Integrating case based reasoning and geographic information systems in a planing support system: Çeşme Peninsula study

Thesis (Doctoral)--Izmir Institute of Technology, City and Regional Planning, Izmir, 2009Includes bibliographical references (leaves: 110-121)Text in English; Abstract: Turkish and Englishxii, 140 leavesUrban and regional planning is experiencing fundamental changes on the use of of computer-based models in planning practice and education. However, with this increased use, .Geographic Information Systems. (GIS) or .Computer Aided Design.(CAD) alone cannot serve all of the needs of planning. Computational approaches should be modified to deal better with the imperatives of contemporary planning by using artificial intelligence techniques in city planning process.The main aim of this study is to develop an integrated .Planning Support System. (PSS) tool for supporting the planning process. In this research, .Case Based Reasoning. (CBR) .an artificial intelligence technique- and .Geographic Information Systems. (GIS) .geographic analysis, data management and visualization techniqueare used as a major PSS tools to build a .Case Based System. (CBS) for knowledge representation on an operational study. Other targets of the research are to discuss the benefits of CBR method in city planning domain and to demonstrate the feasibility and usefulness of this technique in a PSS. .Çeşme Peninsula. case study which applied under the desired methodology is presented as an experimental and operational stage of the thesis.This dissertation tried to find out whether an integrated model which employing CBR&GIS could support human decision making in a city planning task. While the CBS model met many of predefined goals of the thesis, both advantages and limitations have been realized from findings when applied to the complex domain such as city planning

Aircraft electrical power system diagnostics, prognostics and health management

In recent years, the loads needing electrical power in military aircraft and civil jet keep increasing, this put huge pressure on the electrical power system (EPS). As EPS becomes more powerful and complex, its reliability and maintenance becomes difficult problems to designers, manufacturers and customers. To improve the mission reliability and reduce life cycle cost, the EPS needs health management. This thesis developed a set of generic health management methods for the EPS, which can monitor system status; diagnose faults/failures in component level correctly and predict impending faults/failures exactly and predict remaining useful life of critical components precisely. The writer compared a few diagnostic and prognostic approaches in detail, and then found suitable ones for EPS. Then the major components and key parameters needed to be monitored are obtained, after function hazard analysis and failure modes effects analysis of EPS. A diagnostic process is applied to EPS using Dynamic Case-based Reasoning approach, whilst hybrid prognostic methods are suggested to the system. After that, Diagnostic, Prognostic and Health Management architecture of EPS is built up in system level based on diagnostic and prognostic process. Finally, qualitative evaluations of DPHM explain given. This research is an extension of group design project (GDP) work, the GDP report is arranged in the Appendix A

Alliances and Accomplices Rise: A Critical Look at a Partnership with a School Serving an Indigenous Community

Conventional research in the social sciences roots itself in the colonial surmise behind the supremacist ideologies of Western and White knowledge, ways of living, people, and institutions. The well-established hegemony of the Western positivist research paradigm encourages a paternalistic and asymmetrical researcher-researched relationship, which reserves “legitimate” knowledge creation for an elite few. In this way, research traditions have largely functioned to uphold the status quo, especially when conducted with Indigenous peoples. Community-based research challenges the positivist empire by emphasizing community knowledge in researcher-community collaborations for the sake of taking action on community-identified issues. Mutually-beneficial researcher-community partnerships are especially relevant to research with Indigenous communities, who continue to fight marginalizing policies and practices in their fight for self-determination and tribal sovereignty. This critical case study highlights community voices as it tells the story of a CBR venture with non-Indigenous researchers and a school serving a Navajo community. Critical Indigenous Research Methodology (CIRM) (Brayboy et al., 2012) guided the process and findings illustrate the potential of CIRM to support CBR that: (a) disrupts rigid institutional norms; and (b) integrates IWOK. Implications for schools, researchers, and communities are outlined

Real-time Prediction of Cascading Failures in Power Systems

Blackouts in power systems cause major financial and societal losses, which necessitate devising better prediction techniques that are specifically tailored to detecting and preventing them. Since blackouts begin as a cascading failure (CF), an early detection of these CFs gives the operators ample time to stop the cascade from propagating into a large-scale blackout. In this thesis, a real-time load-based prediction model for CFs using phasor measurement units (PMUs) is proposed. The proposed model provides load-based predictions; therefore, it has the advantages of being applicable as a controller input and providing the operators with better information about the affected regions. In addition, it can aid in visualizing the effects of the CF on the grid. To extend the functionality and robustness of the proposed model, prediction intervals are incorporated based on the convergence width criterion (CWC) to allow the model to account for the uncertainties of the network, which was not available in previous works. Although this model addresses many issues in previous works, it has limitations in both scalability and capturing of transient behaviours. Hence, a second model based on recurrent neural network (RNN) long short-term memory (LSTM) ensemble is proposed. The RNN-LSTM is added to better capture the dynamics of the power system while also giving faster responses. To accommodate for the scalability of the model, a novel selection criterion for inputs is introduced to minimize the inputs while maintaining a high information entropy. The criteria include distance between buses as per graph theory, centrality of the buses with respect to fault location, and the information entropy of the bus. These criteria are merged using higher statistical moments to reflect the importance of each bus and generate indices that describe the grid with a smaller set of inputs. The results indicate that this model has the potential to provide more meaningful and accurate results than what is available in the previous literature and can be used as part of the integrated remedial action scheme (RAS) system either as a warning tool or a controller input as the accuracy of detecting affected regions reached 99.9% with a maximum delay of 400 ms. Finally, a validation loop extension is introduced to allow the model to self-update in real-time using importance sampling and case-based reasoning to extend the practicality of the model by allowing it to learn from historical data as time progresses

Tecnología para Tiendas Inteligentes

Trabajo de Fin de Grado en Doble Grado en Ingeniería Informática y Matemáticas, Facultad de Informática UCM, Departamento de Ingeniería del Software e Inteligencia Artificial, Curso 2020/2021Smart stores technologies exemplify how Artificial Intelligence and Internet of Things can effectively join forces to shape the future of retailing. With an increasing number of companies proposing and implementing their own smart store concepts, such as Amazon Go or Tao Cafe, a new field is clearly emerging. Since the technologies used to build their infrastructure offer significant competitive advantages, companies are not publicly sharing their own designs. For this reason, this work presents a new smart store model named Mercury, which aims to take the edge off of the lack of public and accessible information and research documents in this field. We do not only introduce a comprehensive smart store model, but also work-through a feasible detailed implementation so that anyone can build their own system upon it.Las tecnologías utilizadas en las tiendas inteligentes ejemplifican cómo la Inteligencia Artificial y el Internet de las Cosas pueden unir, de manera efectiva, fuerzas para transformar el futuro de la venta al por menor. Con un creciente número de empresas proponiendo e implementando sus propios conceptos de tiendas inteligentes, como Amazon Go o Tao Cafe, un nuevo campo está claramente emergiendo. Debido a que las tecnologías utilizadas para construir sus infraestructuras ofrecen una importante ventaja competitiva, las empresas no están compartiendo públicamente sus diseños. Por esta razón, este trabajo presenta un nuevo modelo de tienda inteligente llamado Mercury, que tiene como objetivo mitigar la falta de información pública y accesible en este campo. No solo introduciremos un modelo general y completo de tienda inteligente, sino que también proponemos una implementación detallada y concreta para que cualquier persona pueda construir su propia tienda inteligente siguiendo nuestro modelo.Depto. de Ingeniería de Software e Inteligencia Artificial (ISIA)Fac. de InformáticaTRUEunpu

Exploiting Locality and Parallelism with Hierarchically Tiled Arrays

The importance of tiles or blocks in mathematics and thus computer science cannot be overstated. From a high level point of view, they are the natural way to express many algorithms, both in iterative and recursive forms. Tiles or sub-tiles are used as basic units in the algorithm description. From a low level point of view, tiling, either as the unit maintained by the algorithm, or as a class of data layouts, is one of the most effective ways to exploit locality, which is a must to achieve good performance in current computers given the growing gap between memory and processor speed. Finally, tiles and operations on them are also basic to express data distribution and parallelism. Despite the importance of this concept, which makes inevitable its widespread usage, most languages do not support it directly. Programmers have to understand and manage the low-level details along with the introduction of tiling. This gives place to bloated potentially error-prone programs in which opportunities for performance are lost. On the other hand, the disparity between the algorithm and the actual implementation enlarges. This thesis illustrates the power of Hierarchically Tiled Arrays (HTAs), a data type which enables the easy manipulation of tiles in object-oriented languages. The objective is to evolve this data type in order to make the representation of all classes for algorithms with a high degree of parallelism and/or locality as natural as possible. We show in the thesis a set of tile operations which leads to a natural and easy implementation of different algorithms in parallel and in sequential with higher clarity and smaller size. In particular, two new language constructs dynamic partitioning and overlapped tiling are discussed in detail. They are extensions of the HTA data type to improve its capabilities to express algorithms with a high abstraction and free programmers from programming tedious low-level tasks. To prove the claims, two popular languages, C++ and MATLAB are extended with our HTA data type. In addition, several important dense linear algebra kernels, stencil computation kernels, as well as some benchmarks in NAS benchmark suite were implemented. We show that the HTA codes needs less programming effort with a negligible effect on performance

Emerging radiopharmaceuticals for PET-imaging gliomas. A multi-: radiopharmaceutical, camera, modality, model, and modelling assessment

Gliomas, which are a type of brain tumour derived from the non-neuronal and nutrient-supplying glial cells of the brain, are particularly devastating disease due to the importance and delicate nature of cerebral matter. Surgical removal, chemotherapy, and radiation therapy often have unwanted consequences depending on a variety of physiological and probability factors. With the human life expectancy averaging 12-15 months after clinical diagnosis (with treatment) for aggressive brain tumours, accurately detecting and characterizing these tumours non-invasively is important for treatment planning. Currently, the highest anatomical resolution imaging modality available for brain imaging is magnetic resonance imaging (MRI), but this lacks biochemical information. Positron emission tomography paired with computed tomography for anatomical reference (PET-CT) divulges quantifiable biochemical information. By selecting imaging radiopharmaceuticals for PET imaging that have relevance to tumour surface proteins or other cellular metabolic processes it is possible to not only aid in detecting or delineating gliomas, but also gain specific biochemical-property insight into these lesions. The aim of these studies was to evaluate the two emerging radiopharmaceuticals (2S, 4R)-4-[18F]fluoroglutamine ([18F]FGln) and Al[18F]F-NOTA-Folate ([18F]FOL) and to directly compare them with routinely clinically-used radiopharmaceuticals 2-deoxy-2-[18F]fluoro-ᴅ-glucose ([18F]FDG) and ʟ-[11C]methionine ([11C]Met) for the PET imaging of gliomas in animal models. Other parameters, such as the in vivo stability, ex vivo biodistribution, in vitro binding and blocking, and the presence of relevant receptors on human tissue samples were investigated in to divulge additional information. The results demonstrated that both [18F]FGln and [18F]FOL provided an enhanced level of contrast between tumour and adjacent non-tumour brain tissue versus that of the clinically used radiopharmaceuticals [18F]FDG and [11C]Met in animal models.Uudet radiolääkeaineet glioomien PET-kuvantamiseen. Tutkimuksia radiolääkeaineista, modaliteeteista, kameroista, kokeellisista malleista ja mallintamisesta Glioomat ovat aivokasvaimia, jotka syntyvät ravinteiden kuljetusta hoitavista glia- eli hermotukisoluista. Ne ovat erityisen tuhoisia sairauksia aivokudoksen tärkeyden ja herkkyyden vuoksi. Kirurgisella leikkauksella, kemoterapialla, ja sädehoidolla on usein ei-toivottuja seurauksia riippuen fysiologisista ja todennäköisyystekijöistä. Koska elinajanodote aggressiivisen aivokasvaimen diagnoosin jälkeen on keskimäärin 12–15 kuukautta (hoidon kanssa), ei-invasiivinen tarkka havaitseminen ja karakterisointi on tärkeää hoidon suunnittelussa. Tällä hetkellä parhaat työkalut aivojen kuvantamiseen ovat magneettikuvaus (MRI), joka mahdollistaa parhaimman anatomisen tarkkuuden, ja positroniemissiotomografia (PET), joka paljastaa biokemiallisen informaation. Valitsemalle PET-kuvantamiseen radiolääkeaine, joka kiinnittyy syöpäsolun pintaproteiineihin tai liittyy solun aineenvaihduntaprosessiin on mahdollista paitsi havaita tai rajata glioomia, myös saada erityistä biokemiallista tietoa näistä leesioista. Tämän tutkimuksen tavoitteena oli arvioida kahta uutta radiolääkeainetta; (2S, 4R)-4-[18F]fluoriglutamiinia ([18F]FGln) ja Al[18F]F-NOTA-folaattia ([18F]FOL) ja verrata niitä kliinisessä käytössä oleviin 2-deoxy-2-[18F]fluori-ᴅ-glukoosiin ([18F]FDG) ja ʟ-[11C]metioniiniin ([11C]Met) glioomien PET-kuvantamisessa. Stabiilisuutta, biologista jakautumista, sitoutumista ja sitoutumisen salpautumista, sekä farmakokineettista mallintamista tutkittiin in vivo, ex vivo ja in vitro olosuhteissa eläinmalleissa ja kudosnäytteillä. Tulokset osoittivat, että eläinmalleissa sekä [18F]FGln että [18F]FOL mahdollistavat paremman kontrastin tuumorin ja viereisen tuumorittoman aivokudoksen välillä verrattuna kliinisessä käytössä oleviin [18F]FDG ja [11C]Met radiolääkeaineisiin

Mechanisms underlying the regulation of Nedd4-family E3 Ubiquitin ligases

Nedd4-family enzymes play key roles in the establishment and regulation of both developmental and carcinogenic processes. Hence, profound studies of the catalytic mechanisms and detailed analysis of protein-specific regulation of these enzymes as presented in this thesis, contribute significantly to the understanding of HECT ligases but also may have implications for the development of pharmaceutical inhibitors

Satellite Networks: Architectures, Applications, and Technologies

Since global satellite networks are moving to the forefront in enhancing the national and global information infrastructures due to communication satellites' unique networking characteristics, a workshop was organized to assess the progress made to date and chart the future. This workshop provided the forum to assess the current state-of-the-art, identify key issues, and highlight the emerging trends in the next-generation architectures, data protocol development, communication interoperability, and applications. Presentations on overview, state-of-the-art in research, development, deployment and applications and future trends on satellite networks are assembled

Working Notes from the 1992 AAAI Spring Symposium on Practical Approaches to Scheduling and Planning

The symposium presented issues involved in the development of scheduling systems that can deal with resource and time limitations. To qualify, a system must be implemented and tested to some degree on non-trivial problems (ideally, on real-world problems). However, a system need not be fully deployed to qualify. Systems that schedule actions in terms of metric time constraints typically represent and reason about an external numeric clock or calendar and can be contrasted with those systems that represent time purely symbolically. The following topics are discussed: integrating planning and scheduling; integrating symbolic goals and numerical utilities; managing uncertainty; incremental rescheduling; managing limited computation time; anytime scheduling and planning algorithms, systems; dependency analysis and schedule reuse; management of schedule and plan execution; and incorporation of discrete event techniques