ENGRAVE is an expert system that performs the work of a music engraver. The system takes a digital image of a conductor's score as input and produces engraved-quality copies of the individual parts. ENGRAVE consists of a vision system and a graphics system. The vision system contains a low-level section that recognizes features and a visual expert system that understands their meanings. Under the current computer vision paradigm, low-level processing is general-purpose while domain knowledge is used only in "high-level" routines. We hypothesize that domain knowledge is necessary at the low level as well for a vision system to work reliably. The visual expert uses a frame-based approach to explain the objects round in music. In the graphics system, we make use of the concept of "spatial planning" to generate correct musical notation. We show by example that spatial planning can be applied to other domains. / Master of Science

The analysis of rotating equipment difficulties is currently accomplished by a specialist in rotating equipment examining the signs and symptoms of the equipment, applying his expert judgement, and determining the cause of the machine's difficulty. This thesis covers the development of an off-line expert system that can be used to emulate the expert's ability to interpret the signs and symptoms of the machine, including suggestions of possible further actions to take for repairing the problem or refining the proof for the proposed cause the difficulty. An editor has also been built which will allow an expert to keep the information used by the system current with the state of the art for rotating machinery diagnostics. This thesis documents the development of the PC-based Turbo Prolog expert shell and external knowledge-base editor. The use of the system editor is illustrated by loading current diagnostic table information into a knowledge base. Then the expert program's operation is illustrated by applying the editor-formed database in a typical session. The expert shell and knowledge base can operate as a stand-alone unit for field application. Resident experts in machinery diagnostics can build and update databases for distribution to users in the company to assure full uniform utilization of the current and most correct knowledge. / Master of Science

Expert system technology has produced systems that perform heuristic classification. These systems solve problems of a type determined by the knowledge engineer and the expert at system design time. A "true consultant" on the contrary, applies domain knowledge to solve a problem not previously seen. For example, a graphic design consultant must accept the statement of almost any problem from a client and turn it into a visual design. This thesis reports the successful construction of the first such true consultant for a well-understood domain: the visual design task of chart construction. The system leads a client in a dialogue to define a problem in the client's terms and then maps the problem representation into a knowledge base for constructing charts. Extensions of the technology reported in this thesis may aid the creation of a new class of expert systems. / Master of Science

Among the various natural calamities, flood is considered one of the most catastrophic natural hazards, which has a significant impact on the socio-economic lifeline of a country. The Assessment of flood risks facilitates taking appropriate measures to reduce the consequences of flooding. The flood risk assessment requires Big data which are coming from different sources, such as sensors, social media, and organizations. However, these data sources contain various types of uncertainties because of the presence of incomplete and inaccurate information. This paper presents a Belief rule-based expert system (BRBES) which is developed in Big data platform to assess flood risk in real time. The system processes extremely large dataset by integrating BRBES with Apache Spark while a web-based interface has developed allowing the visualization of flood risk in real time. Since the integrated BRBES employs knowledge driven learning mechanism, it has been compared with other data-driven learning mechanisms to determine the reliability in assessing flood risk. Integrated BRBES produces reliable results comparing from the other data-driven approaches. Data for the expert system has been collected targeting different case study areas from Bangladesh to validate the integrated system.

Artificial Intelligence (AI) is the part of computer science concerned with designing computer systems, that is, systems that exhibit the characteristics we associate with intelligence in human behavior--understanding language, learning, reasoning, solving problems, and so on. Many believe that insights into the nature of the mind can be gained by studying the operation of such programs. The AI concept has formed the basis for developing the computer-assisted creativity techniques called The Computer Consultant (TCC), and The Idea Machine (TIM). TIM has, so far, been applied to topics in the engineering and "hard sciences" fields. In this study these techniques are presented/reviewed in detail and the research concentrated on the expansion/development of a methodology for computer—assisted creativity. This research will help in further evolution of TIM into a richer process for idea generation and general problem solving, and in enhancing the application capabilities. This is done by: (1) expanding the conceptual and ideas data bases from which analogies can be drawn; (2) conducting comprehensive trials with TIM to establish its strengths and limitations; and (3) doing research on techniques for the screening and packaging of ideas techniques. Rural road projects are an important part of rural development programs in the Third World countries. For some years the construction of such road projects, funded in part by international donor agencies, has been a subject of some controversy. Most policy makers in the developing or underdeveloped countries support the practice of expanding the rural dirt (unpaved) roads rather than spending limited resources on maintenance. Some donor agencies are now inclined to only support maintenance-biased road projects. A similar situation arose in Pakistan where the U.S. Agency for International Development (USAID) proposed to fund a road resources development project in the Sind Province. This real life situation is selected as a basis for developing a road resources management model, and generating ideas using TIM. These ideas are screened and packaged to be used in revising the model for further trials. The application of TIM to this problem from the civil engineering field results in some useful outputs. This study provides a good basis for further enhancing TIM capabilities. / Ph. D.

Technical analysis as a sophisticated form of forecasting technique has a varying popularity in the academic and business world. In the past, users were sceptical about technical trading rules and their performance. This is substantiated by the acceptance of the Efficient Market Hypothesis and mixed empirical findings about technical analysis in widely cited studies. The flag pattern is seen as one of the most significant spread chart patterns amongst stock market charting analysts. The present research validates a trading rule based on the further development of flag pattern recognition. The research question concentrates on whether technical analysis applying the flag pattern can outperform international stock markets indices and prove the inefficiency of these markets. The markets observed are represented by the corresponding indices DAX (Germany), DJIA (United States) and IBEX (Spain). The design of the trading rule presents several changes with respect to previous academic works: The wide sample used when considering intraday data, together with the confiuration of some of the variables and the consideration of risk, concludes that the trading rule provides greater positive risk-adjusted returns than the buy-and-hold strategy which is used as a benchmark. The reported positive results strengthen the robustness of the conclusions reached by other researchers. / El análisis técnico es una forma sofisticada de técnica de predicción cuya popularidad ha ido variando en el mundo académico y de los negocios. En el pasado, los usuarios eran bastante escépticos respecto de las reglas técnicas de trading y su performance. Todo esto, se encuentra sustentado por la aceptación de la hipótesis del mercado eficiente y descubrimientos empíricos mixtos sobre el análisis técnico, que se mencionan en un número amplio de estudios. El patrón bandera es visto como uno de los patrones gráficos más significativo y difundido entre los analistas técnicos de mercado. El presente estudio valida una regla de trading basada en el desarrollo futuro del reconocimiento gráfico del patrón bandera. La pregunta de investigación se centra en si el análisis técnico basado en el patrón bandera puede batir los índices internacionales de mercado y probar, de esta manera, la ineficiencia de dichos mercados. Los mercados observados son representados por los correspondientes índices DAX (Alemania), DJIA (Estados Unidos) e IBEX (España). El diseño de la regla de trading presenta varios cambios y novedades con respecto a trabajos académicos previos. La amplia muestra usada al considerar los datos intradía, junto con la configuración de algunas variables y la consideración del riesgo, confirman que la regla de trading proporciona mejores, y más ajustadas al riesgo, rentabilidades positivas que la estrategia de buy-and-hold que se utiliza como referencia. Los resultados positivos corroboran la robustez de las conclusiones a las que también se llegan en otros trabajos. / L'anàlisi tècnica és una forma sofisticada de tècnica de predicció, la popularitat de la qual ha anat variant al món acadèmic i dels negocis. En el passat, els usuaris eren bastant escèptics respecte de les regles tècniques de trading i la seva performance. Tot això, es troba sustentat per l'acceptació de la hipòtesi del mercat eficient i descobriments empírics mixts sobre l'anàlisi tècnica, que s'esmenten en un nombre ampli d'estudis. El patró bandera és vist com un dels patrons gràfics més significatiu i difós entre els analistes tècnics de mercat. El present estudi valida una regla de trading basada en el desenvolupament futur del reconeixement gràfic del patró bandera. La pregunta de recerca se centra en si l'anàlisi tècnica basada en el patró bandera pot batre els índexs internacionals de mercat i provar, d'aquesta manera, la ineficiència d'aquests mercats. Els mercats observats són representats pels corresponents índexs DAX (Alemanya), *DJIA (Estats Units) i IBEX (Espanya). El disseny de la regla de trading presenta diversos canvis i novetats pel que fa a treballs acadèmics previs. L'àmplia mostra usada en considerar les dades intradia, juntament amb la configuració d'algunes variables i la consideració del risc, confirmen que la regla de trading proporciona millors, i més ajustades al risc, rendibilitats positives que l'estratègia de buy-and-hold que s'utilitza com a referència. Els resultats positius corroboren la robustesa de les conclusions a les quals també s'arriben en altres treballs. / Michniuk, K. (2017). PATTERN RECOGNITION APPLIED TO CHART ANALYSIS. EVIDENCE FROM INTRADAY INTERNATIONAL STOCK MARKETS [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/78837

Yes / Information systems (IS) facilitate organisations to increase responsiveness and reduce the costs of their supply chain. This paper seeks to make a contribution through exploring and visualising knowledge mapping from the perspective of IS investment evaluation. The evaluation of IS is regarded as a challenging and complex process, which becomes even more difficult with the increased complexity of IS. The intricacy of IS evaluation, however, is due to numerous interrelated factors (e.g. costs, benefits and risks) that have human or organisational dimensions. With this in mind, there appears to be an increasing need to assess investment decision-making processes, to better understand the often far-reaching implications associated with technology adoption and interrelated knowledge components (KC). Through the identification and extrapolation of key learning issues from the literature and empirical findings, organisations can better improve their business processes and thereby their effectiveness and efficiency, while preventing others from making costly oversights that may not necessarily be only financial. In seeking to enlighten the often obscure evaluation of IS investments, this paper attempts to inductively emphasise the dissemination of knowledge and learning through the application of a fuzzy Expert System (ES) based knowledge mapping technique (i.e. Fuzzy Cognitive Map [FCM]). The rationale for exploring knowledge and IS investment evaluation is that a knowledge map will materialise for others to exploit during their specific technology evaluation. This is realised through conceptualising the explicit and tacit investment drivers. Among the several findings drawn from this research, the key resulting knowledge mapping through FCM demonstrated the complex, multifaceted and emergent behaviour of causal relationships within the knowledge area. The principal relationships and knowledge within IS investment evaluation are illustrated as being determined by a blend of managerial and user perspectives.

Yes / As far back as the industrial revolution, significant development in technical innovation has succeeded in transforming numerous manual tasks and processes that had been in existence for decades where humans had reached the limits of physical capacity. Artificial Intelligence (AI) offers this same transformative potential for the augmentation and potential replacement of human tasks and activities within a wide range of industrial, intellectual and social applications. The pace of change for this new AI technological age is staggering, with new breakthroughs in algorithmic machine learning and autonomous decision-making, engendering new opportunities for continued innovation. The impact of AI could be significant, with industries ranging from: finance, healthcare, manufacturing, retail, supply chain, logistics and utilities, all potentially disrupted by the onset of AI technologies. The study brings together the collective insight from a number of leading expert contributors to highlight the significant opportunities, realistic assessment of impact, challenges and potential research agenda posed by the rapid emergence of AI within a number of domains: business and management, government, public sector, and science and technology. This research offers significant and timely insight to AI technology and its impact on the future of industry and society in general, whilst recognising the societal and industrial influence on pace and direction of AI development.

Yes / Designing and implementing Performance Measurement System (PMS) is an integral part of management control systems. This paper presents an original and novel approach to designing and benchmarking of PMSs for a manufacturing environment through a hybrid framework which overcomes the shortcomings of earlier models. A detailed review was taken of previous models and their limitations were identified. The present hybrid PMS model seeks to improve the earlier research models by the following novel approach: implementation of a Knowledge Based (KB) expert system, Gauging Absences of Pre-requisite (GAP) analysis and Analytic Hierarchy Process (AHP) methodology in an integrated KBPMS. The paper has shown that the present hybrid (KB-AHP-GAP) approach to developing a KBPMS model is a realistic methodology. The combination of the KB-AHP-GAP approach allows detailed benchmarking of the PMS existing within a manufacturing organisation. Furthermore, this approach can assist in identifying and prioritising the key decisions that need to be actioned to overcome the existing PMS shortcomings.

No description available.