Conditional global entanglement in a Kosterlitz-Thouless quantum phase transition

Entanglement is known as an important indicator for characterizing different types of quantum phase transitions (QPTs), however it faces some challenges in the Kosterlitz-Thouless (KT) phase transitions due to an essential singularity which cannot be identified in finite derivatives of the ground state energy. In this paper, we consider global entanglement (GE) in a KT phase transition and show that while it does not indicate any clear signature of the phase transition, the conditional version of GE is a good indicator with strong signatures of the KT transition. In particular, we study a deformed version of the $Z_d$ Kitaev model which has an intermediate KT phase which separates a $Z_d$ topological phase from a magnetized phase at two different KT transition points. Using a mapping to the classical $d$-state clock model, we consider GE and the generalized GE and show that they do not provide a reliable indicator of transition points. However, their difference called conditional global entanglement (Q) shows a peak at the first KT transition point. Additionally, we show that it can characterize various phases of the model as it behaves substantially different in each phase. We therefore conclude that Q is a useful measure that can characterize various phases of KT QPTs as well as their related critical points.Comment: 8 pages, 4 figure

Time-based fault location method for LVdistributionsystems

© 2015, Springer-Verlag Berlin Heidelberg. Due to the utilization of fundamental frequency, current impedance-based fault location methods are able to locate only permanent and linear faults. The duration of the arc in low and medium voltage systems can be as short as a quarter of a cycle. This period, which is normal for intermittent faults, is insufficient for fundamental frequency-based fault location algorithms. Therefore, available methods are not applicable for intermittent arcing fault location. In this paper, the time-based method previously proposed by the authors has been developed to locate short duration faults in LV distribution systems. The advantage of the proposed method over available methods is its capability for locating faults using fewer samples, which enable the user to locate both arcing faults as well as normal faults in the network. The main characteristics of an arcing fault, i.e., non-linearity and short duration, have been addressed in the proposed algorithms methodology. Various characteristics of a LV distribution system (i.e., heterogeneity, unbalanced load and line, etc.) have been taken into account in the current enhanced algorithm. The validity of the devised algorithm is studied within PSCAD-EMTDC environment and the obtained results show a good accuracy

Effects of drying and salt extraction of Moringa oleifera on its coagulation of high turbidity water

Moringa oleifera (M.O.) has been used as a natural coagulant in water treatment. The present study aims to determine the effect of drying M.O. seed powder that has been extracted with salt (NaNO3) on the coagulation of synthetic (kaolin) water of 200±5 NTU. The optimum quantity of M.O. was 5 mg for both 10 and 200 g/l concentrations of the non-spray-dried salt-extracted M.O. (MOC-SC) solutions, with turbidity removal of 87%. This maximum turbidity removal was achieved with 1 M and 0.5 M of NaNO3 salt in the former and latter concentrations, respectively. The spray-dried M.O. (MOC-SC-SD) solutions exhibited better maximum turbidity removal of more than 95%, which also occurred at 5 mg of M.O., for both concentrations. Finally, the duration of storage of MOC-SC-SD did not affect its performance in the removal of turbidity

Application of Multi-Agent Technology to Fault Diagnosis of Power Distribution Systems

When a fault occurs in a power system, the protective relays detect the fault and trip appropriate circuit breakers, which isolate the affected equipment from the rest of the power system. Fault diagnosis of power systems is the process of identifying faulty components and/or sections by analysing observable symptoms (telemetry messages). As the domain is characterised by dynamic situations, extensive telemetering, complex operations, and distribution of lines and substations over a large geographical area, it is difficult to tackle fault diagnosis problems through the strength and capability of a single intelligent system. This paper describes an experimental multi-agent system developed for and aimed at a computer-supported fault diagnosis in electricity distribution networks. The system is based on a hierarchy of five agents that cooperate with each other to diagnose a fault. A set of detailed case studies is presented, and the results obtained suggest that an agent-based approach is very efficient and has a good potential for real-time application. © 2005, IGI Global. All rights reserved