Lusine Mkrtchyan

Analyzing Risk Impact Factors Using Extended Fuzzy Cognitive Maps

One of the challenges in Risk Analysis and Management (RAM) is identifying the relationships between risk factors and risks. The complexity of the method to analyze these relationships, the time to complete the analysis, the robustness and trustworthiness of the method are important features to be considered. In this paper, we propose using Extended Fuzzy Cognitive Maps (E-FCMs) to analyze the relationships between risk factors and risks, and adopting a pessimistic approach to assess the overall risk of a system or a project. E-FCMs are suggested by Hagiwara to represent causal relationships more naturally. The main differences between E-FCMs and conventional Fuzzy Cognitive Maps (FCMs) are the following: E-FCMs have nonlinear membership functions, conditional weights, and time delay weights. Therefore E-FCMs are suitable for risk analysis as all features of E-FCMs are more informative and can fit the needs of Risk Analysis. In this paper we suggest a framework to analyze risks using E-FCMs and extend E-FCMs themselves by introducing a special graphical representation for risk analysis. We also suggest a framework for group decision making using E-FCMs. Particularly, we explore the Software Project Management (SPM) and discuss risk analysis of SPM applying E-FCMs.

Risk Analysis Using Extended Fuzzy Cognitive Maps

One of the challenges in Risk Analysis and Management (RAM) is identifying the relationships between risk factors and risks. In this paper we propose using Extended Fuzzy Cognitive Maps to analyze the relationships between risk factors and risks. E-FCMs are suggested by Hagiwara to represent causal relationships more naturally. The main differences between E-FCMs and conventional Fuzzy Cognitive Maps are the following: E-FCMs have non-linear membership functions, conditional weights, and time delay weights. Therefore E-FCMs are suitable for risk analysis as all features of E-FCMs are more informative and can fit the needs of Risk Analysis. In this paper we suggest a framework to analyze risks using E-FCMs and extend E-FCMs themselves by introducing a special graphical representation for risk analysis. We also suggest a framework for group decision making using E-FCMs. Particularly, we explore the Software Project Management (SPM) and discuss risk analysis of SPM applying E-FCMs.

A Bayesian Based Method for Agile Software Development Release Planning and Project Health Monitoring

Agile software development (ASD) techniques are iteration based powerful methodologies to deliver high quality software. To ensure on time high quality software, the impact of factors affecting the development cycle should be evaluated constantly. Quick and precise factor evaluation results in better risk assessment, on time delivery and optimal use of resources. Such an assessment is easy to carry out for a small number of factors. However, with the increase of factors, it becomes extremely difficult to assess in short time periods. We have designed and developed a project health measurement model to evaluate the factors affecting software development of the project. We used Bayesian networks (BNs) as an approach that gives such an estimation. We present a quantitative model for project health evaluation that helps decision makers make the right decision early to amend any discrepancy that may hinder on time and high quality software delivery.

A Multimodal Interface Device for Online Board Games Designed for Sight-Impaired People

Online games between remote opponents playing over computer networks are becoming a common activity of everyday life. However, computer interfaces for board games are usually based on the visual channel. For example, they require players to check their moves on a video display and interact by using pointing devices such as a mouse. Hence, they are not suitable for visually impaired people. The present paper discusses a multipurpose system that allows especially blind and deafblind people playing chess or other board games over a network, therefore reducing their disability barrier. We describe and benchmark a prototype of a special interactive haptic device for online gaming providing a dual tactile feedback. The novel interface of this proposed device is able to guarantee not only a better game experience for everyone but also an improved quality of life for sight-impaired people.

Using Belief Degree Distributed Fuzzy Cognitive Maps for Energy Policy Evaluation

Cognitive maps (CMs) were initially for graphical representation of uncertain causal reasoning. Later Kosko suggested Fuzzy Cognitive Maps (FCMs) in which users freely express their opinions in linguistic terms instead of crisp numbers. However, it is not always easy to assign some linguistic term to a causal link. In this paper we suggest a new type of CMs namely, Belief Degree-Distributed FCMs (BDD-FCMs) in which causal links are expressed by belief structures which enable getting the links’ evaluations with distributions over the linguistic terms. We propose a general framework to construct BDD-FCMs by directly using belief structures or other types of structures such as interval values, linguistic terms, or crisp numbers. The proposed framework provides a more flexible tool for causal reasoning as it handles any kind of structures to evaluate causal links. We propose an algorithm to find a similarity between experts judgments by BDD-FCMs for a case study in Energy Policy evaluation.

Ranking of generalized fuzzy numbers and its application to risk analysis

This paper deals with the problem of the ranking of generalized fuzzy numbers. Our aim is to give a possibility to rank any non-identical generalized fuzzy numbers. The majority of existing approaches fail to rank fuzzy numbers in certain cases and give equality when in fact fuzzy numbers are different. We explore and extend Chen and Lus approach that is good enough in terms of computational effort and efficiency in case of large quantity of fuzzy numbers. Chen and Lus algorithm ranks fuzzy numbers based on the left and right dominance established by α-cuts. The only drawback of this algorithm is that it does not differentiate fuzzy numbers in some situations. We suggest an extension of the algorithm to solve this problem. We apply our algorithm to fuzzy risk analysis problems, particularly those concerning risks to choose among several alternatives.

A novel approach for safety culture assessment

Safety Culture describes how safety issues are managed within an enterprise. How to make safety culture strong and sustainable? How to be sure that safety is a prime responsibility or main focus for all types of activity? How to improve safety culture and how to identify the most vulnerable issues of safety culture? These are important questions for safety culture. Huge amount of studies focus on identifying and building the hierarchy of the main indicators of safety culture. However, there are only few methods to assess an organizations safety culture and those methods are often straightforward. In this paper we describe a novel approach for safety culture assessment by using Belief Degree-Distributed Fuzzy Cognitive Maps (BDD-FCMs). Cognitive maps were initially presented for graphical representation of uncertain causal reasoning. Later Kosko suggested Fuzzy Cognitive Maps FCMs in which users freely express their opinions in linguistic terms instead of crisp numbers. However, it is not always easy to assign some linguistic term to a causal link. By using BDD-FCMs, causal links are expressed by belief structures which enable getting the links evaluations with distributions over the linguistic terms. In addition, we propose a general framework to construct BDD-FCMs by directly using belief structures or other types of structures such as intervals, linguistic terms, or crisp numbers. The proposed framework provides a more flexible tool for causal reasoning as it handles different structures to evaluate causal links.

Pessimistic evaluation of risks using ranking of generalized fuzzy numbers

The most important factors contributing to the risk of failure for any type of organization or system are related to poor performance, time pressure, low quality and high cost.

Clustering of Fuzzy Cognitive Maps for Travel Behavior Analysis

The increasing of public transportation or bike use became an important issue in addressing economic, energy and environmental challenges. With this regard one of the most main tasks is to find and analyze the factors influencing car dependency and the attitudes of people in terms of preferred transport mode. In this paper Fuzzy Cognitive Maps (FCM) are explored to show how travelers make decisions based on their knowledge of different transport modes properties. The results of this study will help transportation policy decision makers in better understanding of people’s needs and actualizing different policy formulations and implementations.

Can belief structures improve our understanding of safety climate survey data

Questionnaire-based surveys are a standard method used for assessing the safety climate within an organization. However, their analysis - in particular data aggregation - poses several challenges, among which are subjective judgment, incompleteness and uncertainty. This paper explores the use of approaches based on belief structures for aggregating data from safety climate questionnaires. Data relevant to this study were collected through a questionnaire administered to the employees of a nuclear research centre. The results show that, while belief structures may offer a promising way to represent data collected from questionnaires, the existing aggregation methods are not always adequate. Averaging schemes applied to belief structures seem the most suited - among the methods investigated - in the specific problem context analyzed. The analysis of the survey data shows the limitations of quantitative approaches for safety culture assessment and the need to always complement these with in-depth qualitative analysis. The data collected with a safety climate survey were modeled as belief structures.A number of combination rules are investigated for the purpose of data aggregation.Illustrative examples are used to demonstrate the limitations and suitability of the different combinations rules.