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The purpose of this paper is to describe imperialist competitive algorithm (ICA), a novel socio-politically inspired optimization strategy for proposing a fuzzy variant of this algorithm. ICA is a meta-heuristic algorithm for dealing with different optimization tasks. The basis of the algorithm is inspired by imperialistic competition. It attempts to present the social policy of imperialisms (referred to empires) to control more countries (referred to colonies) and use their sources. If one empire loses its power, among the others making a competition to take possession of it.

In fuzzy imperialist competitive algorithm (FICA), the colonies have a degree of belonging to their imperialists and the top imperialist, as in fuzzy logic, rather than belonging completely to just one empire therefore the colonies move toward the superior empire and their relevant empires. Simultaneously for balancing the exploration and exploitation abilities of the ICA. The algorithms are used for optimization have shortcoming to deal with accuracy rate and local optimum trap and they need complex tuning procedures. FICA is proposed a way for optimizing convex function with high accuracy and avoiding to trap in local optima rather than using original ICA algorithm by implementing fuzzy logic on it.

Therefore several solution procedures, including ICA, FICA, genetic algorithm, particle swarm optimization, tabu search and simulated annealing optimization algorithm are considered. Finally numerical experiments are carried out to evaluate the effectiveness of models as well as solution procedures. Test results present the suitability of the proposed fuzzy ICA for convex functions with little fluctuations.

The proposed evolutionary algorithm, FICA, can be used in diverse areas of optimization problems where convex functions properties are appeared including, industrial planning, resource allocation, scheduling, decision making, pattern recognition and machine learning (optimization techniques; fuzzy logic; convex functions).

A sentinel event is an unexpected occurrence resulting in death or serious physical or psychological injury or the risk thereof. The purpose of this paper is to investigate the influencing factors of sentinel events in the emergency department of a military hospital in Tehran to find out some of the effective solutions.

In this qualitative study with content analysis approach, 20 hospital healthcare personnel participated as participants from the fields of medicine and nursing. Purposive random sampling and semi-structured interviews were used for data collection. Atlas.ti software version 5.2 was used for data analysis.

Four themes and 32 subthemes were identified by numerous revisions and combining the codes. The four main themes of sentinel events were: causes, incidence barriers, cause prevention solutions, and barriers’ improvement solutions. Moreover, these main factors were related to these issues: staff and patients’ education, communication, assessment, patients and their companions, employee rights, leadership, care continuum, human factors, physical environment, information management and medication use. Some solutions were also suggested according to these factors and a policy was recommended.

Hospital managers and authorities should try to find the main causes of sentinel events by periodical analysis to find ways to prevent them in the future, using logical and reasonable solutions.

This study confirms that strategies to reduce the sentinel events in emergency departments should focus on empowerment of all staff.

The purpose of this study is to investigate the status of perceived need, seeking behavior and utilization of health services in the elderly population of Sanandaj (west of Iran).

This is a cross-sectional study conducted on 800 elderly people in Sanandaj. Subjects were selected using multistage sampling and data were collected using self-report questionnaires. A multivariate logistic model with odds ratios (ORs) was used to determine the relationship of independent variables with seeking perceived need. Also, the concentration index was used to measure the inequality in using health services.

The perceived need for outpatient (during the last 30 days) and inpatient health-care services (during the past 12 months) was 69.7% and 29.7%, respectively. Among them, the unmet need for outpatient and inpatient health-care services was 46.6% and 17%, respectively. Having health insurance (adjusted OR 12.08; 95% confidence interval [CI] 1.04–140.11), middle economic status (adjusted OR 5.18; 95% CI 1.30–20.51) and being in an age group of 65–70 years (adjusted OR 7.60; CI 1.42–40.61) increased the chance of seeking inpatient care. Also, being in an age group of 60–65 years (adjusted OR 0.41; 95% CI 0.18–0.95) reduced the chance of seeking outpatient care. There was also a pro-rich inequality in using outpatient health services.

The elderly population suffers from unmet health-care needs, especially in outpatient services. The most important reason for not seeking outpatient and inpatient services was financial barriers and self-medication, respectively. So, designing targeted policies and interventions to address barriers in the conversion of need to demand in the elderly population is essential.

Mental health is one of the most important factors for evaluating the health of different age groups in the community. The most common forms of mental health disorders are depression and anxiety. Health status of students as an important age group has positive consequences in the community. To provide special recommendations for preventing mental disorders, the purpose of this paper is to determine the correlations among the individualism and family orientation and mental health.

A meta-analysis was conducted to find scores of mental health. International databases of Scopus and PubMed as well as Iranian databases of IranMedex and SID were systematically searched in September 2014 for studies conducted on Iranian students. Of 379 reviewed studies, 58 were selected for meta-analysis. A meta-regression model was estimated to show the effects of individualism and family orientation on mental health.

Eight studies were conducted in Tehran. Eight studies were published in English. In nine studies, school students, and in one study both school and university students were surveyed. General Health Questionnaire-28 score varied from 13.77 in Arak to 47.78 in Tehran. The results of this study showed that the pooled mental health score for Iranian students was 23.725, indicating that Iranian students had poor mental health. In meta-regression, the coefficient of family orientation was −0.2893 and it was significant. Other variables did not have any significant relationship with mental health scores.

Improvement of living conditions and enabling the youth to positively communicate with different social groups are recommended.

The purpose of this paper is to introduce an evaluation methodology for employee profiles that will provide feedback to the training decision makers. Employee profiles play a crucial role in the evaluation process to improve the training process performance. This paper focuses on the clustering of the employees based on their profiles into specific categories that represent the employees’ characteristics. The employees are classified into following categories: necessary training, required training, and no training. The work may answer the question of how to spend the budget of training for the employees. This investigation presents the use of fuzzy optimization and clustering hybrid model (data mining approaches) as a fuzzy imperialistic competitive algorithm (FICA) and k-means to find the employees’ categories and predict their training requirements.

Prior research that served as an impetus for this paper is discussed. The approach is to apply evolutionary algorithms and clustering hybrid model to improve the training decision system directions.

This paper focuses on how to find a good model for the evaluation of employee profiles. The paper introduces the use of artificial intelligence methods (fuzzy optimization (FICA) and clustering techniques (K-means)) in management. The suggestion and the recommendations were constructed based on the clustering results that represent the employee profiles and reflect their requirements during the training courses. Finally, the paper proved the ability of fuzzy optimization technique and clustering hybrid model in predicting the employee’s training requirements.

This paper evaluates employee profiles based on new directions and expands the implication of clustering view in solving organizational challenges (in TCT for the first time).

The purpose of this study was to assess the self-perceived need, seeking and use of dental care and its main determinants in Kurdistan province, Iran.

A total of 1,056 adults in Kurdistan province were included in this cross-sectional study. Multistage sampling approach was used to select the samples. Data on sociodemographic characteristics, economic status, self-perceived need, seeking and use of dental care were collected using a self-administrated questionnaire. Multivariate logistic regression model was used to assess factors affecting the use of dental care. In addition, socioeconomic inequality relating to dental care needs and use of dental care were examined using concentration curve and concentration index.

In this study, unmet dental care need was 62.7%. There was a perceived need for dental care among 13.7% (n = 145) of the participants in the past month, with only 39.3% (n = 57) seeking the care. The most important reasons for unmet dental care need were “Could not afford the cost” and “Insurance did not cover the costs.” Multivariate logistic regression showed that supplementary insurance status and household economic status were identified as main determinants affecting dental care-seeking behavior. The result of concentration index revealed that seeking dental care was more concentrated among the rich, whereas the perceived dental care need is more prevalent among the poor.

This study demonstrated that the prevalence of unmet dental care needs is high in the study setting. Also, financial barrier was identified as the main determinant of unmet dental care needs.