Harvard Int’l Journal of Pure and Applied Science (IJPAS) Vol.10 (1) June, 2019


Harvard International Journal of Pure and Applied Science (HIJPAS)

Vol.10 (1) June, 2019 Editions ISSN: 0465 – 7508

 



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Harvard College, 86 Brattle Street Cambridge,

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BANDWIDTH REDUCTION OF VIDEO COMPRESSION USING ANN FOR VIRTUAL MULTIMEDIA

 

PRAKASH JADHAV, SHELJA PANDEY, NANDINI N, SPOORTHI G N, SAI ESHWAR K R & DR. PRAKASH JADHAV,

MVJ College of Engineering, Visvesvaraya Technological University, Bangalore.

 

Abstract

Video compression is the term used to define a method for reducing the data used to encode digital video content. This reduction in data translates to benefits such as smaller storage requirements and low transmission bandwidth requirements for a clip of video content. For example: one colour movie video without compression contains 720*480 pixels per frame with 30 frames per sec resulting in total time 90 min. The total quantity of data = 167.96 GB. The compression technique we have adopted is the adaptive slope of activation function in the supervised learning algorithm for multi-layer feed forward neural networks for bandwidth based demand of video compression in multimedia based applications.

Keywords: Artificial Neural Networks, Feed Forward Neural Networks, LevenbergMarquardt, Back Propagation, Adaptive Slope Based Architecture (ADSL), Fixed Slope of Activation Function (FXSL).

 

 

ANALYSIS OF THE RELIABILITY OF ONLINE MONITORING SOFTWARE TOWARDS THE ENCOURAGEMENT OF REMOTE SEX OFFENDER ADMINISTRATION IN DEVELOPING NATIONS

 

*ADEDAYO M. BALOGUN & **JO DRUMMOND-CHILD

*Department of Computer Science, University of Ilorin, P.M.B 1515, Nigeria **Department of Law, University of Derby, DE22 1GB, United Kingdom

 

Abstract

 

As compromises have become understandably expected of new and improved technologies, the advent of computers and internet has brought about a fearsome prevalence of electronic crimes. Sex-related offences account for the most frequently occurring electronic crimes, after hacking and identity theft. However, laws such as Nigeria’s new Cybercrime Act 2015 melt out prison sentences, whereas the UK’s Sexual Offences Act 2003 places convicted offenders under internet usage restrictions which activists have still regarded as infringement on human rights. Hence, the institution of remote monitoring tools to ensure that offenders stay within pre-defined confines while using internet in their homes was regarded a desirable concession. This paper takes on the task to thoroughly analyse the effectiveness of these tools, with the objective of ascertaining their limitations and sufficiencies to legislators and investigators of developing nations for adoption. A combination of the scientific verification and case study methodologies are employed in this study to assign rankings to select tools. However, a more comprehensive investigation using hands-on digital forensic procedures and software field tests, as well as analysis & illustration of facts elicited from probation officers and digital forensic consultants is proposed towards a future study.

Keywords: Cybercrime, Remote Monitoring, Child Pornography, Automated Offender Management, Child Abuse

 

 

THE EFFECT OF ELEVATED TEMPERATURE ON ULTRA – HIGH STRENGTH CONCRETE

 

*GANA A.J. *OLUWAGBENGA S.B. **OLONI.E.F **ADEWARA S.O.  ***ABOLUSORO A. A.

*Civil Engineering Department, Landmark University Omu Aran, Kwara State. **Department of Economics, Landmark University, Omu-Aran, Kwara State ***College of Agricultural Science, Landmark University, Omu-Aran, Kwara State

 

Abstract

The need for improvement on our construction materials arises each day as technology and demands for more complex structures increases day to day. Different materials have been developed and added to the concrete for the improvement in its strength. Some of these materials are readily available around us, lying as waste and could be recycled at minimum costs and efforts. Rice husk ash is a major example of these materials; it is obtained by the burning of rice husk which is a by-product in the production of rice, one of the most widely consumed food materials in the world. Another of such materials is used and discarded tyres which could be burnt to produce steel fibre; one of the major materials needed for the production of concrete which would possess higher strength and can satisfy the ever increasing demand for improvement for construction materials.

Keywords:  Effect, Elevated Temperature, Ultra – High strength concrete.

 

 

SMART FINANCIAL FRAUD DETECTION AND CUSTOMER RISK PROFILLING IN FINALCIAL INSTITUTIONS TO IDENTIFY POTENTIAL CRIMINALS USING GENETIC MARKOV ALGORITHM.

 

IDRIS MUHAMMAD SANI & DR. ISMAILA IDRIS

Computer Science Department. Federal University of Technology, Minna, Minna, Nigeria

 

Abstract

As computing power keep growing with tremendous growth of electronic transaction, so will the rate of electronic transaction fraud since people will rely more and more on computerized process for their daily activities. Hence, there are needs for more accurate and reliable approach for electronic transaction fraud detection which will help to reduce the illegal activity to the lowest minimum. The use of electronic transaction has increased to a great extent and it caused an explosion in the electronic fraud. Fraud has become one of the major ethical issues in the financial industry. Fraud associated with electronic transaction are also rising today as it is the major mode of payment for both online as well as regular purchase. In order to detect frauds from the mix of genuine as well as fraudulent transactions, efficient fraud detection techniques to detect them accurately are vital rather than simple pattern matching techniques. Here an approach is done to detect the electronic transaction fraud and classify the fraud as either low risk, medium risk or high risk transaction to the financial institution using a fusion approach of genetic and hidden markov algorithm which involve stages of pre-processing in which anonymous transactions were used, genetic algorithm was modelled for feature selection and hidden markov model for classification of fraud as low, medium and high risk transaction. The proposed model is done on existing electronic transaction dataset (anonymous and imbalanced). This research work propose the use of hidden markov model and genetic algorithm to build a model that is able to detect fraud and categorize the customer transaction into three risk levels as low risk, medium risk or high risk transaction to the financial institution to serve as a mechanism which can effectively detect and prevent fraud with great accuracy.

Keywords: Financial Institutions; transaction classification; feature extraction; fraud detection; customer risk profiling; machine learning; genetic algorithm; hidden markov model.

 

 

ASSESSMENT OF THE PHOTOCATALYTIC POTENTIALS OF MAGAMAN-GUMAU ILMENITE FOR USE IN HYDROGEN GAS PRODUCTION

 

GUSHIT, J. S., ISRAILA J. J., JOCK A. A. AND FRANCIS E. M.

Chemical/Petroleum Unit, Department of Science Laboratory Technology, University of Jos, Jos Nigeria.

 

Abstract

The photocatalytic potentials of Ilmenite ore for hydrogen gas production was studied by identifying and characterizing the pre-pulverised ore using  X-Ray Fluorescence (XRF) Spectroscopy, Scanning Electron Microscopy (SEM), Bruneaur-Emmett-Teller (BET) and Fourier Transform Infra-Red (FTIR) Spectroscopy. The XRF result indicated the main constituents of the Ilmenite to be 49.53% and 9.16% of elemental titanium and iron respectively, while the BET provided the surface area of the raw Ilmenite to be 12.8164m2/g. Similarly, the SEM revealed that cleavage planes and fractured surfaces to be prevalent on the surface of the natural Ilmenite ore, which is known to provide much more active sites and slightly higher reactivity than that of its synthetic counterparts with perfect crystal faces. FTIR Spectroscopy spectra showed strong spectral band between 1000 – 900 cm-1 in ilmenite indicating relatively high amount of surface oxygen than in other synthesized TiO2 catalysts. The effect of the ilmenite photocatalyst in the degradation of Methyl Orange (MO) in the dark and under visible light irradiation at different selected times was used to assess the photocatalytic potential of the ilmenite. From the assessment, the degradation of 200mL of 30mg/L MO solution using Ilmenite ore at varying quantities of 1.0g, 1.5g, 2.0g and 2.5g was carried out and it was clear that the degradation of MO under visible light irradiation by 2.0g of Ilmenite gave the highest degradation with 35.64%. Absorption test showed that the degradation was solely due to photocatalytic activity.

Keywords: Photocatalyst, Photocatalysis, Hydrogen Gas, Ilmenite ore, Methyl orange (MO).

 

 

PERFORMANCE EVALUATION OF NARX, RF AND LR MODELS FOR PREDICTION OF MEASLES DISEASE

 

KULUWA HAUWA AHMAD, JOHN KOLO ALHASSAN & ABDULLAHI IBRAHIM MOHAMMED

Computer Science Department, Federal University of Technology Minna 

 

Abstract

This work is on Performance Evaluation of Nonlinear Autoregressive Recurrent Neural Networks with exogenous input (NARX), Random Forest (RF) and Linear Regression (LR) for prediction of measles disease. Predicting measles disease is a difficult task due to seasonable time changes of the disease rate that vary between different locations . The NARX, RF, and LR models were used to predict Measles for the data collected from Federal medical center, Bida, Niger State, Nigeria, and their performance were compared. The results obtained for predicting measles showed that the NARX model proved to be most accurate because it had smaller RMSE of 6.7483 when compared with the RF of 14.4463 and LR  of 23.6065. T  herefore, this paper argues that using this model would enhance the effectiveness of routine immunization in Nigeria. The proposed model is recommended for usage by the researchers and clinicians. Some other diseases can be studied by exploring other machine learning models aside NARX NN, RF, and LR.

Keywords: Data Mining techniques, Measles disease, MATLAB, and Predictive model.

 

 

PREDICTION OF NON-PERFORMING LOANS IN ANCHOR BORROWERS PROGRAMME USING DECISION TREE, NAÏVE BAYES, J48, BAGGING AND ADABOOSTM1 MACHINE LEARNING ALGORITHMS

 

AMINU UMAR AND MUHAMMAD BASHIR ABDULLAHI

Department of Computer Science, Federal University of Technology, Minna, PMB 65, Minna, Niger State, Nigeria

 

Abstract

Anchor borrowers Programme (ABP) was established by the Federal Government of Nigeria for enhancing agricultural development and attaining self-sufficiency in food production in Nigeria. But the programme had been facing so many challenges, among them is the lack of credit worthiness by some of the participants evolved in the programme. This article analysed data from six (6) geo-graphical locations of the country using authentic data. The data were analysed using multiple machine learning algorithms. It was observed that Decision Tree algorithm had the best result among all the base classifiers, and that result was used in predicting the final result. The finding of this study would assist in enrolling the authentic farmers into the programme by eliminating some of the bad experiences encountered earlier and increase the number of the real farmers that can serve as catalyst in achieving Agricultural Transformation Agenda (ATA) of the Federal Government of Nigeria. This article will assist both the Central Bank of Nigeria (CBN) and other Banks in financing the programme such as Bank of Agriculture (BOA), and it will drastically reduce the number of Non-Performing Loan (NPL) of the participating Banks.

Keywords: Anchor Borrowers’ Programme, Bank of Agriculture, Central Bank of Nigeria, Machine Learning Approach

 

 

VEHICLE CRASH LOCATION DETECTION AND ALERTING SYSTEM USING ANDRIOD SMART PHONE AND GPS TECHOLOGIES

 

1,2ABUBAKAR ALHAJI ALFA AND 1MOHAMMAD BASHIR ABDULLAHI

1Department of computer Science, Federal University of Technology, Minna, Niger State 2Department of Computer Science, Federal Polytechnic, Bida, Niger State  

 

Abstract

Nowadays varying degrees of Road Crashes have been recorded from both developed and developing nations of the world. Crashes especially those that involve loss of lives around the world and in particular in developing countries is alarming. The existing solution is in-vehicle accident detection system, which is expensive. In this research paper, a less expensive and system that can be widely used to reduce the time to report and respond to vehicle crash was developed. The system consists of two mobile-phone-based applications, the User or Victim’s App and the Agency App. The Victim App uses the in-phone accelerometer and GPS to detect a crash and its location coordinates respectively, and then a notification is sent to a concerned agency. A maximum of three concerned agencies location coordinates with their respective phone numbers are stored on a Firebase (cloud database) account for mapping to the closest crash site and then send an SMS with the location coordinates and the Google map image of the crash site in real-time . The Agency App is used to register an agency on the Firebase. To be able to view the Google map images, each of the concerned agencies need a smart phone. The two Apps were developed and implemented using Android Studio Integrated Development Environment (IDE), with Java programming language for the Events and XML for the interface design. The implementation was strictly on Android smart phones with minimum Application Programming Interface (API) level 16. The system validation proves high Sensitivity of 93%, Accuracy of 91% and Precision 92%, Specificity 87% which shows that the system is efficient and effective.

Keywords: Crash, Accelerometer, GPS, Smart Phone, Firebase.

 

 

EVALUATING AGE BASED DATA USING DEMOGRAPHIC TECHNIQUES

 

  1. O. ADEYEMO

Maths and Statistics Department, Federal Polytechnic, Nekede, Owerri, Imo State, Nigeria.

 

Abstract

Demographic data are usually classified by age and sex, as they both are very important variables. National plans for the provision of such need as housing, food, education, health, e.t.c depend on the relevant socio – demographic statistics classified by age and sex.  The importance of accurate age-sex data in demographic analysis cannot be over emphasized as there are errors associated with age and sex. As age data tend to be more inaccurate than sex data, there is need for investigation and evaluation of the quality of the data collected on age. This paper is purposely prepared to evaluate the accuracy of age reporting using the demographic and health survey 2008 for both Ghana and Nigeria using demographic techniques. The Whipples’ and Meyer’s indices as well as the United Nations Age-Sex accuracy index were determined. The result of the work has shown very accurate age data reporting for all except male at age ending with “0” in Nigeria only. For the Myer’s index, the most preferred final digits are ‘5’ and ‘0’, while the most avoided final digit by both sexes is ‘1’ in the two countries. Furthermore, the calculated age-sex accuracy index is 35.48 (for Nigeria) that qualified the age data usable with adjustment according to the United Nations scaling.

Keywords: Digit preference, Whipple’s index, Myer’s index, Age, UN age-sex accuracy Index

 

 

MODELLING THE DIFFERENTIAL EFFECTS OF THE INITIAL CONDITION ON THE TYPE OF STABILIZATION

 

1EKE, NWAGRABE2EKAKA-A, E. N.

1Department of Mathematics/Statistics, Ignatius Ajuru University of Education, Port Harcourt, Rivers State 2Department of Mathematics, Rivers State University Nkporlu–Oroworukwo, Port Harcourt, Rivers State

 

Abstract

The deterministic stabilization of a dynamical system using the procedure of a simulation modelling is a challenging mathematical problem especially in the context of considering the differential effects of the initial condition on the qualitative characterization of a dynamical system otherwise called stabilization. We have dominantly observed that the differential effects of changing the initial conditions have produced a robust similar type of stabilization in which each obtained steady state solution is uniformly stable. These novel results that we have obtained can be implemented to construct a feedback control to further stabilize this several stable steady state solution. The full results of this study are presented and discussed quantitatively.

Keywords: Condition, Initial, Stabilization, Modelling, Differrential.

 

 

MODELLING INTERDEPENDENCE OF SOME NIGERIAN INDUSTRIES USING A NUMERICAL METHOD. 

 

*PETER, ONYEDINMA CHINEDU, *E. N  EKAKA-A  **N. M NAFO 

*Department of Mathematics, Rivers State University, Nkpolu-Oroworukwo, Port Harcourt **Department of Mathematics, Rivers State University, Nkpolu-Oroworukwo, Port Harcourt

 

Abstract

While a technological matrix is not a recent construction in the theory of linear algebra, its effective application due to the variation of the demand elements and its impact on the gross productions of agricultural products, steel and coal can be considered as a mathematical problem that requires a MATLAB algorithm solution.  The novel results of this study that we have not seen elsewhere are clearly presented and discussed quantitatively.

Keywords:  Modelling, Numerical, Industries, Method, Nigeria

 

 

MATHEMATICAL MODEL OF TUMOR AND IMMUNE-MODULATIONS DYNAMICS

 

ABDULKAREEM IBRAHIM AFOLABI1, NURUDEEN O. LASISI2

Federal Polytechnic Kaura-Namoda, Zamfara State, Nigeria1,2

 

Abstract

Biomedical studies induce that immunosuppression is the major inhibitory mechanism against effector cells in tumor-immune system interaction. These inhibitions of effector cells were said to be caused by both the tumor and regulatory T-cells through IL-10 and TGF-. In this work, we proposed a model of immune-modulation by Immune-suppression cells. The stability analysis were carried out and two steady states were obtained namely tumor-negative state which is stable if the body cells does not proliferate excessively and the tumor-positive steady states which is critical case which suggested a disappearance of effector cells and the immune-suppression cells will only decay if the interaction leads to elimination of tumor rather than promoting the inhibitory of effector cells.

Keywords: Mathematical models; tumor; immune-modulations; immunosuppression

 

 

DATA MINING AND ITS EFFECT ON DATABASE

 

JOSEPH OKORODUDU & ANTHONY UMUKORO

Computer Science Department, Delta State Polytechnic, Otefe.

 

Abstract

With an enormous amount of data stored in databases and data warehouses, it is increasingly important to develop powerful tools for analysis of such data and mining interesting knowledge from it. Data mining is a process of inferring knowledge from such huge data. The main problem related to the retrieval of information from the World Wide Web is the enormous number of unstructured documents and resources, that is, the difficulty of locating and tracking appropriate sources. In this seminar, a survey of the research in the area of web mining and suggest web mining categories and techniques. Furthermore, a presentation of a web mining environment generator that allows naive users to generate a web mining environment specific to a given domain by providing a set of specifications.

Keywords:  Data Mining, World Wide Web, Data Retriever, Web Mining

 

 

WHAT EXPLAINS THE HIGH RATE OF INFANT MORTALITY IN RURAL NIGERIA: BIODEMOGRAPHIC OR SOCIOECONOMIC FACTORS?

 

1ANTHONY I. WEGBOM, 1DAGOGO S. A. WOKOMA, 1LOVE C. NNOKA,

1Department of Statistics, Rivers State College of Art and Science, Port Harcourt

 

Abstract

Children in the rural Nigeria are faced with higher mortality than their urban counterparts. And a number of factors are responsible for this. This study determines which of bio-demographic or socio-economic factors contribute greatly to high rate of infant mortality in rural Nigeria. Data from the 2013 Nigerian Demographic and Health Survey were re-analysed using multivariate Weibull proportional hazard model to determine the effect of bio-demographic and socio-economic factors on infant mortality in rural Nigeria. After controlling for other factors, child’s sex, maternal age at child birth, birth interval, maternal age at first birth, type of toilet facilities, place of residence and maternal education are factors associated with infant mortality in rural Nigeria. Hazard of infant mortality was lowest among female children (HR = 0.83, CI= 0.75-0.93). Infant whose mother’s age at child birth were 35 yr or more have higher risk of death (HR=1.40, CI=1.13- 1.74).  Hazard of death was 64% (CI= 0.54- 0.76) and 46% (CI= 0.38, 0.56) higher at infancy among birth interval of 20-35 months and more than 35 months respectively. Infant whose mother’s age at first birth was more than 35years have higher risk of death. Bio-demographic factors contribute significantly to infant mortality than socioeconomic factors. Hence, in reducing infant mortality in rural Nigeria attention should be directed more towards biodemiographic variables.

Keywords:  childhood, mortality, determinants, factors, Rural Nigeria.

 

 

THE EFFECT OF FERTILIZER AND TEMPERATURE ON THE YIELD OF RICE USING MULTIPLE REGRESSIONS

 

*BASHIR ALHAJI MUSTAPHA AND **AHMED SULE ASKIRA

*Department of Statistics, Federal Polytechnic, Damaturu, Yobe State, Nigeria. **Department of Statistics, Ramat Polytechnic, Maiduguri, Borno State, Nigeria.

 

Abstract

Analysis was conducted on the effect of fertilizer and temperature on the yield of Rice using multiple regression analysis. Based on the result of the analysis, tone/hec (Y) has negative (weak) correlation with fertilizer (X1) and the Temperature(X2). Only 19.7% of variation in the dependent variable tone/hec (Y) is explained by the model. This shows that the model is not a good model for prediction. The analysis of variance (anova) shows that the result is not significance.

Keywords: Regression, Fertilizer, Effect, Temperature, Multiple.

 

 

PRODUCTION OF WINE FROM PINEAPPLE AND WATERMELON USING YEAST ISOLATED FROM BURUKUTU

 

*UDOSEN, I. E.; OLISA, C., MUSTAPHA, H. G., HAMZA, I. S. AND ISA, A.

1Department of Science Laboratory Technology, Federal Polytechnic, Bauchi..

 

Abstract

Pale yellow wine was produced from watermelon and pineapple mixture using yeast isolated from burukutu. Three yeast strains, (Kloekera apiculata, Candida tropicalis and Saccharomyces cerevisiae) were isolated and subjected to various biochemical and potency estimation tests. Saccharomyces cerevisiae was found to possess the essential characteristics for wine production and was employed in the production of wine at regulated temperature of 15oC ± 2oC and the brix level was raised to 20o. The final result gave a wine with an alcoholic content of 8.3%, final pH 4.19, titratable acidity of 0.85 and brix level of 8.0o sensory evaluation conducted by panel of judges showed that the wine was not well accepted.

Keywords: Wine, Pineapple, Yeast, Isolated, Production

 

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