BoilerModel: a qualitative model-based reasoning system implemented in Ada

Effective, inexpensive, and realistic on-going training is required to keep all Naval personnel proficient in their field. Nowhere is this more true than in steam propulsion engineering plants. The complex systems of valves, piping, and components require continuous refresher for watchstanders to perform their jobs safely. BoilerModel is a qualitative expert system designed using model-based reasoning principles and implemented in Ada. It accurately models a 1200 psi D-type boiler and its associated peripherals. The use of fundamental intra-component relationship ("first principles") and constraint propagation result in compact mode because there is no need for the extensive rule base found in conventional expert systems. Implementation in Ada permits the use of concurrent tasking to simulate simultaneous valve propagation found in real-world boiler systems. Additionally, Ada's portability allows BoilerModel to be compiled and run on virtually any machine, thereby making it an affordable and attractive complement to shipboard engineering training.http://archive.org/details/boilermodelquali00stasLieutenant, United States NavyApproved for public release; distribution is unlimited

Real time control of nonlinear dynamic systems using neuro-fuzzy controllers

The problem of real time control of a nonlinear dynamic system using intelligent control techniques is considered. The current trend is to incorporate neural networks and fuzzy logic into adaptive control strategies. The focus of this work is to investigate the current neuro-fuzzy approaches from literature and adapt them for a specific application. In order to achieve this objective, an experimental nonlinear dynamic system is considered. The motivation for this comes from the desire to solve practical problems and to create a test-bed which can be used to test various control strategies. The nonlinear dynamic system considered here is an unstable balance beam system that contains two fluid tanks, one at each end, and the balance is achieved by pumping the fluid back and forth from the tanks. A popular approach, called ANFIS (Adaptive Networks-based Fuzzy Inference Systems), which combines the structure of fuzzy logic controllers with the learning aspects from neural networks is considered as a basis for developing novel techniques, because it is considered to be one of the most general framework for developing adaptive controllers. However, in the proposed new method, called Generalized Network-based Fuzzy Inferencing Systems (GeNFIS), more conventional fuzzy schemes for the consequent part are used instead of using what is called the Sugeno type rules. Moreover, in contrast to ANFIS which uses a full set of rules, GeNFIS uses only a limited number of rules based on certain expert knowledge. GeNFIS is tested on the balance beam system, both in a real- time actual experiment and the simulation, and is found to perform better than a comparable ANFIS under supervised learning. Based on these results, several modifications of GeNFIS are considered, for example, synchronous defuzzification through triangular as well as bell shaped membership functions. Another modification involves simultaneous use of Sugeno type as well as conventional fuzzy schemes for the consequent part, in an effort to create a more flexible framework. Results of testing different versions of GeNFIS on the balance beam system are presented

The nature of professional reasoning: An analysis of design in the engineering curriculum

Access to the practice of a profession is controlled by formal education structures. These structures are intended to induct future professionals into the specialised knowledge, skills and values that underpin that profession. Yet, despite meeting the academic requirements of a professional degree, many graduates struggle to 'apply' specialised knowledge when confronted with problems in professional practice. This is a study of the nature of knowledge as it is mobilised in professional reasoning. The case studied was located in engineering education, because knowledge relations tend to be more explicit in education than in practice. The data were collected from design projects located in two differently structured curricula in civil and mechanical engineering curricula. The research questions that directed the study were: 1. What is the nature of the reasoning involved when specialised disciplinary knowledge is recruited to develop specific, often concrete, artefacts? 2. What is the logic of progression in a trajectory of engineering design tasks in terms of the relation between knowledge and artefact? The study draws on two intellectual fields: models of professional reasoning and design thinking on one hand, and social realism in the sociology of education on the other. These traditions take different positions on professional reasoning. Design thinking is concerned with contextual detail and case precedent, while social realism in the sociology of education is concerned with conceptual coherence within knowledge specialisations and the power of generalisation. Both offer important insights into professional reasoning, but alone neither is adequate. The analysis was done using the semantics dimension of Legitimation Code Theory, LCT (Semantics), which required an adaptation in order to fully describe the significance of contextual detail evident in the data. The findings showed that specialised knowledge and contextual detail interact far more dialectically than previously assumed. This provides empirical insights for structuring curricula. Students can be more intentionally inducted into recontextualising academic knowledge for the purpose of solving contextually emergent problems. Theoretically the study contributes to the social realist school within the sociology of education by revealing its blindness to contextual detail and consequently offering a fuller understanding of the nature of regions. This has implications for other studies of professional knowledge and education

A framework for the design, prototyping and evaluation of mobile interfaces for domestic environments

The idea of the smart home has been discussed for over three decades, but it has yet to achieve mass-market adoption. This thesis asks the question Why is my home not smart? It highlights four main areas that are barriers to adoption, and concentrates on a single one of these issues: usability. It presents an investigation that focuses on design, prototyping and evaluation of mobile interfaces for domestic environments resulting in the development of a novel framework. A smart home is the physical realisation of a ubiquitous computing system for domestic living. The research area offers numerous benefits to end-users such as convenience, assistive living, energy saving and improved security and safety. However, these benefits have yet to become accessible due to a lack of usable smart home control interfaces. This issue is considered a key reason for lack of adoption and is the focus for this thesis. Within this thesis, a framework is introduced as a novel approach for the design, prototyping and evaluation of mobile interfaces for domestic environments. Included within this framework are three components. Firstly, the Reconfigurable Multimedia Environment (RME), a physical evaluation and observation space for conducting user centred research. Secondly, Simulated Interactive Devices (SID), a video-based development and control tool for simulating interactive devices commonly found within a smart home. Thirdly, iProto, a tool that facilitates the production and rapid deployment of high fidelity prototypes for mobile touch screen devices. This framework is evaluated as a round-tripping toolchain for prototyping smart home control and found to be an efficient process for facilitating the design and evaluation of such interfaces

COBE's search for structure in the Big Bang

The launch of Cosmic Background Explorer (COBE) and the definition of Earth Observing System (EOS) are two of the major events at NASA-Goddard. The three experiments contained in COBE (Differential Microwave Radiometer (DMR), Far Infrared Absolute Spectrophotometer (FIRAS), and Diffuse Infrared Background Experiment (DIRBE)) are very important in measuring the big bang. DMR measures the isotropy of the cosmic background (direction of the radiation). FIRAS looks at the spectrum over the whole sky, searching for deviations, and DIRBE operates in the infrared part of the spectrum gathering evidence of the earliest galaxy formation. By special techniques, the radiation coming from the solar system will be distinguished from that of extragalactic origin. Unique graphics will be used to represent the temperature of the emitting material. A cosmic event will be modeled of such importance that it will affect cosmological theory for generations to come. EOS will monitor changes in the Earth's geophysics during a whole solar color cycle