This study explores the motivational components within teacher rating systems and their impact on professional growth motivation. Employing a systematic review approach, it investigates texts pertaining to teacher rating systems, motivation, and professional development literature. By examining various texts and research findings on teacher motivation, factors influencing teacher ratings based on general, specialized, and professional competencies, as well as experience, are identified. Drawing parallels with Herzberg's motivational theory, this study provides recommendations to bolster teacher motivation and job satisfaction through improvements in the rating system.

K-nearest neighbors (KNN) based recommender systems (KRS) are among the most successful recent available recommender systems. These methods involve in predicting the rating of an item based on the mean of ratings given to similar items, with the similarity defined by considering the mean rating given to each item as its feature. This paper presents a KRS developed by combining the following approaches: (a) Using the mean and variance of item ratings as item features to find similar items in an item-wise KRS (IKRS), (b) Using the mean and variance of user ratings as user features to find similar users with a user-wise KRS (UKRS), (c) Using the weighted mean to integrate the ratings of neighboring users/items, (d) Using ensemble learning. Three proposed methods EVMBR, EWVMBR and EWVMBR-G are presented in this paper. All three methods are user-based, in which VM distance is used as a measure of the difference between users / items, to find neighboring users / items, and then the weighted average is weighted, respectively. Also, weights based on the Gaussian combined covariance model are used to predict unknown user ratings. Our empirical evaluations show that the proposed method EVMBR, EWVMBR and EWVMBR-G, which utilizes ensemble learning, are the most accurate among the methods evaluated. Depending on the dataset, the proposed method EWVMBR-G managed to achieve 20 to 30 percent lower mean absolute error than the original MBR. In terms of runtime, the proposed methods are comparable to the MBR and much faster than the slope-one method and the cosine-or Pearson-based KNN recommenders.

While Kids and adolescents are the largest and most permanent TV audiences, a significant portion of TV programs is made for adults and is not commensurate with their understanding and biological experience. So it may harm their mental, emotional, moral and physical growth. Most countries have developed a system of rating programs to protect children against inappropriate or harmful subjects. The research was conducted with the aim of understanding the theoretical foundations and similarities of this system in Islamic countries comparing of European and American countries including America, France, Malaysia and Turkey. This research was conducted by documentary method (including study of laws, regulations, systems and processes of legislation, implementation, monitoring and control). The findings show that these systems are defined in all countries using the age classification based on a semiotic system consist of letters, numbers positive and negative symptoms. This is done with regard to law and under the Media Regulatory Authority (an independent legal entity with legislative, executive, and judicial functions) and implemented within the framework of the codified guidelines. The main distinctions between them are permitted sexual relationships or references, delinquency, and abnormal in terms of Prohibitions and limitations of content, how to define and categorize content subject to rating by age, based on the normative system of society including Inappropriate speeches, nudity, adult topics and relationships.

Introduction: Social Skills rating system (SSRS) is an important instrument for assessments in children. The purpose of this study was to standardize the SSRS for preschool children in Shiraz. Method: After the scale was translated and adapted into Persian, 700 boys and girls 3 to 6.5 years of age were rated by parents and teachers using the SSRS forms for preschool children. The scores were converted into standardized scores with a mean of 100 and standard deviation of 15 points. Tables were prepared for conversion of raw scores to standard scores. Validity of the scale was tested using different measures. Construct validity was confirmed by factor analysis. Data were analyzed by t-test, ANOVA and correlation coefficient. Results: No significant difference was found based on age and parents' education, i.e. the scaled was not biased towards any age or socioeconomic groups. Reliability of the scales was satisfactory using different methods. Factor analysis also proved its validity. The difference between mean scores of boys and girls in social skills and behavior problems was not significant. Conclusion: The standardized scores of this scale provide a comparison of social skills among different age groups of preschool children.

Taxes, are healthiest source of funds for infrastructure investments and an important stimulus for economic growth and development. Revenues of local government’s substantially relate to the power and efficiency of the tax system Since the tax value of tax system over time, spontaneously changes in the passage of time, tax reforms and regime changes are always necessary. Using of fuzzy sets in decision problems is one of the most important applications of this theory in comparison to classical set theory. The reason is that decision making problems considerably relate to human mind and knowledge. Therefore, in this paper, the fuzzy logic is used for ranking the tax systems. The findings indicate that VAT systemic substantially more favorable than import tax, Property taxes, Income Taxes sale and consumption taxes further, the import tax , Income tax, Taxes on consumption and sale And property taxes are respectively in the next levels.

Objectives: The effectiveness of any change in the education system requires acceptance of the program, the ability to implement it by the implementing agents, the provision of the necessary platforms for dealing with obstacles in the way, and evaluation and ranking to achieve the goals of the organizational program. In addition to these issues, none of the ranking systems can be considered completely flawless, because it is very difficult to achieve a comprehensive and efficient system that takes into account all aspects and missions of education. Therefore, Ranking systems are always faced with serious challenges, the identification of which, from the perspective of their audiences, has a significant impact on providing appropriate strategies. Therefore, the present study was conducted to diagnose the pathology of the teacher rating system.lMaterials and Methods: The current research is based on the paradigm of interpretivism, and in terms of method, it is qualitative and Phenomenography. The statistical population of the present study was the staff, managers, assistants, teachers, and all the people involved in the professional rating of teachers in South Khorasan. Sampling was done using theoretical (non-probability) and purposeful sampling methods. Based on this, 16 people were interviewed. In order to collect data, in-depth and exploratory interviews were used. The obtained data were analyzed using the Collaizi method. In order to validate the research findings of long-term conflict or drowning, confirmation by the subjects and questioning and searching of colleagues, and also to ensure the reliability of the coding methods by the second coder and decoding by the researcher, were used. seDiscussion and Conclusion: Based on the analysis of the findings of the research, the damage of the teacher rating system in 5 secondary categories, including trans-organizational problems and social dissatisfaction (4 categories), weak strategic and development-oriented attitude (3 categories), executive and structural challenges of the teacher rating system (10 categories), basic challenges of the rating system (7 categories) and teacher rating results (7 categories).) were identified. The results of this research show that the low share of education in the country's budget, teachers' livelihood problems, the decline in the status of teachers, interviews with officials, and the psychological climate against educators, a purely economic view of rankings, failure to view rankings as a factor in teacher development and failure to accept the rank earned by teachers, failure to communicate items at the beginning of service, poor proportionality, uniformity, and ambiguity in performance ranking indicators and criteria, sectional implementation of teacher rankings, weakness of the evaluator training program, inappropriate allocation of evaluators, poor training and awareness of teachers regarding the rating process and systems, failure to implement ratings for administrative staff, inappropriate evaluation mechanisms and tools, poor ability to accurately verify uploaded documents, and poor facilities and resources for rating, erosion of the rating process, poor adherence to professional ethics in the teacher rating process, evaluation errors, lack of a system for monitoring and evaluating the ranking process, failure to provide appropriate feedback to teachers and issues related to technology infrastructure and an inefficient teacher performance evaluation system, failure to achieve teacher ranking goals, waste of resources in education, teachers' certification orientation, pushing teachers towards certification orientation, certification fabrication and falsification, weakening the education and training administrative staff, feelings of inequality and organizational injustice, decreased job satisfaction and commitment, and the degradation of teachers' status and position in society are among the harms of the teacher ranking system. Finally, based on the research findings, some suggestions can be made to improve the teacher ranking scheme: precisely specifying job standards and communicating them to teachers, and developing ranking indicators and criteria based on job standards; modifying and improving teacher ranking indicators and criteria and determining appropriate and comprehensive indicators and criteria; training professional evaluators in line with the evaluation process and reforming the method of assigning evaluators; combining teacher rating systems with teacher professional development system; improving technological infrastructure and providing appropriate training to teachers; changing evaluation mechanisms and using new evaluation methods such as evaluation and development centers.

The ever-changing economic turns the decision-making on financing a project into a crucial for banks. There are many cases in developing countries in which projects failed either by completing far later than their dues or by not meeting their minimum economic and managerial requirements.There are many techniques for project evaluation, but it is obvious that the criteria being used depend upon the specific conditions like economic, infrastructure, technical ability, government policy, etc. In this research, a decision-making model for project evaluation is developed using expert systems and AHP technique. AHP technique is used to determine the weights of each criterion these results of evaluation by use of AHP and some other managerial criteria like honesty of the manager and previous history forms the knowledge base for evaluation. VP-Expert shell is used to model the expert system for evaluation. The model is tested in 10 cases and the results confirmed the validating of the developed model.

Nowadays, credit risk is recognized as one of the most important bankruptcy factors of banks and financial institutions. In order to manage and control this risk, design of credit rating models is undeniable necessity. Credit rating is used to identify the probability of credit default and on the other side classify the customers into two groups: good and bad accounts.  Until now, various statistical methods, including discriminant analysis, logistic regression and neural networks have been developed for credit rating. Meanwhile, neural networks due to the high flexibility and precision, in recent years have been considered more. This study presents a credit rating model using adaptive neuro-fuzzy inference system to predict financial performance of bank customers. In this model, debt ratio, operational ratio, and return on equity have been selected as input variables, and on the other side the probability of default has been considered as output variable. After training and testing the model based on data from Keshavarzi bank over 2001-2006, the model predicts the credit status of customers with Accuracy of 69.36%.