There is a growing interest in cross-border medical care and its comparative advantages. In addition, medical care can be defined as a local assurance good. Little research is being carried out in this field. This paper discusses the individual considerations for medical treatment offered at home and abroad within a micro-economical framework. Specific assumptions as mistrust, monetary and non-...

Data envelopment analysis (DEA) is a method for estimating efficiency of decision making units (DMU).The method done by means of weighted output to input ratio with the weights being optimal virtual prices of such activities for all units. Cross efficiency evaluation has long been proposed as an alternative method for ranking DMUs. The major problem that reduced the usefulness of cross efficien...

Dialects of the same language can differ in the casual speech processes they allow; e.g., British English allows the insertion of [r] at word boundaries in sequences such as saw ice, while American English does not. In two speeded word recognition experiments, American listeners heard such British English sequences; in contrast to non-native listeners, they accurately perceived intended vowel-i...

Data envelopment analysis (DEA) is widely used in various practical problems as a general framework for efficiency-evaluation by containing the input-output data. With increasingly complex factors practice, portraying uncertainty necessary ensuring reasonableness of results. As probabilistic linguistic term set (PLTS) powerful tool depicting uncertain information comprehensively, we aim to prop...

The present study is an attempt toward evaluating the performance of portfolios and asset selectionusing cross-efficiency evaluation. Cross-efficiency evaluation is an effective way of ranking decisionmaking units (DMUs) in data envelopment analysis (DEA). Conventional DEA models assume nonnegativevalues for inputs and outputs. However, we know that unlike return and skewness, varianceis the on...

Recently, some authors proposed the use of symmetric weightsfor computing the elements of cross-efficiency matrix. In spite ofthe fact that the proposed method decreases the number of zeroweights, a large number of zero weights may still exist among inputand output symmetric weights. To decrease the number of input andoutput symmetric weights, this paper improves the proposed secondarygoal mode...

Consider two multi-dimensional digital signals, each with Ns samples. For some number of lags Nl Ns, the cost of computing a single cross-correlation of these two signals is proportional to Ns ×Nl. By exploiting several properties of Gaussian windows, we can compute Ns local cross-correlations, again with computational cost proportional to Ns×Nl. Here, local means the cross-correlation of signa...

Cross-efficiency evaluation is an effective way of ranking decision making units (DMUs) in data envelopment analysis (DEA). Existing approaches for cross-efficiency evaluation are mainly focused on the calculation of cross-efficiency matrix, but pay little attention to the aggregation of the efficiencies in the cross-efficiency matrix. The most widely used approach is to aggregate the efficienc...

Extended common-image-point (CIP) gathers can be constructed using wave-equation migration by preserving into the output image the non-zero spaceand timelags of the cross-correlation between the source and receiver wavefields. Correct wavefield reconstruction leads to focused events in the extended CIPs, while incorrect reconstruction leads to de-focused events that can be used for velocity mod...

Latent feature models are attractive for image modeling, since images generally contain multiple objects. However, many latent feature models ignore that objects can appear at different locations or require pre-segmentation of images. While the transformed Indian buffet process (tIBP) provides a method for modeling transformation-invariant features in unsegmented binary images, its current form...