International evaluation of current and future requirements for environmental engineering education

The field of environmental engineering is developing as a result of changing environmental requirements. In response, environmental engineering education (E3) needs to ensure that it provides students with the necessary tools to address these challenges. In this paper the current status and future development of E3 is evaluated based on a questionnaire sent to universities and potential employers of E3 graduates. With increasing demands on environmental quality, the complexity of environmental engineering problems to be solved can be expected to increase. To find solutions environmental engineers will need to work in interdisciplinary teams. Based on the questionnaire there was a broad agreement that the best way to prepare students for these future challenges is to provide them with a fundamental education in basic sciences and related engineering fields. Many exciting developments in the environmental engineering profession will be located at the interface between engineering, science, and society. Aspects of all three areas need to be included in E3 and the student needs to be exposed to the tensions associated with linking the three.

A systems and cybernetic perspective on complex problem solving

This thesis is concerned with Organisational Problem Solving. The work reflects the complexities of organisational problem situations and the eclectic approach that has been necessary to gain an understanding of the processes involved. The thesis is structured into three main parts. Part I describes the author's understanding of problems and suitable approaches. Chapter 2 identifies the Transcendental Realist (TR) view of science (Harre 1970, Bhaskar 1975) as the best general framework for identifying suitable approaches to complex organisational problems. Chapter 3 discusses the relationship between Checkland's methodology (1972) and TR. The need to generate iconic (explanatory) models of the problem situation is identified and the ability of viable system modelling to supplement the modelling stage of the methodology is explored in Chapter 4. Chapter 5 builds further on the methodology to produce an original iconic model of the methodological process. The model characterises the mechanisms of organisational problem situations as well as desirable procedural steps. The Weltanschauungen (W's) or "world views" of key actors is recognised as central to the mechanisms involved. Part II describes the experience which prompted the theoretical investigation. Chapter 6 describes the first year of the project. The success of this stage is attributed to the predominance of a single W. Chapter 7 describes the changes in the organisation which made the remaining phase of the project difficult. These difficulties are attributed to a failure to recognise the importance of differing W's. Part III revisits the theoretical and organisational issues. Chapter 8 identifies a range of techniques embodying W's which are compatible with .the framework of Part I and which might usefully supplement it. Chapter 9 characterises possible W's in the sponsoring organisation. Throughout the work, an attempt 1s made to reflect the process as well as the product of the author's leaving.

Using the Simulation Modeling Methods for the Designing Real-Time Integrated Expert Systems

Certain theoretical and methodological problems of designing real-time dynamical expert systems, which belong to the class of the most complex integrated expert systems, are discussed. Primary attention is given to the problems of designing subsystems for modeling the external environment in the case where the environment is represented by complex engineering systems. A specific approach to designing simulation models for complex engineering systems is proposed and examples of the application of this approach based on the G2 (Gensym Corp.) tool system are described.

A domain decomposition based algorithm for non-linear 2D inverse heat conduction problems

Inverse heat conduction problems (IHCPs) appear in many important scientific and technological fields. Hence analysis, design, implementation and testing of inverse algorithms are also of great scientific and technological interest. The numerical simulation of 2-D and –D inverse (or even direct) problems involves a considerable amount of computation. Therefore, the investigation and exploitation of parallel properties of such algorithms are equally becoming very important. Domain decomposition (DD) methods are widely used to solve large scale engineering problems and to exploit their inherent ability for the solution of such problems.

'Artificial Immune Systems Tutorial'

The biological immune system is a robust, complex, adaptive system that defends the body from foreign pathogens. It is able to categorize all cells (or molecules) within the body as self-cells or non-self cells. It does this with the help of a distributed task force that has the intelligence to take action from a local and also a global perspective using its network of chemical messengers for communication. There are two major branches of the immune system. The innate immune system is an unchanging mechanism that detects and destroys certain invading organisms, whilst the adaptive immune system responds to previously unknown foreign cells and builds a response to them that can remain in the body over a long period of time. This remarkable information processing biological system has caught the attention of computer science in recent years. A novel computational intelligence technique, inspired by immunology, has emerged, called Artificial Immune Systems. Several concepts from the immune have been extracted and applied for solution to real world science and engineering problems. In this tutorial, we briefly describe the immune system metaphors that are relevant to existing Artificial Immune Systems methods. We will then show illustrative real-world problems suitable for Artificial Immune Systems and give a step-by-step algorithm walkthrough for one such problem. A comparison of the Artificial Immune Systems to other well-known algorithms, areas for future work, tips & tricks and a list of resources will round this tutorial off. It should be noted that as Artificial Immune Systems is still a young and evolving field, there is not yet a fixed algorithm template and hence actual implementations might differ somewhat from time to time and from those examples given here.

'Artificial Immune Systems Tutorial'

The biological immune system is a robust, complex, adaptive system that defends the body from foreign pathogens. It is able to categorize all cells (or molecules) within the body as self-cells or non-self cells. It does this with the help of a distributed task force that has the intelligence to take action from a local and also a global perspective using its network of chemical messengers for communication. There are two major branches of the immune system. The innate immune system is an unchanging mechanism that detects and destroys certain invading organisms, whilst the adaptive immune system responds to previously unknown foreign cells and builds a response to them that can remain in the body over a long period of time. This remarkable information processing biological system has caught the attention of computer science in recent years. A novel computational intelligence technique, inspired by immunology, has emerged, called Artificial Immune Systems. Several concepts from the immune have been extracted and applied for solution to real world science and engineering problems. In this tutorial, we briefly describe the immune system metaphors that are relevant to existing Artificial Immune Systems methods. We will then show illustrative real-world problems suitable for Artificial Immune Systems and give a step-by-step algorithm walkthrough for one such problem. A comparison of the Artificial Immune Systems to other well-known algorithms, areas for future work, tips & tricks and a list of resources will round this tutorial off. It should be noted that as Artificial Immune Systems is still a young and evolving field, there is not yet a fixed algorithm template and hence actual implementations might differ somewhat from time to time and from those examples given here.

Interrupted searches in the BBMCSFilter context for MINLP problems

The BBMCSFilter method was developed to solve mixed integer nonlinear programming problems. This kind of problems have integer and continuous variables and they appear very frequently in process engineering problems. The objective of this work is to analyze the performance of the method when the coordinate searches are interrupted in the context of the multistart strategy. From the numerical experiments, we observed a reduction on the number of function evaluations and on the CPU time.

Strategic Optimization Techniques For FRTU Deployment and Chip Physical Design

Combinatorial optimization is a complex engineering subject. Although formulation often depends on the nature of problems that differs from their setup, design, constraints, and implications, establishing a unifying framework is essential. This dissertation investigates the unique features of three important optimization problems that can span from small-scale design automation to large-scale power system planning: (1) Feeder remote terminal unit (FRTU) planning strategy by considering the cybersecurity of secondary distribution network in electrical distribution grid, (2) physical-level synthesis for microfluidic lab-on-a-chip, and (3) discrete gate sizing in very-large-scale integration (VLSI) circuit. First, an optimization technique by cross entropy is proposed to handle FRTU deployment in primary network considering cybersecurity of secondary distribution network. While it is constrained by monetary budget on the number of deployed FRTUs, the proposed algorithm identi?es pivotal locations of a distribution feeder to install the FRTUs in different time horizons. Then, multi-scale optimization techniques are proposed for digital micro?uidic lab-on-a-chip physical level synthesis. The proposed techniques handle the variation-aware lab-on-a-chip placement and routing co-design while satisfying all constraints, and considering contamination and defect. Last, the first fully polynomial time approximation scheme (FPTAS) is proposed for the delay driven discrete gate sizing problem, which explores the theoretical view since the existing works are heuristics with no performance guarantee. The intellectual contribution of the proposed methods establishes a novel paradigm bridging the gaps between professional communities.

Artificial neural networks analysis of Sao Paulo subway tunnel settlement data

Artificial neural networks have been used to analyze a number of engineering problems, including settlement caused by different tunneling methods in various types of ground mass. This paper focuses on settlement over shotcrete- supported tunnels on Sao Paulo subway line 2 (West Extension) that were excavated in Tertiary sediments using the sequential excavation method. The adjusted network is a good tool for predicting settlement above new tunnels to be excavated in similar conditions. The influence of network training parameters on the quality of results is also discussed. (C) 2007 Elsevier Ltd. All rights reserved.

Justified Fault-Ride-Through Requirements for Wind Turbines in Power Systems

In this paper, a novel adaptive strategy to obtain technically justified fault-ride-through requirements for wind turbines (WTs) is proposed. The main objective is to promote an effective integration of wind turbines into power systems with still low penetration levels of wind power based on technical and economical considerations. The level of requirement imposed by the strategy is increased stepwise over time, depending on system characteristics and on wind power penetration level. The idea behind is to introduce stringent requirements only when they are technically needed for a reliable and secure power system operation. Voltage stability support and fault-ride-through requirements are considered in the strategy. Simulations are based on the Chilean transmission network, a midsize isolated power system with still low penetration levels of wind power. Simulations include fixed speed induction generators and doubly fed induction generators. The effects on power system stability of the wind power injections, integrated into the network by adopting the adaptive strategy, are compared with the effects that have the same installed capacity of wind power but only considering WTs able to fulfill stringent requirements (fault-ride-through capability and support voltage stability). Based on simulations and international experience, technically justified requirements for the Chilean case are proposed.

Genetic algorithms for design of liquid retaining structure

In this paper, genetic algorithm (GA) is applied to the optimum design of reinforced concrete liquid retaining structures, which comprise three discrete design variables, including slab thickness, reinforcement diameter and reinforcement spacing. GA, being a search technique based on the mechanics of natural genetics, couples a Darwinian survival-of-the-fittest principle with a random yet structured information exchange amongst a population of artificial chromosomes. As a first step, a penalty-based strategy is entailed to transform the constrained design problem into an unconstrained problem, which is appropriate for GA application. A numerical example is then used to demonstrate strength and capability of the GA in this domain problem. It is shown that, only after the exploration of a minute portion of the search space, near-optimal solutions are obtained at an extremely converging speed. The method can be extended to application of even more complex optimization problems in other domains.

Spring-neap tide-induced beach water table fluctuations in a sloping coastal aquifer

Predictions of water table fluctuations in coastal aquifers are needed for numerous coastal and water resources engineering problems. Most previous investigations have been based on the Boussinesq equation for the case of a vertical beach. In this note an analytical solution based on shallow water expansion for the spring- neap tide- induced water table fluctuations in a coastal aquifer is presented. Unlike most previous investigations, multitidal signals are considered with a sloping coastal aquifer. The new solution is verified by comparing with field observations from Ardeer, Scotland. On the basis of the analytical approximation the influences of higher- order components on water table elevation are examined first. Then, a parametric study has been performed to investigate the effects of the amplitude ratio (lambda), frequency ratio (omega), and phases (delta(1) and delta(2)) on the tide- induced water table fluctuations in a sloping sandy beach.

A modified orthodontic protocol for advanced periodontal disease in Class II division 1 malocclusion

An interdisciplinary approach is often the best option for achieving a predictable outcome for an adult patient with complex clinical problems. This case report demonstrates the combined periodontal/orthodontic treatment for a 49-year-old woman presenting with a Class II Division 1 malocclusion with moderate maxillary anterior crowding, a 9-mm overjet, and moderate to severe bone loss as the main characteristics of the periodontal disease. The orthodontic treatment included 2 maxillary first premolar extractions through forced extrusion. Active orthodontic treatment was completed in 30 months. The treatment outcomes, including the periodontal condition, were stable 17 months after active orthodontic treatment. The advantages of this interdisciplinary approach are discussed. Periodontally compromised orthodontic patients can be satisfactorily treated, achieving most of the conventional orthodontic goals, if a combined orthodontic/periodontic approach is used. (Am J Orthod Dentofacial Orthop 2011; 139:S133-44)

Meta-heuristics self-configuration for scheduling

Scheduling resolution requires the intervention of highly skilled human problemsolvers. This is a very hard and challenging domain because current systems are becoming more and more complex, distributed, interconnected and subject to rapidly changing. A natural Autonomic Computing evolution in relation to Current Computing is to provide systems with Self-Managing ability with a minimum human interference. This paper addresses the resolution of complex scheduling problems using cooperative negotiation. A Multi-Agent Autonomic and Meta-heuristics based framework with self-configuring capabilities is proposed.

Self-managing agents for dynamic scheduling in manufacturing

The main purpose of this paper is to propose a Multi-Agent Autonomic and Bio-Inspired based framework with selfmanaging capabilities to solve complex scheduling problems using cooperative negotiation. Scheduling resolution requires the intervention of highly skilled human problem-solvers. This is a very hard and challenging domain because current systems are becoming more and more complex, distributed, interconnected and subject to rapidly changing. A natural Autonomic Computing (AC) evolution in relation to Current Computing is to provide systems with Self-Managing ability with a minimum human interference.