Taita Taveta University College E-Voting System: A Web Based Approach to Elections Management
J. M. Nzoka,
N. M. Muthama,
N. M. Mung’ithya
Issue:
Volume 2, Issue 5, October 2013
Pages:
70-76
Received:
8 August 2013
Accepted:
Published:
20 September 2013
Abstract: Most institutions of higher learning such as universities and colleges world over provide for an electioneering process where students elect their union leaders in a democratic manner. This is of great importance as it inculcates the principle of democracy into the students who are at the peak of their learning stage and would need these skills for better statesmanship. Proper management therefore is called for to provide foolproof processes which can be termed as free and fair in the standards of universal democracy and employment of Information Technology is a sure way to realize this. Online voting is the application of web based technologies to the automation of voting processes. In online voting a voter cast their ballot from a remote terminal that is connected to the central database where actual processing of the ballot is done. Online systems have the advantage of providing convenience to the voter and reduce the time wasted in the queuing process at election centers. This paper describes a research carried out at Taita Taveta University College, a higher learning institution in Kenya and the process undertaken to achieve development and deployment of a web based system to promote free and fair democratic electioneering process: computerizing registration, voting and tallying process involved. The system described is in form of a portal that is embedded on the Universities website. The system was developed using the incremental prototyping due to the adaptive nature of web based applications and the system proved that a computerized solution is possible with elimination of human related faults that are a commonplace in employment of human clerks to manage the election process. Integration with SMS functionalities helped increase safety and reliability of the system. Application of the online voting has resulted in many advantages in the efficiency of the entire electioneering process and reduced costs the university used to incur using the human clerk mechanism.
Abstract: Most institutions of higher learning such as universities and colleges world over provide for an electioneering process where students elect their union leaders in a democratic manner. This is of great importance as it inculcates the principle of democracy into the students who are at the peak of their learning stage and would need these skills for...
Show More
Forecasting the Saudi Arabia Stock Prices Based on Artificial Neural Networks Model
S. O. Olatunji,
Mohammad Saad Al-Ahmadi,
Moustafa Elshafei,
Yaser Ahmed Fallatah
Issue:
Volume 2, Issue 5, October 2013
Pages:
77-86
Received:
4 August 2013
Accepted:
Published:
20 October 2013
Abstract: In this paper, we have proposed artificial neural network for the prediction of Saudi stock market. The proposed predictions model, with its high degree of accuracy, could be used as investment advisor for the investors and traders in the Saudi stock market. The proposed model is based mainly on Saudi Stock market historical data covering a large span of time. Achieving reasonable accuracy rate of predication models will surely facilitate an increased confidence in the investment in the Saudi stock market. We have only used the closing price of the stock as the stock variable considered for input to the system. The number of windows gap to determine the numbers of previous days to be used in predicting the next day closing price data has been choosing based on experimental simulation carried out to determine the best possible value. Our results indicated that the proposed ANN model predicts the next day closing price stock market value with a very low RMSE down to 1.8174, very low MAD down to 18.2835, very low MAPE of down to 1.6476 and very high correlation coefficient of up to 99.9% for the test set, which is an indication that the model adequately mimics the trend of the market in its prediction. This performance is really encouraging and thus the proposed system will impact positively on the analysis and prediction of Saudi stock market in general.
Abstract: In this paper, we have proposed artificial neural network for the prediction of Saudi stock market. The proposed predictions model, with its high degree of accuracy, could be used as investment advisor for the investors and traders in the Saudi stock market. The proposed model is based mainly on Saudi Stock market historical data covering a large s...
Show More
Algorithms for Trade Modeling with Agent-Based Systems
Monica Dascalu,
Lucian Milea,
Gabriela Ivanus,
Mihail Teodorescu,
Eduard Franti
Issue:
Volume 2, Issue 5, October 2013
Pages:
87-93
Received:
7 October 2013
Accepted:
Published:
30 October 2013
Abstract: This paper presents a set of algorithms for trade modeling with cellular automata (CA). The cellular automata simulator developed for this purpose has allowed the study of phenomena that occur within groups of agents that operate in a dynamic resource field. With this cellular automata simulator algorithms have been developed and tested for clustering of agents in agencies and for studying phenomena within agencies. It was thus evident that within agencies the agents try to group in the neighborhood of leading and rich agents with high performance, in order to learn from them the best rules. In terms of hierarchy, the results show that the places in the immediate neighborhood of the agents with leading positions can be occupied only by agents with wealth.
Abstract: This paper presents a set of algorithms for trade modeling with cellular automata (CA). The cellular automata simulator developed for this purpose has allowed the study of phenomena that occur within groups of agents that operate in a dynamic resource field. With this cellular automata simulator algorithms have been developed and tested for cluster...
Show More
