857 resultados para knowledge based reasoning


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Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six) months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason) of defective information.

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Report for the scientific sojourn carried out at the Model-based Systems and Qualitative Reasoning Group (Technical University of Munich), from September until December 2005. Constructed wetlands (CWs), or modified natural wetlands, are used all over the world as wastewater treatment systems for small communities because they can provide high treatment efficiency with low energy consumption and low construction, operation and maintenance costs. Their treatment process is very complex because it includes physical, chemical and biological mechanisms like microorganism oxidation, microorganism reduction, filtration, sedimentation and chemical precipitation. Besides, these processes can be influenced by different factors. In order to guarantee the performance of CWs, an operation and maintenance program must be defined for each Wastewater Treatment Plant (WWTP). The main objective of this project is to provide a computer support to the definition of the most appropriate operation and maintenance protocols to guarantee the correct performance of CWs. To reach them, the definition of models which represent the knowledge about CW has been proposed: components involved in the sanitation process, relation among these units and processes to remove pollutants. Horizontal Subsurface Flow CWs are chosen as a case study and the filtration process is selected as first modelling-process application. However, the goal is to represent the process knowledge in such a way that it can be reused for other types of WWTP.

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First and second instar larvae of some Sarcophagidae (Diptera) of the tribe Raviniini are described on observations with a scanning electron microscope.

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L1, L2 and L3 of Oxysarcodexia paulistanensis (Mattos), L3 of O. confusa Lopes, L2 of Ravinia belforti (Prado & Fonseca) and L2 of Oxyvinia excisa (Lopes) were described and figured using scanning electron microscope.

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Gestures are the first forms of conventional communication that young children develop in order to intentionally convey a specific message. However, at first, infants rarely communicate successfully with their gestures, prompting caregivers to interpret them. Although the role of caregivers in early communication development has been examined, little is known about how caregivers attribute a specific communicative function to infants' gestures. In this study, we argue that caregivers rely on the knowledge about the referent that is shared with infants in order to interpret what communicative function infants wish to convey with their gestures. We videotaped interactions from six caregiver-infant dyads playing with toys when infants were 8, 10, 12, 14, and 16 months old. We coded infants' gesture production and we determined whether caregivers interpreted those gestures as conveying a clear communicative function or not; we also coded whether infants used objects according to their conventions of use as a measure of shared knowledge about the referent. Results revealed an association between infants' increasing knowledge of object use and maternal interpretations of infants' gestures as conveying a clear communicative function. Our findings emphasize the importance of shared knowledge in shaping infants' emergent communicative skills.

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The aim of this study is to perform a thorough comparison of quantitative susceptibility mapping (QSM) techniques and their dependence on the assumptions made. The compared methodologies were: two iterative single orientation methodologies minimizing the l2, l1TV norm of the prior knowledge of the edges of the object, one over-determined multiple orientation method (COSMOS) and anewly proposed modulated closed-form solution (MCF). The performance of these methods was compared using a numerical phantom and in-vivo high resolution (0.65mm isotropic) brain data acquired at 7T using a new coil combination method. For all QSM methods, the relevant regularization and prior-knowledge parameters were systematically changed in order to evaluate the optimal reconstruction in the presence and absence of a ground truth. Additionally, the QSM contrast was compared to conventional gradient recalled echo (GRE) magnitude and R2* maps obtained from the same dataset. The QSM reconstruction results of the single orientation methods show comparable performance. The MCF method has the highest correlation (corrMCF=0.95, r(2)MCF =0.97) with the state of the art method (COSMOS) with additional advantage of extreme fast computation time. The l-curve method gave the visually most satisfactory balance between reduction of streaking artifacts and over-regularization with the latter being overemphasized when the using the COSMOS susceptibility maps as ground-truth. R2* and susceptibility maps, when calculated from the same datasets, although based on distinct features of the data, have a comparable ability to distinguish deep gray matter structures.

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Game theory describes and analyzes strategic interaction. It is usually distinguished between static games, which are strategic situations in which the players choose only once as well as simultaneously, and dynamic games, which are strategic situations involving sequential choices. In addition, dynamic games can be further classified according to perfect and imperfect information. Indeed, a dynamic game is said to exhibit perfect information, whenever at any point of the game every player has full informational access to all choices that have been conducted so far. However, in the case of imperfect information some players are not fully informed about some choices. Game-theoretic analysis proceeds in two steps. Firstly, games are modelled by so-called form structures which extract and formalize the significant parts of the underlying strategic interaction. The basic and most commonly used models of games are the normal form, which rather sparsely describes a game merely in terms of the players' strategy sets and utilities, and the extensive form, which models a game in a more detailed way as a tree. In fact, it is standard to formalize static games with the normal form and dynamic games with the extensive form. Secondly, solution concepts are developed to solve models of games in the sense of identifying the choices that should be taken by rational players. Indeed, the ultimate objective of the classical approach to game theory, which is of normative character, is the development of a solution concept that is capable of identifying a unique choice for every player in an arbitrary game. However, given the large variety of games, it is not at all certain whether it is possible to device a solution concept with such universal capability. Alternatively, interactive epistemology provides an epistemic approach to game theory of descriptive character. This rather recent discipline analyzes the relation between knowledge, belief and choice of game-playing agents in an epistemic framework. The description of the players' choices in a given game relative to various epistemic assumptions constitutes the fundamental problem addressed by an epistemic approach to game theory. In a general sense, the objective of interactive epistemology consists in characterizing existing game-theoretic solution concepts in terms of epistemic assumptions as well as in proposing novel solution concepts by studying the game-theoretic implications of refined or new epistemic hypotheses. Intuitively, an epistemic model of a game can be interpreted as representing the reasoning of the players. Indeed, before making a decision in a game, the players reason about the game and their respective opponents, given their knowledge and beliefs. Precisely these epistemic mental states on which players base their decisions are explicitly expressible in an epistemic framework. In this PhD thesis, we consider an epistemic approach to game theory from a foundational point of view. In Chapter 1, basic game-theoretic notions as well as Aumann's epistemic framework for games are expounded and illustrated. Also, Aumann's sufficient conditions for backward induction are presented and his conceptual views discussed. In Chapter 2, Aumann's interactive epistemology is conceptually analyzed. In Chapter 3, which is based on joint work with Conrad Heilmann, a three-stage account for dynamic games is introduced and a type-based epistemic model is extended with a notion of agent connectedness. Then, sufficient conditions for backward induction are derived. In Chapter 4, which is based on joint work with Jérémie Cabessa, a topological approach to interactive epistemology is initiated. In particular, the epistemic-topological operator limit knowledge is defined and some implications for games considered. In Chapter 5, which is based on joint work with Jérémie Cabessa and Andrés Perea, Aumann's impossibility theorem on agreeing to disagree is revisited and weakened in the sense that possible contexts are provided in which agents can indeed agree to disagree.

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Report for the scientific sojourn at the University of California at Berkeley, USA, from september 2007 until july 2008. Communities of Learning Practice is an innovative paradigm focused on providing appropriate technological support to both formal and especially informal learning groups who are chiefly formed by non-technical people and who lack of the necessary resources to acquire such systems. Typically, students who are often separated by geography and/or time have the need to meet each other after classes in small study groups to carry out specific learning activities assigned during the formal learning process. However, the lack of suitable and available groupware applications makes it difficult for these groups of learners to collaborate and achieve their specific learning goals. In addition, the lack of democratic decision-making mechanisms is a main handicap to substitute the central authority of knowledge presented in formal learning.

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This paper presents the use of a mobile robot platform as an innovative educational tool in order to promote and integrate different curriculum knowledge. Hence, it is presented the acquired experience within a summer course named ldquoapplied mobile roboticsrdquo. The main aim of the course is to integrate different subjects as electronics, programming, architecture, perception systems, communications, control and trajectory planning by using the educational open mobile robot platform PRIM. The summer course is addressed to a wide range of student profiles. However, it is of special interests to the students of electrical and computer engineering around their final academic year. The summer course consists of the theoretical and laboratory sessions, related to the following topics: design & programming of electronic devices, modelling and control systems, trajectory planning and control, and computer vision systems. Therefore, the clues for achieving a renewed path of progress in robotics are the integration of several knowledgeable fields, such as computing, communications, and control sciences, in order to perform a higher level reasoning and use decision tools with strong theoretical base

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Aims and objectives  This study aimed to determine the discriminant validity and the test-retest reliability of a questionnaire testing the impact of evidence-based medicine (EBM) training on doctors' knowledge and skills. Methods  Questionnaires were sent electronically to all doctors working as residents and chief residents in two French speaking hospital networks in Switzerland. Participants completed the questionnaire twice, within a 4-week interval. The discriminant validity was examined in comparing doctors' performance according to their reported EBM previous training. Proportion of agreement between both sessions of the questionnaire, Cohen's kappa and 'uniform kappa' determined its test-retest reliability. Results  The participation rate was 9.8%/7.1% to first/second session. Performance increased according to the level of doctors' previous training in EBM. The observed proportion of agreement between both sessions was over 70% for 14/19 questions, and the 'uniform kappa' was superior to 0.60 for 15/19 questions. Conclusion  The discriminant validity and test-retest reliability of the questionnaire were satisfying. The low participation rate did not prevent the study from achieving its aims.

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The pace of development of new healthcare technologies and related knowledge is very fast. Implementation of high quality evidence-based knowledge is thus mandatory to warrant an effective healthcare system and patient safety. However, even though only a small fraction of the approximate 2500 scientific publication indexed daily in Medline is actually useful to clinical practice, the amountof the new information is much too large to allow busy healthcare professionals to stay aware of possibly important evidence-based information.

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Abstract Since its creation, the Internet has permeated our daily life. The web is omnipresent for communication, research and organization. This exploitation has resulted in the rapid development of the Internet. Nowadays, the Internet is the biggest container of resources. Information databases such as Wikipedia, Dmoz and the open data available on the net are a great informational potentiality for mankind. The easy and free web access is one of the major feature characterizing the Internet culture. Ten years earlier, the web was completely dominated by English. Today, the web community is no longer only English speaking but it is becoming a genuinely multilingual community. The availability of content is intertwined with the availability of logical organizations (ontologies) for which multilinguality plays a fundamental role. In this work we introduce a very high-level logical organization fully based on semiotic assumptions. We thus present the theoretical foundations as well as the ontology itself, named Linguistic Meta-Model. The most important feature of Linguistic Meta-Model is its ability to support the representation of different knowledge sources developed according to different underlying semiotic theories. This is possible because mast knowledge representation schemata, either formal or informal, can be put into the context of the so-called semiotic triangle. In order to show the main characteristics of Linguistic Meta-Model from a practical paint of view, we developed VIKI (Virtual Intelligence for Knowledge Induction). VIKI is a work-in-progress system aiming at exploiting the Linguistic Meta-Model structure for knowledge expansion. It is a modular system in which each module accomplishes a natural language processing task, from terminology extraction to knowledge retrieval. VIKI is a supporting system to Linguistic Meta-Model and its main task is to give some empirical evidence regarding the use of Linguistic Meta-Model without claiming to be thorough.

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Cape Verde is considered part of Sahelian Africa, where drought and desertification are common occurrences. The main activity of the rural population is rain-fed agriculture, which over time has been increasingly challenged by high temporal and spatial rainfall variability, lack of inputs, limited land area, fragmentation of land, steep slopes, pests, lack of mechanization and loss of top soil by water erosion. Human activities, largely through poor farming practices and deforestation (Gomez, 1989) have accelerated natural erosion processes, shifting the balance between soil erosion and soil formation (Norton, 1987). According to previous studies, vegetation cover is one of the most important factors in controlling soil loss (Cyr et al., 1995; Hupy, 2004; Zhang et al., 2004; Zhou et al., 2006). For this reason, reforestation is a touchstone of the Cape Verdean policy to combat desertification. After Independence in 1975, the Cape Verde government had pressing and closely entangled environmental and socio-economic issues to address, as long-term desertification had resulted in a lack of soil cover, severe soil erosion and a scarcity of water resources and fuel wood. Across the archipelago, desertification was resulting from a variety of processes including poor farming practices, soil erosion by water and wind, soil and water salinity in coastal areas due to over pumping and seawater intrusion, drought and unplanned urbanization (DGA-MAAP, 2004). All these issues directly affected socio-economic vulnerability in rural areas, where about 70% of people depended directly or indirectly on agriculture in 1975. By becoming part of the Inter- State Committee for the Fight against Drought in the Sahel in 1975, the government of Cape Verde gained structured support to address these issues more efficiently. Presentday policies and strategies were defined on the basis of rational use of resources and human efforts and were incorporated into three subsequent national plans: the National Action Plan for Development (NDP) (1982–1986), the NDP (1986–1990) and the NDP (1991–1995) (Carvalho

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More than 60% of neuroendocrine tumours, also called carcinoids, are localised within the gastrointestinal tract. Small bowel neuroendocrine tumours have been diagnosed with increasing frequency over the past 35 years, being the second most frequent tumours of the small intestine. Ileal neuroendocrine tumours diagnosis is late because patients have non-specific symptoms. We have proposed to illustrate as an example the case of a patient, and on its basis, to make a brief review of the literature on small bowel neuroendocrine tumours, resuming several recent changes in the field, concerning classification criteria of these tumours and new recommendations and current advances in diagnosis and treatment. This patient came to our emergency department with a complete bowel obstruction, along with a 2-year history of peristaltic abdominal pain, vomits and diarrhoea episodes. During emergency laparotomy, an ileal stricture was observed, that showed to be a neuroendocrine tumour of the small bowel.