Performance evaluation of three-level Z-source inverters under semiconductor-failure conditions

This paper evaluates and proposes various compensation methods for three-level Z-source inverters under semiconductor-failure conditions. Unlike the fault-tolerant techniques used in traditional three-level inverters, where either an extra phase-leg or collective switching states are used, the proposed methods for three-level Z-source inverters simply reconfigure their relevant gating signals so as to ride-through the failed semiconductor conditions smoothly without any significant decrease in their ac-output quality and amplitude. These features are partly attributed to the inherent boost characteristics of a Z-source inverter, in addition to its usual voltage-buck operation. By focusing on specific types of three-level Z-source inverters, it can also be shown that, for the dual Z-source inverters, a unique feature accompanying it is its extra ability to force common-mode voltage to zero even under semiconductor-failure conditions. For verifying these described performance features, PLECS simulation and experimental testing were performed with some results captured and shown in a later section for visual confirmation.

A distributed services based conference planner application using software agents, grid services and web services

This demonstration highlights the applications of our research work i.e. second generation (Scalable Fault Tolerant Agent Grooming Environment - SAGE) Multi Agent System, Integration of Software Agents and Grid Computing and Autonomous Agent Architecture in the Agent Platform. It is a conference planner application that uses collaborative effort of services deployed geographically wide in different technologies i.e. Software Agents, Grid computing and Web services to perform useful tasks as required. Copyright 2005 ACM.

An efficient and light-weight multi-tasking model to achieve Intra-Agent concurrency for SAGE

Multi-agent systems implicate a high degree of concurrency at both the Inter- and Intra-Agent levels. Scalable, fault tolerant, Agent Grooming Environment (SAGE), the second generation, FIPA compliant MAS requires a built in mechanism to achieve both the Inter- and Intra-Agent concurrency. This paper dilates upon an attempt to provide a reliable, efficient and light-weight solution to provide intra-agent concurrency with-in the internal agent architecture of SAGE. It addresses the issues related to using the JAVA threading model to provide this level of concurrency to the agent and provides an alternative approach that is based on an eventdriven, concurrent and user-scalable multi-tasking model for the agent's internal model. The findings of this paper show that our proposed approach is suitable for providing an efficient and lightweight concurrent task model for SA GE and considerably outweighs the performance of multithreaded tasking model based on JAVA in terms of throughput and efficiency. This has been illustrated using the practical implementation and evaluation of both models. © 2004 IEEE.

A hybrid agent architecture for modeling autonomous agents in SAGE

This paper highlights the Hybrid agent construction model being developed that allows the description and development of autonomous agents in SAGE (Scalable, fault Tolerant Agent Grooming Environment) - a second generation FIPA-Compliant Multi-Agent system. We aim to provide the programmer with a generic and well defined agent architecture enabling the development of sophisticated agents on SAGE, possessing the desired properties of autonomous agents - reactivity, pro-activity, social ability and knowledge based reasoning. © Springer-Verlag Berlin Heidelberg 2005.

Performance modulation of α-MnO2 nanowires by crystal facet engineering

Modulation of material physical and chemical properties through selective surface engineering is currently one of the most active research fields, aimed at optimizing functional performance for applications. The activity of exposed crystal planes determines the catalytic, sensory, photocatalytic, and electrochemical behavior of a material. In the research on nanomagnets, it opens up new perspectives in the fields of nanoelectronics, spintronics, and quantum computation. Herein, we demonstrate controllable magnetic modulation of α-MnO 2 nanowires, which displayed surface ferromagnetism or antiferromagnetism, depending on the exposed plane. First-principles density functional theory calculations confirm that both Mn- and O-terminated α-MnO2(1 1 0) surfaces exhibit ferromagnetic ordering. The investigation of surface-controlled magnetic particles will lead to significant progress in our fundamental understanding of functional aspects of magnetism on the nanoscale, facilitating rational design of nanomagnets. Moreover, we approved that the facet engineering pave the way on designing semiconductors possessing unique properties for novel energy applications, owing to that the bandgap and the electronic transport of the semiconductor can be tailored via exposed surface modulations.

The case for quantum key distribution

Quantum key distribution (QKD) promises secure key agreement by using quantum mechanical systems. We argue that QKD will be an important part of future cryptographic infrastructures. It can provide long-term confidentiality for encrypted information without reliance on computational assumptions. Although QKD still requires authentication to prevent man-in-the-middle attacks, it can make use of either information-theoretically secure symmetric key authentication or computationally secure public key authentication: even when using public key authentication, we argue that QKD still offers stronger security than classical key agreement.

Fault diagnosis of induction motor based on decision trees and adaptive neuro-fuzzy inference

This paper presents a fault diagnosis method based on adaptive neuro-fuzzy inference system (ANFIS) in combination with decision trees. Classification and regression tree (CART) which is one of the decision tree methods is used as a feature selection procedure to select pertinent features from data set. The crisp rules obtained from the decision tree are then converted to fuzzy if-then rules that are employed to identify the structure of ANFIS classifier. The hybrid of back-propagation and least squares algorithm are utilized to tune the parameters of the membership functions. In order to evaluate the proposed algorithm, the data sets obtained from vibration signals and current signals of the induction motors are used. The results indicate that the CART–ANFIS model has potential for fault diagnosis of induction motors.

RCA method for fault diagnosis in digital substations of power systems

The authors present a Cause-Effect fault diagnosis model, which utilises the Root Cause Analysis approach and takes into account the technical features of a digital substation. The Dempster/Shafer evidence theory is used to integrate different types of fault information in the diagnosis model so as to implement a hierarchical, systematic and comprehensive diagnosis based on the logic relationship between the parent and child nodes such as transformer/circuit-breaker/transmission-line, and between the root and child causes. A real fault scenario is investigated in the case study to demonstrate the developed approach in diagnosing malfunction of protective relays and/or circuit breakers, miss or false alarms, and other commonly encountered faults at a modern digital substation.