A word is the smallest unit in a language that has ‘ form’ and ‘ meaning’ . The word might have more than one meaning in which its exact meaning is determined according to the context it is appeared. Collecting all words’ senses manually is a tedious and time consuming task. Moreover, it is possible that the words’ meanings change over time such that the meaning of an existing word will become unusable or a new meaning will be added to the word. Computational methods is one of the approaches used for identifying words’ senses with respect to the linguistic contexts. In this paper, we put an effort to propose an algorithm to identify senses of Persian words automatically without a human supervision. To reach this goal, we utilize the word embedding method in a vector space model. To build words’ vectors, we use an algorithm based on the neural network approach to gather the context information of the words in the vectors. In the proposed model of this research, the divisive clustering algorithm as one of hierarchical clustering algorithms fits with the requirements of our research question. In the proposed model, two modes, namely the Sentence-based and the Context-based, are introduced to identify words’ senses. In the Sentence-based mode, all of the words in a sentence that contain the target word are involved to build the sentence vector; while in the Context-based mode, only a limited number of surrounding words of the target word is involved to build the sentence vector. Two evaluation metrics, namely internal and external, are required to evaluate the performance of the clustering algorithm. The silhouette score for each cluster is computed as the internal evaluation metric for both modes of the proposed model. The external evaluation requires a gold standard data for which a data set containing 20 ambiguous words and 100 sentences for each target word is developed. According to the obtained results of the internal evaluation, the Sentence-based mode has higher density of clusters than the Contextbased mode, and the difference between them is statistically significant. According to the V-and F-measure evaluation metrics in the external evaluation, the Contextbased mode has obtained higher performance against the baselines with statistically significant difference.

Introduction: Complex sociotechnical systems, such as automotive industry, require a proper macroergonomic approach to design and implement the work system at micro-ergonomic level. The purpose of this study was to develop and validate effective macroeconomic factors to improve productivity, health and safety of employees in the automotive industry based on Holden & Karsh model. Material and Methods: At the first step, relevant documents were reviewed, and then experts were interviewed to identify macro-ergonomic factors. The identified factors were categorized into four groups based on Holden & Karsh’, s model. In the follow-up phase of the study, then, the content validity of the factors was calculated using Delphi technique in the form of an expert panel. Finally, validity acceptance was assessed using mean content validity index, and agreement between experts was evaluated using modified kappa coefficient Results: 28 main factors were identified and categorized into four subgroups, including personnel, unit / department, organization and environment factors. 19 main factors were selected as the effective macroergonomic factors to improve employee’, s productivity, health, and safety. The content validity index and the modified kappa coefficient were calculated as 0. 901 and 0. 90, respectively. Conclusion: Macro-ergonomic factors identified in this study can be considered to improve employee’, s productivity, health, and safety in the automotive industry. These factors can be used as specific contextbased criteria for an ergonomic evaluation in the automotive industry, or even be generalized to other industries, organizations and companies.

The aim of this research is to investigate the components of context based on mathematics approach in secondary school curricula. For this pupose content analysis was used as the appraoch. The corpus of this research was the 10th grade mathematics textbook in Iran academic year of 2016-17. The tool in this research was content analysis form with regard to Context-based mathematics approach. The data obtained from content analysis forms were quantitatively characterized (frequency tables and percentages) and analyzed. The Shannon entropy analysis method was also used to determine the effects of the four components of the contextbased approach, including being practical, realistic, relevant to the student's daily life experiences and openness in designing the textbooks and the teaching guideline of the 10th grade mathematics textbook of the humanitarian major. Then, these issues were addressed at a deeper level with an emphasis on the four components of qualitative content analysis. The validity of the research tool was approved by five faculty members of major universities in curriculum and mathematical education. William Scott's method was utilized to ensure the reliability of the content analysis form. The findings indicated that the degree of attention and involvement parameters and the coefficient degree of importance for the Context-based mathematics approach of each component were very low, and hence the contents of 10th grade mathematics textbook were not adapted to the Context-based mathematics approach principles.

Introduction: Nurses' social responsibility has an effective role in improving the quality of services and achieving the desired goals of the health system. Given that social responsibility is contextbased. The aim of this study was to determine the relationship between nurses' social responsibility and organizational culture in teaching hospitals of Kurdistan University of Medical Sciences. Methods: This study was a descriptive-analytical study. The statistical population included all nurses working in three teaching hospitals affiliated to the Kurdistan University of Medical Sciences, including Kowsar, Beasat, and Tohid in Sanandaj in 2020. Using Cochran's formula, 317 people were determined as the sample size. And were selected by stratified random sampling method. The instruments used for data collection were four questionnaires of demographic and social responsibility Carroll (1991) and Robbin's organizational culture (1998). SPSS 23 software and Pearson and Manova correlation tests were used to analyze the data. Results: The average social responsibility of the studied nurses was 131. 72 and the average organizational culture of the studied hospitals was 105. 17, so the status of social responsibility of nurses and organizational culture was moderate to high. there was a direct and significant relationship between the social responsibility of nurses and its components (legal, economic, legal, economic, ethical, altruistic) with the organizational culture of hospitals and their components (control, individual creativity, organizational communication, reward system, clarity of goals, manager support, risk-taking, organizational cohesion, organizational identity, and conflict resolution (p = 0. 05). The highest correlation is between organizational cohesion and moral responsibility (r = 0. 817) and the lowest correlation is between conflict and legal responsibility (r = 0. 224). Conclusions: Providing the ground for changing the organizational culture to the desired situation can play a significant role in increasing and improving the social responsibility of nurses in teaching hospitals affiliated to the University of Medical Sciences. Which can pave the way for quality and increase productivity in teaching hospitals.

Background and Aim: Pre-hospital care is a multidimensional concept with multiple definitions, but the first aid and transportation concept remains unclear. The aim of this study was to clarify the first aid and transportation concept in pre-hospital combat medical care. Methods: The Walker-Avant approach was used for the analysis of the concept of first aid and transportation. This approach is one of the methods of conceptualization and concept development that ultimately leads to the development of the theory. Databases of PubMed, Web of Sciences, Ovid, Iran Medex, Magiran, SID were searched using keywords of "First aid and transportation", and "pre-hospital care". Totally 728 articles were found to be published between 2010-2020 in Persian or English. Eighty-eight articles were found to be suitable after initial screening. Irrelevance or without full text articles were excluded. Finally, 9 articles were analyzed based on Walker and Event analysis steps, and the definition, applications, features, premise, implications and experimental referrals were extracted for the concept of first aid and transportation in pre-hospital care. Results: Concept analysis showed that the concept of first aid and transportation is synonym with concepts such as helping, immediate care, and life preservation. This concept has a complex process characterized by the concepts of rapid response, life-saving, commitment, expertise, responsibility, and is in contrast with the terms of irresponsibility and time-consuming. This concept is related to the concepts of border rescue, pre-hospital care, self-aid and buddy-aid in combat medicine. Conclusion: Identifying and analyzing the first aid and transportation concept is a most used strategy for increasing the knowledge to make changes in combat medicine and crisis management. It is completely contextbased and is influenced by climatic conditions, culture, literacy level, public education, public health, communications and guidelines. It is also related to the provision of pre-hospital care services provided by medical staff, especially nurses in terms of quantity and quality. Skillful resuscitation leads to more life-saving. Responsibility and commitment give credit to first aid and transportation.