درخت حوزه‌های تخصصی

The purpose of research is focused on the insight into the future of Bitcoin on the financial situation, its implications and challenges. The problem of study is to investigate how to deal with a new type of digital currencies (such Bitcoin) that does not have a physical presence and there is no specific body to issue. Thus, this study aims to identify the nature of Bitcoin currency and what are the challenges associated with it as well as exchange rates with some currencies, as the research hypothesized the main hypothesis that Bitcoin will contribute to financial development in the future, the research also used the analytical rooted approach to present concepts and data, using financial technical analysis to display the results The research also came up with a number of conclusions and recommendations. The results of paper significantly contribute to the literature through providing evidence from financial data of Bitcoin.

The improved model of the Agile Kanban (i-KAM) is developed to enhance the software project monitoring task when employing Agile project management (APM) approach. The i-KAM have been initially verified by 11 knowledge and domain experts. In consequence, it has been reconstructed and enhanced based on the remarks and recommendations provided by the experts. This paper aims to present the final evaluation results of i-KAM achieved from seven software practitioners participated in a focus group. The focus group method was selected because it is an empirical approach used in the evaluation studies conducted in the software engineering (SE) domain. Therefore, this method was employed to obtain the practitioners’ feedback on the proposed model. Results confirm the effectiveness of i-KAM, in which it can assist the project managers and team members in monitoring their projects’ progress effectively. In addition, it is indicated that i-KAM is an applicable model with easy and practical implementation. This study contributes to improve the task of monitoring software development projects within the APM environment. Accordingly, this would systematically facilitate the top managements’ work, and assist in making meaningful decisions regarding to the management of projects’ workflow. Practically, case studies will be carried out in different software development organizations (SDOs) to implement i-KAM in actual projects within real environments

The ability of now-casting and eventuality is the most crucial and vital achievement of big data analytics in the area of policy-making. To recognize the trends and to render a real image of the current condition and alarming immediate indicators, the significance and the specific positions of big data in policy-making are undeniable. Moreover, the requirement for policy-making institutions to produce a structured model based on big data analytics for now-casting and eventuality of predictive policies is growing rapidly. The literature review demonstrates that a comprehensive model to assist policy-making institutions by providing all components and indicators in now-casting of predictive policies based on big data analytics is not devised yet. The presentation of the model is the main finding of this research. This research aims to provide a comprehensive model of now-casting and eventuality of predictive policies based on big data analytics for policy-making institutions. The research findings indicate that the dimensions of the comprehensive model include: the alignment of now-casting strategies and the big data analytics’ architecture, now-casting ecosystem, now-casting data resources, now-casting analytics, now-casting model and now-casting skill. The results of using the model were analyzed and the recommendations were presented.

The real-time video surveillance system has become an integral part of our life and Highways play a very crucial role in transportation. For a transportation system to work, the management of highways are necessary. It also prevents accident and other challenging issues on highways. Various machine learning and artificial intelligence based techniques are evolving with numerous advancement in this domain. These algorithms are efficient and very less time consuming. So the use of machine learning and artificial intelligence in transportation systems and highways could be very beneficial. In this paper, various approaches related to moving vehicle detection for the transportation system especially for highways are considered. The literature also reveals for existing research for the machine learning and AI based methodologies to resolve more complex real-time problems. The proposed work is also compared with the existing peer methods and demonstrated better performance achieved experimentally.

This study aims to investigate the effectiveness of university roles in entrepreneurial intentions among university students. This study is also measuring the functions of the system supports as the control variables towards entrepreneurial intentions. Universities seem to compete in the industry to provide and develop the entrepreneurial skills set to their students. Perhaps they may add more benefit in preparing and equipping their students as entrepreneurs once they completed their studies. The study was conducted in local universities. Three hundred respondents were approached in getting the data compiled. Based on that, only 250 complete and usable data received in returns. An 83% response rate is achieved because the sample was from a list of young entrepreneurs' schemes currently being assessed by the government agencies. Questionnaires used to validate the items from university roles (6 items), entrepreneurial intentions (5 items), and finally support systems (6 items). Likert scales were used to measure all the items. Besides that, there are also seven questions for respondents' profiles. The results indicate that all tested hypothesized were positively significant. Universities should consider finding ways to develop and motivating their students towards entrepreneurial intentions. Further study may continue the model with different sets of control variables for concrete solutions in managing the student's entrepreneurial intentions.

The most important aspects of image processing are image enhancement. The visual form of an image can be enhanced by using image enhancement techniques for better human interpretation. In this research paper we discuss an   outline and analysis of commonly used image enhancement techniques using finger vein image or personal authentication. Also, experiments are carried out to compare performance of various types of filters for removal of noise from the noisy images through evaluation performance parameter such as mean square error (MSE), peak signal to noise ratio (PSNR) values and structural similarity (SSIM). It was found that application of max filter technique ensures an improved quality of the finger vein image. The mean filter is most advanced in de-noising the images. Mean filter is most efficient in eliminating the salt and pepper noise. From the experiments performed on finger vein image using SDUMLA-HMT database, it is proven that Weiner filters are outstanding for elimination of Gaussian Speckle and Poisson noises and thus, Weiner filter is found to be most appropriate and well-suited for eliminating nearly all types of noise.

People are used to exploring grayscale images in their family albums but it is difficult to grasp the reality without colours. Luckily, with advancements in Machine Learning it has been possible to solve problems previously thought impossible. The authors aim to automatically colourize grayscale images using a subset of Machine Learning called Deep Learning. The system will be trained on an image dataset and given an input grayscale image the model will be able to assign aesthetically believable colours. A grayscale photograph has been provided; our approach solves the problem of visualizing a reasonable colour version of the grayscale picture. This issue is undoubtedly under controlled; therefore earlier methods to this problem have either counted majorly on user interaction or it leads to in unsaturated colourizations. The authors put forward a completely automatic approach that will try to produce realistic and vibrant colourizations as much as possible. The proposed system has been applied as a feed-forward in a Convolutional Neural Network and has been trained on over twenty thousand colour images currently.

Artificial intelligence (AI) is a discipline interested in the processes and methods that allow a machine to perform tasks related to human intelligence. It offers many opportunities related to problem solving, quick decision-making, increasing efficiency and reducing costs. Because of its so various fields of application, artificial intelligence is at the heart of the new industrial revolution. Algeria aims to present its AI strategy by 2020. In this paper, we are interested in defining AI, its potential fields of application, and in particular, its influence in the customer journey and position of RFID ( Radio-Frequency Identification ) in the chain; application in the aviation sector and its relationship to the Internet of Things are also described through examples.

This study aims to identify the role of information and communication technology in improving electronic payment methods. The descriptive-analytical approach has been applied. We have learned about the concepts of ICT and electronic payment methods and the impact of ICT on these methods. On the applied side, an El Oued was distributed to a staff sample in the Directorate of the Algeria Poste unite of the State of El-Oued and several its postal institutions. The El Oued included two main axes: the first focuses on the reality of ICT in the organization. We discussed the electronic payment methods and the control procedures on their system on the second axis. Also, the challenges and risks which they face, the study revealed a statistically significant relationship between the variable of ICT and the means of electronic payment through the influence of some dimensions in the first axis on the dimensions of the second axis.