Data envelopment analysis (DEA), based on mathematical programming techniques, is a popular method for assessing the relative efficiency of various decision-making units (DMUs). Efficient DEA computations need to circumvent intensive time-consuming calculations. This paper indicates that the “corner points” in single input and single output scatter plot has extreme efficiency with regard to the...

The purpose of the present experiments was to test the hypothesis that diethanolamine (DEA), an alkanolamine shown to be hepatocarcinogenic in mice, induces hepatic choline deficiency and to determine whether altered choline homeostasis was causally related to the carcinogenic outcome. To examine this hypothesis, the biochemical and histopathological changes in male B6C3F1 mice made choline def...

The study aim was to establish the prevalence of DEA 1, the most immunogenic and clinically important blood group in canine blood transfusion, in 7,414 dogs from Italy. The potential sensitization risk following a first transfusion and the acute reaction risk following a second transfusion given without a cross-matching and blood typing test were also calculated. Dogs tested were purebred (4,79...

OBJECTIVES The purpose of this research was to develop a simultaneous determination method for monoethanol-amine (MEA) and diethanolamine (DEA) in workplace air for risk assessment. METHODS The characteristics of the proposed method, such as recovery, quantitation limit, reproducibility and storage stability of the samples, were examined. RESULTS An air sampling cassette containing two sulf...

Amiodarone (AMD) is a benzofurane derivative with class III antiarrhythmic activity that is effective in controlling intractable cardiac arrhythmias. One of the most common and serious drug interactions in clinical practice is the interaction between digoxin and an antiarrhythmic agent. It has been reported that AMD and N-monodesethylamiodarone (DEA), the active metabolite of AMD, inhibit the P...

Life-cycle (LC) approaches play a significant role in energy policy making to determine the environmental impacts associated with the choice of energy source. Data envelopment analysis (DEA) can be combined with LC approaches to provide quantitative benchmarks that orientate the performance of energy systems towards environmental sustainability, with different implications depending on the sele...

The changing economic conditions have challenged many organizations to search for more efficient and effective ways to manage their supply chain. During recent years supplier selection decisions have received considerable attention in the supply chain management (SCM) literature. There are four major decisions that are related to the supplier selection process: what product or services to order...

DEA (Deta Envelopment Analysis) is a non-parametric technique for measuring the efficiency of DMUs (Decision Making Units)with common inputs and outputs [2,5]. viewpoint for each DMU because of taking a maximum ratio. During recent years, the issue of sensitivity and stability of data envelopment analysis results has been extensively studied. The first DEA sensitivity analysis paper by Charnes ...

Data envelopment analysis (DEA) is a methodology for measuring the relative efficiencies of a set of decision making units (DMUs) that use multiple inputs to produce multiple outputs. Crisp input and output data are fundamentally indispensable in conventional DEA. However, the observed values of the input and output data in real-world problems are sometimes imprecise or vague. Many researchers ...

Nowadays, data envelopment analysis (DEA) is a well-established non-parametric methodology for performance evaluation and benchmarking. DEA has witnessed a widespread use in many application areas since the publication of the seminal paper by Charnes, Cooper and Rhodes in 1978. However, to the best of our knowledge, no published work formally addressed out-of-sample evaluation in DEA. In this p...