This study investigates improving the process of Design and interaction analysis of Gama-ray imaging systems. Gama-ray imaging systems have many applications in medical sciences, military and security or-ganizations and for each application area, different parameters have gained attention in the product Design process. The complexity of the product Design process and variety of Design parameters confirm the need for development of a comprehensive map for product Design which demonstrates subsystem interactions and the way that each parameters effects other parameters. Hence the Design Structure Matrix (DSM) is used to display and analyze the interaction of Design influencing parameters. DSM offers network modeling tools that represent the elements of a system and their interactions, thereby highlighting the system's Designed Structure. Its advantages include compact format, visual nature, intuitive representation, powerful analytical capacity, and flexibility. In this research we have proposed a DSM which consists of 49 parameters for the mentioned product and then this Matrix has been analyzed and clustered by using the related software. As a result, the parameters have been divided into five Design cycles after prioritization. The system Designer can identify the parameters' effect and trace the systematic Design process by using this Matrix.

Axiomatic Design is one of the Design approaches. This approach is established on two axioms: Independence and information axioms. In this approach Design Matrix is a key concept. It is categorized to three types Matrix with name uncoupled, decoupled and coupled Design Matrix. The uncoupled Design Matrix satisfies independence axiom. In this paper a new problem is presented in axiomatic Design that is named Design Matrix Reconstruction. The recostructability of Design relation Matrix is investigated in this paper. Design relation Matrix is used for presenting the relation between functional requirements and Design parameters. For Design relation Matrix reconstruction, existence of some projections from unknown Design Matrix is supposed and on this basis some proofs are presented. These proofs show Design relation Matrix is reconstructible when the projections are consistence together. The Design Matrix reconstruction is applicable for reverse engineering, Design evaluation and Design improvement.

Nowadays, the fundamental role of having a purpose for life in physical and mental health has been confirmed. According to victor frankl, presence of a purpose in life gives life a meaning and increases resilience against pains and traumas. The importance of the purpose in life construct reveals the need for a reliable and valid tool to measure it. Crumbaugh and Maholick's purpose in life questionnaire is the first and one of the most applied tools for the assessment of life's purposefulness. The aim of this research is to determine the factor Structure of purpose in life questionnaire. The questionnaire was administered on 206 students who were selected through random stratified sampling at Ferdowsi University of Mashhad. Exploratory factor analysis showed that there are two factors "comprehension" and "purpose" and this finding were confirmed by confirmatory factor analysis. Altogether results of this research showed factor validity of the purpose in life questionnaire with a two factor pattern

The purpose of this paper is to present an integrated approach to the Design of Structure Matrix and fuzzy set theory; and also to provide a method for clustering the system elements. In this approach, know as the \fuzzy Design Structure Matrix", integer numbers are replaced by fuzzy numbers. In fact, one of the problems of Designing Structure Matrix analysis using numbers integer, considering the lack of distinction between the dependence of the interactions of system elements is that such problems will be solved with this approach. On the other hand, the fuzzy Design Structure Matrix of interactions between elements, cost and less time is spent on systems analysis. According to the literature, there are diFFerent methods for clustering system elements. By studying the clustering methods as well as mathematical approaches derived from graph theory, a proposed approach for clustering fuzzy Design Structure Matrix was presented. The proposed approach has five major steps. Each step also includes several subsets. In the First step, the elements are identified with inputs from Designers and system boundaries are determined. In the second step, the fuzzy numbers are used in fuzzy evaluation method. In the third step, the basic fuzzy Design Structure Matrix is formed. In the next step, the grouping proposed for clustering fuzzy Design Structure Matrix is presented. Finally, using the Matrix of hierarchical relationships, priorities and the importance of clusters are determined. Analytical Network Process (ANP) is used for fuzzy evaluation method. In the literature related to the Design Structure Matrix in this case, the Analytical Hierarchy Process (AHP) has been used. considering the AHP hierarchy, some of interactions between elements have been ignored. Therefore, this shortage has been resolved by the ANP and the interactions between the elements have been considered and evaluated with higher accuracy. The proposed approach has been implemented on a servomechanism with two degrees of freedom. The system has 15 elements determined by the Designers. By implementing this approach, two independent elements and three clusters have been determined.

A new algorithm for reconstruction of Design relation Matrix(DRM) is presented. The reconstruction of an unknown DRM is discussed based on some Design Matrix projections, which was expressed by Design experts. The reconstruction algorithm has been formed based on the new concept of DRM. It shows the relation between functional requirements and Design parameters that exists in the related Design Matrix. The specifications of uncoupled, decoupled and coupled Design matrices are scrutinizable by the DRM and related concepts such as Design set (DS), Design row set (DRS) and Design column set (DCS). Then, the DRM reconstruction algorithm and algorithm for selecting the unbiased reconstruction from reconstruction family members are presented based on reconstruct ability analysis. The DRM reconstruction algorithm is applicable in reverse engineering, Design evaluation and improvement.