An important task in big data integration is to derive accurate data records from noisy and conflicting values collected from multiple sources. Most existing truth finding methods assume that the reliability is consistent on the whole data set, ignoring the fact that different attributes, objects and object groups may have different reliabilities even wrt the same source. These reliability differences are caused by the hardness differences in obtaining attribute values, non-uniform updates to objects and the differences in group privileges. This paper addresses the problem how to compute truths by effectively estimating the reliabilities of attributes, objects and object groups in a multi-source heterogeneous data environment. We first propose an optimization framework TFAR, its implementation and Lagrangian duality solution for Truth Finding by Attribute Reliability estimation. We then present a Bayesian probabilistic graphical model TFOR and an inference algorithm applying Collapsed Gibbs Sampling for Truth Finding by Object Reliability estimation. Finally we give an optimization framework TFGR and its implementation for Truth Finding by Group Reliability estimation. All these models lead to a more accurate estimation of the respective attribute, object and object group reliabilities, which in turn can achieve a better accuracy in inferring the truths. Experimental results on both real data and synthetic data show that our methods have better performance than the stateof-art truth discovery methods.
Intensive efforts have been conducted to realize the
reliable interfacial
joining of thermoelectric materials and electrode materials with low
interfacial contact resistance, which is an essential step to make
thermoelectric materials into thermoelectric devices for industrial
application. In this review, the roles of structural integrity, interdiffusion,
and contact resistance in long-term reliabilities of thermoelectric
modules are outlined first. Then interfacial reactions of near-room-temperature
Bi2Te3-based thermoelectric materials and various
electrode materials are reviewed comprehensively. We also summarized
the joining behavior of the mid-temperature PbTe-based thermoelectric
materials and commonly used electrode materials. Subsequently, for
other thermoelectric materials systems, i.e., SiGe, CoSb3, and Mg3Sb2, previous attempts to join with
some electrode materials are also recapitulated. Finally, some future
prospects to further improve the joint reliability in thermoelectric
device manufacturing are proposed. We believe that this review will
provide guidance for preparing thermoelectric devices and optimizing
thermoelectric device design.
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