درخت حوزه‌های تخصصی

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.

The purpose of this paper is to investigate the role of political instability in the context of the association between board of directors (BOD) and audit committee (AC) quality as indicators of corporate governance effectiveness and earnings management (EM). The non-financial listed companies on the Palestine Exchange (PEX) between the period from 2011 to 2018 were the samples of the study. Based on the OLS regression results by using a panel data of 232 observations, the findings show that the BOD quality is positively related to EM, while AC quality is negatively associated with EM. The results also reveal that political instability plays a moderating role by weakening the relationship between the AC quality and EM during the severe unstable political situation, while the BOD quality is negatively associated with EM under the same situation. This finding implies that the BODs might substitute ACs under severe political instabilities to protect the stockholders and stakeholders’ interests. Unlike most previous studies, this article addresses political instability as a moderating variable for the relationship between the BOD and AC quality as a composite measure of EM in the most emerging and smallest stock market in the region. The results of this work may assist the regulatory bodies, policymakers, and practitioners in revising the corporate governance code to promote the efficiency of the BOD and AC monitoring functions for the purpose to improve the faithfulness and reliability of financial reports and also to deter the management from engaging in critical levels of EM.

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 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.

In the era of globalization and standardization, Information Technology (IT) brought many changes in people’s lives, it also influenced people's behaviour, communication, and lifestyle. The ability of IT in the business and community is to sustain in an increasingly competitive and global environment which largely influenced their capacity to access information as a resource and usage of advanced technologies. This paper analyzing the impact of IT on the Muslim community in the era of Globalization and Islamization. Several types of research have been done on IT and Islam, IT and behavioural and so on, while this paper specifically focusing on the Muslim community in the era of Globalization and Islamization. Information technology has undoubtedly become the central drive for the evolution of a modern Muslim society globally. The Muslim world or society, like the rest of the ‘world’, participates in the evolution, as well as the usage of using IT to obtain Islamic materials. Such materials include among others the translation of the Qur’an, Tajweed, Hadith, and Tafseer, which are available in word, audio, and video forms through digital content or via interactive chat rooms and forums. This paper focuses on Islamic literature globally accessible and assumes a vital role in spreading Islam all over the world. The paper recommends initiatives policy by government and NGO to promote IT technologies among Muslims around the world for a viable impact on society

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.

Corporate Social Responsibility (CSR) is a general concept where companies voluntarily decide to adopt social, economic and environmental responsibilities for a better society and environment. Researchers in the management field have created various CSR models and theories. Moreover, enterprises are working out to strength its competitiveness performance though adopting CSR approaches. For that, decision makers in an enterprise have to target the most appropriate CSR approach that fit with the environment and the nature of their enterprise. The Analytical Hierarchy Process (AHP) has been presented through the article in order to help an organization take decision toward the most convenient CSR method according to many characteristics and criteria.

The purpose of this paper is to identify and prioritise mobile wallet (m-wallet) key adoption factors (KAFs). 9 KAFs are proposed by authors on the basis of a systematic literature review. Authors have proposed one novel factor influencing adoption called 'contactless transactions' due to pandemic and new normal post-Covid-19. This has resulted in a total of 10 KAFs. The fuzzy TOPSIS approach is proposed to rank these key adoption factors (KAFs). Sensitivity analysis has also been conducted to check the robustness of the study. Examining the literature indicates that this study is among the first attempts to prioritise key adoption factors (KAFs) using fuzzy TOPSIS. The results show that perceived security, trust, performance expectancy, perceived ease of use and contactless transactions are among the top 5 adoption factors. The findings of this research will be beneficial for both academicians and practitioners. The key adoption factors (KAFs) proposed in the paper will help practitioners develop strategies for building a wider acceptance of m-wallet among customers. Moreover, the fuzzy TOPSIS technique discussed in this paper will apprise managers about critical factors to be focused upon. This study will provide an integrated framework for academicians to carry out further research in the field of mobile wallets.

This article discusses a device focused on images that enables users to recognise and detect many face-related features using the webcam. In this article, we are performing comprehensive and systemic studies to check the efficacy of these classic representation learning structures on class-imbalanced outcomes. We also show that deeper discrimination can be learned by creating a deep network that retains inter-cluster differences both and within groups. MobileNet, which provides both offline and real-time precision and speed to provide fast and consistent stable results, is the recently suggested Convolutional Neural network (CNN) model. The recently proposed Convolutional Neural Network (CNN) model is MobileNet, which has both offline and real-time accuracy and speed to provide fast and predictable real-time results. This also solved a problem related to the face that occurs in the identification and recognition of the face. This paper presents the different methods and models used by numerous researchers in literature to solve the issue of faces. They get a better result in using the highest number of layers. It is also noted that the combination of a machine learning approach with multiple image-based dataset increases the efficiency of the classifier to predict knowledge related to face detection and recognition