The theory of Human Plausible Reasoning (HPR) is an attempt by Collins and Michalski to explain how people answer questions when they are uncertain. The theory consists of a set of patterns and a set of inferences which could be applied on those patterns. This paper, investigates the application of HPR theory to the domain of cross language filtering. Our approach combines Natural Language Processing with HPR. The documents and topics are partially represented by automatically extracted concepts, logical terms and logical statements in a language neutral knowledge base. Reasoning provides the evidence of relevance. We have conducted hundreds of experiments especially with the depth of the reasoning, evidence combination and topic selection methods. The results show that HPR contributes to the overall performance by introducing new terms for topics. Also the number of inference paths from a document to a topic is an indication of its relevance.

Improving the performance of distribution networks is a primary target for power system operators. Besides, energy resource limitations and cost-effective distribution of electricity to the consumers encourage engineers, distribution system operators, and researchers to increase the efficiency of electric power distribution systems. Fortunately, many technologies can effectively make such improvements. Active and reactive power compensators such as distributed generators (DGs) and shunt capacitor banks (SCBs) are examples of compensators that can effectively make such improvements in modern radial distribution systems (RDSs), in addition to using recent techniques such as energy storage technologies. Voltage regulators (VRs) can also help these compensators function better in a much more effective techno-economic manner in RDSs, enhance voltage profiles and load stability, and reduce voltage deviations from acceptable values. Unfortunately, rising project investment may result if uneconomic facilities or expensive technologies are used to reduce electric losses significantly. Therefore, economic considerations related to the installed equipment in the networks should be considered. In this regard, the well-known whale optimization algorithm (WOA) is applied in this work to allocate DGs, SCBs, and VRs in a realistic 37-bus distribution system to minimize power losses while conforming with several linear and nonlinear constraints. A cost-benefit analysis of the optimization problem is made in terms of – investment and running costs of the compensators used; saving gained from the power loss reduction, and benefits from decreasing the power to be purchased from the grid; reducing voltage deviations and overloading; and enhancing voltage stability (VS). Three loading scenarios are considered in this work – light, shoulder, and peak levels of load demand. The numerical findings obtained show a noteworthy techno-economic improvement of the quality of power (QoP) performance level of the RDS and approve the efficiency and economic benefits of the proposed solutions compared to other solutions in the literature.