A. Felix

Bio: A. Felix is an academic researcher from Loyola College, Chennai. The author has contributed to research in topics: Fuzzy number & Fuzzy logic. The author has an hindex of 4, co-authored 21 publications receiving 65 citations.

A Study on the Impact of Violent Video-Games playing among Children in Chennai using Neutrosophic Cognitive Maps (NCMs)

Abstract: In this paper we analyzed, the impact of violent video-games playing among children in Chennai and find out its solution using Neutrosophic Cognitive Maps(NCMs), which is the generalization of Fuzzy Cognitive Maps(FCMs) defined by W.B. Vasantha Kandasamy and Florentine Smarandache. This paper has a five section. First section gives the information about development of Fuzzy Cognitive Maps and Neutrosophic Cognitive Map. Second section gives the preliminaries of FCMs and NCMs. In section three, we give the description of the problem. Final section gives the conclusion based on our study.

A fuzzy dematel approach to study cause and effect relationship of youth violence

Abstract: The Decision making trial and evaluation laboratory (DEMATEL) is a method is useful tool for analyzing correlations among factors using the crisp values. However, in many real life cases, the decision data of human judgments with preferences are often vague so that the traditional ways of using crisp values are inadequate. In this paper, the directed influential degrees between pair wise criteria are expressed in triangular fuzzy numbers is used in DEMATEL method to study on youth violence. Violence is a problem which affects our day today life in a severe way. Even though human beings have been struggling to create civilized societies for many years, they have not able to get free from the influence of violence and aggression yet. Aggressiveness among youth is considered to be a global public health problem in many parts of the world. The existence of violence around a person might provoke him to behave in a more violent way. So in this paper we analyze what makes the youth to be aggressive behavior and involving in violence and its effect.

Haar FCM with DEMATEL Technique to Analyze the Solid Waste Management

Abstract: An interesting attempt is taken to form a hybrid model by integrating Fuzzy Cognitive Map (FCM), the Delphi Method, and the DEMATEL method through the Haar ranking of Hexagonal Fuzzy Number. To examine this model, the problem of solid waste management is taken. Solid waste arises from human and animal activities can generate major health problems and horrible living environment when they are not dumped of safely and appropriately. The proper disposal of solid waste helps to reduce the terrible impacts on both human health and environment to sustain economic growth and better quality of life. Therefore, this present study analyzes the solid waste management through the Haar FCM with DEMATEL technique.

A New Decagonal Fuzzy Number under Uncertain Linguistic Environment

Abstract: Emerging research has focused on uncertain linguistic term in group decision making pro- cesses. The uncertain linguistic term is an important and frequently used as input in decision analysis activities. Linguistic values are usually represented as fuzzy number. Therefore, in this paper a new operation on Decagonal Fuzzy Number under uncertain linguistic environment is presented. The main objective of this paper is to introduce operation for addition, subtraction and multiplication of decagonal fuzzy number on the basis of alpha cut.

A New Bidirectional Associative Neutrosophic Cognitive Dynamical System approaches to study Youth Violence

Abstract: BAM and NCMs have been applied in many fields to show the relationship between the essential components. In this paper we introduce a new Neutrosophic Bimodal called Bidirectional Associative Neutrosophic Cognitive Maps (BANCMs) to analyze the problem of youth violence since enormous growth of violent escalation among youth in every country and culture is alarming. This new model can act simultaneously to give the solution in more accurately. This article organized as follows, section one describes the problem of our study. Section two recalls the basic concepts of BAM and NCM. Section three gives the new modal BANCM. Section four, the adaptation of the problem using BANCM and final section derived conclusion, suggestion and scope for future study.

The Five-Factor Model

Abstract: The Five-Factor Model (FFM) of personality is a trait approach to the conceptualization of personality. The five dimensions of FFM can be measured validly, although some potential confounders still need to be resolved. Furthermore, these psychometric findings have links to biology, like moderate heritability and physiological correlates, which suggests a biological basis for the FFM. Finally, knowledge of a specific subject’s standing on the five dimensions can predict real life behaviour, thereby providing important information in relation to diagnosis, intervention and future outcomes. Although the FFM is only one among several approaches to personality it provides a platform for combining other approaches to personality, with the ultimate goal of providing a unified, research based framework for describing, explaining and doing research in personality.

A novel technique for evaluating and selecting logistics service providers based on the logistics resource view

Abstract: Modelling logistics outsourcing process using logistics resources under uncertainty.Using FDEMATEL to analyse the logistics resources impact relationships and weights.Identifying independent logistics resources and evaluate LSPs using FTOPSIS.Testing the model effectiveness through a developing-economy real case study.Confirming the model robustness through a two-phase sensitivity analysis. The increasing importance of logistics outsourcing and availability of logistics services providers (LSPs) highlights the significance and complexity of the LSP evaluation and selection process. Most existing LSP evaluation and selection studies use historical performance data and assume independence among decision criteria. This paper proposes an integrated logistics outsourcing approach to evaluate and select LSPs based on their logistics resources and capabilities. This novel approach combines a fuzzy decision making trial, evaluation laboratory (FDEMATEL) and fuzzy techniques to order preferences by similarity to ideal solution (FTOPSIS) methods. The new multi-criteria decision making (MCDM) model addresses the impact relationships between decision criteria and ranks LSP alternatives against weighted resources and capabilities. The effectiveness of this approach is demonstrated through a real case study and a two-phase sensitivity analysis confirms its robustness.

Lean Six Sigma project selection using hybrid approach based on fuzzy DEMATEL–ANP–TOPSIS

Abstract: Purpose – The purpose of this paper is to select the optimal Lean Six Sigma (LSS) project using hybrid fuzzy-based Multi-Criteria Decision-Making (MCDM) approach for an automotive component manufacturing organization. Design/methodology/approach – The LSS project selection has been formulated as the MCDM problem. Hybrid MCDM method based on Decision-Making Trial and Evaluation Laboratory Model (DEMATEL), Analytical Network Process (ANP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) has been used to select the optimal LSS project. The methodology enabled the practitioners to systematically prioritize LSS projects. Findings – The finding of this study is that, out of five LSS projects, project P3 is the best LSS project. P3 is the optimal LSS project with reduced failure risk, and efforts are being taken to implement the selected project. Research limitations/implications – The problem formulation and methodology has been tested for a single study. In future, more number of stu...

Environmental Audio Scene and Sound Event Recognition for Autonomous Surveillance: A Survey and Comparative Studies

Abstract: Monitoring of human and social activities is becoming increasingly pervasive in our living environment for public security and safety applications. The recognition of suspicious events is important in both indoor and outdoor environments, such as child-care centers, smart-homes, old-age homes, residential areas, office environments, elevators, and smart cities. Environmental audio scene and sound event recognition are the fundamental tasks involved in many audio surveillance applications. Although numerous approaches have been proposed, robust environmental audio surveillance remains a huge challenge due to various reasons, such as various types of overlapping audio sounds, background noises, and lack of universal and multi-modal datasets. The goal of this article is to review various features of representing audio scenes and sound events and provide appropriate machine learning algorithms for audio surveillance tasks. Benchmark datasets are categorized based on the real-world scenarios of audio surveillance applications. To have a quantitative understanding, some of the state-of-the-art approaches are evaluated based on two benchmark datasets for audio scenes and sound event recognition tasks. Finally, we outline the possible future directions for improving the recognition of environmental audio scenes and sound events.

Hybrid model for medical diagnosis using Neutrosophic Cognitive Maps with Genetic Algorithms

Abstract: This paper presents a combination of two soft computing techniques: Neutrosophic cognitive maps and Genetic algorithm for modeling of medical disease diagnosis. Earlier, medical decision support system was proposed by many researchers where cognitive maps along with genetic algorithm were experimented. The hybrid model of fuzzy cognitive maps with genetic algorithm was implemented to handle situations where decisions are not clearly distinct. In real world situation data is not always consistent so, authors proposed a new hybrid model of Neutrosophic Cognitive Maps with Genetic Algorithms to handle indeterminacy. The proposed model will provide distinct diagnosis of disease in medical decision support system.