درخت حوزه‌های تخصصی

The Analytic visualization suggests representing knowledge during a visual type that may be charts, graphs, lists, or maps. The COVID 19 detection and analysis of spreading is very important for countries. Database management with respect to virus deep analysis is a critical task to the researcher through conventional algorithms. The RNA, DNA, and biological data are helping to the bio-inspired algorithm but its implementation can be complex by software tools. Therefore, an effective technique is required to cross over the above limitations. So that covid 19 pandemic data analysis is performed through FCNN (Fully conventional Neural Network) pre-training network. The dataset is collected from social media, Kaggle, and GitHub databases. At 1st stage, the auto stack encoding process is applied later same data is processed with FCNN deep learning classifier. In this research work, covid-pandemic affects parameters like infected persons, deaths, active cases, and recovering cases. The FCNN is take care of feature extraction, training, testing, and classification. Finally using a confusion matrix accuracy of 98.34%, sensitivity 97.63%, Recall 98.26%, and F measure 98.83% had been estimated.

investors and managers are always faced with uncertainty in the information environment, which uncertainty can be due to factors such as the synchronization of stock returns, extraordinary fluctuations in stock returns and the number of equations. The purpose of this study is to investigate the political uncertainty caused by the size of the firm under the influence of risky information environment, the irregular behavior of accruals anomaly and the anomaly behavior of the cost of normal stock equity of companies. For this purpose, the data of 99 companies listed on the Tehran Stock Exchange and Iran TSETMC during the years 2009 to 2019 were examined and tested through combined data. The results showed that the political uncertainty caused by the firm size affected the concurrency stock returns with the optional accrual anomaly behavior and the cost of normal stock equity behavior of companies has a positive and signification relationship. The results also showed that the political uncertainty caused by the firm size is affected by the extraordinary fluctuation of stock returns with the optional accrual anomaly behavior and the cost of normal stock equity behavior of companies has a positive and signification relationship. In addition, the political uncertainty caused by the firm size is affected by the number of equations with the optional accrual anomaly behavior and the cost of normal stock equity behavior of companies has a positive and signification relationship.

مدیران همواره در تلاشند که در راستای اهداف خاصی که دنبال می کنند، مبلغ سود گزارش شده را دستکاری نمایند. مسئله اصلی در رابطه با این مطلب، این است که چرا مدیران به دنبال دستکاری سود هستند، چگونه سود را مدیریت می کنند و پیامد های این گونه رفتار چیست ؟ رفتار نامتقارن هزینه ها باعث می شود که مدیران شرکت ها در مواقع لزوم برای کاهش ضرر و زیان هایشان دست به مدیریت سود بزنند که با این کار از رفتار نامتقارن هزینه جلوگیری می شود . مدیران یک شرکت اغلب مسائلی نظیر برنامه ریزی و کنترل در شرکت های تجاری روبرو هستند. در مرحله برنامه ریزی مدیران به اطلاعات مربوط به گرایش هزینه ها جهت پیش بینی هزینه های آتی نیاز دارند. هدف از انجام این مطالعه بررسی تأثیر توانایی مدیران بر رابطه بین مدیریت سود و چسبندگی هزینه می باشد. بدین منظور اطلاعات مربوط به 137 شرکت پذیرفته شده در بورس تهران در بازه زمانی 1396-1400 جمع آوری گردید. پس از انجام آزمون های آماری و انتخاب روش اثرات ثابت مدل به علت وجود مشکل ناهمسانی واریانس با روش GLS برآورد گردید. نتایج نشان می دهند که مدیریت سود رابطه مثبت و معناداری با چسبندگی هزینه داشته و توانایی مدیریت این ارتباط را تضعیف می کند.

The widespread use of E-commerce websites has drastically increased the need for automatic recommendation systems with machine learning. In recent years, many ML-based recommenders and analysers have been built; however, their scope is limited to using a single filtering technique and processing with clustering-based predictions. This paper aims to provide a systematic year-wise survey and evolution of these existing recommenders and analysers in specific deep learning-based hybrid filtering categories using movie datasets. They are compared to others based on their problem analysis, learning factors, data sets, performance, and limitations. Most contributions are found with collaborative filtering using user or item similarity and deep learning for the IMDB datasets. In this direction, this paper introduces a new and efficient Hybrid Filtering based Recommendation System using Deep Learning (HFRS-DL), which includes multiple layers and stages to provide a better solution for generating recommendations.

INTRODUCTION: Lack of a comprehensive classification of crisis and emergency management in Helal houses has caused many losses in the Red Crescent Society of Iran. Therefore, the root of these problems can be identified and investigated with a thorough investigation. METHODS: This applied research was conducted using a hybrid design. In this research, field and library methods were used. The data were collected by using questionnaire and conducting in-depth interviews with managers, specialists, and experts of the country's crisis management organization and professionals until theoretical saturation. In the first stage, 24 interviews were conducted and we reached theoretical saturation in the 20th interview. In the second stage, relying on inferential statistics methods, 422 questionnaires were distributed. The statistical population of the research is the Red Crescent Society of Iran and its time domain is the second half of 2022. FINDINGS: After performing the three stages of open, central, and selective coding, the final research model was obtained in which, 6 general categories, 15 subcategories, and 49 main concepts are mentioned. CONCLUSION: The results demonstrated that the categories of human resources, organizational communication, and government policies are among the effective factors on crisis management in Helal houses in the Iranian Red Crescent Society in the critical condition of Covid-19 and the consequences of these categories have a significant impact. There are other problems and crises in the formation.

INTRODUCTION: The achievement of organizational goals depends on the ability of employees to perform the assigned tasks and adapt to the changing environment. The implementation of training and improvement of human resources allow people to effectively continue their activities and increase their efficiency in accordance with organizational and environmental changes. The present study aimed to assess the impact of information and communication technology on self-directed learning among Employees at the Red Crescent Society of Tehran. METHODS: This research was applied-descriptive and survey-type. The statistical population of the current research included all 1800 employees at the Red Crescent Society of Tehran. Based on Cochran's formula, 317 subjects were selected by simple random sampling and answered the questionnaires. To check the variables of the research, a 73-item questionnaire was used, which assesses the two variables of information and communication technology and self-directed learning. The validity of the questionnaire was confirmed by experts' opinions, and its reliability was assessed by Cronbach's alpha method. Research hypotheses were tested by structural equation modeling using LISREL software. Confirmatory factor analysis was used to measure the indicators of the questionnaire, and the model of path coefficients and significant coefficients was applied to examine the hypotheses. FINDINGS: The results of the analyses demonstrated that information and communication technology and each dimension of using computers, media (radio and television), the Internet, educational software, and mobile phones had a significant positive effect on self-control, willingness to learn, and self-management among the employees at Red Crescent Society of Tehran. CONCLUSION: In every organization, the management must make sure that the employees recognize the importance of learning since it is a key factor in the success of the organization. It is necessary for the management of every organization to remove mental models and old beliefs and, considering the role of information technology in learning and creating transformations in learning methods, provide the grounds for its application among employees.