Manifold clustering, which regards clusters as groups of points around compact manifolds, has been realized as a promising generalization of traditional clustering. A number of linear or nonlinear manifold clustering approaches have been developed recently. Although they have attained better performances than traditional clustering methods in many scenarios, most of these approaches suffer from...

Data envelopment analysis (DEA) is recognized as a powerful analytical research tool for performance evaluations by obtaining empirical estimates of relations between multiple inputs and multiple outputs. In order to further embody the hierarchical structures of numerous performance evaluation problems in the DEA framework, a generalized multiple layer DEA (MLDEA) model is proposed, and its lin...

A central decision-maker, the principal, employs performance evaluation criteria consistent with an organization’s overall goal/s to measure the effectiveness of the agents who execute decisions and implement strategies within a specified period. The dataset of performance criteria spanning the performance space will change over time to reflect the principal’s strategic modifications. This pape...

While various approaches to domain adaptation exist, the majority of them requires knowledge of the target domain, and additional data, preferably labeled. For a language like English, it is often feasible to match most of those conditions, but in low-resource languages, it presents a problem. We explore the situation when neither data nor other information about the target domain is available....

This article reports initial evidence of construct validity for a four-factor measure of attributions assessing the dimensions of controllability, stability, globality, and universality (the CSGU). In Study 1, using confirmatory factor analysis, factors were confirmed across least successful and most successful conditions. In Study 2, following less successful performances, correlations support...

This paper presents instrumental variable methods for identifying partial differential equation models of distributed parameter systems in presence of output measurement noise. Two instrumental variable-based techniques are proposed to handle this continuous-time model identification problem: a basic one using input-only instruments and a more sophisticated refined instrumental variable method....

BACKGROUND Existing literature showed improved swimming performances for swimmers wearing wetsuits competing under standardized conditions in races held in pools on short to middle distances. Data about the influence of wetsuits on swimming performances in long and ultra-long open-water swimming races are missing. It is unknown whether the benefit of wearing wetsuits is comparable in men and wo...

BACKGROUND Physical activity is a key component of exploration and development. Poor motor proficiency, by limiting participation in physical and social activities, can therefore contribute to poor psychological and social development. The current study examined the correlates of motor performance in a setting where no locally validated measures of motor skills previously existed. The developme...

Data envelopment analysis (DEA) is a technique for performance evaluation of peer decision making units (DMUs). The network DEA models study the internal structures of DMUs. Using two-stage network structures as an example, the current paper examines additive efficiency decomposition where the overall efficiency is defined as a weighted average of stage efficiencies and the weights are used to ...

A two-stage data envelopment analysis (DEA) model is created to provide valuable managerial insights when assessing the dual impacts of operating and business strategies for the Canadian life and health (L&H) insurance industry. This new model allows integration of the production performance and investment performance for the insurance companies and provides management overall performance evalu...