Gamma-ray Emission from Millisecond Pulsars - An Outergap Perspective

In this review paper we explain the following gamma-ray emission features from the millisecond pulsars. (1)Why is the dipolar field of millisecond pulsars so weak but the magnetic pair creation process may still be able to control the size of the outergap? (2)A sub-GeV pulse component could occur in the vicinity of the radio pulse of millisecond pulsars. (3)Orbital modulated gamma-rays should exist in the black widow systems for large viewing angle.Comment: This is the proceeding paper of 3rd Fermi Asian Network Workshop and will be published by Journal of the Korea Space Science Societ

Dynamic response and stability of a gas-lubricated Rayleigh-step pad

The quasi-static, pressure characteristics of a gas-lubricated thrust bearing with shrouded, Rayleigh-step pads are determined for a time-varying film thickness. The axial response of the thrust bearing to an axial forcing function or an axial rotor disturbance is investigated by treating the gas film as a spring having nonlinear restoring and damping forces. These forces are related to the film thickness by a power relation. The nonlinear equation of motion in the axial mode is solved by the Ritz-Galerkin method as well as the direct, numerical integration. Results of the nonlinear response by both methods are compared with the response based on the linearized equation. Further, the gas-film instability of an infinitely wide Rayleigh step thrust pad is determined by solving the transient Reynolds equation coupled with the equation of the motion of the pad. Results show that the Rayleigh-step geometry is very stable for bearing number A up to 50. The stability threshold is shown to exist only for ultrahigh values of Lambda equal to or greater than 100, where the stability can be achieved by making the mass heavier than the critical mass

Genetic algorithms with elitism-based immigrants for dynamic shortest path problem in mobile ad hoc networks

This article is posted here with permission from the IEEE - Copyright @ 2009 IEEEIn recent years, the static shortest path (SP) problem has been well addressed using intelligent optimization techniques, e.g., artificial neural networks (ANNs), genetic algorithms (GAs), particle swarm optimization (PSO), etc. However, with the advancement in wireless communications, more and more mobile wireless networks appear, e.g., mobile ad hoc network (MANET), wireless sensor network (WSN), etc. One of the most important characteristics in mobile wireless networks is the topology dynamics, that is, the network topology changes over time due to energy conservation or node mobility. Therefore, the SP problem turns out to be a dynamic optimization problem (DOP) in MANETs. In this paper, we propose to use elitism-based immigrants GA (EIGA) to solve the dynamic SP problem in MANETs. We consider MANETs as target systems because they represent new generation wireless networks. The experimental results show that the EIGA can quickly adapt to the environmental changes (i.e., the network topology change) and produce good solutions after each change.This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/1

Joint multicast routing and channel assignment in multiradio multichannel wireless mesh networks using tabu search

Copyright @ 2009 IEEE Computer SocietyThis paper proposes a tabu search (TS) based optimization approach to search a minimum-interference multicast tree which satisfies the end-to-end delay constraint and optimizes the usage of the scarce radio network resource in wireless mesh networks. The path-oriented encoding method is adopted and each candidate solution is represented by a tree data structure (i.e., a set of paths). Since we expect the multicast trees on which the minimum-interference channel assignment can be produced, a fitness function that returns the total channel conflict is devised. The techniques for controlling the tabu search procedure are well developed. A simple yet effective channel assignment algorithm is proposed to reduce the channel conflict. Simulation results show that the proposed TS multicast algorithm can produce the multicast trees which have better performance in terms of both the total channel conflict and the tree cost than that of a well known multicast algorithm in wireless mesh networks.This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/1

A genetic-inspired joint multicast routing and channel assignment algorithm in wireless mesh networks

Copyright @ 2008 IEEEThis paper proposes a genetic algorithm (GA) based optimization approach to search a minimum-interference multicast tree which satis¯es the end-to-end delay constraint and optimizes the usage of the scarce radio network resource in wireless mesh networks. The path-oriented en- coding method is used and each chromosome is represented by a tree data structure (i.e., a set of paths). Since we expect the multicast trees on which the minimum-interference channel assignment can be produced, a fitness function that returns the total channel conflict is devised. Crossover and mutation are well designed to adapt to the tree structure. A simple yet effective channel assignment algorithm is proposed to reduce the channel conflict. Simulation results show that the proposed GA based multicast algorithm achieves better performance in terms of both the total channel conflict and the tree cost than that of a well known algorithm

Low carbon manufacturing: Characterization, theoretical models and implementation

Today, the rising of carbon dioxide (CO2) emissions is becoming the crucial factor for global warming especially in industrial sectors. Therefore, the research to reduce carbon intensity and enhance resources utilization in manufacturing industry is starting to be a timely topic. Low carbon manufacturing (LCM) can be referred to the manufacturing process that produces low carbon emissions intensity and uses energy and resources efficiently and effectively during the process as well. In this paper, the concepts of LCM are discussed and the LCM associated theoretical models, characterization and implementation perspective explored. The paper is structured in four parts. Firstly, the conception of low carbon manufacturing is critically reviewed then the characterization of low carbon manufacturing is discussed and formulated. Third part, the theoretical models are developed with initial models by using the theory from supply chain modeling and linear programming solutions (LP). The models show the relationship of resource utilizations and related variables for LCM in two levels: shop-floor and extended supply chain. Finally, the pilot implementations of LCM are discussed with two approaches: desktop or micro machines and devolved manufacturing. The paper is concluded with further discussions on the potential and application of LCM for manufacturing industry

Genetic algorithms with elitism-based immigrants for dynamic load balanced clustering problem in mobile ad hoc networks

This article is posted here with permission of IEEE - Copyright @ 2011 IEEEIn recent years, the static shortest path (SP) problem has been well addressed using intelligent optimization techniques, e.g., artificial neural networks, genetic algorithms (GAs), particle swarm optimization, etc. However, with the advancement in wireless communications, more and more mobile wireless networks appear, e.g., mobile networks [mobile ad hoc networks (MANETs)], wireless sensor networks, etc. One of the most important characteristics in mobile wireless networks is the topology dynamics, i.e., the network topology changes over time due to energy conservation or node mobility. Therefore, the SP routing problem in MANETs turns out to be a dynamic optimization problem. In this paper, we propose to use GAs with immigrants and memory schemes to solve the dynamic SP routing problem in MANETs. We consider MANETs as target systems because they represent new-generation wireless networks. The experimental results show that these immigrants and memory-based GAs can quickly adapt to environmental changes (i.e., the network topology changes) and produce high-quality solutions after each change.This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/1 and Grant EP/E060722/2