درخت حوزه‌های تخصصی

The purpose of this study is to design a strategic model for international marketing of Iranian handmade carpets - a combined approach. The present study, in terms of its basic applied purpose, in terms of nature, survey research and in terms of paradigm, combined-exploratory research, sampling in the qualitative part of the research was done purposefully and in the quantitative part was done by simple random sampling. In the qualitative stage with 12 experts, who were mainly academic experts in the field of international marketing and senior managers of companies exporting Iranian handmade carpets, the interviews continued until theoretical saturation was achieved, and the sample of the quantitative section consisted of 196 people selected according to the Cochran's formula and the research tool in the qualitative section has been identified using the exploratory method of strategic components of international marketing of Iranian handmade carpets and the factors affecting it and in a small part it was evaluated through descriptive-survey research. The sampling method in the qualitative part was purposeful and in the quantitative part was simple random. The research tool in the qualitative part of exploratory interview was semi-structured and in a small part, for the strategic evaluation of international marketing of Iranian handmade carpets, a researcher-made questionnaire was used, which was designed based on the themes obtained in the qualitative stage. In the qualitative part, the analysis of the interviews was performed using the content analysis method. The validity and reliability of the components were examined and Cronbach's alpha of all the above components was 0.7 and during it; the most important basic, organizing and comprehensive themes on the components of the factors affecting the international marketing strategy of Iranian handmade carpets were assessed. Quantitatively, through structural equation methods, the accuracy of the research model was confirmed and it turned out that the selection of concepts, dimensions and indicators had a high accuracy in the handmade carpet industry and it can provide a suitable framework for compiling a vision document for the handmade carpet industry.

This article discusses a device focused on images that enables users to recognise and detect many face-related features using the webcam. In this article, we are performing comprehensive and systemic studies to check the efficacy of these classic representation learning structures on class-imbalanced outcomes. We also show that deeper discrimination can be learned by creating a deep network that retains inter-cluster differences both and within groups. MobileNet, which provides both offline and real-time precision and speed to provide fast and consistent stable results, is the recently suggested Convolutional Neural network (CNN) model. The recently proposed Convolutional Neural Network (CNN) model is MobileNet, which has both offline and real-time accuracy and speed to provide fast and predictable real-time results. This also solved a problem related to the face that occurs in the identification and recognition of the face. This paper presents the different methods and models used by numerous researchers in literature to solve the issue of faces. They get a better result in using the highest number of layers. It is also noted that the combination of a machine learning approach with multiple image-based dataset increases the efficiency of the classifier to predict knowledge related to face detection and recognition