In this paper, a solution procedure is proposed to solve fuzzy linear fractional programming (FLFP) problem where cost of the objective function, the resources and the technological coefficients are triangular fuzzy numbers. Here, the FLFP problem is transformed into an equivalent deterministic multi-objective linear fractional programming (MOLFP) problem. By using Fuzzy Mathematical programming approach transformed MOLFP problem is reduced single objective linear programming (LP) problem. The proposed procedure illustrated through a numerical example.

Aims & Objectives: To study the epidemiology of workplace hand injuries, to understand relation between mode of injury and prognosis, to investigate into the possible contributing factors and to study the Socio-economic impact. Design of Study: For the prospective study there were 2 sources of data: 1) Proforma which was filled by the hand surgeon and 2) A questionnaire that was filled up by safety officer. For the retrospective study case, sheets were retrieved from the Medical Records section and a telephonic or personal interview was carried out by a single interviewer. Setting: Department of Plastic and Reconstructive Surgery, Parvathy Hospital, Chennai, India. Patients: A total of 419 industrial injury patients treated from January 2008 to January 2013 were included in the study. Further follow-up regarding return to work and residual disability continues. Main Outcome Measures: Personal details (Age, Gender, Handedness, Work experience, Income). Type of injury, mode of injury, day and time of injury, treatment given, disability and number of working days lost were measured. Results: Those workers who were experienced less than 6 months had more workplace injuries and the commonest contributing factor was co-workers carelessness followed by long working hours and faulty machinery. Maximum injuries occurred on Monday and morning shift. Conclusions: Constant supervision of trainees for 2 years, shorter working hours with regular breaks, regular health checkups for personnel, regular servicing of machines can prevent occurrence of hand injuries. Corrective surgery within 6 hours, systematic and protocol based physiotherapy and rehabilitation can reduce the economic loss and disability arising out of work place injuries.

In this study an attempt is made to mathematically model and predict algal blooms in Tolo Harbour (Hong Kong) using Genetic Programming (GP). Chlorophyll plays a vital role and is taken as a measure of algal bloom biomass and 8 other variables are taken as input for its prediction. It is observed that GP evolves multiple models with almost same values of errors -of -measure. Previous studies on GP modeling primarily focused on comparing the GP results with actual values. In contrast, in this study, the main aim is to propose a systematic procedure for identifying the most appropriate GP model from a list of feasible models (with almost same errorof measure) using physical understanding of the process aided by data interpretation. The study of the GP-evolved equations shows that they correctly identify the ecologically significant variables.Analysis of final GP evolved mathematical model indicates that of the 8 variables assumed to affect the algal bloom, the most significant effect is due to chlorophyll, total inorganic nitrogen and dissolved oxygen, as far as one week prediction is concerned. For higher lead prediction (biweekly), secchi disc depth and temperature appears as significant variables in addition to chlorophyll.

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