درخت حوزه‌های تخصصی

SCImago Journal Rank (SJR) is one indicator of a journal's reputation.  The value is calculated based on several published journals, such as scholarly journals' scientific impact, representing the number of quotes sent to a journal and the relevance or reputation of journals from which the quotations originate. A high SJR value means that the corresponding journal has a high reputation. This study aims to approach the SJR classification by implementing a machine learning approach. A simple yet powerful method Naïve Bayes Classifier (NBC), is selected. NBC utilizes probability calculations based on Bayes' theorem. However, NBC has an assumption that the attribute values do not depend on each other. This method is optimized using Particle Swarm Optimization (PSO) to overcome this weakness. This study used SJR data of the computer science domain from 2014 to 2017. Publication without Q rank is filtered for better performance. As a result, the accuracy of the proposed method is higher than the baseline. The use of PSO  significantly improves the NBC performance based on the performed T-test. The PSO-NBC selects four of eight features: H index, Cites/ Doc (2 Years), and Ref. / Doc. Overall results show that using PSO-NBC is closer to SJR rather than using mere NBC.

After the Coronavirus diseases (COVID-19) outbreak, the Whole world witnessed the strangest buying behavior within the customers. Suddenly masks, hand sanitizers, and toilet papers became the priority list of the customers. High demand and lesser availability of essentials products like masks, toilet papers, and hand sanitizers create a chaotic situation inside the retail outlet's stores.  The buyer’s behavior and the chaotic scenario inside a retail outlet drew the attention of several consumer psychologists, academicians, and researchers. A panic buying situation is the most common behavior that exists in a time of crisis. This paper discusses the panic buying situation briefly during COVID-19. However, a few types of research and studies were captured in the panic buying behavior. The current study examined the factors that influenced the customers buying decisions during the COVID-19 outbreak and secondly, it examined to what extent the buying decision of a customer creates a panic situation. Furthermore, the study looked at the emotional and cognitive responses of the individuals which play a pivotal role in influencing customer decision making the journey. Qualitative content analysis and thematic methodology were considered for data analysis. The results indicated that fear and uncertainties were the key emotional responses; whereas rumors, fallacious thinking, and survivalist psychological were the key cognitive responses that influenced the customer decision journey.

As electronic commerce has gained widespread popularity, payments made for users' transactions through credit cards also gained an equal amount of reputation. Whenever shopping through the web is made, the chance for the occurrence of fraudulent activities are escalating. In this paper, we have proposed a three-phase scheme to detect fraudulent activities. A profile for the card users based on their behavior is created by employing a machine learning technique in the second phase extraction of a precise communicative pattern for the card users depending upon the accumulated transactions and the user's earlier transactions. A collection of classifiers are then trained based on all behavioral pattern. The trained collection of classifiers are then used to detect the fraudulent online activities that occurred. If an emerging transaction is fraudulent, feedback is taken, which resolves the drift's difficulty in the notion. Experiments performed indicated that the proposed scheme works better than other schemes.

The modeling engineering of psychotherapeutic approaches to diabetic patients has a positive impact on the quality of the support process and organizational, personal and professional development, in the sense that the education and neuro-educational training project constitutes a powerful human resources management vector. The research would attempt to analyze therapeutic education models and corresponding health promotion approaches, as well as the identification of methods and techniques used in health practice As a result, the quality of the neuro-educational approaches is the guarantor of the effectiveness of the recommended support system. Adopting this imperative highlight, a new PCA patient-centered approach. This major concern therefore calls on the medical profession to question the impact and effects of collaborative support in the process of building and developing the conceptual, procedural and behavioral skills of diabetic patients which facilitate their self-knowledge, their self-determination and their awareness of the factors of therapeutic effectiveness and the promotion of their physical, moral, social and psychological well-being. It prompts us to ask ourselves how the different care teams and support actors organize and coordinate their andragogical actions, with a view to complementarity and synergy. We proceed, through a descriptive and exploratory research approach, opting for a so-called longitudinal survey, by a semi-directive questionnaire and by an interview technique. By comparing the results of the study with the validation interviews, it emerges that appropriate attention must be paid to the support process to allow the diabetic patient to master all the components of reflective therapeutic practice and to achieve his personal and organizational development necessary for the development of a subject actor of change and innovation. This support system engineering will define the frame of reference, including the ethical values ​​and the basis of the required professional skills which will be applicable to any program for the development of cognitive and behavioral skills in diabetic patients. The new vision will be built around adapted support practices, collaborative approaches, a comprehensive, harmonious and balanced therapeutic education program, personalized training courses and inclusive evaluation methods that go well beyond validation and tenure. (Towards a sick-centered vocation).

Smart applications with interconnected intelligent devices for sharing services arise serious security problems to the stability of this IoT complex and heterogeneous environment. Unless security considerations are analyzed and implemented properly in real time then IoT cannot be perceived as a pervasive network for the possible stakeholders. Current state of the art has analyzed trust-based security solutions as additional feature to application layer of the system which can identify and filter out the malicious nodes. In this paper we are proposing holistic trust management with edge computing mechanism to create trustworthy zones comprising different clusters, where Gateway on behalf of clusters will initiate migration of their nodes if falls below the defined Zone trust threshold level. The created zones are self-resilient against any malicious attacks and saves lots processing usage time and energy to address the security issues. By analyzing our proposed algorithm with other contemporary approaches to handle IoT security issues using trust mechanism, this approach is more precise in terms of protecting system against incurring malicious behavior, and also prolong the application operation duration by reducing communication and processing overhead.

Background: The Internet of things (IoT) is a new technology that expanding rapidly and has led to the emergence of new services in the banking industry. Although IoT is an emerging technology in Iran, it is expected to become a paradigm in the future. IoT applications in banking have helped to provide high quality and fast responses to customers anytime, anywhere. Purpose: This research aims to identify and prioritize IoT applications in the Iranian banking industry based on business continuity indicators. Methods: First, based on the comprehensive literature review and practical experiences, IoT applications in the banking industry are identified. Then, each indicator's weight was calculated using the Grey Decision-making trial and evaluation laboratory (DEMATEL). Finally, IoT-based applications in the Iranian banking industry have prioritized using the multi-attribute utility theory (MAUT). Due to the unstable economic conditions for the financial sector, business continuity indicators are employed in this study. Also, the reason for using MAUT is to consider the utility of banking experts for performing IoT banking services. Findings: According to results, IoT-based services in the banking industry, including Transmit instant reports, smart ATMs, non-contact electronic payments, and electronic checks, are identified for Iranian banks. Then, These appropriate services are prioritized with the capabilities of Iranian banks.

The progression of Internet as a vehicle to penetrate and develop markets is far reached. Advancement in telecommunication and technology are very rapid in Malaysia. Further, the spur is supported and promoted by the government whilst Malaysian’s are receptive to this. However, Malaysian retailers seem to channel much of its turnover through the old avenue. This study is a litmus test on Malaysians awareness on the local apparel sites. Some of the highlighted rationale to shop for apparels online is the experience, convenience and availability. On the flip side, non-user friendly, safety and non-sensory environment are underscored. These variables are analyzed using Chi-Square analysis to test its statistical independence, followed by correlation and further regressed. The research is focused on university students within Klang Valley. There are limited resources to previous studies done on this subject as source of reference. Therefore, further studies can bring forth insights on retailers in Malaysia and the consumer’s behavior; or either one, as the catalyst influence awareness on our local apparel sites. Rhetorical as it may sound, no one is prepared to assume risks in a questionable market

This paper focuses on the problems of company’s sustainable management in an emergent environment. The authors’ vision of the functioning peculiarities in the formulation of a company’s strategy based on the information support is presented in the article. The world experience of studying the development of investment projects in companies of different industry sectors is investigated and analyzed according to the economic and mathematical modeling. A multivariate model of evaluation and selection of the investment project based on the hierarchy criterion of company's economic objectives with the information technology is developed as an embodiment of the strategic goal of ensuring the company's sustainability. The essence of the hierarchy criterion method is to determine the order and the value of priority of each individual criterion, thus, application of this method allows providing recommendations for making an effective management decision in unpredictable environment. The proposed model based on the hierarchy criterion of company’s economic tasks allows providing sustainability in emergent environment. The analysis and substantiation of the necessity of applying the proposed model with the information technology support is presented in this paper.

The article presents the results of studies on the development of new statistical and econometric approaches to modeling budget policy. The obtained results are applied on the example of tax revenue modeling. Accounting for various factors, including through the use of mathematical methods, will allow you to plan reforms with a scientific position. In particular, this is especially true in connection with the introduction of multi-year budget planning. To identify the main threats to the tax base, the phenomenon of “tax passes” wasused, which is based on an assessment of the effectiveness of a tax credit. The main participants in the formation of the “gross gap” in the value added tax revenues in Ukraine are shown. A correlation and regression analysis of the natural logarithms of the gross domestic product and tax revenues is carried out. This allowed us to determine the elasticity of tax revenues and GDP in Ukraine. A change in GDP directly affects the amount of tax payments to the budget, and the rate of change of indicators is proportional and changes insignificantly. These results allow us to strategically model the reform of discretionary tax policy mechanisms based on a quantitative assessment of tax gaps and the elasticity of tax payments. The authors were able to substantiate some proposals for reforming the budget policy regarding tax revenues.