درخت حوزه‌های تخصصی

The introduction of cloud computing techniques revolutionized the current of information processing and storing. Cloud computing as a competitive edge provides easy and automated access to the vast ocean of resources through standard network mechanisms to businesses and organizations. Due to the vast diversity of service providers and their respective variety of available services with different qualities, top managements often face difficulty for choosing the best available option. So, considering the growing significance of the mentioned issue, this study aims to identify and rank contributing factors in selection of cloud service providers. In that attempt, this research approaches its goal by going through three major phases. Firstly, in phase one, prior studies are reviewed for extracting related elements of selection. Secondly, by employing Fuzzy Delphi method and obtaining results by interviewing experts in this field such as IT managers and technicians, this study tries to finalize the list of contributing factors. Lastly, by utilizing Fuzzy best-worst multi-criteria decision-making method, which is one of the most recent techniques employed to statistically rank variables, this research introduces a list of vital factors for cloud service selection. Based on the findings of this study, there are five major categories involved in the selection process which are: performance, security, data management, personal data protection and environmental-organizational. The finalized result of ranking shows that, performance related factors such as accessibility, response time and capacity are the first priority. The runner-up is security with reliability and governance. Environmental-organizational variables lands in the third place by considering rental and network costs.

The infestation of the world pandemic has significantly changed the landscape of teaching and learning experience in Malaysia.  Particularly for the institution under study, E-learning, previously used as the support medium to face-to-face classroom teaching, has become the primary medium of teaching and learning amid Covid-19.  E-learning platform has replaced the face-to-face classes. Even though it is only a temporary approach, less is known in terms of its effectiveness.  The present paper intends to examine the factors contributing to E-learning's effectiveness in a Higher Education Institution in Malaysia amid the COVID-19 crisis. The Technology Acceptance Model underpinned the conceptual framework.   This study investigated the relationship between the independent variables (perceived usefulness, perceived ease of use, and self-motivation) and E-learning effectiveness.  The data were collected through an online self-administrated questionnaire using Google form and received a total of 354 respondents.  The data were analyzed using SPSS and Smart PLS.  The findings revealed that perceived usefulness, perceived ease of use, and self-motivation positively influenced E-learning's effectiveness.  This paper concluded that regardless of whether as the support medium or the primary medium in the teaching and learning process, the determinant to E-Learning effectiveness is still perceived the same. This study also supports the TAM proposition while incorporate self-motivation in measuring learning effectiveness.

Digital technologies are actively implemented in all areas of tourism. The article identifies the main areas of balancing interests in the field of tourism on the basis of optimization of digital marketing tools. Analytical research has shown that a set of sales channels in the Internet environment and a set of tools are formed, depending on the marketing strategy of the travel company. The main tactics and tools of digital marketing in tourism are highlighted. These are: the company's website, digital marketing channels - online channels for promoting and attracting customers: SEO, online advertising, email marketing, sales funnel, content marketing, teaser advertising, SMM, etc. The study proposes the application of portfolio investment theory to optimize investment in digital marketing tools to achieve a specific goal. The article uses a method of building a mathematical model that will optimally distribute financial investments in digital marketing. Thus balancing of interests in the field of tourism on the basis of digital marketing tools is offered on the basis of KPI indicators, according to the allocated purposes.

The conjecture of stock exchange is the demonstration of attempting to decide the forecast estimation of a particular sector or the market, or the market as a whole. Every stock every investor needs to foresee the future evaluation of stocks, so a predicted forecast of a stock’s future cost could return enormous benefit. To increase the accuracy of the Conjecture of stock Exchange with daily changes in the market value is a bottleneck task. The existing stock market prediction focused on forecasting the regular stock market by using various machine learning algorithms and in-depth methodologies. The proposed work we have implemented describes the new NN model with the help of different learning techniques like hyperparameter tuning which includes batch normalization and fitting it with the help of random-search-cv. The prediction of the Stock exchange is an active area for research and completion in Numerai. The Numerai is the most robust data science competition for stock market prediction. Numerai provides weekly new datasets to mold the most exceptional prediction model. The dataset has 310 features, and the entries are more than 100000 per week. Our proposed new neural network model gives accuracy is closely 86%. The critical point, it isn’t easy with our proposed model with existing models because we are training and testing the proposed model with a new unlabeled dataset every week. Our ultimate aim for participating in Numerai competition is to suggest a neural network methodology to forecast the stock exchange independent of datasets with reasonable accuracy.

Information Management and Analysis (IMA) implies the single data and knowledge base of the business organization whose algorithm and software complex is designed to solve functional problems of operating and dispatch management, marketing, financial arrangements, accounting, strategic planning and organizing e-document flow between the sources and users of information. The “information – communication - control” vector is directed at the achievement of corporate objectives. Assessment of IMA implementation efficiency is complicated by the fact that implementation of managerial (informational) solutions is possible indirectly, with the flows of material, financial and informational resources; the IMA algorithms are valid for a certain range of situations and modes, whose frequency and duration of action are not known in advance. The study is aimed at formalizing compatibility conditions for a set of economic and technical, actual, and probabilistic indicators applied for justifying the IMA implementation efficiency for industrial entrepreneurship. The IMA effectiveness is expected to be calculated as a total of network (communication) effects per each block of IMA algorithms, factored the presentation of information operability; to calculate cost-effectiveness (recoupment of investment) it is supposed to modernize the structural capital evaluation procedure according to A.Puliс. The article contains an introduction, concept of IMA, application of system efficiency theory to IMA, building the structure of IMA efficiency indicators, and conclusion. The main method of study: system approach.

Handwriting Analysis has been used for a very long time to analyze an individual’s suitability for a job, and is in recent times, gaining popularity as a valid means of a person’s evaluation. Extensive Research has been done in the field of determining the Personality Traits of a person through handwriting. We intend to analyze an individual’s personality by breaking it down into the Big Five Personality Traits using their handwriting samples. We present a dataset that links personality traits to the handwriting features. We then propose our algorithm - consisting of one ANN based model and PersonaNet, a CNN based model. The paper evaluates our algorithm’s performance with baseline machine learning models on our dataset. Testing our novel architecture on this dataset, we compare our algorithm based on various metrics, and show that our novel algorithm performs better than the baseline Machine Learning models.

For the last three decades, research on Information Technology Business Value (ITBV) has highlighted how organizations can create greater value from IT investments in different industries, including the healthcare sector. There has been some research investigating the business value of Health Information Systems (HIS). However, the current body of knowledge regarding the challenges in front of proper business value realization of these systems is limited. This study investigates the challenges of HIS business value creation using a combination of the Fuzzy Analytic Hierarchy Process (FAHP) and fuzzy Decision-making Trial and Evaluation Laboratory (DEMATEL). First, this study reviews the literature to identify the main challenges in the field. The outcome of this step revealed three main categories and 22 challenges, including technological (ten challenges), organizational (eight challenges), and environmental (four challenges). Then, this study first uses FAHP to evaluate the weighting for each criterion and then adopts the fuzzy DEMATEL method to establish contextual relationships among those criteria. We find out that technological challenges are the most crucial dimension. Moreover, we observed that “infrastructure costs” has the highest priority. Under the technological dimension, “maintenance costs” and “systems compatibility” challenges are the most critical since they are in the cause area and directly influence the HIS outcomes. Under the organizational dimension, “Change in strategic objectives” is the most important challenge. Moreover, “inter-departmental coordination”, “training costs”, “proficiency”, and “users’ knowledge” are affected by each other as well as influenced by the net causes. The outcome of this study shows that to handle HIS business value creation challenges, healthcare executives should start with infrastructure costs, maintenance costs, and systems compatibility challenges.