LTD型パルスパワー発生器の特性評価とこれを用いた大気圧放電研究

国立大学法人長岡技術科学大

Identifying the Factors Affecting Entrepreneurial Attitude of Athlete & Non-athlete University Students

Considering entrepreneurship as a state of mind, we have to admit that nowadays, apart from business and economy, any person can think and act in an entrepreneurial manner. Hence, not only the “entrepreneurship enhancing†policies should not be confined to higher education levels, but also they have to be included in elementary and non-athlete programs. In this study, the level of entrepreneurial attitude, and the effect of some demographic variables on it were investigated among a group of 406 university students in Tehran. The main tool used in this study was the translated Athyde’s ATE questionnaire (attitude towards entrepreneurial business initialization) which was tested for reliability by a pretest and computation of Cronbach’s Alpha coefficient for the main study and all its components. The results showed that the level of entrepreneurial attitude was above average among athlete students, in all of the investigated aspects and components. They also showed that variables such as gender, having a self-employed father, employment status of mother, and the type of university (athlete &non-athlete) have no significant impact on the level of entrepreneurial attitude in students

Identifying Effective Factors on Technological Entrepreneurship in Iranian Nanotechnology SMEs

Technological entrepreneurship is the latest issue in the field of entrepreneurship and fostering competitive advantages in Small and Medium Enterprises (SMEs) which has been received special attention. Given the lack of coherent literature review to apply technological strategies in SMEs, and also because of the role of technology based firms which are active in industries with new technologies, such as Nano-Technology industry, while the technological entrepreneurship literature review has been investigated, this article is principally intended to identify effective factors on technological entrepreneurship in Iranian Nanotechnology SMEs. The research methodology of the current article is a mixed one; in the qualitative stage, semi-structured and open interviews and investigation of related documents have been used, and in the quantitative stage, the questionnaire has been applied to gather data. In the research’s quantitative stage, a statistical population consisted of managers, expert employees of the case study have been considered, and the simple random sampling method has been used. In addition, in this stage, the questionnaires have been used as the data collection tool and the experts in the qualitative stage measured the research’s validity, and the questionnaire’s reliability has been approved through Cronbach’s alpha of 0.81. The mean analysis has been applied in this stage for the data analysis. The findings of this paper shows that the effective factors on technological entrepreneurship in Iranian Nanotechnology SMEs are categorizes in the four issues of “Internal Processesâ€, “Individual Factorsâ€, “Institutions†and “External Networksâ€

Weighted Cumulative Past Extropy and Its Inference

This paper introduces and studies a new generalization of cumulative past extropy called weighted cumulative past extropy (WCPJ) for continuous random variables. We explore the following: if the WCPJs of the last order statistic are equal for two distributions, then these two distributions will be equal. We examine some properties of the WCPJ, and a number of inequalities involving bounds for WCPJ are obtained. Studies related to reliability theory are discussed. Finally, the empirical version of the WCPJ is considered, and a test statistic is proposed. The critical cutoff points of the test statistic are computed numerically. Then, the power of this test is compared to a number of alternative approaches. In some situations, its power is superior to the rest, and in some other settings, it is somewhat weaker than the others. The simulation study shows that the use of this test statistic can be satisfactory with due attention to its simple form and the rich information content behind it

Obesity paradox versus frailty syndrome in first-ever ischemic stroke survivors

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A comparison of artificial intelligence algorithms in diagnosing and predicting gastric cancer: a review study

Today, artificial intelligence is considered a powerful tool that can help physicians identify and diagnose and predict diseases. Gastric cancer has been the fourth most common malignancy and the second leading cause of cancer mortality in the world. Thus, timely diagnosis of this type of cancer could effectively control it. This paper compares AI (artificial intelligence) algorithms in diagnosing and predicting gastric cancer based on types of AI algorithms, sample size, accuracy, sensitivity, and specificity.  This narrative-review paper aims to explore AI algorithms in diagnosing and predicting gastric cancer. To achieve this goal, we reviewed English articles published between 2011 and 2021 in PubMed and Science direct databases. According to the reviews conducted on the published papers, the endoscopic method has been the most used method to collect and incorporate samples into designed models. Also, the SVM (support vector machine), convolutional neural network (CNN), and deep-type CNN have been used the most; therefore, we propose the usage of these algorithms in medical subjects, especially in gastric cancer