Airplane design; a textbook of airplane layout and stress analysis calculations with examples and problems.

"Complementary to ... ʻTechnical aerodynamics' by the same author."--Pref.

A generalized network formulation for aperture problems /

"AFCRL-TR-75-0589."

Geohydrology of the Antelope Valley Area, California and design for a ground-water-quality monitoring network /

Mode of access: Internet.

Multi-valued control problems and mixture density network

We have proposed a novel robust inversion-based neurocontroller that searches for the optimal control law by sampling from the estimated Gaussian distribution of the inverse plant model. However, for problems involving the prediction of continuous variables, a Gaussian model approximation provides only a very limited description of the properties of the inverse model. This is usually the case for problems in which the mapping to be learned is multi-valued or involves hysteritic transfer characteristics. This often arises in the solution of inverse plant models. In order to obtain a complete description of the inverse model, a more general multicomponent distributions must be modeled. In this paper we test whether our proposed sampling approach can be used when considering an arbitrary conditional probability distributions. These arbitrary distributions will be modeled by a mixture density network. Importance sampling provides a structured and principled approach to constrain the complexity of the search space for the ideal control law. The effectiveness of the importance sampling from an arbitrary conditional probability distribution will be demonstrated using a simple single input single output static nonlinear system with hysteretic characteristics in the inverse plant model.

Distributed processing, reconfigurable processes and active network

The fast spread of the Internet and the increasing demands of the service are leading to radical changes in the structure and management of underlying telecommunications systems. Active networks (ANs) offer the ability to program the network on a per-router, per-user, or even per-packet basis, thus promise greater flexibility than current networks. To make this new network paradigm of active network being widely accepted, a lot of issues need to be solved. Management of the active network is one of the challenges. This thesis investigates an adaptive management solution based on genetic algorithm (GA). The solution uses a distributed GA inspired by bacterium on the active nodes within an active network, to provide adaptive management for the network, especially the service provision problems associated with future network. The thesis also reviews the concepts, theories and technologies associated with the management solution. By exploring the implementation of these active nodes in hardware, this thesis demonstrates the possibility of implementing a GA based adaptive management in the real network that being used today. The concurrent programming language, Handel-C, is used for the description of the design system and a re-configurable computer platform based on a FPGA process element is used for the hardware implementation. The experiment results demonstrate both the availability of the hardware implementation and the efficiency of the proposed management solution.

Quality risk in global supply network

Purpose - The rise of recent product recalls reveals that manufacturing firms are particularly vulnerable to product quality and safety where goods and materials have been sourced globally. The purpose of this paper is to explore the issues of quality and safety problems in global supply networks, and introduce a supply chain risk management (SCRM) framework to reduce the quality risk. Design/methodology/approach - A conceptual SCRM framework for mitigating quality risk is developed. In addition, four SCRM treatment practices are proposed by consolidating the empirical literature in the operations management and supply chain management areas. The general feasibility was discussed based on literature. Findings - The research has identified the root causes of the recent product recalls and a series of product harm scandals ranging from automobiles to unsafe toys. Supply chains are extended by outsourcing and stretched by globalization, which greatly increase the complexity of supply networks and decrease the visibility in risk and operation processes. Originality/value - The paper identifies four SCRM practices, and proposes two distinct antecedents that can prompt the effectiveness of SCRM. © 2011 Emerald Group Publishing Limited. All rights reserved.

Neural network enhanced self tuning adaptive control application for non-linear control of dynamic systems

The main theme of research of this project concerns the study of neutral networks to control uncertain and non-linear control systems. This involves the control of continuous time, discrete time, hybrid and stochastic systems with input, state or output constraints by ensuring good performances. A great part of this project is devoted to the opening of frontiers between several mathematical and engineering approaches in order to tackle complex but very common non-linear control problems. The objectives are: 1. Design and develop procedures for neutral network enhanced self-tuning adaptive non-linear control systems; 2. To design, as a general procedure, neural network generalised minimum variance self-tuning controller for non-linear dynamic plants (Integration of neural network mapping with generalised minimum variance self-tuning controller strategies); 3. To develop a software package to evaluate control system performances using Matlab, Simulink and Neural Network toolbox. An adaptive control algorithm utilising a recurrent network as a model of a partial unknown non-linear plant with unmeasurable state is proposed. Appropriately, it appears that structured recurrent neural networks can provide conveniently parameterised dynamic models for many non-linear systems for use in adaptive control. Properties of static neural networks, which enabled successful design of stable adaptive control in the state feedback case, are also identified. A survey of the existing results is presented which puts them in a systematic framework showing their relation to classical self-tuning adaptive control application of neural control to a SISO/MIMO control. Simulation results demonstrate that the self-tuning design methods may be practically applicable to a reasonably large class of unknown linear and non-linear dynamic control systems.

A systematic approach to establish fundamental principles of computer applications packages design

This work attempts to create a systemic design framework for man-machine interfaces which is self consistent, compatible with other concepts, and applicable to real situations. This is tackled by examining the current architecture of computer applications packages. The treatment in the main is philosophical and theoretical and analyses the origins, assumptions and current practice of the design of applications packages. It proposes that the present form of packages is fundamentally contradictory to the notion of packaging itself. This is because as an indivisible ready-to-implement solution, current package architecture displays the following major disadvantages. First, it creates problems as a result of user-package interactions, in which the designer tries to mould all potential individual users, no matter how diverse they are, into one model. This is worsened by the minute provision, if any, of important properties such as flexibility, independence and impartiality. Second, it displays rigid structure that reduces the variety and/or multi-use of the component parts of such a package. Third, it dictates specific hardware and software configurations which probably results in reducing the number of degrees of freedom of its user. Fourth, it increases the dependence of its user upon its supplier through inadequate documentation and understanding of the package. Fifth, it tends to cause a degeneration of the expertise of design of the data processing practitioners. In view of this understanding an alternative methodological design framework which is both consistent with systems approach and the role of a package in its likely context is proposed. The proposition is based upon an extension of the identified concept of the hierarchy of holons* which facilitates the examination of the complex relationships of a package with its two principal environments. First, the user characteristics and his decision making practice and procedures; implying an examination of the user's M.I.S. network. Second, the software environment and its influence upon a package regarding support, control and operation of the package. The framework is built gradually as discussion advances around the central theme of a compatible M.I.S., software and model design. This leads to the formation of the alternative package architecture that is based upon the design of a number of independent, self-contained small parts. Such is believed to constitute the nucleus around which not only packages can be more effectively designed, but is also applicable to many man-machine systems design.

Network lifetime maximization with cross-layer design in wireless sensor networks

This paper investigates a cross-layer design approach for minimizing energy consumption and maximizing network lifetime (NL) of a multiple-source and single-sink (MSSS) WSN with energy constraints. The optimization problem for MSSS WSN can be formulated as a mixed integer convex optimization problem with the adoption of time division multiple access (TDMA) in medium access control (MAC) layer, and it becomes a convex problem by relaxing the integer constraint on time slots. Impacts of data rate, link access and routing are jointly taken into account in the optimization problem formulation. Both linear and planar network topologies are considered for NL maximization (NLM). With linear MSSS and planar single-source and single-sink (SSSS) topologies, we successfully use Karush-Kuhn-Tucker (KKT) optimality conditions to derive analytical expressions of the optimal NL when all nodes are exhausted simultaneously. The problem for planar MSSS topology is more complicated, and a decomposition and combination (D&C) approach is proposed to compute suboptimal solutions. An analytical expression of the suboptimal NL is derived for a small scale planar network. To deal with larger scale planar network, an iterative algorithm is proposed for the D&C approach. Numerical results show that the upper-bounds of the network lifetime obtained by our proposed optimization models are tight. Important insights into the NL and benefits of cross-layer design for WSN NLM are obtained.

Design and evaluation of a framework for cooperative and adaptive QoS control of DSRC network for road safety applications

Dedicated short-range communications (DSRC) are a promising vehicle communication technique for collaborative road safety applications (CSA). However, road safety applications require highly reliable and timely wireless communications, which present big challenges to DSRC based vehicle networks on effective and robust quality of services (QoS) provisioning due to the random channel access method applied in the DSRC technique. In this paper we examine the QoS control problem for CSA in the DSRC based vehicle networks and presented an overview of the research work towards the QoS control problem. After an analysis of the system application requirements and the DSRC vehicle network features, we propose a framework for cooperative and adaptive QoS control, which is believed to be a key for the success of DSRC on supporting effective collaborative road safety applications. A core design in the proposed QoS control framework is that network feedback and cross-layer design are employed to collaboratively achieve targeted QoS. A design example of cooperative and adaptive rate control scheme is implemented and evaluated, with objective of illustrating the key ideas in the framework. Simulation results demonstrate the effectiveness of proposed rate control schemes in providing highly available and reliable channel for emergency safety messages. © 2013 Wenyang Guan et al.

Design of a genetic algorithm for bi-objective flow shop scheduling problems with re-entrant jobs

This paper presents a simulated genetic algorithm (GA) model of scheduling the flow shop problem with re-entrant jobs. The objective of this research is to minimize the weighted tardiness and makespan. The proposed model considers that the jobs with non-identical due dates are processed on the machines in the same order. Furthermore, the re-entrant jobs are stochastic as only some jobs are required to reenter to the flow shop. The tardiness weight is adjusted once the jobs reenter to the shop. The performance of the proposed GA model is verified by a number of numerical experiments where the data come from the case company. The results show the proposed method has a higher order satisfaction rate than the current industrial practices.

Interface Engineering and Design: Adaptibility Problems

* The research work reviewed in this paper has been carried out in the context of the Russian Foundation for Basic Research funded project “Adaptable Intelligent Interfaces Research and Development for Distance Learning Systems”(grant N 02-01-81019). The authors wish to acknowledge the co-operation with the Byelorussian partners of this project.