997 resultados para Intuitive Knowledge
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ABSTRACT When Hume, in the Treatise on Human Nature, began his examination of the relation of cause and effect, in particular, of the idea of necessary connection which is its essential constituent, he identified two preliminary questions that should guide his research: (1) For what reason we pronounce it necessary that every thing whose existence has a beginning should also have a cause and (2) Why we conclude that such particular causes must necessarily have such particular effects? (1.3.2, 14-15) Hume observes that our belief in these principles can result neither from an intuitive grasp of their truth nor from a reasoning that could establish them by demonstrative means. In particular, with respect to the first, Hume examines and rejects some arguments with which Locke, Hobbes and Clarke tried to demonstrate it, and suggests, by exclusion, that the belief that we place on it can only come from experience. Somewhat surprisingly, however, Hume does not proceed to show how that derivation of experience could be made, but proposes instead to move directly to an examination of the second principle, saying that, "perhaps, be found in the end, that the same answer will serve for both questions" (1.3.3, 9). Hume's answer to the second question is well known, but the first question is never answered in the rest of the Treatise, and it is even doubtful that it could be, which would explain why Hume has simply chosen to remove any mention of it when he recompiled his theses on causation in the Enquiry concerning Human Understanding. Given this situation, an interesting question that naturally arises is to investigate the relations of logical or conceptual implication between these two principles. Hume seems to have thought that an answer to (2) would also be sufficient to provide an answer to (1). Henry Allison, in his turn, argued (in Custom and Reason in Hume, p. 94-97) that the two questions are logically independent. My proposal here is to try to show that there is indeed a logical dependency between them, but the implication is, rather, from (1) to (2). If accepted, this result may be particularly interesting for an interpretation of the scope of the so-called "Kant's reply to Hume" in the Second Analogy of Experience, which is structured as a proof of the a priori character of (1), but whose implications for (2) remain controversial.
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The proposal presented in this thesis is to provide designers of knowledge based supervisory systems of dynamic systems with a framework to facilitate their tasks avoiding interface problems among tools, data flow and management. The approach is thought to be useful to both control and process engineers in assisting their tasks. The use of AI technologies to diagnose and perform control loops and, of course, assist process supervisory tasks such as fault detection and diagnose, are in the scope of this work. Special effort has been put in integration of tools for assisting expert supervisory systems design. With this aim the experience of Computer Aided Control Systems Design (CACSD) frameworks have been analysed and used to design a Computer Aided Supervisory Systems (CASSD) framework. In this sense, some basic facilities are required to be available in this proposed framework: ·
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This article explores the fine detail of practice by three teachers, recognised as effective teachers of literacy. All three were observed during nine literacy lessons, working with Year 2 (6/7 year olds) classes of successful inner-city primary schools in the South of England. Data collection took place in 2003, just as their schools were moving away from the early prescription of the National Literacy Strategy (NLS), and follow up visits were made in 2005. My initial interest had been in what these three teachers did with the NLS in order to motivate pupils and ensure high pupil attainment. Following observations, interviews and coding of teacher-pupil interaction, it became clear that The NLS Framework for Teaching (DfES, 2001) was not the driver of their success but a valuable vehicle for subtle and intuitive teacher behaviours that grew from a detailed understanding of how children develop as readers and writers. Implications for training student teachers to marry theoretical understanding with the expectations of a prescribed curriculum for literacy are discussed.
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The analysis of large amounts of data is better performed by humans when represented in a graphical format. Therefore, a new research area called the Visual Data Mining is being developed endeavoring to use the number crunching power of computers to prepare data for visualization, allied to the ability of humans to interpret data presented graphically.This work presents the results of applying a visual data mining tool, called FastMapDB to detect the behavioral pattern exhibited by a dataset of clinical information about hemoglobinopathies known as thalassemia. FastMapDB is a visual data mining tool that get tabular data stored in a relational database such as dates, numbers and texts, and by considering them as points in a multidimensional space, maps them to a three-dimensional space. The intuitive three-dimensional representation of objects enables a data analyst to see the behavior of the characteristics from abnormal forms of hemoglobin, highlighting the differences when compared to data from a group without alteration.
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Research into intuitive problem solving has shown that objective closeness of participants' hypotheses were closer to the accurate solution than their subjective ratings of closeness. After separating conceptually intuitive problem solving from the solutions of rational incremental tasks and of sudden insight tasks, we replicated this finding by using more precise measures in a conceptual problem-solving task. In a second study, we distinguished performance level, processing style, implicit knowledge and subjective feeling of closeness to the solution within the problem-solving task and examined the relationships of these different components with measures of intelligence and personality. Verbal intelligence correlated with performance level in problem solving, but not with processing style and implicit knowledge. Faith in intuition, openness to experience, and conscientiousness correlated with processing style, but not with implicit knowledge. These findings suggest that one needs to decompose processing style and intuitive components in problem solving to make predictions on effects of intelligence and personality measures.
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Tradicionalmente, el uso de técnicas de análisis de datos ha sido una de las principales vías para el descubrimiento de conocimiento oculto en grandes cantidades de datos, recopilados por expertos en diferentes dominios. Por otra parte, las técnicas de visualización también se han usado para mejorar y facilitar este proceso. Sin embargo, existen limitaciones serias en la obtención de conocimiento, ya que suele ser un proceso lento, tedioso y en muchas ocasiones infructífero, debido a la dificultad de las personas para comprender conjuntos de datos de grandes dimensiones. Otro gran inconveniente, pocas veces tenido en cuenta por los expertos que analizan grandes conjuntos de datos, es la degradación involuntaria a la que someten a los datos durante las tareas de análisis, previas a la obtención final de conclusiones. Por degradación quiere decirse que los datos pueden perder sus propiedades originales, y suele producirse por una reducción inapropiada de los datos, alterando así su naturaleza original y llevando en muchos casos a interpretaciones y conclusiones erróneas que podrían tener serias implicaciones. Además, este hecho adquiere una importancia trascendental cuando los datos pertenecen al dominio médico o biológico, y la vida de diferentes personas depende de esta toma final de decisiones, en algunas ocasiones llevada a cabo de forma inapropiada. Ésta es la motivación de la presente tesis, la cual propone un nuevo framework visual, llamado MedVir, que combina la potencia de técnicas avanzadas de visualización y minería de datos para tratar de dar solución a estos grandes inconvenientes existentes en el proceso de descubrimiento de información válida. El objetivo principal es hacer más fácil, comprensible, intuitivo y rápido el proceso de adquisición de conocimiento al que se enfrentan los expertos cuando trabajan con grandes conjuntos de datos en diferentes dominios. Para ello, en primer lugar, se lleva a cabo una fuerte disminución en el tamaño de los datos con el objetivo de facilitar al experto su manejo, y a la vez preservando intactas, en la medida de lo posible, sus propiedades originales. Después, se hace uso de efectivas técnicas de visualización para representar los datos obtenidos, permitiendo al experto interactuar de forma sencilla e intuitiva con los datos, llevar a cabo diferentes tareas de análisis de datos y así estimular visualmente su capacidad de comprensión. De este modo, el objetivo subyacente se basa en abstraer al experto, en la medida de lo posible, de la complejidad de sus datos originales para presentarle una versión más comprensible, que facilite y acelere la tarea final de descubrimiento de conocimiento. MedVir se ha aplicado satisfactoriamente, entre otros, al campo de la magnetoencefalografía (MEG), que consiste en la predicción en la rehabilitación de lesiones cerebrales traumáticas (Traumatic Brain Injury (TBI) rehabilitation prediction). Los resultados obtenidos demuestran la efectividad del framework a la hora de acelerar y facilitar el proceso de descubrimiento de conocimiento sobre conjuntos de datos reales. ABSTRACT Traditionally, the use of data analysis techniques has been one of the main ways of discovering knowledge hidden in large amounts of data, collected by experts in different domains. Moreover, visualization techniques have also been used to enhance and facilitate this process. However, there are serious limitations in the process of knowledge acquisition, as it is often a slow, tedious and many times fruitless process, due to the difficulty for human beings to understand large datasets. Another major drawback, rarely considered by experts that analyze large datasets, is the involuntary degradation to which they subject the data during analysis tasks, prior to obtaining the final conclusions. Degradation means that data can lose part of their original properties, and it is usually caused by improper data reduction, thereby altering their original nature and often leading to erroneous interpretations and conclusions that could have serious implications. Furthermore, this fact gains a trascendental importance when the data belong to medical or biological domain, and the lives of people depends on the final decision-making, which is sometimes conducted improperly. This is the motivation of this thesis, which proposes a new visual framework, called MedVir, which combines the power of advanced visualization techniques and data mining to try to solve these major problems existing in the process of discovery of valid information. Thus, the main objective is to facilitate and to make more understandable, intuitive and fast the process of knowledge acquisition that experts face when working with large datasets in different domains. To achieve this, first, a strong reduction in the size of the data is carried out in order to make the management of the data easier to the expert, while preserving intact, as far as possible, the original properties of the data. Then, effective visualization techniques are used to represent the obtained data, allowing the expert to interact easily and intuitively with the data, to carry out different data analysis tasks, and so visually stimulating their comprehension capacity. Therefore, the underlying objective is based on abstracting the expert, as far as possible, from the complexity of the original data to present him a more understandable version, thus facilitating and accelerating the task of knowledge discovery. MedVir has been succesfully applied to, among others, the field of magnetoencephalography (MEG), which consists in predicting the rehabilitation of Traumatic Brain Injury (TBI). The results obtained successfully demonstrate the effectiveness of the framework to accelerate and facilitate the process of knowledge discovery on real world datasets.
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Currently there is no structured data standard for representing elements commonly found in transmedia fictional universes. There are websites dedicated to individual universes, however, information found on these sites separates the various formats into books, movies, comics, etc.; concentrate on only the bibliographic aspects of the material; and are only full-text searchable. We have created an ontological model that will allow researchers, fans, brand managers, and creators to search for and retrieve the information contained in these worlds based on how they are structured. We conducted a domain analysis and user studies based on the contents of Harry Potter, Lord of the Rings, the Marvel Universe, and Star Wars in order to build a new model using the Ontology Web Language (OWL) and an artificial intelligence reasoning engine. This model can infer connections between characters, elements of power, items, places, events, etc. This model will facilitate better search and retrieval of the information contained within these vast story universes for all users interested in them. The result of this project is and OWL ontology that is intuitive for users; can be used by AI systems; and has been updated to reflect real user needs based on user research.
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Rated trust in intuitive efficacy (measured as trust, belief, use, accuracy and weighting of intuition) was investigated as a predictor of self-designated use of intuitive (hunch and hunch plus evidential belief) vs. deliberative (evidential belief and evidential belief plus hunch) deception detection judgments and actual accuracy. Twenty-nine student participants were filmed as they made true and deceptive statements about their everyday activities on a given evening (last Friday night), and college students (N=238) judged 20 (10=true, 10=deceptive) of these filmed statements as truthful or deceptive. Participants provided ratings of reliance on hunches vs. evidential belief, confidence in film judgments, intuitive efficacy, accuracy in deception detection, reliance on cues to deception, and experiences with intuition. Generalized estimated equation modeling using binary logistics demonstrated accuracy in identifying true vs. deceptive statements was predicted by film number, hunch-evidence ratings, weighting of intuition, and total cues cited. Weighting of intuition was predictive of accuracy across participants, with higher weighting predictive of higher accuracy in general. Participants who cited evidential belief plus hunch and moderate to high weighting incorrectly reversed their true vs. deceptive judgments. Accuracy for true statements was higher for hunches and hunch plus evidential belief, whereas accuracy for deceptive statements was higher for evidential belief Accuracy for participants who relied on evidential belief plus hunch was at chance. Subjective experiences underlying judgments differed by participant and type of film viewed (true vs. deceptive) and were predicted by hunch-evidence ratings, trust, use, intuitive accuracy, and total cues cited. Trust predicted increases in judging films to be true, whereas use and accuracy predicted increases in judging films as deceptive; none were predictive of accuracy. Increased number of cues cited predicted judgments of deception, whereas decreased number of cues cited predicted truth. The study concluded that participants have the capacity to self-define their judgments as subjectively vs. deliberately based, provide subjective assessments of the influence of intuitive vs. objective information on their judgments, and can apply this self-knowledge, through effective weighting of intuition vs. other types of information, in making accurate judgments of true and deceptive everyday statements.
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It is widely accepted that knowledge of certain of one’s own mental states is authoritative in being epistemically more secure than knowledge of the mental states of others, and theories of self-knowledge have largely appealed to one or the other of two sources to explain this special epistemic status. The first, ‘detectivist’, position, appeals to an inner perception-like basis, whereas the second, ‘constitutivist’, one, appeals to the view that the special security awarded to certain self-knowledge is a conceptual matter. I argue that there is a fundamental class of cases of authoritative self-knowledge, ones in which subjects are consciously thinking about their current, conscious intentional states, that is best accounted for in terms of a theory that is,
broadly speaking, introspectionist and detectivist. The position developed has an intuitive plausibility that has inspired many who work in the Cartesian tradition, and the potential to yield a single treatment of the basis of authoritative self-knowledge for both intentional states and sensation states.
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It is widely accepted that knowledge of certain of one’s own mental states is authoritative in being epistemically more secure than knowledge of the mental states of others, and theories of self-knowledge have largely appealed to one or the other of two sources to explain this special epistemic status. The first, ‘detectivist’, position, appeals to an inner perception-like basis, whereas the second, ‘constitutivist’, one, appeals to the view that the special security awarded to certain self-knowledge is a conceptual matter. I argue that there is a fundamental class of cases of authoritative self-knowledge, ones in which subjects are consciously thinking about their current, conscious intentional states, that is best accounted for in terms of a theory that is, broadly speaking, introspectionist and detectivist. The position developed has an intuitive plausibility that has inspired many who work in the Cartesian tradition, and the potential to yield a single treatment of the basis of authoritative self-knowledge for both intentional states and sensation states.
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This study investigates the practices involved in the production of knowledge about menopause at Caism, Unicamp, a reference center for public policies for women's health. Gynecological appointments and psychological support meetings were observed, and women and doctors were interviewed in order to identify what discourse circulates there and how different actors are brought in to ensure that the knowledge produced attains credibility and travels beyond the boundaries of the teaching hospital to become universal. The analysis is based on localized studies aligned with social studies of science and technology.
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This study investigates the practices involved in the production of knowledge about menopause at Caism, Unicamp, a reference center for public policies for women's health. Gynecological appointments and psychological support meetings were observed, and women and doctors were interviewed in order to identify what discourse circulates there and how different actors are brought in to ensure that the knowledge produced attains credibility and travels beyond the boundaries of the teaching hospital to become universal. The analysis is based on localized studies aligned with social studies of science and technology.
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Universidade Estadual de Campinas . Faculdade de Educação Física
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Universidade Estadual de Campinas . Faculdade de Educação Física
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Dental caries is a transmissible infectious disease in which mutans streptococci are generally considered to be the main etiological agents. Although the transmissibility of dental caries is relatively well established in the literature, little is known whether information regarding this issue is correctly provided to the population. The present study aimed at evaluating, by means of a questionnaire, the knowledge and usual attitude of 640 parents and caretakers regarding the transmissibility of caries disease. Most interviewed adults did not know the concept of dental caries being an infectious and transmissible disease, and reported the habit of blowing and tasting food, sharing utensils and kissing the children on their mouth. 372 (58.1%) adults reported that their children had already been seen by a dentist, 264 (41.3%) answered that their children had never gone to a dentist, and 4 (0.6%) did not know. When the adults were asked whether their children had already had dental caries, 107 (16.7%) answered yes, 489 (76.4%) answered no, and 44 (6.9%) did not know. Taken together, these data reinforce the need to provide the population with some important information regarding the transmission of dental caries in order to facilitate a more comprehensive approach towards the prevention of the disease.