Immediate monitoring of the patient has always been very important. Achieving this knowledge, which can be integrated to monitor damaged tissue, is very important. In previous methods, the tissue was monitored using a sensor. In this article, not only is a tissue monito More
Immediate monitoring of the patient has always been very important. Achieving this knowledge, which can be integrated to monitor damaged tissue, is very important. In previous methods, the tissue was monitored using a sensor. In this article, not only is a tissue monitored using a sensor, but also the monitoring and evaluation of the effect of other tissues on tumor tissue is evaluated. The smart grid discussed in this article is designed to monitor the condition of a patient with a breast tumor. The structure of the smart grid, given the weight of the communication paths between the nodes and the ability of the nodes, shows us a strong network to assess the patient's condition. As the patient's condition changes, the nodes and weights of the communication pathways change, indicating that there is important information in the network and helping specialists to better assess the condition of the disease. Network monitoring is such that the evaluator node continuously evaluates the tumor node, by changing the status of the tumor node, the status of other nodes and communication paths between them changes, the result of changes in the network by the node The evaluator is evaluated. The simulation results show that this network has the necessary intelligence to assess the patient's condition in adverse conditions.
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In this article, a smart network is proposed to monitor a patient with breast cancer. Increasing the speed of the patient monitoring network depends on our observation, thinking and understanding of the patient. Various factors of the network make us more aware of the d More
In this article, a smart network is proposed to monitor a patient with breast cancer. Increasing the speed of the patient monitoring network depends on our observation, thinking and understanding of the patient. Various factors of the network make us more aware of the disease. has it. The cycle of controlling and monitoring the patient includes observation, orientation, decision and action, this cycle is a set of consecutive actions, which changes with the change of network arrangement, orientation, decision and action. In this article, we design the structure of the smart network according to the weight of the nodes, the communication paths in such a way that the cycle of control and monitoring (analysis, decision and action) performs well. We model the control and monitoring cycle with the proposed method of fuzzy hierarchical analysis process (FAHP). This model adjusts the decision-making criteria by recognizing the identification priorities in such a way that the speed of network detection increases with the least time. It is also a suitable tool for modeling the monitoring cycle and the results of the smart network. The simulation results show that this network has the necessary intelligence to assess the patient's condition in adverse conditions, has the power to continuously analyze and evaluate the patient, and also has the power to make timely decisions in different situations. These results show that according to the network arrangement and fuzzy hierarchical analysis, the speed rate of the network has improved by 10% compared to other networks.
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The purpose of this study was to examine the impact of international entrepreneurship orientation on international performance, considering the role of mediating network capability, competitive strategy and international market orientation. The present study is of a pra More
The purpose of this study was to examine the impact of international entrepreneurship orientation on international performance, considering the role of mediating network capability, competitive strategy and international market orientation. The present study is of a practical nature and because of the fact that it analyzes the status quo, the method used in this research is analytical-survey. The surveyed community is Iran's oil and gas company managers and staff, with 460 employees. According to the limited number of employees, 210 people were randomly selected from Cochran formula and a questionnaire was distributed among these people. For collecting data on theoretical foundations and extracting factors and indicators, library and internet resources including books, articles, and case studies were used. In inferential statistics, the indicators were first determined and extracted according to the dimensions. After checking the validity and reliability of the questionnaire, the data were normalized using Kolmogorov-Smirnov test. Then, using the Structural Equation Modeling Test and Lisrel software, we analyzed the hypotheses. Based on the results, all assumptions were accepted.
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