The stock market is one of the key sectors of a country's economy. It provides investors with an opportunity to invest and gain returns on their investment. Predicting the stock market is a very challenging task and has attracted serious interest from researchers from many fields such as statistics, artificial intelligence, economics, and finance. An accurate prediction of the stock market reduces investment risk in the market. Different approaches have been used to predict the stock market. The performances of Machine learning (ML) models are typically superior to those of statistical and econometric models. The ability of Gaussian Naïve Bayes ML algorithm to predict stock price movement has not been addressed properly in the existing literature, hence this attempt to fill that gap in the literature by evaluating the performance of GNB algorithm when combined with different feature scaling and feature extraction techniques in stock price movement prediction. The performance of the GNB models set up were ranked using the Kendall's test of concordance for the various evaluation metrics used. The results indicated that, the predictive model based on integration of GNB algorithm and Linear Discriminant Analysis (GNB_LDA) outperformed all the other models of GNB considered in three of the four evaluation metrics (i.e., accuracy, and AUC). Similarly, the predictive model based on GNB algorithm, Min-Max scaling, and PCA produced the best rank using the specificity results. In addition, GNB produced better performance with Min-Max scaling technique than it does with standardization scaling techniques Povzetek: Predstavljena je metoda Gausovega naivnega Bayesa za borzne napovedi.
This paper proposed an Optical Markup Recognition (OMR) system to be used to detect
Web security is a critical aspect for many web-based applications, along its research track, keystroke dynamics techniques have attracted broad interests due to their high efficiency in security. In this paper, the aim was to come out with a keystroke login system that overcomes the typical challenges associated with keystroke dynamics and improves on password security but with focus on irritability nature of keystroke dynamics based systems. Specifically, we proposed two stages user matching method, training/enrolment phase of users and authenticating registered users with previously stored data. Furthermore, the proposed algorithm added dwell, flight times and multiplied by the locate time to get the upper and lower bounds. Moreover, the uniform differences between the bound timings were calculated to further enhance security. Experimental results show that the proposed keystroke dynamics approach used in augmenting password security emerged to be superior as compared to existing customary distance metrics.
The internet has become an essential part of the world today. The internet will need to reach a wide range of individuals’ family members, friends, acquaintances, or even share data or information with a group of people. Imagine a constant and reliable internet connection, regardless of location or place. The CKT-UTAS (C.K. Tedam University of Technology and Applied Sciences) Campus is an example of an area where internet connection is inferior and unreliable. This research work studied the benefits and limitations of satellite internet, which can be a solution to the current state of internet connection unreliability on the CKT-UTAS campus and derive into the benefits it will provide to the university if implemented. This study aimed to compare the current telecommunication network services to the Satellite Internet services, analyses the awareness level of Satellite Internet in rural areas and examine the significance of Satellite Internet technology in rural areas. In-depth research was done by administering questionnaires and studying other related works on this study to gather all the necessary information. After the data were analyzed, it was concluded that the Satellite Internet had more advantages that are significant in rural areas than the Current/Traditional Internet.
CCTV monitoring system is an essential security tool for visual surveillance accelerating the investigation in potential criminal activities when the need arises. Although expensive, universities mostly with public-access campuses in general, all need this system mainly to maintain safety and security in real-time, allowing legitimate students and staff to access campus resources and concurrently preventing any unauthorized persons access within the campus as well as responding to incidents with necessary action. C. K. Tedam University of Technology and Applied Sciences (CKT-UTAS) is a university in the Upper East Region of Ghana that does not have such a monitoring system. Since it is a newly established public university, its allocated funds are limited and could not be used to establish such an expensive system. To supplement their ongoing efforts in building security monitoring system, this study constitutes the blueprint procedures for building economical but reliable and efficient CCTV camera system for monitoring the property on campus and also the in and out of students and university staff members. The CCTV system was tested in monitoring vantage security post of the University. After observing and analyzing the trends in data from both the physical and our proposed automated monitoring approach, it can be concluded that the CCTV camera setup outperforms the physical and manual form or monitoring vantage security posts on University campus. Since the of monitoring security post using the proposed CCTV setup is advantageous in requiring lesser human effort and skills, it can be recommended for universities with low income-flow and low budget. This probably can make the university campus more secure and reliable.
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