Multi-criteria decision-making and life cycle assessment model for optimal product selection: case study of knee support

Selection of the optimal product, where several products’ aspects are expressed through criteria, is a multi-criteria decision-making problem. Besides technical, exploitational, functional, structural, market and aesthetic criteria, nowadays, environmental criteria are inevitable aspects of a modern product. Environmental product properties can be successfully evaluated with a life cycle assessment. This paper proposes a multi-criteria decision-making model for optimal product assessment that uses environmental criteria obtained from a life cycle assessment. The proposed model presents a comprehensive approach that aims to overcome complex decision-making problems for optimal product selection, where special attention is given to the product’s environmental impact. Verification of the proposed multi-criteria decision-making and life cycle assessment model was performed on the case study of optimal knee support selection. By changing the criteria weights in multi-criteria decision-making, a sensitivity analysis was performed. The model output results show the product alternatives ranking that supports decision-making in optimal product selection.     

Co-residence of household heads with parents in Japan: a multivariate explanation

"This paper uses a multivariate logit model to study the factors affecting the Japanese household heads' propensities to co-reside with elderly parents, based on the micro data of a 1986 national survey. Our major findings are as follows. The most important factors are (1) inheritance of house or residential land from parent; (2) parent's spouseless status and age; (3) household head's sibling status; and (4) household head's nativity status. In a multivariate context, the negative effect of the household head's level of education was significant but not very important, whereas the presence of a working wife with child had a very weak positive effect on the co-residence with parent. Our overall conclusion is that the intergenerational co-residence in Japan is strongly affected by cultural norms and has a strong rational (economic) basis."     

Geospatial Ontology Development and Semantic Analytics

Geospatial ontology development and semantic knowledge discovery addresses the need for modeling, analyzing and visualizing multimodal information, and is unique in offering integrated analytics that encompasses spatial, temporal and thematic dimensions of information and knowledge. The comprehensive ability to provide integrated analysis from multiple forms of information and use of explicit knowledge make this approach unique. This also involves specification of spatiotemporal thematic ontologies and populating such ontologies with high quality knowledge. Such ontologies form the basis for defining the meaning of important relations terms, such as near or surrounded by, and enable computation of spatiotemporal thematic proximity measures we define. SWETO (Semantic Web Technology Evaluation Ontology) and geospatial extension SWETO‐GS are examples of these ontologies. The Geospatial Semantics Analytics (GSA) framework incorporates: (1) the ability to automatically and semi‐automatically tract metadata from syntactically (including unstructured, semi‐structured and structured data) and semantically heterogeneous and multimodal data from diverse sources; and (2) analytical processing that exploits these ontologies and associated knowledge bases, with integral support for what we term spatiotemporal thematic proximity (STTP) reasoning and interactive visualization capabilities. This paper discusses the results of our geospatial ontology development efforts as well as some new semantic analytics methods on this ontology such as STTP.