Fuzzy adaptive resonance theory approach to supplier involvement in product development: a case study in Turkish automobile industry

This study proposes a mechanism to evaluate suppliers for involvement during product development process. The proposed methodology is discussed within a multinational automobile firm and preliminary analysis indicates that the approach provides an effective mechanism for selecting suppliers involved in the product development process. To remedy to supplier integration problems, a clustering approach – fuzzy adaptive resonance theory (Fuzzy ART) – is used. The proposed methodology is explained using a case study that is realised in an automobile firm. Eventually, the results are presented comparatively, which obtained by current supplier evaluation system of the firm and provided from Fuzzy ART methodology. [Submitted 14 July 2009; Revised 16 November 2009; Accepted 17 November 2009]supplier involvement; supply chain management; SCM; adaptive resonance theory; fuzzy ART; product development; classification; Turkey; automobile industry; automotive supply chains; clustering.

Using principal component analysis and fuzzy c–means clustering for the assessment of air quality monitoring

AbstractDetermining whether a reduction can be made in the total number of monitoring stations within the Air Quality Monitoring Network is very important since in case of necessity, the devices at one group of stations having similar air pollution characteristics can be transferred to another zone. This would significantly decrease the capital investment and operational cost. Therefore, the objective of this study was grouping the monitoring stations that share similar air pollution characteristics by using the methods of principal component analysis (PCA) and fuzzy c– means (FCM). In addition, this study also enables determining the emission sources, evaluating the performances of the methods and examining the zone in terms of pollution. In the classification of monitoring stations, different groups were formed depending on both the method of analysis and the type of pollutants. As a result of PCA, 5 and 3 classes have been determined for SO2 and PM10, respectively. This shows that the number of monitoring stations can be decreased. When reduced classes were analyzed, it was observed that a clear distinction cannot be made considering the affected source type. During the implementation of the FCM method, in order to facilitate comparison with the PCA, the monitoring stations were classified into 5 and 3 groups for SO2 and PM10, respectively. When the results were analyzed, it was seen that the uncertainty in PCA was reduced. When the two methods are compared, FCM was found to provide more significant results than PCA. The evaluation in terms of pollution, the results of the study showed that PM10 exceeded the limit values at all the monitoring stations, and SO2 exceeded the limit values at only 3 of the 22 stations

Assessment of the New 2012 EULAR/ACR Clinical Classification Criteria for Polymyalgia Rheumatica: A Prospective Multicenter Study

WOS: 000380854200011PubMed ID: 26834222Objective. To assess the performance of the new 2012 provisional European League Against Rheumatism (EULAR)/ American College of Rheumatology (ACR) polymyalgia rheumatica (PMR) clinical classification criteria in discriminating PMR from other mimicking conditions compared with the previous 5 diagnostic criteria in a multicenter prospective study. Methods. Patients older than 50 years, presenting with new-onset bilateral shoulder pain with elevated acute-phase reactants (APR), were assessed for the fulfillment of the new and old classification/diagnostic criteria sets for PMR. At the end of the 1-year followup, 133 patients were diagnosed with PMR (expert opinion) and 142 with non-PMR conditions [69 rheumatoid arthritis (RA)]. Discriminating capacity, sensitivity, and specificity of the criteria sets were estimated. Results. Discriminating capacity of the new clinical criteria for PMR from non-PMR conditions and RA as estimated by area under the curve (AUC) were good with AUC of 0.736 and 0.781, respectively. The new criteria had a sensitivity of 89.5% and a specificity of 57.7% when tested against all non-PMR cases. When tested against all RA, seropositive RA, seronegative RA, and non-RA control patients, specificity changed to 66.7%, 100%, 20.7%, and 49.3%, respectively. Except for the Bird criteria, the 4 previous criteria had lower sensitivity and higher specificity (ranging from 83%-93%) compared with the new clinical criteria in discriminating PMR from all other controls. Conclusion. The new 2012 EULAR/ ACR clinical classification criteria for PMR is highly sensitive; however, its ability to discriminate PMR from other inflammatory/noninflammatory shoulder conditions, especially from seronegative RA, is not adequate. Imaging and other modifications such as cutoff values for APR might increase the specificity of the criteria