894 resultados para Relational Reasoning


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There may be advantages to be gained by combining Case-Based Reasoning (CBR) techniques with numerical models. In this paper we consider how CBR can be used as a flexible query engine to improve the usability of numerical models. Particularly they can help to solve inverse and mixed problems, and to solve constraint problems. We discuss this idea with reference to the illustrative example of a pneumatic conveyor. We describe a model of the problem of particle degradation in such a conveyor, and the problems faced by design engineers. The solution of these problems requires a system that allows iterative sharing of control between user, CBR system, and numerical model. This multi-initiative interaction is illustrated for the pneumatic conveyor by means of Unified Modeling Language (UML) collaboration and sequence diagrams. We show approaches to the solution of these problems via a CBR tool.

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INTRODUCTION: The current study aimed to describe the relational and reproductive trajectories leading to adolescent pregnancy in Portugal, and to explore whether there were differences in this process according to adolescents' place of residence. MATERIAL AND METHODS: Data were collected between 2008 and 2013 in 42 public health services using a self-report questionnaire developed by the researchers. The sample consisted of a nationally representative group of pregnant adolescents (n = 459). RESULTS: Regardless of having had one (59.91%) or multiple sexual partners (40.09%), the majority of adolescents became pregnant in a romantic relationship, using contraception at the time of the conception and knowing the contraceptive failure which led to pregnancy (39.22%). In some regions other trajectories were highly prevalent, reflecting options such as planning the pregnancy (Alentejo Region/ Azores Islands), not using contraception (Centro Region/Madeira Islands) or using it incorrectly, without identifying the contraceptive failure (Madeira Islands). On average, romantic relationships were longer than 19 months and adolescents' partners were older than themselves (> 4 years) and no longer in school (75.16%); these results were particularly significant when the pregnancy was planned. DISCUSSION: The knowledge gained in this study shows that prevention efforts must be targeted according to the adolescents' needs in each region and should include high-risk male groups. CONCLUSION: Our results may enable more efficient health policies to prevent adolescent pregnancy in different country regions and support educators and health care providers on sexual education and family planning efforts.

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In this paper, we present a case-based reasoning (CBR) approach solving educational time-tabling problems. Following the basic idea behind CBR, the solutions of previously solved problems are employed to aid finding the solutions for new problems. A list of feature-value pairs is insufficient to represent all the necessary information. We show that attribute graphs can represent more information and thus can help to retrieve re-usable cases that have similar structures to the new problems. The case base is organised as a decision tree to store the attribute graphs of solved problems hierarchically. An example is given to illustrate the retrieval, re-use and adaptation of structured cases. The results from our experiments show the effectiveness of the retrieval and adaptation in the proposed method.

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The structured representation of cases by attribute graphs in a Case-Based Reasoning (CBR) system for course timetabling has been the subject of previous research by the authors. In that system, the case base is organised as a decision tree and the retrieval process chooses those cases which are sub attribute graph isomorphic to the new case. The drawback of that approach is that it is not suitable for solving large problems. This paper presents a multiple-retrieval approach that partitions a large problem into small solvable sub-problems by recursively inputting the unsolved part of the graph into the decision tree for retrieval. The adaptation combines the retrieved partial solutions of all the partitioned sub-problems and employs a graph heuristic method to construct the whole solution for the new case. We present a methodology which is not dependant upon problem specific information and which, as such, represents an approach which underpins the goal of building more general timetabling systems. We also explore the question of whether this multiple-retrieval CBR could be an effective initialisation method for local search methods such as Hill Climbing, Tabu Search and Simulated Annealing. Significant results are obtained from a wide range of experiments. An evaluation of the CBR system is presented and the impact of the approach on timetabling research is discussed. We see that the approach does indeed represent an effective initialisation method for these approaches.

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This paper studies Knowledge Discovery (KD) using Tabu Search and Hill Climbing within Case-Based Reasoning (CBR) as a hyper-heuristic method for course timetabling problems. The aim of the hyper-heuristic is to choose the best heuristic(s) for given timetabling problems according to the knowledge stored in the case base. KD in CBR is a 2-stage iterative process on both case representation and the case base. Experimental results are analysed and related research issues for future work are discussed.

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This paper presents a new hyper-heuristic method using Case-Based Reasoning (CBR) for solving course timetabling problems. The term Hyper-heuristics has recently been employed to refer to 'heuristics that choose heuristics' rather than heuristics that operate directly on given problems. One of the overriding motivations of hyper-heuristic methods is the attempt to develop techniques that can operate with greater generality than is currently possible. The basic idea behind this is that we maintain a case base of information about the most successful heuristics for a range of previous timetabling problems to predict the best heuristic for the new problem in hand using the previous knowledge. Knowledge discovery techniques are used to carry out the training on the CBR system to improve the system performance on the prediction. Initial results presented in this paper are good and we conclude by discussing the con-siderable promise for future work in this area.

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An earlier Case-based Reasoning (CBR) approach developed by the authors for educational course timetabling problems employed structured cases to represent the complex relationships between courses. Previous solved cases represented by attribute graphs were organized hierarchically into a decision tree. The retrieval searches for graph isomorphism among these attribute graphs. In this paper, the approach is further developed to solve a wider range of problems. We also attempt to retrieve those graphs that have common similar structures but also have some differences. Costs that are assigned to these differences have an input upon the similarity measure. A large number of experiments are performed consisting of different randomly produced timetabling problems and the results presented here strongly indicate that a CBR approach could provide a significant step forward in the development of automated system to solve difficult timetabling problems. They show that using relatively little effort, we can retrieve these structurally similar cases to provide high quality timetables for new timetabling problems.

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The structured representation of cases by attribute graphs in a Case-Based Reasoning (CBR) system for course timetabling has been the subject of previous research by the authors. In that system, the case base is organised as a decision tree and the retrieval process chooses those cases which are sub attribute graph isomorphic to the new case. The drawback of that approach is that it is not suitable for solving large problems. This paper presents a multiple-retrieval approach that partitions a large problem into small solvable sub-problems by recursively inputting the unsolved part of the graph into the decision tree for retrieval. The adaptation combines the retrieved partial solutions of all the partitioned sub-problems and employs a graph heuristic method to construct the whole solution for the new case. We present a methodology which is not dependant upon problem specific information and which, as such, represents an approach which underpins the goal of building more general timetabling systems. We also explore the question of whether this multiple-retrieval CBR could be an effective initialisation method for local search methods such as Hill Climbing, Tabu Search and Simulated Annealing. Significant results are obtained from a wide range of experiments. An evaluation of the CBR system is presented and the impact of the approach on timetabling research is discussed. We see that the approach does indeed represent an effective initialisation method for these approaches.

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The subject of the text is the issue of the "political", which is defined as the nature and level of the final judgment and ultimate reasoning. The issues of this kind of the "political" has been attempted to distinguish in political sciences. The text focuses on: (1) the scientist as an agent for the final judgment and reasoning, (2) the subject of study of political science, (3) "theoretical strategies" in the science of politics. The latter problem has been discussed mainly on the example of Polish political science. Discussed were among others: (1) "the dilemma of scale", (2) limited operational capacity (methodological and theoretical), (3) aesthetic imagery of political life, (4) structural ignorance in the field of ontology, epistemology and methodology.

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Hybrid logic is a valuable tool for specifying relational structures, at the same time that allows defining accessibility relations between states, it provides a way to nominate and make mention to what happens at each specific state. However, due to the many sources nowadays available, we may need to deal with contradictory information. This is the reason why we came with the idea of Quasi-hybrid logic, which is a paraconsistent version of hybrid logic capable of dealing with inconsistencies in the information, written as hybrid formulas. In [5] we have already developed a semantics for this paraconsistent logic. In this paper we go a step forward, namely we study its proof-theoretical aspects. We present a complete tableau system for Quasi-hybrid logic, by combining both tableaux for Quasi-classical and Hybrid logics.

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Abstract not available

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Parlare di KeyCrime significa rapportarsi con un software che si fonda prioritariamente su di un metodo scientifico che fa proprio il ragionamento conclusivo (conclusive reasoning), applicato al decison making , pertanto all’intelligence investigativa e alla predictive policing. Potremmo pensare a KeyCrime come un paradigma operativo che si pone in sinergia tra la filosofia, il cognitivismo giuridico e le scienze applicate (Romeo F., 2006). Quando analisi e decision making trovano in un unico contesto il terreno fertile dove svilupparsi, ma ancor più, creare presupposti di ragionamento, ecco che da queste è facile comprendere da quale altra condizione sono nate, attivate e soprattutto utilizzate ai fini di un risultato: questa non è altro che “l’osservazione”; se ben fatta, profonda e scientifica offre una sistematica quanto utile predisposizione alle indagini, specialmente di carattere preventivo per l’anticrimine e la sicurezza.

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There is clear evidence that in typically developing children reasoning and sense-making are essential in all mathematical learning and understanding processes. In children with autism spectrum disorders (ASD), however, these become much more significant, considering their importance to successful independent living. This paper presents a preliminary proposal of a digital environment, specifically targeted to promote the development of mathematical reasoning in students with ASD. Given the diversity of ASD, the prototyping of this environment requires the study of dynamic adaptation processes and the development of activities adjusted to each user’s profile. We present the results obtained during the first phase of this ongoing research, describing a conceptual model of the proposed digital environment. Guidelines for future research are also discussed.