On partial-information optimal singular control problem for mean-field stochastic differential equations driven by Teugels martingales measures

This paper is concerned with partial-information mixed optimal stochastic continuous–singular control problem for mean-field stochastic differential equation driven by Teugels martingales and an independent Brownian motion, where the Teugels martingales are a family of pairwise strongly orthonormal martingales associated with Lévy processes. The control variable has two components; the first being absolutely continuous, and the second singular. Partial-information necessary and sufficient conditions of optimal continuous–singular control for these mean-field models are investigated. As an illustration, this paper studies a partial-information linear quadratic control problem of mean-field type involving continuous–singular control.     

H∞ state estimation of generalised neural networks with interval time-varying delays

This paper focuses on studying the H_∞ state estimation of generalised neural networks with interval time-varying delays. The integral terms in the time derivative of the Lyapunov–Krasovskii functional are handled by the Jensen’s inequality, reciprocally convex combination approach and a new Wirtinger-based double integral inequality. A delay-dependent criterion is derived under which the estimation error system is globally asymptotically stable with H_∞ performance. The proposed conditions are represented by linear matrix inequalities. Optimal H_∞ norm bounds are obtained easily by solving convex problems in terms of linear matrix inequalities. The advantage of employing the proposed inequalities is illustrated by numerical examples.     

Asymptotic Stability of Cohen–Grossberg BAM Neutral Type Neural Networks with Distributed Time Varying Delays

This paper is concerned with the problem of asymptotic stability of neutral type Cohen–Grossberg BAM neural networks with discrete and distributed time-varying delays. By constructing a suitable Lyapunov–Krasovskii functional (LKF), reciprocal convex technique and Jensen’s inequality are used to delay-dependent conditions are established to analysis the asymptotic stability of Cohen–Grossberg BAM neural networks with discrete and distributed time-varying delays. These stability conditions are formulated as linear matrix inequalities (LMIs) which can be easily solved by various convex optimization algorithms. Finally numerical examples are given to illustrate the usefulness of our proposed method.     

Fuzzy based multi-criteria vertical handover decision modeling in heterogeneous wireless networks

Vertical handover gain significant importance due to the enhancements in mobility models by the Fourth Generation (4G) technologies. However, these enhancements are limited to specific scenarios and hence do not provide support for generic mobility. Similarly, various schemes are proposed based on these mobility models but most of them are suffered from the high packet loss, frequent handovers, too early and late handovers, inappropriate network selection, etc. To address these challenges, a generic vertical handover management scheme for heterogeneous wireless networks is proposed in this article. The proposed scheme works in three phases. In the first phase, a handover triggering approach is designed to identify the appropriate place for initiating handover based on the estimated coverage area of a WLAN access point or cellular base station. In the second phase, fuzzy rule based system is designed to eliminate the inappropriate networks before deciding an optimal network for handover. In the third phase, a network selection scheme is developed based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) decision mechanism. Various parameters such as delay, jitter, Bit Error Rate (BER), packet loss, communication cost, response time, and network load are considered for selecting an optimal network. The proposed scheme is tested in a mobility scenario with different speeds of a mobile node ranging from very low to very high. The simulation results are compared with the existing decision models used for network selection and handover triggering approaches. The proposed scheme outperforms these schemes in terms of energy consumption, handover delay and time, packet loss, good put, etc.     

Laminar convection in the annulus of a double-pipe with triangular fins

A steady and laminar convective flow has been numerically simulated in the fully-developed annular region of a finned double-pipe subjected to the constant heat flux boundary condition imposed at the inner-pipe wall. Finite element method has been employed in this study. Friction factor and Nusselt number have been studied as flow characteristics against variations in the ratio of radii of the inner and the outer pipes, the fin height, the fin half angle and the number of fins. The results show significant enhancement in the heat transfer rate in both the cases when sufficient pumping power is available and when it is not. The minimum and maximum increase in the product of friction factor and Reynolds number relative to the finless geometry is more than one time and more than 40 times respectively while gain in the relative value of Nusselt number lies in the range 1–177. This provides an evidence of more than four times enhancement in the heat transfer coefficient relative to that in the pressure loss as a result of extended fin surfaces.     

Dataflow Architectures for GALS

In Kahn process network (KPN), the processes (nodes) communicate by unbounded unidirectional FIFO channels (arcs), with the property of non-blocking writes and blocking reads on the channels. KPN provides a semantic model of computation, where a computation can be expressed as a set of asynchronously communicating processes. However, the unbounded FIFO based asynchrony is not realizable in practice and hence requires refinement in real hardware. In this work, we start with KPN as the model of computation for GALS, and discuss how different GALS architectures can be realized. We borrow some ideas from existing dataflow architectures for our GALS designs.     

Flexible and Autonomous Integrated System for Characterizing Metal Oxide Gas Sensor Response in Dynamic Environment

Characterization and calibration of gas sensor is a complex problem due to the dynamic behavior of gases and the limitations of current technology. This article reports a flexible, robust, and autonomous integrated system that is able to perform characterization on metal oxide-based gas sensors in dynamic environments. The system controls the concentration and flow of the relevant gases into the gas chamber and simultaneously measuring the sensor response. This feature allows the characterization of the sensor under continuous dynamic flow of gases similar to conditions on a robot or flow pipes. Several experiments have been performed on the system using hydrogen sulfide. The results provide information on the general characteristics of the sensor as well as its sensitivity. The noise levels were studied with different reference voltages. Overall, the results verify that the system is reliable and able to produce repeatable measurements.     

Fast attack detection using correlation and summarizing of security alerts in grid computing networks

Due to the extensive growth of grid computing networks, security is becoming a challenge. Usual solutions are not enough to prevent sophisticated attacks fabricated by multiple users especially when the number of nodes connected to the network is changing over the time. Attackers can use multiple nodes to launch DDoS attacks which generate a large amount of security alerts. On the one hand, this large number of security alerts degrades the overall performance of the network and creates instability in the operation of the security management solutions. On the other hand, they can help in camouflaging other real attacks. To address these issues, a?correlation mechanism is proposed which reduces the security alerts and continue detecting attacks in grid computing networks. To obtain the more accurate results, a?major portion of the experiments are performed by launching DDoS and Brute Force (BF) attacks in real grid environment, i.e., the Grid??5000 (G5K) network.     

Extended temperature–entropy (T–s) diagrams for aqueous lithium bromide absorption refrigeration cycles

Temperature–entropy (T–s) diagrams have the unique capability of being able to quantify processes in terms of both the first and second laws of thermodynamics. Although use of generalised T–s diagrams has been made to indicate or represent generalised absorption cycles, with the exception for NH₃/water systems, these diagrams have not been specifically tailored to scale to quantify LiBr/water systems. The main barrier for this is that the diagram needs to represent the necessary properties of both the refrigerant (water) and of the solution (LiBr/water). This paper describes the use of the T–s diagram of water extended with additional curves to represent real and ideal LiBr/water absorption cycles. An explanation is provided on several methods available, including details of the thermodynamic justification of the method that was used, to construct the extended diagrams. Finally, the extended T–s diagram is provided with the representation of a real single-effect LiBr/water absorption refrigeration cycle. This should prove to be a valuable tool for design and research engineers to study and optimise LiBr/water chillers.