Background: In spite of many advantages in Lenke classification of adolescent idiopathic scoliosis, the latest study of Richards et al showed that the King classification is better than had been reported recently and the Lenke classification system of adolescent idiopathic scoliosis is less reliable than previously reported.Methods: In this study, we performed a multi-surgeon comparison of these two classification systems. After teaching and discussing all available data of these classification systems with four spine surgeons, a pilot classification was performed. Then, they independently evaluated preoperative radiographs (standing posteroanterior, lateral, and two supine side-bending views) of 99 patients with adolescent idiopathic scoliosis. The results were determined by calculating the average percentage of intraobserver and interobserver agreement. Reliability was quantified using kappa statistics.Findings: The King classification demonstrated good intraobserver and interobserver Reliability, with an intraobserver agreement of 85.8% (kappa coefficient, 0.80). Interobserver percentage of agreement averaged 80.8% (kappa coefficient, 0.74). The complete Lenke classification, combining curve type, lumbar modifier, and sagittal thoracic modifier, demonstrated good Reliability for both intraobserver and interobserver measurements. The intraobserver percentage of agreement averaged 85.8% (kappa coefficient, 0.82). The interobserver percentage of agreement averaged 80.8% (kappa coefficient, 0.77).Conclusion: In this study, with each investigator performing the radiographic measurements, the King and Lenke classifications were almost similar (the Lenke classification had slightly better results). Such better results might be due to more training of this complex classification system. So, because of greater coverage of idiopathic scoliosis curve and usefulness of Lenke classification system, we prefer using this classification system in our center.

The Big Five Inventory (BFI) is one of the most widely used personality questionnaires, but very few studies have been conducted on its psychometric properties in Iranian population. This study was carried out with the aim of studying the psychometric properties of the BFI questionnaire. For this purpose, 390 university students in Tehran (210 girls and 180 boys) with an age range of 18 to 56 years (M = 27.52; SD = 8.79) were selected using the convenience sampling method and completed BFI and NEO-FFI questionnaires. Cronbach's alpha, multitrait-multimethod matrix, and confirmatory factor analysis were used to estimate the psychometric properties of the questionnaire. The result of the confirmatory factor analysis showed that 15 of the 44 items did not have a strong factor loading (higher than 0.40) on the corresponding factors and were therefore removed from the questionnaire. The fit indices showed that the Persian version of 29 questions (BFI-29) with 5 factors has a good fit with the data. The Reliability analysis also showed that the range of Cronbach's alpha coefficients of the factors is from 0.70 to 0.79. The lowest Cronbach's alpha coefficient was related to agreeableness factor and the highest was related to conscientiousness. The findings from the multitrait-multimethod matrix showed that the BFI-29 questionnaire has good convergent and divergent validity with the NEO-FFI questionnaire. In general, based on the results of the present study, it can be said that the BFI-29 questionnaire has desirable psychometric properties and whenever a short tool for personality measurement is needed, this questionnaire can be used.

In the process of designing a product or a physical system, Reliability engineering is an important factor to be considered. Also, as an essential step in Reliability evaluation during the design phase, it is necessary to allocate Reliability to subsystems, in such a way that full system Reliability is satisfied. Performing this process, which is called Reliability allocation, creates a more reliable and competitive system, which, at the same time, is compatible with our limitations. The consequences of considering this phase in designing a product are improved design and manufacturing methods, and, as a result, it is possible to gain cheap and reliable products compatible with customer demand. Many parameters that exist in the process of Reliability allocation have been generated based on research investigations. These techniques have different attitudes towards performing an allocation process. By analyzing these approaches, the researchers discovered remarkable disorders. These disorders are consequences of weaknesses, some of which all techniques share. One important aspect not considered in these techniques, and considered to be a great weakness, is the importance of subsystems, regarding their place in system configuration and their contribution to full system Reliability. In this study, according to the importance and e effectiveness of Reliability importance measures, we have utilized them as an approach to suggest a new and effective technique. In this process, we use the technique of Reliability importance measures to propose a new way to overcome this weakness, and, in two examples, will show the effects of using these measures in the process of Reliability allocation. Based on a comparison between the new technique and the two most applicable techniques in literature; ARINC and MAXIMAL ENTROPY, using one hypothetical and one real example, we have shown the preferable results of the new technique.

This article presents an efficient Reliability-based optimization method for critical structural design, in which, the probability of failure (Pf) should remain in a small bound. Critical structures should be designed to be optimal and reliable. Despite significant progress in Reliability and optimization techniques, their interaction, which is considered in Reliability-based optimization (RBDO), is faced with several challenges, especially in Reliability analysis of critical constraints (constraints with Pf less than 10-5). To address this issue, in this paper the cross-entropy method is intended for Reliability analysis and is combined with Genetic Algorithm in a double-loop framework to implement RBDO. The cross-entropy method is based on Monte Carlo simulation, except that the variance of sampling is reduced, which leads to a faster and more accurate Reliability analysis method. The proposed RBDO method is demonstrated on two structural design. The obtained results show a high capability in Reliability-based optimization of critical structures. In addition, using the proposed method, in comparison with traditional safety factor method, provides a more substantial manner in Reliability improvement.

Modern systems have four basic components: hardware, software, organizational, and human. With the development of new technologies and systems, the hardware and software Reliability has increased dramatically during the past decades, while in many cases the human Reliability has remained either unchanged or even deteriorated over the same period as the result of complexity of systems. Human interactions are an important factor during the design, installation, production and operation, and maintenance phases of a product or system. The capacity of human beings to make mistakes and errors has been recognized since the beginning of recorded history. The new view on human error is that you can see the human error as the symptom of deeper trouble, in this case, human error is not a cause of failure. Human error is the effect, or symptom, of deeper trouble inside a system. It is not fair, logical and professionally ethical and sound for experts in the field of human factors and safety to say that human is recognized as the cause of as the matter of fact it is the failure of design and operation team and those who were unable to predict and mitigate source of human failure. This paper review was examined and summarized the history, significance, concepts, contributing factors, and all invented analytical methods and procedures in a systematic human Reliability assessment (HRA). Furthermore, available human Reliability data banks were introduced and elaborated. The challenges and issues in the field of human Reliability field were later highlighted and emphasized. Lastly, the expected directions for future works by researchers and practitioners were suggested.