A Fuzzy Topsis Method for Prioritized Aggregation in Multi‐Criteria Decision Making Problems

Aggregation in a decision making environment requires the fusion of opinions of a group of decision makers. The group of decision makers are required to analyse a set of interrelated criteria that are usually measured on a linguistic scale. This process requires, in many instances, to capture experts experience, intuition and thinking that are traditionally expressed in a linguistic fashion rather than a numerical fashion. Furthermore, the necessity of considering the relationship between the criteria to the overall decision must be considered by the group of decision makers. This paper extends the application of fuzzy numbers, fuzzy relative importance scores (FRIS), fuzzy relative weights (FRW) and the fuzzy technique of order preference by similarity to ideal solution (TOPSIS) in prioritized aggregation. This extension provides a mean to systematically aggregate a group of decision makers' views for a set of interrelated criteria that are measured on a linguistic scale. First, an overview of the application of fuzzy numbers and the characteristics of aggregating fuzzy numbers in multi‐criteria decision making problems are presented. Then, the application of TOPSIS in fuzzy environments is presented. Next, past research is highlighted to present prioritized aggregation and the different aggregation operators' classes. Subsequently, a new prioritized aggregation method is presented. This method utilizes fuzzy TOPSIS with prioritized aggregation in fuzzy environments. Finally, the fuzzy prioritized aggregation method presented in this paper is applied on an actual case study. According to the results, the method presented in this paper provides a systematic approach to capture the uncertainty and imprecision associated with quantifying linguistic measurements in multi‐criteria decision making problems. Furthermore, it considers the relationship between the set of linguistically measured criteria undergoing prioritized aggregation in a fuzzy environment. Lastly, findings, conclusions and future work are presented. Copyright © 2016 John Wiley & Sons, Ltd.     

A Decision Support System for Prioritizing Investments in an Energy Efficiency Program in Favelas in the City of Rio de Janeiro

This study proposes an integrated qualitative and quantitative assessment of expert opinions aiming at ranking a set of five shantytowns (favelas) located in the city of Rio de Janeiro. These communities are candidates for investments in an energy efficiency program implemented by the local electric utility company. The city, state, and federal governments want to eliminate domination of these areas by organized criminal gangs and present the city as a peaceful metropolis while hosting two big sports events: the soccer World Cup in 2014 and the Olympic Games in 2016. In recent years, some favelas were chosen to be prototypes for an ambitious project to reshape Rio de Janeiro. This involves first sending in special tactics police to drive drug gangs out, then installing the Pacifying Police Unit in the favela. Once security has been established, it is possible to improve general living conditions in these areas, including by providing public services such as health clinics, formal electricity connections and cable television. The core of the energy efficiency program was to convert informal customers to formal ones, because such communities were responsible for approximately 40% of the commercial losses (stolen energy) in the city. The model specification presented in this paper was set up with ten relevant criteria for decision making, identified through an in‐depth interview with the decision maker. The relative importance of the criteria and the performance of each favela regarding each criterion were measured by the Simos method. The preferences resulting from this method were translated into a nine‐point scale. The imprecision of subjective judgment was partially compensated by using a fuzzy analytical hierarchy process. Some criteria were ordinal, such as ‘Fair Relationship with the Community’ and ‘Complexity to Rebuild the Distribution Lines’, whereas other were cardinal, like ‘Percentage of Clients in Default’ and ‘Commercial Loss Due to Energy Theft’. At the end, the model was efficient in ranking the five favelas, therefore contributing to a rational and transparent approach for capital investment in social projects. Copyright © 2014 John Wiley & Sons, Ltd.     

Ranking of Drivers for Green Manufacturing Implementation Using Fuzzy Technique for Order of Preference by Similarity to Ideal Solution Method

The governments are under tremendous pressure to sustain high manufacturing growth in emerging economies. Unfortunately, the manufacturing sector consumes much energy and other resources and emits a large amount of green house gases, which increases environmental problems such as climate change and global warming. One possible solution to this problem is green manufacturing (GM) implementation in industry. However, GM implementation faces many challenges. Various motivating factors named as ‘drivers’ should be facilitated by the government and industry to make this change possible. This paper investigates the drivers for GM implementation and their ranking based on fuzzy technique for order of preference by similarity to ideal solution method using government, industry and experts perspectives. The study concluded that competitiveness, incentives, organizational resources and technology are top ranked drivers and should be facilitated by the government and industry to help implement GM. The ranking of these drivers is expected to help the government and industry to focus on few important drivers to facilitate the GM implementation with limited resources. Copyright © 2014 John Wiley & Sons, Ltd.     

Interpretation and method

Abstract

Interpretation started as the central tool of psychoanalytic theory, but it has undergone changes, just as the theory it was based on has evolved. Not only have these significant changes been determined by cultural trends, but different authors have also contributed to their evolution through their approaches to various other pathologies besides neurosis. Today, the cure process is divided between those who believe that therapeutic efficiency should be based on the different interpretation models, and those who maintain that it can be only sustained by the modifying capacity of the therapeutic relationship. Both positions are supposedly upheld by the results of tests that both models believe are sufficient proof but that, in the current author's opinion, lead back to the type of pathology they arose from, although they may at times attempt to cover the entire theoretical spectrum. The position upheld by Gedo—who considers that the psychoanalyst's intervention will depend on the degree of evolution that the pathology has achieved—is of great interest for specific practice. Hence, the more primitive levels require a treatment founded on holding, whereas more evolved pathologies require a more classic level of interpretation. This implies that the stages of a particular patient's evolution may require interventions at different levels, even though these may be founded on different theoretical models. This model, which we may brand as eclectic, is basically the one we find underpinning different theoretical models, which effectively appear to integrate others.     

Interfacial waves between two piezoelectric half-spaces with electro-mechanical imperfect interface

We study the propagation of shear horizontal waves between the interface of two piezoelectric materials with an electro-mechanical imperfect contact. Mechanical and electrical imperfections are modeled by means of a spring and a capacitor, respectively. The corresponding mathematical expressions for the imperfect contact are given in this article. The system of differential equations for the waves in the considered half-space is derived and the associate solutions are found. A general expression for the dispersion relation, not reported previously in the literature, is given in an explicit form, with the diverse limit cases analyzed in detail. In some of these limit cases, new expressions are also obtained, which predict the existence of interfacial waves. In the other cases, where already reported results exist, a comparison with them is done. Some physical interpretations are derived from the limit cases. The influence of mechanical and electrical imperfect contacts are shown in some numerical examples.     

Change detection inflates confidence on a subsequent recognition task

A face viewed under good encoding conditions is more likely to be remembered than a face viewed under poor encoding conditions. In four experiments we investigated how encoding conditions affected confidence in recognising faces from line-ups. Participants performed a change detection task followed by a recognition task and then rated how confident they were in their recognition accuracy. In the first two experiments the same faces were repeated across trials. In the final two experiments novel faces were used on each trial. Target-present and target-absent line-ups were utilised. In each experiment participants had greater recognition confidence after change detection than after change blindness. The finding that change detection inflates confidence, even for inaccurate recognitions, indicates recognition certainty can be a product of perceived encoding conditions rather than authentic memory strength.     

Semantic priming in French children with varying comprehension skills

Semantic priming was analysed in two groups of French children contrasted on comprehension skills with a visual lexical-decision task using a long SOA (800 ms). Two relation types between related primes and targets were examined: pure semantic relation (categorical vs. functional), and lexical association strength (strong vs. weak). Targets were preceded by related, unrelated, and neutral primes. Skilled comprehenders showed semantic priming only for category-related words, whatever their association strength, and without any evidence of an associative boost. Less-skilled comprehenders also showed semantic priming for category-related words, irrespective of their association strength, but with an indication of an associative boost. They also displayed semantic priming for function-related awords that are strongly associated, but not for those that are weakly associated. These results are discussed within the theoretical frame proposed by Plaut and Booth (2000 Plaut, D. C. and Booth, J. R. 2000. Individual and developmental differences in semantic priming: Empirical and computational support for a single-mechanism account of lexical processing. Psychological Review, 4: 786–823.  [Google Scholar]).     

Co-occurrence frequency evaluated with large language corpora boosts semantic priming effects

In recent decades, many computational techniques have been developed to analyse the contextual usage of words in large language corpora. The present study examined whether the co-occurrence frequency obtained from large language corpora might boost purely semantic priming effects. Two experiments were conducted: one with conscious semantic priming, the other with subliminal semantic priming. Both experiments contrasted three semantic priming contexts: an unrelated priming context and two related priming contexts with word pairs that are semantically related and that co-occur either frequently or infrequently. In the conscious priming presentation (166-ms stimulus-onset asynchrony, SOA), a semantic priming effect was recorded in both related priming contexts, which was greater with higher co-occurrence frequency. In the subliminal priming presentation (66-ms SOA), no significant priming effect was shown, regardless of the related priming context. These results show that co-occurrence frequency boosts pure semantic priming effects and are discussed with reference to models of semantic network.     

Internet Safety and the Silver Surfer: The Relationship Between Gist Reasoning and Adults' Risky Online Behavior

Currently, fewer older adults are online compared with younger generations. However, with many new initiatives aiming to significantly increase the number of older internet users, they will increasingly be exposed to potential victimisation from internet fraud, a fundamental issue affecting all adult internet users. Despite this, little research has examined online risk‐taking across the adult lifespan or adults' reasoning about risky online behaviors. Using fuzzy trace theory, we investigated adults' online risk‐taking behavior and intentions, and whether these behaviors were related to different ways of reasoning about risk, namely, gist reasoning (using qualitative, intuitive knowledge) and verbatim reasoning (using quantitative, specific knowledge). Participants (326 adults, 18–79 years old, M_age = 49.54 years) reported their past risk‐taking behavior, future online risk intentions, gist and verbatim reasoning about online risk, sensation seeking, and time spent online. Age was negatively correlated with past risk‐taking, time online, future risk intentions, and sensation seeking. However, time spent online was positively related to future risk intentions, suggesting that spending more time using the internet could lead individuals to take more risks. Increased verbatim reasoning predicted increased intentions to take online risks, while gist reasoning predicted reduced intentions to take risks online. Our findings extend online risk research applying fuzzy trace theory to adolescents and young adults and suggest that online safety training incorporating gist‐based reasoning strategies could benefit all adults and, in particular, older generations. Copyright © 2017 John Wiley & Sons, Ltd.     

Prioritizing emergency shelter areas using hybrid multi‐criteria decision approach: A case study

Every year, more than 400 natural disasters affect global population. Adopting a resilient approach strengthens communities to survive and recover well from destabilizing events. Disasters destroy or damage houses and infrastructure, which calls for arrangement of temporary establishments to provide immediate evacuation and shelter to affected population. These sites are vital for an effective relief and must be strategically planned. Communities living in disaster‐prone areas should prepare themselves well in advance for any future catastrophic event. This study adopts a hybrid group decision support approach for emergency shelter site selection problem. Initially, relevant factors for locating potential sites are identified by reviewing extant literature and through consultation from a panel of disaster management experts. Next, fuzzy analytic hierarchy process theory and technique for order preference by similarity to ideal solution have been used to prioritize identified criteria and to evaluate potential locations for displacement sites. A case study of the recent Nepal earthquake has been used to illustrate the effectiveness of the proposed model. The model offers a resilience building approach to prepare communities for any future contingency by proposing and prioritizing a set of planned displacement sites.