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Pandemic has brought all together a new environment of working and compelled all the off line educational institutions to become online educational platforms and strengthen their online resources. We need to understand online platforms as universities, institutes, schools, colleges or any educational institute which are working online and providing degrees, certificates, diplomas for several courses and programs. In different researches related to online education and Covid -19, investigations addressed student’s perspective or teachers perspective. Literature review has showed the gap in exploring the turnaround strategies inspired by the parent’s perspective for online education especially with respect to young children (Age group 8 to 12 years). Apart from literature review and analysis of secondary data from websites and search engines, qualitative research was undertaken to know about parent’s views in general about the online platforms and particularly about WHJ (White Hat Junior). The focused group discussion and the indepth interviews revealed very useful information with regard to Online educational platforms and especially WHJ in relation to Covid -19 times. Findings relate to awareness, acceptability, perception change, costs, safety issues, etc. It has brought out elaborately in this case based research, how parents expectation may impact the turnaround strategies of their wards’ online educational platforms. In different researches related to online education and Covid -19, investigations addressed student’s perspective or teacher’s perspective.

This study was conducted to determine the stock portfolio with the best return and low-risk investments using momentum-contrarian strategies (MCSs). The momentum-Contrarian strategy is one of the well-known models to construct the portfolio which suggests buying the stocks with the best performance (the winner stocks) and selling the stocks with the worst performance (the loser stocks). The optimal values of the portfolio's objective function and the weight of all assets in the portfolio that are not necessarily the same are calculated by defining a nonlinear multivariate optimization model combined with momentum-contrarian strategies (MCSs). The return information of companies listed on the Tehran Stock Exchange from 2014 to 2019 was used to select the best optimal portfolio. The results confirmed the stability in the profitability of the contrarian optimal portfolio with minimum risk compared to other optimal portfolios. Furthermore, through MATLAB software the optimal weight of assets in the optimal portfolio is calculated based on statistical data.

This research, in line with the strategy of the World Customs Organization, order to provide a structural model for improving the ethics and administrative health of employees based on the use of information technology in customs affairs with a combined approach of fundamental theory and interpretive structural modeling to understand how information technology affects ethics and Administrative health and investigating the power of influence and the degree of dependence of the variables of ethics and administrative health of employees in the form of drawing a comprehensive structuring model. In the implementation of this research, a mixed method was used in the qualitative part of the foundation's data theory according to the research needs and structured interviews were used to collect data. To collect data in a qualitative method, with the help of Maxqda software, research findings through the opinions of 13 experts in three stages of open-centered and selective coding in the form of 6 categories affecting the ethics and administrative health of employees in the form of the Strauss paradigm model and Corbin and it was expressed theoretically. After building the theory, in the quantitative stage, interpretive structural modeling has been used in order to understand the relationship between the variables and the leveling of the promotion of ethics and administrative health of Iran Customs. The results of the research show that the variable "use of smart technologies" is the first level variable in the promotion of ethics and health, and the variables "Analysis of the situation of manpower and customs processes, ethical characteristics of employees and laws and management of information technology and human resources" » is the second level variable. And the variables of "conditions and structure of the organization and the requirements and infrastructure of information technology" are the variables of the third level.

In recent years, industrial clusters have received considerable attention from economists and industry analysts because they are seen as the main reason for certain economic regions' economic growth and success. For many Industrial States Organization, the selection of industrial clusters has become a critical strategic consideration due to the Budget allocation priority. In this paper, an extended qualitative flexible multiple (QUALIFLEX) methods is used to solve problems regarding the priority among this cluster using probability hesitant fuzzy information, which can lead to allocating the budget for industrial clusters more effectively. For more accuracy, we have applied a Hesitant fuzzy Topsis for prioritizing. Both rankings have been aggregated by the Copeland method. From our research results, the Larestan Muscat is of great importance, and Abade Inlaid Wood, Citrus packaging, Shiraz Marquetry, and Niriz stone have ranked respectively.

Social networks advertisements can be employed as a powerful means of communication to achieve goals such as sales, profitability and reinforcing brand image. Organizations managers have established a department titled “public relations” in their organizations, through which they communicate with individuals inside and outside the organization, so that they can fulfill their goals at lower costs and within shorter time by informing and persuading those individuals. In this regards, the present study is aimed at evaluating the extent to which public relations of private organizations employ social networks to introduce their products and services. Research population consists of managers and public relation experts of private sector’s organizations in Yazd, Iran. The present study takes a survey method and is regarded as field-work research. Sampling method is based probability and availability. Due to the limited population, 76 individuals were selected as the sample through limited population formula. Data was analyzed via Smart-PLS. results reveal that public relations of private organizations employ social networks at an optimal and acceptable level to introduce their products and services. Hence the hypothesis of the study is confirmed.

The purpose of this study was to present an optimal model Predicting Future Cash Flows optimized neural network with genetic (ANN+GA) and particle swarm algorithms (ANN+PSO). In this study, due to the nonlinear relationship among accounting information, we have tried to predict future cash flows by combining artificial intelligence algorithms. Variables of accruals components and operating cash flows were employed to investigate this prediction; therefore, the data of 137 companies listed in Tehran Stock Exchange during (2009-2017) were analysed. The results of this study showed that both neural network models optimized by genetic and particle swarm algorithms with all variables presented in this study (with 15 predictor variables) are able to provide an optimal model Predicting Future Cash Flows. The results of fitting models also showed that neural network optimized with particle swarm algorithm (ANN+PSO) has lower error coefficient (better efficiency and higher prediction accuracy) than neural network optimized with ge-netic algorithms (ANN+GA).

The application of machine learning technologies for cancer detection purposes are rising due to their ever-increasing accuracy. Melanoma is one of the most common types of skin cancer. Detection of melanoma in the early stages can significantly prevent illness and fetal death. The application of innovative machine learning technology is highly relevant and valuable due to medical practitioners' difficulty in early-stage diagnoses. This paper provides an open-source tutorial on the performance of an algorithm that helps to diagnose melanoma by extracting features from dermatoscopic images and their classification. First, we used a Dull-Razor preprocessing method to remove extra details such as hair. Next, histogram adjustments and lighting thresholds were used to increase the contrast and select lesion boundaries. After using a threshold, a binary-classified version of image was obtained, and the boundary of the lesion was determined. As a result, the features from skin tissue were extracted. Finally, a comparative study was conducted between three methods which are Artificial Neural Network (ANN), Support Vector Machine (SVM) and K-Nearest Neighbor (KNN). The results show that ANN could achieve better accuracy (83.5%). In order to mitigate the biases in existing studies, the source code of this research is available at hadi-naghavipour.com/ml to serve aspiring researchers for improvement, correction and learning and provide a guideline for technology manager practitioners.

In the 21st century, the meaning of places is essential to people. Meanings have gained symbolic importance through tourism heritage. Tourism is a powerful force  in shaping the world and our understanding of different cultures, people, and  places. This research investigates the complexities of religious tourism and the  management of religious destinations. It obtains criteria for managing religious  goals with a detailed look and uses the descriptive-analytical method based on  library documents and the opinion of research experts. Then, using research experts  and ISM-PLS hybrid approach, a three-level framework for managing religious  goals in Yazd city has been presented and analyzed. The results showed that the  government's decisions and actions were the most effective criteria. The ultimate  goal was to create a sense of trust and security among religious tourists. It is hoped  that the findings of this research will be a starting point for managing religious  tourism destinations and a guide for examining the complexities of Islamic tourism  destinations and their management.

Nowadays, customer satisfaction is regarded as a strategic and influential factor for the success of various businesses. On the other hand, tourism, the world's largest and most diverse industry, is also a significant source of income and job creation for many countries. Therefore, the present study examines the effect of nostalgia, experiential marketing, and experiential values as relatively novel concepts on satisfaction in the tourism industry. In light of the COVID-19 outbreak, the research population includes all tourists who have previously visited the Kashan Rosewater Festival. Furthermore, since the population size is uncertain, it is assumed unlimited. A convenience sampling method was used to select sample members from the population. Methodologically, it is a descriptive survey study based on the subject matter under investigation. It is also a correlational study. A partial least squares structural equation modeling (PLS-SEM) technique was used to analyze the questionnaire results. Based on our findings, nostalgia affects pull motivation, patronage behavior, and future travel intention. However, pull motivation does not influence travel intentions.

هدف: هدف اصلی این پژوهش، بررسی تأثیر عدالت سازمانی بر اعتماد سازمانی و همچنین تأثیر عدالت سازمانی از طریق اعتماد سازمانی بر وفاداری سازمانی کارکنان شرکت برق منطقه ای خراسان است. طرح/روش/روش شناسی: روش انجام تحقیق توصیفی و پیمایشی است. جامعه آماری این تحقیق شامل کلیه کارکنان شرکت برق منطقه ای خراسان مشهد می باشد به طوری که 93 نفر به روش نمونه گیری تصادفی ساده و بدون جایگزینی به عنوان نمونه مورد بررسی انتخاب شدند. برای جمع آوری اطلاعات مربوط به عدالت، اعتماد و وفاداری سازمانی از پرسشنامه استاندارد استفاده شد. پایایی پرسشنامه ها با استفاده از ضریب آلفای کرونباخ تأیید گردید. به منظور تجزیه و تحلیل داده ها از آمار توصیفی و استنباطی استفاده شد. در آمار استنباطی از مدل سازی معادلات ساختاری (SEM) و تحلیل مسیر استفاده شد. یافته ها: نتایج به دست آمده از پژوهش نشان داد که عدالت سازمانی تأثیر مثبت و معناداری بر اعتماد سازمانی داشته است. به عبارت دیگر، می توان ادعا کرد که اگر مدیران به بهبود فضای عدالت در سازمان بپردازند و به آن ادای احترام کنند، می توان انتظار داشت که سطح اعتماد سازمانی بهبود یابد. همچنین نتایج نشان داد که عدالت سازمانی از طریق اعتماد سازمانی تأثیر معناداری بر وفاداری سازمانی ندارد و این بدان معناست که تأثیر مثبت و معنادار عدالت سازمانی بر اعتماد سازمانی نمی تواند منجر به پیدایش وفاداری کارکنان نسبت به سازمان آنها شود.