درخت حوزه‌های تخصصی

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).

World of technology provides everyone with a great outlet to give their opinion, using social media like Twitter and other platforms. This paper employs machine learning methods for text analysis to obtain sentiments of reviews by the people on twitter. Sentiment analysis of the text uses Natural language processing, a machine learning technique to tell the orientation of opinion of a piece of text. This system extracts attributes from the piece of writing such as a) The polarity of text, whether the speaker is criticizing or appreciating, b) The topic of discussion, subject of the text. A comparison of the work done so far on sentiment analysis on tweets has been shown. A detailed discussion on feature extraction and feature representation is provided. Comparison of six classifiers: Naïve Bayes, Decision Tree, Logistic Regression, Support Vector Machine, XGBoost and Random Forest, based on their accuracy depending upon type of feature, is shown. Moreover, this paper also provides sentiment analysis of political views and public opinion on lockdown in India. Tweets with ‘#lockdown’ are analysed for their sentiment categorically and a schematic analysis is shown.

Blockchain is one of the trending emerging technologies that enables immutable data storage over distributed ledgers. The fundamental features of blockchain technology, such as record and identity traceability and immutability makes it an attractive alternative for the state-of-the-art information systems. Thus, blockchain has found its way into various fields. In Iran, blockchain technology has been employed in different areas including: commercial mining platforms, secure exchange platforms, and innovative trustless projects. One of the main applications of blockchain is secure management of sensitive information, which makes it a suitable infrastructure for providing advanced control over data in police task forces. The motivation behind this research is to provide a conceptual framework for employing blockchain in law enforcement organizations by analysis and comparison of best practices in other countries and academic case-studies. We provide a systematic overview of case-studies by qualitative content analysis. Moreover, the reliability of our statistics is evaluated by Cohen's kappa coefficient roughly 0.64. Finally, the prioritized applications were evaluated by a 14 member experts panel through fuzzy Delphi method with a Kendall’s Coefficient of Concordance of W=0.711, indicating high rates of agreement among members. To this end, “trustless authentication systems”, “distributed data/resource/information management”, and “inter-department integrated information systems” were selected as most valuable applications of blockchain for police task forces and law enforcement agencies in Iran.

This paper describes an alternative view of the internationalization process in higher education by comparing the traditional and non-traditional indicators on how the level of internationalization is measured; additionally, barriers that exist on both sides are reviewed and discussed. As higher education institutions are very accustomed to and focused on the number of international students, international cooperation agreements, visiting guest professors and international projects, another dimension could be added if we start to account and measure things that are happening in the digital communication, online data exchange, usage of mobile devices and other technologies. Authors argue that it would be necessary to include this perspective in the development of internationalization strategies, institutional development plans as well as external outreach tactics. The paper is based upon empirical knowledge coming from Erasmus+ KA2 project and a brief institutional self-assessment performed by Riga Technical University International Cooperation and Foreign Students Department.

The inefficiency of the national security system is one of the biggest threats to Ukraine's national security. The strategic planning in the field of security and defense has designed to identify the means, including the future structure of forces, that would allow the institutions of the defense and security sector to effectively deal with potential future threats. The purpose of this study is development of theoretical and practical measures to increase the effectiveness of strategic management of national security processes on the basis of goal setting, forecasting and planning in the context of informatization of society. The relevance of this study is due to the needlegal regulation and improvement of the state system of strategic planning of national security of Ukraine. To achieve the goal of the study was used special scientific methods of legal knowledge. The results of the analysis showedwhat in the basis ensuring national security must rely on the principle of systematization, which means that the security and defense sector of Ukraine is considered as a single object of forecasting and planning. This study substantiates the main directions systemic reform of the security and defense sector, which has carried out in Ukraine to ensure the protection of the constitutional order, sovereignty, territorial integrity of the state in the face of armed aggression. The priorities should be implemented through key tasks, such as the establishment of a comprehensive strategic analysis of military threats to Ukraine's national security, coordination of intelligence activities, development of joint intelligence capabilities of the defense forces in order to obtain complete and reliable warning information for timely decision-making guaranteeing the military security of the state.

Nowadays with the ever-increasing growth in social media platforms and the creation of different forms of online activism, the word known as “Campaign” has become a familiar and useful term in people’s everyday lives. Campaigns with all kinds of social aims especially using Hashtags are run on social media platforms by individuals, charities, NGOs, governments, municipalities and brand companies and with peoples' participation and value co-creation, appropriate results are achieved and the desired changes are made in people’s attitudes and the behavior of individuals, businesses, or governments. Therefore, there seems to be a new form of a virtual public sphere where there is action, dialog and social mobilization, which leads to the formation of public opinion and social change in the digital era. In this paper, using a critical review method, we are going to investigate a public sphere's literature and study its core features (1. access, 2. dialog, 3. action, and 4. public opinion) in digital campaigns and online platforms. Then, in the last part, we are going to map those in a real case study in order to further clarify the arguments and show how social campaigns on online platforms contribute to the formation of a public sphere in the digital era.

Deep learning techniques have become very popular among Artificial Intelligence (AI) techniques in many areas of life. Among many types of deep learning techniques, Convolutional Neural Networks (CNN) can be useful in image classification applications. In this work, a hybridized approach has been followed to classify lung nodule as benign or malignant. This will help in early detection of lung cancer and help in the life expectancy of lung cancer patients thereby reducing the mortality rate by this deadly disease scourging the world. The hybridization has been carried out between handcrafted features and deep features. The machine learning algorithms such as SVM and Logistic Regression have been used to classify the nodules based on the features. The dimensionality reduction technique, Principle Component Analysis (PCA) has been introduced to improve the performance of hybridized features with SVM. The experiments have been carried out with 14 different methods. It has been found that GLCM + VGG19 + PCA + SVM outperformed all other models with an accuracy of 94.93%, sensitivity of 90.9%, specificity of 97.36% and precision of 95.44%. The F1 score was found to be 0.93 and the AUC was 0.9843. The False Positive Rate was found to be 2.637% and False Negative Rate was 9.09%.

The E-commerce has been grown rapidly with the rise in the number of business entities. The expansion of e-commerce businesses, however, has created challenges to the tax authorities around the world. Due to the way in which e-commerce is being carry out, it may provide tax planning opportunities. This study aims to explore whether businesses that conducted e-commerce in Malaysia has the intention to do tax planning. Interviews were conducted with e-commerce business administrators. Result indicates that tax issues is not the main motivations for companies to do e-commerce. This indicates that other factors are more important for e-commerce businesses to consider in their planning stage