Multi-label classification aims at assigning more than one label to each instance. Many real-world multi-label classification tasks are high dimensional, leading to reduced performance of traditional classifiers. Feature selection is a common approach to tackle this issue by choosing prominent features. Multi-label feature selection is an NP-hard approach, and so far, some swarm Intelligence-based strategies and have been proposed to find a near optimal solution within a reasonable time. In this paper, a hybrid Intelligence algorithm based on the binary algorithm of particle swarm optimization and a novel local search strategy has been proposed to select a set of prominent features. To this aim, features are divided into two categories based on the extension rate and the relationship between the output and the local search strategy to increase the convergence speed. The first group features have more similarity to class and less similarity to other features, and the second is redundant and less relevant features. Accordingly, a local operator is added to the particle swarm optimization algorithm to reduce redundant features and keep relevant ones among each solution. The aim of this operator leads to enhance the convergence speed of the proposed algorithm compared to other algorithms presented in this field. Evaluation of the proposed solution and the proposed statistical test shows that the proposed approach improves different classification criteria of multi-label classification and outperforms other methods in most cases. Also in cases where achieving higher accuracy is more important than time, it is more appropriate to use this method.

Researchers have concluded on human abilities during the recent decades that beside two general Intelligence (IQ) and excitement Intelligence (EQ), there is another aspect of Intelligence which is completely limited to human. In fact, it is said that IQ and EQ are not accountable for everything and not really effective. However, human needs a third factor, which is called spiritual Intelligence (SQ). Accepting multi Intelligences and existence of different approaches on this matter, it seems that not only the common fields but also spiritual Intelligence being unique could be explained briefly comparing to other types of Intelligences and its abilities. Spiritual Intelligence could be openly recognized from other Intelligences by some inherent abilities, features such as ability for spiritual state, metaphorical mental process, and create a general viewpoint to life experiences.

Background and Objectives: One of the indicators of mental health is life satisfaction, and the individual's attitude toward life satisfaction is the general assessment of the whole of his life or some aspects of life such as family life and educational experience. The aim of this study was to determine the relationship between emotional Intelligence, successful Intelligence, moral Intelligence, and cultural Intelligence, and life satisfaction with mental health mediation. Materials and Methods: This descriptive-correlational study was a path analysis. The statistical population consisted of all students of Tonekabon Azad University in the academic year 2019-2020 who were selected by non-random sampling method and available to 200 students. Data were collected using a life satisfaction scale, unaffiliated culture Intelligence test, emotional Intelligence test, successful Intelligence questionnaire, moral Intelligence questionnaire, cultural Intelligence questionnaire, and general health questionnaire. Data analysis was performed using SPSS and AMOS software using path analysis method. Results: The mean (SD) age of male students was 27. 7 (6. 9), and female students were 25. 8 (6. 5) years. With increasing emotional Intelligence with an average (SD) of 3. 0 (0. 4), moral Intelligence with an average (SD) (0. 5) 3. 9, successful Intelligence with mean (SD) (0. 5) 6. 6, cultural Intelligence increased with an mean (SD) of 2. 6 (0. 6), life satisfaction with mean (SD) 1. 0 (0. 6) (P<0. 01). With the increase of emotional Intelligence, moral Intelligence, successful Intelligence, and cultural Intelligence, mental health improved with a mean (SD) of 2. 9 (0. 5), where lower scores of mental health meant higher mental health level, (P<0. 01). Also, with increasing mental health, life satisfaction decreased (low scores in mental health mean higher mental health) (P<0. 01). Mental health has a mediating role in the relationship between emotional Intelligence, moral Intelligence, successful Intelligence, and cultural Intelligence with life satisfaction (P<0. 01). Conclusion: The study showed that with increasing emotional Intelligence, moral Intelligence, successful Intelligence, and cultural Intelligence, life satisfaction increased. With increasing emotional Intelligence, moral Intelligence, successful Intelligence, and cultural Intelligence, mental health status improved. Also, life satisfaction decreased with increasing mental health. Mental health played a mediating role in the relationship between emotional Intelligence, moral Intelligence, successful Intelligence, and cultural Intelligence and life satisfaction. Life satisfaction increased with the direct effect of emotional Intelligence, moral Intelligence, successful Intelligence, and cultural Intelligence on mental health.