are compared by Mean Absolute Percentage Error (MAPE) and coefficient of determination R2. As a result, back propagation neural network is better than hybrid model because it showed a higher level of forecast accuracy with 0.5057% of MAPE and 95.94% of R2.

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Page 57-61