درخت حوزه‌های تخصصی

Learning effective segment depictions and resemblance measures are fundamental to the recuperation execution of a substance based picture recuperation (CBIR) structure. Regardless of wide research tries for a significant long time, it stays one of the most testing open gives that broadly impedes the achievements of real-world CBIR structures. The key test has been credited to the extraordinary "semantic hole" subject that happens between low-level photo pixels got by technologies and raised close semantic thoughts saw by a human. Among various techniques, AI has been successfully analyzed as a possible course to interface the semantic gap in the whole deal. Impelled by late triumphs of significant learning techniques for PC vision and various applications, in this paper, we try to address an open issue: if significant learning is a longing for spreading over the semantic gap in CBIR and how much updates in CBIR endeavors can be cultivated by exploring the front line significant learning methodology for learning feature depictions and likeness measures. Specifically, we explore a structure of significant learning with application to CBIR assignments with a wide game plan of definite examinations by investigating front line significant learning methodologies for CBIR endeavors under moved settings. From our exploratory examinations, we find some encouraging results and compress some huge bits of information for upcoming research.

Buying online is a trend especially for young customers aged less than 30 years old. A lot of studies have been conducted to investigate this phenomenon but hitherto no cohesive model has been established. Therefore, the present study is meant to investigate online shopping factors that contribute to customers’ purchase decision. Five factors were identified to have potential influence on online purchase decision and one factor is expected to be a mediator to affect the relationship. From 384 data collected from online customers who visited popular online shopping sites, it was found that all five factors (perceived convenience, perceived risk, perceived competence, perceived benevolence, and perceived integrity) lead to trust and at the same time trust acts as a quasi mediator to affect the relationship between these factors and online purchase decision. The findings provide the actively sought after evidence to support the claims on the role of these factors in affecting online purchase decision. Online businesses should incorporate the findings in order to facilitate customers’ decision making process while visiting their websites. The websites must contain or portray all the elements as found in this study.

The main aspects of using digital marketing tools in strategic management in the field of tourism have considered in the article. The study proved that the marketing strategy of the tourist enterprise is a determining factor in the choice of the main sales channels in the Internet environment. The article highlights the keydigital marketing tactics and tools. In the main directions defined strategic management in the field of tourismon the basis of optimization of digital marketing tools. To implement the target approach in the implementation of the marketing strategy of the enterprise, a system of KPIs proposed.

Sentiment Analysis or opinion mining is NLP's method to computationally identify and categorize user opinions expressed in textual data.  Mainly it is used to determine the user's opinions, emotions, appraisals, or judgments towards a specific event, topic, product, etc. is positive, negative, or neutral. In this approach, a huge amount of digital data generated online from blogs and social media websites is gathered and analyzed to discover the insights and help make business decisions. Social media is web-based applications that are designed and developed to allow people to share digital content in real-time quickly and efficiently.  Many people define social media as apps on their Smartphone or tablet, but the truth is, this communication tool started with computers. It became an essential and inseparable part of human life. Most business uses social media to market products, promote brands, and connect to current customers and foster new business. Online social media data is pervasive. It allows people to post their opinions and sentiments about products, events, and other people in the form of short text messages. For example, Twitter is an online social networking service where users post and interact with short messages, called "tweets." Hence, currently, social media has become a prospective source for businesses to discover people's sentiments and opinions about a particular event or product. This paper focuses on the development of a Multinomial Naïve Bayes Based social media data emotion analyzer and sentiment classifier. This paper also explains various enriched methods used in pre-processing techniques. This paper also focuses on various Machine Learning Techniques and steps to use the text classifier and different types of language models.

The purpose of this research was to identify the skills and abilities learners need in a digital learning environment during the Corona crisis. The research approach was applied in terms of objective and the data collected using the mixed-method approach. In the first part, using a qualitative approach and a document search method, 33 components (related to the skills and abilities of e-learners) were identified, and then19 components out of 33 with the highest frequencies were selected. The target population for this study included all MA students of the University of Tehran who had the experience of studying in an online learning environment, then 374 individuals were selected as a sample using the random sampling method. In the second part, using a quantitative approach and a descriptive-analytical research method, the questionnaire developed by the researcher relies on 19 components identified in the previous step. The experts' opinions proved the validity of the questionnaire—moreover, its reliability in 0.94 (Cronbach alpha). The data was analyzed by SPSS and LISREL, and the results of the data analysis demonstrate that the proposed model is a good fit. Among the 19 components surveyed, all are above average. Finally, the results indicated that the most critical components from e-learners’ view which more critical in digital learning were effective communication, use of the computer, active learning, learning skills, resilience, motivation toward e-learning, emotional intelligence, interaction with e-learning system, self-direct learning, time management, flexibility and adaptability, critical thinking, creativity, asking someone for help, leadership skills, stress management, self-organized, cognitive skills and self-assessment

The study has two main objectives: firstly, to examine the opportunity of the Momentum and Contrarian investment strategy for three different monetary systems to trade currencies in Forex markets using Symlet wavelet decomposition approach. Secondly, to examine the co-movements between the three monetary systems using wavelet coherence analysis. The findings indicate that an investor with momentum strategy can consider investing in Bitcoin and Gold market, while the contrarian investment strategy is more advisable for the fiat money market during crisis period. Furthermore, the wavelet coherence analysis indicates that Bitcoin currency is the most leading monetary system during the Covid-19 pandemic crisis, followed by gold. However, US dollar mostly leads Bitcoin during non-crisis periods, while Gold is found to lead the US dollar throughout the sample period of the study. This suggests that the cryptocurrency system or gold standard should be considered as the alternative monetary system for better economic stability specially during the crisis period. Moreover, Bitcoin and gold had an anti-phase correlation before the Covid-19 pandemic crisis, which implies better benefits of hedging in the non-crisis period, while during a crisis they are moving together across different horizons. In contrast, Bitcoin and Fiat Money are strongly correlated during non-crisis periods, while during covide-19 pandemic crisis the correlation is statistically insignificant. Overall, the outcomes offer significant guidance for policymakers in understanding which monetary system leads to better economic stability during the crisis period and provides many implications for market players such hedging and Diversification investments strategy in forex markets.

The heavy trends of the Information Society are knowledge that requires the spirit of innovation, creativity, flexibility and critical thinking “more than benign introspection.” In addition, information about each other’s relationships with oneself, the other and the environment is crucial to enable individuals to understand the complex reality. The Moroccan school is part of this societal vision, by renovating its education and training programs, which claim the development of the quality of procedural, cognitive and metacognitive strategies. In this perspective this research work aimed at studying the engineering analysis of investigation approaches in the teaching of SVT for the implementation of a reflexive practice in lycian learners, generating the ability to process information and invest in mechanisms for understanding, conceptualizing and proceduralizing cognitive and metacognitive strategies. Informational investigative capacity is crucial because it informs learning decisions, which can lead to innovations in the delivery of cognitive styles. To do this, we chose to conduct our study, through interview surveys and semi-structured questionnaires. The first among teachers and the second for SVT inspectors from three provincial directorates of National Education. The results show that the majority of those involved in education are involved in the classical informational approach and the experimental approach. The use of investigative analysis approaches remains episodic in some learning units (scientific ecological output and DNA extraction). Teachers are keen to introduce new information technologies to create favourable conditions for learning about investigative approaches, in order to improve the power of analysis, treatment and critical thinking and coping with situations of authentic and novel learning. We are concerned about the ability to understand what and how each of its actors is further shaping.