Introduction: Academic faculty members need to emphasize ethical principles in order to improve higher education, with the understanding of this importance, the current research was conducted with the aim of designing the ethical model of academic faculty members in Iran's higher education. Material & Methods: This research is a type of qualitative study that uses foundational data theory. The participants, including experts and faculty members of the country's public universities, who were responsible for the promotion of academic members, were selected as key informants through a targeted sampling method of 45 people. Data were collected through semi-structured interviews. The reliability and validity of the data were obtained from the two methods of reviewing the participants and recoding by experts. Data were analyzed by open, central and selective coding. Results: The results showed that the moral model of faculty members in Iran's higher education is explained in 10 main categories and 27 subcategories. Major and core categories in the form of 6 dimensions of causal conditions including (individual factors, organizational factors), core (cultural-educational, educational ethics, research ethics, scientific-executive), background conditions (higher education policies, moral activism), intervening conditions (environmental factors), strategies (micro level-university, macro level-higher education) and consequences (individual and organizational) were elevated to a higher abstract level and finally the research paradigm model was presented. Conclusion: The regulations for the promotion of academic staff members in Iran require a detailed revision of the content with an ethical and qualitative approach in order to make the indicators of the promotion regulations efficient and effective.

Introduction: With writing the special code based on Grid search technique, best method for describing the elements energy spectrum is introduced. This method is suitable for investigation of Atomic, molecular and nuclear Energy spectrum, laser pulses and study of spectrum that obtained by laser interaction with cell and human body.Microraman spectrum of eye lens that fitted by De. Mul and time spectrum of one molecule that excited by 585 nm laser and fitted by Gnu plot software. In a special application, this method is used for 22Na spectrums.Material and Methods: For fitting mathematical function to a set of experimental data, the first step is seeing data plot in every software. Then, an initial mathematical function is guessed and the function parameters change as far as possible for initial fitting. After this step, by using this special code based on Grid search technique, is the X2 changes between function data and experimental data are compared. If the X2 is high, it will reduce by introducing small change in every parameter of mathematical function. This is done step, by step, so the X2 reaches to the lowest.Results: By this method, we can have the formulation of element energy spectrum. For example, the equation of 22Na energy spectrum’s description with least squares fitted by experiment data is: N=199.0477 +76100EXP (0.00167 (E-508.7539) 2) + 75100EXP (0.00168 (E-509.2428) 2) + 3450.8070 EXP (0.0000831(E-655.356) 2) + 4002.813EXP (0.0001431(E-839.401) 2) + 11000EXP (0.00105 (E-1048.0230) 2) Fitting start with fit parameter X2=1107.6 and finished with X2 =44.16.Conclusion: By using the special code based on Grid search technique, we try to introduce the best method for describing of the elements energy spectrum.

The vibration Pattern of a rotor system reflects the mechanical parameter changes in the system. Hence, the use of vibration monitoring is considered as a possible means of detecting the presence and growth of the cracks. In this paper, a Pattern search based method for shaft crack detection is proposed and described which formulates the shaft crack detection as an optimization problem by means of the finite element method and utilizes the Pattern search algorithm to search the solution. Using a direct search method avoids some of the weaknesses of the traditional gradient based analytical search method, including the difficulty in constructing well-defined mathematical models directly from practical inverse problems. First, a finite element code was developed for analyzing a rotor system with open cracks. To extract the flexibility matrix of an element containing cracks an exact integration scheme was adopted which is more accurate than the conventional methods. Then, the crack detection method was formulated as an inverse problem which can be solved by optimization algorithms. The numerical simulations suggest that good predictions of shaft crack location and depth are possible and the proposed method is feasible.

Teenager users apply a limited vocabulary when they proceed to look for their desired materials. Another important issue is that teenagers often click mostly on the first items presented in the list of the search results. This research shows that, in order to amend and compensate these issues, we can extract and suggest a more appropriate query to the teenager user. This can be accomplished by discovering the relevant subject Patterns from the behavior of the teenage user according to his or her previous search quarries and based on the already found Patterns. In the proposed method, the topic Patterns of the user are discovered based on the popularity of the clicks and the most relevant topics from the search logs which are generally massive. Afterwards, by using the binary classification method, the closest query to the query given by the user would be specified. Then, by filtering the subject navigation noise via extraction of the subject Patterns of the teen user’s clicks, a user model with a higher accuracy can be obtained. We evaluated performance of the proposed method using the Alteryx and Weka tools, over the AOL search log, which includes about twenty million sample search transactions from six hundred and fifty different users. The results obtained from the experiments indicate that the queries presented by the proposed system are closer to the target user's query, and consequently, leads to achievement of more related results.

Summary: The aim of this work is to present a model of predictors of job self-efficacy for sports science graduates. 360 people selected as the sample answered the questions of the 3 questionnaires of internal factors, external factors, and job-search self-efficacy. The results obtained show that the internal and external factors affect the job-search self-efficacy. Introduction: Employment challenges and the issue of unemployment are not only one of the most important social issues in the country today but also by considering the rate of population growth in the last two decades, it can be considered as the most important social challenge in the next few decades. The immediate consequences of this crisis are the spread of poverty and the increase in the other social and cultural harms, which naturally endanger the social stability and cohesion. Methodology and Approach: The research method was descriptive-correlational and applied in terms of purpose. The sample consisted of 360 people, who were selected by the simple random sampling. The measurement tool was a three-item 28-item questionnaire of internal factors that included the components of self-esteem Chang et al. (2018), tolerance of ambiguity Hazn et al. (2012), control source Kesavayuth et al. (2018), and self-presentation Hart et al. (2017). Twelve questions in the questionnaire of the external factors of Gnyawali Fogel (1994) consisted of the four components of government policies and procedures, socioeconomic conditions, financial assistance, non-financial assistance, and a questionnaire was on the ten questions of job-search self-efficacy of Salehi (2005). The content validity was confirmed by sixteen professors of the sports management. Also, the values of reliability, divergent, and convergent validity of the questionnaires were estimated. The results obtained were analyzed using the structural equations. Results and Conclusions: The results obtained showed that most of the subjects were women and had a master degree, and most of them were between 26 and 30 years old. Also, the value of the coefficient of determination of the self-efficacy structure was 0. 755, which confirmed the suitability of the structural model. Also, the internal factors with an effect factor of 0. 489 and the external factors with an effect factor of 0. 417 had an effect on the self-efficacy and job search for the sports science graduates. The issue of employment of the university graduates, especially sports graduates, is an important issue that affects many aspects of their lives. Creating employment for people is influenced by many factors, each of which in its own way can be decisive. The achievements of this work for the country's sports authorities includes providing the most important factors of economic and social support and the need to develop policies tailored to the personality traits of individuals in order to employ more graduates of the sports science. Therefore, the main officials and trustees of the country's sports, especially the officials of the Ministry of Sports and Youth, can provide more support for self-employment projects and formulate more financial and supportive laws and regulations taking into account the existing conditions and providing the necessary areas. Low-interest loans and elimination of cumbersome laws can provide the ground for the employment of more and more sports science graduates.

Index tracking is an important issue in portfolio theory. Index tracking is a passive approach in the portfolio optimization problem based on which finite stock should be selected to track the benchmark index. Enhanced index tracking is a selection of the portfolio with limited stock so that its return is maximized and track error is minimized without buying all stock in benchmark portfolio. The main aim of this paper was to propose a two-stage mixed integer model for enhancing portfolio performance. In order to show the approach performance, top 50 companies were traced. Return, tracking error, excess return and information ratio were used as Portfolio performance measurement. Genetic Algorithm and Pattern search Algorithm were also used to solve the models. The findings showed that the two-stage model was better than one stage model. Likewise, Pattern search enjoyed higher performance than Genetic Algorithm in the two-stage model. Therefore, twostage model had higher performance during Pattern search algorithm compared to one stage model or Genetic algorithm.