Perception of employers and employees regarding the attitude of businesses toward the environment: a qualitative analysis

Commitment and involvement from the different members of an organization are two key elements for an organization to achieve its environmental excellence. Firstly, businesses are aware of the close relationship between their activities and the environment, for they are not only polluting agents but also agents with the capacity to reduce adverse environmental impacts. Secondly, the fact that employees can play a relevant role in terms of the socially responsible measures to be taken by organizations has started to become an irrefutably important issue. This piece of research is intended to help gain knowledge concerning the attitude of the two main actors in productive activity toward the environmental, that is, employers and employees; as well, this research intends to identify factors determining behaviour towards the environmental. For this, we have gathered the ideas and assessments contained in the discourse of a group of small and medium-sized businesses, large company owners and officers, employees, and work related risk prevention representatives. Qualitative work consisted of in-depth interviews and the creation of discussion groups.

Adaptive neuro-fuzzy inference systems (ANFIS) for supervised classification of competence in MIS based on psychomotor skills

INTRODUCTION: Objective assessment of motor skills has become an important challenge in minimally invasive surgery (MIS) training.Currently, there is no gold standard defining and determining the residents' surgical competence.To aid in the decision process, we analyze the validity of a supervised classifier to determine the degree of MIS competence based on assessment of psychomotor skills METHODOLOGY: The ANFIS is trained to classify performance in a box trainer peg transfer task performed by two groups (expert/non expert). There were 42 participants included in the study: the non-expert group consisted of 16 medical students and 8 residents (< 10 MIS procedures performed), whereas the expert group consisted of 14 residents (> 10 MIS procedures performed) and 4 experienced surgeons. Instrument movements were captured by means of the Endoscopic Video Analysis (EVA) tracking system. Nine motion analysis parameters (MAPs) were analyzed, including time, path length, depth, average speed, average acceleration, economy of area, economy of volume, idle time and motion smoothness. Data reduction was performed by means of principal component analysis, and then used to train the ANFIS net. Performance was measured by leave one out cross validation. RESULTS: The ANFIS presented an accuracy of 80.95%, where 13 experts and 21 non-experts were correctly classified. Total root mean square error was 0.88, while the area under the classifiers' ROC curve (AUC) was measured at 0.81. DISCUSSION: We have shown the usefulness of ANFIS for classification of MIS competence in a simple box trainer exercise. The main advantage of using ANFIS resides in its continuous output, which allows fine discrimination of surgical competence. There are, however, challenges that must be taken into account when considering use of ANFIS (e.g. training time, architecture modeling). Despite this, we have shown discriminative power of ANFIS for a low-difficulty box trainer task, regardless of the individual significances between MAPs. Future studies are required to confirm the findings, inclusion of new tasks, conditions and sample population.