Search results for: Case Based Reasoning

Authors: Alexander P. Eremeev, Ivan E. Kurilenko, Pavel R. Varshavskiy

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In this paper, the problem of the application of temporal reasoning and case-based reasoning in intelligent decision support systems is considered. The method of case-based reasoning with temporal dependences for the solution of problems of real-time diagnostics and forecasting in intelligent decision support systems is described. This paper demonstrates how the temporal case-based reasoning system can be used in intelligent decision support systems of the car access control. This work was supported by RFBR.

Keywords: analogous reasoning, case-based reasoning, intelligent decision support systems, temporal reasoning

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Authors: D. Zhang, H. Y. Du, G. W. Li, J. Zeng, D. W. Zuo, Y. P. You

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For the difficult issues of process selection, case-based reasoning technology is applied to computer aided process planning system for cold form tapping of internal threads on the basis of similarity in the process. A model is established based on the analysis of process planning. Case representation and similarity computing method are given. Confidence degree is used to evaluate the case. Rule-based reuse strategy is presented. The scheme is illustrated and verified by practical application. The case shows the design results with the proposed method are effective.

Keywords: case-based reasoning, internal thread, cold extrusion, process planning

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Authors: Mikhail Zarechnev, Bora I. Kumova

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A syllogism is a deductive inference scheme used to derive a conclusion from a set of premises. In a categorical syllogisms, there are only two premises and every premise and conclusion is given in form of a quantified relationship between two objects. The different order of objects in premises give classification known as figures. We have shown that the ordered combinations of 3 generalized quantifiers with certain figure provide in total of 108 syllogistic moods which can be considered as different inference rules. The classical syllogistic system allows to model human thought and reasoning with syllogistic structures always attracted the attention of cognitive scientists. Since automated reasoning is considered as part of learning subsystem of AI agents, syllogistic system can be applied for this approach. Another application of syllogistic system is related to inference mechanisms on the Semantic Web applications. In this paper we proposed the mathematical model and algorithm for syllogistic reasoning. Also the model of iterative syllogistic reasoning in case of continuous flows of incoming data based on case–based reasoning and possible applications of proposed system were discussed.

Keywords: categorical syllogism, case-based reasoning, cognitive architecture, inference on the semantic web, syllogistic reasoning

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Authors: Yang Cui, Yong Qiang Chen

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An appropriate project delivery system (PDS) is crucial to the success of a construction project. Case-based reasoning (CBR) is a useful support for PDS selection. However, the traditional CBR approach represents cases as attribute-value vectors without taking relations among attributes into consideration, and could not calculate the similarity when the structures of cases are not strictly same. Therefore, this paper solves this problem by adopting the relational case-based reasoning (RCBR) approach for PDS selection, considering both the structural similarity and feature similarity. To develop the feature terms of the construction projects, the criteria and factors governing PDS selection process are first identified. Then, feature terms for the construction projects are developed. Finally, the mechanism of similarity calculation and a case study indicate how RCBR works for PDS selection. The adoption of RCBR in PDS selection expands the scope of application of traditional CBR method and improves the accuracy of the PDS selection system.

Keywords: relational cased-based reasoning, case-based reasoning, project delivery system, PDS selection

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Authors: M. Dasgupta, S. Banerjee

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Content Based Image Retrieval (CBIR) coupled with Case Based Reasoning (CBR) is a paradigm that is becoming increasingly popular in the diagnosis and therapy planning of medical ailments utilizing the digital content of medical images. This paper presents a survey of some of the promising approaches used in the detection of abnormalities in retina images as well in mammographic screening and detection of regions of interest in MRI scans of the brain. We also describe our proposed algorithm to detect hard exudates in fundus images of the retina of Diabetic Retinopathy patients.

Keywords: case based reasoning, exudates, retina image, similarity based retrieval

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Authors: Elionai Moura, José A. Cunha, César Analide

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This work introduces a proposal scheme for an Intelligent System applied to Pedagogical Advising using Case-Based Reasoning, to find consolidated solutions before used for the new problems, making easier the task of advising students to the pedagogical staff. We do intend, through this work, introduce the motivation behind the choices for this system structure, justifying the development of an incremental and smart web system who learns bests solutions for new cases when it’s used, showing technics and technology.

Keywords: case-based reasoning, pedagogical advising, educational data-mining (EDM), machine learning

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Authors: Maximilian Winkens, Peter Nyhuis

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Components with sensory properties such as gentelligent components developed at the Collaborative Research Center 653 offer a new angle on the full utilization of the remaining service life in case of a preventive maintenance. The developed methodology of component status driven maintenance analyses the stress data obtained during the component's useful life and on the basis of this knowledge assesses the type of maintenance called for in this case. The procedure is derived from the case-based reasoning method and will be elucidated in detail. The method's functionality is demonstrated with real-life data obtained during test runs of a racing car prototype.

Keywords: gentelligent component, preventive maintenance, case-based reasoning, sensory

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Authors: Ben G. Weber, Michael Mateas

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We present a case-based reasoning technique for selecting build orders in a real-time strategy game. The case retrieval process generalizes features of the game state and selects cases using domain-specific recall methods, which perform exact matching on a subset of the case features. We demonstrate the performance of the technique by implementing it as a component of the integrated agent framework of McCoy and Mateas. Our results demonstrate that the technique outperforms nearest-neighbor retrieval when imperfect information is enforced in a real-time strategy game.

Keywords: case based reasoning, real time strategy systems, requirements elicitation, requirement analyst, artificial intelligence

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Authors: Bruno Trstenjak, Dzenana Donko

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Data mining and classification of objects is the process of data analysis, using various machine learning techniques, which is used today in various fields of research. This paper presents a concept of hybrid classification model improved with the expert knowledge. The hybrid model in its algorithm has integrated several machine learning techniques (Information Gain, K-means, and Case-Based Reasoning) and the expert’s knowledge into one. The knowledge of experts is used to determine the importance of features. The paper presents the model algorithm and the results of the case study in which the emphasis was put on achieving the maximum classification accuracy without reducing the number of features.

Keywords: case based reasoning, classification, expert's knowledge, hybrid model

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Authors: Yaojun Wang, Yaoqing Wang

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Stock selection is an important decision-making problem. Many machine learning and data mining technologies are employed to build automatic stock-selection system. A profitable stock-selection system should consider the stock’s investment value and the market timing. In this paper, we present a hybrid system including both engage for stock selection. This system uses a case-based reasoning (CBR) model to execute the stock classification, uses a decision-tree model to help with market timing and stock selection. The experiments show that the performance of this hybrid system is better than that of other techniques regarding to the classification accuracy, the average return and the Sharpe ratio.

Keywords: case-based reasoning, decision tree, stock selection, machine learning

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Authors: Kamalendu Pal

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This paper describes the main features of a knowledge-based system evaluation method. System evaluation is placed in the context of a hybrid legal decision-support system, Advisory Support for Home Settlement in Divorce (ASHSD). Legal knowledge for ASHSD is represented in two forms, as rules and previously decided cases. Besides distinguishing the two different forms of knowledge representation, the paper outlines the actual use of these forms in a computational framework that is designed to generate a plausible solution for a given case, by using rule-based reasoning (RBR) and case-based reasoning (CBR) in an integrated environment. The nature of suitability assessment of a solution has been considered as a multiple criteria decision making process in ASHAD evaluation. The evaluation was performed by a combination of discussions and questionnaires with different user groups. The answers to questionnaires used in this evaluations method have been measured as a combination of linguistic variables, fuzzy numbers, and by using defuzzification process. The results show that the designed evaluation method creates suitable mechanism in order to improve the performance of the knowledge-based system.

Keywords: case-based reasoning, fuzzy number, legal decision-support system, linguistic variable, rule-based reasoning, system evaluation

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Authors: Javier Parra-Domínguez, Juan Manuel Corchado

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At present, public efficiency is a concept that intends to maximize return on public investment focus on minimizing the use of resources and maximizing the outputs. The concept takes into account statistical criteria drawn up according to techniques such as DEA (Data Envelopment Analysis). The purpose of the current work is to consider, more precisely, the theoretical application of CBR (Case-Based Reasoning) from economics and computer science, as a preliminary step to improving the efficiency of law enforcement agencies (public sector). With the aim of increasing the efficiency of the public sector, we have entered into a phase whose main objective is the implementation of new technologies. Our main conclusion is that the application of computer techniques, such as CBR, has become key to the efficiency of the public sector, which continues to require economic valuation based on methodologies such as DEA. As a theoretical result and conclusion, the incorporation of CBR systems will reduce the number of inputs and increase, theoretically, the number of outputs generated based on previous computer knowledge.

Keywords: case-based reasoning, knowledge, police, public efficiency

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Authors: Cory A. Bennett

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Teaching and learning through the use of discourse support students’ conceptual understanding by attending to key concepts and relationships. One discourse structure used in primary classrooms is number talks wherein students mentally calculate, discuss, and reason about the appropriateness and efficiency of their strategies. In the secondary mathematics classroom, the mathematics understudy does not often lend itself to mental calculations yet learning to reason, and articulate reasoning, is central to learning mathematics. This qualitative case study discusses how one secondary school in the Middle East adapted the number talk protocol for secondary mathematics classrooms. Several challenges in implementing ‘reasoning talks’ became apparent including shifting current discourse protocols and practices to a more student-centric model, accurately recording and probing student thinking, and specifically attending to reasoning rather than computations.

Keywords: discourse, reasoning, secondary mathematics, teacher development

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Authors: Ramy Shaaban

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The purpose of this study was to examine the difference in clinical reasoning skills of students when using virtual audiology cases with and without collaborative assistance from major learning approaches important to clinical reasoning skills and computer-based learning models: Situated Learning Theory, Social Development Theory, Scaffolding, and Collaborative Learning. A quasi-experimental design was conducted at two United States universities to examine whether there is a significant difference in clinical reasoning skills between three treatment groups using IUP Audiosim software. Two computer-based audiology case simulations were developed, and participants were randomly placed into the three groups: no collaboration, virtual collaboration, and live collaboration. The clinical reasoning data were analyzed using One-Way ANOVA and Tukey posthoc analyses. The results show that there was a significant difference in clinical reasoning skills between the three treatment groups. The score obtained by the no collaboration group was significantly less than the scores obtained by the virtual and live collaboration groups. Collaboration, whether virtual or in person, has a positive effect on students’ clinical reasoning. These results with audiology students indicate that combining collaboration models with scaffolding and embedding situated learning and social development theories into the design of future virtual patients has the potential to improve students’ clinical reasoning skills.

Keywords: clinical reasoning, virtual patients, collaborative learning, scaffolding

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Authors: Chandan Hegde, K. Ashwini

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Commonsense reasoning is the simulation of human ability to make decisions during the situations that we encounter every day. It has been several decades since the introduction of this subfield of artificial intelligence, but it has barely made some significant progress. The modern computing aids also have remained impotent in this regard due to the absence of a strong methodology towards commonsense reasoning development. Among several accountable reasons for the lack of progress, drawing inference out of commonsense knowledge-base stands out. This review paper emphasizes on a detailed analysis of representation of reasoning uncertainties and feasible prospects of programming aids for drawing inferences. Also, the difficulties in deducing and systematizing commonsense reasoning and the substantial progress made in reasoning that influences the study have been discussed. Additionally, the paper discusses the possible impacts of an effective inference technique in commonsense reasoning.

Keywords: artificial intelligence, commonsense reasoning, knowledge base, uncertainty in reasoning

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Authors: Li Qiang, Yang Ze-Ming, Liu Bao-Xu, Jiang Zheng-Wei

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With the increasing complexity of cyberspace security, the cyber-attack attribution has become an important challenge of the security protection systems. The difficult points of cyber-attack attribution were forced on the problems of huge data handling and key data missing. According to this situation, this paper presented a reasoning method of cyber-attack attribution based on threat intelligence. The method utilizes the intrusion kill chain model and Bayesian network to build attack chain and evidence chain of cyber-attack on threat intelligence platform through data calculation, analysis and reasoning. Then, we used a number of cyber-attack events which we have observed and analyzed to test the reasoning method and demo system, the result of testing indicates that the reasoning method can provide certain help in cyber-attack attribution.

Keywords: reasoning, Bayesian networks, cyber-attack attribution, Kill Chain, threat intelligence

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Authors: Marcin Michalak

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Biclustering is the way of two-dimensional data analysis. For several years it became possible to express such issue in terms of Boolean reasoning, for processing continuous, discrete and binary data. The mathematical backgrounds of such approach — proved ability of induction of exact and inclusion–maximal biclusters fulfilling assumed criteria — are strong advantages of the method. Unfortunately, the core of the method has quite high computational complexity. In the paper the basics of Boolean reasoning approach for biclustering are presented. In such context the problems of computation parallelization are risen.

Keywords: Boolean reasoning, biclustering, parallelization, prime implicant

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Authors: Mariamawit T. Belete

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Cereal production and marketing are the means of livelihood for millions of households in Ethiopia. However, cereal production is constrained by technical and socio-economic factors. Among the technical factors, cereal crop diseases are the major contributing factors to the low yield. The aim of this research is to develop an integration of data mining and knowledge based system for sorghum anthracnose disease diagnosis that assists agriculture experts and development agents to make timely decisions. Anthracnose diagnosing systems gather information from Melkassa agricultural research center and attempt to score anthracnose severity scale. Empirical research is designed for data exploration, modeling, and confirmatory procedures for testing hypothesis and prediction to draw a sound conclusion. WEKA (Waikato Environment for Knowledge Analysis) was employed for the modeling. Knowledge based system has come across a variety of approaches based on the knowledge representation method; case-based reasoning (CBR) is one of the popular approaches used in knowledge-based system. CBR is a problem solving strategy that uses previous cases to solve new problems. The system utilizes hidden knowledge extracted by employing clustering algorithms, specifically K-means clustering from sampled anthracnose dataset. Clustered cases with centroid value are mapped to jCOLIBRI, and then the integrator application is created using NetBeans with JDK 8.0.2. The important part of a case based reasoning model includes case retrieval; the similarity measuring stage, reuse; which allows domain expert to transfer retrieval case solution to suit for the current case, revise; to test the solution, and retain to store the confirmed solution to the case base for future use. Evaluation of the system was done for both system performance and user acceptance. For testing the prototype, seven test cases were used. Experimental result shows that the system achieves an average precision and recall values of 70% and 83%, respectively. User acceptance testing also performed by involving five domain experts, and an average of 83% acceptance is achieved. Although the result of this study is promising, however, further study should be done an investigation on hybrid approach such as rule based reasoning, and pictorial retrieval process are recommended.

Keywords: sorghum anthracnose, data mining, case based reasoning, integration

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Authors: Weiran An, Junyou Shi

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Health management has become one of the design goals in the research and development of new generation avionics systems, and is an important complement and development for the testability and fault diagnosis technology. Currently, the research and application for avionics system health dividing and diagnosis technology is still at the starting stage, lack of related technologies and methods reserve. In this paper, based on the health three-state dividing of avionics products, state lateral transfer coupling modeling and diagnosis reasoning method considering sub-health are researched. With the study of typical case application, the feasibility and correctness of the method and the software are verified.

Keywords: sub-health, diagnosis reasoning, three-valued coupled logic, extended dependency model, avionics

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Authors: Wen Li, Zhengyu Bai, Qi Zhang

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The demand for smart scheduling platform in agriculture, particularly in the scheduling process of machinery equipment, is high. With the continuous development of agricultural machinery equipment technology, a large number of agricultural machinery equipment and agricultural machinery cooperative service organizations continue to appear in China. The large area of cultivated land and a large number of agricultural activities in the central and western regions of China have made the demand for smart and efficient agricultural machinery equipment scheduling platforms more intense. In this study, we design and implement a platform for agricultural machinery equipment scheduling to allocate agricultural machinery equipment resources reasonably. With agricultural machinery equipment scheduling platform taken as the research object, we discuss its research significance and value, use the service blueprint technology to analyze and characterize the agricultural machinery equipment schedule workflow, the network analytic method to obtain the demand platform function requirements, and divide the platform functions through the platform function division diagram. Simultaneously, based on the case-based reasoning (CBR) algorithm, the equipment scheduling module of the agricultural machinery equipment scheduling platform is realized; finally, a design scheme of the agricultural machinery equipment scheduling platform architecture is provided, and the visualization interface of the platform is established via VB programming language. It provides design ideas and theoretical support for the construction of a modern agricultural equipment information scheduling platform.

Keywords: case-based reasoning, service blueprint, system design, ANP, VB programming language

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Authors: David Glassmeyer

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Quantitative reasoning is necessary to robustly understand mathematical concepts ranging from elementary to university levels. Quantitative reasoning involves identifying and representing quantities and the relationships between these quantities. Without reasoning quantitatively, students often resort to memorizing formulas and procedures, which have negative impacts when they encounter mathematical topics in the future. This study investigated how high school students’ quantitative reasoning could be fostered within a unit on arc measure and angle relationships. Arc measure, or the measure of a central angle that cuts off a portion of a circle’s circumference, is often confused with arclength. In this study, the researcher redesigned an activity to clearly distinguish arc measure and arc length by using a quantitative reasoning framework. Data were collected from high school students to determine if this approach impacted their understanding of these concepts. Initial data indicates the approach was successful in supporting students’ quantitative reasoning of these topics. Implications for the work are that teachers themselves may also benefit from considering mathematical definitions from a quantitative reasoning framework and can use this activity in their own classrooms.

Keywords: arc length, arc measure, quantitative reasoning, student content knowledge

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Authors: Zhangquan Zhou, Guilin Qi

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Materialization is an important reasoning service for applications built on the Web Ontology Language (OWL). To make materialization efficient in practice, current research focuses on deciding tractability of an ontology language and designing parallel reasoning algorithms. However, some well-known large-scale ontologies, such as YAGO, have been shown to have good performance for parallel reasoning, but they are expressed in ontology languages that are not parallelly tractable, i.e., the reasoning is inherently sequential in the worst case. This motivates us to study the problem of parallel tractability of ontology materialization from a theoretical perspective. That is we aim to identify the ontologies for which materialization is parallelly tractable, i.e., in the NC complexity. Since the NC complexity is defined based on Boolean circuit that is widely used to investigate parallel computing problems, we first transform the problem of materialization to evaluation of Boolean circuits, and then study the problem of parallel tractability based on circuits. In this work, we focus on datalog rewritable ontology languages. We use Boolean circuits to identify two classes of datalog rewritable ontologies (called parallelly tractable classes) such that materialization over them is parallelly tractable. We further investigate the parallel tractability of materialization of a datalog rewritable OWL fragment DHL (Description Horn Logic). Based on the above results, we analyze real-world datasets and show that many ontologies expressed in DHL belong to the parallelly tractable classes.

Keywords: ontology materialization, parallel reasoning, datalog, Boolean circuit

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Authors: Ayşegül Çabuk, Mine Işıksal

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Mathematics is a sense-making activity so that it requires meaningful learning. Hence based on this idea, meaningful mathematical connections are necessary to learn mathematics. At that point, the major question has become that which educational methods can provide opportunities to provide mathematical connections and to understand mathematics. The amalgam of reasoning and proof can be the one of the methods that creates opportunities to learn mathematics in a meaningful way. However, even if reasoning and proof should be included from prekindergarten to grade 12, studies in literature generally include secondary school students and pre-service mathematics teachers. With the light of the idea that the amalgam of reasoning and proof has significant effect on middle school students' mathematical learning, this study aims to investigate middle grade students' tendencies while reasoning the correctness of statements related to numbers. The sample included 272 middle grade students, specifically 69 of them were sixth grade students (25.4%), 101 of them were seventh grade students (37.1%) and 102 of them were eighth grade students (37.5%). Data was gathered through an achievement test including 2 essay types of problems about algebra. The answers of two items were analyzed both quantitatively and qualitatively in terms of students' solutions strategies while reasoning the correctness of the statements. Similar on the findings in the literature, most of the students, in all grade levels, used numerical examples to judge the statements. Moreover the results also showed that the majority of these students appear to believe that providing one or more selected examples is sufficient to show the correctness of the statement. Hence based on the findings of the study, even students in earlier ages have proving and reasoning abilities their reasoning's generally based on the empirical evidences. Therefore, it is suggested that examples and example-based reasoning can be a fundamental role on to generate systematical reasoning and proof insight in earlier ages.

Keywords: reasoning, mathematics learning, middle grade students

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Authors: Supratman Ahman Maedi

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The construction of knowledge is the goal of learning. The purpose of this research is to know how the role of Piaget theory in allegation via analogy reasoning. This study uses Think out loads when troubleshooting. To explore conjecturing via analogical reasoning is given the question of open analogy. The result: conjecture via analogical reasoning has been done by students in the construction of knowledge, in conjecture there are differences in thinking flow depending on the basic knowledge of the students, in the construction of knowledge occurs assimilation and accommodation problems, strategies and relationships.

Keywords: analogical reasoning, conjecturing, knowledge construction, Piaget's theory

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Authors: Yenie Norambuena

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Analogical reasoning is a cognitive process that consists of structured comparisons of mental representations and scheme construction. Because of its heuristic function, it is ubiquitous in cognition and could play an important role in language development. The use of analogies is expressed early in children and this behavior is also reflected in language, suggesting a possible way to understand the complex links between thought and language. The current research examines factors of verbal and non-verbal reasoning that should be taken into consideration in the study of language development for their relations and predictive value. The study was conducted with 48 Chilean preschoolers (Spanish speakers) from 4 to 6-year-old. We assessed children’s verbal analogical reasoning, non-verbal analogical reasoning and linguistics skills (Listening Comprehension, Phonemic awareness, Alphabetic principle, Syllabification, Lexical repetition and Lexical decision). The results evidenced significant correlations between analogical reasoning factors and linguistic skills and they can predict linguistic performance mainly on oral comprehension, lexical decision and phonological skills. These findings suggest a fundamental interrelationship between analogical reasoning and linguistic performance on children’s and points to the need to consider this cognitive process in comprehensive theories of children's language development.

Keywords: verbal analogical reasoning, non-verbal analogical reasoning, linguistic skills, language development

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Authors: Olteanu Constanta, Olteanu Lucian

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Researchers note that algebraic reasoning and sense making is essential for building conceptual knowledge in school mathematics. Consequently, pre-service teachers’ own reasoning and sense making are useful in fostering and developing students’ algebraic reasoning and sense making. This article explores the forms of reasoning and sense making that pre-service mathematics teachers exhibit and use in the process of analysing problem-posing tasks with a focus on first-degree equations. Our research question concerns the characteristics of the problem-posing tasks used for reasoning and sense making of first-degree equations as well as the characteristics of pre-service teachers’ reasoning and sense making in problem-posing tasks. The analyses are grounded in a post-structuralist philosophical perspective and variation theory. Sixty-six pre-service primary teachers participated in the study. The results show that the characteristics of reasoning in problem-posing tasks and of pre-service teachers are selecting, exploring, reconfiguring, encoding, abstracting and connecting. The characteristics of sense making in problem-posing tasks and of pre-service teachers are recognition, relationships, profiling, comparing, laddering and verifying. Beside this, the connection between reasoning and sense making is rich in line of flight in problem-posing tasks, while the connection is rich in line of rupture for pre-service teachers.

Keywords: first-degree equations, problem posing, reasoning, rhizomatic assemblage, sense-making, variation theory

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Authors: Ebenezer Joseph, Veena Easvaradoss, S. Sundar Manoharan, David Chandran, Sumathi Chandrasekaran, T. R. Uma

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Perceptual reasoning is the ability that incorporates fluid reasoning, spatial processing, and visual motor integration. Several theories of cognitive functioning emphasize the importance of fluid reasoning. The ability to manipulate abstractions and rules and to generalize is required for reasoning tasks. This study, funded by the Cognitive Science Research Initiative, Department of Science and Technology, Government of India, analyzed the effect of 1-year chess training on the perceptual reasoning of children. A pretest–posttest with control group design was used, with 43 (28 boys, 15 girls) children in the experimental group and 42 (26 boys, 16 girls) children in the control group. The sample was selected from children studying in two private schools from South India (grades 3 to 9), which included both the genders. The experimental group underwent weekly 1-hour chess training for 1 year. Perceptual reasoning was measured by three subtests of WISC-IV INDIA. Pre-equivalence of means was established. Further statistical analyses revealed that the experimental group had shown statistically significant improvement in perceptual reasoning compared to the control group. The present study clearly establishes a correlation between chess learning and perceptual reasoning. If perceptual reasoning can be enhanced in children, it could possibly result in the improvement of executive functions as well as the scholastic performance of the child.

Keywords: chess, cognition, intelligence, perceptual reasoning

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Authors: Sonia Anand Knowlton

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As the use of Artificial Intelligence is becoming increasingly integrated in virtually every area of life, the need and interest to logically formalize the law and judicial reasoning is growing tremendously. The study of argumentation frameworks (AFs) provides promise in this respect. AF’s provide a way of structuring human reasoning using a formal system of non-monotonic logic. P.M. Dung first introduced this framework and demonstrated that certain arguments must prevail and certain arguments must perish based on whether they are logically “attacked” by other arguments. Dung labelled the set of prevailing arguments as the “preferred extension” of the given argumentation framework. Trevor Bench-Capon’s Value-based Argumentation Frameworks extended Dung’s AF system by allowing arguments to derive their force from the promotion of “preferred” values. In VAF systems, the success of an attack from argument A to argument B (i.e., the triumph of argument A) requires that argument B does not promote a value that is preferred to argument A. There has been thorough discussion of the application of VAFs to the law within the computer science literature, mainly demonstrating that legal cases can be effectively mapped out using VAFs. This article analyses VAFs from a jurisprudential standpoint to provide a philosophical and theoretical analysis of what VAFs tell the legal community about the judicial reasoning, specifically distinguishing between legal and moral reasoning. It highlights the limitations of using VAFs to account for judicial moral reasoning in theory and in practice.

Keywords: nonmonotonic logic, legal formalization, computer science, artificial intelligence, morality

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Authors: Abderrahmane Khiat, Moussa Benaissa

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Due to the increasing number of sources of information available on the web and their distribution and heterogeneity, ontology alignment became a very important and inevitable problem to ensure semantic interoperability. Instance-based ontology alignment is based on the comparison of the extensions of concepts; and represents a very promising technique to find semantic correspondences between entities of different ontologies. In practice, two situations may arise: ontologies that share many common instances and ontologies that share few or do not share common instances. In this paper, we describe an approach to manage the latter case. This approach exploits the reasoning on ontologies in order to create a corpus of common instances. We show that it is theoretically powerful because it is based on description logics and very useful in practice. We present the experimental results obtained by running our approach on ontologies of OAEI 2012 benchmark test. The results show the performance of our approach.

Keywords: description logic inference, instance-based ontology alignment, semantic interoperability, semantic web

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Authors: Hafida Bouarfa, Mohamed Abed

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The main object of our work is the development and the validation of a system indicated Fuzzy Vulnerability. Fuzzy Vulnerability uses a fuzzy representation in order to tolerate the imprecision during the description of construction. At the the second phase, we evaluated the similarity between the vulnerability of a new construction and those of the whole of the historical cases. This similarity is evaluated on two levels: 1) individual similarity: bases on the fuzzy techniques of aggregation; 2) Global similarity: uses the increasing monotonous linguistic quantifiers (RIM) to combine the various individual similarities between two constructions. The third phase of the process of Fuzzy Vulnerability consists in using vulnerabilities of historical constructions narrowly similar to current construction to deduce its estimate vulnerability. We validated our system by using 50 cases. We evaluated the performances of Fuzzy Vulnerability on the basis of two basic criteria, the precision of the estimates and the tolerance of the imprecision along the process of estimation. The comparison was done with estimates made by tiresome and long models. The results are satisfactory.

Keywords: case based reasoning, fuzzy logic, fuzzy case based reasoning, seismic vulnerability

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