درخت حوزه‌های تخصصی

Learning effective segment depictions and resemblance measures are fundamental to the recuperation execution of a substance based picture recuperation (CBIR) structure. Regardless of wide research tries for a significant long time, it stays one of the most testing open gives that broadly impedes the achievements of real-world CBIR structures. The key test has been credited to the extraordinary "semantic hole" subject that happens between low-level photo pixels got by technologies and raised close semantic thoughts saw by a human. Among various techniques, AI has been successfully analyzed as a possible course to interface the semantic gap in the whole deal. Impelled by late triumphs of significant learning techniques for PC vision and various applications, in this paper, we try to address an open issue: if significant learning is a longing for spreading over the semantic gap in CBIR and how much updates in CBIR endeavors can be cultivated by exploring the front line significant learning methodology for learning feature depictions and likeness measures. Specifically, we explore a structure of significant learning with application to CBIR assignments with a wide game plan of definite examinations by investigating front line significant learning methodologies for CBIR endeavors under moved settings. From our exploratory examinations, we find some encouraging results and compress some huge bits of information for upcoming research.

This study aims to explain and elaborate a new model for the business environmental hostility in small and medium enterprises in the science and technology park in Kermanshah (Iran). The research method is a mixed method. Content analysis was used in the qualitative part, and a confirmatory factor analysis was used in the quantitative section. In the qualitative section for the environmental hostility dimension of the environmental turbulence, two components of competitive turbulence and regulatory turbulence, as well as seven sub-components were identified and validated. As a consequence, the conceptual model was extracted. This study proposed a conceptual model of business environmental hostility and the researcher-made questionnaire of environmental hostility confirmed with high validity and reliability. The model was verified based on the small and medium-sized enterprises in Kermanshah (Iran), and it is suggested that this new environmental hostility model can be used in practice to improve managing the small and medium-sized enterprises.

The purpose of this study is to provide a model with a dynamic system method to investigate the factors affecting the technological capabilities enhancement in the high-tech industries of high-speed train of the rail transportation system. For this purpose, after reviewing the literature and conducting several meetings with experts in the rail transportation industry, a conceptual and qualitative structure of the subsystems and how they relate in this area were obtained. Then, in order to identify the effective dynamics in upgrading technological capabilities in high-tech industries in high-speed rail transportation, causal loops were drawn and the model was simulated with VENSIM software. Then, using a simulation model, the technology development process was modeled based on the developed structure. Finally, in order to consider the uncertainty space, based on the expert’s opinions, two scenarios of optimism and pessimism were considered. Based on the obtained results, variables such as having a suitable vision for technology development, recognizing basic technological priorities, ability to use and control technology effectively in main and support processes, ability to learn from one technology to another, ability to identify, evaluate, negotiate and finalize the terms of technology acquisition and support facilities, the ability to identify customers, announce auction prices and negotiate terms of sale, the ability to plan, monitor and control research and development projects and having  a proper system for evaluating technological projects,  have  great impact.