Analysis of Decision Support Systems of Industrial Relevance: Application Potential of Fuzzy and Grey Set Theories

The present work articulates few case empirical studies on decision making in industrial context. Development of variety of Decision Support System (DSS) under uncertainty and vague information is attempted herein. The study emphases on five important decision making domains where effective decision making may surely enhance overall performance of the organization. The focused territories of this work are i) robot selection, ii) g-resilient supplier selection, iii) third party logistics (3PL) service provider selection, iv) assessment of supply chain’s g-resilient index and v) risk assessment in e-commerce exercises. Firstly, decision support systems in relation to robot selection are conceptualized through adaptation to fuzzy set theory in integration with TODIM and PROMETHEE approach, Grey set theory is also found useful in this regard; and is combined with TODIM approach to identify the best robot alternative. In this work, an attempt is also made to tackle subjective (qualitative) and objective (quantitative) evaluation information simultaneously, towards effective decision making. Supplier selection is a key strategic concern for the large-scale organizations. In view of this, a novel decision support framework is proposed to address g-resilient (green and resilient) supplier selection issues. Green capability of suppliers’ ensures the pollution free operation; while, resiliency deals with unexpected system disruptions. A comparative analysis of the results is also carried out by applying well-known decision making approaches like Fuzzy- TOPSIS and Fuzzy-VIKOR. In relation to 3PL service provider selection, this dissertation proposes a novel ‘Dominance- Based’ model in combination with grey set theory to deal with 3PL provider selection, considering linguistic preferences of the Decision-Makers (DMs). An empirical case study is articulated to demonstrate application potential of the proposed model. The results, obtained thereof, have been compared to that of grey-TOPSIS approach. Another part of this dissertation is to provide an integrated framework in order to assess gresilient (ecosilient) performance of the supply chain of a case automotive company. The overall g-resilient supply chain performance is determined by computing a unique ecosilient (g-resilient) index. The concepts of Fuzzy Performance Importance Index (FPII) along with Degree of Similarity (DOS) (obtained from fuzzy set theory) are applied to rank different gresilient criteria in accordance to their current status of performance. The study is further extended to analyze, and thereby, to mitigate various risk factors (risk sources) involved in e-commerce exercises. A total forty eight major e-commerce risks are recognized and evaluated in a decision making perspective by utilizing the knowledge acquired from the fuzzy set theory. Risk is evaluated as a product of two risk quantifying parameters viz. (i) Likelihood of occurrence and, (ii) Impact. Aforesaid two risk quantifying parameters are assessed in a subjective manner (linguistic human judgment), rather than exploring probabilistic approach of risk analysis. The ‘crisp risk extent’ corresponding to various risk factors are figured out through the proposed fuzzy risk analysis approach. The risk factor possessing high ‘crisp risk extent’ score is said be more critical for the current problem context (toward e-commerce success). Risks are now categorized into different levels of severity (adverse consequences) (i.e. negligible, minor, marginal, critical and catastrophic). Amongst forty eight risk sources, top five risk sources which are supposed to adversely affect the company’s e-commerce performance are recognized through such categorization. The overall risk extent is determined by aggregating individual risks (under ‘critical’ level of severity) using Fuzzy Inference System (FIS). Interpretive Structural Modeling (ISM) is then used to obtain structural relationship amongst aforementioned five risk sources. An appropriate action requirement plan is also suggested, to control and minimize risks associated with e-commerce exercises

Usporedbeno proučavanje razbijanja deuterona alfa česticama

Experimental triple correlation cross–sections in the reaction d + α → α + p + n, have been analysed following different approaches, in the framework of single level R–matrix theory (RM). Concentrating on the spectra dominated by α–neutron final–state–interaction (αn FSI), a rather large amount of data have been investigated. Fits due to existing Faddeev type calculations have been compared and relative merits discussed.Eksperimentalni se tro–korelacijski udarni presjeci reakcije d+α → α+ p+ n analiziraju raznim metodama na osnovi jednorazinske R–matrične teorije. Istražuju se mnogi spektri u kojima prevladava međudjelovanje α–neutron u konačnom stanju. Dobiveni se rezultati uspoređuju s ranijim računima zasnovanim na Faddeevovoj teoriji

Prediction Equations for Body-fat Percentage in Indian Infants and Young Children Using Skinfold Thickness and Mid-arm Circumference

The objective of the study was to develop prediction equations for fat-mass percentage in infants in India based on skinfold thickness, mid-arm circumference, and age. Skinfold thicknesses and mid-arm circumference of 46 apparently-healthy infants (27 girls and 19 boys), aged 6–24 months, from among the urban poor attending a well baby clinic of a hospital in Kolkata were measured. Their body-fat percentage was measured using the D2O dilution technique as the reference method. Equations for body-fat percentage were developed using a stepwise forward regression model using skinfold thicknesses, mid-arm circumference, and age as independent variables, and the body-fat percentage was derived by D2O dilution as the dependent variable. The new prediction equations are: body-fat percentage=-69.26+5.76×B-0.33×T2+5.40×M+0.01×A2 for girls and body-fat percentage=-8.75+3.73×B+2.57×S for boys, where B=biceps skinfold thickness, T=triceps skinfold thickness, and S=suprailiac skinfold thickness all in mm, M=mid-arm circumference in cm, and A=age in month. Using the D2O dilution technique, the means (SD) of the calculated body-fat percentage were 17.11 (7.25) for girls and 16.93 (6.62) for boys and, using the new prediction equations, these were 17.11 (6.25) for girls and 16.93 (6.02) for boys. The mean of the differences of paired values in body-fat percentage was zero. The mean (SD) of the differences of paired values for body-fat percentage derived by the D2O technique and the new equations, applied on an independent sample of 23 infants (11 girls and 12 boys) were -0.93 (6.56) for girls and 1.14 (2.43) for boys; the 95% confidence limits of the differences of paired values for body-fat percentage were -2.03 to +3.89 for girls and -0.26 to +2.54 for boys. Given that the trajectories of growth during infancy and childhood are a major risk factor for a group of diseases in adulthood, including coronary heart disease and diabetes, these predictive equations should be useful in field studies

Development of prediction equations for body composition in Indian children using bioelectrical impedance analysis

We aimed to develop a BIA equation to predict fat free mass (FFM) using deuterium oxide (2H2O) dilution as the reference method for children. Seventy seven children (36 boys and 41 girls), aged 6 to 24 month participated in the study. The best fit FFM prediction equation included weight, sex and length2/resistance (adjusted R2=0.83 and root mean square error of 0.49 kg). Applying ‘leave-one-out’ method the mean of the differences of FFM in kg and % body weight were nearly zero with 95% confidence intervals of ±0.108 kg between those derived by 2H2O dilution and by the validated equation. PRESS statistic residual was 473g (»0). The best fit equation for FFMkg was: FFMkg=0.72+0.30× (weight) +0.16× (sex) +0.52× (Length2/resistance) (Length in cm, weight in kg, resistance in W, sex: boys=1, girls=0) The derived predictive equation has good precision and is useful for community based studies on body composition in South Asian children

Development of prediction equations for body composition in Indian children using bioelectrical impedance analysis

We aimed to develop a BIA equation to predict fat free mass (FFM) using deuterium oxide (2H2O) dilution as the reference method for children. Seventy seven children (36 boys and 41 girls), aged 6 to 24 month participated in the study. The best fit FFM prediction equation included weight, sex and length2/resistance (adjusted R2=0.83 and root mean square error of 0.49 kg). Applying ‘leave-one-out’ method the mean of the differences of FFM in kg and % body weight were nearly zero with 95% confidence intervals of ±0.108 kg between those derived by 2H2O dilution and by the validated equation. PRESS statistic residual was 473g (»0). The best fit equation for FFMkg was: FFMkg=0.72+0.30× (weight) +0.16× (sex) +0.52× (Length2/resistance) (Length in cm, weight in kg, resistance in W, sex: boys=1, girls=0) The derived predictive equation has good precision and is useful for community based studies on body composition in South Asian children

Role of Androgens in Cardiovascular Diseases in Men: A Comprehensive Review

The present knowledge on the androgens role in cardiovascular physiology is not fully completed. It remains unclear whether low serum testosterone concentrations in men are an independent risk factor for cardiovascular diseases (CVDs) or a marker of the presence of CVD. However, we demonstrated that endogenous testosterone levels may be implicated in CVDs. Androgens role in modulating cardiovascular function is one of the highest importances, given that its deficiency is strongly associated with hypertension, atherosclerosis, diabetes, obesity, and cardiac hypertrophy. Although significant and independent association between testosterone levels and cardiovascular events in elderly men have not been confirmed in large prospective studies, cross-sectional studies, however, suggested that low testosterone levels in elderly men are associated with CVDs. The results of androgen therapy are not also conclusive. Perhaps, the effects of testosterone treatment of cardiovascular mortality and morbidity have not been extensively examined in control studies. Data on male animal experimentation of the effect of testosterone replacement therapy are either neutral or beneficial on the development of atherosclerosis. Since circulatory androgen levels modulation is expected to cause many other side effects, it seems to be essential to develop a strategy to target androgen receptor for better treating the CVDs