درخت حوزه‌های تخصصی

Equity is the basic structural component of the development of any business, so it is important for an industrial enterprise to develop tools to determine its effective management. It it is impossible without conducting qualitative financial analysis, timely and effective adaptation of valuation approaches in the modern conditions of functioning of enterprises. The effective functioning of enterprises is impossible without the use of modern complex methods, which include not only a methodology, a system of indicators, but also modern technologies for their assessment, planning and control. Information management is one of these technologies. To solve the problems of the study we used the method of structural-logical analysis, methods of theoretical generalization and comparative analysis, synthesis and method of grouping of absolute and relative values, graphical method and information management methods. The result of the study is the formation of a comprehensive approach to the financial analysis of the equity of the enterprise on the formed system of four groups of indicators. These indicators take into account the state of equity, its efficiency, ensuring risks in the process of the enterprise and directions of financial analysis.

The motivation of this paper is to examine empirically the effect of social media marketing on value equity, relationship equity and brand equity on fashion apparel brand among Universiti Malaysia Kelantan (UMK) students who have high attributes of internet savvy’s and take delight in undertaking social media marketing. This study is backed by the use and gratification theory that creates desire for amusement and enhancement of information while people use social media marketing.  Data was collected by means of Google Form online survey from a total of 361 respondents. The simple random sampling approach was utilized to collect data from the respondents and data analyzed using the SPSS. The findings indicated that social media marketing activities, which are entertainment, interaction, trendiness, and customization had a positive effect on customers’ equity among students. The results confirm that social media marketing is one of the key success factors in enhancing customer equity. Further, the results showed that interaction is the first concern among the respondents. In other words, the communication between the apparel fashion brands industry with customers is important and helps to create relationships so that customers can get more information about them.

Globalization is one of the important elements of external environment of the enterprises, that is why it is defined to be the main object of this study. The main signs of globalization in international trade and the qualitative / quantitative changes caused are studied, in particular, attention is paid to the mutual exchange of resources to solve international problems, including environmental ones. The transformation of competitive / monopoly relations under the influence of globalization in the areas of levels of cooperation, the ratio of competition / rivalry, the dependence of competition on innovation, models of competitive behavior are analyzed. The impact of globalization on economic processes of influences redistribution in the markets between residents and nonresidents is investigated, the factors that cause changes in investment activity of nonresidents are identified, namely the direct relationship between changes in the index of economic globalization and the number of foreign enterprises in Ukraine. Based on the research, the identified exogenous factors are complemented by such factors as protection of intellectual property rights and prevention of abuse of intellectual property rights, and endogenous - as a relationship of decisive influence on businesses in specific markets, management awareness of the impact of their transactions on the market and others. It is concluded that globalization does not take into account the national characteristics of individual economies, the resource potential of development, but involves the use of existing benefits, respectively, those who want to become part of it must acquire certain exclusivity, disseminate relevant information, introduce innovation in enterprise management systems, show interest in cooperation with the relevant participant for the development of digitalization, social and economic transformations.

The aim of the study is to develop a set of organizational and pedagogical conditions for integrated training of working teachers and students of pedagogical institutions of higher education to perform labor functions, highlighting the role of teachers in the professionalization of the educational process in a Smart Environment. The article considers the main directions of transformation of the role position of future teachers in the professionalization of the educational process. The article has presented structurally functional model development of role positions of teachers in the formation of professional competencies of students. The development of the role position of the teacher has considered in relation to his professional and personal development and self-awareness as a subject of the educational process under the influence of a Smart Environment. The mechanism of realization of such model has offered by the integrative program which provides integration of formal and informal education and formation on such basis of new competences and development of components of a role position of the future teacher.

Information technology is becoming a basic tool for many industries, as well as creating an opportunity for direct active communication of all market participants, which significantly increases competition. As a result, customers have a very large selection of goods and services, fairly easy access to them, and significant price diversification. All this leads to new requirements for modern marketing. Modern marketing significantly changes not only the functions but also the approaches to business processes. A highly competitive environment requires companies to use a system of interconnected marketing tools using an integrated marketing approach. The paper is devoted to investigating advertising prices and advertising strategies of Google. The list of major Google products is analyzed. The relevance of advertising strategies to goals, ad placement, message creation, budget constraints, and ad delivery is determined. The difference in advertising prices in different countries has been studied. The cost per click analysis of European countries is carried out. Using the DEA model analyzed advertisement efficiency by VRS technology and input-oriented efficiency for European countries.

In an EPS lesson, the student can learn in three different ways, including learning by doing, observing, or thinking; the last method will be the subject of our study, the objective of which is to show how a debate of ideas (sociocognitive conflict), between a group of students will make it possible to construct learning through the educational mediation of the teacher? So by verbalizing the problems encountered in learning situations and concretizing theoretical behaviors (proceduralization of knowledge), students will be able to learn in an autonomous and responsible manner (self-management). This expected result is one of the purposes of competence-based pedagogy as well as the pedagogical orientations, namely to train a citizen capable of developing powers of analysis and reflection and the ability to adapt (the national charter for education and training) Control groups were planned to facilitate comparison of the results. At the end of the experiment, we noticed that the students in the experienced groups made greater progress than those in the control groups. The progress that has been made by the experienced groups confirms the research hypothesis that the learning built by the students themselves through a collective project based on the verbalization of actions and problem solving is not only more profitable for the students but also for the teacher

Blockchain technology is rapidly gaining the attention of financial institutions around the world, especially among decision makers in Islamic financial institutions who are planning to apply this innovative technology into their institutions activities which could be an upright solution for their issues and challenges. This paper contributes to the emerging literature on financial technology by discussing some of the innovative applications of blockchain in Islamic financial institutions. In addition, this paper sheds light on the main opportunities and challenges facing application of Blockchain Technology in the Islamic financial industry and highlight the way forward to address these issues. Relying on the previous literature and analysis; this paper confirms the enormous opportunities for utilizing blockchain technology in various Islamic financial applications such as Waqf, Zakat and Sukuk. On the other hand, the main challenges towards implementing blockchain in this industry are the complexity of Islamic finance products added to the opacity of its application which end up with unclear regulations and lack of standards.

One of the most important risks that the banks and financial institutes face, is credit risk which is related to not-paid instalments or the instalments paid with delay by borrowers. Banks use credit scoring models In order to prevent this type of risk. The goal of this research is to investigate the joint effect of economic time cycles and the industry sector on credit scoring models we are seeking to answer the key question: “when should bank change their credit scoring models based on economic time cycles and for which industry sectors?”. The dataset of the research involves all companies that were applied for a loan in one of the Iranian major banks during the years 2008-2011. The companies have been divided into four industry sectors including “Industry and Mine”, “Oil and chemical”, “Service and Infrastructure” and finally “Agriculture”. Based on the sector of the industry and year, 54 explanatory variables, both financial and non-financial, 12 distinct industry sectors and time-specific data sets are built then classification methods were used to classify customers into two groups of defaults and non-defaults. Finally, we compared the results by Wilcoxon Test. The results show that the companies that are in the groups of Industry and Mine and Agriculture, need their own special credit scoring based on industry type model and time but two other groups don’t need of course in the studies dataset duration. Finally, the study concluded by introducing the credit scoring strategies for different four-cycle of economies

Due to enchantment in network technology, the worldwide numbers of internet users are growing rapidly. Most of the internet users are using online purchasing from various sites. Due to new online shopping trends over the internet, the seller needs to predict the online customer’s choice. This field is a new area of research for machine learning researchers. A random forest (RF) machine learning method is a widely used classification method. It is mainly based on an ensemble of a single decision tree. Online e-commerce websites accumulate a massive quantity of data in large dimensions. A Random Forest is an efficient filter in high-dimensional data to reliably classify consumer behaviour factors. This research article mainly proposed an extension of the Random Forest classifier named “Weighted Random Forests” (wRF), which incorporates tree-level weights to provide much more accurate trees throughout the calculation as well as an assessment of vector relevance. The weighted random forest algorithm incorporates the C4.5 method named a “Hybrid Weighted Random Forest” (HWRF) to forecast online consumer purchasing behaviour. The experimental results influence the quality of the proposed method in the prediction of the behaviour of online buying customers over existing methods.

Mobile Banking has always been the focus of the banks to provide an alternative banking channel for the bank customers. However, the adoption rate was still relatively low and increased gradually over the decade. Thus, it is important to examine the factors affecting Mobile Banking Adoption to provide better insights to improve the situation for the bank customers to adopt it for banking purpose. In this conceptual article, the past literature related to the investigation of Technology Adoption was reviewed. Based on the review and also the understanding of the theory, this article further explores on the interactions of the constructs from Technology Acceptance Model (TAM) & Unified Theory of Acceptance and Use of Technology (UTAUT), Perceived Trust, Technology Awareness and Mobile Banking Adoption. With the study of these interactions, it is very likely to create new avenues for future research.

Now a day's software is the baseline for the success of any organization. There is a huge demand of quality software in the customer-oriented market. Regression testing makes it possible but it’s a costly affair. Regression test suite minimization is way to reduce this cost but it is NP hard problem. This paper proposes an effective approach for regression test suite minimization using Artificial Ecosystem Optimization algorithm. To improve its performance a modified Artificial Ecosystem Optimization algorithm is proposed for Test case minimization. To evaluate the performance of proposed approach experiment is conducted in controlled parameter setting on open-source subject program from SIR repository. The results are collected and analyzed in comparison to existing approaches using statistical test. The test results reflect the superiority of proposed approach.

Object Detection has been one of the areas of interest of research community for over years and has made significant advances in its journey so far. There is a tremendous scope in the applications that would benefit with more innovations in the domain of object detection. Rapid growth in the field of machine learning has complemented the efforts in this area and in the recent times, research community has contributed a lot in real time object detection. In the current work, authors have implemented real time object detection and have made efforts to improve the accuracy of the detection mechanism. In the current research, we have used ssd_v2_inception_coco model as Single Shot Detection models deliver significantly better results. A dataset of more than 100 raw images is used for training and then xml files are generated using labellimg. Tensor flow records generated are passed through training pipelines using the proposed model. OpenCV captures real-time images and CNN performs convolution operations on images. The real time object detection delivers an accuracy of 92.7%, which is an improvement over some of the existing models already proposed earlier. Model detects hundreds of objects simultaneously. In the proposed model, accuracy of object detection significantly improvises over existing methodologies in practice. There is a substantial dataset to evaluate the accuracy of proposed model. The model may be readily useful for object detection applications including parking lots, human identification, and inventory management.

In the current paper, we have assimilated fuzzy techniques and optimization techniques, namely differential evolution, to put forward a modern archive-based fuzzy evolutionary algorithm for multi-objective optimization using clustering. The current work account for the application of a cluster associated approach. Specific quantitative cluster validity measures, i.e., J-measure and Xie-Beni, have been referenced to carry out the appropriate partitioning. The proposed algorithm introduces a new form of strategy which attempts to benefit the feasible search domain of the algorithm by minimizing the analysis and exploration of less beneficial search scope. This clustering method yields a group of trade-off solutions on the ultimate optimal pare to front. Eventually, these solutions are united and maintained in an archive for further evaluation. The current work summarizes and organizes an archive concerned with excellent and diversified solutions in an effort to outline comprehensive non-dominated solutions. The degree of efficiency is revealed with respect to partitioning on gene expression and real-life datasets. The proposed algorithm seeks to reduce the function assessment analysis and maintains a very small working population size. The effectiveness of the proposed method is presented in comparison with some state-of-art methods.