In Supply Chain Management (SCM), strengthening partnerships with suppliers is a significant factor for enhancing competitiveness. Hence, firms increasingly emphasize supplier evaluation processes. Supplier evaluation systems are basically developed in terms of criteria such as quality, cost, delivery, and flexibility. Because there are many variables to be analyzed, this process becomes hard t...

Importance of environmental efficiency of electric power industry stems from high demand for energy combined with global warming concerns. It is especially essential for the world largest economies like that of the United States. The paper introduces a Data Envelopment Analysis (DEA) model of environmental efficiency using indicators of fossil fuels utilization, emissions rate, and electric pow...

BACKGROUND The Dog erythrocyte antigen (DEA) 1 blood group system was thought to contain types DEA 1.1 and 1.2 (and possibly 1.3 [A3]). However, DEA 1.2+ dogs are very rare and newer typing methods reveal varying degrees of DEA 1 positivity. OBJECTIVES To assess if variation in DEA 1 positivity is because of quantitative differences in surface antigen expression. To determine expression patte...

Keywords: Data envelopment analysis (DEA) Common weights analysis (CWA) Ranking The ideal line The special line a b s t r a c t Conventional data envelopment analysis (DEA) assists decision makers in distinguishing between efficient and inefficient decision making units (DMUs) in a homogeneous group. However, DEA does not provide more information about the efficient DMUs. In this research, the ...

Data envelopment analysis (DEA) is a method for measuring the efficiency of peer decision making units (DMUs). Recently network DEA models been developed to examine the efficiency of DMUs with internal structures. The internal network structures range from a simple two-stage process to a complex system where multiple divisions are linked together with intermediate measures. In general, there ar...

A hierarchical framework is proposed to address the issues of modeling different type of words in keyword spotting (KWS). Keyword models are built at various levels according to the availability of training set resources for each individual word. The proposed approach improves the performance of KWS even when no training speech is available for the keywords. It also suggests an easier way to co...

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