Supplier selection in risk consideration: a fuzzy based topsis approach

Supplier selection, the process of finding the right suppliers who are able to provide the buyer with the right quality products and/or services at the right price, at the right time and in the right quantities, is one of the most critical activities for establishing an effective supply chain. In classical Multi-Criteria Decision Making (MCDM) methods, the ratings and the weights of the criteria are known precisely. Owning to vagueness of the decision data, the crisp data are inadequate for real-life situations. Since human judgments including preferences are often vague and cannot be expressed by exact numerical values, the application of fuzzy concepts in decision making is deemed to be relevant. On the other hand, it is a hard problem since supplier selection is typically a MCDM problem involving several conflicting criteria on which decision maker’s knowledge is usually vague and imprecise. In the present work, a risk-based suppliers’ evaluation module is proposed. Linguistic values are used to assess the ratings and weights for the risk based supplier selection factors. These linguistic ratings can be expressed in triangular fuzzy numbers. Then, a hierarchy MCDM model based on fuzzy-sets theory is proposed to deal with the supplier selection problems in the supply chain system. According to the concept of the fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), a closeness coefficient is defined to determine the ranking order of all suppliers by calculating the both fuzzy positive-ideal solution and fuzzy negative-ideal solution, simultaneously. Empirical data have been analysed and results obtained thereof, have been reported to exhibit application potential of the decision-support systems in appropriate situation

The decision tree approach to classification

A class of multistage decision tree classifiers is proposed and studied relative to the classification of multispectral remotely sensed data. The decision tree classifiers are shown to have the potential for improving both the classification accuracy and the computation efficiency. Dimensionality in pattern recognition is discussed and two theorems on the lower bound of logic computation for multiclass classification are derived. The automatic or optimization approach is emphasized. Experimental results on real data are reported, which clearly demonstrate the usefulness of decision tree classifiers

Pixel labeling by supervised probabilistic relaxation

There are no author-identified significant results in this report

Processing techniques development, volume 3. Part 2: Data preprocessing and information extraction techniques

There are no author-identified significant results in this report

Implementation of ILLIAC 4 algorithms for multispectral image interpretation

Research has focused on the design and partial implementation of a comprehensive ILLIAC software system for computer-assisted interpretation of multispectral earth resources data such as that now collected by the Earth Resources Technology Satellite. Research suggests generally that the ILLIAC 4 should be as much as two orders of magnitude more cost effective than serial processing computers for digital interpretation of ERTS imagery via multivariate statistical classification techniques. The potential of the ARPA Network as a mechanism for interfacing geographically-dispersed users to an ILLIAC 4 image processing facility is discussed

ECHO user's guide

There are no author-identified significant results in this report

Training and orthotic effects related to functional electrical stimulation of the peroneal nerve in stroke.

OBJECTIVE: To examine the evidence for a training effect on the lower limb of functional electrical stimulation. DESIGN: Cohort study. PATIENTS: A total of 133 patients >6 months post-stroke. METHODS: Training and orthotic effects were determined from walking speed over 10 m, associated minimal and substantial clinically important differences (i.e. >0.05 and >0.10 m/s), and Functional Ambulation Category (FAC), ranging from household walking to independent walking in the community. RESULTS: An overall significant (p < 0.01) training effect was found that was not a clinically important difference (0.02 m/s); however, "community" FAC (≥ 0.8 m/s) and "most limited community walkers" FAC (0.4-0.58 m/s), but not "household walkers" (< 0.4 m/s), benefitted from a clinically important difference. A highly significant (p< 0.001), substantial clinically important orthotic effect (0.10 m/s) was found. In terms of overall improvement of one or more FACs, 23% achieved this due to a training effect, compared with 43% due to an orthotic effect. CONCLUSION: The findings suggest that functional electrical stimulation provides a training effect in those who are less impaired. Further work, which optimizes the use of the device for restoration of function, rather than as an orthotic device, will provide greater clarity on the effectiveness of functional electrical stimulation for eliciting a training effect

Quality of life and cost effectiveness following the use of Functional Electrical Stimulation (FES) of the peroneal nerve for people with multiple sclerosis

There is a large gap in quality of life for people with MS and the general population. FES is an effective intervention for dropped foot reducing falls by 72% (1), with a mean usage of 4.9 years (2). Improving health related quality of life and cost effectiveness are a priority for the national health system in the UK, who have set a cost effectiveness threshold of £20,000(€24,218) per Quality Adjusted Life Year (QALY) under which interventions will be considered. Method: 45 people with multiple sclerosis (mean age 53, range 40-70) and foot drop completed the EQ-5D-5L (Euroqol) quality of life questionnaire before and after using FES for 20 weeks. Index values were calculated using the latest available value set and checked with the crosswalk value set (3). QALY gain was calculated by multiplying the utility value by the average length of time of FES use, discounted at 3.5% per year. The mean cost minus the expected cost saving due to falls prevention was divided by the QALY gain to give the mean net cost per QALY. Results: The mean index value before treatment (0.542) was highly significant compared to after treatment (0.656) (t=-4.68, p< 0.001), providing a utility value of 0.114 which works out to 0.542 when extrapolated to 4.9 years. The cost of providing FES for 4.9 years is £3095(€3,742)(1), giving a cost per QALY of £5,705(€6,901). However, it is estimated that the reduction of falls may result in a cost saving of £375(€454) per year, bringing the net cost to £1,256(€1,519) and cost per QALY to £2,316(€2,801). Conclusion: These preliminary results must be treated with caution as the data used was taken from three different studies. Nevertheless the analysis indicates that FES is associated with improved health related quality of life and is well within cost effectiveness thresholds