Risk Acceptance in the Furniture Sector: Analysis of Acceptance Level and Relevant Influence Factors

Risk acceptance has been broadly discussed in relation to hazardous risk activities and/or technologies. A better understanding of risk acceptance in occupational settings is also important; however, studies on this topic are scarce. It seems important to understand the level of risk that stakeholders consider sufficiently low, how stakeholders form their opinion about risk, and why they adopt a certain attitude toward risk. Accordingly, the aim of this study is to examine risk acceptance in regard to occupational accidents in furniture industries. The safety climate analysis was conducted through the application of the Safety Climate in Wood Industries questionnaire. Judgments about risk acceptance, trust, risk perception, benefit perception, emotions, and moral values were measured. Several models were tested to explain occupational risk acceptance. The results showed that the level of risk acceptance decreased as the risk level increased. High-risk and death scenarios were assessed as unacceptable. Risk perception, emotions, and trust had an important influence on risk acceptance. Safety climate was correlated with risk acceptance and other variables that influence risk acceptance. These results are important for the risk assessment process in terms of defining risk acceptance criteria and strategies to reduce risks.

System Level Simulation and Radio Resource Management for Distributed Antenna Systems with Cognitive Radio and Multi-Cell Cooperation

4th International Conference on Future Generation Communication Technologies (FGCT 2015), Luton, United Kingdom.

A multi-objective optimization of the active and reactive resource scheduling at a distribution level in a smart grid context

In the traditional paradigm, the large power plants supply the reactive power required at a transmission level and the capacitors and transformer tap changer were also used at a distribution level. However, in a near future will be necessary to schedule both active and reactive power at a distribution level, due to the high number of resources connected in distribution levels. This paper proposes a new multi-objective methodology to deal with the optimal resource scheduling considering the distributed generation, electric vehicles and capacitor banks for the joint active and reactive power scheduling. The proposed methodology considers the minimization of the cost (economic perspective) of all distributed resources, and the minimization of the voltage magnitude difference (technical perspective) in all buses. The Pareto front is determined and a fuzzy-based mechanism is applied to present the best compromise solution. The proposed methodology has been tested in the 33-bus distribution network. The case study shows the results of three different scenarios for the economic, technical, and multi-objective perspectives, and the results demonstrated the importance of incorporating the reactive scheduling in the distribution network using the multi-objective perspective to obtain the best compromise solution for the economic and technical perspectives.

Testing Nelder-Mead Based Repulsion Algorithms for Multiple Roots of Nonlinear Systems via a Two-Level Factorial Design of Experiments

This paper addresses the challenging task of computing multiple roots of a system of nonlinear equations. A repulsion algorithm that invokes the Nelder-Mead (N-M) local search method and uses a penalty-type merit function based on the error function, known as 'erf', is presented. In the N-M algorithm context, different strategies are proposed to enhance the quality of the solutions and improve the overall efficiency. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm.