درخت حوزه‌های تخصصی

INTRODUCTION: Helicopter Emergency Medical Services (HEMS) provide medical care to critically ill patients and the injured immediately and provide faster treatment, thereby reducing the length of hospitalization. This study aimed to identify the policy implications of HEMS in Isfahan province. METHODS: This qualitative study was conducted using the thematic analysis method. The study population included the managers, personnel, and flight crews of Isfahan HEMS. The participants were selected using the purposive sampling method, followed by the snowball method. Initially, 14 individuals from the HEMS personnel were interviewed using the interview guide form, and then, the opinions of 15 participants from the flight crews were collected through an open questionnaire. Maxqda10 software was used for data coding. FINDINGS: The research findings were classified into challenges, opportunities, and implications. In terms of challenges, 11 themes and 34 categories were identified in this study. HEMS opportunities were also divided into 8 themes and 11 categories. The policy implications provided by the participants were also categorized into 8 themes and 28 categories. CONCLUSION: Considering that one of the most important known challenges was the lack of specialized helicopters and medicopters, according to the results, it is suggested that the managers of Isfahan HEMS take measures to solve the existing challenges and develop plans to strengthen the capacities and utilize the opportunities.

This article deals with developing a model of digital marketing with a focus on customer experience and with the aim of optimizing the customer management process, increasing the quality and length of the customer journey (increasing loyalty), and improving the consequences of the marketing process in companies, and seeks to answer this question. What is the digital marketing model with the customer experience management approach and what components does it include? The research method is mixed (qualitative-quantitative) and since a model for this issue is not available in past research, the first part of the research explores model extraction through qualitative methods (here, foundation data analysis) and to determine Relationships within the model quantitatively explain the model using quantitative methods (here structural equations). The method of collecting information in the qualitative part, in addition to conducting library studies, in the form of in-depth interviews with experts in the fields of information technology, marketing, and commerce, information technology policy, and actually business managers and stores that provide services and products through channels and digital tools in this section, the statistical sample limit was carried out by the snowball method (saturation to the end of the problem) and the quantitative part of the research and explanation of the model was through data collection with questionnaire tools and closed interviews from the customers of several digital businesses, which was done with the method 385 people were randomly selected and available using Cochran's formula. In the end, the main conditions, background conditions, intervening conditions, phenomena, strategies, and consequences affecting the digital marketing model with the customer experience management approach were extracted and the relationships between them were determined.

The purpose of the present study is to use the ensemble learning model to combine the predictions of Random Forest (RF), Long-Short Term Memory (LSTM), and Recurrent Neural Network (RNN) models for the Top and Bottom Prices of Bitcoin. To this aim, in the first stage, Bitcoin's top and bottom prices are predicted using three machine learning models. In the second stage, the outputs of the models are presented as feature variables to the Extreme Gradient Boosting (Xgboost) and Light Gradient Boosting Machine (LightGBM) models to predict the price tops and bottoms. Then, in the third stage, the outputs of the second stage are combined through the voting ensemble classifier pattern to predict the next top and bottom prices. The data of top and bottom Bitcoin prices in the 1-hour time frame from 1/1/2018 to the end of 6/30/2022 are used as target variables and 31 technical analysis indicators as feature variables for the three models in the first stage. 70% of the data is regarded as learning data, and the remaining 30% is considered for the second and third stages. In the second phase, 50% of the data is considered for learning the output of the previous stage and 50% for the test data. Finally, the prediction values are evaluated with real data for the three models and the proposed ensemble learning model. The results reveal the improvement of the performance, precision, and accuracy of the ensemble model compared to weak learning models.

Without utilization of computer and its related technology, modern day’s life cannot be headway. It has also transformed into an incredibly troublesome task. The genuine challenges included are shorter life cycles, cost effective and higher software quality goals. Despite these challenges the software developers have started to give cautious thought on to the procedure to develop software, testing and reliability investigation of software and to reinforce the method. Developer most fundamental decisions related to the perfect release time of Software. Software development method incorporates a piece of vulnerabilities and ambiguities. We have proposed a multi objective software release time issue under fuzzy environment using a software reliability growth model to overcome such vulnerabilities and ambiguities. Further we have discussed the fuzzy environment framework to deal with the issue. Considering model and issue, we can especially address the issue of when to release software under these conditions. Results are illustrated numerically.

Purpose: The spread of consumption in this day and age has gone so far that today it is considered an indicator of lifestyle and even some  find modern life without consumption meaningless and unthinkable. In this regard, since the consumption of smuggled cosmetics in West Azerbaijan province has an increasing trend, so in this study, the communicative and social determinants and factors affecting the consumption of smuggled cosmetics in West Azerbaijan province are investigated.Method: The research method is an applied type as regards purpose and has been carried out using a survey method.  The statistical population includes citizens over 15 in West Azerbaijan province, 674 of whom have been selected by multi-stage cluster sampling. Data was collected using a questionnaire and research variables are above 0.7, which indicates the acceptable reliability of the variables. Statistical data analysis was done using SPSS and Lisrel software.Findings: The findings showed that the consumption of smuggled cosmetics and toiletry products is more than average among the respondents and the use of domestic media is less than average and the use of foreign and virtual media is above average. The results of explanatory analyses in the quantitative phase of the research showed  the variables of gender (in favor of women), socio-economic status (in a positive direction), rate of using internal media (in a negative direction), rate of using external media (in a positive direction), The use of virtual media (in a positive direction), health literacy (in a negative direction) and tendency towards differentiation (in a positive direction) have a significant impact on the consumption of smuggled cosmetics and toiletries. It is explained that the impact of foreign and virtual media is greater than other variables.Conclusion: As a result of lack of content management and inaccuracy in advertising in the virtual sector and social media, the possibility of emergence and escalation of social issues and all kinds of deviant trends related to consumerism in the field of cosmetics and toiletry products increases. Also, domestic mass media can be effective in reducing the consumption of cosmetics by not broadcasting commercial advertisements at intervals.