Real-time process plant fault diagnosis

Operators can become confused while diagnosing faults in process plant while in operation. This may prevent remedial actions being taken before hazardous consequences can occur. The work in this thesis proposes a method to aid plant operators in systematically finding the causes of any fault in the process plant. A computer aided fault diagnosis package has been developed for use on the widely available IBM PC compatible microcomputer. The program displays a coloured diagram of a fault tree on the VDU of the microcomputer, so that the operator can see the link between the fault and its causes. The consequences of the fault and the causes of the fault are also shown to provide a warning of what may happen if the fault is not remedied. The cause and effect data needed by the package are obtained from a hazard and operability (HAZOP) study on the process plant. The result of the HAZOP study is recorded as cause and symptom equations which are translated into a data structure and stored in the computer as a file for the package to access. Probability values are assigned to the events that constitute the basic causes of any deviation. From these probability values, the a priori probabilities of occurrence of other events are evaluated. A top-down recursive algorithm, called TDRA, for evaluating the probability of every event in a fault tree has been developed. From the a priori probabilities, the conditional probabilities of the causes of the fault are then evaluated using Bayes' conditional probability theorem. The posteriori probability values could then be used by the operators to check in an orderly manner the cause of the fault. The package has been tested using the results of a HAZOP study on a pilot distillation plant. The results from the test show how easy it is to trace the chain of events that leads to the primary cause of a fault. This method could be applied in a real process environment.

Setting parameters in MRP for the effective management of bought-out inventory in a JIT assembly environment

In recent years, UK industry has seen an explosive growth in the number of `Computer Aided Production Management' (CAPM) system installations. Of the many CAPM systems, materials requirement planning/manufacturing resource planning (MRP/MRPII) is the most widely implemented. Despite the huge investments in MRP systems, over 80 percent are said to have failed within 3 to 5 years of installation. Many people now assume that Just-In-Time (JIT) is the best manufacturing technique. However, those who have implemented JIT have found that it also has many problems. The author argues that the success of a manufacturing company will not be due to a system which complies with a single technique; but due to the integration of many techniques and the ability to make them complement each other in a specific manufacturing environment. This dissertation examines the potential for integrating MRP with JIT and Two-Bin systems to reduce operational costs involved in managing bought-out inventory. Within this framework it shows that controlling MRP is essential to facilitate the integrating process. The behaviour of MRP systems is dependent on the complex interactions between the numerous control parameters used. Methodologies/models are developed to set these parameters. The models are based on the Pareto principle. The idea is to use business targets to set a coherent set of parameters, which not only enables those business targets to be realised, but also facilitates JIT implementation. It illustrates this approach in the context of an actual manufacturing plant - IBM Havant. (IBM Havant is a high volume electronics assembly plant with the majority of the materials bought-out). The parameter setting models are applicable to control bought-out items in a wide range of industries and are not dependent on specific MRP software. The models have produced successful results in several companies and are now being developed as commercial products.

The mechanical behaviour of cylindrical GRP panels

Glass reinforced plastic (GRP) is now an established material for the fabrication of sonar windows. Its good mechanical strength, light weight, resistance to corrosion and acoustic transparency, are all properties which fit it for this application. This thesis describes a study, undertaken at the Royal Naval Engineering College, Plymouth, into the mechanical behaviour of a circular cylindrical sonar panel. This particular type of panel would be used to cover a flank array sonar in a ship or submarine. The case considered is that of a panel with all of its edges mechanically clamped and subject to pressure loading on its convex surface. A comprehensive program of testing, to determine the orthotropic elastic properties of the laminated composite panel material is described, together with a series of pressure tests on 1:5 scale sonar panels. These pressure tests were carried out in a purpose designed test rig, using air pressure to provide simulated hydrostatic and hydrodynamic loading. Details of all instrumentation used in the experimental work are given in the thesis. The experimental results from the panel testing are compared with predictions of panel behaviour obtained from both the Galerkin solution of Flugge's cylindrical shell equations (orthotropic case), and finite element modelling of the panels using PAFEC. A variety of appropriate panel boundary conditions are considered in each case. A parametric study, intended to be of use as a preliminary design tool, and based on the above Galerkin solution, is also presented. This parametric study considers cases of boundary conditions, material properties, and panel geometry, outside of those investigated in the experimental work Final conclusions are drawn and recommendations made regarding possible improvements to the procedures for design, manufacture and fixing of sonar panels in the Royal Navy.

Quality Measurement of Business Web Application

With the development of the Internet culture applications are becoming simpler and simpler, users need less IT knowledge than earlier; from the ‘reader’ status they have reached that of the content creator and editor. In our days, the effects of the web are becoming stronger and stronger— computer-aided work is conventional almost everywhere. The spread of the Internet applications has several reasons: first of all, their accessibility is widespread; second, their use is not limited to only one computer or network on which they have been installed. Also, the quantity of accessible information now and earlier is not even comparable. Not counting the applications which need high broadband or high counting capacity (for example video editing), Internet applications are reaching the functionality of the thick clients associates. The most serious disadvantage of Internet applications – for security reasons — is that the resources of the client computer are not fully accessible or accessible only to a restricted extent. Still thick clients do have some advantages: better multimedia perdormance with more flexibility due to local resources and the possibility for offline working.

webComputing Service Framework

Presented is webComputing – a general framework of mathematically oriented services including remote access to hardware and software resources for mathematical computations, and web interface to dynamic interactive computations and visualization in a diversity of contexts: mathematical research and engineering, computer-aided mathematical/technical education and distance learning. webComputing builds on the innovative webMathematica technology connecting technical computing system Mathematica to a web server and providing tools for building dynamic and interactive web-interface to Mathematica-based functionality. Discussed are the conception and some of the major components of webComputing service: Scientific Visualization, Domain- Specific Computations, Interactive Education, and Authoring of Interactive Pages.

About the Multi Criteria Ranging Problem in the Fuzzy Environment

Decision making and technical decision analysis demand computer-aided techniques and therefore more and more support by formal techniques. In recent years fuzzy decision analysis and related techniques gained importance as an efficient method for planning and optimization applications in fields like production planning, financial and economical modeling and forecasting or classification. It is also known, that the hierarchical modeling of the situation is one of the most popular modeling method. It is shown, how to use the fuzzy hierarchical model in complex with other methods of Multiple Criteria Decision Making. We propose a novel approach to overcome the inherent limitations of Hierarchical Methods by exploiting multiple criteria decision making.

Информационно-Аналитические Модели и Эволюционные Аспекты Решения Задачи Комплектования

В статье рассмотрена технология решения задачи комплектования аварийно- спасательной техники с использованием многокритериальной оптимизации, последовательного анализа вариантов и эволюционного моделирования. Разработаны модели, служащие информационно- аналитическим базисом формирования интегрального критерия.

Структуризация Задач и Функциональных Модулей Системы Поддержки Принятия Решений при Пожаротушении на Основе Принципа Информационного Единства

В статье рассмотрены особенности проектирования системы поддержки принятия решений «Безопасность», предназначенной для информационно-консультативного сопровождения процессов принятия решений руководителями пожарных подразделений во время тушения пожара.

Next generation high density three-dimensional magnetic recording systems

This work is the first work using patterned soft underlayers in multilevel three-dimensional vertical magnetic data storage systems. The motivation stems from an exponentially growing information stockpile, and a corresponding need for more efficient storage devices with higher density. The world information stockpile currently exceeds 150EB (ExaByte=1x1018Bytes); most of which is in analog form. Among the storage technologies (semiconductor, optical and magnetic), magnetic hard disk drives are posed to occupy a big role in personal, network as well as corporate storage. However; this mode suffers from a limit known as the Superparamagnetic limit; which limits achievable areal density due to fundamental quantum mechanical stability requirements. There are many viable techniques considered to defer superparamagnetism into the 100's of Gbit/in2 such as: patterned media, Heat-Assisted Magnetic Recording (HAMR), Self Organized Magnetic Arrays (SOMA), antiferromagnetically coupled structures (AFC), and perpendicular magnetic recording. Nonetheless, these techniques utilize a single magnetic layer; and can thusly be viewed as two-dimensional in nature. In this work a novel three-dimensional vertical magnetic recording approach is proposed. This approach utilizes the entire thickness of a magnetic multilayer structure to store information; with potential areal density well into the Tbit/in2 regime. ^ There are several possible implementations for 3D magnetic recording; each presenting its own set of requirements, merits and challenges. The issues and considerations pertaining to the development of such systems will be examined, and analyzed using empirical and numerical analysis techniques. Two novel key approaches are proposed and developed: (1) Patterned soft underlayer (SUL) which allows for enhanced recording of thicker media, (2) A combinatorial approach for 3D media development that facilitates concurrent investigation of various film parameters on a predefined performance metric. A case study is presented using combinatorial overcoats of Tantalum and Zirconium Oxides for corrosion protection in magnetic media. ^ Feasibility of 3D recording is demonstrated, and an emphasis on 3D media development is emphasized as a key prerequisite. Patterned SUL shows significant enhancement over conventional "un-patterned" SUL, and shows that geometry can be used as a design tool to achieve favorable field distribution where magnetic storage and magnetic phenomena are involved. ^

Spatial-temporal mining of archived automatic vehicle location (AVL) data for transit service planning applications

An Automatic Vehicle Location (AVL) system is a computer-based vehicle tracking system that is capable of determining a vehicle's location in real time. As a major technology of the Advanced Public Transportation System (APTS), AVL systems have been widely deployed by transit agencies for purposes such as real-time operation monitoring, computer-aided dispatching, and arrival time prediction. AVL systems make a large amount of transit performance data available that are valuable for transit performance management and planning purposes. However, the difficulties of extracting useful information from the huge spatial-temporal database have hindered off-line applications of the AVL data. ^ In this study, a data mining process, including data integration, cluster analysis, and multiple regression, is proposed. The AVL-generated data are first integrated into a Geographic Information System (GIS) platform. The model-based cluster method is employed to investigate the spatial and temporal patterns of transit travel speeds, which may be easily translated into travel time. The transit speed variations along the route segments are identified. Transit service periods such as morning peak, mid-day, afternoon peak, and evening periods are determined based on analyses of transit travel speed variations for different times of day. The seasonal patterns of transit performance are investigated by using the analysis of variance (ANOVA). Travel speed models based on the clustered time-of-day intervals are developed using important factors identified as having significant effects on speed for different time-of-day periods. ^ It has been found that transit performance varied from different seasons and different time-of-day periods. The geographic location of a transit route segment also plays a role in the variation of the transit performance. The results of this research indicate that advanced data mining techniques have good potential in providing automated techniques of assisting transit agencies in service planning, scheduling, and operations control. ^

User-centric music information retrieval

The rapid growth of the Internet and the advancements of the Web technologies have made it possible for users to have access to large amounts of on-line music data, including music acoustic signals, lyrics, style/mood labels, and user-assigned tags. The progress has made music listening more fun, but has raised an issue of how to organize this data, and more generally, how computer programs can assist users in their music experience. An important subject in computer-aided music listening is music retrieval, i.e., the issue of efficiently helping users in locating the music they are looking for. Traditionally, songs were organized in a hierarchical structure such as genre->artist->album->track, to facilitate the users’ navigation. However, the intentions of the users are often hard to be captured in such a simply organized structure. The users may want to listen to music of a particular mood, style or topic; and/or any songs similar to some given music samples. This motivated us to work on user-centric music retrieval system to improve users’ satisfaction with the system. The traditional music information retrieval research was mainly concerned with classification, clustering, identification, and similarity search of acoustic data of music by way of feature extraction algorithms and machine learning techniques. More recently the music information retrieval research has focused on utilizing other types of data, such as lyrics, user-access patterns, and user-defined tags, and on targeting non-genre categories for classification, such as mood labels and styles. This dissertation focused on investigating and developing effective data mining techniques for (1) organizing and annotating music data with styles, moods and user-assigned tags; (2) performing effective analysis of music data with features from diverse information sources; and (3) recommending music songs to the users utilizing both content features and user access patterns.

Optimization of three-dimensional branching networks of microchannels for thermal management of microelectronics

The aim of this work is to present a methodology to develop cost-effective thermal management solutions for microelectronic devices, capable of removing maximum amount of heat and delivering maximally uniform temperature distributions. The topological and geometrical characteristics of multiple-story three-dimensional branching networks of microchannels were developed using multi-objective optimization. A conjugate heat transfer analysis software package and an automatic 3D microchannel network generator were developed and coupled with a modified version of a particle-swarm optimization algorithm with a goal of creating a design tool for 3D networks of optimized coolant flow passages. Numerical algorithms in the conjugate heat transfer solution package include a quasi-ID thermo-fluid solver and a steady heat diffusion solver, which were validated against results from high-fidelity Navier-Stokes equations solver and analytical solutions for basic fluid dynamics test cases. Pareto-optimal solutions demonstrate that thermal loads of up to 500 W/cm2 can be managed with 3D microchannel networks, with pumping power requirements up to 50% lower with respect to currently used high-performance cooling technologies.

Classificação de nódulos pulmonares em imagens tomográficas utilizando redes neurais artificiais em cascata

Lung cancer is the most common of malignant tumors, with 1.59 million new cases worldwide in 2012. Early detection is the main factor to determine the survival of patients affected by this disease. Furthermore, the correct classification is important to define the most appropriate therapeutic approach as well as suggest the prognosis and the clinical disease evolution. Among the exams used to detect lung cancer, computed tomography have been the most indicated. However, CT images are naturally complex and even experts medical are subject to fault detection or classification. In order to assist the detection of malignant tumors, computer-aided diagnosis systems have been developed to aid reduce the amount of false positives biopsies. In this work it was developed an automatic classification system of pulmonary nodules on CT images by using Artificial Neural Networks. Morphological, texture and intensity attributes were extracted from lung nodules cut tomographic images using elliptical regions of interest that they were subsequently segmented by Otsu method. These features were selected through statistical tests that compare populations (T test of Student and U test of Mann-Whitney); from which it originated a ranking. The features after selected, were inserted in Artificial Neural Networks (backpropagation) to compose two types of classification; one to classify nodules in malignant and benign (network 1); and another to classify two types of malignancies (network 2); featuring a cascade classifier. The best networks were associated and its performance was measured by the area under the ROC curve, where the network 1 and network 2 achieved performance equal to 0.901 and 0.892 respectively.

Informelles Lernen Studierender mit Social Software unterstützen

E-Learning-Aktivitäten von Hochschulen haben häufig eine einseitige Ausrichtung auf die Unterstützung von Lehrveranstaltungen durch Technologien, insbesondere Lernmanagementsysteme. Dabei geraten die Studierenden als Zielgruppe nur mittelbar in den Blick. Diese Beobachtung nehmen die Autorinnen und Autoren des Bandes zum Anlass, das Lern-Erleben und die unterschiedlichen Phasen des Studiums aus Perspektive der Studierenden zu betrachten. Untersucht wird zudem, welche Unterstützungsangebote Hochschulen in welchen Phasen idealerweise bereitstellen. Die Autorinnen und Autoren formulieren detailliert, wie Hochschulen das studentische Lernen mit Hilfe von Social Software unterstützen können. Diese Empfehlungen basieren auf den Ergebnissen empirischer Untersuchungen sowie auf Fallstudien nationaler und internationaler Beispiele guter Praxis, die ausführlich präsentiert werden. Mit diesem Band möchten die Autorinnen und Autoren denjenigen, die in Bildungseinrichtungen des tertiären Sektors (aber auch in anderen Sektoren) tätig sind, konkrete Anregungen liefern, Unterstützungsangebote für das informelle Lernen von Studierenden mit Social Software stärker in den Blick zu nehmen und geeignete Angebote zu entwickeln. Die Publikation basiert auf Ergebnissen des Projekts „Learner Communities of Practice“, das zwischen 2009 und 2012 als Verbundprojekt sächsischer Hochschulen mit Förderung durch das SMWK unter Leitung des Medienzentrums der TU Dresden bearbeitet wurde.