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All Journal JOIV : International Journal on Informatics Visualization
Muhammad Aamir
Universiti Tun Hussein Onn Malaysia, Johor, Malaysia
Computer Science & IT

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An E-learning System in Malaysia based on Green Computing and Energy Level Arif Ullah; Nazri Mohd Nawi; Asim Shahzad; Sundas Naqeeb Khan; Muhammad Aamir
JOIV : International Journal on Informatics Visualization Vol 1, No 4-2 (2017): The Advancement of System and Applications
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1130.492 KB) | DOI: 10.30630/joiv.1.4-2.63

Abstract

The increasing of energy cost and also environmental concern on green computing gaining more and more attention. Power and energy are a primary concern in the design and implementing green computing. Green is of the main step to make the computing world friendly with the environment.  In this paper, an analysis on the comparison of green computer with other computing in E-learning environment had been done. The results show that green computing is friendly and less energy consuming. Therefore, this paper provide some suggestions in overcoming one of main challenging problems in environment problems which need to convert normally computing into green computing. In this paper also, we try to find out some specific area which consumes energy as compared to green computing in E –learning centre in Malaysia. The simulation results show that more than 30% of energy reduction by using green computing.
Comparative Analysis for Heart Disease Prediction Sundas Naqeeb Khan; Nazri Mohd Nawi; Asim Shahzad; Arif Ullah; Muhammad Faheem Mushtaq; Jamaluddin Mir; Muhammad Aamir
JOIV : International Journal on Informatics Visualization Vol 1, No 4-2 (2017): The Advancement of System and Applications
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (700.404 KB) | DOI: 10.30630/joiv.1.4-2.66

Abstract

Today, heart diseases have become one of the leading causes of deaths in nationwide. The best prevention for this disease is to have an early system that can predict the early symptoms which can save more life. Recently research in data mining had gained a lot of attention and had been used in different kind of applications including in medical. The use of data mining techniques can help researchers in predicting the probability of getting heart diseases among susceptible patients. Among prior studies, several researchers articulated their efforts for finding a best possible technique for heart disease prediction model. This study aims to draw a comparison among different algorithms used to predict heart diseases. The results of this paper will helps towards developing an understanding of the recent methodologies used for heart disease prediction models. This paper presents analysis results of significant data mining techniques that can be used in developing highly accurate and efficient prediction model which will help doctors in reducing the number of deaths cause by heart disease.
The Impact of Search Engine Optimization on The Visibility of Research Paper and Citations Asim Shahzad; Nazri Mohd Nawi; Norhamreeza Abd Hamid; Sundas Naqeeb Khan; Muhammad Aamir; Arif Ullah; Salfarina Abdullah
JOIV : International Journal on Informatics Visualization Vol 1, No 4-2 (2017): The Advancement of System and Applications
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (777.346 KB) | DOI: 10.30630/joiv.1.4-2.77

Abstract

The initial criteria for evaluating a researcher's output is the number of papers published. Furthermore, for the measurement of author's research quality, the number of citations is significant.  Typically, citations are directly linked with the visibility of a research paper. Many researches had shown that the visibility of a research paper can be improved further by using the search engine optimization techniques. In addition, some research already proved that the visibility of an article could improve the citation results. In this article, we analysed the impact of search engine optimization techniques that can improve the visibility of a research paper. Furthermore, this paper also proposing some strategies that can help and making the research publication visible to a large number of users. 
Neural Network Techniques for Time Series Prediction: A Review Muhammad Faheem Mushtaq; Urooj Akram; Muhammad Aamir; Haseeb Ali; Muhammad Zulqarnain
JOIV : International Journal on Informatics Visualization Vol 3, No 3 (2019)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (902.684 KB) | DOI: 10.30630/joiv.3.3.281

Abstract

It is important to predict a time series because many problems that are related to prediction such as health prediction problem, climate change prediction problem and weather prediction problem include a time component. To solve the time series prediction problem various techniques have been developed over many years to enhance the accuracy of forecasting. This paper presents a review of the prediction of physical time series applications using the neural network models. Neural Networks (NN) have appeared as an effective tool for forecasting of time series.  Moreover, to resolve the problems related to time series data, there is a need of network with single layer trainable weights that is Higher Order Neural Network (HONN) which can perform nonlinearity mapping of input-output. So, the developers are focusing on HONN that has been recently considered to develop the input representation spaces broadly. The HONN model has the ability of functional mapping which determined through some time series problems and it shows the more benefits as compared to conventional Artificial Neural Networks (ANN). The goal of this research is to present the reader awareness about HONN for physical time series prediction, to highlight some benefits and challenges using HONN.
Co-Authors Arif Ullah Asim Shahzad Haseeb Ali Jamaluddin Mir Muhammad Faheem Mushtaq Muhammad Zulqarnain Nazri Mohd Nawi Norhamreeza Abd Hamid Salfarina Abdullah Sundas Naqeeb Khan Urooj Akram