درخت حوزه‌های تخصصی

The purpose of the current study is to validate the pattern of brand marketing efforts on social media with customers in the dermo-cosmetic industry.In terms of method and time frame of data collection this study is considered cross-sectional research. The statistical population involved the dermoc-osmetics industry clients of Serita brand. The sample size was 384 people and the employed sampling method was simple randomization method. To validate the pattern of brand marketing efforts on social media, the researcher made use of the partial least squares method alongside with Smart PLS software. The data collection tool was a questionnaire that was validated by structural validity, convergent validity and divergent validity. The reliability of the questionnaire was judged by employing Cronbach's alpha and combined reliability. The outcome indicated that the creating informative content and social content are considered to be the fundamental factors of the model that affects client trust. Client confidence brings about. Client engagement and encourages attractive page design. Accordingly, interacting with clients and designing attractive pages touches word-of-mouth advertising and eventually leads to the efficacy of social marketing efforts.

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).

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.