A case-based reasoning tool for breast cancer knowledge management with data mining concepts and techniques

Science.gov (United States)

Demigha, Souâd.

2016-03-01

The paper presents a Case-Based Reasoning Tool for Breast Cancer Knowledge Management to improve breast cancer screening. To develop this tool, we combine both concepts and techniques of Case-Based Reasoning (CBR) and Data Mining (DM). Physicians and radiologists ground their diagnosis on their expertise (past experience) based on clinical cases. Case-Based Reasoning is the process of solving new problems based on the solutions of similar past problems and structured as cases. CBR is suitable for medical use. On the other hand, existing traditional hospital information systems (HIS), Radiological Information Systems (RIS) and Picture Archiving Information Systems (PACS) don't allow managing efficiently medical information because of its complexity and heterogeneity. Data Mining is the process of mining information from a data set and transform it into an understandable structure for further use. Combining CBR to Data Mining techniques will facilitate diagnosis and decision-making of medical experts.

Case-based Reasoning for Automotive Engine Performance Tune-up

International Nuclear Information System (INIS)

Vong, C. M.; Huang, H.; Wong, P. K.

2010-01-01

The automotive engine performance tune-up is greatly affected by the calibration of its electronic control unit (ECU). The ECU calibration is traditionally done by trial-and-error method. This traditional method consumes a large amount of time and money because of a large number of dynamometer tests. To resolve this problem, case based reasoning (CBR) is employed, so that an existing and effective ECU setup can be adapted to fit another similar class of engines. The adaptation procedure is done through a more sophisticated step called case-based adaptation (CBA)[1, 2]. CBA is an effective knowledge management tool, which can interactively learn the expert adaptation knowledge. The paper briefly reviews the methodologies of CBR and CBA. Then the application to ECU calibration is described via a case study. With CBR and CBA, the efficiency of calibrating an ECU can be enhanced. A prototype system has also been developed to verify the usefulness of CBR in ECU calibration.

Learning material recommendation based on case-based reasoning similarity scores

Science.gov (United States)

Masood, Mona; Mokmin, Nur Azlina Mohamed

2017-10-01

A personalized learning material recommendation is important in any Intelligent Tutoring System (ITS). Case-based Reasoning (CBR) is an Artificial Intelligent Algorithm that has been widely used in the development of ITS applications. This study has developed an ITS application that applied the CBR algorithm in the development process. The application has the ability to recommend the most suitable learning material to the specific student based on information in the student profile. In order to test the ability of the application in recommending learning material, two versions of the application were created. The first version displayed the most suitable learning material and the second version displayed the least preferable learning material. The results show the application has successfully assigned the students to the most suitable learning material.

Case-based reasoning support for engineering design

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Lees, Brian; Hamza, Meer; Irgens, Chris

2000-10-01

The potential application of case-based reasoning (CBR) in design support is illustrated through examples drawn from research at the University of Paisley, demonstrating the suitability of CBR for different aspects of design, different problem areas, and different design goals. A quality advisory system has been developed for the early stages of mechanical engineering design, the aim of which is to provide quality advice in a variant design situation. In the domain of software engineering CBR has been applied to advise on which metrics are appropriate fora assessing the quality of the software currently under design. The system integrates CBR with concepts from quality function deployment (QFD) and incorporates a case library holding past software quality histories. CBR has been applied in support of conceptual design: to capture detailed design histories by monitoring designer actions, and thereby support design reuse through the evaluation of designs, through the provision of query, browsing and replay facilities. The resulting system is aimed to support the design of safety critical systems, by assisting in the construction of safety arguments, and cooperative design.

Signal Analysis of Automotive Engine Spark Ignition System using Case-Based Reasoning (CBR) and Case-based Maintenance (CBM)

International Nuclear Information System (INIS)

Huang, H.; Vong, C. M.; Wong, P. K.

2010-01-01

With the development of modern technology, modern vehicles adopt electronic control system for injection and ignition. In traditional way, whenever there is any malfunctioning in an automotive engine, an automotive mechanic usually performs a diagnosis in the ignition system of the engine to check any exceptional symptoms. In this paper, we present a case-based reasoning (CBR) approach to help solve human diagnosis problem. Nevertheless, one drawback of CBR system is that the case library will be expanded gradually after repeatedly running the system, which may cause inaccuracy and longer time for the CBR retrieval. To tackle this problem, case-based maintenance (CBM) framework is employed so that the case library of the CBR system will be compressed by clustering to produce a set of representative cases. As a result, the performance (in retrieval accuracy and time) of the whole CBR system can be improved.

Construction Tender Subcontract Selection using Case-based Reasoning

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Due Luu

2012-11-01

Full Text Available Obtaining competitive quotations from suitably qualified subcontractors at tender tim n significantly increase the chance of w1nmng a construction project. Amidst an increasingly growing trend to subcontracting in Australia, selecting appropriate subcontractors for a construction project can be a daunting task requiring the analysis of complex and dynamic criteria such as past performance, suitable experience, track record of competitive pricing, financial stability and so on. Subcontractor selection is plagued with uncertainty and vagueness and these conditions are difficul_t o represent in generalised sets of rules. DeciSIOns pertaining to the selection of subcontr:act?s tender time are usually based on the mtu1t1onand past experience of construction estimators. Case-based reasoning (CBR may be an appropriate method of addressing the chal_lenges of selecting subcontractors because CBR 1s able to harness the experiential knowledge of practitioners. This paper reviews the practicality and suitability of a CBR approach for subcontractor tender selection through the development of a prototype CBR procurement advisory system. In this system, subcontractor selection cases are represented by a set of attributes elicited from experienced construction estimators. The results indicate that CBR can enhance the appropriateness of the selection of subcontractors for construction projects.

Case-Based Reasoning as a Heuristic Selector in a Hyper-Heuristic for Course Timetabling Problems

OpenAIRE

Petrovic, Sanja; Qu, Rong

2002-01-01

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 dis...

Supportive decision making at the point of care: refinement of a case-based reasoning application for use in nursing practice.

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DI Pietro, Tammie L; Doran, Diane M; McArthur, Gregory

2010-01-01

Variations in nursing care have been observed, affecting patient outcomes and quality of care. Case-based reasoners that benchmark for patient indicators can reduce variation through decision support. This study evaluated and validated a case-based reasoning application to establish benchmarks for nursing-sensitive patient outcomes of pain, fatigue, and toilet use, using patient characteristic variables for generating similar cases. Three graduate nursing students participated. Each ranked 25 patient cases using demographics of age, sex, diagnosis, and comorbidities against 10 patients from a database. Participant judgments of case similarity were compared with the case-based reasoning system. Feature weights for each indicator were adjusted to make the case-based reasoning system's similarity ranking correspond more closely to participant judgment. Small differences were noted between initial weights and weights generated from participants. For example, initial weight for comorbidities was 0.35, whereas weights generated by participants for pain, fatigue, and toilet use were 0.49, 0.42, and 0.48, respectively. For the same outcomes, the initial weight for sex was 0.15, but weights generated by the participants were 0.025, 0.002, and 0.000, respectively. Refinement of the case-based reasoning tool established valid benchmarks for patient outcomes in relation to participants and assisted in point-of-care decision making.

Effects of a Case-Based Reasoning System on Student Performance in a Java Programming Course

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Schmidt, Cecil

2007-01-01

The purpose of this study was to determine if a case-based reasoning tool would improve a student's understanding of the complex concepts in a Java programming course. Subjects for the study were randomly assigned from two sections of an introductory Java programming course. Posttests were used to measure the effects of the case-based reasoning…

PENGEMBANGAN SISTEM CERDAS MENGGUNAKAN PENALARAN BERBASIS KASUS (CASE BASED REASONING UNTUK DIAGNOSA PENYAKIT AKIBAT VIRUS EKSANTEMA

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Agus Sasmito Aribowo

2015-04-01

Full Text Available Disease caused by a exanthema virus is a common disease in Indonesia. There are many types of diseases caused by this virus. Examples are chicken pox, measles, variola, etc. with symptoms almost similar to each other. To correctly identify the symptoms  need experts. But the problem is very limited number of experts. Then the expert system is needed which has been given by the expert knowledge to assist in the diagnosis. Expert system in this research uses a case-based reasoning approach. If there is a similar case, the reasoning for considering the case of the nearest using Probabilistic Bayes. The result is the system will still be able to provide the best recommendations solution for new cases based on the solution to an old case that the nearest level of similarity.

How Case-Based Reasoning on e-Community Knowledge Can Be Improved Thanks to Knowledge Reliability

OpenAIRE

Gaillard , Emmanuelle; Lieber , Jean; Nauer , Emmanuel; Cordier , Amélie

2014-01-01

International audience; This paper shows that performing case-based reasoning (CBR) on knowledge coming from an e-community is improved by taking into account knowledge reliability. MKM (meta-knowledge model) is a model for managing reliability of the knowledge units that are used in the reasoning process. For this, MKM uses meta-knowledge such as belief, trust and reputation, about knowledge units and users. MKM is used both to select relevant knowledge to conduct the reasoning process, and ...

Emerging medical informatics with case-based reasoning for aiding clinical decision in multi-agent system.

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Shen, Ying; Colloc, Joël; Jacquet-Andrieu, Armelle; Lei, Kai

2015-08-01

This research aims to depict the methodological steps and tools about the combined operation of case-based reasoning (CBR) and multi-agent system (MAS) to expose the ontological application in the field of clinical decision support. The multi-agent architecture works for the consideration of the whole cycle of clinical decision-making adaptable to many medical aspects such as the diagnosis, prognosis, treatment, therapeutic monitoring of gastric cancer. In the multi-agent architecture, the ontological agent type employs the domain knowledge to ease the extraction of similar clinical cases and provide treatment suggestions to patients and physicians. Ontological agent is used for the extension of domain hierarchy and the interpretation of input requests. Case-based reasoning memorizes and restores experience data for solving similar problems, with the help of matching approach and defined interfaces of ontologies. A typical case is developed to illustrate the implementation of the knowledge acquisition and restitution of medical experts. Copyright © 2015 Elsevier Inc. All rights reserved.

Problem-Oriented Corporate Knowledge Base Models on the Case-Based Reasoning Approach Basis

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Gluhih, I. N.; Akhmadulin, R. K.

2017-07-01

One of the urgent directions of efficiency enhancement of production processes and enterprises activities management is creation and use of corporate knowledge bases. The article suggests a concept of problem-oriented corporate knowledge bases (PO CKB), in which knowledge is arranged around possible problem situations and represents a tool for making and implementing decisions in such situations. For knowledge representation in PO CKB a case-based reasoning approach is encouraged to use. Under this approach, the content of a case as a knowledge base component has been defined; based on the situation tree a PO CKB knowledge model has been developed, in which the knowledge about typical situations as well as specific examples of situations and solutions have been represented. A generalized problem-oriented corporate knowledge base structural chart and possible modes of its operation have been suggested. The obtained models allow creating and using corporate knowledge bases for support of decision making and implementing, training, staff skill upgrading and analysis of the decisions taken. The universal interpretation of terms “situation” and “solution” adopted in the work allows using the suggested models to develop problem-oriented corporate knowledge bases in different subject domains. It has been suggested to use the developed models for making corporate knowledge bases of the enterprises that operate engineer systems and networks at large production facilities.

An effective framework for finding similar cases of dengue from audio and text data using domain thesaurus and case base reasoning

Science.gov (United States)

Sandhu, Rajinder; Kaur, Jaspreet; Thapar, Vivek

2018-02-01

Dengue, also known as break-bone fever, is a tropical disease transmitted by mosquitoes. If the similarity between dengue infected users can be identified, it can help government's health agencies to manage the outbreak more effectively. To find similarity between cases affected by Dengue, user's personal and health information are the two fundamental requirements. Identification of similar symptoms, causes, effects, predictions and treatment procedures, is important. In this paper, an effective framework is proposed which finds similar patients suffering from dengue using keyword aware domain thesaurus and case base reasoning method. This paper focuses on the use of ontology dependent domain thesaurus technique to extract relevant keywords and then build cases with the help of case base reasoning method. Similar cases can be shared with users, nearby hospitals and health organizations to manage the problem more adequately. Two million case bases were generated to test the proposed similarity method. Experimental evaluations of proposed framework resulted in high accuracy and low error rate for finding similar cases of dengue as compared to UPCC and IPCC algorithms. The framework developed in this paper is for dengue but can easily be extended to other domains also.

Research on conflict resolution of collaborative design with fuzzy case-based reasoning method

Institute of Scientific and Technical Information of China (English)

HOU Jun-ming; SU Chong; LIANG Shuang; WANG Wan-shan

2009-01-01

Collaborative design is a new style for modern mechanical design to meet the requirement of increasing competition. Designers of different places complete the same work, but the conflict appears in the process of design which may interface the design. Case-based reasoning (CBR) method is applied to the problem of conflict resolution, which is in the artificial intelligence field. However, due to the uncertainties in knowledge representation, attribute description, and similarity measures of CBR, it is very difficult to find the similar cases from case database. A fuzzy CBR method was proposed to solve the problem of conflict resolution in collaborative design. The process of fuzzy CBR was introduced. Based on the feature attributes and their relative weights determined by a fuzzy technique, a fuzzy CBR retrieving mechanism was developed to retrieve conflict resolution cases that tend to enhance the functions of the database. By indexing, calculating the weight and defuzzicating of the cases, the case similarity can be obtained. Then the case consistency was measured to keep the right result. Finally, the fuzzy CBR method for conflict resolution was demonstrated by means of a case study. The prototype system based on web is developed to illustrate the methodology.

Case-based clinical reasoning in feline medicine: 2: Managing cognitive error.

Science.gov (United States)

Canfield, Paul J; Whitehead, Martin L; Johnson, Robert; O'Brien, Carolyn R; Malik, Richard

2016-03-01

This is Article 2 of a three-part series on clinical reasoning that encourages practitioners to explore and understand how they think and make case-based decisions. It is hoped that, in the process, they will learn to trust their intuition but, at the same time, put in place safeguards to diminish the impact of bias and misguided logic on their diagnostic decision-making. Article 1, published in the January 2016 issue of JFMS, discussed the relative merits and shortcomings of System 1 thinking (immediate and unconscious) and System 2 thinking (effortful and analytical). This second article examines ways of managing cognitive error, particularly the negative impact of bias, when making a diagnosis. Article 3, to appear in the May 2016 issue, explores the use of heuristics (mental short cuts) and illness scripts in diagnostic reasoning. © The Author(s) 2016.

Novel Agent Based-approach for Industrial Diagnosis: A Combined use Between Case-based Reasoning and Similarity Measure

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Fatima Zohra Benkaddour

2016-12-01

Full Text Available In spunlace nonwovens industry, the maintenance task is very complex, it requires experts and operators collaboration. In this paper, we propose a new approach integrating an agent- based modelling with case-based reasoning that utilizes similarity measures and preferences module. The main purpose of our study is to compare and evaluate the most suitable similarity measure for our case. Furthermore, operators that are usually geographically dispersed, have to collaborate and negotiate to achieve mutual agreements, especially when their proposals (diagnosis lead to a conflicting situation. The experimentation shows that the suggested agent-based approach is very interesting and efficient for operators and experts who collaborate in INOTIS enterprise.

PDA: A coupling of knowledge and memory for case-based reasoning

Science.gov (United States)

Bharwani, S.; Walls, J.; Blevins, E.

1988-01-01

Problem solving in most domains requires reference to past knowledge and experience whether such knowledge is represented as rules, decision trees, networks or any variant of attributed graphs. Regardless of the representational form employed, designers of expert systems rarely make a distinction between the static and dynamic aspects of the system's knowledge base. The current paper clearly distinguishes between knowledge-based and memory-based reasoning where the former in its most pure sense is characterized by a static knowledge based resulting in a relatively brittle expert system while the latter is dynamic and analogous to the functions of human memory which learns from experience. The paper discusses the design of an advisory system which combines a knowledge base consisting of domain vocabulary and default dependencies between concepts with a dynamic conceptual memory which stores experimental knowledge in the form of cases. The case memory organizes past experience in the form of MOPs (memory organization packets) and sub-MOPs. Each MOP consists of a context frame and a set of indices. The context frame contains information about the features (norms) common to all the events and sub-MOPs indexed under it.

INTEGRATING CASE-BASED REASONING, KNOWLEDGE-BASED APPROACH AND TSP ALGORITHM FOR MINIMUM TOUR FINDING

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Hossein Erfani

2009-07-01

Full Text Available Imagine you have traveled to an unfamiliar city. Before you start your daily tour around the city, you need to know a good route. In Network Theory (NT, this is the traveling salesman problem (TSP. A dynamic programming algorithm is often used for solving this problem. However, when the road network of the city is very complicated and dense, which is usually the case, it will take too long for the algorithm to find the shortest path. Furthermore, in reality, things are not as simple as those stated in AT. For instance, the cost of travel for the same part of the city at different times may not be the same. In this project, we have integrated TSP algorithm with AI knowledge-based approach and case-based reasoning in solving the problem. With this integration, knowledge about the geographical information and past cases are used to help TSP algorithm in finding a solution. This approach dramatically reduces the computation time required for minimum tour finding.

Case-based clinical reasoning in feline medicine: 1: Intuitive and analytical systems.

Science.gov (United States)

Canfield, Paul J; Whitehead, Martin L; Johnson, Robert; O'Brien, Carolyn R; Malik, Richard

2016-01-01

This is Article 1 of a three-part series on clinical reasoning that encourages practitioners to explore and understand how they think and make case-based decisions. It is hoped that, in the process, they will learn to trust their intuition but, at the same time, put in place safeguards to diminish the impact of bias and misguided logic on their diagnostic decision-making. This first article discusses the relative merits and shortcomings of System 1 thinking (immediate and unconscious) and System 2 thinking (effortful and analytical). Articles 2 and 3, to appear in the March and May 2016 issues of JFMS, respectively, will examine managing cognitive error, and use of heuristics (mental short cuts) and illness scripts in diagnostic reasoning. © The Author(s) 2016.

Clinical reasoning and case-based decision making: the fundamental challenge to veterinary educators.

Science.gov (United States)

May, Stephen A

2013-01-01

Confusion about the nature of human reasoning and its appropriate application to patients has hampered veterinary students' development of these skills. Expertise is associated with greater ability to deploy pattern recognition (type 1 reasoning), which is aided by progressive development of data-driven, forward reasoning (in contrast to scientific, backward reasoning), analytical approaches that lead to schema acquisition. The associative nature of type 1 reasoning makes it prone to bias, particularly in the face of "cognitive miserliness," when clues that indicate the need for triangulation with an analytical approach are ignored. However, combined reasoning approaches, from the earliest stages, are more successful than one approach alone, so it is important that those involved in curricular design and delivery promote student understanding of reasoning generally, and the situations in which reasoning goes awry, and develop students' ability to reason safely and accurately whether presented with a familiar case or with a case that they have never seen before.

Knowledge discovery in hyper-heuristic using case-based reasoning on course timetabling

OpenAIRE

Burke, Edmund; MacCarthy, Bart L.; Petrovic, Sanja; Qu, Rong

2002-01-01

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 main...

A fuzzy-ontology-oriented case-based reasoning framework for semantic diabetes diagnosis.

Science.gov (United States)

El-Sappagh, Shaker; Elmogy, Mohammed; Riad, A M

2015-11-01

Case-based reasoning (CBR) is a problem-solving paradigm that uses past knowledge to interpret or solve new problems. It is suitable for experience-based and theory-less problems. Building a semantically intelligent CBR that mimic the expert thinking can solve many problems especially medical ones. Knowledge-intensive CBR using formal ontologies is an evolvement of this paradigm. Ontologies can be used for case representation and storage, and it can be used as a background knowledge. Using standard medical ontologies, such as SNOMED CT, enhances the interoperability and integration with the health care systems. Moreover, utilizing vague or imprecise knowledge further improves the CBR semantic effectiveness. This paper proposes a fuzzy ontology-based CBR framework. It proposes a fuzzy case-base OWL2 ontology, and a fuzzy semantic retrieval algorithm that handles many feature types. This framework is implemented and tested on the diabetes diagnosis problem. The fuzzy ontology is populated with 60 real diabetic cases. The effectiveness of the proposed approach is illustrated with a set of experiments and case studies. The resulting system can answer complex medical queries related to semantic understanding of medical concepts and handling of vague terms. The resulting fuzzy case-base ontology has 63 concepts, 54 (fuzzy) object properties, 138 (fuzzy) datatype properties, 105 fuzzy datatypes, and 2640 instances. The system achieves an accuracy of 97.67%. We compare our framework with existing CBR systems and a set of five machine-learning classifiers; our system outperforms all of these systems. Building an integrated CBR system can improve its performance. Representing CBR knowledge using the fuzzy ontology and building a case retrieval algorithm that treats different features differently improves the accuracy of the resulting systems. Copyright © 2015 Elsevier B.V. All rights reserved.

A prototype case-based reasoning human assistant for space crew assessment and mission management

Science.gov (United States)

Owen, Robert B.; Holland, Albert W.; Wood, Joanna

1993-01-01

We present a prototype human assistant system for space crew assessment and mission management. Our system is based on case episodes from American and Russian space missions and analog environments such as polar stations and undersea habitats. The general domain of small groups in isolated and confined environments represents a near ideal application area for case-based reasoning (CBR) - there are few reliable rules to follow, and most domain knowledge is in the form of cases. We define the problem domain and outline a unique knowledge representation system driven by conflict and communication triggers. The prototype system is able to represent, index, and retrieve case studies of human performance. We index by social, behavioral, and environmental factors. We present the problem domain, our current implementation, our research approach for an operational system, and prototype performance and results.

Context based support for Clinical Reasoning

DEFF Research Database (Denmark)

Vilstrup Pedersen, Klaus

2004-01-01

In many areas of the medical domain, the decision process i.e. reasoning, involving health care professionals is distributed, cooperative and complex. Computer based decision support systems has usually been focusing on the outcome of the decision making and treated it as a single task....... In this paper a framework for a Clinical Reasoning Knowledge Warehouse (CRKW) is presented, intended to support the reasoning process, by providing the decision participants with an analysis platform that captures and enhances information and knowledge. The CRKW mixes theories and models from Artificial...... Intelligence, Knowledge Management Systems and Business Intelligence to make context sensitive, patient case specific analysis and knowledge management. The knowledge base consists of patient health records, reasoning process information and clinical guidelines. Patient specific information and knowledge...

Retrieval with Clustering in a Case-Based Reasoning System for Radiotherapy Treatment Planning

Science.gov (United States)

Khussainova, Gulmira; Petrovic, Sanja; Jagannathan, Rupa

2015-05-01

Radiotherapy treatment planning aims to deliver a sufficient radiation dose to cancerous tumour cells while sparing healthy organs in the tumour surrounding area. This is a trial and error process highly dependent on the medical staff's experience and knowledge. Case-Based Reasoning (CBR) is an artificial intelligence tool that uses past experiences to solve new problems. A CBR system has been developed to facilitate radiotherapy treatment planning for brain cancer. Given a new patient case the existing CBR system retrieves a similar case from an archive of successfully treated patient cases with the suggested treatment plan. The next step requires adaptation of the retrieved treatment plan to meet the specific demands of the new case. The CBR system was tested by medical physicists for the new patient cases. It was discovered that some of the retrieved cases were not suitable and could not be adapted for the new cases. This motivated us to revise the retrieval mechanism of the existing CBR system by adding a clustering stage that clusters cases based on their tumour positions. A number of well-known clustering methods were investigated and employed in the retrieval mechanism. Results using real world brain cancer patient cases have shown that the success rate of the new CBR retrieval is higher than that of the original system.

Retrieval with Clustering in a Case-Based Reasoning System for Radiotherapy Treatment Planning

International Nuclear Information System (INIS)

Khussainova, Gulmira; Petrovic, Sanja; Jagannathan, Rupa

2015-01-01

Radiotherapy treatment planning aims to deliver a sufficient radiation dose to cancerous tumour cells while sparing healthy organs in the tumour surrounding area. This is a trial and error process highly dependent on the medical staff's experience and knowledge. Case-Based Reasoning (CBR) is an artificial intelligence tool that uses past experiences to solve new problems. A CBR system has been developed to facilitate radiotherapy treatment planning for brain cancer. Given a new patient case the existing CBR system retrieves a similar case from an archive of successfully treated patient cases with the suggested treatment plan. The next step requires adaptation of the retrieved treatment plan to meet the specific demands of the new case. The CBR system was tested by medical physicists for the new patient cases. It was discovered that some of the retrieved cases were not suitable and could not be adapted for the new cases. This motivated us to revise the retrieval mechanism of the existing CBR system by adding a clustering stage that clusters cases based on their tumour positions. A number of well-known clustering methods were investigated and employed in the retrieval mechanism. Results using real world brain cancer patient cases have shown that the success rate of the new CBR retrieval is higher than that of the original system. (paper)

Spatial and Temporal Wind Power Forecasting by Case-Based Reasoning Using Big-Data

Directory of Open Access Journals (Sweden)

Fabrizio De Caro

2017-02-01

Full Text Available The massive penetration of wind generators in electrical power systems asks for effective wind power forecasting tools, which should be high reliable, in order to mitigate the effects of the uncertain generation profiles, and fast enough to enhance power system operation. To address these two conflicting objectives, this paper advocates the role of knowledge discovery from big-data, by proposing the integration of adaptive Case Based Reasoning models, and cardinality reduction techniques based on Partial Least Squares Regression, and Principal Component Analysis. The main idea is to learn from a large database of historical climatic observations, how to solve the windforecasting problem, avoiding complex and time-consuming computations. To assess the benefits derived by the application of the proposed methodology in complex application scenarios, the experimental results obtained in a real case study will be presented and discussed.

Irrelevance Reasoning in Knowledge Based Systems

Science.gov (United States)

Levy, A. Y.

1993-01-01

This dissertation considers the problem of reasoning about irrelevance of knowledge in a principled and efficient manner. Specifically, it is concerned with two key problems: (1) developing algorithms for automatically deciding what parts of a knowledge base are irrelevant to a query and (2) the utility of relevance reasoning. The dissertation describes a novel tool, the query-tree, for reasoning about irrelevance. Based on the query-tree, we develop several algorithms for deciding what formulas are irrelevant to a query. Our general framework sheds new light on the problem of detecting independence of queries from updates. We present new results that significantly extend previous work in this area. The framework also provides a setting in which to investigate the connection between the notion of irrelevance and the creation of abstractions. We propose a new approach to research on reasoning with abstractions, in which we investigate the properties of an abstraction by considering the irrelevance claims on which it is based. We demonstrate the potential of the approach for the cases of abstraction of predicates and projection of predicate arguments. Finally, we describe an application of relevance reasoning to the domain of modeling physical devices.

Case-based reasoning diagnostic technique based on multi-attribute similarity

Energy Technology Data Exchange (ETDEWEB)

Makoto, Takahashi [Tohoku University, Miyagi (Japan); Akio, Gofuku [Okayama University, Okayamaa (Japan)

2014-08-15

Case-based diagnostic technique has been developed based on the multi-attribute similarity. Specific feature of the developed system is to use multiple attributes of process signals for similarity evaluation to retrieve a similar case stored in a case base. The present technique has been applied to the measurement data from Monju with some simulated anomalies. The results of numerical experiments showed that the present technique can be utilizes as one of the methods for a hybrid-type diagnosis system.

Fuzzy Case-Based Reasoning in Product Style Acquisition Incorporating Valence-Arousal-Based Emotional Cellular Model

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Fuqian Shi

2012-01-01

Full Text Available Emotional cellular (EC, proposed in our previous works, is a kind of semantic cell that contains kernel and shell and the kernel is formalized by a triple- L = , where P denotes a typical set of positive examples relative to word-L, d is a pseudodistance measure on emotional two-dimensional space: valence-arousal, and δ is a probability density function on positive real number field. The basic idea of EC model is to assume that the neighborhood radius of each semantic concept is uncertain, and this uncertainty will be measured by one-dimensional density function δ. In this paper, product form features were evaluated by using ECs and to establish the product style database, fuzzy case based reasoning (FCBR model under a defined similarity measurement based on fuzzy nearest neighbors (FNN incorporating EC was applied to extract product styles. A mathematical formalized inference system for product style was also proposed, and it also includes uncertainty measurement tool emotional cellular. A case study of style acquisition of mobile phones illustrated the effectiveness of the proposed methodology.

Cost-sensitive case-based reasoning using a genetic algorithm: application to medical diagnosis.

Science.gov (United States)

Park, Yoon-Joo; Chun, Se-Hak; Kim, Byung-Chun

2011-02-01

The paper studies the new learning technique called cost-sensitive case-based reasoning (CSCBR) incorporating unequal misclassification cost into CBR model. Conventional CBR is now considered as a suitable technique for diagnosis, prognosis and prescription in medicine. However it lacks the ability to reflect asymmetric misclassification and often assumes that the cost of a positive diagnosis (an illness) as a negative one (no illness) is the same with that of the opposite situation. Thus, the objective of this research is to overcome the limitation of conventional CBR and encourage applying CBR to many real world medical cases associated with costs of asymmetric misclassification errors. The main idea involves adjusting the optimal cut-off classification point for classifying the absence or presence of diseases and the cut-off distance point for selecting optimal neighbors within search spaces based on similarity distribution. These steps are dynamically adapted to new target cases using a genetic algorithm. We apply this proposed method to five real medical datasets and compare the results with two other cost-sensitive learning methods-C5.0 and CART. Our finding shows that the total misclassification cost of CSCBR is lower than other cost-sensitive methods in many cases. Even though the genetic algorithm has limitations in terms of unstable results and over-fitting training data, CSCBR results with GA are better overall than those of other methods. Also the paired t-test results indicate that the total misclassification cost of CSCBR is significantly less than C5.0 and CART for several datasets. We have proposed a new CBR method called cost-sensitive case-based reasoning (CSCBR) that can incorporate unequal misclassification costs into CBR and optimize the number of neighbors dynamically using a genetic algorithm. It is meaningful not only for introducing the concept of cost-sensitive learning to CBR, but also for encouraging the use of CBR in the medical area

Using case-based reasoning for the reconstitution and manipulation of voxelized phantoms

International Nuclear Information System (INIS)

Henriet, J.; Fontaine, E.; Bopp, M.; Makovicka, L.; Farah, J.; Broggio, D.; Franck, D.; Chebel-Morello, B.

2010-01-01

The authors reports the development of the EquiVox platform, the aim of which is to allow a radioprotection expert (physician, biologist or other) to work with a phantom which will be the closest possible to the examined person in order to make an as precise as possible dosimetric assessment. The objective is to help to select the best phantom among those the expert knows depending on the assessment type he wants to make. First, they present the general principles of the case-based reasoning, and then the EquiVox platform which proposes all the steps: formalization, elaboration, comparison, and so on. Based on typical numerical values associated with different morphological characteristics, they present and discuss graphical results obtained by the platform. They also discuss their validity and reliability

Toward translational incremental similarity-based reasoning in breast cancer grading

Science.gov (United States)

Tutac, Adina E.; Racoceanu, Daniel; Leow, Wee-Keng; Müller, Henning; Putti, Thomas; Cretu, Vladimir

2009-02-01

One of the fundamental issues in bridging the gap between the proliferation of Content-Based Image Retrieval (CBIR) systems in the scientific literature and the deficiency of their usage in medical community is based on the characteristic of CBIR to access information by images or/and text only. Yet, the way physicians are reasoning about patients leads intuitively to a case representation. Hence, a proper solution to overcome this gap is to consider a CBIR approach inspired by Case-Based Reasoning (CBR), which naturally introduces medical knowledge structured by cases. Moreover, in a CBR system, the knowledge is incrementally added and learned. The purpose of this study is to initiate a translational solution from CBIR algorithms to clinical practice, using a CBIR/CBR hybrid approach. Therefore, we advance the idea of a translational incremental similarity-based reasoning (TISBR), using combined CBIR and CBR characteristics: incremental learning of medical knowledge, medical case-based structure of the knowledge (CBR), image usage to retrieve similar cases (CBIR), similarity concept (central for both paradigms). For this purpose, three major axes are explored: the indexing, the cases retrieval and the search refinement, applied to Breast Cancer Grading (BCG), a powerful breast cancer prognosis exam. The effectiveness of this strategy is currently evaluated over cases provided by the Pathology Department of Singapore National University Hospital, for the indexing. With its current accuracy, TISBR launches interesting perspectives for complex reasoning in future medical research, opening the way to a better knowledge traceability and a better acceptance rate of computer-aided diagnosis assistance among practitioners.

Optimization of the Case Based Reasoning Systems

International Nuclear Information System (INIS)

Mohamed, A.H.

2014-01-01

Intrusion Detection System (IDS) have a great importance in saving the authority of the information widely spread all over the world through the networks. Many Case Based Systems concerned on the different methods of the unauthorized users/hackers that face the developers of the IDS. The proposed system introduces a new hybrid system that uses the genetic algorithm to optimize an IDS - case based system. It can detect the new anomalies appeared through the network and use the cases in the case library to determine the suitable solution for their behavior. The suggested system can solve the problem either by using an old identical solution or adapt the optimum one till have the targeted solution. The proposed system has been applied to block unauthorized users / hackers from attach the medical images for radiotherapy of the cancer diseases during their transmission through web. The proposed system can prove its accepted performance in this manner

Knowledge-light adaptation approaches in case-based reasoning for radiotherapy treatment planning.

Science.gov (United States)

Petrovic, Sanja; Khussainova, Gulmira; Jagannathan, Rupa

2016-03-01

Radiotherapy treatment planning aims at delivering a sufficient radiation dose to cancerous tumour cells while sparing healthy organs in the tumour-surrounding area. It is a time-consuming trial-and-error process that requires the expertise of a group of medical experts including oncologists and medical physicists and can take from 2 to 3h to a few days. Our objective is to improve the performance of our previously built case-based reasoning (CBR) system for brain tumour radiotherapy treatment planning. In this system, a treatment plan for a new patient is retrieved from a case base containing patient cases treated in the past and their treatment plans. However, this system does not perform any adaptation, which is needed to account for any difference between the new and retrieved cases. Generally, the adaptation phase is considered to be intrinsically knowledge-intensive and domain-dependent. Therefore, an adaptation often requires a large amount of domain-specific knowledge, which can be difficult to acquire and often is not readily available. In this study, we investigate approaches to adaptation that do not require much domain knowledge, referred to as knowledge-light adaptation. We developed two adaptation approaches: adaptation based on machine-learning tools and adaptation-guided retrieval. They were used to adapt the beam number and beam angles suggested in the retrieved case. Two machine-learning tools, neural networks and naive Bayes classifier, were used in the adaptation to learn how the difference in attribute values between the retrieved and new cases affects the output of these two cases. The adaptation-guided retrieval takes into consideration not only the similarity between the new and retrieved cases, but also how to adapt the retrieved case. The research was carried out in collaboration with medical physicists at the Nottingham University Hospitals NHS Trust, City Hospital Campus, UK. All experiments were performed using real-world brain cancer

A self-adaptive case-based reasoning system for dose planning in prostate cancer radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Mishra, Nishikant; Petrovic, Sanja; Sundar, Santhanam [Automated Scheduling, Optimisation and Planning Research Group, School of Computer Science, University of Nottingham, Nottingham NG8 1BB (United Kingdom); Department of Oncology, Nottingham University Hospitals NHS Trust, Nottingham NG5 1PB (United Kingdom)

2011-12-15

Purpose: Prostate cancer is the most common cancer in the male population. Radiotherapy is often used in the treatment for prostate cancer. In radiotherapy treatment, the oncologist makes a trade-off between the risk and benefit of the radiation, i.e., the task is to deliver a high dose to the prostate cancer cells and minimize side effects of the treatment. The aim of our research is to develop a software system that will assist the oncologist in planning new treatments. Methods: A nonlinear case-based reasoning system is developed to capture the expertise and experience of oncologists in treating previous patients. Importance (weights) of different clinical parameters in the dose planning is determined by the oncologist based on their past experience, and is highly subjective. The weights are usually fixed in the system. In this research, the weights are updated automatically each time after generating a treatment plan for a new patient using a group based simulated annealing approach. Results: The developed approach is analyzed on the real data set collected from the Nottingham University Hospitals NHS Trust, City Hospital Campus, UK. Extensive experiments show that the dose plan suggested by the proposed method is coherent with the dose plan prescribed by an experienced oncologist or even better. Conclusions: The developed case-based reasoning system enables the use of knowledge and experience gained by the oncologist in treating new patients. This system may play a vital role to assist the oncologist in making a better decision in less computational time; it utilizes the success rate of the previously treated patients and it can also be used in teaching and training processes.

A self-adaptive case-based reasoning system for dose planning in prostate cancer radiotherapy

International Nuclear Information System (INIS)

Mishra, Nishikant; Petrovic, Sanja; Sundar, Santhanam

2011-01-01

Purpose: Prostate cancer is the most common cancer in the male population. Radiotherapy is often used in the treatment for prostate cancer. In radiotherapy treatment, the oncologist makes a trade-off between the risk and benefit of the radiation, i.e., the task is to deliver a high dose to the prostate cancer cells and minimize side effects of the treatment. The aim of our research is to develop a software system that will assist the oncologist in planning new treatments. Methods: A nonlinear case-based reasoning system is developed to capture the expertise and experience of oncologists in treating previous patients. Importance (weights) of different clinical parameters in the dose planning is determined by the oncologist based on their past experience, and is highly subjective. The weights are usually fixed in the system. In this research, the weights are updated automatically each time after generating a treatment plan for a new patient using a group based simulated annealing approach. Results: The developed approach is analyzed on the real data set collected from the Nottingham University Hospitals NHS Trust, City Hospital Campus, UK. Extensive experiments show that the dose plan suggested by the proposed method is coherent with the dose plan prescribed by an experienced oncologist or even better. Conclusions: The developed case-based reasoning system enables the use of knowledge and experience gained by the oncologist in treating new patients. This system may play a vital role to assist the oncologist in making a better decision in less computational time; it utilizes the success rate of the previously treated patients and it can also be used in teaching and training processes.

Case-based clinical reasoning in feline medicine: 3: Use of heuristics and illness scripts.

Science.gov (United States)

Whitehead, Martin L; Canfield, Paul J; Johnson, Robert; O'Brien, Carolyn R; Malik, Richard

2016-05-01

This is Article 3 of a three-part series on clinical reasoning that encourages practitioners to explore and understand how they think and make case-based decisions. It is hoped that, in the process, they will learn to trust their intuition but, at the same time, put in place safeguards to diminish the impact of bias and misguided logic on their diagnostic decision-making. Article 1, published in the January 2016 issue of JFMS, discussed the relative merits and shortcomings of System 1 thinking (immediate and unconscious) and System 2 thinking (effortful and analytical). In Article 2, published in the March 2016 issue, ways of managing cognitive error, particularly the negative impact of bias, in making a diagnosis were examined. This final article explores the use of heuristics (mental short cuts) and illness scripts in diagnostic reasoning. © The Author(s) 2016.

Reasoning based in cases applied to diagnosis of electric generators; Razonamiento basado en casos aplicado al diagnostico de generadores electricos

Energy Technology Data Exchange (ETDEWEB)

De la Torre Vega, H. Octavio; Garcia Tevillo, Arturo; Campuzano Martinez, Roberto [Instituto de Investigaciones Electricas, Temixco, Morelos (Mexico); Lopez Azamar, Ernesto [Comision Federal de Electricidad (Mexico)

2000-07-01

The development of a system for the diagnosis of electrical generators that apply techniques of artificial intelligence, is presented, as it is the reasoning based on cases, to support the work of the diagnosis engineer. This system is part of a system called CADIS, dedicated to the diagnosis of electrical generators out of line and reason of previous articles. In this occasion the characteristics of the reasoning module based on experiences (SirBE) are emphasized, indicating how to make a diagnosis using similar cases and how to edit the system base of experience, using the interactive editor of cases. It is included, in addition, a summarized example which represents a case for SirBE and how the system helps to make a diagnosis. [Spanish] Se presenta el desarrollo de un sistema de diagnostico de generadores electricos que aplica tecnicas de inteligencia artificial, como es el razonamiento basado en casos, para apoyar la labor del ingeniero de diagnostico. Este sistema es parte de un sistema denominado CADIS, dedicado al diagnostico de generadores electricos fuera de linea y motivo de articulos anteriores. En esta ocasion se resaltan las caracteristicas del modulo de razonamiento basado en experiencias (SirBE), indicando como realizar un diagnostico utilizando casos similares y como editar la base de experiencia del sistema utilizando el editor interactivo de casos. Se incluye, ademas, un ejemplo resumido de lo que representa un caso para SiRBE y como el sistema ayuda a realizar un diagnostico.

A conversational case-based reasoning approach to assisting experts in solving professional problems

Directory of Open Access Journals (Sweden)

Negar Armaghan

2018-03-01

Full Text Available Nowadays, organizations attempt to retrieve, collect, preserve and manage knowledge and experience of experts in order to reuse them later and to promote innovation. In this sense, Experience Management is one of the important organizational issues. This article is discussed the main ideas of a future Conversational Case-Based Reasoning (CCBR intended to assist the experts of after-sales service in a French industrial company. The aim of this research is to formalize the experience of experts in after-sales service in order to better reuse them for similar problems in future. The research opts for an action research method which consists of two main parts: description of failure and proposition of decision protocol. The data were complemented by questionnaires, documentary analysis (including technical reports and other technical documents, observation and many interviews with experts. The findings include several aspects: the formalization of Problem-solving Cards, proposing the structure of case base, as well as the framework of proposed system. These formalizations permit after-sales service experts to provide effective diagnosis and problem-solving.

A case-based assistant for clinical psychiatry expertise.

OpenAIRE

Bichindaritz, I.

1994-01-01

Case-based reasoning is an artificial intelligence methodology for the processing of empirical knowledge. Recent case-based reasoning systems also use theoretic knowledge about the domain to constrain the case-based reasoning. The organization of the memory is the key issue in case-based reasoning. The case-based assistant presented here has two structures in memory: cases and concepts. These memory structures permit it to be as skilled in problem-solving tasks, such as diagnosis and treatmen...

Reasoning by cases in Default Logic

NARCIS (Netherlands)

Roos, N.; Roos, Nico

1998-01-01

Reiter's Default Logic is one of the most popular formalisms for describing default reasoning. One important defect of Default Logic is, however, the inability to reason by cases. Over the years, several solutions for this problem have been proposed. All these proposals deal with deriving new

A combined data mining approach using rough set theory and case-based reasoning in medical datasets

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Mohammad Taghi Rezvan

2014-06-01

Full Text Available Case-based reasoning (CBR is the process of solving new cases by retrieving the most relevant ones from an existing knowledge-base. Since, irrelevant or redundant features not only remarkably increase memory requirements but also the time complexity of the case retrieval, reducing the number of dimensions is an issue worth considering. This paper uses rough set theory (RST in order to reduce the number of dimensions in a CBR classifier with the aim of increasing accuracy and efficiency. CBR exploits a distance based co-occurrence of categorical data to measure similarity of cases. This distance is based on the proportional distribution of different categorical values of features. The weight used for a feature is the average of co-occurrence values of the features. The combination of RST and CBR has been applied to real categorical datasets of Wisconsin Breast Cancer, Lymphography, and Primary cancer. The 5-fold cross validation method is used to evaluate the performance of the proposed approach. The results show that this combined approach lowers computational costs and improves performance metrics including accuracy and interpretability compared to other approaches developed in the literature.

Case Studies of Secondary School Teachers Designing Socioscientific Issues-Based Instruction and Their Students' Socioscientific Reasoning

Science.gov (United States)

Karahan, Engin

Addressing socioscientific issues (SSI) has been one of the main focuses in science education since the Science, Technology, and Society (STS) movement in the 1970s (Levinson, 2006); however, teaching controversial socioscientific issues has always been challenging for teachers (Dillon, 1994; Osborne, Duschl, & Fairbrother, 2002). Although teachers exhibit positive attitudes for using controversial socioscientific issues in their science classrooms, only a small percentage of them actually incorporate SSI content into their science curricula on a regular basis (Sadler, Amirshokoohi, Kazempour, & Allspaw, 2006; Lee & Witz, 2009). The literature in science education has highlighted the signi?cant relationships among teacher beliefs, teaching practices, and student learning (Bryan & Atwater, 2002; King, Shumow, & Lietz, 2001; Lederman, 1992). Despite the fact that the case studies present a relatively detailed picture of teachers' values and motivations for teaching SSI (e.g. Lee, 2006; Lee & Witz, 2009; Reis & Galvao, 2004), these studies still miss the practices of these teachers and potential outcomes for their students. Therefore, there is a great need for in-depth case studies that would focus on teachers' practices of designing and teaching SSI-based learning environments, their deeper beliefs and motivations for teaching SSI, and their students' response to these practices (Lee, 2006). This dissertation is structured as three separate, but related, studies about secondary school teachers' experiences of designing and teaching SSI-based classes and their students' understanding of science and SSI reasoning. The case studies in this dissertation seek answers for (1) teachers' practices of designing and teaching SSI-based instruction, as well as its relation to their deeper personal beliefs and motivations to teach SSI, and (2) how their students respond to their approaches of teaching SSI in terms of their science understanding and SSI reasoning. The first paper

A case-based assistant for clinical psychiatry expertise.

Science.gov (United States)

Bichindaritz, I

1994-01-01

Case-based reasoning is an artificial intelligence methodology for the processing of empirical knowledge. Recent case-based reasoning systems also use theoretic knowledge about the domain to constrain the case-based reasoning. The organization of the memory is the key issue in case-based reasoning. The case-based assistant presented here has two structures in memory: cases and concepts. These memory structures permit it to be as skilled in problem-solving tasks, such as diagnosis and treatment planning, as in interpretive tasks, such as clinical research. A prototype applied to clinical work about eating disorders in psychiatry, reasoning from the alimentary questionnaires of these patients, is presented as an example of the system abilities.

A prognostic model for temporal courses that combines temporal abstraction and case-based reasoning.

Science.gov (United States)

Schmidt, Rainer; Gierl, Lothar

2005-03-01

Since clinical management of patients and clinical research are essentially time-oriented endeavours, reasoning about time has become a hot topic in medical informatics. Here we present a method for prognosis of temporal courses, which combines temporal abstractions with case-based reasoning. It is useful for application domains where neither well-known standards, nor known periodicity, nor a complete domain theory exist. We have used our method in two prognostic applications. The first one deals with prognosis of the kidney function for intensive care patients. The idea is to elicit impairments on time, especially to warn against threatening kidney failures. Our second application deals with a completely different domain, namely geographical medicine. Its intention is to compute early warnings against approaching infectious diseases, which are characterised by irregular cyclic occurrences. So far, we have applied our program on influenza and bronchitis. In this paper, we focus on influenza forecast and show first experimental results.

Case-based medical informatics

Directory of Open Access Journals (Sweden)

Arocha José F

2004-11-01

Full Text Available Abstract Background The "applied" nature distinguishes applied sciences from theoretical sciences. To emphasize this distinction, we begin with a general, meta-level overview of the scientific endeavor. We introduce the knowledge spectrum and four interconnected modalities of knowledge. In addition to the traditional differentiation between implicit and explicit knowledge we outline the concepts of general and individual knowledge. We connect general knowledge with the "frame problem," a fundamental issue of artificial intelligence, and individual knowledge with another important paradigm of artificial intelligence, case-based reasoning, a method of individual knowledge processing that aims at solving new problems based on the solutions to similar past problems. We outline the fundamental differences between Medical Informatics and theoretical sciences and propose that Medical Informatics research should advance individual knowledge processing (case-based reasoning and that natural language processing research is an important step towards this goal that may have ethical implications for patient-centered health medicine. Discussion We focus on fundamental aspects of decision-making, which connect human expertise with individual knowledge processing. We continue with a knowledge spectrum perspective on biomedical knowledge and conclude that case-based reasoning is the paradigm that can advance towards personalized healthcare and that can enable the education of patients and providers. We center the discussion on formal methods of knowledge representation around the frame problem. We propose a context-dependent view on the notion of "meaning" and advocate the need for case-based reasoning research and natural language processing. In the context of memory based knowledge processing, pattern recognition, comparison and analogy-making, we conclude that while humans seem to naturally support the case-based reasoning paradigm (memory of past experiences

Penerapan Case-Based Reasoning Pada Sistem Cerdas Untuk Pendeteksian dan Penanganan Dini Penyakit Sapi

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Irlando Moggi Prakoso

2012-09-01

Full Text Available Penyakit sapi memberikan dampak yang signifikan terhadap penurunan produksi daging bagi para peternak sapi. Untuk meminimalisir dampak dari penyakit perlu dilakukan pendeteksian dan penanganan dini untuk mencegah tingginya kerugian yang terjadi. Sistem cerdas dapat memudahkan peternak sapi untuk mendiagnosa secara mandiri. Penelitian sebelumnya menghasilkan sistem cerdas  untuk mendiagnosa penyakit sapi menggunakan algoritma Backpropagation Artificial neural Network(ANN. Namun ANN bersifat black-box karena kita tidak dapat melihat informasi yang mendasari hasil diagnosa. Tugas akhir ini memiliki tujuan untuk menjawab permasalahan tersebut, yakni dengan membuat sistem cerdas berbasis Cased-Based Reasoning(CBR untuk menyempurnakan sistem cerdas yang sebelumnya dibuat menggunakan ANN. CBR memberikan hasil diagnosa berdasarkan permasalahan terdahulu yang dapat direvisi untuk memecahkan permasalahan terbaru. Dari ketiga uji coba dengan case didalam case memory(skenario 1, diluar case memory(skenario 2, dan gejala parsial dari case memory(skenario 3 mendapatkan hasil yang baik dengan nilai precision 100% dan 95.83% untuk skenario 1 dan 3.   Serta nilai precision yang memang kurang baik untuk skenario 2 sebesar 59.31%. Dengan demikian, sistem cerdas ini dapat memberikan hasil diagnosa yang akurat dan memudahkan peternak sapi dalam mendiagnosa secara mandiri.

A Cold Start Context-Aware Recommender System for Tour Planning Using Artificial Neural Network and Case Based Reasoning

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Zahra Bahramian

2017-01-01

Full Text Available Nowadays, large amounts of tourism information and services are available over the Web. This makes it difficult for the user to search for some specific information such as selecting a tour in a given city as an ordered set of points of interest. Moreover, the user rarely knows all his needs upfront and his preferences may change during a recommendation process. The user may also have a limited number of initial ratings and most often the recommender system is likely to face the well-known cold start problem. The objective of the research presented in this paper is to introduce a hybrid interactive context-aware tourism recommender system that takes into account user’s feedbacks and additional contextual information. It offers personalized tours to the user based on his preferences thanks to the combination of a case based reasoning framework and an artificial neural network. The proposed method has been tried in the city of Tehran in Iran. The results show that the proposed method outperforms current artificial neural network methods and combinations of case based reasoning with k-nearest neighbor methods in terms of user effort, accuracy, and user satisfaction.

Learning and case-based reasoning for faults diagnosis-aiding in nuclear power plants

International Nuclear Information System (INIS)

Nicolini, C.

1998-01-01

The aim of this thesis is the design of a faults diagnosis-aiding system in a nuclear facility of the Cea. Actually the existing system allows the optimization of the production processes in regular operating conditions. Meanwhile during accidental events, the alarms, managed by threshold, are bringing no relevant information. To increase the reliability and the safety, the human operator needs a faults diagnosis-aiding system. The developed system, SECAPI, combines problem solving techniques and automatic learning techniques, that allow the diagnosis and the the simulation of various faults happening on nuclear facilities. Its reasoning principle uses case-based and rules-based techniques. SECAPI owns a learning module which reads out knowledge connected with faults. It can then simulate various faults, using the inductive logical computing. SECAPI has been applied on a radioactive tritium treatment operating channel, at the Cea with good results. (A.L.B.)

A Case-based Reasoning Approach to Validate Grammatical Gender and Number Agreement in Spanish language

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Jorge Bacca

2013-03-01

Full Text Available Across Latin America 420 indigenous languages are spoken. Spanish is considered a second language in indigenous communities and is progressively introduced in education. However, most of the tools to support teaching processes of a second language have been developed for the most common languages such as English, French, German, Italian, etc. As a result, only a small amount of learning objects and authoring tools have been developed for indigenous people considering the specific needs of their population. This paper introduces Multilingual–Tiny as a web authoring tool to support the virtual experience of indigenous students and teachers when they are creating learning objects in indigenous languages or in Spanish language, in particular, when they have to deal with the grammatical structures of Spanish. Multilingual–Tiny has a module based on the Case-based Reasoning technique to provide recommendations in real time when teachers and students write texts in Spanish. An experiment was performed in order to compare some local similarity functions to retrieve cases from the case library taking into account the grammatical structures. As a result we found the similarity function with the best performance

Model Based Temporal Reasoning

Science.gov (United States)

Rabin, Marla J.; Spinrad, Paul R.; Fall, Thomas C.

1988-03-01

Systems that assess the real world must cope with evidence that is uncertain, ambiguous, and spread over time. Typically, the most important function of an assessment system is to identify when activities are occurring that are unusual or unanticipated. Model based temporal reasoning addresses both of these requirements. The differences among temporal reasoning schemes lies in the methods used to avoid computational intractability. If we had n pieces of data and we wanted to examine how they were related, the worst case would be where we had to examine every subset of these points to see if that subset satisfied the relations. This would be 2n, which is intractable. Models compress this; if several data points are all compatible with a model, then that model represents all those data points. Data points are then considered related if they lie within the same model or if they lie in models that are related. Models thus address the intractability problem. They also address the problem of determining unusual activities if the data do not agree with models that are indicated by earlier data then something out of the norm is taking place. The models can summarize what we know up to that time, so when they are not predicting correctly, either something unusual is happening or we need to revise our models. The model based reasoner developed at Advanced Decision Systems is thus both intuitive and powerful. It is currently being used on one operational system and several prototype systems. It has enough power to be used in domains spanning the spectrum from manufacturing engineering and project management to low-intensity conflict and strategic assessment.

Modelling Legal Argument: Reasoning with Cases and Hypotheticals

Science.gov (United States)

1988-02-01

case- based reasoning plays an important role in such diverse domains as law [Levi, 1949), historical political analysis [Neustadt and May, 1986; Alker...contained information on physical, economic and political disputes and common mediation 5 tactics, their failures and corrections for those failures...library of 13 Wall Street. He had opera tickets in his pocket for 8:00 that night - "Pagliacci" - and his socialite fiance and her parents were to

Design of a Golf Swing Injury Detection and Evaluation open service platform with Ontology-oriented clustering case-based reasoning mechanism.

Science.gov (United States)

Ku, Hao-Hsiang

2015-01-01

Nowadays, people can easily use a smartphone to get wanted information and requested services. Hence, this study designs and proposes a Golf Swing Injury Detection and Evaluation open service platform with Ontology-oritened clustering case-based reasoning mechanism, which is called GoSIDE, based on Arduino and Open Service Gateway initative (OSGi). GoSIDE is a three-tier architecture, which is composed of Mobile Users, Application Servers and a Cloud-based Digital Convergence Server. A mobile user is with a smartphone and Kinect sensors to detect the user's Golf swing actions and to interact with iDTV. An application server is with Intelligent Golf Swing Posture Analysis Model (iGoSPAM) to check a user's Golf swing actions and to alter this user when he is with error actions. Cloud-based Digital Convergence Server is with Ontology-oriented Clustering Case-based Reasoning (CBR) for Quality of Experiences (OCC4QoE), which is designed to provide QoE services by QoE-based Ontology strategies, rules and events for this user. Furthermore, GoSIDE will automatically trigger OCC4QoE and deliver popular rules for a new user. Experiment results illustrate that GoSIDE can provide appropriate detections for Golfers. Finally, GoSIDE can be a reference model for researchers and engineers.

Safety early warning research for highway construction based on case-based reasoning and variable fuzzy sets.

Science.gov (United States)

Liu, Yan; Yi, Ting-Hua; Xu, Zhen-Jun

2013-01-01

As a high-risk subindustry involved in construction projects, highway construction safety has experienced major developments in the past 20 years, mainly due to the lack of safe early warnings in Chinese construction projects. By combining the current state of early warning technology with the requirements of the State Administration of Work Safety and using case-based reasoning (CBR), this paper expounds on the concept and flow of highway construction safety early warnings based on CBR. The present study provides solutions to three key issues, index selection, accident cause association analysis, and warning degree forecasting implementation, through the use of association rule mining, support vector machine classifiers, and variable fuzzy qualitative and quantitative change criterion modes, which fully cover the needs of safe early warning systems. Using a detailed description of the principles and advantages of each method and by proving the methods' effectiveness and ability to act together in safe early warning applications, effective means and intelligent technology for a safe highway construction early warning system are established.

Safety Early Warning Research for Highway Construction Based on Case-Based Reasoning and Variable Fuzzy Sets

Directory of Open Access Journals (Sweden)

Yan Liu

2013-01-01

Full Text Available As a high-risk subindustry involved in construction projects, highway construction safety has experienced major developments in the past 20 years, mainly due to the lack of safe early warnings in Chinese construction projects. By combining the current state of early warning technology with the requirements of the State Administration of Work Safety and using case-based reasoning (CBR, this paper expounds on the concept and flow of highway construction safety early warnings based on CBR. The present study provides solutions to three key issues, index selection, accident cause association analysis, and warning degree forecasting implementation, through the use of association rule mining, support vector machine classifiers, and variable fuzzy qualitative and quantitative change criterion modes, which fully cover the needs of safe early warning systems. Using a detailed description of the principles and advantages of each method and by proving the methods’ effectiveness and ability to act together in safe early warning applications, effective means and intelligent technology for a safe highway construction early warning system are established.

A case-based reasoning approach for estimating the costs of pump station projects

Directory of Open Access Journals (Sweden)

Mohamed M. Marzouk

2011-10-01

Full Text Available The effective estimation of costs is crucial to the success of construction projects. Cost estimates are used to evaluate, approve and/or fund projects. Organizations use some form of classification system to identify the various types of estimates that may be prepared during the lifecycle of a project. This research presents a parametric-cost model for pump station projects. Fourteen factors have been identified as important to the influence of the cost of pump station projects. A data set that consists of forty-four pump station projects (fifteen water and twenty-nine waste water are collected to build a Case-Based Reasoning (CBR library and to test its performance. The results obtained from the CBR tool are processed and adopted to improve the accuracy of the results. A numerical example is presented to demonstrate the development of the effectiveness of the tool.

Case based reasoning applied to medical diagnosis using multi-class classifier: A preliminary study

Directory of Open Access Journals (Sweden)

D. Viveros-Melo

2017-02-01

Full Text Available Case-based reasoning (CBR is a process used for computer processing that tries to mimic the behavior of a human expert in making decisions regarding a subject and learn from the experience of past cases. CBR has demonstrated to be appropriate for working with unstructured domains data or difficult knowledge acquisition situations, such as medical diagnosis, where it is possible to identify diseases such as: cancer diagnosis, epilepsy prediction and appendicitis diagnosis. Some of the trends that may be developed for CBR in the health science are oriented to reduce the number of features in highly dimensional data. An important contribution may be the estimation of probabilities of belonging to each class for new cases. In this paper, in order to adequately represent the database and to avoid the inconveniences caused by the high dimensionality, noise and redundancy, a number of algorithms are used in the preprocessing stage for performing both variable selection and dimension reduction procedures. Also, a comparison of the performance of some representative multi-class classifiers is carried out to identify the most effective one to include within a CBR scheme. Particularly, four classification techniques and two reduction techniques are employed to make a comparative study of multiclass classifiers on CBR

Monitoring progression of clinical reasoning skills during health sciences education using the case method - a qualitative observational study.

Science.gov (United States)

Orban, Kristina; Ekelin, Maria; Edgren, Gudrun; Sandgren, Olof; Hovbrandt, Pia; Persson, Eva K

2017-09-11

Outcome- or competency-based education is well established in medical and health sciences education. Curricula are based on courses where students develop their competences and assessment is also usually course-based. Clinical reasoning is an important competence, and the aim of this study was to monitor and describe students' progression in professional clinical reasoning skills during health sciences education using observations of group discussions following the case method. In this qualitative study students from three different health education programmes were observed while discussing clinical cases in a modified Harvard case method session. A rubric with four dimensions - problem-solving process, disciplinary knowledge, character of discussion and communication - was used as an observational tool to identify clinical reasoning. A deductive content analysis was performed. The results revealed the students' transition over time from reasoning based strictly on theoretical knowledge to reasoning ability characterized by clinical considerations and experiences. Students who were approaching the end of their education immediately identified the most important problem and then focused on this in their discussion. Practice knowledge increased over time, which was seen as progression in the use of professional language, concepts, terms and the use of prior clinical experience. The character of the discussion evolved from theoretical considerations early in the education to clinical reasoning in later years. Communication within the groups was supportive and conducted with a professional tone. Our observations revealed progression in several aspects of students' clinical reasoning skills on a group level in their discussions of clinical cases. We suggest that the case method can be a useful tool in assessing quality in health sciences education.

Screening of pollution control and clean-up materials for river chemical spills using the multiple case-based reasoning method with a difference-driven revision strategy.

Science.gov (United States)

Liu, Rentao; Jiang, Jiping; Guo, Liang; Shi, Bin; Liu, Jie; Du, Zhaolin; Wang, Peng

2016-06-01

In-depth filtering of emergency disposal technology (EDT) and materials has been required in the process of environmental pollution emergency disposal. However, an urgent problem that must be solved is how to quickly and accurately select the most appropriate materials for treating a pollution event from the existing spill control and clean-up materials (SCCM). To meet this need, the following objectives were addressed in this study. First, the material base and a case base for environment pollution emergency disposal were established to build a foundation and provide material for SCCM screening. Second, the multiple case-based reasoning model method with a difference-driven revision strategy (DDRS-MCBR) was applied to improve the original dual case-based reasoning model method system, and screening and decision-making was performed for SCCM using this model. Third, an actual environmental pollution accident from 2012 was used as a case study to verify the material base, case base, and screening model. The results demonstrated that the DDRS-MCBR method was fast, efficient, and practical. The DDRS-MCBR method changes the passive situation in which the choice of SCCM screening depends only on the subjective experience of the decision maker and offers a new approach to screening SCCM.

DALI - drilling advisor with logic interpretations: methodological issues for designing underbalanced drilling operations. Improving efficiency using case-based reasonic

Energy Technology Data Exchange (ETDEWEB)

Santana, Gustavo A.; Velazquez C, David [Mexican Oil Institute, Mexico DF (Mexico)

2004-07-01

A system that applies a method of knowledge-intensive case-based reasoning, for repair and prevention of unwanted events in the domain of offshore oil well drilling, has been developed in cooperation with an oil company. From several reoccurring problems during oil well drilling the problem of 'lost circulation', i.e. loss of circulating drilling fluid into the geological formation, was picked out as a pilot problem. An extensive general knowledge model was developed for the domain of oil well drilling. Different cases were created on the basis of information from one Mexican Gulf operator. When the completed CBR-system was tested against a new case, cases with descending similarity were selected by the tool. In an informal evaluation, the two best fitting cases proved to give the operator valuable advise on how to go about solving the new case (author)

Emotional reasoning and parent-based reasoning in normal children.

OpenAIRE

Morren, M.; Muris, P.; Kindt, M.

2004-01-01

A previous study by Muris, Merckelbach, and Van Spauwen demonstrated that children display emotional reasoning irrepective of their anxiety levels. That is when estimating whether a situation is dangerous, childen not only rely on objective danger information but also on their own anciety-response. The present study further examined emotional reasoning in childeren aged 7-13 years (N=508). In addition, it was investigated whether children also show parent-based reasoning, which can be defined...

What physicians reason about during admission case review.

Science.gov (United States)

Juma, Salina; Goldszmidt, Mark

2017-08-01

Research suggests that physicians perform multiple reasoning tasks beyond diagnosis during patient review. However, these remain largely theoretical. The purpose of this study was to explore reasoning tasks in clinical practice during patient admission review. The authors used a constant comparative approach-an iterative and inductive process of coding and recoding-to analyze transcripts from 38 audio-recorded case reviews between junior trainees and their senior residents or attendings. Using a previous list of reasoning tasks, analysis focused on what tasks were performed, when they occurred, and how they related to the other tasks. All 24 tasks were observed in at least one review with a mean of 17.9 (Min = 15, Max = 22) distinct tasks per review. Two new tasks-assess illness severity and patient decision-making capacity-were identified, thus 26 tasks were examined. Three overarching tasks were identified-assess priorities, determine and refine the most likely diagnosis and establish and refine management plans-that occurred throughout all stages of the case review starting from patient identification and continuing through to assessment and plan. A fourth possible overarching task-reflection-was also identified but only observed in four instances across three cases. The other 22 tasks appeared to be context dependent serving to support, expand, and refine one or more overarching tasks. Tasks were non-sequential and the same supporting task could serve more than one overarching task. The authors conclude that these findings provide insight into the 'what' and 'when' of physician reasoning during case review that can be used to support professional development, clinical training and patient care. In particular, they draw attention to the iterative way in which each task is addressed during a case review and how this finding may challenge conventional ways of teaching and assessing clinical communication and reasoning. They also suggest that further research

Thermodynamic heuristics with case-based reasoning: combined insights for RNA pseudoknot secondary structure.

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Al-Khatib, Ra'ed M; Rashid, Nur'Aini Abdul; Abdullah, Rosni

2011-08-01

The secondary structure of RNA pseudoknots has been extensively inferred and scrutinized by computational approaches. Experimental methods for determining RNA structure are time consuming and tedious; therefore, predictive computational approaches are required. Predicting the most accurate and energy-stable pseudoknot RNA secondary structure has been proven to be an NP-hard problem. In this paper, a new RNA folding approach, termed MSeeker, is presented; it includes KnotSeeker (a heuristic method) and Mfold (a thermodynamic algorithm). The global optimization of this thermodynamic heuristic approach was further enhanced by using a case-based reasoning technique as a local optimization method. MSeeker is a proposed algorithm for predicting RNA pseudoknot structure from individual sequences, especially long ones. This research demonstrates that MSeeker improves the sensitivity and specificity of existing RNA pseudoknot structure predictions. The performance and structural results from this proposed method were evaluated against seven other state-of-the-art pseudoknot prediction methods. The MSeeker method had better sensitivity than the DotKnot, FlexStem, HotKnots, pknotsRG, ILM, NUPACK and pknotsRE methods, with 79% of the predicted pseudoknot base-pairs being correct.

MANAGEMENT OF A GUILLAIN BARRE SYNDROME PATIENT THROUGH THREE TRACK REASONING: A CASE STUDY

Directory of Open Access Journals (Sweden)

Shamima Islam Nipa

2015-12-01

Full Text Available Background: Clinical reasoning is a thinking and decision making process which occur in clinical practice. It helps the health care providers to solve the clinical problem by using their reasoning process in an effective and efficient manner. Three track reasoning in one of the clinical reasoning process which includes the procedural, interactive and conditional reasoning to diagnose as well as ensure proper rehabilitation service according to patient and patient’s family members’ needs. Methods: A single case based study through the three track reasoning process. The purpose of this study was to explore the management strategies of a Gullian Barrie Syndrome (GBS patient through three track reasoning. We have tried to show how the basic idea behind the reasoning process helped to determine the reasoning process and diagnosis. However it has performed through theory and observation. We have also showed how we used the reasoning process through with the common sense reasoning. However it was the part of procedural reasoning in three track clinical reasoning. In three track reasoning, there is also interactive and procedural reasoning part through which we told patient story about his condition, identified his and his family members expectations and to establish hypothesis as GBS. So three track reasoning also supported us to do reasoning process rather than selecting another reasoning process. Results: After analyzing the reasoning process it was identified that to be strict in a single reasoning process is very difficult. Clinical reasoning is the clinician’s ability through which they can consider the interpretation of different clinical findings. An expert clinician must have critical thinking skill rather than ignoring any symptoms or overemphasize the symptoms. In addition, patient’s knowledge, believes and reasoning was found an important part of clinical reasoning process in this study. Conclusion: We have been practicing clinical

Rule-Based Reasoning Is Fast and Belief-Based Reasoning Can Be Slow: Challenging Current Explanations of Belief-Bias and Base-Rate Neglect

Science.gov (United States)

Newman, Ian R.; Gibb, Maia; Thompson, Valerie A.

2017-01-01

It is commonly assumed that belief-based reasoning is fast and automatic, whereas rule-based reasoning is slower and more effortful. Dual-Process theories of reasoning rely on this speed-asymmetry explanation to account for a number of reasoning phenomena, such as base-rate neglect and belief-bias. The goal of the current study was to test this…

A Framework of Combining Case-Based Reasoning with a Work Breakdown Structure for Estimating the Cost of Online Course Production Projects

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He, Wu

2014-01-01

Currently, a work breakdown structure (WBS) approach is used as the most common cost estimation approach for online course production projects. To improve the practice of cost estimation, this paper proposes a novel framework to estimate the cost for online course production projects using a case-based reasoning (CBR) technique and a WBS. A…

Promoting student case creation to enhance instruction of clinical reasoning skills: a pilot feasibility study.

Science.gov (United States)

Chandrasekar, Hamsika; Gesundheit, Neil; Nevins, Andrew B; Pompei, Peter; Bruce, Janine; Merrell, Sylvia Bereknyei

2018-01-01

It is a common educational practice for medical students to engage in case-based learning (CBL) exercises by working through clinical cases that have been developed by faculty. While such faculty-developed exercises have educational strengths, there are at least two major drawbacks to learning by this method: the number and diversity of cases is often limited; and students decrease their engagement with CBL cases as they grow accustomed to the teaching method. We sought to explore whether student case creation can address both of these limitations. We also compared student case creation to traditional clinical reasoning sessions in regard to tutorial group effectiveness, perceived gains in clinical reasoning, and quality of student-faculty interaction. Ten first-year medical students participated in a feasibility study wherein they worked in small groups to develop their own patient case around a preassigned diagnosis. Faculty provided feedback on case quality afterwards. Students completed pre- and post-self-assessment surveys. Students and faculty also participated in separate focus groups to compare their case creation experience to traditional CBL sessions. Students reported high levels of team engagement and peer learning, as well as increased ownership over case content and understanding of clinical reasoning nuances. However, students also reported decreases in student-faculty interaction and the use of visual aids ( P study suggest that student-generated cases can be a valuable adjunct to traditional clinical reasoning instruction by increasing content ownership, encouraging student-directed learning, and providing opportunities to explore clinical nuances. However, these gains may reduce student-faculty interaction. Future studies may be able to identify an improved model of faculty participation, the ideal timing for incorporation of this method in a medical curriculum, and a more rigorous assessment of the impact of student case creation on the

Technology-based strategies for promoting clinical reasoning skills in nursing education.

Science.gov (United States)

Shellenbarger, Teresa; Robb, Meigan

2015-01-01

Faculty face the demand of preparing nursing students for the constantly changing health care environment. Effective use of online, classroom, and clinical conferencing opportunities helps to enhance nursing students' clinical reasoning capabilities needed for practice. The growth of technology creates an avenue for faculty to develop engaging learning opportunities. This article presents technology-based strategies such as electronic concept mapping, electronic case histories, and digital storytelling that can be used to facilitate clinical reasoning skills.

Risk Factors Analysis and Death Prediction in Some Life-Threatening Ailments Using Chi-Square Case-Based Reasoning (χ2 CBR) Model.

Science.gov (United States)

Adeniyi, D A; Wei, Z; Yang, Y

2018-01-30

A wealth of data are available within the health care system, however, effective analysis tools for exploring the hidden patterns in these datasets are lacking. To alleviate this limitation, this paper proposes a simple but promising hybrid predictive model by suitably combining the Chi-square distance measurement with case-based reasoning technique. The study presents the realization of an automated risk calculator and death prediction in some life-threatening ailments using Chi-square case-based reasoning (χ 2 CBR) model. The proposed predictive engine is capable of reducing runtime and speeds up execution process through the use of critical χ 2 distribution value. This work also showcases the development of a novel feature selection method referred to as frequent item based rule (FIBR) method. This FIBR method is used for selecting the best feature for the proposed χ 2 CBR model at the preprocessing stage of the predictive procedures. The implementation of the proposed risk calculator is achieved through the use of an in-house developed PHP program experimented with XAMP/Apache HTTP server as hosting server. The process of data acquisition and case-based development is implemented using the MySQL application. Performance comparison between our system, the NBY, the ED-KNN, the ANN, the SVM, the Random Forest and the traditional CBR techniques shows that the quality of predictions produced by our system outperformed the baseline methods studied. The result of our experiment shows that the precision rate and predictive quality of our system in most cases are equal to or greater than 70%. Our result also shows that the proposed system executes faster than the baseline methods studied. Therefore, the proposed risk calculator is capable of providing useful, consistent, faster, accurate and efficient risk level prediction to both the patients and the physicians at any time, online and on a real-time basis.

Case-Based Reasoning on E-Community Knowledge

OpenAIRE

Gaillard , Emmanuelle; Lieber , Jean; Naudet , Yannick; Nauer , Emmanuel

2013-01-01

International audience; This paper presents MKM, a meta-knowledge model to manage knowledge reliability, in order to extend a CBR system so that it can reason on partially reliable, non expert, knowledge from the Web. Knowledge reliability is considered from the point of view of the decision maker using the CBR system. It is captured by the MKM model including notions such as belief, trust, reputation and quality, as well as their relationships and rules to evaluate knowledge reliability. We ...

Designing Intelligent Tutoring Systems: A Personalization Strategy using Case-Based Reasoning and Multi-Agent Systems

Directory of Open Access Journals (Sweden)

Rosalía LAZA

2013-05-01

Full Text Available Intelligent Tutoring Systems (ITSs are educational systems that use artificial intelligence techniques for representing the knowledge. ITSs design is often criticized for being a complex and challenging process. In this article, we propose a framework for the ITSs design using Case Based Reasoning (CBR and Multiagent systems (MAS. The major advantage of using CBR is to allow the intelligent system to propose smart and quick solutions to problems, even in complex domains, avoiding the time necessary to derive those solutions from scratch. The use of intelligent agents and MAS architectures supports the retrieval of similar students models and the adaptation of teaching strategies according to the student profile. We describe deeply how the combination of both technologies helps to simplify the design of new ITSs and personalize the e-learning process for each student

The clustering-based case-based reasoning for imbalanced business failure prediction: a hybrid approach through integrating unsupervised process with supervised process

Science.gov (United States)

Li, Hui; Yu, Jun-Ling; Yu, Le-An; Sun, Jie

2014-05-01

Case-based reasoning (CBR) is one of the main forecasting methods in business forecasting, which performs well in prediction and holds the ability of giving explanations for the results. In business failure prediction (BFP), the number of failed enterprises is relatively small, compared with the number of non-failed ones. However, the loss is huge when an enterprise fails. Therefore, it is necessary to develop methods (trained on imbalanced samples) which forecast well for this small proportion of failed enterprises and performs accurately on total accuracy meanwhile. Commonly used methods constructed on the assumption of balanced samples do not perform well in predicting minority samples on imbalanced samples consisting of the minority/failed enterprises and the majority/non-failed ones. This article develops a new method called clustering-based CBR (CBCBR), which integrates clustering analysis, an unsupervised process, with CBR, a supervised process, to enhance the efficiency of retrieving information from both minority and majority in CBR. In CBCBR, various case classes are firstly generated through hierarchical clustering inside stored experienced cases, and class centres are calculated out by integrating cases information in the same clustered class. When predicting the label of a target case, its nearest clustered case class is firstly retrieved by ranking similarities between the target case and each clustered case class centre. Then, nearest neighbours of the target case in the determined clustered case class are retrieved. Finally, labels of the nearest experienced cases are used in prediction. In the empirical experiment with two imbalanced samples from China, the performance of CBCBR was compared with the classical CBR, a support vector machine, a logistic regression and a multi-variant discriminate analysis. The results show that compared with the other four methods, CBCBR performed significantly better in terms of sensitivity for identifying the

Promoting student case creation to enhance instruction of clinical reasoning skills: a pilot feasibility study

Directory of Open Access Journals (Sweden)

Chandrasekar H

2018-04-01

Full Text Available Hamsika Chandrasekar,1 Neil Gesundheit,2 Andrew B Nevins,3 Peter Pompei,4 Janine Bruce,5 Sylvia Bereknyei Merrell6 1Department of Pediatrics, Boston Children’s Hospital, Boston, MA, USA; 2Department of Medicine, Division of Endocrinology, Stanford University School of Medicine, Stanford, CA, USA; 3Department of Medicine, Division of Infectious Diseases, Stanford University School of Medicine, Stanford, CA, USA; 4Department of Medicine, Division of Primary Care and Population Health, Stanford University School of Medicine, Stanford, CA, USA; 5Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA; 6Department of Surgery, Stanford University School of Medicine, Stanford, CA, USA Background: It is a common educational practice for medical students to engage in case-based learning (CBL exercises by working through clinical cases that have been developed by faculty. While such faculty-developed exercises have educational strengths, there are at least two major drawbacks to learning by this method: the number and diversity of cases is often limited; and students decrease their engagement with CBL cases as they grow accustomed to the teaching method. We sought to explore whether student case creation can address both of these limitations. We also compared student case creation to traditional clinical reasoning sessions in regard to tutorial group effectiveness, perceived gains in clinical reasoning, and quality of student–faculty interaction. Methods: Ten first-year medical students participated in a feasibility study wherein they worked in small groups to develop their own patient case around a preassigned diagnosis. Faculty provided feedback on case quality afterwards. Students completed pre- and post-self-assessment surveys. Students and faculty also participated in separate focus groups to compare their case creation experience to traditional CBL sessions. Results: Students reported high levels of team engagement

Dynamic reasoning in a knowledge-based system

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Rao, Anand S.; Foo, Norman Y.

1988-01-01

Any space based system, whether it is a robot arm assembling parts in space or an onboard system monitoring the space station, has to react to changes which cannot be foreseen. As a result, apart from having domain-specific knowledge as in current expert systems, a space based AI system should also have general principles of change. This paper presents a modal logic which can not only represent change but also reason with it. Three primitive operations, expansion, contraction and revision are introduced and axioms which specify how the knowledge base should change when the external world changes are also specified. Accordingly the notion of dynamic reasoning is introduced, which unlike the existing forms of reasoning, provide general principles of change. Dynamic reasoning is based on two main principles, namely minimize change and maximize coherence. A possible-world semantics which incorporates the above two principles is also discussed. The paper concludes by discussing how the dynamic reasoning system can be used to specify actions and hence form an integral part of an autonomous reasoning and planning system.

A robot sets a table: a case for hybrid reasoning with different types of knowledge

Science.gov (United States)

Mansouri, Masoumeh; Pecora, Federico

2016-09-01

An important contribution of AI to Robotics is the model-centred approach, whereby competent robot behaviour stems from automated reasoning in models of the world which can be changed to suit different environments, physical capabilities and tasks. However models need to capture diverse (and often application-dependent) aspects of the robot's environment and capabilities. They must also have good computational properties, as robots need to reason while they act in response to perceived context. In this article, we investigate the use of a meta-CSP-based technique to interleave reasoning in diverse knowledge types. We reify the approach through a robotic waiter case study, for which a particular selection of spatial, temporal, resource and action KR formalisms is made. Using this case study, we discuss general principles pertaining to the selection of appropriate KR formalisms and jointly reasoning about them. The resulting integration is evaluated both formally and experimentally on real and simulated robotic platforms.

Properties of inductive reasoning.

Science.gov (United States)

Heit, E

2000-12-01

This paper reviews the main psychological phenomena of inductive reasoning, covering 25 years of experimental and model-based research, in particular addressing four questions. First, what makes a case or event generalizable to other cases? Second, what makes a set of cases generalizable? Third, what makes a property or predicate projectable? Fourth, how do psychological models of induction address these results? The key results in inductive reasoning are outlined, and several recent models, including a new Bayesian account, are evaluated with respect to these results. In addition, future directions for experimental and model-based work are proposed.

Investigating Students' Reasoning about Acid-Base Reactions

Science.gov (United States)

Cooper, Melanie M.; Kouyoumdjian, Hovig; Underwood, Sonia M.

2016-01-01

Acid-base chemistry is central to a wide range of reactions. If students are able to understand how and why acid-base reactions occur, it should provide a basis for reasoning about a host of other reactions. Here, we report the development of a method to characterize student reasoning about acid-base reactions based on their description of…

Catching the Drift : Using Feature-Free Case-Based Reasoning for Spam Filtering.

OpenAIRE

Delany, Sarah Jane; Bridge, Derek

2007-01-01

n this paper, we compare case-based spam filters, focusing on their resilience to concept drift. In particular, we evaluate how to track concept drift using a case-based spam filter that uses a feature-free distance measure based on text compression. In our experiments, we compare two ways to normalise such a distance measure, finding that the one proposed in [1] performs better. We show that a policy as simple as retaining misclassified examples has a hugely beneficial effect on handling con...

Evidence in clinical reasoning: a computational linguistics analysis of 789,712 medical case summaries 1983-2012.

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Seidel, Bastian M; Campbell, Steven; Bell, Erica

2015-03-21

Better understanding of clinical reasoning could reduce diagnostic error linked to 8% of adverse medical events and 30% of malpractice cases. To a greater extent than the evidence-based movement, the clinical reasoning literature asserts the importance of practitioner intuition—unconscious elements of diagnostic reasoning. The study aimed to analyse the content of case report summaries in ways that explored the importance of an evidence concept, not only in relation to research literature but also intuition. The study sample comprised all 789,712 abstracts in English for case reports contained in the database PUBMED for the period 1 January 1983 to 31 December 2012. It was hypothesised that, if evidence and intuition concepts were viewed by these clinical authors as essential to understanding their case reports, they would be more likely to be found in the abstracts. Computational linguistics software was used in 1) concept mapping of 21,631,481 instances of 201 concepts, and 2) specific concept analyses examining 200 paired co-occurrences for 'evidence' and research 'literature' concepts. 'Evidence' is a fundamentally patient-centred, intuitive concept linked to less common concepts about underlying processes, suspected disease mechanisms and diagnostic hunches. In contrast, the use of research literature in clinical reasoning is linked to more common reasoning concepts about specific knowledge and descriptions or presenting features of cases. 'Literature' is by far the most dominant concept, increasing in relevance since 2003, with an overall relevance of 13% versus 5% for 'evidence' which has remained static. The fact that the least present types of reasoning concepts relate to diagnostic hunches to do with underlying processes, such as what is suspected, raises questions about whether intuitive practitioner evidence-making, found in a constellation of dynamic, process concepts, has become less important. The study adds support to the existing corpus of

Model-based reasoning technology for the power industry

International Nuclear Information System (INIS)

Touchton, R.A.; Subramanyan, N.S.; Naser, J.A.

1991-01-01

This paper reports on model-based reasoning which refers to an expert system implementation methodology that uses a model of the system which is being reasoned about. Model-based representation and reasoning techniques offer many advantages and are highly suitable for domains where the individual components, their interconnection, and their behavior is well-known. Technology Applications, Inc. (TAI), under contract to the Electric Power Research Institute (EPRI), investigated the use of model-based reasoning in the power industry including the nuclear power industry. During this project, a model-based monitoring and diagnostic tool, called ProSys, was developed. Also, an alarm prioritization system was developed as a demonstration prototype

Improving the learning of clinical reasoning through computer-based cognitive representation.

Science.gov (United States)

Wu, Bian; Wang, Minhong; Johnson, Janice M; Grotzer, Tina A

2014-01-01

Clinical reasoning is usually taught using a problem-solving approach, which is widely adopted in medical education. However, learning through problem solving is difficult as a result of the contextualization and dynamic aspects of actual problems. Moreover, knowledge acquired from problem-solving practice tends to be inert and fragmented. This study proposed a computer-based cognitive representation approach that externalizes and facilitates the complex processes in learning clinical reasoning. The approach is operationalized in a computer-based cognitive representation tool that involves argument mapping to externalize the problem-solving process and concept mapping to reveal the knowledge constructed from the problems. Twenty-nine Year 3 or higher students from a medical school in east China participated in the study. Participants used the proposed approach implemented in an e-learning system to complete four learning cases in 4 weeks on an individual basis. For each case, students interacted with the problem to capture critical data, generate and justify hypotheses, make a diagnosis, recall relevant knowledge, and update their conceptual understanding of the problem domain. Meanwhile, students used the computer-based cognitive representation tool to articulate and represent the key elements and their interactions in the learning process. A significant improvement was found in students' learning products from the beginning to the end of the study, consistent with students' report of close-to-moderate progress in developing problem-solving and knowledge-construction abilities. No significant differences were found between the pretest and posttest scores with the 4-week period. The cognitive representation approach was found to provide more formative assessment. The computer-based cognitive representation approach improved the learning of clinical reasoning in both problem solving and knowledge construction.

A Framework for a Clinical Reasoning Knowledge Warehouse

DEFF Research Database (Denmark)

Vilstrup Pedersen, Klaus; Boye, Niels

2004-01-01

is stored and made accessible when relevant to the reasoning context and the specific patient case. Furthermore, the information structure supports the creation of new generalized knowledge using data mining tools. The patient case is divided into an observation level and an opinion level. At the opinion......, Knowledge Management Systems and Business Intelligence to make context based, patient case specific analysis and knowledge management. The knowledge base integrates three sources of information that supports clinical reasoning: general information, guidelines and health records. New generalized knowledge...... level, reasoning participants can express their argument based opinions about a patient case, thereby enhancing the knowledge about the state of and plans for the patient. An opinion language that supports expressing a possible imprecise/uncertain opinion based on imprecise...

A knowledge-based system for prototypical reasoning

Science.gov (United States)

Lieto, Antonio; Minieri, Andrea; Piana, Alberto; Radicioni, Daniele P.

2015-04-01

In this work we present a knowledge-based system equipped with a hybrid, cognitively inspired architecture for the representation of conceptual information. The proposed system aims at extending the classical representational and reasoning capabilities of the ontology-based frameworks towards the realm of the prototype theory. It is based on a hybrid knowledge base, composed of a classical symbolic component (grounded on a formal ontology) with a typicality based one (grounded on the conceptual spaces framework). The resulting system attempts to reconcile the heterogeneous approach to the concepts in Cognitive Science with the dual process theories of reasoning and rationality. The system has been experimentally assessed in a conceptual categorisation task where common sense linguistic descriptions were given in input, and the corresponding target concepts had to be identified. The results show that the proposed solution substantially extends the representational and reasoning 'conceptual' capabilities of standard ontology-based systems.

Delusional Ideation, Cognitive Processes and Crime Based Reasoning.

Science.gov (United States)

Wilkinson, Dean J; Caulfield, Laura S

2017-08-01

Probabilistic reasoning biases have been widely associated with levels of delusional belief ideation (Galbraith, Manktelow, & Morris, 2010; Lincoln, Ziegler, Mehl, & Rief, 2010; Speechley, Whitman, & Woodward, 2010; White & Mansell, 2009), however, little research has focused on biases occurring during every day reasoning (Galbraith, Manktelow, & Morris, 2011), and moral and crime based reasoning (Wilkinson, Caulfield, & Jones, 2014; Wilkinson, Jones, & Caulfield, 2011). 235 participants were recruited across four experiments exploring crime based reasoning through different modalities and dual processing tasks. Study one explored delusional ideation when completing a visually presented crime based reasoning task. Study two explored the same task in an auditory presentation. Study three utilised a dual task paradigm to explore modality and executive functioning. Study four extended this paradigm to the auditory modality. The results indicated that modality and delusional ideation have a significant effect on individuals reasoning about violent and non-violent crime (p < .05), which could have implication for the presentation of evidence in applied setting such as the courtroom.

Case-Based Analogical Reasoning: A Pedagogical Tool for Promotion of Clinical Reasoning

Science.gov (United States)

Speicher, Timothy E.; Bell, Alexandra; Kehrhahn, Marijke; Casa, Douglas J.

2012-01-01

Context: One of the most common instructional methods utilized to promote learning transfer in health profession education is examination of a single patient case. However, in non-healthcare settings this practice has shown to be less effective in promoting learning than the examination of multiple cases with cueing. Objective(s): The primary…

Estimation of the monthly average daily solar radiation using geographic information system and advanced case-based reasoning.

Science.gov (United States)

Koo, Choongwan; Hong, Taehoon; Lee, Minhyun; Park, Hyo Seon

2013-05-07

The photovoltaic (PV) system is considered an unlimited source of clean energy, whose amount of electricity generation changes according to the monthly average daily solar radiation (MADSR). It is revealed that the MADSR distribution in South Korea has very diverse patterns due to the country's climatic and geographical characteristics. This study aimed to develop a MADSR estimation model for the location without the measured MADSR data, using an advanced case based reasoning (CBR) model, which is a hybrid methodology combining CBR with artificial neural network, multiregression analysis, and genetic algorithm. The average prediction accuracy of the advanced CBR model was very high at 95.69%, and the standard deviation of the prediction accuracy was 3.67%, showing a significant improvement in prediction accuracy and consistency. A case study was conducted to verify the proposed model. The proposed model could be useful for owner or construction manager in charge of determining whether or not to introduce the PV system and where to install it. Also, it would benefit contractors in a competitive bidding process to accurately estimate the electricity generation of the PV system in advance and to conduct an economic and environmental feasibility study from the life cycle perspective.

Case Based Asset Maintenance for the Electric Equipment

International Nuclear Information System (INIS)

Kim, Ji-Hyeon; Jung, Jae-Cheon; Chang, Young-Woo; Chang, Hoon-Seon; Kim, Jae-Cheol; Kim, Hang-Bae; Kim, Kyu-Ho; Hur, Yong; Lee, Dong-Chul

2006-01-01

The electric equipment maintenance strategies are changing from PM(Preventive Maintenance) or CM(Corrective Maintenance) to CBM(Condition Based Maintenance). The main benefits of CBM are reduced possibility of service failures of critical equipment and reduced costs or maintenance work. In CBM, the equipment status need to be monitored continuously and a decision should be made whether an equipment need to be repaired or replaced. For the maintenance decision making, the CBR(Case Base Reasoning) system is introduced. The CBR system receives the current equipment status and retrieves the case based historic database to determine any possible equipment failure under current conditions. In retrieving the case based historic data, the suggested DSS(Decision Support System) uses a reasoning engine with an equipment/asset ontology that describes the equipment subsumption relationships

Improving the learning of clinical reasoning through computer-based cognitive representation

Directory of Open Access Journals (Sweden)

Bian Wu

2014-12-01

Full Text Available Objective: Clinical reasoning is usually taught using a problem-solving approach, which is widely adopted in medical education. However, learning through problem solving is difficult as a result of the contextualization and dynamic aspects of actual problems. Moreover, knowledge acquired from problem-solving practice tends to be inert and fragmented. This study proposed a computer-based cognitive representation approach that externalizes and facilitates the complex processes in learning clinical reasoning. The approach is operationalized in a computer-based cognitive representation tool that involves argument mapping to externalize the problem-solving process and concept mapping to reveal the knowledge constructed from the problems. Methods: Twenty-nine Year 3 or higher students from a medical school in east China participated in the study. Participants used the proposed approach implemented in an e-learning system to complete four learning cases in 4 weeks on an individual basis. For each case, students interacted with the problem to capture critical data, generate and justify hypotheses, make a diagnosis, recall relevant knowledge, and update their conceptual understanding of the problem domain. Meanwhile, students used the computer-based cognitive representation tool to articulate and represent the key elements and their interactions in the learning process. Results: A significant improvement was found in students’ learning products from the beginning to the end of the study, consistent with students’ report of close-to-moderate progress in developing problem-solving and knowledge-construction abilities. No significant differences were found between the pretest and posttest scores with the 4-week period. The cognitive representation approach was found to provide more formative assessment. Conclusions: The computer-based cognitive representation approach improved the learning of clinical reasoning in both problem solving and knowledge

MANAGEMENT OF AN ATYPICAL ANKLE SPRAIN PATIENT THROUGH HYPOTHETICO DEDUCTIVE REASONING MODEL OF CLINICAL REASONING IMPLEMENTED BY INTERNATIONAL CLASSIFICATION OF FUNCTIONING DISABILITY AND HEALTH A CASE STUDY

Directory of Open Access Journals (Sweden)

Mohammad Habibur Rahman

2016-09-01

Full Text Available Background: Clinical reasoning is a process by which physiotherapists interacted with patients, their family and other health- care professionals. It is the thinking process that professionals tend to apply in clinical practice. Given that novice as well as expert practitioners prefer to go through some steps while they were dealing with unfamiliar cases. This process is known as hypothetico deductive reasoning. This reasoning approach involved the generation of hypothesis based on clinical data and knowledge and testing of hypothesis through further inquiry. We are expert in musculoskeletal physiotherapy treatment and favoring the atypical history of patient we went through step by step from assessment to discharge Methods: A case based study through hypothetico deductive reasoning model of clinical reasoning. The objective of the study was to investigate the physiotherapy management strategies of an atypical ankle sprain patient through hypothetico deductive reasoning which comprised of cue acquisition, hypothesis generation, cue interpretation and hypothesis evaluation by implementing International Classification of Functioning, Disability and Health (ICF. Results: The patient responded well to treatment as patient reported that 100% swelling decreased, could bear more weight (95% on foot, decrease pain (1 cm on 10 cm VAS scale, improved muscle strength by manual muscle testing by grade V in ankle planter flexors (PF as well as dorsiflexors (DF, invertors as well as evertors and the functional status of patient was improved by 80% according to lower extremity functional scale. Conclusion: Clinical reasoning is an important approach in physiotherapy. It helps the practitioners in decision making and choosing the best alternative options for the well being of patients. We think it is necessary for all practitioners to have sound propositional and non-propositional knowledge in order to provide effective management protocol for patients focusing

A case study on the investigation of reasoning skills in geometry ...

African Journals Online (AJOL)

The aim of this study is to evaluate the reasoning skills in geometry-related subjects of six 8th Grade students. The study data were obtained at the end of the 2011-2012 spring period in a public elementary school. The study uses a case study with qualitative research techniques to investigate how students use reasoning ...

Hybrid Genetic Algorithm Optimization for Case Based Reasoning Systems

International Nuclear Information System (INIS)

Mohamed, A.H.

2008-01-01

The success of a CBR system largely depen ds on an effective retrieval of useful prior case for the problem. Nearest neighbor and induction are the main CBR retrieval algorithms. Each of them can be more suitable in different situations. Integrated the two retrieval algorithms can catch the advantages of both of them. But, they still have some limitations facing the induction retrieval algorithm when dealing with a noisy data, a large number of irrelevant features, and different types of data. This research utilizes a hybrid approach using genetic algorithms (GAs) to case-based induction retrieval of the integrated nearest neighbor - induction algorithm in an attempt to overcome these limitations and increase the overall classification accuracy. GAs can be used to optimize the search space of all the possible subsets of the features set. It can deal with the irrelevant and noisy features while still achieving a significant improvement of the retrieval accuracy. Therefore, the proposed CBR-GA introduces an effective general purpose retrieval algorithm that can improve the performance of CBR systems. It can be applied in many application areas. CBR-GA has proven its success when applied for different problems in real-life

Case-Base Maintenance for CCBR-Based Process Evolution

NARCIS (Netherlands)

Weber, B.; Reichert, M.U.; Wild, W.; Roth-Berghofer, T.; Göker, M.H.; Güvenir, H.A.

2006-01-01

The success of a company more and more depends on its ability to flexibly and quickly react to changes. Combining process management techniques and conversational case-based reasoning (CCBR) allows for flexibly aligning the business processes to new requirements by providing integrated process life

Cultural Diversity and Reasonable Accommodation. An Approach based on Freedom as Non-domination

Directory of Open Access Journals (Sweden)

Isabel Wences

2015-12-01

Full Text Available One of the challenges that culturally diverse societies now face is that of learning to live with differences. Harmonization practices such as concerted adjustment and reasonable accommodation are some of the mechanisms proposed by cultural diversity management policies to deal with this contemporary situation. In the case of reasonable accommodation, this practice can be justified not only because it is based on a recognition of equality in difference, but also on a belief in freedom as a form of non domination, given the inequality present in power relations.

Longitudinal Assessment of Progress in Reasoning Capacity and Relation with Self-Estimation of Knowledge Base

Science.gov (United States)

Collard, Anne; Mélot, France; Bourguignon, Jean-Pierre

2015-01-01

The aim of the study was to investigate progress in reasoning capacity and knowledge base appraisal in a longitudinal analysis of data from summative evaluation throughout a medical problem-based learning curriculum. The scores in multidisciplinary discussion of a clinical case and multiple choice questionnaires (MCQs) were studied longitudinally…

Examining Preservice Teachers' Classroom Management Decisions in Three Case-Based Teaching Approaches

Science.gov (United States)

Cevik, Yasemin Demiraslan; Andre, Thomas

2013-01-01

This study was aimed at comparing the impact of three types of case-based approaches (worked example, faded work example, and case-based reasoning) on preservice teachers' decision making and reasoning skills related to realistic classroom management situations. Participants in this study received a short-term implementation of one of these three…

Conceptualizing Rolling Motion through an Extreme Case Reasoning Approach

Science.gov (United States)

Hasovic, Elvedin; Mešic, Vanes; Erceg, Nataša

2017-01-01

In this paper we are going to show how learning about some counterintuitive aspects of rolling motion can be facilitated by combining the use of analogies with extreme case reasoning. Specifically, the intuitively comprehensible examples of "rolling" polygonal prisms are used as an analogical anchor that is supposed to help the students…

Research on SDG-Based Qualitative Reasoning in Conceptual Design

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Kai Li

2013-01-01

Full Text Available Conceptual design is the initial stage throughout the product life cycle, whose main purposes include function creation, function decomposition, and function and subfunction designs. At this stage, the information about product function and structure has the characteristics of imprecision, incompleteness, being qualitative, and so forth, which will affect the validity of conceptual design. In this paper, the signed directed graph is used to reveal the inherent causal relationship and interactions among the variables and find qualitative interactions between design variables and design purpose with the help of causal sequence analysis and constraint propagation. In the case of incomplete information, qualitative reasoning, which has the function of qualitative behavior prediction, can improve conceptual design level aided by the computer. To some extent, qualitative reasoning plays a supplementary role in evaluating scheme and predicting function. At last, with the problem of planar four-bar mechanism design, a qualitative reasoning flowchart based on the Signed Directed Graph is introduced, and an analysis is made of how to adjust design parameters to make the trajectory of a moving point reach to the predetermined position so as to meet the design requirements and achieve the effect that aided designers expect in conceptual design.

It's not all about moral reasoning: Understanding the content of Moral Case Deliberation.

Science.gov (United States)

Svantesson, Mia; Silén, Marit; James, Inger

2018-03-01

Moral Case Deliberation is one form of clinical ethics support described as a facilitator-led collective moral reasoning by healthcare professionals on a concrete moral question connected to their practice. Evaluation research is needed, but, as human interaction is difficult to standardise, there is a need to capture the content beyond moral reasoning. This allows for a better understanding of Moral Case Deliberation, which may contribute to further development of valid outcome criteria and stimulate the normative discussion of what Moral Case Deliberation should contain. To explore and compare the content beyond moral reasoning in the dialogue in Moral Case Deliberation at Swedish workplaces. A mixed-methods approach was applied for analysing audio-recordings of 70 periodic Moral Case Deliberation meetings at 10 Swedish workplaces. Moral Case Deliberation facilitators and various healthcare professions participated, with registered nurses comprising the majority. Ethical considerations: No objection to the study was made by an Ethical Review Board. After oral and written information was provided, consent to be recorded was assumed by virtue of participation. Other than 'moral reasoning' (median (md): 45% of the spoken time), the Moral Case Deliberations consisted of 'reflections on the psychosocial work environment' to a varying extent (md: 29%). Additional content comprised 'assumptions about the patient's psychosocial situation' (md: 6%), 'facts about the patient's situation' (md: 5%), 'concrete problem-solving' (md: 6%) and 'process' (md: 3%). The findings suggest that a restorative function of staff's wellbeing in Moral Case Deliberation is needed, as this might contribute to good patient care. This supports outcome criteria of improved emotional support, which may include relief of moral distress. However, facilitators need a strategy for how to proceed from the participants' own emotional needs and to develop the use of their emotional knowing to focus on

Semantic reasoning with XML-based biomedical information models.

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O'Connor, Martin J; Das, Amar

2010-01-01

The Extensible Markup Language (XML) is increasingly being used for biomedical data exchange. The parallel growth in the use of ontologies in biomedicine presents opportunities for combining the two technologies to leverage the semantic reasoning services provided by ontology-based tools. There are currently no standardized approaches for taking XML-encoded biomedical information models and representing and reasoning with them using ontologies. To address this shortcoming, we have developed a workflow and a suite of tools for transforming XML-based information models into domain ontologies encoded using OWL. In this study, we applied semantics reasoning methods to these ontologies to automatically generate domain-level inferences. We successfully used these methods to develop semantic reasoning methods for information models in the HIV and radiological image domains.

Reasoning over taxonomic change: exploring alignments for the Perelleschus use case.

Science.gov (United States)

Franz, Nico M; Chen, Mingmin; Yu, Shizhuo; Kianmajd, Parisa; Bowers, Shawn; Ludäscher, Bertram

2015-01-01

Classifications and phylogenetic inferences of organismal groups change in light of new insights. Over time these changes can result in an imperfect tracking of taxonomic perspectives through the re-/use of Code-compliant or informal names. To mitigate these limitations, we introduce a novel approach for aligning taxonomies through the interaction of human experts and logic reasoners. We explore the performance of this approach with the Perelleschus use case of Franz & Cardona-Duque (2013). The use case includes six taxonomies published from 1936 to 2013, 54 taxonomic concepts (i.e., circumscriptions of names individuated according to their respective source publications), and 75 expert-asserted Region Connection Calculus articulations (e.g., congruence, proper inclusion, overlap, or exclusion). An Open Source reasoning toolkit is used to analyze 13 paired Perelleschus taxonomy alignments under heterogeneous constraints and interpretations. The reasoning workflow optimizes the logical consistency and expressiveness of the input and infers the set of maximally informative relations among the entailed taxonomic concepts. The latter are then used to produce merge visualizations that represent all congruent and non-congruent taxonomic elements among the aligned input trees. In this small use case with 6-53 input concepts per alignment, the information gained through the reasoning process is on average one order of magnitude greater than in the input. The approach offers scalable solutions for tracking provenance among succeeding taxonomic perspectives that may have differential biases in naming conventions, phylogenetic resolution, ingroup and outgroup sampling, or ostensive (member-referencing) versus intensional (property-referencing) concepts and articulations.

Problem Representation, Background Evidence, Analysis, Recommendation: An Oral Case Presentation Tool to Promote Diagnostic Reasoning.

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Carter, Cristina; Akar-Ghibril, Nicole; Sestokas, Jeff; Dixon, Gabrina; Bradford, Wilhelmina; Ottolini, Mary

2018-03-01

Oral case presentations provide an opportunity for trainees to communicate diagnostic reasoning at the bedside. However, few tools exist to enable faculty to provide effective feedback. We developed a tool to assess diagnostic reasoning and communication during oral case presentations. Published by Elsevier Inc.

How clear is transparent? Reporting expert reasoning in legal cases

NARCIS (Netherlands)

Sjerps, M.J.; Berger, C.E.H.

2012-01-01

Experts providing evidence in legal cases are universally recommended to be transparent, particularly in their reasoning, so that legal practitioners can critically check whether the conclusions are adequately supported by the results. However, when exploring the practical meaning of this

A fuzzy ontology modeling for case base knowledge in diabetes mellitus domain

Directory of Open Access Journals (Sweden)

Shaker El-Sappagh

2017-06-01

Full Text Available Knowledge-Intensive Case-Based Reasoning Systems (KI-CBR mainly depend on ontologies. Ontology can play the role of case-base knowledge. The combination of ontology and fuzzy logic reasoning is critical in the medical domain. Case-base representation based on fuzzy ontology is expected to enhance the semantic and storage of CBR knowledge-base. This paper provides an advancement to the research of diabetes diagnosis CBR by proposing a novel case-base fuzzy OWL2 ontology (CBRDiabOnto. This ontology can be considered as the first fuzzy case-base ontology in the medical domain. It is based on a case-base fuzzy Extended Entity Relation (EER data model. It contains 63 (fuzzy classes, 54 (fuzzy object properties, 138 (fuzzy datatype properties, and 105 fuzzy datatypes. We populated the ontology with 60 cases and used SPARQL-DL for its query. The evaluation of CBRDiabOnto shows that it is accurate, consistent, and cover terminologies and logic of diabetes mellitus diagnosis.

Model-Based Reasoning in Humans Becomes Automatic with Training.

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Marcos Economides

2015-09-01

Full Text Available Model-based and model-free reinforcement learning (RL have been suggested as algorithmic realizations of goal-directed and habitual action strategies. Model-based RL is more flexible than model-free but requires sophisticated calculations using a learnt model of the world. This has led model-based RL to be identified with slow, deliberative processing, and model-free RL with fast, automatic processing. In support of this distinction, it has recently been shown that model-based reasoning is impaired by placing subjects under cognitive load--a hallmark of non-automaticity. Here, using the same task, we show that cognitive load does not impair model-based reasoning if subjects receive prior training on the task. This finding is replicated across two studies and a variety of analysis methods. Thus, task familiarity permits use of model-based reasoning in parallel with other cognitive demands. The ability to deploy model-based reasoning in an automatic, parallelizable fashion has widespread theoretical implications, particularly for the learning and execution of complex behaviors. It also suggests a range of important failure modes in psychiatric disorders.

An ontological case base engineering methodology for diabetes management.

Science.gov (United States)

El-Sappagh, Shaker H; El-Masri, Samir; Elmogy, Mohammed; Riad, A M; Saddik, Basema

2014-08-01

Ontology engineering covers issues related to ontology development and use. In Case Based Reasoning (CBR) system, ontology plays two main roles; the first as case base and the second as domain ontology. However, the ontology engineering literature does not provide adequate guidance on how to build, evaluate, and maintain ontologies. This paper proposes an ontology engineering methodology to generate case bases in the medical domain. It mainly focuses on the research of case representation in the form of ontology to support the case semantic retrieval and enhance all knowledge intensive CBR processes. A case study on diabetes diagnosis case base will be provided to evaluate the proposed methodology.

Model-Based Reasoning

Science.gov (United States)

Ifenthaler, Dirk; Seel, Norbert M.

2013-01-01

In this paper, there will be a particular focus on mental models and their application to inductive reasoning within the realm of instruction. A basic assumption of this study is the observation that the construction of mental models and related reasoning is a slowly developing capability of cognitive systems that emerges effectively with proper…

Emotional Reasoning and Parent-Based Reasoning in Non-Clinical Children, and Their Prospective Relationships with Anxiety Symptoms

Science.gov (United States)

Morren, Mattijn; Muris, Peter; Kindt, Merel; Schouten, Erik; van den Hout, Marcel

2008-01-01

Emotional and parent-based reasoning refer to the tendency to rely on personal or parental anxiety response information rather than on objective danger information when estimating the dangerousness of a situation. This study investigated the prospective relationships of emotional and parent-based reasoning with anxiety symptoms in a sample of…

The Milling Assistant, Case-Based Reasoning, and machining strategy: A report on the development of automated numerical control programming systems at New Mexico State University

Energy Technology Data Exchange (ETDEWEB)

Burd, W. [Sandia National Labs., Albuquerque, NM (United States); Culler, D.; Eskridge, T.; Cox, L.; Slater, T. [New Mexico State Univ., Las Cruces, NM (United States)

1993-08-01

The Milling Assistant (MA) programming system demonstrates the automated development of tool paths for Numerical Control (NC) machine tools. By integrating a Case-Based Reasoning decision processor with a commercial CAD/CAM software, intelligent tool path files for milled and point-to-point features can be created. The operational system is capable of reducing the time required to program a variety of parts and improving product quality by collecting and utilizing ``best of practice`` machining strategies.

Machine Learning-based Intelligent Formal Reasoning and Proving System

Science.gov (United States)

Chen, Shengqing; Huang, Xiaojian; Fang, Jiaze; Liang, Jia

2018-03-01

The reasoning system can be used in many fields. How to improve reasoning efficiency is the core of the design of system. Through the formal description of formal proof and the regular matching algorithm, after introducing the machine learning algorithm, the system of intelligent formal reasoning and verification has high efficiency. The experimental results show that the system can verify the correctness of propositional logic reasoning and reuse the propositional logical reasoning results, so as to obtain the implicit knowledge in the knowledge base and provide the basic reasoning model for the construction of intelligent system.

Agent Based Reasoning in Multilevel Flow Modeling

DEFF Research Database (Denmark)

Lind, Morten; Zhang, Xinxin

2012-01-01

to launch the MFM Workbench into an agent based environment, which can complement disadvantages of the original software. The agent-based MFM Workbench is centered on a concept called “Blackboard System” and use an event based mechanism to arrange the reasoning tasks. This design will support the new...

Explicit Knowledge-based Reasoning for Visual Question Answering

OpenAIRE

Wang, Peng; Wu, Qi; Shen, Chunhua; Hengel, Anton van den; Dick, Anthony

2015-01-01

We describe a method for visual question answering which is capable of reasoning about contents of an image on the basis of information extracted from a large-scale knowledge base. The method not only answers natural language questions using concepts not contained in the image, but can provide an explanation of the reasoning by which it developed its answer. The method is capable of answering far more complex questions than the predominant long short-term memory-based approach, and outperform...

Effects of Inquiry-Based Agriscience Instruction on Student Scientific Reasoning

Science.gov (United States)

Thoron, Andrew C.; Myers, Brian E.

2012-01-01

The purpose of this study was to determine the effect of inquiry-based agriscience instruction on student scientific reasoning. Scientific reasoning is defined as the use of the scientific method, inductive, and deductive reasoning to develop and test hypothesis. Developing scientific reasoning skills can provide learners with a connection to the…

Visual Reasoning in Computational Environment: A Case of Graph Sketching

Science.gov (United States)

Leung, Allen; Chan, King Wah

2004-01-01

This paper reports the case of a form six (grade 12) Hong Kong student's exploration of graph sketching in a computational environment. In particular, the student summarized his discovery in the form of two empirical laws. The student was interviewed and the interviewed data were used to map out a possible path of his visual reasoning. Critical…

MTK: An AI tool for model-based reasoning

Science.gov (United States)

Erickson, William K.; Schwartz, Mary R.

1987-01-01

A 1988 goal for the Systems Autonomy Demonstration Project Office of the NASA Ames Research Center is to apply model-based representation and reasoning techniques in a knowledge-based system that will provide monitoring, fault diagnosis, control and trend analysis of the space station Thermal Management System (TMS). A number of issues raised during the development of the first prototype system inspired the design and construction of a model-based reasoning tool called MTK, which was used in the building of the second prototype. These issues are outlined, along with examples from the thermal system to highlight the motivating factors behind them. An overview of the capabilities of MTK is given.

Energy Optimization Using a Case-Based Reasoning Strategy.

Science.gov (United States)

González-Briones, Alfonso; Prieto, Javier; De La Prieta, Fernando; Herrera-Viedma, Enrique; Corchado, Juan M

2018-03-15

At present, the domotization of homes and public buildings is becoming increasingly popular. Domotization is most commonly applied to the field of energy management, since it gives the possibility of managing the consumption of the devices connected to the electric network, the way in which the users interact with these devices, as well as other external factors that influence consumption. In buildings, Heating, Ventilation and Air Conditioning (HVAC) systems have the highest consumption rates. The systems proposed so far have not succeeded in optimizing the energy consumption associated with a HVAC system because they do not monitor all the variables involved in electricity consumption. For this reason, this article presents an agent approach that benefits from the advantages provided by a Multi-Agent architecture (MAS) deployed in a Cloud environment with a wireless sensor network (WSN) in order to achieve energy savings. The agents of the MAS learn social behavior thanks to the collection of data and the use of an artificial neural network (ANN). The proposed system has been assessed in an office building achieving an average energy savings of 41% in the experimental group offices.

Energy Optimization Using a Case-Based Reasoning Strategy

Science.gov (United States)

Herrera-Viedma, Enrique

2018-01-01

At present, the domotization of homes and public buildings is becoming increasingly popular. Domotization is most commonly applied to the field of energy management, since it gives the possibility of managing the consumption of the devices connected to the electric network, the way in which the users interact with these devices, as well as other external factors that influence consumption. In buildings, Heating, Ventilation and Air Conditioning (HVAC) systems have the highest consumption rates. The systems proposed so far have not succeeded in optimizing the energy consumption associated with a HVAC system because they do not monitor all the variables involved in electricity consumption. For this reason, this article presents an agent approach that benefits from the advantages provided by a Multi-Agent architecture (MAS) deployed in a Cloud environment with a wireless sensor network (WSN) in order to achieve energy savings. The agents of the MAS learn social behavior thanks to the collection of data and the use of an artificial neural network (ANN). The proposed system has been assessed in an office building achieving an average energy savings of 41% in the experimental group offices. PMID:29543729

Energy Optimization Using a Case-Based Reasoning Strategy

Directory of Open Access Journals (Sweden)

Alfonso González-Briones

2018-03-01

Full Text Available At present, the domotization of homes and public buildings is becoming increasingly popular. Domotization is most commonly applied to the field of energy management, since it gives the possibility of managing the consumption of the devices connected to the electric network, the way in which the users interact with these devices, as well as other external factors that influence consumption. In buildings, Heating, Ventilation and Air Conditioning (HVAC systems have the highest consumption rates. The systems proposed so far have not succeeded in optimizing the energy consumption associated with a HVAC system because they do not monitor all the variables involved in electricity consumption. For this reason, this article presents an agent approach that benefits from the advantages provided by a Multi-Agent architecture (MAS deployed in a Cloud environment with a wireless sensor network (WSN in order to achieve energy savings. The agents of the MAS learn social behavior thanks to the collection of data and the use of an artificial neural network (ANN. The proposed system has been assessed in an office building achieving an average energy savings of 41% in the experimental group offices.

Using Computer Simulations for Promoting Model-based Reasoning. Epistemological and Educational Dimensions

Science.gov (United States)

Develaki, Maria

2017-11-01

Scientific reasoning is particularly pertinent to science education since it is closely related to the content and methodologies of science and contributes to scientific literacy. Much of the research in science education investigates the appropriate framework and teaching methods and tools needed to promote students' ability to reason and evaluate in a scientific way. This paper aims (a) to contribute to an extended understanding of the nature and pedagogical importance of model-based reasoning and (b) to exemplify how using computer simulations can support students' model-based reasoning. We provide first a background for both scientific reasoning and computer simulations, based on the relevant philosophical views and the related educational discussion. This background suggests that the model-based framework provides an epistemologically valid and pedagogically appropriate basis for teaching scientific reasoning and for helping students develop sounder reasoning and decision-taking abilities and explains how using computer simulations can foster these abilities. We then provide some examples illustrating the use of computer simulations to support model-based reasoning and evaluation activities in the classroom. The examples reflect the procedure and criteria for evaluating models in science and demonstrate the educational advantages of their application in classroom reasoning activities.

Improving case-based reasoning systems by combining k-nearest neighbour algorithm with logistic regression in the prediction of patients' registration on the renal transplant waiting list.

Directory of Open Access Journals (Sweden)

Boris Campillo-Gimenez

Full Text Available Case-based reasoning (CBR is an emerging decision making paradigm in medical research where new cases are solved relying on previously solved similar cases. Usually, a database of solved cases is provided, and every case is described through a set of attributes (inputs and a label (output. Extracting useful information from this database can help the CBR system providing more reliable results on the yet to be solved cases.We suggest a general framework where a CBR system, viz. K-Nearest Neighbour (K-NN algorithm, is combined with various information obtained from a Logistic Regression (LR model, in order to improve prediction of access to the transplant waiting list.LR is applied, on the case database, to assign weights to the attributes as well as the solved cases. Thus, five possible decision making systems based on K-NN and/or LR were identified: a standalone K-NN, a standalone LR and three soft K-NN algorithms that rely on the weights based on the results of the LR. The evaluation was performed under two conditions, either using predictive factors known to be related to registration, or using a combination of factors related and not related to registration.The results show that our suggested approach, where the K-NN algorithm relies on both weighted attributes and cases, can efficiently deal with non relevant attributes, whereas the four other approaches suffer from this kind of noisy setups. The robustness of this approach suggests interesting perspectives for medical problem solving tools using CBR methodology.

Enhancements to knowledge discovery framework of SOPHIA textual case-based reasoning

Directory of Open Access Journals (Sweden)

Islam Elhalwany

2014-11-01

This paper contributes to propose enhancements to SOPHIA approach that aims to enhance the retrieval efficiency and increase the precision degree. It also aimed to grantee that all results will have the same subject of the user query. The enhancements include performing an automatic classification to the case-base before the clustering step in the indexing stage, and include performing an automatic classification to the user query before the retrieval stage. Moreover, proofing that SOPHIA approach is a domain and language independent by applying it in the domain of Islamic jurisprudence in Arabic language.

Stimulating Scientific Reasoning with Drawing-Based Modeling

Science.gov (United States)

Heijnes, Dewi; van Joolingen, Wouter; Leenaars, Frank

2018-01-01

We investigate the way students' reasoning about evolution can be supported by drawing-based modeling. We modified the drawing-based modeling tool SimSketch to allow for modeling evolutionary processes. In three iterations of development and testing, students in lower secondary education worked on creating an evolutionary model. After each…

A Model-based Avionic Prognostic Reasoner (MAPR)

Data.gov (United States)

National Aeronautics and Space Administration — The Model-based Avionic Prognostic Reasoner (MAPR) presented in this paper is an innovative solution for non-intrusively monitoring the state of health (SoH) and...

Inductive reasoning.

Science.gov (United States)

Hayes, Brett K; Heit, Evan; Swendsen, Haruka

2010-03-01

Inductive reasoning entails using existing knowledge or observations to make predictions about novel cases. We review recent findings in research on category-based induction as well as theoretical models of these results, including similarity-based models, connectionist networks, an account based on relevance theory, Bayesian models, and other mathematical models. A number of touchstone empirical phenomena that involve taxonomic similarity are described. We also examine phenomena involving more complex background knowledge about premises and conclusions of inductive arguments and the properties referenced. Earlier models are shown to give a good account of similarity-based phenomena but not knowledge-based phenomena. Recent models that aim to account for both similarity-based and knowledge-based phenomena are reviewed and evaluated. Among the most important new directions in induction research are a focus on induction with uncertain premise categories, the modeling of the relationship between inductive and deductive reasoning, and examination of the neural substrates of induction. A common theme in both the well-established and emerging lines of induction research is the need to develop well-articulated and empirically testable formal models of induction. Copyright © 2010 John Wiley & Sons, Ltd. For further resources related to this article, please visit the WIREs website. Copyright © 2010 John Wiley & Sons, Ltd.

A public health decision support system model using reasoning methods.

Science.gov (United States)

Mera, Maritza; González, Carolina; Blobel, Bernd

2015-01-01

Public health programs must be based on the real health needs of the population. However, the design of efficient and effective public health programs is subject to availability of information that can allow users to identify, at the right time, the health issues that require special attention. The objective of this paper is to propose a case-based reasoning model for the support of decision-making in public health. The model integrates a decision-making process and case-based reasoning, reusing past experiences for promptly identifying new population health priorities. A prototype implementation of the model was performed, deploying the case-based reasoning framework jColibri. The proposed model contributes to solve problems found today when designing public health programs in Colombia. Current programs are developed under uncertain environments, as the underlying analyses are carried out on the basis of outdated and unreliable data.

Registered nurses' clinical reasoning skills and reasoning process: A think-aloud study.

Science.gov (United States)

Lee, JuHee; Lee, Young Joo; Bae, JuYeon; Seo, Minjeong

2016-11-01

As complex chronic diseases are increasing, nurses' prompt and accurate clinical reasoning skills are essential. However, little is known about the reasoning skills of registered nurses. This study aimed to determine how registered nurses use their clinical reasoning skills and to identify how the reasoning process proceeds in the complex clinical situation of hospital setting. A qualitative exploratory design was used with a think-aloud method. A total of 13 registered nurses (mean years of experience=11.4) participated in the study, solving an ill-structured clinical problem based on complex chronic patients cases in a hospital setting. Data were analyzed using deductive content analysis. Findings showed that the registered nurses used a variety of clinical reasoning skills. The most commonly used skill was 'checking accuracy and reliability.' The reasoning process of registered nurses covered assessment, analysis, diagnosis, planning/implementation, and evaluation phase. It is critical that registered nurses apply appropriate clinical reasoning skills in complex clinical practice. The main focus of registered nurses' reasoning in this study was assessing a patient's health problem, and their reasoning process was cyclic, rather than linear. There is a need for educational strategy development to enhance registered nurses' competency in determining appropriate interventions in a timely and accurate fashion. Copyright © 2016 Elsevier Ltd. All rights reserved.

Data science in R a case studies approach to computational reasoning and problem solving

CERN Document Server

Nolan, Deborah

2015-01-01

Effectively Access, Transform, Manipulate, Visualize, and Reason about Data and ComputationData Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving illustrates the details involved in solving real computational problems encountered in data analysis. It reveals the dynamic and iterative process by which data analysts approach a problem and reason about different ways of implementing solutions. The book's collection of projects, comprehensive sample solutions, and follow-up exercises encompass practical topics pertaining to data processing, including: Non-standar

Children's Gender-Based Reasoning about Toys.

Science.gov (United States)

Martin, Carol Lynn; And Others

1995-01-01

Three studies examined how preschool children used gender-based reasoning in making judgments about toy preferences for themselves and for others. Found that children used gender labels to guide their own preferences and their expectations of others. Even with very attractive toys, children liked the toys less if they were labeled as being for the…

An approach to the verification of a fault-tolerant, computer-based reactor safety system: A case study using automated reasoning: Volume 1: Interim report

International Nuclear Information System (INIS)

Chisholm, G.H.; Kljaich, J.; Smith, B.T.; Wojcik, A.S.

1987-01-01

The purpose of this project is to explore the feasibility of automating the verification process for computer systems. The intent is to demonstrate that both the software and hardware that comprise the system meet specified availability and reliability criteria, that is, total design analysis. The approach to automation is based upon the use of Automated Reasoning Software developed at Argonne National Laboratory. This approach is herein referred to as formal analysis and is based on previous work on the formal verification of digital hardware designs. Formal analysis represents a rigorous evaluation which is appropriate for system acceptance in critical applications, such as a Reactor Safety System (RSS). This report describes a formal analysis technique in the context of a case study, that is, demonstrates the feasibility of applying formal analysis via application. The case study described is based on the Reactor Safety System (RSS) for the Experimental Breeder Reactor-II (EBR-II). This is a system where high reliability and availability are tantamount to safety. The conceptual design for this case study incorporates a Fault-Tolerant Processor (FTP) for the computer environment. An FTP is a computer which has the ability to produce correct results even in the presence of any single fault. This technology was selected as it provides a computer-based equivalent to the traditional analog based RSSs. This provides a more conservative design constraint than that imposed by the IEEE Standard, Criteria For Protection Systems For Nuclear Power Generating Stations (ANSI N42.7-1972)

On Derek Parfit' s Objectivist Theory of Reasons for Action:Desire-based or Value-based?

Institute of Scientific and Technical Information of China (English)

Zhang Jieting

2017-01-01

The issue of the sources of normativity has been a very hot topic in contem-porary Anglo-American ethics. Some scholars believe that the normativity should be interpre-ted as a reason-implying concept and it can be analyzed further as moral reasons. So,to better understand the sources of normativity,we have to explore the sources of the reasons further. Generally,there are two competing views on the sources of reasons:subjectivism and objectiv-ism. Subjectivism argues that the reasons for action are ultimately based on desires or facts a-bout desires. Objectivism argues that the reasons are given by the objects,determined by the value of the relevant facts about desired objects. Parfit proposed an objectivist theory of reasons for action,and he tried to prove that reasons are external,objective,and value-based,through his three arguments,i. e. ,the agony argument,the all or none argument,and the incoherence argument. He finally demonstrated that what can determine reasons for action are facts rather than desires.

Reasoning in explanation-based decision making.

Science.gov (United States)

Pennington, N; Hastie, R

1993-01-01

A general theory of explanation-based decision making is outlined and the multiple roles of inference processes in the theory are indicated. A typology of formal and informal inference forms, originally proposed by Collins (1978a, 1978b), is introduced as an appropriate framework to represent inferences that occur in the overarching explanation-based process. Results from the analysis of verbal reports of decision processes are presented to demonstrate the centrality and systematic character of reasoning in a representative legal decision-making task.

CASE-BASED PRODUCT CONFIGURATION AND REUSE IN MASS CUSTOMIZATION

Institute of Scientific and Technical Information of China (English)

Wang Shiwei; Tan Jianrong; Zhang Shuyou; Wang Xin; He Chenqi

2004-01-01

The increasing complexity and size of configuration knowledge bases requires the provision of advanced methods supporting the development of the actual configuration process and design reuse.A new framework to find a feasible and practical product configuration method is presented in mass customization.The basic idea of the approach is to integrate case-based reasoning (CBR) with a constraint satisfaction problem(CSP).The similarity measure between a crisp and range is also given,which is common in case retrieves.Based on the configuration model,a product platform and customer needs,case adaptation is carried out with the repair-based algorithm.Lastly,the methodology in the elevator configuration design domain is tested.

A Rule-Based Spatial Reasoning Approach for OpenStreetMap Data Quality Enrichment; Case Study of Routing and Navigation

Science.gov (United States)

2017-01-01

Finding relevant geospatial information is increasingly critical because of the growing volume of geospatial data available within the emerging “Big Data” era. Users are expecting that the availability of massive datasets will create more opportunities to uncover hidden information and answer more complex queries. This is especially the case with routing and navigation services where the ability to retrieve points of interest and landmarks make the routing service personalized, precise, and relevant. In this paper, we propose a new geospatial information approach that enables the retrieval of implicit information, i.e., geospatial entities that do not exist explicitly in the available source. We present an information broker that uses a rule-based spatial reasoning algorithm to detect topological relations. The information broker is embedded into a framework where annotations and mappings between OpenStreetMap data attributes and external resources, such as taxonomies, support the enrichment of queries to improve the ability of the system to retrieve information. Our method is tested with two case studies that leads to enriching the completeness of OpenStreetMap data with footway crossing points-of-interests as well as building entrances for routing and navigation purposes. It is concluded that the proposed approach can uncover implicit entities and contribute to extract required information from the existing datasets. PMID:29088125

A Rule-Based Spatial Reasoning Approach for OpenStreetMap Data Quality Enrichment; Case Study of Routing and Navigation

Directory of Open Access Journals (Sweden)

Amin Mobasheri

2017-10-01

Full Text Available Finding relevant geospatial information is increasingly critical because of the growing volume of geospatial data available within the emerging “Big Data” era. Users are expecting that the availability of massive datasets will create more opportunities to uncover hidden information and answer more complex queries. This is especially the case with routing and navigation services where the ability to retrieve points of interest and landmarks make the routing service personalized, precise, and relevant. In this paper, we propose a new geospatial information approach that enables the retrieval of implicit information, i.e., geospatial entities that do not exist explicitly in the available source. We present an information broker that uses a rule-based spatial reasoning algorithm to detect topological relations. The information broker is embedded into a framework where annotations and mappings between OpenStreetMap data attributes and external resources, such as taxonomies, support the enrichment of queries to improve the ability of the system to retrieve information. Our method is tested with two case studies that leads to enriching the completeness of OpenStreetMap data with footway crossing points-of-interests as well as building entrances for routing and navigation purposes. It is concluded that the proposed approach can uncover implicit entities and contribute to extract required information from the existing datasets.

Intelligent Case Based Decision Support System for Online Diagnosis of Automated Production System

International Nuclear Information System (INIS)

Ben Rabah, N; Saddem, R; Carre-Menetrier, V; Ben Hmida, F; Tagina, M

2017-01-01

Diagnosis of Automated Production System (APS) is a decision-making process designed to detect, locate and identify a particular failure caused by the control law. In the literature, there are three major types of reasoning for industrial diagnosis: the first is model-based, the second is rule-based and the third is case-based. The common and major limitation of the first and the second reasonings is that they do not have automated learning ability. This paper presents an interactive and effective Case Based Decision Support System for online Diagnosis (CB-DSSD) of an APS. It offers a synergy between the Case Based Reasoning (CBR) and the Decision Support System (DSS) in order to support and assist Human Operator of Supervision (HOS) in his/her decision process. Indeed, the experimental evaluation performed on an Interactive Training System for PLC (ITS PLC) that allows the control of a Programmable Logic Controller (PLC), simulating sensors or/and actuators failures and validating the control algorithm through a real time interactive experience, showed the efficiency of our approach. (paper)

Improving the Reliability of Case-Based Reasoning Systems

Directory of Open Access Journals (Sweden)

Xu Xu

2010-09-01

also discussed in this paper, especially the property that whether inter-feature of case exists redundancy. After that, the reliability of an individual suggested solution is studied. To illustrate these ideas, some experiments and their results are discussed in this paper. The results of experiments show a new route concerning on how to improve the reliability of a CBR system at an overall level.

Secondary School Students' Understanding of Science and Their Socioscientific Reasoning

Science.gov (United States)

Karahan, Engin; Roehrig, Gillian

2017-08-01

Research in socioscientific issue (SSI)-based interventions is relatively new (Sadler in Journal of Research in Science Teaching 41:513-536, 2004; Zeidler et al. in Journal of Research in Science Teaching 46:74-101, 2009), and there is a need for understanding more about the effects of SSI-based learning environments (Sadler in Journal of Research in Science Teaching 41:513-536, 2004). Lee and Witz (International Journal of Science Education 31:931-960, 2009) highlighted the need for detailed case studies that would focus on how students respond to teachers' practices of teaching SSI. This study presents case studies that investigated the development of secondary school students' science understanding and their socioscientific reasoning within SSI-based learning environments. A multiple case study with embedded units of analysis was implemented for this research because of the contextual differences for each case. The findings of the study revealed that students' understanding of science, including scientific method, social and cultural influences on science, and scientific bias, was strongly influenced by their experiences in SSI-based learning environments. Furthermore, multidimensional SSI-based science classes resulted in students having multiple reasoning modes, such as ethical and economic reasoning, compared to data-driven SSI-based science classes. In addition to portraying how participants presented complexity, perspectives, inquiry, and skepticism as aspects of socioscientific reasoning (Sadler et al. in Research in Science Education 37:371-391, 2007), this study proposes the inclusion of three additional aspects for the socioscientific reasoning theoretical construct: (1) identification of social domains affecting the SSI, (2) using cost and benefit analysis for evaluation of claims, and (3) understanding that SSIs and scientific studies around them are context-bound.

Development of abstract mathematical reasoning: the case of algebra.

Science.gov (United States)

Susac, Ana; Bubic, Andreja; Vrbanc, Andrija; Planinic, Maja

2014-01-01

Algebra typically represents the students' first encounter with abstract mathematical reasoning and it therefore causes significant difficulties for students who still reason concretely. The aim of the present study was to investigate the developmental trajectory of the students' ability to solve simple algebraic equations. 311 participants between the ages of 13 and 17 were given a computerized test of equation rearrangement. Equations consisted of an unknown and two other elements (numbers or letters), and the operations of multiplication/division. The obtained results showed that younger participants are less accurate and slower in solving equations with letters (symbols) than those with numbers. This difference disappeared for older participants (16-17 years), suggesting that they had reached an abstract reasoning level, at least for this simple task. A corresponding conclusion arises from the analysis of their strategies which suggests that younger participants mostly used concrete strategies such as inserting numbers, while older participants typically used more abstract, rule-based strategies. These results indicate that the development of algebraic thinking is a process which unfolds over a long period of time. In agreement with previous research, we can conclude that, on average, children at the age of 15-16 transition from using concrete to abstract strategies while solving the algebra problems addressed within the present study. A better understanding of the timing and speed of students' transition from concrete arithmetic reasoning to abstract algebraic reasoning might help in designing better curricula and teaching materials that would ease that transition.

Applying Case-Based Reasoning in Supporting Strategy Decisions

OpenAIRE

S. M. Seyedhosseini; A. Makui; M. Ghadami

2011-01-01

Globalization and therefore increasing tight competition among companies, have resulted to increase the importance of making well-timed decision. Devising and employing effective strategies, that are flexible and adaptive to changing market, stand a greater chance of being effective in the long-term. In other side, a clear focus on managing the entire product lifecycle has emerged as critical areas for investment. Therefore, applying wellorganized tools to employ past experience in new case, ...

Nurses' ethical reasoning in cases of physical restraint in acute elderly care: a qualitative study.

Science.gov (United States)

Goethals, Sabine; Dierckx de Casterlé, Bernadette; Gastmans, Chris

2013-11-01

In their practice, nurses make daily decisions that are ethically informed. An ethical decision is the result of a complex reasoning process based on knowledge and experience and driven by ethical values. Especially in acute elderly care and more specifically decisions concerning the use of physical restraint require a thoughtful deliberation of the different values at stake. Qualitative evidence concerning nurses' decision-making in cases of physical restraint provided important insights in the complexity of decision-making as a trajectory. However a nuanced and refined understanding of the reasoning process in terms of ethical values is still lacking. A qualitative interview design, inspired by the Grounded Theory approach, was carried out to explore nurses' reasoning process in terms of ethical values. We interviewed 21 acute geriatric nurses from 12 hospitals in different regions in Flanders, Belgium in the period October 2009-April 2011. The Qualitative Analysis Guide of Leuven was used to analyse interview data. Nurses' decision-making is characterized as an ethical deliberation process where different values are identified and where the process of balancing these values forms the essence of ethical deliberation. Ethical decision-making in cases of physical restraint implies that nurses have to choose which values receive priority in the process, which entails that not all values can be respected to the same degree. As a result, decision making can be experienced as difficult, even as a dilemma. Driven by the overwhelming goal of protecting physical integrity, nurses took into account the values of dignity and justice more implicitly and less dominantly.

Use of case-based reasoning to enhance intensive management of patients on insulin pump therapy.

Science.gov (United States)

Schwartz, Frank L; Shubrook, Jay H; Marling, Cynthia R

2008-07-01

This study was conducted to develop case-based decision support software to improve glucose control in patients with type 1 diabetes mellitus (T1DM) on insulin pump therapy. While the benefits of good glucose control are well known, achieving and maintaining good glucose control remains a difficult task. Case-based decision support software may assist by recalling past problems in glucose control and their associated therapeutic adjustments. Twenty patients with T1DM on insulin pumps were enrolled in a 6-week study. Subjects performed self-glucose monitoring and provided daily logs via the Internet, tracking insulin dosages, work, sleep, exercise, meals, stress, illness, menstrual cycles, infusion set changes, pump problems, hypoglycemic episodes, and other events. Subjects wore a continuous glucose monitoring system at weeks 1, 3, and 6. Clinical data were interpreted by physicians, who explained the relationship between life events and observed glucose patterns as well as treatment rationales to knowledge engineers. Knowledge engineers built a prototypical system that contained cases of problems in glucose control together with their associated solutions. Twelve patients completed the study. Fifty cases of clinical problems and solutions were developed and stored in a case base. The prototypical system detected 12 distinct types of clinical problems. It displayed the stored problems that are most similar to the problems detected, and offered learned solutions as decision support to the physician. This software can screen large volumes of clinical data and glucose levels from patients with T1DM, identify clinical problems, and offer solutions. It has potential application in managing all forms of diabetes.

Model-based reasoning and the control of process plants

International Nuclear Information System (INIS)

Vaelisuo, Heikki

1993-02-01

In addition to feedback control, safe and economic operation of industrial process plants requires discrete-event type logic control like for example automatic control sequences, interlocks, etc. A lot of complex routine reasoning is involved in the design and verification and validation (VandV) of such automatics. Similar reasoning tasks are encountered during plant operation in action planning and fault diagnosis. The low-level part of the required problem solving is so straightforward that it could be accomplished by a computer if only there were plant models which allow versatile mechanised reasoning. Such plant models and corresponding inference algorithms are the main subject of this report. Deep knowledge and qualitative modelling play an essential role in this work. Deep knowledge refers to mechanised reasoning based on the first principles of the phenomena in the problem domain. Qualitative modelling refers to knowledge representation formalism and related reasoning methods which allow solving problems on an abstraction level higher than for example traditional simulation and optimisation. Prolog is a commonly used platform for artificial intelligence (Al) applications. Constraint logic languages like CLP(R) and Prolog-III extend the scope of logic programming to numeric problem solving. In addition they allow a programming style which often reduces the computational complexity significantly. An approach to model-based reasoning implemented in constraint logic programming language CLP(R) is presented. The approach is based on some of the principles of QSIM, an algorithm for qualitative simulation. It is discussed how model-based reasoning can be applied in the design and VandV of plant automatics and in action planning during plant operation. A prototype tool called ISIR is discussed and some initial results obtained during the development of the tool are presented. The results presented originate from preliminary test results of the prototype obtained

Case-Based Reasoning in Mixed Paradigm Settings and with Learning

Science.gov (United States)

1994-04-30

Learning Prototypical Cases OFF-BROADWAY, MCI and RMHC -* are three CBR-ML systems that learn case prototypes. We feel that methods that enable the...at Irvine Machine Learning Repository, including heart disease and breast cancer databases. OFF-BROADWAY, MCI and RMHC -* made the following notable

Fuzzy Reasoning Based on First-Order Modal Logic,

NARCIS (Netherlands)

Zhang, Xiaoru; Zhang, Z.; Sui, Y.; Huang, Z.

2008-01-01

As an extension of traditional modal logics, this paper proposes a fuzzy first-order modal logic based on believable degree, and gives out a description of the fuzzy first-order modal logic based on constant domain semantics. In order to make the reasoning procedure between the fuzzy assertions

Real-time context aware reasoning in on-board intelligent traffic systems: An Architecture for Ontology-based Reasoning using Finite State Machines

NARCIS (Netherlands)

Stoter, Arjan; Dalmolen, Simon; Drenth, Eduard; Cornelisse, Erik; Mulder, Wico

2011-01-01

In-vehicle information management is vital in intelligent traffic systems. In this paper we motivate an architecture for ontology-based context-aware reasoning for in-vehicle information management. An ontology is essential for system standardization and communication, and ontology-based reasoning

An Indexing Scheme for Case-Based Manufacturing Vision Development

DEFF Research Database (Denmark)

Wang, Chengbo; Johansen, John; Luxhøj, James T.

2004-01-01

with the competence improvement of an enterprises manufacturing system. There are two types of cases within the CBRM – an event case (EC) and a general supportive case (GSC). We designed one set of indexing vocabulary for the two types of cases, but a different indexing representation structure for each of them......This paper focuses on one critical element, indexing – retaining and representing knowledge in an applied case-based reasoning (CBR) model for supporting strategic manufacturing vision development (CBRM). Manufacturing vision (MV) is a kind of knowledge management concept and process concerned...

Rule Based Reasoning Untuk Monitoring Distribusi Bahan Bakar Minyak Secara Online dan Realtime menggunakan Radio Frequency Identification

Directory of Open Access Journals (Sweden)

Mokhamad Iklil Mustofa

2017-05-01

Full Text Available The scarcity of fuel oil in Indonesia often occurs due to delays in delivery caused by natural factors or transportation constraints. Theaim of this  research is to develop systems of fuel distribution monitoring online and realtime using rule base reasoning method and radio frequency identification technology. The rule-based reasoning method is used as a rule-based reasoning model used for monitoring distribution and determine rule-based safety stock. The monitoring system program is run with a web-based computer application. Radio frequency identification technology is used by utilizing radio waves as an media identification. This technology is used as a system of tracking and gathering information from objects automatically. The research data uses data of delayed distribution of fuel from fuel terminal to consumer. The monitoring technique uses the time of departure, the estimated time to arrive, the route / route passed by a fuel tanker attached to the radio frequency Identification tag. This monitoring system is carried out by the radio frequency identification reader connected online at any gas station or specified position that has been designed with study case in Semarang. The results of the research covering  the status of rule based reasoning that sends status, that is timely and appropriate paths, timely and truncated pathways, late and on track, late and cut off, and tank lost. The monitoring system is also used in determining the safety stock warehouse, with the safety stock value determined based on the condition of the stock warehouse rules.

Describing the clinical reasoning process: application of a model of enablement to a pediatric case.

Science.gov (United States)

Furze, Jennifer; Nelson, Kelly; O'Hare, Megan; Ortner, Amanda; Threlkeld, A Joseph; Jensen, Gail M

2013-04-01

Clinical reasoning is a core tenet of physical therapy practice leading to optimal patient care. The purpose of this case was to describe the outcomes, subjective experience, and reflective clinical reasoning process for a child with cerebral palsy using the International Classification of Functioning, Disability, and Health (ICF) model. Application of the ICF framework to a 9-year-old boy with spastic triplegic cerebral palsy was utilized to capture the interwoven factors present in this case. Interventions in the pool occurred twice weekly for 1 h over a 10-week period. Immediately post and 4 months post-intervention, the child made functional and meaningful gains. The family unit also developed an enjoyment of exercising together. Each individual family member described psychological, emotional, or physical health improvements. Reflection using the ICF model as a framework to discuss clinical reasoning can highlight important factors contributing to effective patient management.

Executable specifications for hypothesis-based reasoning with Prolog and Constraint Handling Rules

DEFF Research Database (Denmark)

Christiansen, Henning

2009-01-01

Constraint Handling Rules (CHR) is an extension to Prolog which opens up a  spectrum of hypotheses-based reasoning in logic programs without additional interpretation overhead. Abduction with integrity constraints is one example of hypotheses-based reasoning which can be implemented directly...... in Prolog and CHR with a straightforward use of available and efficiently implemented facilities The present paper clarifies the semantic foundations for this way of doing abduction in CHR and Prolog as well as other examples  of hypotheses-based reasoning that is possible, including assumptive logic...

Neural Correlates of Post-Conventional Moral Reasoning: A Voxel-Based Morphometry Study

Science.gov (United States)

Prehn, Kristin; Korczykowski, Marc; Rao, Hengyi; Fang, Zhuo; Detre, John A.; Robertson, Diana C.

2015-01-01

Going back to Kohlberg, moral development research affirms that people progress through different stages of moral reasoning as cognitive abilities mature. Individuals at a lower level of moral reasoning judge moral issues mainly based on self-interest (personal interests schema) or based on adherence to laws and rules (maintaining norms schema), whereas individuals at the post-conventional level judge moral issues based on deeper principles and shared ideals. However, the extent to which moral development is reflected in structural brain architecture remains unknown. To investigate this question, we used voxel-based morphometry and examined the brain structure in a sample of 67 Master of Business Administration (MBA) students. Subjects completed the Defining Issues Test (DIT-2) which measures moral development in terms of cognitive schema preference. Results demonstrate that subjects at the post-conventional level of moral reasoning were characterized by increased gray matter volume in the ventromedial prefrontal cortex and subgenual anterior cingulate cortex, compared with subjects at a lower level of moral reasoning. Our findings support an important role for both cognitive and emotional processes in moral reasoning and provide first evidence for individual differences in brain structure according to the stages of moral reasoning first proposed by Kohlberg decades ago. PMID:26039547

Neural correlates of post-conventional moral reasoning: a voxel-based morphometry study.

Directory of Open Access Journals (Sweden)

Kristin Prehn

Full Text Available Going back to Kohlberg, moral development research affirms that people progress through different stages of moral reasoning as cognitive abilities mature. Individuals at a lower level of moral reasoning judge moral issues mainly based on self-interest (personal interests schema or based on adherence to laws and rules (maintaining norms schema, whereas individuals at the post-conventional level judge moral issues based on deeper principles and shared ideals. However, the extent to which moral development is reflected in structural brain architecture remains unknown. To investigate this question, we used voxel-based morphometry and examined the brain structure in a sample of 67 Master of Business Administration (MBA students. Subjects completed the Defining Issues Test (DIT-2 which measures moral development in terms of cognitive schema preference. Results demonstrate that subjects at the post-conventional level of moral reasoning were characterized by increased gray matter volume in the ventromedial prefrontal cortex and subgenual anterior cingulate cortex, compared with subjects at a lower level of moral reasoning. Our findings support an important role for both cognitive and emotional processes in moral reasoning and provide first evidence for individual differences in brain structure according to the stages of moral reasoning first proposed by Kohlberg decades ago.

Neural correlates of post-conventional moral reasoning: a voxel-based morphometry study.

Science.gov (United States)

Prehn, Kristin; Korczykowski, Marc; Rao, Hengyi; Fang, Zhuo; Detre, John A; Robertson, Diana C

2015-01-01

Going back to Kohlberg, moral development research affirms that people progress through different stages of moral reasoning as cognitive abilities mature. Individuals at a lower level of moral reasoning judge moral issues mainly based on self-interest (personal interests schema) or based on adherence to laws and rules (maintaining norms schema), whereas individuals at the post-conventional level judge moral issues based on deeper principles and shared ideals. However, the extent to which moral development is reflected in structural brain architecture remains unknown. To investigate this question, we used voxel-based morphometry and examined the brain structure in a sample of 67 Master of Business Administration (MBA) students. Subjects completed the Defining Issues Test (DIT-2) which measures moral development in terms of cognitive schema preference. Results demonstrate that subjects at the post-conventional level of moral reasoning were characterized by increased gray matter volume in the ventromedial prefrontal cortex and subgenual anterior cingulate cortex, compared with subjects at a lower level of moral reasoning. Our findings support an important role for both cognitive and emotional processes in moral reasoning and provide first evidence for individual differences in brain structure according to the stages of moral reasoning first proposed by Kohlberg decades ago.

Intelligent Adaptation Process for Case Based Systems

International Nuclear Information System (INIS)

Nassar, A.M.; Mohamed, A.H.; Mohamed, A.H.

2014-01-01

Case Based Reasoning (CBR) Systems is one of the important decision making systems applied in many fields all over the world. The effectiveness of any CBR system based on the quality of the storage cases in the case library. Similar cases can be retrieved and adapted to produce the solution for the new problem. One of the main issues faced the CBR systems is the difficulties of achieving the useful cases. The proposed system introduces a new approach that uses the genetic algorithm (GA) technique to automate constructing the cases into the case library. Also, it can optimize the best one to be stored in the library for the future uses. However, the proposed system can avoid the problems of the uncertain and noisy cases. Besides, it can simply the retrieving and adaptation processes. So, it can improve the performance of the CBR system. The suggested system can be applied for many real-time problems. It has been applied for diagnosis the faults of the wireless network, diagnosis of the cancer diseases, diagnosis of the debugging of a software as cases of study. The proposed system has proved its performance in this field

REASONING IN THE FUZZY FRONT END OF INNOVATION:

DEFF Research Database (Denmark)

Haase, Louise Møller; Laursen, Linda Nhu

2018-01-01

in the fuzzy front end is the reasoning process: innovation teams are faced with open-ended, ill-defined problems, where they need to make decisions about an unknown future but have only incomplete, ambiguous and contradicting insights available. We study the reasoning of experts, how they frame to make sense...... of all the insights and create a basis for decision-making in relation to a new project. Based on case studies of five innovative products from various industries, we propose a Product DNA model for understanding the reasoning in the fuzzy front end of innovation. The Product DNA Model explains how...... experts reason and what direct their reasoning....

Emotional reasoning and parent-based reasoning in non-clinical children and their prospective relationships with anxiety symptoms

NARCIS (Netherlands)

Morren, M.; Muris, P.; Kindt, M.; Schouten, E.; van den Hout, M.

2008-01-01

Emotional and parent-based reasoning refer to the tendency to rely on personal or parental anxiety response information rather than on objective danger information when estimating the dangerousness of a situation. This study investigated the prospective relationships of emotional and parent-based

AUTOMATIC MULTILEVEL IMAGE SEGMENTATION BASED ON FUZZY REASONING

Directory of Open Access Journals (Sweden)

Liang Tang

2011-05-01

Full Text Available An automatic multilevel image segmentation method based on sup-star fuzzy reasoning (SSFR is presented. Using the well-known sup-star fuzzy reasoning technique, the proposed algorithm combines the global statistical information implied in the histogram with the local information represented by the fuzzy sets of gray-levels, and aggregates all the gray-levels into several classes characterized by the local maximum values of the histogram. The presented method has the merits of determining the number of the segmentation classes automatically, and avoiding to calculating thresholds of segmentation. Emulating and real image segmentation experiments demonstrate that the SSFR is effective.

Continuity and change in the development of category-based induction: The test case of diversity-based reasoning.

Science.gov (United States)

Rhodes, Marjorie; Liebenson, Peter

2015-11-01

The present research examined the extent to which the cognitive mechanisms available to support inductive inference stay constant across development or undergo fundamental change. Four studies tested how children (ages 5-10) incorporate information about sample composition into their category-based generalizations. Children's use of sample composition varied across age and type of category. For familiar natural kinds, children ages 5-8 generalized similarly from diverse and non-diverse samples of evidence, whereas older children generalized more broadly from more diverse sets. In contrast, for novel categories, children of each age made broader generalizations from diverse than non-diverse samples. These studies provide the first clear evidence that young children are able to incorporate sample diversity into their inductive reasoning. These findings suggest developmental continuity in the cognitive mechanisms available for inductive inference, but developmental changes in the role that prior knowledge plays in shaping these processes. Copyright © 2015 Elsevier Inc. All rights reserved.

Computational approaches to analogical reasoning current trends

CERN Document Server

Richard, Gilles

2014-01-01

Analogical reasoning is known as a powerful mode for drawing plausible conclusions and solving problems. It has been the topic of a huge number of works by philosophers, anthropologists, linguists, psychologists, and computer scientists. As such, it has been early studied in artificial intelligence, with a particular renewal of interest in the last decade. The present volume provides a structured view of current research trends on computational approaches to analogical reasoning. It starts with an overview of the field, with an extensive bibliography. The 14 collected contributions cover a large scope of issues. First, the use of analogical proportions and analogies is explained and discussed in various natural language processing problems, as well as in automated deduction. Then, different formal frameworks for handling analogies are presented, dealing with case-based reasoning, heuristic-driven theory projection, commonsense reasoning about incomplete rule bases, logical proportions induced by similarity an...

Examining Preservice Teachers' Decision Behaviors and Individual Differences in Three Online Case-Based Approaches

Science.gov (United States)

Cevik, Yasemin Demiraslan; Andre, Thomas

2013-01-01

This study compared the impact of three types of case-based methods (case-based reasoning, worked example, and faded worked example) on preservice teachers' (n = 71) interaction with decision tasks and whether decision related measures (task difficulty, mental effort, decision making performance) were associated with the differences in student…

Clinical reasoning in nursing, a think-aloud study using virtual patients - a base for an innovative assessment.

Science.gov (United States)

Forsberg, Elenita; Ziegert, Kristina; Hult, Håkan; Fors, Uno

2014-04-01

In health-care education, it is important to assess the competencies that are essential for the professional role. To develop clinical reasoning skills is crucial for nursing practice and therefore an important learning outcome in nursing education programmes. Virtual patients (VPs) are interactive computer simulations of real-life clinical scenarios and have been suggested for use not only for learning, but also for assessment of clinical reasoning. The aim of this study was to investigate how experienced paediatric nurses reason regarding complex VP cases and how they make clinical decisions. The study was also aimed to give information about possible issues that should be assessed in clinical reasoning exams for post-graduate students in diploma specialist paediatric nursing education. The information from this study is believed to be of high value when developing scoring and grading models for a VP-based examination for the specialist diploma in paediatric nursing education. Using the think-aloud method, data were collected from 30 RNs working in Swedish paediatric departments, and child or school health-care centres. Content analysis was used to analyse the data. The results indicate that experienced nurses try to consolidate their hypotheses by seeing a pattern and judging the value of signs, symptoms, physical examinations, laboratory tests and radiology. They show high specific competence but earlier experience of similar cases was also of importance for the decision making. The nurses thought it was an innovative assessment focusing on clinical reasoning and clinical decision making. They thought it was an enjoyable way to be assessed and that all three main issues could be assessed using VPs. In conclusion, VPs seem to be a possible model for assessing the clinical reasoning process and clinical decision making, but how to score and grade such exams needs further research. © 2013.

Conceptualizing reasoning-and-proving opportunities in textbook expositions : Cases from secondary calculus

OpenAIRE

Bergwall, Andreas

2017-01-01

Several recent textbook studies focus on opportunities to learn reasoning-and-proving. They typically investigate the extent to which justifications are general proofs and what opportunities exist for learning important elements of mathematical reasoning. In this paper, I discuss how a particular analytical framework for this might be refined. Based on an in-depth analysis of certain textbook passages in upper secondary calculus textbooks, I make an account for analytical issues encountered d...

Intertwining evidence- and model-based reasoning in physics sensemaking: An example from electrostatics

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Russ, Rosemary S.; Odden, Tor Ole B.

2017-12-01

Our field has long valued the goal of teaching students not just the facts of physics, but also the thinking and reasoning skills of professional physicists. The complexity inherent in scientific reasoning demands that we think carefully about how we conceptualize for ourselves, enact in our classes, and encourage in our students the relationship between the multifaceted practices of professional science. The current study draws on existing research in the philosophy of science and psychology to advocate for intertwining two important aspects of scientific reasoning: using evidence from experimentation and modeling. We present a case from an undergraduate physics course to illustrate how these aspects can be intertwined productively and describe specific ways in which these aspects of reasoning can mutually reinforce one another in student learning. We end by discussing implications for this work for instruction in introductory physics courses and for research on scientific reasoning at the undergraduate level.

Reasoning about modular datatypes with Mendler induction

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Paolo Torrini

2015-09-01

Full Text Available In functional programming, datatypes a la carte provide a convenient modular representation of recursive datatypes, based on their initial algebra semantics. Unfortunately it is highly challenging to implement this technique in proof assistants that are based on type theory, like Coq. The reason is that it involves type definitions, such as those of type-level fixpoint operators, that are not strictly positive. The known work-around of impredicative encodings is problematic, insofar as it impedes conventional inductive reasoning. Weak induction principles can be used instead, but they considerably complicate proofs. This paper proposes a novel and simpler technique to reason inductively about impredicative encodings, based on Mendler-style induction. This technique involves dispensing with dependent induction, ensuring that datatypes can be lifted to predicates and relying on relational formulations. A case study on proving subject reduction for structural operational semantics illustrates that the approach enables modular proofs, and that these proofs are essentially similar to conventional ones.

Model Based Reasoning by Introductory Students When Analyzing Earth Systems and Societal Challenges

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Holder, L. N.; Herbert, B. E.

2014-12-01

Understanding how students use their conceptual models to reason about societal challenges involving societal issues such as natural hazard risk assessment, environmental policy and management, and energy resources can improve instructional activity design that directly impacts student motivation and literacy. To address this question, we created four laboratory exercises for an introductory physical geology course at Texas A&M University that engages students in authentic scientific practices by using real world problems and issues that affect societies based on the theory of situated cognition. Our case-study design allows us to investigate the various ways that students utilize model based reasoning to identify and propose solutions to societally relevant issues. In each of the four interventions, approximately 60 students in three sections of introductory physical geology were expected to represent and evaluate scientific data, make evidence-based claims about the data trends, use those claims to express conceptual models, and use their models to analyze societal challenges. Throughout each step of the laboratory exercise students were asked to justify their claims, models, and data representations using evidence and through the use of argumentation with peers. Cognitive apprenticeship was the foundation for instruction used to scaffold students so that in the first exercise they are given a partially completed model and in the last exercise students are asked to generate a conceptual model on their own. Student artifacts, including representation of earth systems, representation of scientific data, verbal and written explanations of models and scientific arguments, and written solutions to specific societal issues or environmental problems surrounding earth systems, were analyzed through the use of a rubric that modeled authentic expertise and students were sorted into three categories. Written artifacts were examined to identify student argumentation and

Danish Majority Children’s Reasoning About Exclusion Based on Gender and Ethnicity

DEFF Research Database (Denmark)

Møller, Signe Juhl; Tenenbaum, Harriet R.

2011-01-01

This study investigated 282 eight- to twelve-year-old Danish majority children's judgments and justifications of exclusion based on gender and ethnicity (i.e., Danish majority children and ethnic-minority children of a Muslim background). Children's judgments and reasoning varied with the perpetr......This study investigated 282 eight- to twelve-year-old Danish majority children's judgments and justifications of exclusion based on gender and ethnicity (i.e., Danish majority children and ethnic-minority children of a Muslim background). Children's judgments and reasoning varied...... with the perpetrator of the exclusion and the social identity of the target. Children assessed exclusion based on ethnicity as less acceptable than exclusion based on gender and used more moral reasoning for the former than the latter. Children judged it less acceptable for a teacher than a child to exclude a child...

Undermining Reasonableness: Expert Testimony in a Case Involving a Battered Woman Who Kills

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Terrance, Cheryl; Matheson, Kimberly

2003-01-01

Student participants (N = 316) viewed a videotaped simulated case involving a woman who had entered a self-defense plea in the shooting death of her abusive husband. As successful claims of self-defense rest on the portrayal of a defendant who has responded reasonably to his/her situation, the implications of various forms of expert testimony in…

Architectural design thinking as a form of model-based reasoning

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Pauwels, P.; Bod, R.

2014-01-01

Model-based reasoning can be considered central in very diverse domains of practice. Recently considered domains of practice are political discourse, social intercourse, language learning, archaeology, collaboration and conversation, and so forth. In this paper, we explore features of model-based

Investigating Image-Based Perception and Reasoning in Geometry

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Campbell, Stephen R.; Handscomb, Kerry; Zaparyniuk, Nicholas E.; Sha, Li; Cimen, O. Arda; Shipulina, Olga V.

2009-01-01

Geometry is required for many secondary school students, and is often learned, taught, and assessed more in a heuristic image-based manner, than as a formal axiomatic deductive system. Students are required to prove general theorems, but diagrams are usually used. It follows that understanding how students engage in perceiving and reasoning about…

Semantics-based plausible reasoning to extend the knowledge coverage of medical knowledge bases for improved clinical decision support.

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Mohammadhassanzadeh, Hossein; Van Woensel, William; Abidi, Samina Raza; Abidi, Syed Sibte Raza

2017-01-01

Capturing complete medical knowledge is challenging-often due to incomplete patient Electronic Health Records (EHR), but also because of valuable, tacit medical knowledge hidden away in physicians' experiences. To extend the coverage of incomplete medical knowledge-based systems beyond their deductive closure, and thus enhance their decision-support capabilities, we argue that innovative, multi-strategy reasoning approaches should be applied. In particular, plausible reasoning mechanisms apply patterns from human thought processes, such as generalization, similarity and interpolation, based on attributional, hierarchical, and relational knowledge. Plausible reasoning mechanisms include inductive reasoning , which generalizes the commonalities among the data to induce new rules, and analogical reasoning , which is guided by data similarities to infer new facts. By further leveraging rich, biomedical Semantic Web ontologies to represent medical knowledge, both known and tentative, we increase the accuracy and expressivity of plausible reasoning, and cope with issues such as data heterogeneity, inconsistency and interoperability. In this paper, we present a Semantic Web-based, multi-strategy reasoning approach, which integrates deductive and plausible reasoning and exploits Semantic Web technology to solve complex clinical decision support queries. We evaluated our system using a real-world medical dataset of patients with hepatitis, from which we randomly removed different percentages of data (5%, 10%, 15%, and 20%) to reflect scenarios with increasing amounts of incomplete medical knowledge. To increase the reliability of the results, we generated 5 independent datasets for each percentage of missing values, which resulted in 20 experimental datasets (in addition to the original dataset). The results show that plausibly inferred knowledge extends the coverage of the knowledge base by, on average, 2%, 7%, 12%, and 16% for datasets with, respectively, 5%, 10%, 15

Bringing explicit insight into cognitive psychology features during clinical reasoning seminars: a prospective, controlled study.

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Nendaz, Mathieu R; Gut, Anne M; Louis-Simonet, Martine; Perrier, Arnaud; Vu, Nu V

2011-04-01

Facets of reasoning competence influenced by an explicit insight into cognitive psychology features during clinical reasoning seminars have not been specifically explored. This prospective, controlled study, conducted at the University of Geneva Faculty of Medicine, Switzerland, assessed the impact on sixth-year medical students' patient work-up of case-based reasoning seminars, bringing them explicit insight into cognitive aspects of their reasoning. Volunteer students registered for our three-month Internal Medicine elective were assigned to one of two training conditions: standard (control) or modified (intervention) case-based reasoning seminars. These seminars start with the patient's presenting complaint and the students must ask the tutor for additional clinical information to progress through case resolution. For this intervention, the tutors made each step explicit to students and encouraged self-reflection on their reasoning processes. At the end of their elective, students' performances were assessed through encounters with two standardized patients and chart write-ups. Twenty-nine students participated, providing a total of 58 encounters. The overall differences in accuracy of the final diagnosis given to the patient at the end of the encounter (control 63% vs intervention 74%, p = 0.53) and of the final diagnosis mentioned in the patient chart (61% vs 70%, p = 0.58) were not statistically significant. The students in the intervention group significantly more often listed the correct diagnosis among the differential diagnoses in their charts (75% vs 97%, p = 0.02). This case-based clinical reasoning seminar intervention, designed to bring students insight into cognitive features of their reasoning, improved aspects of diagnostic competence.

Hurrah for the Reasonable Woman.

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Leland, Dorothy

1994-01-01

Recent court cases on sexual harassment, and the outcomes, were reviewed in terms of how the court viewed a "reasonable" woman. Rulings in such cases can vary because of different interpretations of the "reasonable" concept. Also discusses how recent rulings will affect sexual harassment policymakers in the workplace and educational institutions.…

Solving probability reasoning based on DNA strand displacement and probability modules.

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Zhang, Qiang; Wang, Xiaobiao; Wang, Xiaojun; Zhou, Changjun

2017-12-01

In computation biology, DNA strand displacement technology is used to simulate the computation process and has shown strong computing ability. Most researchers use it to solve logic problems, but it is only rarely used in probabilistic reasoning. To process probabilistic reasoning, a conditional probability derivation model and total probability model based on DNA strand displacement were established in this paper. The models were assessed through the game "read your mind." It has been shown to enable the application of probabilistic reasoning in genetic diagnosis. Copyright © 2017 Elsevier Ltd. All rights reserved.

Online Open Circuit Fault Diagnosis for Rail Transit Traction Converter Based on Object-Oriented Colored Petri Net Topology Reasoning

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Lei Wang

2016-01-01

Full Text Available For online open circuit fault diagnosis of the traction converter in rail transit vehicles, conventional approaches depend heavily on component parameters and circuit layouts. For better universality and less parameter sensitivity during the diagnosis, this paper proposes a novel topology analysis approach to diagnose switching device open circuit failures. During the diagnosis, the topology is analyzed with fault reasoning mechanism, which is based on object-oriented Petri net (OOCPN. The OOCPN model takes in digitalized current inputs as fault signatures, and dynamical transitions between discrete switching states of a circuit with broken device are symbolized with the dynamical transitions of colored tokens in OOCPN. Such transitions simulate natural reasoning process of an expert’s brain during diagnosis. The dependence on component parameters and on circuit layouts is finally eliminated by such circuit topology reasoning process. In the last part, the proposed online reasoning and diagnosis process is exemplified with the case of a certain switching device failure in the power circuit of traction converter.

Reliability Assessment of Cloud Computing Platform Based on Semiquantitative Information and Evidential Reasoning

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Hang Wei

2016-01-01

Full Text Available A reliability assessment method based on evidential reasoning (ER rule and semiquantitative information is proposed in this paper, where a new reliability assessment architecture including four aspects with both quantitative data and qualitative knowledge is established. The assessment architecture is more objective in describing complex dynamic cloud computing environment than that in traditional method. In addition, the ER rule which has good performance for multiple attribute decision making problem is employed to integrate different types of the attributes in assessment architecture, which can obtain more accurate assessment results. The assessment results of the case study in an actual cloud computing platform verify the effectiveness and the advantage of the proposed method.

Using case-based reasoning for the reconstitution and manipulation of voxelized phantoms; Utilisation du raisonnement a partir de cas pour la reconstitution et la manipulation de fantomes voxelises

Energy Technology Data Exchange (ETDEWEB)

Henriet, J.; Fontaine, E.; Bopp, M.; Makovicka, L. [IRMAIENISYSI Institut FEMTO - UMR CNRS 6174, Pole Universitaire des Portes du Jura, 4 Place Tharradin - BP 71427, 25211 - Montbeliard (France); Farah, J.; Broggio, D.; Franck, D. [CEA Fontenay-aux-Roses, LEDIISDIIDPRH, IRSN, 92 (France); Chebel-Morello, B. [COSMI/AS2M/Institut FEMTO - UMR CNRS 6174, 24 Rue Alain Savary, 25000 - Besaneon (France)

2010-07-01

The authors reports the development of the EquiVox platform, the aim of which is to allow a radioprotection expert (physician, biologist or other) to work with a phantom which will be the closest possible to the examined person in order to make an as precise as possible dosimetric assessment. The objective is to help to select the best phantom among those the expert knows depending on the assessment type he wants to make. First, they present the general principles of the case-based reasoning, and then the EquiVox platform which proposes all the steps: formalization, elaboration, comparison, and so on. Based on typical numerical values associated with different morphological characteristics, they present and discuss graphical results obtained by the platform. They also discuss their validity and reliability

Cognitive Trait Modelling: The Case of Inductive Reasoning Ability

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Kinshuk, Taiyu Lin; McNab, Paul

2006-01-01

Researchers have regarded inductive reasoning as one of the seven primary mental abilities that account for human intelligent behaviours. Researchers have also shown that inductive reasoning ability is one of the best predictors for academic performance. Modelling of inductive reasoning is therefore an important issue for providing adaptivity in…

Reasonable Accommodation Information Tracking System

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U.S. Environmental Protection Agency — The Reasonable Accommodation Information Tracking System (RAITS) is a case management system that allows the National Reasonable Accommodation Coordinator (NRAC) and...

Visualizing complex processes using a cognitive-mapping tool to support the learning of clinical reasoning.

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Wu, Bian; Wang, Minhong; Grotzer, Tina A; Liu, Jun; Johnson, Janice M

2016-08-22

Practical experience with clinical cases has played an important role in supporting the learning of clinical reasoning. However, learning through practical experience involves complex processes difficult to be captured by students. This study aimed to examine the effects of a computer-based cognitive-mapping approach that helps students to externalize the reasoning process and the knowledge underlying the reasoning process when they work with clinical cases. A comparison between the cognitive-mapping approach and the verbal-text approach was made by analyzing their effects on learning outcomes. Fifty-two third-year or higher students from two medical schools participated in the study. Students in the experimental group used the computer-base cognitive-mapping approach, while the control group used the verbal-text approach, to make sense of their thinking and actions when they worked with four simulated cases over 4 weeks. For each case, students in both groups reported their reasoning process (involving data capture, hypotheses formulation, and reasoning with justifications) and the underlying knowledge (involving identified concepts and the relationships between the concepts) using the given approach. The learning products (cognitive maps or verbal text) revealed that students in the cognitive-mapping group outperformed those in the verbal-text group in the reasoning process, but not in making sense of the knowledge underlying the reasoning process. No significant differences were found in a knowledge posttest between the two groups. The computer-based cognitive-mapping approach has shown a promising advantage over the verbal-text approach in improving students' reasoning performance. Further studies are needed to examine the effects of the cognitive-mapping approach in improving the construction of subject-matter knowledge on the basis of practical experience.

Reasons for receiving or not receiving HPV vaccination in primary schoolgirls in Tanzania: a case control study.

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Watson-Jones, Deborah; Tomlin, Keith; Remes, Pieter; Baisley, Kathy; Ponsiano, Riziki; Soteli, Selephina; de Sanjosé, Silvia; Changalucha, John; Kapiga, Saidi; Hayes, Richard J

2012-01-01

There are few data on factors influencing human papillomavirus (HPV) vaccination uptake in sub-Saharan Africa. We examined the characteristics of receivers and non-receivers of HPV vaccination in Tanzania and identified reasons for not receiving the vaccine. We conducted a case control study of HPV vaccine receivers and non-receivers within a phase IV cluster-randomised trial of HPV vaccination in 134 primary schools in Tanzania. Girls who failed to receive vaccine (pupil cases) and their parents/guardians (adult cases) and girls who received dose 1 (pupil controls) of the quadrivalent vaccine (Gardasil™) and their parents/guardians (adult controls) were enrolled from 39 schools in a 1∶1 ratio and interviewed about cervical cancer, HPV vaccine knowledge and reasons why they might have received or not received the vaccine. Conditional logistic regression was used to determine factors independently associated with not receiving HPV vaccine. We interviewed 159 pupil/adult cases and 245 pupil/adult controls. Adult-factors independently associated with a daughter being a case were older age, owning fewer household items, not attending a school meeting about HPV vaccine, and not knowing anyone with cancer. Pupil-factors for being a case included having a non-positive opinion about the school de-worming programme, poor knowledge about the location of the cervix, and not knowing that a vaccine could prevent cervical cancer. Reasons for actively refusing vaccination included concerns about side effects and infertility. Most adult and pupil cases reported that they would accept the HPV vaccine if it were offered again (97% and 93% respectively). Sensitisation messages, especially targeted at older and poorer parents, knowledge retention and parent meetings are critical for vaccine acceptance in Tanzania. Vaccine side effects and fertility concerns should be addressed prior to a national vaccination program. Parents and pupils who initially decline vaccination should be

Emotional reasoning and parent-based reasoning in normal children

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Morren, M.; Muris, P.; Kindt, M.

2004-01-01

A previous study by Muris, Merckelbach, and Van Spauwen demonstrated that children display emotional reasoning irrespective of their anxiety levels. That is, when estimating whether a situation is dangerous, children not only rely on objective danger information but also on their own

Working memory, reasoning, and expertise in medicine-insights into their relationship using functional neuroimaging.

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Hruska, Pam; Krigolson, Olav; Coderre, Sylvain; McLaughlin, Kevin; Cortese, Filomeno; Doig, Christopher; Beran, Tanya; Wright, Bruce; Hecker, Kent G

2016-12-01

Clinical reasoning is dependent upon working memory (WM). More precisely, during the clinical reasoning process stored information within long-term memory is brought into WM to facilitate the internal deliberation that affords a clinician the ability to reason through a case. In the present study, we examined the relationship between clinical reasoning and WM while participants read clinical cases with functional magnetic resonance imaging (fMRI). More specifically, we examined the impact of clinical case difficulty (easy, hard) and clinician level of expertise (2nd year medical students, senior gastroenterologists) on neural activity within regions of cortex associated with WM (i.e., the prefrontal cortex) during the reasoning process. fMRI was used to scan ten second-year medical students and ten practicing gastroenterologists while they reasoned through sixteen clinical cases [eight straight forward (easy) and eight complex (hard)] during a single 1-h scanning session. Within-group analyses contrasted the easy and hard cases which were then subsequently utilized for a between-group analysis to examine effects of expertise (novice > expert, expert > novice). Reading clinical cases evoked multiple neural activations in occipital, prefrontal, parietal, and temporal cortical regions in both groups. Importantly, increased activation in the prefrontal cortex in novices for both easy and hard clinical cases suggests novices utilize WM more so than experts during clinical reasoning. We found that clinician level of expertise elicited differential activation of regions of the human prefrontal cortex associated with WM during clinical reasoning. This suggests there is an important relationship between clinical reasoning and human WM. As such, we suggest future models of clinical reasoning take into account that the use of WM is not consistent throughout all clinical reasoning tasks, and that memory structure may be utilized differently based on level of expertise.

Language-Based Reasoning in Primary Science

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Hackling, Mark; Sherriff, Barbara

2015-01-01

Language is critical in the mediation of scientific reasoning, higher-order thinking and the development of scientific literacy. This study investigated how an exemplary primary science teacher scaffolds and supports students' reasoning during a Year 4 materials unit. Lessons captured on video, teacher and student interviews and micro-ethnographic…

Diversity-based reasoning in children.

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Heit, E; Hahn, U

2001-12-01

One of the hallmarks of inductive reasoning by adults is the diversity effect, namely that people draw stronger inferences from a diverse set of evidence than from a more homogenous set of evidence. However, past developmental work has not found consistent diversity effects with children age 9 and younger. We report robust sensitivity to diversity in children as young as 5, using everyday stimuli such as pictures of objects with people. Experiment 1 showed the basic diversity effect in 5- to 9-year-olds. Experiment 2 showed that, like adults, children restrict their use of diversity information when making inferences about remote categories. Experiment 3 used other stimulus sets to overcome an alternate explanation in terms of sample size rather than diversity effects. Finally, Experiment 4 showed that children more readily draw on diversity when reasoning about objects and their relations with people than when reasoning about objects' internal, hidden properties, thus partially explaining the negative findings of previous work. Relations to cross-cultural work and models of induction are discussed. Copyright 2001 Academic Press.

From qualitative reasoning models to Bayesian-based learner modeling

NARCIS (Netherlands)

Milošević, U.; Bredeweg, B.; de Kleer, J.; Forbus, K.D.

2010-01-01

Assessing the knowledge of a student is a fundamental part of intelligent learning environments. We present a Bayesian network based approach to dealing with uncertainty when estimating a learner’s state of knowledge in the context of Qualitative Reasoning (QR). A proposal for a global architecture

Understanding of emotions based on counterfactual reasoning in children with autism spectrum disorders.

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Begeer, Sander; De Rosnay, Marc; Lunenburg, Patty; Stegge, Hedy; Terwogt, Mark Meerum

2014-04-01

The understanding of emotions based on counterfactual reasoning was studied in children with high-functioning autism spectrum disorders (n = 71) and in typically developing children (n = 71), aged 6-12 years. Children were presented with eight stories about two protagonists who experienced the same positive or negative outcome, either due to their own action or by default. Relative to the comparison group, children with high-functioning autism spectrum disorder were poor at explaining emotions based on downward counterfactual reasoning (i.e. contentment and relief). There were no group differences in upward counterfactual reasoning (i.e. disappointment and regret). In the comparison group, second-order false-belief reasoning was related to children's understanding of second-order counterfactual emotions (i.e. regret and relief), while children in the high-functioning autism spectrum disorder group relied more on their general intellectual skills. Results are discussed in terms of the different functions of counterfactual reasoning about emotion and the cognitive style of children with high-functioning autism spectrum disorder.

Emotional reasoning and parent-based reasoning in normal children.

NARCIS (Netherlands)

Morren, M.; Muris, P.; Kindt, M.

2004-01-01

A previous study by Muris, Merckelbach, and Van Spauwen demonstrated that children display emotional reasoning irrepective of their anxiety levels. That is when estimating whether a situation is dangerous, childen not only rely on objective danger information but also on their own anciety-response.

Implementation of a Clinical Reasoning Course in the Internal Medicine trimester of the final year of undergraduate medical training and its effect on students' case presentation and differential diagnostic skills.

Science.gov (United States)

Harendza, Sigrid; Krenz, Ingo; Klinge, Andreas; Wendt, Ulrike; Janneck, Matthias

2017-01-01

Background: Clinical reasoning, comprising the processes of clinical thinking, which form the basis of medical decisions, constitutes a central competence in the clinical routine on which diagnostic and therapeutic steps are based. In medical curricula in Germany, clinical reasoning is currently taught explicitly only to a small extend. Therefore, the aim of this project was to develop and implement a clinical reasoning course in the final year of undergraduate medical training. Project description: A clinical reasoning course with six learning units and 18 learning objectives was developed, which was taught by two to four instructors on the basis of 32 paper cases from the clinical practice of the instructors. In the years 2011 to 2013, the course of eight weeks with two hours per week was taught seven times. Before the first and after the last seminar, the participating students filled out a self-assessment questionnaire with a 6-point Likert scale regarding eight different clinical reasoning skills. At the same times, they received a patient case with the assignment to prepare a case presentation and differential diagnoses. Results: From 128 participating students altogether, 42 complete data sets were available. After the course, participants assessed themselves significantly better than before the course in all eight clinical reasoning skills, for example in "Summarizing and presentation of a paper case" or in the "Skill to enumerate differential diagnoses" (ppresentation of the paper case was significantly more focused after the course (p=0.011). A significant increase in the number of gathered differential diagnoses was not detected after the course. Conclusion: The newly developed and established Clinical Reasoning Course leads to a gain in the desired skills from the students' self-assessment perspective and to a more structured case presentation. To establish better options to exercise clinical reasoning, a longitudinal implementation in the medical

The Effects of Successful versus Failure-Based Cases on Argumentation while Solving Decision-Making Problems

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Tawfik, Andrew; Jonassen, David

2013-01-01

Solving complex, ill-structured problems may be effectively supported by case-based reasoning through case libraries that provide just-in-time domain-specific principles in the form of stories. The cases not only articulate previous experiences of practitioners, but also serve as problem-solving narratives from which learners can acquire meaning.…

Global polar geospatial information service retrieval based on search engine and ontology reasoning

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Chen, Nengcheng; E, Dongcheng; Di, Liping; Gong, Jianya; Chen, Zeqiang

2007-01-01

In order to improve the access precision of polar geospatial information service on web, a new methodology for retrieving global spatial information services based on geospatial service search and ontology reasoning is proposed, the geospatial service search is implemented to find the coarse service from web, the ontology reasoning is designed to find the refined service from the coarse service. The proposed framework includes standardized distributed geospatial web services, a geospatial service search engine, an extended UDDI registry, and a multi-protocol geospatial information service client. Some key technologies addressed include service discovery based on search engine and service ontology modeling and reasoning in the Antarctic geospatial context. Finally, an Antarctica multi protocol OWS portal prototype based on the proposed methodology is introduced.

Watch what happens: using a web-based multimedia platform to enhance intraoperative learning and development of clinical reasoning.

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Fingeret, Abbey L; Martinez, Rebecca H; Hsieh, Christine; Downey, Peter; Nowygrod, Roman

2016-02-01

We aim to determine whether observed operations or internet-based video review predict improved performance in the surgery clerkship. A retrospective review of students' usage of surgical videos, observed operations, evaluations, and examination scores were used to construct an exploratory principal component analysis. Multivariate regression was used to determine factors predictive of clerkship performance. Case log data for 231 students revealed a median of 25 observed cases. Students accessed the web-based video platform a median of 15 times. Principal component analysis yielded 4 factors contributing 74% of the variability with a Kaiser-Meyer-Olkin coefficient of .83. Multivariate regression predicted shelf score (P < .0001), internal clinical skills examination score (P < .0001), subjective evaluations (P < .001), and video website utilization (P < .001) but not observed cases to be significantly associated with overall performance. Utilization of a web-based operative video platform during a surgical clerkship is an independently associated with improved clinical reasoning, fund of knowledge, and overall evaluation. Thus, this modality can serve as a useful adjunct to live observation. Copyright © 2016 Elsevier Inc. All rights reserved.

Scientific reasoning abilities of nonscience majors in physics-based courses

Science.gov (United States)

Moore, J. Christopher; Rubbo, Louis J.

2012-06-01

We have found that non-STEM (science, technology, engineering, and mathematics) majors taking either a conceptual physics or astronomy course at two regional comprehensive institutions score significantly lower preinstruction on the Lawson’s Classroom Test of Scientific Reasoning (LCTSR) in comparison to national average STEM majors. Based on LCTSR score, the majority of non-STEM students can be classified as either concrete operational or transitional reasoners in Piaget’s theory of cognitive development, whereas in the STEM population formal operational reasoners are far more prevalent. In particular, non-STEM students demonstrate significant difficulty with proportional and hypothetico-deductive reasoning. Prescores on the LCTSR are correlated with normalized learning gains on various concept inventories. The correlation is strongest for content that can be categorized as mostly theoretical, meaning a lack of directly observable exemplars, and weakest for content categorized as mostly descriptive, where directly observable exemplars are abundant. Although the implementation of research-verified, interactive engagement pedagogy can lead to gains in content knowledge, significant gains in theoretical content (such as force and energy) are more difficult with non-STEM students. We also observe no significant gains on the LCTSR without explicit instruction in scientific reasoning patterns. These results further demonstrate that differences in student populations are important when comparing normalized gains on concept inventories, and the achievement of significant gains in scientific reasoning requires a reevaluation of the traditional approach to physics for non-STEM students.

Scientific reasoning abilities of nonscience majors in physics-based courses

Directory of Open Access Journals (Sweden)

J. Christopher Moore

2012-02-01

Full Text Available We have found that non-STEM (science, technology, engineering, and mathematics majors taking either a conceptual physics or astronomy course at two regional comprehensive institutions score significantly lower preinstruction on the Lawson’s Classroom Test of Scientific Reasoning (LCTSR in comparison to national average STEM majors. Based on LCTSR score, the majority of non-STEM students can be classified as either concrete operational or transitional reasoners in Piaget’s theory of cognitive development, whereas in the STEM population formal operational reasoners are far more prevalent. In particular, non-STEM students demonstrate significant difficulty with proportional and hypothetico-deductive reasoning. Prescores on the LCTSR are correlated with normalized learning gains on various concept inventories. The correlation is strongest for content that can be categorized as mostly theoretical, meaning a lack of directly observable exemplars, and weakest for content categorized as mostly descriptive, where directly observable exemplars are abundant. Although the implementation of research-verified, interactive engagement pedagogy can lead to gains in content knowledge, significant gains in theoretical content (such as force and energy are more difficult with non-STEM students. We also observe no significant gains on the LCTSR without explicit instruction in scientific reasoning patterns. These results further demonstrate that differences in student populations are important when comparing normalized gains on concept inventories, and the achievement of significant gains in scientific reasoning requires a reevaluation of the traditional approach to physics for non-STEM students.

Clinical reasoning of junior doctors in emergency medicine: a grounded theory study.

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Adams, E; Goyder, C; Heneghan, C; Brand, L; Ajjawi, R

2017-02-01

Emergency medicine (EM) has a high case turnover and acuity making it a demanding clinical reasoning domain especially for junior doctors who lack experience. We aimed to better understand their clinical reasoning using dual cognition as a guiding theory. EM junior doctors were recruited from six hospitals in the south of England to participate in semi-structured interviews (n=20) and focus groups (n=17) based on recall of two recent cases. Transcripts were analysed using a grounded theory approach to identify themes and to develop a model of junior doctors' clinical reasoning in EM. Within cases, clinical reasoning occurred in three phases. In phase 1 (case framing), initial case cues and first impressions were predominantly intuitive, but checked by analytical thought and determined the urgency of clinical assessment. In phase 2 (evolving reasoning), non-analytical single cue and pattern recognitions were common which were subsequently validated by specific analytical strategies such as use of red flags. In phase 3 (ongoing uncertainty) analytical self-monitoring and reassurance strategies were used to precipitate a decision regarding discharge. We found a constant dialectic between intuitive and analytical cognition throughout the reasoning process. Our model of clinical reasoning by EM junior doctors illustrates the specific contextual manifestations of the dual cognition theory. Distinct diagnostic strategies are identified and together these give EM learners and educators a framework and vocabulary for discussion and learning about clinical reasoning. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Semantical Markov Logic Network for Distributed Reasoning in Cyber-Physical Systems

Directory of Open Access Journals (Sweden)

Abdul-Wahid Mohammed

2017-01-01

Full Text Available The challenges associated with developing accurate models for cyber-physical systems are attributable to the intrinsic concurrent and heterogeneous computations of these systems. Even though reasoning based on interconnected domain specific ontologies shows promise in enhancing modularity and joint functionality modelling, it has become necessary to build interoperable cyber-physical systems due to the growing pervasiveness of these systems. In this paper, we propose a semantically oriented distributed reasoning architecture for cyber-physical systems. This model accomplishes reasoning through a combination of heterogeneous models of computation. Using the flexibility of semantic agents as a formal representation for heterogeneous computational platforms, we define autonomous and intelligent agent-based reasoning procedure for distributed cyber-physical systems. Sensor networks underpin the semantic capabilities of this architecture, and semantic reasoning based on Markov logic networks is adopted to address uncertainty in modelling. To illustrate feasibility of this approach, we present a Markov logic based semantic event model for cyber-physical systems and discuss a case study of event handling and processing in a smart home.

Towards Cache-Enabled, Order-Aware, Ontology-Based Stream Reasoning Framework

Energy Technology Data Exchange (ETDEWEB)

Yan, Rui; Praggastis, Brenda L.; Smith, William P.; McGuinness, Deborah L.

2016-08-16

While streaming data have become increasingly more popular in business and research communities, semantic models and processing software for streaming data have not kept pace. Traditional semantic solutions have not addressed transient data streams. Semantic web languages (e.g., RDF, OWL) have typically addressed static data settings and linked data approaches have predominantly addressed static or growing data repositories. Streaming data settings have some fundamental differences; in particular, data are consumed on the fly and data may expire. Stream reasoning, a combination of stream processing and semantic reasoning, has emerged with the vision of providing "smart" processing of streaming data. C-SPARQL is a prominent stream reasoning system that handles semantic (RDF) data streams. Many stream reasoning systems including C-SPARQL use a sliding window and use data arrival time to evict data. For data streams that include expiration times, a simple arrival time scheme is inadequate if the window size does not match the expiration period. In this paper, we propose a cache-enabled, order-aware, ontology-based stream reasoning framework. This framework consumes RDF streams with expiration timestamps assigned by the streaming source. Our framework utilizes both arrival and expiration timestamps in its cache eviction policies. In addition, we introduce the notion of "semantic importance" which aims to address the relevance of data to the expected reasoning, thus enabling the eviction algorithms to be more context- and reasoning-aware when choosing what data to maintain for question answering. We evaluate this framework by implementing three different prototypes and utilizing five metrics. The trade-offs of deploying the proposed framework are also discussed.

Emotional Reasoning and Parent-Based Reasoning in Normal Children

Science.gov (United States)

Morren, Mattijn; Muris, Peter; Kindt, Merel

2004-01-01

A previous study by Muris, Merckelbach, and Van Spauwen [1] demonstrated that children display emotional reasoning irrespective of their anxiety levels. That is, when estimating whether a situation is dangerous, children not only rely on objective danger information but also on their "own" anxiety-response. The present study further examined…

Reasoning in Design: Idea Generation Condition Effects on Reasoning Processes and Evaluation of Ideas

DEFF Research Database (Denmark)

Cramer-Petersen, Claus Lundgaard; Ahmed-Kristensen, Saeema

2015-01-01

to investigate idea generation sessions of two industry cases. Reasoning was found to appear in sequences of alternating reasoning types where the initiating reasoning type was decisive. The study found that abductive reasoning led to more radical ideas, whereas deductive reasoning led to ideas being for project...... requirements, but having a higher proportion being rejected as not valuable. The study sheds light on the conditions that promote these reasoning types. The study is one of the first of its kind and advances an understanding of reasoning in design by empirical means and suggests a relationship between......Reasoning is at the core of design activity and thinking. Thus, understanding and explaining reasoning in design is fundamental to understand and support design practice. This paper investigates reasoning in design and its relationship to varying foci at the stage of idea generation and subsequent...

Development of Reasoning Test Instruments Based on TIMSS Framework for Measuring Reasoning Ability of Senior High School Student on the Physics Concept

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Muslim; Suhandi, A.; Nugraha, M. G.

2017-02-01

The purposes of this study are to determine the quality of reasoning test instruments that follow the framework of Trends in International Mathematics and Science Study (TIMSS) as a development results and to analyse the profile of reasoning skill of senior high school students on physics materials. This research used research and development method (R&D), furthermore the subject were 104 students at three senior high schools in Bandung selected by random sampling technique. Reasoning test instruments are constructed following the TIMSS framework in multiple choice forms in 30 questions that cover five subject matters i.e. parabolic motion and circular motion, Newton’s law of gravity, work and energy, harmonic oscillation, as well as the momentum and impulse. The quality of reasoning tests were analysed using the Content Validity Ratio (CVR) and classic test analysis include the validity of item, level of difficulty, discriminating power, reliability and Ferguson’s delta. As for the students’ reasoning skills profiles were analysed by the average score of achievements on eight aspects of the reasoning TIMSS framework. The results showed that reasoning test have a good quality as instruments to measure reasoning skills of senior high school students on five matters physics which developed and able to explore the reasoning of students on all aspects of reasoning based on TIMSS framework.

Implementing accountability for reasonableness--the case of pharmaceutical reimbursement in Sweden.

Science.gov (United States)

Jansson, Sandra

2007-04-01

This paper aims to describe the priority-setting procedure for new original pharmaceuticals practiced by the Swedish Pharmaceutical Benefits Board (LFN), to analyse the outcome of the procedure in terms of decisions and the relative importance of ethical principles, and to examine the reactions of stakeholders. All the 'principally important' decisions made by the LFN during its first 33 months of operation were analysed. The study is theoretically anchored in the theory of fair and legitimate priority-setting procedures by Daniels and Sabin, and is based on public documents, media articles, and semi-structured interviews. Only nine cases resulted in a rejection of a subsidy by the LFN and 15 in a limited or conditional subsidy. Total rejections rather than limitations gave rise to actions by stakeholders. Primarily, the principle of cost-effectiveness was used when limiting/conditioning or totally rejecting a subsidy. This study suggests that implementing a priority-setting process that fulfils the conditions of accountability for reasonableness can result in a priority-setting process which is generally perceived as fair and legitimate by the major stakeholders and may increase social learning in terms of accepting the necessity of priority setting in health care. The principle of cost-effectiveness increased in importance when the demand for openness and transparency increased.

Synthesis Reasoning and Its Application in Chinese Calligraphy Generation

Institute of Scientific and Technical Information of China (English)

XUSong-Hua; PANYun-He; ZHUANGYue-Ting; FRANCISC.M.Lau

2005-01-01

In this paper, we address the demanding task of developing intelligent systems equipped with machine creativity that can perform design tasks automatically. The main challenge is how to model human beings' creativity mathematically and mimic such creativity computationally. We propose a “synthesis reasoning model” as the underlying mechanism to simulate human beings’ creative thinking when they are handling design tasks. We present the theory of the synthesis reasoning model, and the detailed procedure of designing an intelligent system based on the model.We offer a case study of an intelligent Chinese calligraphy generation system which we have developed.Based on implementation experiences of the calligraphy generation system as well as a few other systems for solving real-world problems, we suggest a generic methodology for constructing intelligent systems using the synthesis reasoning model.

Assessing model-based reasoning using evidence-centered design a suite of research-based design patterns

CERN Document Server

Mislevy, Robert J; Riconscente, Michelle; Wise Rutstein, Daisy; Ziker, Cindy

2017-01-01

This Springer Brief provides theory, practical guidance, and support tools to help designers create complex, valid assessment tasks for hard-to-measure, yet crucial, science education standards. Understanding, exploring, and interacting with the world through models characterizes science in all its branches and at all levels of education. Model-based reasoning is central to science education and thus science assessment. Current interest in developing and using models has increased with the release of the Next Generation Science Standards, which identified this as one of the eight practices of science and engineering. However, the interactive, complex, and often technology-based tasks that are needed to assess model-based reasoning in its fullest forms are difficult to develop. Building on research in assessment, science education, and learning science, this Brief describes a suite of design patterns that can help assessment designers, researchers, and teachers create tasks for assessing aspects of model-based...

Reasons for receiving or not receiving HPV vaccination in primary schoolgirls in Tanzania: a case control study.

Directory of Open Access Journals (Sweden)

Deborah Watson-Jones

Full Text Available There are few data on factors influencing human papillomavirus (HPV vaccination uptake in sub-Saharan Africa. We examined the characteristics of receivers and non-receivers of HPV vaccination in Tanzania and identified reasons for not receiving the vaccine.We conducted a case control study of HPV vaccine receivers and non-receivers within a phase IV cluster-randomised trial of HPV vaccination in 134 primary schools in Tanzania. Girls who failed to receive vaccine (pupil cases and their parents/guardians (adult cases and girls who received dose 1 (pupil controls of the quadrivalent vaccine (Gardasil™ and their parents/guardians (adult controls were enrolled from 39 schools in a 1∶1 ratio and interviewed about cervical cancer, HPV vaccine knowledge and reasons why they might have received or not received the vaccine. Conditional logistic regression was used to determine factors independently associated with not receiving HPV vaccine.We interviewed 159 pupil/adult cases and 245 pupil/adult controls. Adult-factors independently associated with a daughter being a case were older age, owning fewer household items, not attending a school meeting about HPV vaccine, and not knowing anyone with cancer. Pupil-factors for being a case included having a non-positive opinion about the school de-worming programme, poor knowledge about the location of the cervix, and not knowing that a vaccine could prevent cervical cancer. Reasons for actively refusing vaccination included concerns about side effects and infertility. Most adult and pupil cases reported that they would accept the HPV vaccine if it were offered again (97% and 93% respectively.Sensitisation messages, especially targeted at older and poorer parents, knowledge retention and parent meetings are critical for vaccine acceptance in Tanzania. Vaccine side effects and fertility concerns should be addressed prior to a national vaccination program. Parents and pupils who initially decline vaccination

Probabilistic reasoning for assembly-based 3D modeling

KAUST Repository

Chaudhuri, Siddhartha

2011-01-01

Assembly-based modeling is a promising approach to broadening the accessibility of 3D modeling. In assembly-based modeling, new models are assembled from shape components extracted from a database. A key challenge in assembly-based modeling is the identification of relevant components to be presented to the user. In this paper, we introduce a probabilistic reasoning approach to this problem. Given a repository of shapes, our approach learns a probabilistic graphical model that encodes semantic and geometric relationships among shape components. The probabilistic model is used to present components that are semantically and stylistically compatible with the 3D model that is being assembled. Our experiments indicate that the probabilistic model increases the relevance of presented components. © 2011 ACM.

iCBLS: An interactive case-based learning system for medical education.

Science.gov (United States)

Ali, Maqbool; Han, Soyeon Caren; Bilal, Hafiz Syed Muhammad; Lee, Sungyoung; Kang, Matthew Jee Yun; Kang, Byeong Ho; Razzaq, Muhammad Asif; Amin, Muhammad Bilal

2018-01-01

Medical students should be able to actively apply clinical reasoning skills to further their interpretative, diagnostic, and treatment skills in a non-obtrusive and scalable way. Case-Based Learning (CBL) approach has been receiving attention in medical education as it is a student-centered teaching methodology that exposes students to real-world scenarios that need to be solved using their reasoning skills and existing theoretical knowledge. In this paper, we propose an interactive CBL System, called iCBLS, which supports the development of collaborative clinical reasoning skills for medical students in an online environment. The iCBLS consists of three modules: (i) system administration (SA), (ii) clinical case creation (CCC) with an innovative semi-automatic approach, and (iii) case formulation (CF) through intervention of medical students' and teachers' knowledge. Two evaluations under the umbrella of the context/input/process/product (CIPP) model have been performed with a Glycemia study. The first focused on the system satisfaction, evaluated by 54 students. The latter aimed to evaluate the system effectiveness, simulated by 155 students. The results show a high success rate of 70% for students' interaction, 76.4% for group learning, 72.8% for solo learning, and 74.6% for improved clinical skills. Copyright © 2017 Elsevier B.V. All rights reserved.

Case-Based Multi-Sensor Intrusion Detection

Science.gov (United States)

Schwartz, Daniel G.; Long, Jidong

2009-08-01

Multi-sensor intrusion detection systems (IDSs) combine the alerts raised by individual IDSs and possibly other kinds of devices such as firewalls and antivirus software. A critical issue in building a multi-sensor IDS is alert-correlation, i.e., determining which alerts are caused by the same attack. This paper explores a novel approach to alert correlation using case-based reasoning (CBR). Each case in the CBR system's library contains a pattern of alerts raised by some known attack type, together with the identity of the attack. Then during run time, the alert streams gleaned from the sensors are compared with the patterns in the cases, and a match indicates that the attack described by that case has occurred. For this purpose the design of a fast and accurate matching algorithm is imperative. Two such algorithms were explored: (i) the well-known Hungarian algorithm, and (ii) an order-preserving matching of our own device. Tests were conducted using the DARPA Grand Challenge Problem attack simulator. These showed that the both matching algorithms are effective in detecting attacks; but the Hungarian algorithm is inefficient; whereas the order-preserving one is very efficient, in fact runs in linear time.

Using a Recommendation System to Support Problem Solving and Case-Based Reasoning Retrieval

Science.gov (United States)

Tawfik, Andrew A.; Alhoori, Hamed; Keene, Charles Wayne; Bailey, Christian; Hogan, Maureen

2018-01-01

In case library learning environments, learners are presented with an array of narratives that can be used to guide their problem solving. However, according to theorists, learners struggle to identify and retrieve the optimal case to solve a new problem. Given the challenges novice face during case retrieval, recommender systems can be embedded…

INTERNET BANKING ACCEPTANCE IN MALAYSIA BASED ON THE THEORY OF REASONED ACTION

Directory of Open Access Journals (Sweden)

J Michael Pearson

2008-09-01

Full Text Available ABSTRACT The theory of reasoned action originally introduced in the field of Social Psychology has been widely used to explain individuals’ behaviour. The theory postulates that individuals’ behaviour is influenced by their attitude and subjective norm. The purpose of this study was to determine factors that influence an individual’s intention to use a technology based on the theory of reasoned action. We used Internet banking as the target technology and Malaysian subjects as the sampling frame. A principal component analysis was used to validate the constructs and multiple regressions were used to analyze the data. As expected, the results supported the theory’s proposition as that an individuals’ behavioural intention to use Internet banking is influenced by their attitude and subjective norm. Based on the findings, theoretical and practical implications were offered. Keywords: theory of reasoned action, Internet banking, technology acceptance

Archivists Killed for Political Reasons

NARCIS (Netherlands)

de Baets, Antoon

2015-01-01

This essay, Archivists Killed for Political Reasons, offers an overview of archivists who were killed for political reasons through the ages. After determining the criteria for inclusion, sixteen such political murders of archivists are briefly discussed. These cases were distributed over six

Generic project definitions for improvement of health care delivery: A case-base approach

NARCIS (Netherlands)

Niemeijer, G.C.; Does, R.J.M.M.; de Mast, J.; Trip, A.; van den Heuvel, J.

2011-01-01

Background: The purpose of this article is to create actionable knowledge, making the definition of process improvement projects in health care delivery more effective. Methods: This study is a retrospective analysis of process improvement projects in hospitals, facilitating a case-based reasoning

Formalization and Analysis of Reasoning by Assumption

NARCIS (Netherlands)

Bosse, T.; Jonker, C.M.; Treur, J.

2006-01-01

This article introduces a novel approach for the analysis of the dynamics of reasoning processes and explores its applicability for the reasoning pattern called reasoning by assumption. More specifically, for a case study in the domain of a Master Mind game, it is shown how empirical human reasoning

Esophageal cancer prediction based on qualitative features using adaptive fuzzy reasoning method

Directory of Open Access Journals (Sweden)

Raed I. Hamed

2015-04-01

Full Text Available Esophageal cancer is one of the most common cancers world-wide and also the most common cause of cancer death. In this paper, we present an adaptive fuzzy reasoning algorithm for rule-based systems using fuzzy Petri nets (FPNs, where the fuzzy production rules are represented by FPN. We developed an adaptive fuzzy Petri net (AFPN reasoning algorithm as a prognostic system to predict the outcome for esophageal cancer based on the serum concentrations of C-reactive protein and albumin as a set of input variables. The system can perform fuzzy reasoning automatically to evaluate the degree of truth of the proposition representing the risk degree value with a weight value to be optimally tuned based on the observed data. In addition, the implementation process for esophageal cancer prediction is fuzzily deducted by the AFPN algorithm. Performance of the composite model is evaluated through a set of experiments. Simulations and experimental results demonstrate the effectiveness and performance of the proposed algorithms. A comparison of the predictive performance of AFPN models with other methods and the analysis of the curve showed the same results with an intuitive behavior of AFPN models.

The nature of the scientific evidence leading to drug withdrawals for pharmacovigilance reasons in France.

Science.gov (United States)

Olivier, Pascale; Montastruc, Jean-Louis

2006-11-01

Because of design, objectives and number of included subjects, clinical studies are insufficient to assess the safety of new drugs. Sometimes, serious adverse drug reactions (ADRs) led to withdrawal of the drug from the market after their approval. The objective of our study was to determine the scientific evidences leading to drug withdrawal for pharmacovigilance reasons in France. Data coming from French Health Products Safety Agency, literature and Toulouse Pharmacovigilance Center allowed to identify all drugs withdrawn from the French market for pharmacovigilance reasons from 1998 to 2004. We classified data according to their study design (Randomized Clinical Trial [RCT], case serie or case report, case-control study, cohort study, observational study, animal study), the organ/system affected and the type of ADR. A total of 21 drugs were withdrawn for safety reasons between 1998 and 2004 in France. The most frequent ADRs were hepatic (n = 7), cardiovascular (n = 4) or neurological (n = 3) ones. Eleven withdrawals were due to type-B ('unexpected') reactions (52%). For 19 out of 21 drugs, scientific evidence leading to drug withdrawal came from spontaneous case reports (or case series). Among these, case reports were the sole evidence in 12 cases. Withdrawals were based on evidence from case reports in combination with case-control or cohort study in four cases, in combination with observational study in two cases or in combination with animal study in two other cases. In only one case, a RCT supported the decision. This study underlines the importance of spontaneous case reports in detecting signals and supporting withdrawal of drug for pharmacovigilance reasons in France. Health authorities suffer from lack of comparative data resource. In this perspective, a pharmaco-epidemiological population-based database could represent a helpful tool to both generate and test safety hypotheses.

Unified modeling language and design of a case-based retrieval system in medical imaging.

Science.gov (United States)

LeBozec, C; Jaulent, M C; Zapletal, E; Degoulet, P

1998-01-01

One goal of artificial intelligence research into case-based reasoning (CBR) systems is to develop approaches for designing useful and practical interactive case-based environments. Explaining each step of the design of the case-base and of the retrieval process is critical for the application of case-based systems to the real world. We describe herein our approach to the design of IDEM--Images and Diagnosis from Examples in Medicine--a medical image case-based retrieval system for pathologists. Our approach is based on the expressiveness of an object-oriented modeling language standard: the Unified Modeling Language (UML). We created a set of diagrams in UML notation illustrating the steps of the CBR methodology we used. The key aspect of this approach was selecting the relevant objects of the system according to user requirements and making visualization of cases and of the components of the case retrieval process. Further evaluation of the expressiveness of the design document is required but UML seems to be a promising formalism, improving the communication between the developers and users.

A ligand predication tool based on modeling and reasoning with imprecise probabilistic knowledge.

Science.gov (United States)

Liu, Weiru; Yue, Anbu; Timson, David J

2010-04-01

Ligand prediction has been driven by a fundamental desire to understand more about how biomolecules recognize their ligands and by the commercial imperative to develop new drugs. Most of the current available software systems are very complex and time-consuming to use. Therefore, developing simple and efficient tools to perform initial screening of interesting compounds is an appealing idea. In this paper, we introduce our tool for very rapid screening for likely ligands (either substrates or inhibitors) based on reasoning with imprecise probabilistic knowledge elicited from past experiments. Probabilistic knowledge is input to the system via a user-friendly interface showing a base compound structure. A prediction of whether a particular compound is a substrate is queried against the acquired probabilistic knowledge base and a probability is returned as an indication of the prediction. This tool will be particularly useful in situations where a number of similar compounds have been screened experimentally, but information is not available for all possible members of that group of compounds. We use two case studies to demonstrate how to use the tool. 2009 Elsevier Ireland Ltd. All rights reserved.

Historical reasoning: towards a framework for analyzing students' reasoning about the past

NARCIS (Netherlands)

van Drie, J.; van Boxtel, C.

2008-01-01

This article explores historical reasoning, an important activity in history learning. Based upon an extensive review of empirical literature on students’ thinking and reasoning about history, a theoretical framework of historical reasoning is proposed. The framework consists of six components:

Artificial intelligence approach to legal reasoning

International Nuclear Information System (INIS)

Gardner, A.V.D.L.

1984-01-01

For artificial intelligence, understanding the forms of human reasoning is a central goal. Legal reasoning is a form that makes a new set of demands on artificial intelligence methods. Most importantly, a computer program that reasons about legal problems must be able to distinguish between questions it is competent to answer and questions that human lawyers could seriously argue either way. In addition, a program for analyzing legal problems should be able to use both general legal rules and decisions in past cases; and it should be able to work with technical concepts that are only partly defined and subject to shifts of meaning. Each of these requirements has wider applications in artificial intelligence, beyond the legal domain. This dissertation presents a computational framework for legal reasoning, within which such requirements can be accommodated. The development of the framework draws significantly on the philosophy of law, in which the elucidation of legal reasoning is an important topic. A key element of the framework is the legal distinction between hard cases and clear cases. In legal writing, this distinction has been taken for granted more often than it has been explored. Here, some initial heuristics are proposed by which a program might make the distinction

A Quantitative Reasoning Approach to Algebra Using Inquiry-Based Learning

Directory of Open Access Journals (Sweden)

Victor I. Piercey

2017-07-01

Full Text Available In this paper, I share a hybrid quantitative reasoning/algebra two-course sequence that challenges the common assumption that quantitative literacy and reasoning are less rigorous mathematics alternatives to algebra and illustrates that a quantitative reasoning framework can be used to teach traditional algebra. The presentation is made in two parts. In the first part, which is somewhat philosophical and theoretical, I explain my personal perspective of what I mean by “algebra” and “doing algebra.” I contend that algebra is a form of communication whose value is precision, which allows us to perform algebraic manipulations in the form of simplification and solving moves. A quantitative reasoning approach to traditional algebraic manipulations rests on intentional and purposeful use of simplification and solving moves within contextual situations. In part 2, I describe a 6-week instructional module intended for undergraduate business students that was delivered to students who had placed into beginning algebra. The perspective described in part 1 heavily informed the design of this module. The course materials, which involve the use of Excel in multiple authentic contexts, are built around the use of inquiry-based learning. Upon completion of this module, the percentage of students who successfully complete model problems in an assessment is in the same range as surveyed students in precalculus and calculus, approximately two “grade levels” ahead of their placement.

Student use of model-based reasoning when troubleshooting an electronic circuit

Science.gov (United States)

Lewandowski, Heather; Stetzer, Mackenzie; van de Bogart, Kevin; Dounas-Frazer, Dimitri

2016-03-01

Troubleshooting systems is an integral part of experimental physics in both research and educational settings. Accordingly, ability to troubleshoot is an important learning goal for undergraduate physics lab courses. We investigate students' model-based reasoning on a troubleshooting task using data collected in think-aloud interviews during which pairs of students from two institutions attempted to diagnose and repair a malfunctioning circuit. Our analysis scheme was informed by the Experimental Modeling Framework, which describes physicists' use of mathematical and conceptual models when reasoning about experimental systems. We show that system and subsystem models were crucial for the evaluation of repairs to the circuit and played an important role in some troubleshooting strategies. Finally, drawing on data from interviews with electronics instructors from a broad range of institution types, we outline recommendations for model-based approaches to teaching and learning troubleshooting skills.

Student use of model-based reasoning when troubleshooting an electric circuit

Science.gov (United States)

Dounas-Frazer, Dimitri

2016-05-01

Troubleshooting systems is an integral part of experimental physics in both research and educational settings. Accordingly, ability to troubleshoot is an important learning goal for undergraduate physics lab courses. We investigate students' model-based reasoning on a troubleshooting task using data collected in think-aloud interviews during which pairs of students from two institutions attempted to diagnose and repair a malfunctioning circuit. Our analysis scheme was informed by the Experimental Modeling Framework, which describes physicists' use of mathematical and conceptual models when reasoning about experimental systems. We show that system and subsystem models were crucial for the evaluation of repairs to the circuit and played an important role in some troubleshooting strategies. Finally, drawing on data from interviews with electronics instructors from a broad range of institution types, we outline recommendations for model-based approaches to teaching and learning troubleshooting skills.

OGC Geographic Information Service Deductive Semantic Reasoning Based on Description Vocabularies Reduction

Directory of Open Access Journals (Sweden)

MIAO Lizhi

2015-09-01

Full Text Available As geographic information interoperability and sharing developing, more and more interoperable OGC (open geospatial consortium Web services (OWS are generated and published through the internet. These services can facilitate the integration of different scientific applications by searching, finding, and utilizing the large number of scientific data and Web services. However, these services are widely dispersed and hard to be found and utilized with executive semantic retrieval. This is especially true when considering the weak semantic description of geographic information service data. Focusing on semantic retrieval and reasoning of the distributed OWS resources, a deductive and semantic reasoning method is proposed to describe and search relevant OWS resources. Specifically, ①description words are extracted from OWS metadata file to generate GISe ontology-database and instance-database based on geographic ontology according to basic geographic elements category, ②a description words reduction model is put forward to implement knowledge reduction on GISe instance-database based on rough set theory and generate optimized instances database, ③utilizing GISe ontology-database and optimized instance-database to implement semantic inference and reasoning of geographic searching objects is used as an example to demonstrate the efficiency, feasibility and recall ration of the proposed description-word-based reduction model.

A Web-Based Rice Plant Expert System Using Rule-Based Reasoning

Directory of Open Access Journals (Sweden)

Anton Setiawan Honggowibowo

2009-12-01

Full Text Available Rice plants can be attacked by various kinds of diseases which are possible to be determined from their symptoms. However, it is to recognize that to find out the exact type of disease, an agricultural expert’s opinion is needed, meanwhile the numbers of agricultural experts are limited and there are too many problems to be solved at the same time. This makes a system with a capability as an expert is required. This system must contain the knowledge of the diseases and symptom of rice plants as an agricultural expert has to have. This research designs a web-based expert system using rule-based reasoning. The rule are modified from the method of forward chaining inference and backward chaining in order to to help farmers in the rice plant disease diagnosis. The web-based rice plants disease diagnosis expert system has the advantages to access and use easily. With web-based features inside, it is expected that the farmer can accesse the expert system everywhere to overcome the problem to diagnose rice diseases.

[Three good reasons to perform a postmortem examination in all cases of juvenile sudden death].

Science.gov (United States)

d'Amati, Giulia; di Gioia, Cira R T; Silenzi, Paola F; Gallo, Pietro

2009-04-01

The aim of this review is to underline the reasons why a post-mortem examination has to be performed in all cases of juvenile sudden death. Sudden death in children and young adults can be caused by potentially heritable cardiovascular disorders and fatal outcome is often the first symptom in apparently healthy subjects. In these cases, a careful autopsy, performed according to a standardized protocol, becomes the sole diagnostic tool to guide clinical and molecular genetic family screening and to adopt the proper therapeutic and preventive strategies. Thus, a post-mortem examination is a fundamental part of a multidisciplinary approach to the issue of juvenile sudden death.

A cloud-based multimodality case file for mobile devices.

Science.gov (United States)

Balkman, Jason D; Loehfelm, Thomas W

2014-01-01

Recent improvements in Web and mobile technology, along with the widespread use of handheld devices in radiology education, provide unique opportunities for creating scalable, universally accessible, portable image-rich radiology case files. A cloud database and a Web-based application for radiologic images were developed to create a mobile case file with reasonable usability, download performance, and image quality for teaching purposes. A total of 75 radiology cases related to breast, thoracic, gastrointestinal, musculoskeletal, and neuroimaging subspecialties were included in the database. Breast imaging cases are the focus of this article, as they best demonstrate handheld display capabilities across a wide variety of modalities. This case subset also illustrates methods for adapting radiologic content to cloud platforms and mobile devices. Readers will gain practical knowledge about storage and retrieval of cloud-based imaging data, an awareness of techniques used to adapt scrollable and high-resolution imaging content for the Web, and an appreciation for optimizing images for handheld devices. The evaluation of this software demonstrates the feasibility of adapting images from most imaging modalities to mobile devices, even in cases of full-field digital mammograms, where high resolution is required to represent subtle pathologic features. The cloud platform allows cases to be added and modified in real time by using only a standard Web browser with no application-specific software. Challenges remain in developing efficient ways to generate, modify, and upload radiologic and supplementary teaching content to this cloud-based platform. Online supplemental material is available for this article. ©RSNA, 2014.

Security Situation Assessment of All-Optical Network Based on Evidential Reasoning Rule

Directory of Open Access Journals (Sweden)

Zhong-Nan Zhao

2016-01-01

Full Text Available It is important to determine the security situations of the all-optical network (AON, which is more vulnerable to hacker attacks and faults than other networks in some cases. A new approach of the security situation assessment to the all-optical network is developed in this paper. In the new assessment approach, the evidential reasoning (ER rule is used to integrate various evidences of the security factors including the optical faults and the special attacks in the AON. Furthermore, a new quantification method of the security situation is also proposed. A case study of an all-optical network is conducted to demonstrate the effectiveness and the practicability of the new proposed approach.

Formalization and Analysis of Reasoning by Assumption

OpenAIRE

Bosse, T.; Jonker, C.M.; Treur, J.

2006-01-01

This article introduces a novel approach for the analysis of the dynamics of reasoning processes and explores its applicability for the reasoning pattern called reasoning by assumption. More specifically, for a case study in the domain of a Master Mind game, it is shown how empirical human reasoning traces can be formalized and automatically analyzed against dynamic properties they fulfill. To this end, for the pattern of reasoning by assumption a variety of dynamic properties have been speci...

An Argumentation-Based Approach to Normative Practical Reasoning

OpenAIRE

Shams, Zohreh

2015-01-01

Autonomous agents operating in a dynamic environment must be able to reason about their actions in pursuit of their goals. An additional consideration for such agents is that their actions may be constrained by norms that aim at defining an acceptable behaviour for the agents. The inclusion of normative reasoning into practical reasoning is derived from the necessity for effective mechanisms that regulate an agent’s behaviour in an open environment without compromising their autonomy. However...

Part-whole reasoning in medical ontologies revisited--introducing SEP triplets into classification-based description logics.

Science.gov (United States)

Schulz, S; Romacker, M; Hahn, U

1998-01-01

The development of powerful and comprehensive medical ontologies that support formal reasoning on a large scale is one of the key requirements for clinical computing in the next millennium. Taxonomic medical knowledge, a major portion of these ontologies, is mainly characterized by generalization and part-whole relations between concepts. While reasoning in generalization hierarchies is quite well understood, no fully conclusive mechanism as yet exists for part-whole reasoning. The approach we take emulates part-whole reasoning via classification-based reasoning using SEP triplets, a special data structure for encoding part-whole relations that is fully embedded in the formal framework of standard description logics.

All Roads Lead to Fault Diagnosis : Model-Based Reasoning with LYDIA

NARCIS (Netherlands)

Feldman, A.B.; Pietersma, J.; Van Gemund, A.J.C.

2006-01-01

Model-Based Reasoning (MBR) over qualitative models of complex, real-world systems has proven succesful for automated fault diagnosis, control, and repair. Expressing a system under diagnosis in a formal model and infering a diagnosis given observations are both challenging problems. In this paper

Semantics-based plausible reasoning to extend the knowledge coverage of medical knowledge bases for improved clinical decision support

OpenAIRE

Mohammadhassanzadeh, Hossein; Van Woensel, William; Abidi, Samina Raza; Abidi, Syed Sibte Raza

2017-01-01

Background Capturing complete medical knowledge is challenging-often due to incomplete patient Electronic Health Records (EHR), but also because of valuable, tacit medical knowledge hidden away in physicians? experiences. To extend the coverage of incomplete medical knowledge-based systems beyond their deductive closure, and thus enhance their decision-support capabilities, we argue that innovative, multi-strategy reasoning approaches should be applied. In particular, plausible reasoning mech...

EFFECTIVENESS OF PROBLEM BASED LEARNING AS A STRATEGY TO FOSTER PROBLEM SOLVING AND CRITICAL REASONING SKILLS AMONG MEDICAL STUDENTS.

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Asad, Munazza; Iqbal, Khadija; Sabir, Mohammad

2015-01-01

Problem based learning (PBL) is an instructional approach that utilizes problems or cases as a context for students to acquire problem solving skills. It promotes communication skills, active learning, and critical thinking skills. It encourages peer teaching and active participation in a group. It was a cross-sectional study conducted at Al Nafees Medical College, Isra University, Islamabad, in one month duration. This study was conducted on 193 students of both 1st and 2nd year MBBS. Each PBL consists of three sessions, spaced by 2-3 days. In the first session students were provided a PBL case developed by both basic and clinical science faculty. In Session 2 (group discussion), they share, integrate their knowledge with the group and Wrap up (third session), was concluded at the end. A questionnaire based survey was conducted to find out overall effectiveness of PBL sessions. Teaching through PBLs greatly improved the problem solving and critical reasoning skills with 60% students of first year and 71% of 2nd year agreeing that the acquisition of knowledge and its application in solving multiple choice questions (MCQs) was greatly improved by these sessions. They observed that their self-directed learning, intrinsic motivation and skills to relate basic concepts with clinical reasoning which involves higher order thinking have greatly enhanced. Students found PBLs as an effective strategy to promote teamwork and critical thinking skills. PBL is an effective method to improve critical thinking and problem solving skills among medical students.

Computer aided fixture design - A case based approach

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Tanji, Shekhar; Raiker, Saiesh; Mathew, Arun Tom

2017-11-01

Automated fixture design plays important role in process planning and integration of CAD and CAM. An automated fixture setup design system is developed where when fixturing surfaces and points are described allowing modular fixture components to get automatically select for generating fixture units and placed into position with satisfying assembled conditions. In past, various knowledge based system have been developed to implement CAFD in practice. In this paper, to obtain an acceptable automated machining fixture design, a case-based reasoning method with developed retrieval system is proposed. Visual Basic (VB) programming language is used in integrating with SolidWorks API (Application programming interface) module for better retrieval procedure reducing computational time. These properties are incorporated in numerical simulation to determine the best fit for practical use.

Modal Change Logic (MCL) : Specifying the reasoning of knowledge-based systems

NARCIS (Netherlands)

Fensel, D; Groenboom, H.M; Renardel de Lavalette, G.R.

We investigate the formal specification of the reasoning process of knowledge-based systems in this paper. We analyze the corresponding parts of the KADS specification languages KARL and (ML)(2) and deduce some general requirements. The essence of these languages is that they integrate a declarative

Disgust- and anxiety-based emotional reasoning in non-clinical fear of vomiting.

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Verwoerd, Johan; van Hout, Wiljo J P J; de Jong, Peter J

2016-03-01

Emotional reasoning has been described as a dysfunctional tendency to use subjective responses to make erroneous inferences about threatening outcomes in objectively safe situations (e.g., "If I feel anxious/disgusted, there must be danger/risk of becoming ill"). Prior studies found evidence for anxiety-based emotional reasoning (ER) in several anxiety disorders as well as disgust-based ER in healthy individuals scoring above the clinical cut-off on a measure of contamination fear. The current study tested whether disgust- and anxiety-based ER might be involved in fear of vomiting, a phobic disorder in which both fear/anxiety and disgust are assumed to play an important role. Non-clinical participants scoring high (>75%; n = 35) and low (emotions revealed that more pronounced ER in the high vomit fearful group was mainly driven by the emotion of disgust. Current study asked participants to imagine experienced emotions in scenarios instead of experimentally inducing real-life emotions. These findings are consistent with the view that disgust-based ER is involved in fear of vomiting. Copyright © 2015 Elsevier Ltd. All rights reserved.

Logical reasoning versus information processing in the dual-strategy model of reasoning.

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Markovits, Henry; Brisson, Janie; de Chantal, Pier-Luc

2017-01-01

One of the major debates concerning the nature of inferential reasoning is between counterexample-based strategies such as mental model theory and statistical strategies underlying probabilistic models. The dual-strategy model, proposed by Verschueren, Schaeken, & d'Ydewalle (2005a, 2005b), which suggests that people might have access to both kinds of strategy has been supported by several recent studies. These have shown that statistical reasoners make inferences based on using information about premises in order to generate a likelihood estimate of conclusion probability. However, while results concerning counterexample reasoners are consistent with a counterexample detection model, these results could equally be interpreted as indicating a greater sensitivity to logical form. In order to distinguish these 2 interpretations, in Studies 1 and 2, we presented reasoners with Modus ponens (MP) inferences with statistical information about premise strength and in Studies 3 and 4, naturalistic MP inferences with premises having many disabling conditions. Statistical reasoners accepted the MP inference more often than counterexample reasoners in Studies 1 and 2, while the opposite pattern was observed in Studies 3 and 4. Results show that these strategies must be defined in terms of information processing, with no clear relations to "logical" reasoning. These results have additional implications for the underlying debate about the nature of human reasoning. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Meta-Reasoning: Monitoring and Control of Thinking and Reasoning.

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Ackerman, Rakefet; Thompson, Valerie A

2017-08-01

Meta-Reasoning refers to the processes that monitor the progress of our reasoning and problem-solving activities and regulate the time and effort devoted to them. Monitoring processes are usually experienced as feelings of certainty or uncertainty about how well a process has, or will, unfold. These feelings are based on heuristic cues, which are not necessarily reliable. Nevertheless, we rely on these feelings of (un)certainty to regulate our mental effort. Most metacognitive research has focused on memorization and knowledge retrieval, with little attention paid to more complex processes, such as reasoning and problem solving. In that context, we recently developed a Meta-Reasoning framework, used here to review existing findings, consider their consequences, and frame questions for future research. Copyright © 2017 Elsevier Ltd. All rights reserved.

Problem Solving Reasoning and Problem Based Instruction in Geometry Learning

Science.gov (United States)

Sulistyowati, F.; Budiyono, B.; Slamet, I.

2017-09-01

This research aims to analyze the comparison Problem Solving Reasoning (PSR) and Problem Based Instruction (PBI) on problem solving and mathematical communication abilities viewed from Self-Regulated Learning (SRL). Learning was given to grade 8th junior high school students. This research uses quasi experimental method, and then with descriptive analysis. Data were analyzed using two-ways multivariate analysis of variance (MANOVA) and one-way analysis of variance (ANOVA) with different cells. The result of data analysis were learning model gives different effect, level of SRL gives the same effect, and there is no interaction between the learning model with the SRL on the problem solving and mathematical communication abilities. The t-test statistic was used to find out more effective learning model. Based on the test, regardless of the level of SRL, PSR is more effective than PBI for problemsolving ability. The result of descriptive analysis was PSR had the advantage in creating learning that optimizing the ability of learners in reasoning to solve a mathematical problem. Consequently, the PSR is the right learning model to be applied in the classroom to improve problem solving ability of learners.

Foundations for Reasoning in Cognition-Based Computational Representations of Human Decision Making; TOPICAL

International Nuclear Information System (INIS)

SENGLAUB, MICHAEL E.; HARRIS, DAVID L.; RAYBOURN, ELAINE M.

2001-01-01

In exploring the question of how humans reason in ambiguous situations or in the absence of complete information, we stumbled onto a body of knowledge that addresses issues beyond the original scope of our effort. We have begun to understand the importance that philosophy, in particular the work of C. S. Peirce, plays in developing models of human cognition and of information theory in general. We have a foundation that can serve as a basis for further studies in cognition and decision making. Peircean philosophy provides a foundation for understanding human reasoning and capturing behavioral characteristics of decision makers due to cultural, physiological, and psychological effects. The present paper describes this philosophical approach to understanding the underpinnings of human reasoning. We present the work of C. S. Peirce, and define sets of fundamental reasoning behavior that would be captured in the mathematical constructs of these newer technologies and would be able to interact in an agent type framework. Further, we propose the adoption of a hybrid reasoning model based on his work for future computational representations or emulations of human cognition

Model of critical diagnostic reasoning: achieving expert clinician performance.

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Harjai, Prashant Kumar; Tiwari, Ruby

2009-01-01

Diagnostic reasoning refers to the analytical processes used to determine patient health problems. While the education curriculum and health care system focus on training nurse clinicians to accurately recognize and rescue clinical situations, assessments of non-expert nurses have yielded less than satisfactory data on diagnostic competency. The contrast between the expert and non-expert nurse clinician raises the important question of how differences in thinking may contribute to a large divergence in accurate diagnostic reasoning. This article recognizes superior organization of one's knowledge base, using prototypes, and quick retrieval of pertinent information, using similarity recognition as two reasons for the expert's superior diagnostic performance. A model of critical diagnostic reasoning, using prototypes and similarity recognition, is proposed and elucidated using case studies. This model serves as a starting point toward bridging the gap between clinical data and accurate problem identification, verification, and management while providing a structure for a knowledge exchange between expert and non-expert clinicians.

How does questioning influence nursing students' clinical reasoning in problem-based learning? A scoping review.

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Merisier, Sophia; Larue, Caroline; Boyer, Louise

2018-06-01

Problem-based learning is an educational method promoting clinical reasoning that has been implemented in many fields of health education. Questioning is a learning strategy often employed in problem-based learning sessions. To explore what is known about the influence of questioning on the promotion of clinical reasoning of students in health care education, specifically in the field of nursing and using the educational method of problem-based learning. A scoping review following Arksey and O'Malley's five stages was conducted. The CINAHL, EMBASE, ERIC, Medline, and PubMed databases were searched for articles published between the years of 2000 and 2017. Each article was summarized and analyzed using a data extraction sheet in relation to its purpose, population group, setting, methods, and results. A descriptive explication of the studies based on an inductive analysis of their findings to address the aim of the review was made. Nineteen studies were included in the analysis. The studies explored the influence of questioning on critical thinking rather than on clinical reasoning. The nature of the questions asked and the effect of higher-order questions on critical thinking were the most commonly occurring themes. Few studies addressed the use of questioning in problem-based learning. More empirical evidence is needed to gain a better understanding of the benefit of questioning in problem-based learning to promote students' clinical reasoning. Copyright © 2018 Elsevier Ltd. All rights reserved.

Measuring Relational Reasoning

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Alexander, Patricia A.; Dumas, Denis; Grossnickle, Emily M.; List, Alexandra; Firetto, Carla M.

2016-01-01

Relational reasoning is the foundational cognitive ability to discern meaningful patterns within an informational stream, but its reliable and valid measurement remains problematic. In this investigation, the measurement of relational reasoning unfolded in three stages. Stage 1 entailed the establishment of a research-based conceptualization of…

Developing Computer Model-Based Assessment of Chemical Reasoning: A Feasibility Study

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Liu, Xiufeng; Waight, Noemi; Gregorius, Roberto; Smith, Erica; Park, Mihwa

2012-01-01

This paper reports a feasibility study on developing computer model-based assessments of chemical reasoning at the high school level. Computer models are flash and NetLogo environments to make simultaneously available three domains in chemistry: macroscopic, submicroscopic, and symbolic. Students interact with computer models to answer assessment…

Systematizing Scaffolding for Problem-Based Learning: A View from Case-Based Reasoning

Science.gov (United States)

Tawfik, Andrew A.; Kolodner, Janet L.

2016-01-01

Current theories and models of education often argue that instruction is best administered when knowledge is situated within a context. Problem-based learning (PBL) provides an approach to education that has particularly powerful affordances for learning disciplinary content and practices by solving authentic problems within a discipline. However,…

EMOTIONS AND REASONING IN MORAL DECISION MAKING

Directory of Open Access Journals (Sweden)

V. V. Nadurak

2016-12-01

Full Text Available Purpose of the research is the study of relationship between emotional and rational factors in moral decisions making. Methodology. The work is primarily based on the analysis and synthesis of the main empirical studies of the problem, each of which uses the methods of those sciences in which they were conducted (neurosciences. Originality. In general, the process of moral decision making cannot be described by a single simple model that would see only emotional or rational factor in foundation of this process. Moral decision making is characterized by different types of interaction between emotions and rational considerations. The influence of emotional and rational factors on moral decision is nonlinear: moral decision, which person makes, isn’t proportional to those emotions that preceded it and isn't unambiguously determined by them, because rational reasoning and contextual factors can significantly change it. Similarly, the reasoning that precede the decision is not necessarily reflected in the decision, because it can be significantly corrected by those emotions that accompany it. Conclusions. The process of moral decision making involves complex, heterogeneous interaction between emotional and rational factors. There are three main types of such interaction: first, the reasoning serves to rationalize prior emotional response; second, there are cases when reasoning precedes emotional reactions and determines it; third, interaction between these factors is characterized by cyclic causality (emotion impacts reasoning, which in turn impacts emotions. The influence of emotions or rational reasoning on moral decision is nonlinear.

Computer-Based Assessment of School Readiness and Early Reasoning

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Csapó, Beno; Molnár, Gyöngyvér; Nagy, József

2014-01-01

This study explores the potential of using online tests for the assessment of school readiness and for monitoring early reasoning. Four tests of a face-to-face-administered school readiness test battery (speech sound discrimination, relational reasoning, counting and basic numeracy, and deductive reasoning) and a paper-and-pencil inductive…

Drawing-to-Learn: A Framework for Using Drawings to Promote Model-Based Reasoning in Biology

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Quillin, Kim; Thomas, Stephen

2015-01-01

The drawing of visual representations is important for learners and scientists alike, such as the drawing of models to enable visual model-based reasoning. Yet few biology instructors recognize drawing as a teachable science process skill, as reflected by its absence in the Vision and Change report’s Modeling and Simulation core competency. Further, the diffuse research on drawing can be difficult to access, synthesize, and apply to classroom practice. We have created a framework of drawing-to-learn that defines drawing, categorizes the reasons for using drawing in the biology classroom, and outlines a number of interventions that can help instructors create an environment conducive to student drawing in general and visual model-based reasoning in particular. The suggested interventions are organized to address elements of affect, visual literacy, and visual model-based reasoning, with specific examples cited for each. Further, a Blooming tool for drawing exercises is provided, as are suggestions to help instructors address possible barriers to implementing and assessing drawing-to-learn in the classroom. Overall, the goal of the framework is to increase the visibility of drawing as a skill in biology and to promote the research and implementation of best practices. PMID:25713094

Learning clinical reasoning.

Science.gov (United States)

Pinnock, Ralph; Welch, Paul

2014-04-01

Errors in clinical reasoning continue to account for significant morbidity and mortality, despite evidence-based guidelines and improved technology. Experts in clinical reasoning often use unconscious cognitive processes that they are not aware of unless they explain how they are thinking. Understanding the intuitive and analytical thinking processes provides a guide for instruction. How knowledge is stored is critical to expertise in clinical reasoning. Curricula should be designed so that trainees store knowledge in a way that is clinically relevant. Competence in clinical reasoning is acquired by supervised practice with effective feedback. Clinicians must recognise the common errors in clinical reasoning and how to avoid them. Trainees can learn clinical reasoning effectively in everyday practice if teachers provide guidance on the cognitive processes involved in making diagnostic decisions. © 2013 The Authors. Journal of Paediatrics and Child Health © 2013 Paediatrics and Child Health Division (Royal Australasian College of Physicians).

A Framework for a Clinical Reasoning Knowledge Warehouse

DEFF Research Database (Denmark)

Vilstrup Pedersen, Klaus; Boye, Niels

2004-01-01

In many areas of the medical domain, the decision process i.e. reasoning, involving health care professionals is distributed, cooperative and complex. This paper presents a framework for a Clinical Reasoning Knowledge Warehouse that combines theories and models from Artificial Intelligence...... is stored and made accessible when relevant to the reasoning context and the specific patient case. Furthermore, the information structure supports the creation of new generalized knowledge using data mining tools. The patient case is divided into an observation level and an opinion level. At the opinion...

Integration of domain and resource-based reasoning for real-time control in dynamic environments

Science.gov (United States)

Morgan, Keith; Whitebread, Kenneth R.; Kendus, Michael; Cromarty, Andrew S.

1993-01-01

A real-time software controller that successfully integrates domain-based and resource-based control reasoning to perform task execution in a dynamically changing environment is described. The design of the controller is based on the concept of partitioning the process to be controlled into a set of tasks, each of which achieves some process goal. It is assumed that, in general, there are multiple ways (tasks) to achieve a goal. The controller dynamically determines current goals and their current criticality, choosing and scheduling tasks to achieve those goals in the time available. It incorporates rule-based goal reasoning, a TMS-based criticality propagation mechanism, and a real-time scheduler. The controller has been used to build a knowledge-based situation assessment system that formed a major component of a real-time, distributed, cooperative problem solving system built under DARPA contract. It is also being employed in other applications now in progress.

Push and pull models to manage patient consent and licensing of multimedia resources in digital repositories for case-based reasoning.

Science.gov (United States)

Kononowicz, Andrzej A; Zary, Nabil; Davies, David; Heid, Jörn; Woodham, Luke; Hege, Inga

2011-01-01

Patient consents for distribution of multimedia constitute a significant element of medical case-based repositories in medicine. A technical challenge is posed by the right of patients to withdraw permission to disseminate their images or videos. A technical mechanism for spreading information about changes in multimedia usage licenses is sought. The authors gained their experience by developing and managing a large (>340 cases) repository of virtual patients within the European project eViP. The solution for dissemination of license status should reuse and extend existing metadata standards in medical education. Two methods: PUSH and PULL are described differing in the moment of update and the division of responsibilities between parties in the learning object exchange process. The authors recommend usage of the PUSH scenario because it is better adapted to legal requirements in many countries. It needs to be stressed that the solution is based on mutual trust of the exchange partners and therefore is most appropriate for use in educational alliances and consortia. It is hoped that the proposed models for exchanging consents and licensing information will become a crucial part of the technical frameworks for building case-based repositories.

Inductive reasoning 2.0.

Science.gov (United States)

Hayes, Brett K; Heit, Evan

2018-05-01

Inductive reasoning entails using existing knowledge to make predictions about novel cases. The first part of this review summarizes key inductive phenomena and critically evaluates theories of induction. We highlight recent theoretical advances, with a special emphasis on the structured statistical approach, the importance of sampling assumptions in Bayesian models, and connectionist modeling. A number of new research directions in this field are identified including comparisons of inductive and deductive reasoning, the identification of common core processes in induction and memory tasks and induction involving category uncertainty. The implications of induction research for areas as diverse as complex decision-making and fear generalization are discussed. This article is categorized under: Psychology > Reasoning and Decision Making Psychology > Learning. © 2017 Wiley Periodicals, Inc.

Ferris Wheels and Filling Bottles: A Case of a Student's Transfer of Covariational Reasoning across Tasks with Different Backgrounds and Features

Science.gov (United States)

Johnson, Heather Lynn; McClintock, Evan; Hornbein, Peter

2017-01-01

Using an actor-oriented perspective on transfer, we report a case of a student's transfer of covariational reasoning across tasks involving different backgrounds and features. In this study, we investigated the research question: How might a student's covariational reasoning on Ferris wheel tasks, involving attributes of distance, width, and…

Analysis of BF Hearth Reasonable Cooling System Based on the Water Dynamic Characteristics

Science.gov (United States)

Zuo, Haibin; Jiao, Kexin; Zhang, Jianliang; Li, Qian; Wang, Cui

A rational cooling water system is the assurance for long campaign life of blast furnace. In the paper, the heat transfer of different furnace period and different furnace condition based on the water quality characteristics were analysed, and the reason of the heat flux over the normal from the hydrodynamics was analysed. The results showed that, the vapour-film and scale existence significantly influenced the hearth heat transfer, which accelerated the brick lining erosion. The water dynamic characteristics of the parallel inner pipe or among the pipes were the main reason for the abnormal heat flux and film boiling. As to the reasonable cooling water flow, the gas film and the scale should be controlled and the energy saving should be considered.

The reasonable woman standard: effects on sexual harassment court decisions.

Science.gov (United States)

Perry, Elissa L; Kulik, Carol T; Bourhis, Anne C

2004-02-01

Some federal courts have used a reasonable woman standard rather than the traditional reasonable man or reasonable person standard to determine whether hostile environment sexual harassment has occurred. The current research examined the impact of the reasonable woman standard on federal district court decisions, controlling for other factors found to affect sexual harassment court decisions. Results indicated that there was a weak relationship between whether a case followed a reasonable woman precedent-setting case and the likelihood that the court decision favored the plaintiff. The implications of our findings for individuals and organizations involved in sexual harassment claims are discussed.

Symbolic Processing Combined with Model-Based Reasoning

Science.gov (United States)

James, Mark

2009-01-01

A computer program for the detection of present and prediction of future discrete states of a complex, real-time engineering system utilizes a combination of symbolic processing and numerical model-based reasoning. One of the biggest weaknesses of a purely symbolic approach is that it enables prediction of only future discrete states while missing all unmodeled states or leading to incorrect identification of an unmodeled state as a modeled one. A purely numerical approach is based on a combination of statistical methods and mathematical models of the applicable physics and necessitates development of a complete model to the level of fidelity required for prediction. In addition, a purely numerical approach does not afford the ability to qualify its results without some form of symbolic processing. The present software implements numerical algorithms to detect unmodeled events and symbolic algorithms to predict expected behavior, correlate the expected behavior with the unmodeled events, and interpret the results in order to predict future discrete states. The approach embodied in this software differs from that of the BEAM methodology (aspects of which have been discussed in several prior NASA Tech Briefs articles), which provides for prediction of future measurements in the continuous-data domain.

Selfregulation – the key to progress in clinical reasoning

Directory of Open Access Journals (Sweden)

T Postma

2015-12-01

Full Text Available Background. In 2009 a new case-based instructional design was implemented during the preclinical year of study of the undergraduate dental curriculum of the University of Pretoria, South Africa. The objective of the educational intervention was to improve the development of clinical reasoning skills. To achieve this, systematic scaffolding, relevance, integration and problem-solving were actively promoted as part of teaching and learning. A student’s clinical reasoning was measured by a progress test containing 32 multiple choice questions (MCQs, formulated on a knowledge application level. In 2011 it became clear that some students showed progression while others did not. Objectives. This study was conducted to gauge the value of the case-based intervention with the aim of determining the need for further scaffolding and support, especially for non-progressing students. Methods. The 2011 BChD IV cohort (N=48 was identified for the study. Two semi-structured focus group discussions were conducted. Group 1 (n=8 consisted of students who progressed ≥9%, while group 2 (n=8 comprised students who did not progress to the same extent. Results. Both groups lauded the scaffolding that the case-based curriculum provided. Strategic thinking, goal orientation and self-regulation ability were identified in group 1. A lack of diligence, poor data-processing ability and a possible lack of interest were identified in group 2 students, who were unaware of learning opportunities. Conclusion. There is a need for early identification of students lacking self-regulated learning and for providing timely feedback and support to progressively develop their clinical reasoning skills.

Theory-based Bayesian models of inductive learning and reasoning.

Science.gov (United States)

Tenenbaum, Joshua B; Griffiths, Thomas L; Kemp, Charles

2006-07-01

Inductive inference allows humans to make powerful generalizations from sparse data when learning about word meanings, unobserved properties, causal relationships, and many other aspects of the world. Traditional accounts of induction emphasize either the power of statistical learning, or the importance of strong constraints from structured domain knowledge, intuitive theories or schemas. We argue that both components are necessary to explain the nature, use and acquisition of human knowledge, and we introduce a theory-based Bayesian framework for modeling inductive learning and reasoning as statistical inferences over structured knowledge representations.

Modeling and knowledge acquisition processes using case-based inference

Directory of Open Access Journals (Sweden)

Ameneh Khadivar

2017-03-01

Full Text Available The method of acquisition and presentation of the organizational Process Knowledge has considered by many KM researches. In this research a model for process knowledge acquisition and presentation has been presented by using the approach of Case Base Reasoning. The validation of the presented model was evaluated by conducting an expert panel. Then a software has been developed based on the presented model and implemented in Eghtesad Novin Bank of Iran. In this company, based on the stages of the presented model, first the knowledge intensive processes has been identified, then the Process Knowledge was stored in a knowledge base in the format of problem/solution/consequent .The retrieval of the knowledge was done based on the similarity of the nearest neighbor algorithm. For validating of the implemented system, results of the system has compared by the results of the decision making of the expert of the process.

Combining bimodal presentation schemes and buzz groups improves clinical reasoning and learning at morning report.

Science.gov (United States)

Balslev, Thomas; Rasmussen, Astrid Bruun; Skajaa, Torjus; Nielsen, Jens Peter; Muijtjens, Arno; De Grave, Willem; Van Merriënboer, Jeroen

2014-12-11

Abstract Morning reports offer opportunities for intensive work-based learning. In this controlled study, we measured learning processes and outcomes with the report of paediatric emergency room patients. Twelve specialists and 12 residents were randomised into four groups and discussed the same two paediatric cases. The groups differed in their presentation modality (verbal only vs. verbal + text) and the use of buzz groups (with vs. without). The verbal interactions were analysed for clinical reasoning processes. Perceptions of learning and judgment of learning were reported in a questionnaire. Diagnostic accuracy was assessed by a 20-item multiple-choice test. Combined bimodal presentation and buzz groups increased the odds ratio of clinical reasoning to occur in the discussion of cases by a factor of 1.90 (p = 0.013), indicating superior reasoning for buzz groups working with bimodal materials. For specialists, a positive effect of bimodal presentation was found on perceptions of learning (p presentation on diagnostic accuracy was noted in the specialists (p presentation and buzz group discussion of emergency cases improves clinicians' clinical reasoning and learning.

Analysis of students’ mathematical reasoning

Science.gov (United States)

Sukirwan; Darhim; Herman, T.

2018-01-01

The reasoning is one of the mathematical abilities that have very complex implications. This complexity causes reasoning including abilities that are not easily attainable by students. Similarly, studies dealing with reason are quite diverse, primarily concerned with the quality of mathematical reasoning. The objective of this study was to determine the quality of mathematical reasoning based perspective Lithner. Lithner looked at how the environment affects the mathematical reasoning. In this regard, Lithner made two perspectives, namely imitative reasoning and creative reasoning. Imitative reasoning can be memorized and algorithmic reasoning. The Result study shows that although the students generally still have problems in reasoning. Students tend to be on imitative reasoning which means that students tend to use a routine procedure when dealing with reasoning. It is also shown that the traditional approach still dominates on the situation of students’ daily learning.

Systematizing Scaffolding for Problem-Based Learning: A View from Case-Based Reasoning

OpenAIRE

Tawfik, Andrew A; Kolodner, Janet L

2016-01-01

Current theories and models of education often argue that instruction is best administered when knowledge is situated within a context. Problem-based learning (PBL) provides an approach to education that has particularly powerful affordances for learning disciplinary content and practices by solving authentic problems within a discipline. However, not all implementations of PBL have been equally successful at fostering such learning, and some argue that this form of instruction is beyond the ...

Effects of Scaffolds and Scientific Reasoning Ability on Web-Based Scientific Inquiry

Science.gov (United States)

Wu, Hui-Ling; Weng, Hsiao-Lan; She, Hsiao-Ching

2016-01-01

This study examined how background knowledge, scientific reasoning ability, and various scaffolding forms influenced students' science knowledge and scientific inquiry achievements. The students participated in an online scientific inquiry program involving such activities as generating scientific questions and drawing evidence-based conclusions,…

Protection as care: moral reasoning and moral orientation among ethnically and socioeconomically diverse older women.

Science.gov (United States)

Dakin, Emily

2014-01-01

This study examined moral reasoning among ethnically and socioeconomically diverse older women based on the care and justice moral orientations reflecting theoretical frameworks developed by Carol Gilligan and Lawrence Kohlberg, respectively. A major gap in this area of research and theory development has been the lack of examination of moral reasoning in later life. This study addressed this gap by assessing socioeconomically and ethnically diverse older women's reasoning in response to ethical dilemmas showing conflict between autonomy, representative of Kohlberg's justice orientation, and protection, representative of Gilligan's care orientation. The dilemmas used in this study came from adult protective services (APS), the U.S. system that investigates and intervenes in cases of elder abuse and neglect. Subjects were 88 African American, Latina, and Caucasian women age 60 or over from varying socioeconomic status backgrounds who participated in eight focus groups. Overall, participants favored protection over autonomy in responding to the case scenarios. Their reasoning in responding to these dilemmas reflected an ethic of care and responsibility and a recognition of the limitations of autonomy. This reasoning is highly consistent with the care orientation. Variations in the overall ethic of care and responsibility based on ethnicity and SES also are discussed. Copyright © 2013. Published by Elsevier Inc.

Generic project definitions for improvement of health care delivery: a case-based approach.

Science.gov (United States)

Niemeijer, Gerard C; Does, Ronald J M M; de Mast, Jeroen; Trip, Albert; van den Heuvel, Jaap

2011-01-01

The purpose of this article is to create actionable knowledge, making the definition of process improvement projects in health care delivery more effective. This study is a retrospective analysis of process improvement projects in hospitals, facilitating a case-based reasoning approach to project definition. Data sources were project documentation and hospital-performance statistics of 271 Lean Six Sigma health care projects from 2002 to 2009 of general, teaching, and academic hospitals in the Netherlands and Belgium. Objectives and operational definitions of improvement projects in the sample, analyzed and structured in a uniform format and terminology. Extraction of reusable elements of earlier project definitions, presented in the form of 9 templates called generic project definitions. These templates function as exemplars for future process improvement projects, making the selection, definition, and operationalization of similar projects more efficient. Each template includes an explicated rationale, an operationalization in the form of metrics, and a prototypical example. Thus, a process of incremental and sustained learning based on case-based reasoning is facilitated. The quality of project definitions is a crucial success factor in pursuits to improve health care delivery. We offer 9 tried and tested improvement themes related to patient safety, patient satisfaction, and business-economic performance of hospitals.

Belief Inhibition in Children's Reasoning: Memory-Based Evidence

Science.gov (United States)

Steegen, Sara; Neys, Wim De

2012-01-01

Adult reasoning has been shown as mediated by the inhibition of intuitive beliefs that are in conflict with logic. The current study introduces a classic procedure from the memory field to investigate belief inhibition in 12- to 17-year-old reasoners. A lexical decision task was used to probe the memory accessibility of beliefs that were cued…

Measurement Model of Reasoning Skills among Science Students Based on Socio Scientific Issues (SSI

Directory of Open Access Journals (Sweden)

MOHD AFIFI BAHURUDIN SETAMBAH

2018-05-01

Full Text Available The lack of reasoning skills has been recognized as one of the contributing factors to the declined achievement in the Trends in Mathematics and Science Studies (TIMSS and Programme for International Student Assessment (PISA assessments in Malaysia. The use of socio-scientific issues (SSI as a learning strategy offers the potential of improving the level of students' reasoning skills and consequently improves students’ achievement in science subjects. This study examined the development of a measurement model of reasoning skills among science students based on SSI using the analysis of moment structure (AMOS approach before going to second level to full structured equation modelling (SEM. A total of 450 respondents were selected using a stratified random sampling. Results showed a modified measurement model of reasoning skills consisting of the View Knowledge (VK was as a main construct. The items that measure the level of pre-reflection of students fulfilled the elements of unidimensionality, validity, and reliability. Although the level of student reasoning skills was still low but this development of measurement model could be identified and proposed teaching methods that could be adopted to improve students’ reasoning skills.

The Co-Emergence of Aggregate and Modelling Reasoning

Science.gov (United States)

Aridor, Keren; Ben-Zvi, Dani

2017-01-01

This article examines how two processes--reasoning with statistical modelling of a real phenomenon and aggregate reasoning--can co-emerge. We focus in this case study on the emergent reasoning of two fifth graders (aged 10) involved in statistical data analysis, informal inference, and modelling activities using TinkerPlots™. We describe nine…

Improving practical reasoning and argumentation

OpenAIRE

Baumtrog, Michael David

2015-01-01

This thesis justifies the need for and develops a new integrated model of practical reasoning and argumentation. After framing the work in terms of what is reasonable rather than what is rational (chapter 1), I apply the model for practical argumentation analysis and evaluation provided by Fairclough and Fairclough (2012) to a paradigm case of unreasonable individual practical argumentation provided by mass murderer Anders Behring Breivik (chapter 2). The application shows that by following t...

Minimally inconsistent reasoning in Semantic Web.

Science.gov (United States)

Zhang, Xiaowang

2017-01-01

Reasoning with inconsistencies is an important issue for Semantic Web as imperfect information is unavoidable in real applications. For this, different paraconsistent approaches, due to their capacity to draw as nontrivial conclusions by tolerating inconsistencies, have been proposed to reason with inconsistent description logic knowledge bases. However, existing paraconsistent approaches are often criticized for being too skeptical. To this end, this paper presents a non-monotonic paraconsistent version of description logic reasoning, called minimally inconsistent reasoning, where inconsistencies tolerated in the reasoning are minimized so that more reasonable conclusions can be inferred. Some desirable properties are studied, which shows that the new semantics inherits advantages of both non-monotonic reasoning and paraconsistent reasoning. A complete and sound tableau-based algorithm, called multi-valued tableaux, is developed to capture the minimally inconsistent reasoning. In fact, the tableaux algorithm is designed, as a framework for multi-valued DL, to allow for different underlying paraconsistent semantics, with the mere difference in the clash conditions. Finally, the complexity of minimally inconsistent description logic reasoning is shown on the same level as the (classical) description logic reasoning.

Pisa Question and Reasoning Skill

Directory of Open Access Journals (Sweden)

Ersoy Esen

2017-01-01

Full Text Available The objective of the study is to determine the level of the reasoning skills of the secondary school students. This research has been conducted during the academic year of 2015-2016 with the participation of 51 students in total, from a province in the Black Sea region of Turkey by using random sampling method. Case study method has been used in this study, since it explains an existing situation. In this study, content analysis from the qualitative research methods was carried out. In order to ensure the validity of the scope, agreement percentage formula was used and expert opinions were sought.The problem named Holiday from the Chapter 1 of the normal units in Problem Solving Questions from PISA (Program for International Student Assessments [35] are used as the data collection tool for the study. The problem named Holiday consists of two questions. Applied problems were evaluated according to the mathematical reasoning stages of TIMSS (2003. The findings suggest that the students use proportional reasoning while solving the problems and use the geometric shapes to facilitate the solution of the problem. When they come across problems related to each other, it is observed that they create connections between the problems based on the results of the previous problem. In conclusion, the students perform crosscheck to ensure that their solutions to the problems are accurate.

Case-Based Reasoning in Transfer Learning

Science.gov (United States)

2009-01-01

study of transfer in psychology and education (e.g., Thorndike & Woodworth, 1901; Perkins & Salomon, 1994; Bransford et al., 2000), among other...Sutton, R., & Barto, A. (1998). Reinforcement learning: An introduction. Cambridge, MA: MIT Press. Thorndike , E.L., & Woodworth, R.S. (1901). The

Knowledge-based reasoning in the Paladin tactical decision generation system

Science.gov (United States)

Chappell, Alan R.

1993-01-01

A real-time tactical decision generation system for air combat engagements, Paladin, has been developed. A pilot's job in air combat includes tasks that are largely symbolic. These symbolic tasks are generally performed through the application of experience and training (i.e. knowledge) gathered over years of flying a fighter aircraft. Two such tasks, situation assessment and throttle control, are identified and broken out in Paladin to be handled by specialized knowledge based systems. Knowledge pertaining to these tasks is encoded into rule-bases to provide the foundation for decisions. Paladin uses a custom built inference engine and a partitioned rule-base structure to give these symbolic results in real-time. This paper provides an overview of knowledge-based reasoning systems as a subset of rule-based systems. The knowledge used by Paladin in generating results as well as the system design for real-time execution is discussed.

The Christological Ontology of Reason

DEFF Research Database (Denmark)

Nissen, Ulrik Becker

2006-01-01

Taking the startingpoint in an assertion of an ambiguity in the Lutheran tradition’s assessment of reason, the essay argues that the Kantian unreserved confidence in reason is criticised in Bonhoeffer. Based upon a Christological understanding of reason, Bonhoeffer endorses a view of reason which...... is treated in the essay. Here it is argued that Bonhoeffer may be appropriated in attempting to outline a Christological ontology of reason holding essential implications for the sources and conditions of public discourse....

Facilitating progress in health behaviour theory development and modification: the reasoned action approach as a case study.

Science.gov (United States)

Head, Katharine J; Noar, Seth M

2014-01-01

This paper explores the question: what are barriers to health behaviour theory development and modification, and what potential solutions can be proposed? Using the reasoned action approach (RAA) as a case study, four areas of theory development were examined: (1) the theoretical domain of a theory; (2) tension between generalisability and utility, (3) criteria for adding/removing variables in a theory, and (4) organisational tracking of theoretical developments and formal changes to theory. Based on a discussion of these four issues, recommendations for theory development are presented, including: (1) the theoretical domain for theories such as RAA should be clarified; (2) when there is tension between generalisability and utility, utility should be given preference given the applied nature of the health behaviour field; (3) variables should be formally removed/amended/added to a theory based on their performance across multiple studies and (4) organisations and researchers with a stake in particular health areas may be best suited for tracking the literature on behaviour-specific theories and making refinements to theory, based on a consensus approach. Overall, enhancing research in this area can provide important insights for more accurately understanding health behaviours and thus producing work that leads to more effective health behaviour change interventions.

Do medical students’ scores using different assessment instruments predict their scores in clinical reasoning using a computer-based simulation?

Directory of Open Access Journals (Sweden)

Fida M

2015-02-01

Full Text Available Mariam Fida,1 Salah Eldin Kassab2 1Department of Molecular Medicine, College of Medicine and Medical Sciences, Arabian Gulf University, Manama, Bahrain; 2Department of Medical Education, Faculty of Medicine, Suez Canal University, Ismailia, Egypt Purpose: The development of clinical problem-solving skills evolves over time and requires structured training and background knowledge. Computer-based case simulations (CCS have been used for teaching and assessment of clinical reasoning skills. However, previous studies examining the psychometric properties of CCS as an assessment tool have been controversial. Furthermore, studies reporting the integration of CCS into problem-based medical curricula have been limited. Methods: This study examined the psychometric properties of using CCS software (DxR Clinician for assessment of medical students (n=130 studying in a problem-based, integrated multisystem module (Unit IX during the academic year 2011–2012. Internal consistency reliability of CCS scores was calculated using Cronbach's alpha statistics. The relationships between students' scores in CCS components (clinical reasoning, diagnostic performance, and patient management and their scores in other examination tools at the end of the unit including multiple-choice questions, short-answer questions, objective structured clinical examination (OSCE, and real patient encounters were analyzed using stepwise hierarchical linear regression. Results: Internal consistency reliability of CCS scores was high (α=0.862. Inter-item correlations between students' scores in different CCS components and their scores in CCS and other test items were statistically significant. Regression analysis indicated that OSCE scores predicted 32.7% and 35.1% of the variance in clinical reasoning and patient management scores, respectively (P<0.01. Multiple-choice question scores, however, predicted only 15.4% of the variance in diagnostic performance scores (P<0.01, while

Mapping Variation in Children's Mathematical Reasoning: The Case of "What Else Belongs?"

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Vale, Colleen; Widjaja, Wanty; Herbert, Sandra; Bragg, Leicha A.; Loong, Esther Yoon-Kin

2017-01-01

Explaining appears to dominate primary teachers' understanding of mathematical reasoning when it is not confused with problem solving. Drawing on previous literature of mathematical reasoning, we generate a view of the critical aspects of reasoning that may assist primary teachers when designing and enacting tasks to elicit and develop…

Teachers’ professional reasoning about their pedagogical use of technology

NARCIS (Netherlands)

Heitink, M.; Voogt, J.; Verplanken, L.; van Braak, J.; Fisser, P.

2016-01-01

This study focused on teachers’ reasoning about the use of technology in practice. Both teachers’ professional reasoning and their technology use were investigated. Through video cases, 157 teachers demonstrated their technology use in practice and commented on the reasoning behind their actions.

A case-study of a socio-scientific issues curricular and pedagogical intervention in an undergraduate microbiology course: A focus on informal reasoning

Science.gov (United States)

Schalk, Kelly A.

The purpose of this investigation was to measure specific ways a student interest SSI-based curricular and pedagogical affects undergraduates' ability informally reason. The delimited components of informal reasoning measured were undergraduates' Nature of Science conceptualizations and ability to evaluate scientific information. The socio-scientific issues (SSI) theoretical framework used in this case-study has been advocated as a means for improving students' functional scientific literacy. This investigation focused on the laboratory component of an undergraduate microbiology course in spring 2008. There were 26 participants. The instruments used in this study included: (1) Individual and Group research projects, (2) journals, (3) laboratory write-ups, (4) a laboratory quiz, (5) anonymous evaluations, and (6) a pre/post article exercise. All instruments yielded qualitative data, which were coded using the qualitative software NVivo7. Data analyses were subjected to instrumental triangulation, inter-rater reliability, and member-checking. It was determined that undergraduates' epistemological knowledge of scientific discovery, processes, and justification matured in response to the intervention. Specifically, students realized: (1) differences between facts, theories, and opinions; (2) testable questions are not definitively proven; (3) there is no stepwise scientific process; and (4) lack of data weakens a claim. It was determined that this knowledge influenced participants' beliefs and ability to informally reason. For instance, students exhibited more critical evaluations of scientific information. It was also found that undergraduates' prior opinions had changed over the semester. Further, the student interest aspect of this framework engaged learners by offering participants several opportunities to influentially examine microbiology issues that affected their life. The investigation provided empirically based insights into the ways undergraduates' interest

CAD Parts-Based Assembly Modeling by Probabilistic Reasoning

KAUST Repository

Zhang, Kai-Ke

2016-04-11

Nowadays, increasing amount of parts and sub-assemblies are publicly available, which can be used directly for product development instead of creating from scratch. In this paper, we propose an interactive design framework for efficient and smart assembly modeling, in order to improve the design efficiency. Our approach is based on a probabilistic reasoning. Given a collection of industrial assemblies, we learn a probabilistic graphical model from the relationships between the parts of assemblies. Then in the modeling stage, this probabilistic model is used to suggest the most likely used parts compatible with the current assembly. Finally, the parts are assembled under certain geometric constraints. We demonstrate the effectiveness of our framework through a variety of assembly models produced by our prototype system. © 2015 IEEE.

CAD Parts-Based Assembly Modeling by Probabilistic Reasoning

KAUST Repository

Zhang, Kai-Ke; Hu, Kai-Mo; Yin, Li-Cheng; Yan, Dongming; Wang, Bin

2016-01-01

Nowadays, increasing amount of parts and sub-assemblies are publicly available, which can be used directly for product development instead of creating from scratch. In this paper, we propose an interactive design framework for efficient and smart assembly modeling, in order to improve the design efficiency. Our approach is based on a probabilistic reasoning. Given a collection of industrial assemblies, we learn a probabilistic graphical model from the relationships between the parts of assemblies. Then in the modeling stage, this probabilistic model is used to suggest the most likely used parts compatible with the current assembly. Finally, the parts are assembled under certain geometric constraints. We demonstrate the effectiveness of our framework through a variety of assembly models produced by our prototype system. © 2015 IEEE.

What role for the anterior cingulate in analogical reasoning?

Science.gov (United States)

O'Boyle, Michael W

2010-06-01

Abstract While prefrontal and frontal cortex of the brain are well documented to mediate many executive functions, including creativity, flexibility, and adaptability, the anterior cingulate cortex (ACC) is known to be involved in error detection and conflict resolution, and is crucial to reward-based learning. A case is made for the notion that any neural model of analogical reasoning must incorporate the critical (and specialized) contributions of the ACC.

The Probability Heuristics Model of Syllogistic Reasoning.

Science.gov (United States)

Chater, Nick; Oaksford, Mike

1999-01-01

Proposes a probability heuristic model for syllogistic reasoning and confirms the rationality of this heuristic by an analysis of the probabilistic validity of syllogistic reasoning that treats logical inference as a limiting case of probabilistic inference. Meta-analysis and two experiments involving 40 adult participants and using generalized…

Identifying Kinds of Reasoning in Collective Argumentation

Science.gov (United States)

Conner, AnnaMarie; Singletary, Laura M.; Smith, Ryan C.; Wagner, Patty Anne; Francisco, Richard T.

2014-01-01

We combine Peirce's rule, case, and result with Toulmin's data, claim, and warrant to differentiate between deductive, inductive, abductive, and analogical reasoning within collective argumentation. In this theoretical article, we illustrate these kinds of reasoning in episodes of collective argumentation using examples from one…

A semi-quantitative reasoning methodology for filtering and ranking HAZOP results in HAZOPExpert

International Nuclear Information System (INIS)

Vaidhyanathan, Ramesh; Venkatasubramanian, Venkat

1996-01-01

Hazard and Operability (HAZOP) analysis is the most widely used and recognized as the preferred Process Hazards Analysis (PHA) approach in the chemical process industry. Recently, a diagraph-model based framework and an expert system called HAZOPExpert was developed for automating this analysis. Upon testing the performance of the system on various industrial case studies. HAZOPExpert was found to successfully mimic the human expert's reasoning and identify the hazards. But, with the increasing complexity of the processes, the HAZOPExpert system generated a large number of consequences compared to those identified by a team of experts. This is mainly due to the strict qualitative reasoning approach implemented in the HAZOPExpert system. In order to filter and rank the consequences generated by the HAZOPExpert system, a semi-quantitative reasoning methodology is proposed using additional quantitative knowledge in the form of design and operating specifications of the process units, and process material property values. This filtering approach combines the qualitative digraph-based HAZOP models and the quantitative knowledge to eliminate the unrealizable consequences. Significant reduction in the number of consequences was obtained using this approach on an ethylene process plant HAZOP case study

Minimally inconsistent reasoning in Semantic Web.

Directory of Open Access Journals (Sweden)

Xiaowang Zhang

Full Text Available Reasoning with inconsistencies is an important issue for Semantic Web as imperfect information is unavoidable in real applications. For this, different paraconsistent approaches, due to their capacity to draw as nontrivial conclusions by tolerating inconsistencies, have been proposed to reason with inconsistent description logic knowledge bases. However, existing paraconsistent approaches are often criticized for being too skeptical. To this end, this paper presents a non-monotonic paraconsistent version of description logic reasoning, called minimally inconsistent reasoning, where inconsistencies tolerated in the reasoning are minimized so that more reasonable conclusions can be inferred. Some desirable properties are studied, which shows that the new semantics inherits advantages of both non-monotonic reasoning and paraconsistent reasoning. A complete and sound tableau-based algorithm, called multi-valued tableaux, is developed to capture the minimally inconsistent reasoning. In fact, the tableaux algorithm is designed, as a framework for multi-valued DL, to allow for different underlying paraconsistent semantics, with the mere difference in the clash conditions. Finally, the complexity of minimally inconsistent description logic reasoning is shown on the same level as the (classical description logic reasoning.

Conveying Clinical Reasoning Based on Visual Observation via Eye-Movement Modelling Examples

Science.gov (United States)

Jarodzka, Halszka; Balslev, Thomas; Holmqvist, Kenneth; Nystrom, Marcus; Scheiter, Katharina; Gerjets, Peter; Eika, Berit

2012-01-01

Complex perceptual tasks, like clinical reasoning based on visual observations of patients, require not only conceptual knowledge about diagnostic classes but also the skills to visually search for symptoms and interpret these observations. However, medical education so far has focused very little on how visual observation skills can be…

Consequence Reasoning in Multilevel Flow Modelling

DEFF Research Database (Denmark)

Zhang, Xinxin; Lind, Morten; Ravn, Ole

2013-01-01

Consequence reasoning is a major element for operation support system to assess the plant situations. The purpose of this paper is to elaborate how Multilevel Flow Models can be used to reason about consequences of disturbances in complex engineering systems. MFM is a modelling methodology...... for representing process knowledge for complex systems. It represents the system by using means-end and part-whole decompositions, and describes not only the purposes and functions of the system but also the causal relations between them. Thus MFM is a tool for causal reasoning. The paper introduces MFM modelling...... syntax and gives detailed reasoning formulas for consequence reasoning. The reasoning formulas offers basis for developing rule-based system to perform consequence reasoning based on MFM, which can be used for alarm design, risk monitoring, and supervision and operation support system design....

Formalization and analysis of reasoning by assumption.

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Bosse, Tibor; Jonker, Catholijn M; Treur, Jan

2006-01-02

This article introduces a novel approach for the analysis of the dynamics of reasoning processes and explores its applicability for the reasoning pattern called reasoning by assumption. More specifically, for a case study in the domain of a Master Mind game, it is shown how empirical human reasoning traces can be formalized and automatically analyzed against dynamic properties they fulfill. To this end, for the pattern of reasoning by assumption a variety of dynamic properties have been specified, some of which are considered characteristic for the reasoning pattern, whereas some other properties can be used to discriminate among different approaches to the reasoning. These properties have been automatically checked for the traces acquired in experiments undertaken. The approach turned out to be beneficial from two perspectives. First, checking characteristic properties contributes to the empirical validation of a theory on reasoning by assumption. Second, checking discriminating properties allows the analyst to identify different classes of human reasoners. 2006 Lawrence Erlbaum Associates, Inc.

Are there reasons to challenge a symbolic computationalist approach in explaining deductive reasoning?

Science.gov (United States)

Faiciuc, Lucia E

2008-06-01

The majority of the existing theories explaining deductive reasoning could be included in a classic computationalist approach of the cognitive processes. In fact, deductive reasoning could be seen to be the pinnacle of the symbolic computationalism, its last fortress to be defended in the face of new, dynamic, and ecological perspectives over cognition. But are there weak points in that position regarding deductive reasoning? What would be the reasons for which new perspectives could gain in credibility? What could be their most important tenets? The answers given to those questions in the paper include two main points. The first one is that the present empirical data could not sustain unambiguously one view over the other, that they are obtained in artificial experimental conditions, and that there are data that are not easily explainable using the traditional computationalist paradigm. The second one is that approaching the deductive reasoning from dynamic and ecological perspectives could have significant advantages. The most obvious one is the possibility to integrate more easily the research regarding the deductive reasoning with the results obtained in other domains of the psychology (especially in what respects the lower cognitive processes), in artificial intelligence or in neurophysiology. The reasons for that would be that such perspectives, as they are sketched in the paper, would imply, essentially, processes of second-order pattern formation and recognition (as it is the case for perception), embodied cognition, and dynamic processes as the brain ones are.

Design Case Retrieval by Generic Representations

NARCIS (Netherlands)

Achten, H.H.; Gero, J.S.

2000-01-01

Case-Based Reasoning and Case-Based Design have been proposed to utilize knowledge of previous design solutions to understand or solve current design problems. Case retrieval is often performed on the basis of verbal indexing systems, whereas in design the use of graphic representations is

Quantitative Algebraic Reasoning

DEFF Research Database (Denmark)

Mardare, Radu Iulian; Panangaden, Prakash; Plotkin, Gordon

2016-01-01

We develop a quantitative analogue of equational reasoning which we call quantitative algebra. We define an equality relation indexed by rationals: a =ε b which we think of as saying that “a is approximately equal to b up to an error of ε”. We have 4 interesting examples where we have a quantitative...... equational theory whose free algebras correspond to well known structures. In each case we have finitary and continuous versions. The four cases are: Hausdorff metrics from quantitive semilattices; pWasserstein metrics (hence also the Kantorovich metric) from barycentric algebras and also from pointed...

The Process of Clinical Reasoning among Medical Students

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Djon Machado Lopes

Full Text Available ABSTRACT Introduction: Research in the field of medical reasoning has shed light on the reasoning process used by medical students. The strategies in this process are related to the analytical [hypothetical-deductive (HD] and nonanalytic [scheme-inductive (SI] systems, and pattern recognition (PR]. Objective: To explore the clinical reasoning process of students from the fifth year of medical school at the end of the clinical cycle of medical internship, and to identify the strategies used in preparing diagnostic hypotheses, knowledge organization and content. Method: Qualitative research conducted in 2014 at a Brazilian public university with medical interns. Following Stamm's method, a case in internal medicine (IM was built based on the theory of prototypes (Group 1 = 47 interns, in which the interns listed, according to their own perceptions, the signs, symptoms, syndromes, and diseases typical of internal medicine. This case was used for evaluating the clinical reasoning process of Group 2 (30 students = simple random sample obtained with the "think aloud" process. The verbalizations were transcribed and evaluated by Bardin's thematic analysis. The content analysis were approved by two experts at the beginning and at the end of the analysis process. Results: The interns developed 164 primary and secondary hypotheses when solving the case. The SI strategy prevailed with 48.8%, followed by PR (35.4%, HD (12.2%, and mixed (1.8 % each: SI + HD and HD + PR. The students built 146 distinct semantic axes, resulting in an average of 4.8/ participant. During the analysis, 438 interpretation processes were executed (average of 14.6/participant, and 124 combination processes (average of 4.1/participant. Conclusions: The nonanalytic strategies prevailed with the PR being the most used in the development of primary hypotheses (46.8% and the SI in secondary hypotheses (93%. The interns showed a strong semantic network and did three and a half times more

The Relationship between American Sign Language Vocabulary and the Development of Language-Based Reasoning Skills in Deaf Children

Science.gov (United States)

Henner, Jonathan

2016-01-01

The language-based analogical reasoning abilities of Deaf children are a controversial topic. Researchers lack agreement about whether Deaf children possess the ability to reason using language-based analogies, or whether this ability is limited by a lack of access to vocabulary, both written and signed. This dissertation examines factors that…

What's in a Label? Is Diagnosis the Start or the End of Clinical Reasoning?

Science.gov (United States)

Ilgen, Jonathan S; Eva, Kevin W; Regehr, Glenn

2016-04-01

Diagnostic reasoning has received substantial attention in the literature, yet what we mean by "diagnosis" may vary. Diagnosis can align with assignment of a "label," where a constellation of signs, symptoms, and test results is unified into a solution at a single point in time. This "diagnostic labeling" conceptualization is embodied in our case-based learning curricula, published case reports, and research studies, all of which treat diagnostic accuracy as the primary outcome. However, this conceptualization may oversimplify the richly iterative and evolutionary nature of clinical reasoning in many settings. Diagnosis can also represent a process of guiding one's thoughts by "making meaning" from data that are intrinsically dynamic, experienced idiosyncratically, negotiated among team members, and rich with opportunities for exploration. Thus, there are two complementary constructions of diagnosis: 1) the correct solution resulting from a diagnostic reasoning process, and 2) a dynamic aid to an ongoing clinical reasoning process. This article discusses the importance of recognizing these two conceptualizations of "diagnosis," outlines the unintended consequences of emphasizing diagnostic labeling as the primary goal of clinical reasoning, and suggests how framing diagnosis as an ongoing process of meaning-making might change how we think about teaching and assessing clinical reasoning.

An Evidential Reasoning-Based CREAM to Human Reliability Analysis in Maritime Accident Process.

Science.gov (United States)

Wu, Bing; Yan, Xinping; Wang, Yang; Soares, C Guedes

2017-10-01

This article proposes a modified cognitive reliability and error analysis method (CREAM) for estimating the human error probability in the maritime accident process on the basis of an evidential reasoning approach. This modified CREAM is developed to precisely quantify the linguistic variables of the common performance conditions and to overcome the problem of ignoring the uncertainty caused by incomplete information in the existing CREAM models. Moreover, this article views maritime accident development from the sequential perspective, where a scenario- and barrier-based framework is proposed to describe the maritime accident process. This evidential reasoning-based CREAM approach together with the proposed accident development framework are applied to human reliability analysis of a ship capsizing accident. It will facilitate subjective human reliability analysis in different engineering systems where uncertainty exists in practice. © 2017 Society for Risk Analysis.

Tactical Diagrammatic Reasoning

Directory of Open Access Journals (Sweden)

Sven Linker

2017-01-01

Full Text Available Although automated reasoning with diagrams has been possible for some years, tools for diagrammatic reasoning are generally much less sophisticated than their sentential cousins. The tasks of exploring levels of automation and abstraction in the construction of proofs and of providing explanations of solutions expressed in the proofs remain to be addressed. In this paper we take an interactive proof assistant for Euler diagrams, Speedith, and add tactics to its reasoning engine, providing a level of automation in the construction of proofs. By adding tactics to Speedith's repertoire of inferences, we ease the interaction between the user and the system and capture a higher level explanation of the essence of the proof. We analysed the design options for tactics by using metrics which relate to human readability, such as the number of inferences and the amount of clutter present in diagrams. Thus, in contrast to the normal case with sentential tactics, our tactics are designed to not only prove the theorem, but also to support explanation.

The Development of Mathematical Knowledge for Teaching for Quantitative Reasoning Using Video-Based Instruction

Science.gov (United States)

Walters, Charles David

Quantitative reasoning (P. W. Thompson, 1990, 1994) is a powerful mathematical tool that enables students to engage in rich problem solving across the curriculum. One way to support students' quantitative reasoning is to develop prospective secondary teachers' (PSTs) mathematical knowledge for teaching (MKT; Ball, Thames, & Phelps, 2008) related to quantitative reasoning. However, this may prove challenging, as prior to entering the classroom, PSTs often have few opportunities to develop MKT by examining and reflecting on students' thinking. Videos offer one avenue through which such opportunities are possible. In this study, I report on the design of a mini-course for PSTs that featured a series of videos created as part of a proof-of-concept NSF-funded project. These MathTalk videos highlight the ways in which the quantitative reasoning of two high school students developed over time. Using a mixed approach to grounded theory, I analyzed pre- and postinterviews using an extant coding scheme based on the Silverman and Thompson (2008) framework for the development of MKT. This analysis revealed a shift in participants' affect as well as three distinct shifts in their MKT around quantitative reasoning with distances, including shifts in: (a) quantitative reasoning; (b) point of view (decentering); and (c) orientation toward problem solving. Using the four-part focusing framework (Lobato, Hohensee, & Rhodehamel, 2013), I analyzed classroom data to account for how participants' noticing was linked with the shifts in MKT. Notably, their increased noticing of aspects of MKT around quantitative reasoning with distances, which features prominently in the MathTalk videos, seemed to contribute to the emergence of the shifts in MKT. Results from this study link elements of the learning environment to the development of specific facets of MKT around quantitative reasoning with distances. These connections suggest that vicarious experiences with two students' quantitative

An Ontology-Based Reasoning Framework for Querying Satellite Images for Disaster Monitoring.

Science.gov (United States)

Alirezaie, Marjan; Kiselev, Andrey; Längkvist, Martin; Klügl, Franziska; Loutfi, Amy

2017-11-05

This paper presents a framework in which satellite images are classified and augmented with additional semantic information to enable queries about what can be found on the map at a particular location, but also about paths that can be taken. This is achieved by a reasoning framework based on qualitative spatial reasoning that is able to find answers to high level queries that may vary on the current situation. This framework called SemCityMap, provides the full pipeline from enriching the raw image data with rudimentary labels to the integration of a knowledge representation and reasoning methods to user interfaces for high level querying. To illustrate the utility of SemCityMap in a disaster scenario, we use an urban environment-central Stockholm-in combination with a flood simulation. We show that the system provides useful answers to high-level queries also with respect to the current flood status. Examples of such queries concern path planning for vehicles or retrieval of safe regions such as "find all regions close to schools and far from the flooded area". The particular advantage of our approach lies in the fact that ontological information and reasoning is explicitly integrated so that queries can be formulated in a natural way using concepts on appropriate level of abstraction, including additional constraints.

An Ontology-Based Reasoning Framework for Querying Satellite Images for Disaster Monitoring

Directory of Open Access Journals (Sweden)

Marjan Alirezaie

2017-11-01

Full Text Available This paper presents a framework in which satellite images are classified and augmented with additional semantic information to enable queries about what can be found on the map at a particular location, but also about paths that can be taken. This is achieved by a reasoning framework based on qualitative spatial reasoning that is able to find answers to high level queries that may vary on the current situation. This framework called SemCityMap, provides the full pipeline from enriching the raw image data with rudimentary labels to the integration of a knowledge representation and reasoning methods to user interfaces for high level querying. To illustrate the utility of SemCityMap in a disaster scenario, we use an urban environment—central Stockholm—in combination with a flood simulation. We show that the system provides useful answers to high-level queries also with respect to the current flood status. Examples of such queries concern path planning for vehicles or retrieval of safe regions such as “find all regions close to schools and far from the flooded area”. The particular advantage of our approach lies in the fact that ontological information and reasoning is explicitly integrated so that queries can be formulated in a natural way using concepts on appropriate level of abstraction, including additional constraints.

The effect of multiple external representations (MERs) worksheets toward complex system reasoning achievement

Science.gov (United States)

Sumarno; Ibrahim, M.; Supardi, Z. A. I.

2018-03-01

The application of a systems approach to assessing biological systems provides hope for a coherent understanding of cell dynamics patterns and their relationship to plant life. This action required the reasoning about complex systems. In other sides, there were a lot of researchers who provided the proof about the instructional successions. They involved the multiple external representations which improved the biological learning. The researcher conducted an investigation using one shoot case study design which involved 30 students in proving that the MERs worksheets could affect the student's achievement of reasoning about complex system. The data had been collected based on test of reasoning about complex system and student's identification result who worked through MERs. The result showed that only partially students could achieve reasoning about system complex, but their MERs skill could support their reasoning ability of complex system. This study could bring a new hope to develop the MERs worksheet as a tool to facilitate the reasoning about complex system.

Bayesian reasoning in high-energy physics. Principles and applications

International Nuclear Information System (INIS)

D'Agostini, G.

1999-01-01

Bayesian statistics is based on the intuitive idea that probability quantifies the degree of belief in the occurrence of an event. The choice of name is due to the key role played by Bayes' theorem, as a logical tool to update probability in the light of new pieces of information. This approach is very close to the intuitive reasoning of experienced physicists, and it allows all kinds of uncertainties to be handled in a consistent way. Many cases of evaluation of measurement uncertainty are considered in detail in this report, including uncertainty arising from systematic errors, upper/lower limits and unfolding. Approximate methods, very useful in routine applications, are provided and several standard methods are recovered for cases in which the (often hidden) assumptions on which they are based hold. (orig.)

Bayesian reasoning in high-energy physics. Principles and applications

Energy Technology Data Exchange (ETDEWEB)

D' Agostini, G [Rome Univ. (Italy). Dipt. di Fisica; [European Organization for Nuclear Research, Geneva (Switzerland)

1999-07-19

Bayesian statistics is based on the intuitive idea that probability quantifies the degree of belief in the occurrence of an event. The choice of name is due to the key role played by Bayes' theorem, as a logical tool to update probability in the light of new pieces of information. This approach is very close to the intuitive reasoning of experienced physicists, and it allows all kinds of uncertainties to be handled in a consistent way. Many cases of evaluation of measurement uncertainty are considered in detail in this report, including uncertainty arising from systematic errors, upper/lower limits and unfolding. Approximate methods, very useful in routine applications, are provided and several standard methods are recovered for cases in which the (often hidden) assumptions on which they are based hold. (orig.)

Robotics Vision-based Heuristic Reasoning for Underwater Target Tracking and Navigation

OpenAIRE

Kia, Chua; Arshad, Mohd Rizal

2006-01-01

This paper presents a robotics vision-based heuristic reasoning system for underwater target tracking and navigation. This system is introduced to improve the level of automation of underwater Remote Operated Vehicles (ROVs) operations. A prototype which combines computer vision with an underwater robotics system is successfully designed and developed to perform target tracking and intelligent navigation. This study focuses on developing image processing algorithms and fuzzy inference system ...

Farmers’ reasons for deregistering from organic farming

DEFF Research Database (Denmark)

Koesling, Matthias; Løes, Anne-Kristin; Flaten, Ola

2012-01-01

Every year since 2002, 150 to 200 farmers in Norway have deregistered from certified organic production. The aim of this study was to get behind these figures and improve our understanding of the reasoning leading to decisions to opt out. Four cases of deregistered organic farmers with grain, sheep......, dairy or vegetable production were selected for in-depth studies. The cases were analysed from the perspective of individual competencies and the competencies available in the networks of the selected organic farmers. Besides the conspicuous reasons to opt out of certified organic farming......, such as regulations getting stricter over time and low income, personal reasons such as disappointment and need for acceptance were also important. This shows that hard mechanisms, such as economic support and premium prices, are not sufficient to motivate farmers for sustained organic management. Support...

OWL-based reasoning methods for validating archetypes.

Science.gov (United States)

Menárguez-Tortosa, Marcos; Fernández-Breis, Jesualdo Tomás

2013-04-01

Some modern Electronic Healthcare Record (EHR) architectures and standards are based on the dual model-based architecture, which defines two conceptual levels: reference model and archetype model. Such architectures represent EHR domain knowledge by means of archetypes, which are considered by many researchers to play a fundamental role for the achievement of semantic interoperability in healthcare. Consequently, formal methods for validating archetypes are necessary. In recent years, there has been an increasing interest in exploring how semantic web technologies in general, and ontologies in particular, can facilitate the representation and management of archetypes, including binding to terminologies, but no solution based on such technologies has been provided to date to validate archetypes. Our approach represents archetypes by means of OWL ontologies. This permits to combine the two levels of the dual model-based architecture in one modeling framework which can also integrate terminologies available in OWL format. The validation method consists of reasoning on those ontologies to find modeling errors in archetypes: incorrect restrictions over the reference model, non-conformant archetype specializations and inconsistent terminological bindings. The archetypes available in the repositories supported by the openEHR Foundation and the NHS Connecting for Health Program, which are the two largest publicly available ones, have been analyzed with our validation method. For such purpose, we have implemented a software tool called Archeck. Our results show that around 1/5 of archetype specializations contain modeling errors, the most common mistakes being related to coded terms and terminological bindings. The analysis of each repository reveals that different patterns of errors are found in both repositories. This result reinforces the need for making serious efforts in improving archetype design processes. Copyright © 2012 Elsevier Inc. All rights reserved.

The Christological Ontology of Reason

DEFF Research Database (Denmark)

Nissen, Ulrik Becker

2006-01-01

Taking the startingpoint in an assertion of an ambiguity in the Lutheran tradition’s assessment of reason, the essay argues that the Kantian unreserved confidence in reason is criticised in Bonhoeffer. Based upon a Christological understanding of reason, Bonhoeffer endorses a view of reason which...... is specifically Christian and yet maintains a universality. With a focus on Bonhoeffer’s »Ethik« as the hermeneutical key to his theology, Bonhoeffer’s notion is also discussed in the light of contemporary Christian ethics. In this part it is particularly the role of reason within a public dis-course which...

Argumentation and Reasoning in Design: An Empirical Analysis of the Effects of Verbal Reasoning on Idea Value in Group Idea Generation

DEFF Research Database (Denmark)

Cramer-Petersen, Claus L.; Ahmed-Kristensen, Saeema

2016-01-01

Reasoning is argumentative and is at the core of design activity and thinking. Understanding the influence of reasoning on the value of ideas is key to support design practice. The paper aims to show the effect of verbal reasoning on the value of ideas. Protocol analyses of four industry cases...... doing idea generation shows that framing by certainty and deductive reasoning lead to useful incremental ideas while framing by uncertainty and abductive reasoning lead to radical ideas. The paper concludes that the way of framing ideas is indicative of how ideas add value to on-going design processes....

Episodic Reasoning for Vision-Based Human Action Recognition

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Maria J. Santofimia

2014-01-01

Full Text Available Smart Spaces, Ambient Intelligence, and Ambient Assisted Living are environmental paradigms that strongly depend on their capability to recognize human actions. While most solutions rest on sensor value interpretations and video analysis applications, few have realized the importance of incorporating common-sense capabilities to support the recognition process. Unfortunately, human action recognition cannot be successfully accomplished by only analyzing body postures. On the contrary, this task should be supported by profound knowledge of human agency nature and its tight connection to the reasons and motivations that explain it. The combination of this knowledge and the knowledge about how the world works is essential for recognizing and understanding human actions without committing common-senseless mistakes. This work demonstrates the impact that episodic reasoning has in improving the accuracy of a computer vision system for human action recognition. This work also presents formalization, implementation, and evaluation details of the knowledge model that supports the episodic reasoning.

Midwives' Clinical Reasons for Performing Episiotomies in the Kurdistan Region: Are they evidence-based?

Science.gov (United States)

Ahmed, Hamdia M

2014-08-01

An episiotomy is one of the most common obstetric surgical procedures and is performed mainly by midwives. The decision to perform an episiotomy depends on related clinical factors. This study aimed to find out midwives' reasons for performing episiotomies and to identify the relationship between these reasons and the demographic characteristics of the midwives. This cross-sectional study was conducted between 1(st) July and 30(th) September 2013 in three governmental maternity teaching hospitals in the three main cities of the Kurdistan Region of Iraq. All of the midwives who had worked in the delivery rooms of these hospitals for at least one year were invited to participate in the study (n = 53). Data were collected through interviews with midwives as well as via a questionnaire constructed for the purpose of the study. The questionnaire sought to determine: midwives' demographic characteristics; type of episiotomy performed; authority of the decision to perform the procedure, and reasons for performing episiotomies. THE MAIN CLINICAL REASONS REPORTED BY MIDWIVES FOR PERFORMING AN EPISIOTOMY WERE: macrosomia/large fetus (38, 71.7%), breech delivery (31, 58.5%), shoulder dystocia (29, 54.7%), anticipated perineal tear (27, 50.9%) and fetal distress (27, 50.9%). There was a significant association between the frequency of these reasons and midwives' total experience in delivery rooms as well as their levels of education. Most of the reasons given by the midwives for performing episiotomies were not evidence-based. Age, years of experience, specialties and level of education also had an effect on midwives' reasons for performing episiotomies.

46,XX males: a case series based on clinical and genetics evaluation.

Science.gov (United States)

Mohammadpour Lashkari, F; Totonchi, M; Zamanian, M R; Mansouri, Z; Sadighi Gilani, M A; Sabbaghian, M; Mohseni Meybodi, A

2017-09-01

46,XX male sex reversal syndrome is one of the rarest sex chromosomal aberrations. The presence of SRY gene on one of the X chromosomes is the most frequent cause of this syndrome. Based on Y chromosome profile, there are SRY-positive and SRY-negative forms. The purpose of our study was to report first case series of Iranian patients and describe the different clinical appearances based on their genetic component. From the 8,114 azoospermic and severe oligozoospermic patients referred to Royan institute, we diagnosed 57 cases as sex reversal patients. Based on the endocrinological history, we performed karyotyping, SRY and AZF microdeletion screening. Patients had a female karyotype. According to available hormonal reports of 37 patients, 16 cases had low levels of testosterone (43.2%). On the other hand, 15 males were SRY positive (90.2%), while they lacked the spermatogenic factors encoding genes on Yq. Commencing the testicular differentiation in males, the SRY gene is considered to be very important in this process. Due to homogeneous results of karyotyping and AZF deletion, there are both positive and negative SRY cases that show similar sex reversal phenotypes. Evidences show that there could be diverse phenotypic differences that could be raised from various reasons. © 2016 Blackwell Verlag GmbH.

Calvin on Human Reason

Directory of Open Access Journals (Sweden)

Nicolaas Vorster

2014-10-01

Full Text Available In his recent book The Unintended Reformation, Brad Gregory makes the statement that the Reformation replaced the teleological social ethics of Roman Catholicism based on virtue with formal social ethics based on rules and enforced by magistrates, because they regarded human reason as too depraved to acquire virtue. The result, according to Gregory, is that the relation between internalised values and rules were undermined. This article asks whether this accusation is true with regard to Calvin. The first section discusses the intellectual environment of Calvin’s day – something that inevitably influenced his theory on reason, whilst the second part analyses Calvin’s view on the created nature of reason. The third section investigates Calvin’s view on the effects of sin on reason; and the fourth section discusses Calvin’s perspective on the relation between grace and reason. The article concludes that Gregory’s accusation against the Reformation is not applicable to Calvin. Gregory fails to take into account Calvin’s modified position that the imago Dei was not totally destroyed by sin as well as his teaching on common grace that maintains that even non-believers are able to acquire virtue through the common grace of God.

A Reasoning Method of Cyber-Attack Attribution Based on Threat Intelligence

OpenAIRE

Li Qiang; Yang Ze-Ming; Liu Bao-Xu; Jiang Zheng-Wei

2016-01-01

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 a...

Acquiring skills in malignant hyperthermia crisis management: comparison of high-fidelity simulation versus computer-based case study

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Vilma Mejía

Full Text Available Abstract Introduction: The primary purpose of this study was to compare the effect of high fidelity simulation versus a computer-based case solving self-study, in skills acquisition about malignant hyperthermia on first year anesthesiology residents. Methods: After institutional ethical committee approval, 31 first year anesthesiology residents were enrolled in this prospective randomized single-blinded study. Participants were randomized to either a High Fidelity Simulation Scenario or a computer-based Case Study about malignant hyperthermia. After the intervention, all subjects' performance in was assessed through a high fidelity simulation scenario using a previously validated assessment rubric. Additionally, knowledge tests and a satisfaction survey were applied. Finally, a semi-structured interview was done to assess self-perception of reasoning process and decision-making. Results: 28 first year residents finished successfully the study. Resident's management skill scores were globally higher in High Fidelity Simulation versus Case Study, however they were significant in 4 of the 8 performance rubric elements: recognize signs and symptoms (p = 0.025, prioritization of initial actions of management (p = 0.003, recognize complications (p = 0.025 and communication (p = 0.025. Average scores from pre- and post-test knowledge questionnaires improved from 74% to 85% in the High Fidelity Simulation group, and decreased from 78% to 75% in the Case Study group (p = 0.032. Regarding the qualitative analysis, there was no difference in factors influencing the student's process of reasoning and decision-making with both teaching strategies. Conclusion: Simulation-based training with a malignant hyperthermia high-fidelity scenario was superior to computer-based case study, improving knowledge and skills in malignant hyperthermia crisis management, with a very good satisfaction level in anesthesia residents.

An evidential reasoning-based AHP approach for the selection of environmentally-friendly designs

Energy Technology Data Exchange (ETDEWEB)

NG, C.Y., E-mail: ng.cy@cityu.edu.hk

2016-11-15

Due to the stringent environmental regulatory requirements being imposed by cross-national bodies in recent years, manufacturers have to minimize the environmental impact of their products. Among those environmental impact evaluation tools available, Life Cycle Assessment (LCA) is often employed to quantify the product's environmental impact throughout its entire life cycle. However, owing to the requirements of expert knowledge in environmental science and vast effort for data collection in carrying out LCA, as well as the common absence of complete product information during product development processes, there is a need to develop a more suitable tool for product designers. An evidential reasoning-based approach, which aims at providing a fast-track method to perform design alternative evaluations for non-LCA experts, is therefore introduced as a new initiative to deal with the incomplete or uncertain information. The proposed approach also enables decision makers to quantitatively assess the life cycle phases and design alternatives by comparing their potential environmental impacts, thus effectively and efficiently facilitates the identification of greener designs. A case application is carried out to demonstrate the applicability of the proposed approach.

Content-related interactions and methods of reasoning within self-initiated organic chemistry study groups

Science.gov (United States)

Christian, Karen Jeanne

2011-12-01

Students often use study groups to prepare for class or exams; yet to date, we know very little about how these groups actually function. This study looked at the ways in which undergraduate organic chemistry students prepared for exams through self-initiated study groups. We sought to characterize the methods of social regulation, levels of content processing, and types of reasoning processes used by students within their groups. Our analysis showed that groups engaged in predominantly three types of interactions when discussing chemistry content: co-construction, teaching, and tutoring. Although each group engaged in each of these types of interactions at some point, their prevalence varied between groups and group members. Our analysis suggests that the types of interactions that were most common depended on the relative content knowledge of the group members as well as on the difficulty of the tasks in which they were engaged. Additionally, we were interested in characterizing the reasoning methods used by students within their study groups. We found that students used a combination of three content-relevant methods of reasoning: model-based reasoning, case-based reasoning, or rule-based reasoning, in conjunction with one chemically-irrelevant method of reasoning: symbol-based reasoning. The most common way for groups to reason was to use rules, whereas the least common way was for students to work from a model. In general, student reasoning correlated strongly to the subject matter to which students were paying attention, and was only weakly related to student interactions. Overall, results from this study may help instructors to construct appropriate tasks to guide what and how students study outside of the classroom. We found that students had a decidedly strategic approach in their study groups, relying heavily on material provided by their instructors, and using the reasoning strategies that resulted in the lowest levels of content processing. We suggest

Strategic project selection based on evidential reasoning approach for high-end equipment manufacturing industry

Directory of Open Access Journals (Sweden)

Lu Guangyan

2017-01-01

Full Text Available With the rapid development of science and technology, emerging information technologies have significantly changed the daily life of people. In such context, strategic project selection for high-end equipment manufacturing industries faces more and more complexities and uncertainties with the consideration of several complex criteria. For example, a group of experts rather than a single expert should be invited to select strategic project for high-end equipment manufacturing industries and the experts may feel difficulty to express their preferences towards different strategic projects due to their limited cognitive capabilities. In order to handle these complexities and uncertainties, the criteria framework of strategic project selection is firstly constructed based on the characteristics of high-end equipment manufacturing industries and then evidential reasoning (ER approach is introduced in this paper to help experts express their uncertain preferences and aggregate these preferences to generate an appropriate strategic project. A real case of strategic project selection in a high-speed train manufacturing enterprise is investigated to demonstrate the validity of the ER approach in solving strategic project selection problem.

Neural differences between intrinsic reasons for doing versus extrinsic reasons for doing: an fMRI study.

Science.gov (United States)

Lee, Woogul; Reeve, Johnmarshall; Xue, Yiqun; Xiong, Jinhu

2012-05-01

The contemporary neural understanding of motivation is based almost exclusively on the neural mechanisms of incentive motivation. Recognizing this as a limitation, we used event-related functional magnetic resonance imaging (fMRI) to pursue the viability of expanding the neural understanding of motivation by initiating a pioneering study of intrinsic motivation by scanning participants' neural activity when they decided to act for intrinsic reasons versus when they decided to act for extrinsic reasons. As expected, intrinsic reasons for acting more recruited insular cortex activity while extrinsic reasons for acting more recruited posterior cingulate cortex (PCC) activity. The results demonstrate that engagement decisions based on intrinsic motivation are more determined by weighing the presence of spontaneous self-satisfactions such as interest and enjoyment while engagement decisions based on extrinsic motivation are more determined by weighing socially-acquired stored values as to whether the environmental incentive is attractive enough to warrant action.

Drawing-to-learn: a framework for using drawings to promote model-based reasoning in biology.

Science.gov (United States)

Quillin, Kim; Thomas, Stephen

2015-03-02

The drawing of visual representations is important for learners and scientists alike, such as the drawing of models to enable visual model-based reasoning. Yet few biology instructors recognize drawing as a teachable science process skill, as reflected by its absence in the Vision and Change report's Modeling and Simulation core competency. Further, the diffuse research on drawing can be difficult to access, synthesize, and apply to classroom practice. We have created a framework of drawing-to-learn that defines drawing, categorizes the reasons for using drawing in the biology classroom, and outlines a number of interventions that can help instructors create an environment conducive to student drawing in general and visual model-based reasoning in particular. The suggested interventions are organized to address elements of affect, visual literacy, and visual model-based reasoning, with specific examples cited for each. Further, a Blooming tool for drawing exercises is provided, as are suggestions to help instructors address possible barriers to implementing and assessing drawing-to-learn in the classroom. Overall, the goal of the framework is to increase the visibility of drawing as a skill in biology and to promote the research and implementation of best practices. © 2015 K. Quillin and S. Thomas. CBE—Life Sciences Education © 2015 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Multimodal hybrid reasoning methodology for personalized wellbeing services.

Science.gov (United States)

Ali, Rahman; Afzal, Muhammad; Hussain, Maqbool; Ali, Maqbool; Siddiqi, Muhammad Hameed; Lee, Sungyoung; Ho Kang, Byeong

2016-02-01

A wellness system provides wellbeing recommendations to support experts in promoting a healthier lifestyle and inducing individuals to adopt healthy habits. Adopting physical activity effectively promotes a healthier lifestyle. A physical activity recommendation system assists users to adopt daily routines to form a best practice of life by involving themselves in healthy physical activities. Traditional physical activity recommendation systems focus on general recommendations applicable to a community of users rather than specific individuals. These recommendations are general in nature and are fit for the community at a certain level, but they are not relevant to every individual based on specific requirements and personal interests. To cover this aspect, we propose a multimodal hybrid reasoning methodology (HRM) that generates personalized physical activity recommendations according to the user׳s specific needs and personal interests. The methodology integrates the rule-based reasoning (RBR), case-based reasoning (CBR), and preference-based reasoning (PBR) approaches in a linear combination that enables personalization of recommendations. RBR uses explicit knowledge rules from physical activity guidelines, CBR uses implicit knowledge from experts׳ past experiences, and PBR uses users׳ personal interests and preferences. To validate the methodology, a weight management scenario is considered and experimented with. The RBR part of the methodology generates goal, weight status, and plan recommendations, the CBR part suggests the top three relevant physical activities for executing the recommended plan, and the PBR part filters out irrelevant recommendations from the suggested ones using the user׳s personal preferences and interests. To evaluate the methodology, a baseline-RBR system is developed, which is improved first using ranged rules and ultimately using a hybrid-CBR. A comparison of the results of these systems shows that hybrid-CBR outperforms the

Research of Litchi Diseases Diagnosis Expertsystem Based on Rbr and Cbr

Science.gov (United States)

Xu, Bing; Liu, Liqun

To conquer the bottleneck problems existing in the traditional rule-based reasoning diseases diagnosis system, such as low reasoning efficiency and lack of flexibility, etc.. It researched the integrated case-based reasoning (CBR) and rule-based reasoning (RBR) technology, and put forward a litchi diseases diagnosis expert system (LDDES) with integrated reasoning method. The method use data mining and knowledge obtaining technology to establish knowledge base and case library. It adopt rules to instruct the retrieval and matching for CBR, and use association rule and decision trees algorithm to calculate case similarity.The experiment shows that the method can increase the system's flexibility and reasoning ability, and improve the accuracy of litchi diseases diagnosis.

Effective Teaching in Case-Based Education: Patterns in Teacher Behavior and Their Impact on the Students' Clinical Problem Solving and Learning

Science.gov (United States)

Ramaekers, Stephan; van Keulen, Hanno; Kremer, Wim; Pilot, Albert; van Beukelen, Peter

2011-01-01

Case-based learning formats, in which relevant case information is provided just in time, require teachers to combine their scaffolding role with an information-providing one. The objective of this study is to establish how this combination of roles affects teacher behavior and that, in turn, mediates students' reasoning and problem solving. Data…

The Moral Reasoning of Public Accountants in the Development of a Code of Ethics: the Case of Indonesia

Directory of Open Access Journals (Sweden)

A. S. L. Lindawati

2012-03-01

Full Text Available The objective of this study is to explore the user’s perceptions of the role of moral reasoning in influencing the implementation of codes of ethics as standards and guidance for professional audit practice by Indonesian public accountants. The study focuses on two important aspects of influence: (i the key factors influencing professional public accountants in implementing a code of ethics as a standard for audit practice, and (ii the key activities performed by public accountants as moral agents for establishing awareness of professional values. Two theoretical approaches/models are used as guides for exploring the influence of moral reasoning of public accountants: first, Kolhberg’s model of moral development (Kolhberg 1982 and, secondly, the American Institute of Certified Public Accountants (AICPA’s Code of Conduct, especially the five principles of the code of ethics (1992, 2004. The study employs a multiple case study model to analyse the data collected from interviewing 15 financial managers of different company categories (as users. The findings indicate that (i moral development is an important component in influencing the moral reasoning of the individual public accountants, (ii the degree of professionalism of public accountants is determined by the degree of the development of their moral reasoning, and (iii moral reasoning of individuals influences both Indonesian public accountants and company financial managers in building and improving the effectiveness of the implementation of codes of conduct. It is concluded that the role of moral reasoning is an important influence on achieving ethical awareness in public accountants and financial managers. The development of a full code of ethics and an effective compliance monitoring system is essential for Indonesia if it is to play a role in the emerging global economy.

[Reasons for exchange and explantation of intraocular lenses].

Science.gov (United States)

Neuhann, I; Fleischer, F; Neuhann, T

2012-08-01

This study was performed to analyse the reasons for explantation/exchange of intraocular lenses (IOL), which had originally been implanted for the correction of aphakia during cataract extraction. All cases with IOL explantation, which had been performed at one institution between 1/2008 and 12/2009 were analysed retrospectively. A total of 105 eyes of 100 patients were analysed. The median time interval between implantation and explantation of the IOL was 5.9 years (min. 0, max. 29.6). The most frequent cause for the intervention was subluxation/dislocation of the implant in 55.2% of cases. This group comprised 21% of cases with subluxation within the capsular bag in pseudoexfoliation syndrome. Other reasons were optical problems/incorrect IOL power (21%), calcification of hydrophilic acrylic IOL (7.6%), corneal decompensation associated with an anterior chamber lens (4.8%), and single cases with varying problems. The reasons for IOL exchange presented in this study are comparable to those of other series in the literature. Explantations due to optical problems may gain weight in the future due to a rise in refractive procedures and demands. © Georg Thieme Verlag KG Stuttgart · New York.

Knowledge representation to support reasoning based on multiple models

Science.gov (United States)

Gillam, April; Seidel, Jorge P.; Parker, Alice C.

1990-01-01

Model Based Reasoning is a powerful tool used to design and analyze systems, which are often composed of numerous interactive, interrelated subsystems. Models of the subsystems are written independently and may be used together while they are still under development. Thus the models are not static. They evolve as information becomes obsolete, as improved artifact descriptions are developed, and as system capabilities change. Researchers are using three methods to support knowledge/data base growth, to track the model evolution, and to handle knowledge from diverse domains. First, the representation methodology is based on having pools, or types, of knowledge from which each model is constructed. In addition information is explicit. This includes the interactions between components, the description of the artifact structure, and the constraints and limitations of the models. The third principle we have followed is the separation of the data and knowledge from the inferencing and equation solving mechanisms. This methodology is used in two distinct knowledge-based systems: one for the design of space systems and another for the synthesis of VLSI circuits. It has facilitated the growth and evolution of our models, made accountability of results explicit, and provided credibility for the user community. These capabilities have been implemented and are being used in actual design projects.

MANAGEMENT OF A GUILLAIN BARRE SYNDROME PATIENT THROUGH THREE TRACK REASONING: A CASE STUDY

OpenAIRE

Shamima Islam Nipa; Mohammad Mustafa Kamal Rahat Khan; Mohammad Sohrab Hossain; Mohammad Habibur Rahman; Md. Shofiqul Islam

2015-01-01

Background: Clinical reasoning is a thinking and decision making process which occur in clinical practice. It helps the health care providers to solve the clinical problem by using their reasoning process in an effective and efficient manner. Three track reasoning in one of the clinical reasoning process which includes the procedural, interactive and conditional reasoning to diagnose as well as ensure proper rehabilitation service according to patient and patient’s family members’ needs. M...

Measuring scientific reasoning through behavioral analysis in a computer-based problem solving exercise

Science.gov (United States)

Mead, C.; Horodyskyj, L.; Buxner, S.; Semken, S. C.; Anbar, A. D.

2016-12-01

Developing scientific reasoning skills is a common learning objective for general-education science courses. However, effective assessments for such skills typically involve open-ended questions or tasks, which must be hand-scored and may not be usable online. Using computer-based learning environments, reasoning can be assessed automatically by analyzing student actions within the learning environment. We describe such an assessment under development and present pilot results. In our content-neutral instrument, students solve a problem by collecting and interpreting data in a logical, systematic manner. We then infer reasoning skill automatically based on student actions. Specifically, students investigate why Earth has seasons, a scientifically simple but commonly misunderstood topic. Students are given three possible explanations and asked to select a set of locations on a world map from which to collect temperature data. They then explain how the data support or refute each explanation. The best approaches will use locations in both the Northern and Southern hemispheres to argue that the contrasting seasonality of the hemispheres supports only the correct explanation. We administered a pilot version to students at the beginning of an online, introductory science course (n = 223) as an optional extra credit exercise. We were able to categorize students' data collection decisions as more and less logically sound. Students who choose the most logical measurement locations earned higher course grades, but not significantly higher. This result is encouraging, but not definitive. In the future, we will clarify our results in two ways. First, we plan to incorporate more open-ended interactions into the assessment to improve the resolving power of this tool. Second, to avoid relying on course grades, we will independently measure reasoning skill with one of the existing hand-scored assessments (e.g., Critical Thinking Assessment Test) to cross-validate our new

Structural logical relations with case analysis and equality reasoning

DEFF Research Database (Denmark)

Rasmussen, Ulrik Terp; Filinski, Andrzej

2013-01-01

requires the assertion logic to be extended with reasoning principles not present in the original presentation of the formalization method. We address this by generalizing the assertion logic to include dependent sorts, and demonstrate that the original cut elimination proof continues to apply without...

Scientific Reasoning and Its Relationship with Problem Solving: The Case of Upper Primary Science Teachers

Science.gov (United States)

Alshamali, Mahmoud A.; Daher, Wajeeh M.

2016-01-01

This study aimed at identifying the levels of scientific reasoning of upper primary stage (grades 4-7) science teachers based on their use of a problem-solving strategy. The study sample (N = 138; 32 % male and 68 % female) was randomly selected using stratified sampling from an original population of 437 upper primary school teachers. The…

["As Good as it Gets at Home" - Reasons for Institutionalisation in Dementia].

Science.gov (United States)

Grau, H; Berth, H; Lauterberg, J; Holle, R; Gräßel, E

2016-09-01

What are the reasons for institutionalising community-dwelling persons with dementia? A written survey of family caregivers and general practitioners was undertaken. Within 2 years 47 of 351 people with dementia (13%) were institutionalised. The person with dementia was involved in the decision in only 1/3 of the cases. The 3 most common reasons were: ensuring the best possible care, high expenditure of care-giving time at home, deterioration of the health of the care-receiver. From the ethical point of view the exclusion of the persons with dementia from the decision-making with regard to institutionalisation has to be examined critically. The often given reason of ensuring the best possible care through institutionalisation could be counteracted by the improvement of community-based care. © Georg Thieme Verlag KG Stuttgart · New York.

Robotics Vision-based Heuristic Reasoning for Underwater Target Tracking and Navigation

Directory of Open Access Journals (Sweden)

Chua Kia

2005-09-01

Full Text Available This paper presents a robotics vision-based heuristic reasoning system for underwater target tracking and navigation. This system is introduced to improve the level of automation of underwater Remote Operated Vehicles (ROVs operations. A prototype which combines computer vision with an underwater robotics system is successfully designed and developed to perform target tracking and intelligent navigation. This study focuses on developing image processing algorithms and fuzzy inference system for the analysis of the terrain. The vision system developed is capable of interpreting underwater scene by extracting subjective uncertainties of the object of interest. Subjective uncertainties are further processed as multiple inputs of a fuzzy inference system that is capable of making crisp decisions concerning where to navigate. The important part of the image analysis is morphological filtering. The applications focus on binary images with the extension of gray-level concepts. An open-loop fuzzy control system is developed for classifying the traverse of terrain. The great achievement is the system's capability to recognize and perform target tracking of the object of interest (pipeline in perspective view based on perceived condition. The effectiveness of this approach is demonstrated by computer and prototype simulations. This work is originated from the desire to develop robotics vision system with the ability to mimic the human expert's judgement and reasoning when maneuvering ROV in the traverse of the underwater terrain.

Robotics Vision-based Heuristic Reasoning for Underwater Target Tracking and Navigation

Directory of Open Access Journals (Sweden)

Chua Kia

2008-11-01

Full Text Available This paper presents a robotics vision-based heuristic reasoning system for underwater target tracking and navigation. This system is introduced to improve the level of automation of underwater Remote Operated Vehicles (ROVs operations. A prototype which combines computer vision with an underwater robotics system is successfully designed and developed to perform target tracking and intelligent navigation. This study focuses on developing image processing algorithms and fuzzy inference system for the analysis of the terrain. The vision system developed is capable of interpreting underwater scene by extracting subjective uncertainties of the object of interest. Subjective uncertainties are further processed as multiple inputs of a fuzzy inference system that is capable of making crisp decisions concerning where to navigate. The important part of the image analysis is morphological filtering. The applications focus on binary images with the extension of gray-level concepts. An open-loop fuzzy control system is developed for classifying the traverse of terrain. The great achievement is the system's capability to recognize and perform target tracking of the object of interest (pipeline in perspective view based on perceived condition. The effectiveness of this approach is demonstrated by computer and prototype simulations. This work is originated from the desire to develop robotics vision system with the ability to mimic the human expert's judgement and reasoning when maneuvering ROV in the traverse of the underwater terrain.

Conscientious refusals and reason-giving.

Science.gov (United States)

Marsh, Jason

2014-07-01

Some philosophers have argued for what I call the reason-giving requirement for conscientious refusal in reproductive healthcare. According to this requirement, healthcare practitioners who conscientiously object to administering standard forms of treatment must have arguments to back up their conscience, arguments that are purely public in character. I argue that such a requirement, though attractive in some ways, faces an overlooked epistemic problem: it is either too easy or too difficult to satisfy in standard cases. I close by briefly considering whether a version of the reason-giving requirement can be salvaged despite this important difficulty. © 2013 John Wiley & Sons Ltd.

An Automated Approach to Reasoning Under Multiple Perspectives

Science.gov (United States)

deBessonet, Cary

2004-01-01

This is the final report with emphasis on research during the last term. The context for the research has been the development of an automated reasoning technology for use in SMS (symbolic Manipulation System), a system used to build and query knowledge bases (KBs) using a special knowledge representation language SL (Symbolic Language). SMS interpreters assertive SL input and enters the results as components of its universe. The system operates in two basic models: 1) constructive mode (for building KBs); and 2) query/search mode (for querying KBs). Query satisfaction consists of matching query components with KB components. The system allows "penumbral matches," that is, matches that do not exactly meet the specifications of the query, but which are deemed relevant for the conversational context. If the user wants to know whether SMS has information that holds, say, for "any chow," the scope of relevancy might be set so that the system would respond based on a finding that it has information that holds for "most dogs," although this is not exactly what was called for by the query. The response would be qualified accordingly, as would normally be the case in ordinary human conversation. The general goal of the research was to develop an approach by which assertive content could be interpreted from multiple perspectives so that reasoning operations could be successfully conducted over the results. The interpretation of an SL statement such as, "{person believes [captain (asserted (perhaps)) (astronaut saw (comet (bright)))]}," which in English would amount to asserting something to the effect that, "Some person believes that a captain perhaps asserted that an astronaut saw a bright comet," would require the recognition of multiple perspectives, including some that are: a) epistemically-based (focusing on "believes"); b) assertion-based (focusing on "asserted"); c) perception-based (focusing on "saw"); d) adjectivally-based (focusing on "bight"); and e) modally-based

Knowledge engineering tools for reasoning with scientific observations and interpretations: a neural connectivity use case.

Science.gov (United States)

Russ, Thomas A; Ramakrishnan, Cartic; Hovy, Eduard H; Bota, Mihail; Burns, Gully A P C

2011-08-22

We address the goal of curating observations from published experiments in a generalizable form; reasoning over these observations to generate interpretations and then querying this interpreted knowledge to supply the supporting evidence. We present web-application software as part of the 'BioScholar' project (R01-GM083871) that fully instantiates this process for a well-defined domain: using tract-tracing experiments to study the neural connectivity of the rat brain. The main contribution of this work is to provide the first instantiation of a knowledge representation for experimental observations called 'Knowledge Engineering from Experimental Design' (KEfED) based on experimental variables and their interdependencies. The software has three parts: (a) the KEfED model editor - a design editor for creating KEfED models by drawing a flow diagram of an experimental protocol; (b) the KEfED data interface - a spreadsheet-like tool that permits users to enter experimental data pertaining to a specific model; (c) a 'neural connection matrix' interface that presents neural connectivity as a table of ordinal connection strengths representing the interpretations of tract-tracing data. This tool also allows the user to view experimental evidence pertaining to a specific connection. BioScholar is built in Flex 3.5. It uses Persevere (a noSQL database) as a flexible data store and PowerLoom® (a mature First Order Logic reasoning system) to execute queries using spatial reasoning over the BAMS neuroanatomical ontology. We first introduce the KEfED approach as a general approach and describe its possible role as a way of introducing structured reasoning into models of argumentation within new models of scientific publication. We then describe the design and implementation of our example application: the BioScholar software. This is presented as a possible biocuration interface and supplementary reasoning toolkit for a larger, more specialized bioinformatics system: the Brain

Teaching Inductive Reasoning in Primary Education.

Science.gov (United States)

de Koning, Els; Hamers, Jo H. M.; Sijtsma, Klaas; Vermeer, Adri

2002-01-01

Used a three-phase teaching procedure based on the development of metacognition to extend emphasis on inductive reasoning in primary education to Grades 3 and 4. Found that teachers could apply the programs as intended, but needed support to shift attention from reasoning product to reasoning process. Program learning effects indicated that better…

26 CFR 1.412(c)(3)-1 - Reasonable funding methods.

Science.gov (United States)

2010-04-01

... 26 Internal Revenue 5 2010-04-01 2010-04-01 false Reasonable funding methods. 1.412(c)(3)-1... Reasonable funding methods. (a) Introduction—(1) In general. This section prescribes rules for determining whether or not, in the case of an ongoing plan, a funding method is reasonable for purposes of section 412...

[Acquiring skills in malignant hyperthermia crisis management: comparison of high-fidelity simulation versus computer-based case study].

Science.gov (United States)

Mejía, Vilma; Gonzalez, Carlos; Delfino, Alejandro E; Altermatt, Fernando R; Corvetto, Marcia A

The primary purpose of this study was to compare the effect of high fidelity simulation versus a computer-based case solving self-study, in skills acquisition about malignant hyperthermia on first year anesthesiology residents. After institutional ethical committee approval, 31 first year anesthesiology residents were enrolled in this prospective randomized single-blinded study. Participants were randomized to either a High Fidelity Simulation Scenario or a computer-based Case Study about malignant hyperthermia. After the intervention, all subjects' performance in was assessed through a high fidelity simulation scenario using a previously validated assessment rubric. Additionally, knowledge tests and a satisfaction survey were applied. Finally, a semi-structured interview was done to assess self-perception of reasoning process and decision-making. 28 first year residents finished successfully the study. Resident's management skill scores were globally higher in High Fidelity Simulation versus Case Study, however they were significant in 4 of the 8 performance rubric elements: recognize signs and symptoms (p = 0.025), prioritization of initial actions of management (p = 0.003), recognize complications (p = 0.025) and communication (p = 0.025). Average scores from pre- and post-test knowledge questionnaires improved from 74% to 85% in the High Fidelity Simulation group, and decreased from 78% to 75% in the Case Study group (p = 0.032). Regarding the qualitative analysis, there was no difference in factors influencing the student's process of reasoning and decision-making with both teaching strategies. Simulation-based training with a malignant hyperthermia high-fidelity scenario was superior to computer-based case study, improving knowledge and skills in malignant hyperthermia crisis management, with a very good satisfaction level in anesthesia residents. Copyright © 2018 Sociedade Brasileira de Anestesiologia. Publicado por Elsevier Editora Ltda. All rights

The role of ethics in information technology decisions: a case-based approach to biomedical informatics education.

Science.gov (United States)

Anderson, James G

2004-03-18

The purpose of this paper is to propose a case-based approach to instruction regarding ethical issues raised by the use of information technology (IT) in healthcare. These issues are rarely addressed in graduate degree and continuing professional education programs in health informatics. There are important reasons why ethical issues need to be addressed in informatics training. Ethical issues raised by the introduction of information technology affect practice and are ubiquitous. These issues are frequently among the most challenging to young practitioners who are ill prepared to deal with them in practice. First, the paper provides an overview of methods of moral reasoning that can be used to identify and analyze ethical problems in health informatics. Second, we provide a framework for defining cases that involve ethical issues and outline major issues raised by the use of information technology. Specific cases are used as examples of new dilemmas that are posed by the introduction of information technology in healthcare. These cases are used to illustrate how ethics can be integrated with the other elements of informatics training. The cases discussed here reflect day-to-day situations that arise in health settings that require decisions. Third, an approach that can be used to teach ethics in health informatics programs is outlined and illustrated.

Competent Reasoning with Rational Numbers.

Science.gov (United States)

Smith, John P. III

1995-01-01

Analyzed students' reasoning with fractions. Found that skilled students applied strategies specifically tailored to restricted classes of fractions and produced reliable solutions with a minimum of computation effort. Results suggest that competent reasoning depends on a knowledge base that includes numerically specific and invented strategies,…

THE EFFECT OF INQUIRY BASED LEARNING ON THE REASONING ABILITY OF GRADE VII STUDENTS ABOUT HEAT CONCEPT

Directory of Open Access Journals (Sweden)

N. A. C. Damawati

2016-01-01

Full Text Available This study aimed to analyze the effect of Inquiry Based Learningon the reasoning ability of grade 7 students about heat concept. This study is a quasi-experimental research design with non-equivalent post-test only controls group design. Two groups of seventh grade students were included as samples, which receive the experimental class of Inquiry Based Learning treatment while the other group acted as a control group who received the learning process in accordance with the applicable provisions of the curriculum. The data collected in this study is the students reasoning ability which obtained from the test of reasoning ability. Data were analyzed using descriptive statistics and statistical parametric t-test. Results of independet research shows that there are significant differences in reasoning abilities between the experimental class and control class. In this research, the experiment class perform more better reasoning skills than the control class.Penelitian ini bertujuan untuk menganalisis pengaruh Inquiry Based Learning terhadap kemampuan penalaran siswa kelas VII pada materi Kalor. Penelitian ini merupakan penelitian eksperimen semu dengan rancangan non-equivalent post-test only control group design.  Dua kelompok siswa kelas VII  dilibatkan sebagai sampel penelitian, dimana kelas eksperimen menerima perlakuan Inquiry Based Learning sementara kelompok lainnya bertindak sebagai kelas kontrol yang menerima proses pembelajaran sesuai dengan ketentuan kurikulum yang berlaku di sekolah tempat penelitian dilaksanakan. Data yang dikumpulkan dalam penelitian ini adalah kemampuan penalaran siswa yang diperoleh dari hasil tes kemampuan penalaran. Data dianalisis dengan menggunakan statistik deskriptif dan statistik parametrik Independent t-test. Hasil penelitian menunjukkan bahwa terdapat perbedaan kemampuan penalaran yang signifikan antara kelas eksperimen dan kelas kontrol Kelas eksperimen menunjukkan kemampuan penalaran yang lebih baik

Design for reasoning

DEFF Research Database (Denmark)

Christiansen, Ellen Tove

2009-01-01

The aim of this paper is to position interaction design and information architecture in relation to design of interfaces to ICT applications meant to serve the goal of supporting users’ reasoning, be it learning applications or self-service applications such as citizen self-service. Interaction...... with such applications comprises three forms of reasoning: deduction, induction and abduction. Based on the work of Gregory Bateson, it is suggested that the disciplines of interaction design and information architecture are complementary parts of information processes. To show that abduction, induction and deduction...

Reasons Internalism and the function of normative reasons

OpenAIRE

Sinclair, Neil

2017-01-01

What is the connection between reasons and motives? According to Reasons Internalism there is a non-trivial conceptual connection between normative reasons and the possibility of rationally accessing relevant motivation. Reasons Internalism is attractive insofar as it captures the thought that reasons are for reasoning with and repulsive insofar as it fails to generate sufficient critical distance between reasons and motives. Rather than directly adjudicate this dispute, I extract from it two...

Theoretical and practical significance of formal reasoning

Science.gov (United States)

Linn, Marcia C.

Piaget's theory has profoundly influenced science education research. Following Piaget, researchers have focused on content-free strategies, developmentally based mechanisms, and structural models of each stage of reasoning. In practice, factors besides those considered in Piaget's theory influence whether or not a theoretically available strategy is used. Piaget's focus has minimized the research attention placed on what could be called practical factors in reasoning. Practical factors are factors that influence application of a theoretically available strategy, for example, previous experience with the task content, familiarity with task instructions, or personality style of the student. Piagetian theory has minimized the importance of practical factors and discouraged investigation of (1) the role of factual knowledge in reasoning, (2) the diagnosis of specific, task-based errors in reasoning, (3) the influence of individual aptitudes on reasoning (e.g., field dependence-independence), and (4) the effect of educational interventions designed to change reasoning. This article calls for new emphasis on practical factors in reasoning and suggests why research on practical factors in reasoning will enhance our understanding of how scientific reasoning is acquired and of how science education programs can foster it.

A Clinical Reasoning Tool for Virtual Patients: Design-Based Research Study.

Science.gov (United States)

Hege, Inga; Kononowicz, Andrzej A; Adler, Martin

2017-11-02

Clinical reasoning is a fundamental process medical students have to learn during and after medical school. Virtual patients (VP) are a technology-enhanced learning method to teach clinical reasoning. However, VP systems do not exploit their full potential concerning the clinical reasoning process; for example, most systems focus on the outcome and less on the process of clinical reasoning. Keeping our concept grounded in a former qualitative study, we aimed to design and implement a tool to enhance VPs with activities and feedback, which specifically foster the acquisition of clinical reasoning skills. We designed the tool by translating elements of a conceptual clinical reasoning learning framework into software requirements. The resulting clinical reasoning tool enables learners to build their patient's illness script as a concept map when they are working on a VP scenario. The student's map is compared with the experts' reasoning at each stage of the VP, which is technically enabled by using Medical Subject Headings, which is a comprehensive controlled vocabulary published by the US National Library of Medicine. The tool is implemented using Web technologies, has an open architecture that enables its integration into various systems through an open application program interface, and is available under a Massachusetts Institute of Technology license. We conducted usability tests following a think-aloud protocol and a pilot field study with maps created by 64 medical students. The results show that learners interact with the tool but create less nodes and connections in the concept map than an expert. Further research and usability tests are required to analyze the reasons. The presented tool is a versatile, systematically developed software component that specifically supports the clinical reasoning skills acquisition. It can be plugged into VP systems or used as stand-alone software in other teaching scenarios. The modular design allows an extension with new

Does Access Trump Ownership? Exploring Consumer Acceptance of Access-Based Consumption in the Case of Smartphones

Directory of Open Access Journals (Sweden)

Flora Poppelaars

2018-06-01

Full Text Available Value creation in a circular economy is based on products being returned after use. In the case of smartphones, most are never returned and tend to be kept in drawers. Smartphone access services (e.g., leasing or upgrade have been experimented with in the Netherlands but have been largely unsuccessful. This study explores the reasons why consumers rejected these access-based smartphone services and is one of the very few to address this topic. The findings are compared with the case of car access services, which are socially better accepted, to identify potential areas for improvement. The qualitative study consists of in-depth interviews with consumers (n = 18 who either adopted and used a smartphone or car access service, or had considered a new smartphone or car but did not choose access-based consumption. The findings of this small-scale study suggest that the main reasons for the rejection of smartphone access services are a lack of awareness, misunderstanding of terms and conditions, and unsatisfactory compensation for their sacrifice of not owning. Smartphone access providers could thus clearly communicate customers’ rights and responsibilities, offer an excellent service experience (especially during repair by taking over the burdens of ownership, and stimulate the societal logic shift from ownership to access.

Spatio-Temporal Neural Networks for Vision, Reasoning and Rapid Decision Making

Science.gov (United States)

1994-08-31

sports, art, and music trivia ; and our models of social and strengths and weaknesses. Typically, a node in a connec- civic interactions. tionist...connectionist interface that allows two phase-based modules, each with its own phase structure, 10.3. Now are phase recycle ? to exchange binding...interlinked chains of reasoning are required. In such cases, the set of entities in "focus’ must keep changing dynamically, recycling the available

Reasons for Whistleblowing: A Qualitative Study

Directory of Open Access Journals (Sweden)

Ali BALTACI

2017-04-01

Full Text Available Whistleblowing has become a commonly encountered concept in recent times. Negative behaviors and actions can be experienced in any organization, and whistleblowing, as a communication process, is a kind of ethical behavior. Whistleblowing is the transmission of an unfavorable situation discovered in the organization to either internal or external authorities. An examination of the reasons for the employee’s whistleblowing is important for a better understanding of this concept; hence, this research focuses on the reasons for whistleblowing. In addition, the reasons for avoiding whistleblowing were also investigated. This research, which is designed as a qualitative study, is based on the phenomenological approach. Interviews were conducted with open-ended, semi-structured interview form in the study. The research was conducted on 20 teachers, 12 administrators, and 7 inspectors. The data were analyzed using the content analysis method. As a result of the research, the individual, organizational and social reasons for whistleblowing have been differentiated. Among the individual reasons for whistleblowing are the considerations of protecting and gaining interests. Organizational reasons include business ethics and the expectation of subsequent promotion. Social reasons encompass social benefits, social justice, and religious belief. Reasons for avoiding whistleblowing vary based on retaliation and worry. This research is considered important because as it is believed to be the first qualitative research to approach the reasons for whistleblowing. The results of this research have revealed gaps in the understanding of this area for future studies.

A Framework for Assessing High School Students' Statistical Reasoning.

Science.gov (United States)

Chan, Shiau Wei; Ismail, Zaleha; Sumintono, Bambang

2016-01-01

Based on a synthesis of literature, earlier studies, analyses and observations on high school students, this study developed an initial framework for assessing students' statistical reasoning about descriptive statistics. Framework descriptors were established across five levels of statistical reasoning and four key constructs. The former consisted of idiosyncratic reasoning, verbal reasoning, transitional reasoning, procedural reasoning, and integrated process reasoning. The latter include describing data, organizing and reducing data, representing data, and analyzing and interpreting data. In contrast to earlier studies, this initial framework formulated a complete and coherent statistical reasoning framework. A statistical reasoning assessment tool was then constructed from this initial framework. The tool was administered to 10 tenth-grade students in a task-based interview. The initial framework was refined, and the statistical reasoning assessment tool was revised. The ten students then participated in the second task-based interview, and the data obtained were used to validate the framework. The findings showed that the students' statistical reasoning levels were consistent across the four constructs, and this result confirmed the framework's cohesion. Developed to contribute to statistics education, this newly developed statistical reasoning framework provides a guide for planning learning goals and designing instruction and assessments.

Signaling emotion and reason in cooperation.

Science.gov (United States)

Levine, Emma E; Barasch, Alixandra; Rand, David; Berman, Jonathan Z; Small, Deborah A

2018-05-01

We explore the signal value of emotion and reason in human cooperation. Across four experiments utilizing dyadic prisoner dilemma games, we establish three central results. First, individuals infer prosocial feelings and motivations from signals of emotion. As a result, individuals believe that a reliance on emotion signals that one will cooperate more so than a reliance on reason. Second, these beliefs are generally accurate-those who act based on emotion are more likely to cooperate than those who act based on reason. Third, individuals' behavioral responses towards signals of emotion and reason depend on their own decision mode: those who rely on emotion tend to conditionally cooperate (that is, cooperate only when they believe that their partner has cooperated), whereas those who rely on reason tend to defect regardless of their partner's signal. These findings shed light on how different decision processes, and lay theories about decision processes, facilitate and impede cooperation. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Case-Based Fault Diagnostic System

International Nuclear Information System (INIS)

Mohamed, A.H.

2014-01-01

Nowadays, case-based fault diagnostic (CBFD) systems have become important and widely applied problem solving technologies. They are based on the assumption that “similar faults have similar diagnosis”. On the other hand, CBFD systems still suffer from some limitations. Common ones of them are: (1) failure of CBFD to have the needed diagnosis for the new faults that have no similar cases in the case library. (2) Limited memorization when increasing the number of stored cases in the library. The proposed research introduces incorporating the neural network into the case based system to enable the system to diagnose all the faults. Neural networks have proved their success in the classification and diagnosis problems. The suggested system uses the neural network to diagnose the new faults (cases) that cannot be diagnosed by the traditional CBR diagnostic system. Besides, the proposed system can use the another neural network to control adding and deleting the cases in the library to manage the size of the cases in the case library. However, the suggested system has improved the performance of the case based fault diagnostic system when applied for the motor rolling bearing as a case of study

Internet-Based Asthma Education -- A Novel Approach to Compliance: A case Report

Directory of Open Access Journals (Sweden)

Cindy O'hara

2006-01-01

Full Text Available Asthma costs Canadians over $1.2 billion per annum and, despite advances, many asthmatic patients still have poor control. An action plan, symptom diary and measurement of peak expiratory flow have been shown to improve clinical outcomes. Effective educational interventions are an important component of good care. However, many rural sites lack not only access to education but physician care as well. It is reasonable, therefore, that an Internet-based asthma management program may be used as an approach. In the present case report, a novel approach that may increase access in these poorly serviced areas is presented. In an Internet-based asthma management program, patients are reviewed by a physician, receive education and are given a unique password that provides program access. Patients record symptoms and peak expiratory flow rates. The present case report shows that a patient can be assisted through an exacerbation, thus averting emergency intervention and stabilizing control, even when travelling on another continent.

Gaming and the Commodities Market: An Economic-Based Game for Developing Reasoning Skills

Science.gov (United States)

Witschonke, Christopher; Herrera, Jose Maria

2013-01-01

The authors describe an economics-based game they have developed to instruct student teachers in the value of games and gaming for developing reasoning and decision-making skills in economics in K-12 students (5-18-year-olds). The game is designed to progress through each grade level so that by high school students have a thorough appreciation and…

Application of plausible reasoning to AI-based control systems

Science.gov (United States)

Berenji, Hamid; Lum, Henry, Jr.

1987-01-01

Some current approaches to plausible reasoning in artificial intelligence are reviewed and discussed. Some of the most significant recent advances in plausible and approximate reasoning are examined. A synergism among the techniques of uncertainty management is advocated, and brief discussions on the certainty factor approach, probabilistic approach, Dempster-Shafer theory of evidence, possibility theory, linguistic variables, and fuzzy control are presented. Some extensions to these methods are described, and the applications of the methods are considered.

The Role of Argumentation in Hypothetico-Deductive Reasoning during Problem-Based Learning in Medical Education: A Conceptual Framework

Science.gov (United States)

Ju, Hyunjung; Choi, Ikseon

2018-01-01

One of the important goals of problem-based learning (PBL) in medical education is to enhance medical students' clinical reasoning--hypothetico-deductive reasoning (HDR) in particular--through small group discussions. However, few studies have focused on explicit strategies for promoting students' HDR during group discussions in PBL. This paper…

Towards Automated Reasoning on ORM Schemes

Science.gov (United States)

Jarrar, Mustafa

The goal of this article is to formalize Object Role Modeling (ORM) using the {DLR} description logic. This would enable automated reasoning on the formal properties of ORM diagrams, such as detecting constraint contradictions and implications. In addition, the expressive, methodological, and graphical capabilities of ORM make it a good candidate for use as a graphical notation for most description logic languages. In this way, industrial experts who are not IT savvy will still be able to build and view axiomatized theories (such as ontologies, business rules, etc.) without needing to know the logic or reasoning foundations underpinning them. Our formalization in this paper is structured as 29 formalization rules, that map all ORM primitives and constraints into {DLR}, and 2 exceptions of complex cases. To this end, we illustrate the implementation of our formalization as an extension to DogmaModeler, which automatically maps ORM into DIG and uses Racer as a background reasoning engine to reason about ORM diagrams.

Case-Based Reasoning untuk Diagnosis Penyakit Jantung

Directory of Open Access Journals (Sweden)

Eka Wahyudi

2017-01-01

            The test results using medical records data validated by expert indicate that the system is able to recognize diseases heart using nearest neighbor similarity method, minskowski distance similarity and euclidean distance similarity correctly respectively of 100%. Using nearest neighbor get accuracy of 86.21%, minkowski 100%, and euclidean 94.83%

SemantGeo: Powering Ecological and Environment Data Discovery and Search with Standards-Based Geospatial Reasoning

Science.gov (United States)

Seyed, P.; Ashby, B.; Khan, I.; Patton, E. W.; McGuinness, D. L.

2013-12-01

Recent efforts to create and leverage standards for geospatial data specification and inference include the GeoSPARQL standard, Geospatial OWL ontologies (e.g., GAZ, Geonames), and RDF triple stores that support GeoSPARQL (e.g., AllegroGraph, Parliament) that use RDF instance data for geospatial features of interest. However, there remains a gap on how best to fuse software engineering best practices and GeoSPARQL within semantic web applications to enable flexible search driven by geospatial reasoning. In this abstract we introduce the SemantGeo module for the SemantEco framework that helps fill this gap, enabling scientists find data using geospatial semantics and reasoning. SemantGeo provides multiple types of geospatial reasoning for SemantEco modules. The server side implementation uses the Parliament SPARQL Endpoint accessed via a Tomcat servlet. SemantGeo uses the Google Maps API for user-specified polygon construction and JsTree for providing containment and categorical hierarchies for search. SemantGeo uses GeoSPARQL for spatial reasoning alone and in concert with RDFS/OWL reasoning capabilities to determine, e.g., what geofeatures are within, partially overlap with, or within a certain distance from, a given polygon. We also leverage qualitative relationships defined by the Gazetteer ontology that are composites of spatial relationships as well as administrative designations or geophysical phenomena. We provide multiple mechanisms for exploring data, such as polygon (map-based) and named-feature (hierarchy-based) selection, that enable flexible search constraints using boolean combination of selections. JsTree-based hierarchical search facets present named features and include a 'part of' hierarchy (e.g., measurement-site-01, Lake George, Adirondack Region, NY State) and type hierarchies (e.g., nodes in the hierarchy for WaterBody, Park, MeasurementSite), depending on the ';axis of choice' option selected. Using GeoSPARQL and aforementioned ontology

Partial logics with two kinds of negation as a foundation for knowledge-based reasoning

NARCIS (Netherlands)

H. Herre; J.O.M. Jaspars; G. Wagner

1995-01-01

textabstractWe show how to use model classes of partial logic to define semantics of general knowledge-based reasoning. Its essential benefit is that partial logics allow us to distinguish two sorts of negative information: the absence of information and the explicit rejection or falsification of

Clinical reasoning and population health: decision making for an emerging paradigm of health care.

Science.gov (United States)

Edwards, Ian; Richardson, Barbara

2008-01-01

Chronic conditions now provide the major disease and disability burden facing humanity. This development has necessitated a reorientation in the practice skills of health care professions away from hospital-based inpatient and outpatient care toward community-based management of patients with chronic conditions. Part of this reorientation toward community-based management of chronic conditions involves practitioners' understanding and adoption of a concept of population health management based on appropriate theoretical models of health care. Drawing on recent studies of expertise in physiotherapy, this article proposes a clinical reasoning and decision-making framework to meet these challenges. The challenge of population and community-based management of chronic conditions also provides an opportunity for physiotherapists to further clarify a professional epistemology of practice that embraces the kinds of knowledge and clinical reasoning processes used in physiotherapy practice. Three case studies related to the management of chronic musculoskeletal pain in different populations are used to exemplify the range of epistemological perspectives that underpin community-based practice. They illustrate the link between conceptualizations of practice problems and knowledge sources that are used as a basis for clinical reasoning and decision making as practitioners are increasingly required to move between the clinic and the community.

Knowledge engineering tools for reasoning with scientific observations and interpretations: a neural connectivity use case

Directory of Open Access Journals (Sweden)

Bota Mihail

2011-08-01

Full Text Available Abstract Background We address the goal of curating observations from published experiments in a generalizable form; reasoning over these observations to generate interpretations and then querying this interpreted knowledge to supply the supporting evidence. We present web-application software as part of the 'BioScholar' project (R01-GM083871 that fully instantiates this process for a well-defined domain: using tract-tracing experiments to study the neural connectivity of the rat brain. Results The main contribution of this work is to provide the first instantiation of a knowledge representation for experimental observations called 'Knowledge Engineering from Experimental Design' (KEfED based on experimental variables and their interdependencies. The software has three parts: (a the KEfED model editor - a design editor for creating KEfED models by drawing a flow diagram of an experimental protocol; (b the KEfED data interface - a spreadsheet-like tool that permits users to enter experimental data pertaining to a specific model; (c a 'neural connection matrix' interface that presents neural connectivity as a table of ordinal connection strengths representing the interpretations of tract-tracing data. This tool also allows the user to view experimental evidence pertaining to a specific connection. BioScholar is built in Flex 3.5. It uses Persevere (a noSQL database as a flexible data store and PowerLoom® (a mature First Order Logic reasoning system to execute queries using spatial reasoning over the BAMS neuroanatomical ontology. Conclusions We first introduce the KEfED approach as a general approach and describe its possible role as a way of introducing structured reasoning into models of argumentation within new models of scientific publication. We then describe the design and implementation of our example application: the BioScholar software. This is presented as a possible biocuration interface and supplementary reasoning toolkit for a larger

Knowledge engineering tools for reasoning with scientific observations and interpretations: a neural connectivity use case

Science.gov (United States)

2011-01-01

Background We address the goal of curating observations from published experiments in a generalizable form; reasoning over these observations to generate interpretations and then querying this interpreted knowledge to supply the supporting evidence. We present web-application software as part of the 'BioScholar' project (R01-GM083871) that fully instantiates this process for a well-defined domain: using tract-tracing experiments to study the neural connectivity of the rat brain. Results The main contribution of this work is to provide the first instantiation of a knowledge representation for experimental observations called 'Knowledge Engineering from Experimental Design' (KEfED) based on experimental variables and their interdependencies. The software has three parts: (a) the KEfED model editor - a design editor for creating KEfED models by drawing a flow diagram of an experimental protocol; (b) the KEfED data interface - a spreadsheet-like tool that permits users to enter experimental data pertaining to a specific model; (c) a 'neural connection matrix' interface that presents neural connectivity as a table of ordinal connection strengths representing the interpretations of tract-tracing data. This tool also allows the user to view experimental evidence pertaining to a specific connection. BioScholar is built in Flex 3.5. It uses Persevere (a noSQL database) as a flexible data store and PowerLoom® (a mature First Order Logic reasoning system) to execute queries using spatial reasoning over the BAMS neuroanatomical ontology. Conclusions We first introduce the KEfED approach as a general approach and describe its possible role as a way of introducing structured reasoning into models of argumentation within new models of scientific publication. We then describe the design and implementation of our example application: the BioScholar software. This is presented as a possible biocuration interface and supplementary reasoning toolkit for a larger, more specialized

INTERSECTION DETECTION BASED ON QUALITATIVE SPATIAL REASONING ON STOPPING POINT CLUSTERS

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S. Zourlidou

2016-06-01

Full Text Available The purpose of this research is to propose and test a method for detecting intersections by analysing collectively acquired trajectories of moving vehicles. Instead of solely relying on the geometric features of the trajectories, such as heading changes, which may indicate turning points and consequently intersections, we extract semantic features of the trajectories in form of sequences of stops and moves. Under this spatiotemporal prism, the extracted semantic information which indicates where vehicles stop can reveal important locations, such as junctions. The advantage of the proposed approach in comparison with existing turning-points oriented approaches is that it can detect intersections even when not all the crossing road segments are sampled and therefore no turning points are observed in the trajectories. The challenge with this approach is that first of all, not all vehicles stop at the same location – thus, the stop-location is blurred along the direction of the road; this, secondly, leads to the effect that nearby junctions can induce similar stop-locations. As a first step, a density-based clustering is applied on the layer of stop observations and clusters of stop events are found. Representative points of the clusters are determined (one per cluster and in a last step the existence of an intersection is clarified based on spatial relational cluster reasoning, with which less informative geospatial clusters, in terms of whether a junction exists and where its centre lies, are transformed in more informative ones. Relational reasoning criteria, based on the relative orientation of the clusters with their adjacent ones are discussed for making sense of the relation that connects them, and finally for forming groups of stop events that belong to the same junction.

A Priori Knowledge and Heuristic Reasoning in Architectural Design.

Science.gov (United States)

Rowe, Peter G.

1982-01-01

It is proposed that the various classes of a priori knowledge incorporated in heuristic reasoning processes exert a strong influence over architectural design activity. Some design problems require exercise of some provisional set of rules, inference, or plausible strategy which requires heuristic reasoning. A case study illustrates this concept.…

The ethical reasoning variations of personal characteristics

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Khalizani Khalid

2012-06-01

Full Text Available This study provides a comparison of the ethical reasoning components of business managers and executives based on personal characteristics of working experiences, gender and age group. Data were collected in Malaysia within the small and medium sized industry in the form of questionnaires which contain vignettes of questionable ethical reasoning issues. Factor analysis was used to identify the major ethical reasoning dimensions which were then used as the basic comparison. Our study reviews that SMEs managers’ and executives’ ethical reasoning influenced by their years of working experiences. The gap analysis between male and female managers and executives revealed that the significant difference only occurs for ethical awareness in business management and business practices but not for other dimensions. Besides, there are indications that generally, business people tend to have higher ethical reasoning evaluation when they reach thirty six years old. Based on our results, recommendations are made to improve the ethical reasoning evaluation of business managers and executives.

A population-based investigation into the self-reported reasons for sleep problems.

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David Armstrong

Full Text Available Typologies of sleep problems have usually relied on identifying underlying causes or symptom clusters. In this study the value of using the patient's own reasons for sleep disturbance are explored. Using secondary data analysis of a nationally representative psychiatric survey the patterning of the various reasons respondents provided for self-reported sleep problems were examined. Over two thirds (69.3% of respondents could identify a specific reason for their sleep problem with worry (37.9% and illness (20.1% representing the most commonly reported reasons. And while women reported more sleep problems for almost every reason compared with men, the patterning of reasons by age showed marked variability. Sleep problem symptoms such as difficulty getting to sleep or waking early also showed variability by different reasons as did the association with major correlates such as worry, depression, anxiety and poor health. While prevalence surveys of 'insomnia' or 'poor sleep' often assume the identification of an underlying homogeneous construct there may be grounds for recognising the existence of different sleep problem types particularly in the context of the patient's perceived reason for the problem.

Virtual patients design and its effect on clinical reasoning and student experience: a protocol for a randomised factorial multi-centre study

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Bateman James

2012-08-01

Full Text Available Abstract Background Virtual Patients (VPs are web-based representations of realistic clinical cases. They are proposed as being an optimal method for teaching clinical reasoning skills. International standards exist which define precisely what constitutes a VP. There are multiple design possibilities for VPs, however there is little formal evidence to support individual design features. The purpose of this trial is to explore the effect of two different potentially important design features on clinical reasoning skills and the student experience. These are the branching case pathways (present or absent and structured clinical reasoning feedback (present or absent. Methods/Design This is a multi-centre randomised 2x2 factorial design study evaluating two independent variables of VP design, branching (present or absent, and structured clinical reasoning feedback (present or absent.The study will be carried out in medical student volunteers in one year group from three university medical schools in the United Kingdom, Warwick, Keele and Birmingham. There are four core musculoskeletal topics. Each case can be designed in four different ways, equating to 16 VPs required for the research. Students will be randomised to four groups, completing the four VP topics in the same order, but with each group exposed to a different VP design sequentially. All students will be exposed to the four designs. Primary outcomes are performance for each case design in a standardized fifteen item clinical reasoning assessment, integrated into each VP, which is identical for each topic. Additionally a 15-item self-reported evaluation is completed for each VP, based on a widely used EViP tool. Student patterns of use of the VPs will be recorded. In one centre, formative clinical and examination performance will be recorded, along with a self reported pre and post-intervention reasoning score, the DTI. Our power calculations indicate a sample size of 112 is required for

Advances in Reasoning-Based Image Processing Intelligent Systems Conventional and Intelligent Paradigms

CERN Document Server

Nakamatsu, Kazumi

2012-01-01

The book puts special stress on the contemporary techniques for reasoning-based image processing and analysis: learning based image representation and advanced video coding; intelligent image processing and analysis in medical vision systems; similarity learning models for image reconstruction; visual perception for mobile robot motion control, simulation of human brain activity in the analysis of video sequences; shape-based invariant features extraction; essential of paraconsistent neural networks, creativity and intelligent representation in computational systems. The book comprises 14 chapters. Each chapter is a small monograph, representing resent investigations of authors in the area. The topics of the chapters cover wide scientific and application areas and complement each-other very well. The chapters’ content is based on fundamental theoretical presentations, followed by experimental results and comparison with similar techniques. The size of the chapters is well-ballanced which permits a thorough ...

Evolutions in clinical reasoning assessment: The Evolving Script Concordance Test.

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Cooke, Suzette; Lemay, Jean-François; Beran, Tanya

2017-08-01

Script concordance testing (SCT) is a method of assessment of clinical reasoning. We developed a new type of SCT case design, the evolving SCT (E-SCT), whereby the patient's clinical story is "evolving" and with thoughtful integration of new information at each stage, decisions related to clinical decision-making become increasingly clear. We aimed to: (1) determine whether an E-SCT could differentiate clinical reasoning ability among junior residents (JR), senior residents (SR), and pediatricians, (2) evaluate the reliability of an E-SCT, and (3) obtain qualitative feedback from participants to help inform the potential acceptability of the E-SCT. A 12-case E-SCT, embedded within a 24-case pediatric SCT (PaedSCT), was administered to 91 pediatric residents (JR: n = 50; SR: n = 41). A total of 21 pediatricians served on the panel of experts (POE). A one-way analysis of variance (ANOVA) was conducted across the levels of experience. Participants' feedback on the E-SCT was obtained with a post-test survey and analyzed using two methods: percentage preference and thematic analysis. Statistical differences existed across levels of training: F = 19.31 (df = 2); p decision-making process. The E-SCT demonstrated very good reliability and was effective in distinguishing clinical reasoning ability across three levels of experience. Participants found the E-SCT engaging and representative of real-life clinical reasoning and decision-making processes. We suggest that further refinement and utilization of the evolving style case will enhance SCT as a robust, engaging, and relevant method for the assessment of clinical reasoning.

Medication Error, What Is the Reason?

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Ali Banaozar Mohammadi

2015-09-01

Full Text Available Background: Medication errors due to different reasons may alter the outcome of all patients, especially patients with drug poisoning. We introduce one of the most common type of medication error in the present article. Case:A 48 year old woman with suspected organophosphate poisoning was died due to lethal medication error. Unfortunately these types of errors are not rare and had some preventable reasons included lack of suitable and enough training and practicing of medical students and some failures in medical students’ educational curriculum. Conclusion:Hereby some important reasons are discussed because sometimes they are tre-mendous. We found that most of them are easily preventable. If someone be aware about the method of use, complications, dosage and contraindication of drugs, we can minimize most of these fatal errors.

Developing teaching material based on realistic mathematics andoriented to the mathematical reasoning and mathematical communication

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Fitria Habsah

2017-05-01

Full Text Available This research aims to produce mathematics textbook for grade VII junior high school students based on realistic mathematics and oriented to the mathematical reasoning and mathematical communication. The quality is determined based on Nieveen criteria, including validity, practicality, and effectiveness.This study was a research and development and used Borg & Gall model. The subject of this research were the students of SMPN 2 Pujon-Kabupaten Malang, that is 30 students in an experimental class (using the developed textbook and 29 students in a control class (using BSE book from the government. The teaching material was categorized valid if the expert's judgment at least is categorized as “good”. The teaching material was categorized practical if both of teachers and students assessment at least categorized as “good”. The teaching material was categorized effectively if minimum 75% of student scores at least is categorized as “good” for the mathematical reasoning test and mathematical communication test. This research resulted in a valid, practical, and effective teaching material. The resulted of the validation show that material teaching is valid. The resulted of teachers and students assessment show that the product is practical. The tests scores show that the product is effective. Percentage of students who categorized at least as “good” is 83,33% for the mathematical reasoning and 86,67% for the mathematical communication. The resulted of statistic test shows that the product more effective than the BSE book from the government in terms of mathematical reasoning and mathematical communication.

Case-based Agile Fixture Design

Institute of Scientific and Technical Information of China (English)

无

2001-01-01

In order to realize the agility of the fixture design, such asreconfigurability, rescalability and reusability, fixture structure is function unit-based decomposed from a fire-new point of view. Which makes it easy for agile fixture to be reconfigured and modified. Thereby, the base of case-based agile fixture design system info is established.Whole case-based agile fixture design model is presented. In which, three modules are added relative to the other models, including case matching of fixture planning module, conflict arbitration module and agile fixture case modify module. The three modules could solve the previous problem that the experience and result are difficult to be reused in the process of design.Two key techniques in the process of the agile fixture design, the evaluation of case similarity, and restriction-based conflict arbitration, are listed. And some methods are presented to evaluate the similarity and clear up the conflict.

Worked Examples Leads to Better Performance in Analyzing and Solving Real-Life Decision Cases

Science.gov (United States)

Cevik, Yasemin Demiraslan; Andre, Thomas

2012-01-01

This study compared the impact of three types of case-based methods (worked example, faded worked example, and case-based reasoning) on preservice teachers' (n=71) decision making and reasoning related to realistic classroom management situations. Participants in this study received a short-term implementation of one of these three major…

Intuitionistic Fuzzy Time Series Forecasting Model Based on Intuitionistic Fuzzy Reasoning

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Ya’nan Wang

2016-01-01

Full Text Available Fuzzy sets theory cannot describe the data comprehensively, which has greatly limited the objectivity of fuzzy time series in uncertain data forecasting. In this regard, an intuitionistic fuzzy time series forecasting model is built. In the new model, a fuzzy clustering algorithm is used to divide the universe of discourse into unequal intervals, and a more objective technique for ascertaining the membership function and nonmembership function of the intuitionistic fuzzy set is proposed. On these bases, forecast rules based on intuitionistic fuzzy approximate reasoning are established. At last, contrast experiments on the enrollments of the University of Alabama and the Taiwan Stock Exchange Capitalization Weighted Stock Index are carried out. The results show that the new model has a clear advantage of improving the forecast accuracy.

Writing Anxiety: A Case Study on Students’ Reasons for Anxiety in Writing

OpenAIRE

Kara, Selma

2013-01-01

The purpose of the present study was twofold. First, the present study set out to investigate the learners‟ attitudes towards academic writing courses that they have to take as part of their curriculum, whether they experience second language writing anxiety and what reasons they report for their anxiety and failure in academic writing courses. Second, the study aimed to develop a selfreport measure of second language writing anxiety reasons

Case - Case-Law - Law

DEFF Research Database (Denmark)

Sadl, Urska

2013-01-01

Reasoning of the Court of Justice of the European Union – Constr uction of arguments in the case-law of the Court – Citation technique – The use of formulas to transform case-law into ‘law’ – ‘Formulaic style’ – European citizenship as a fundamental status – Ruiz Zambrano – Reasoning from...

REASONS FOR TECHNOLOGY-BASED COMPANIES CONTEMPLATED BY THE FIRST COMPANY PROGRAM TO SEEK ISO 9001:2008 CERTIFICATION

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Eduardo Gomes Salgado

2016-03-01

Full Text Available The search for implementation of Quality Management Systems aims to continuously improve their results. Thus, for the services and/or products offered to convey trust and credibility, they must be designed within appropriate norms and standards. In this sense, this study seeks to assess the reasons that induce incubated technology-based companies to seek adequacy of their quality management system to the NBR ISO 9001:2008 standard. Through an exploratory survey in twenty-six incubated technology-based companies, a twelve-question questionnaire proposed by Bhuiyan and Alam (2005 was applied. After analyzing the data, it is concluded that the reasons for adequacy of QMS to the NBR ISO 9001:2008 standard are: competitive advantage over competitors; consultant´s approach for implementation; improvement in product quality; and government funding for ISO 9001 certification.  It is found that the consultant´s approach stands out as a strong reason for seeking the adequacy of QMS to the NBR ISO 9001 standard.

Internet-based Advertising Claims and Consumer Reasons for Using Electronic Cigarettes by Device Type in the US

OpenAIRE

Pulvers, K; Sun, JY; Zhuang, Y-L; Holguin, G; Zhu, S-H

2017-01-01

Objectives Important differences exist between closed-system and open-system e-cigarettes, but it is unknown whether online companies are marketing these devices differently and whether consumer reasons for using e-cigarettes vary by device type. This paper compares Internet-based advertising claims of closed- versus open-system products, and evaluates US consumers’ reasons for using closed- versus open-system e-cigarettes. Methods Internet sites selling exclusively closed (N = 130)...

Diagnostic reasoning using qualitative causal models

International Nuclear Information System (INIS)

Sudduth, A.L.

1992-01-01

The application of expert systems to reasoning problems involving real-time data from plant measurements has been a topic of much research, but few practical systems have been deployed. One obstacle to wider use of expert systems in applications involving real-time data is the lack of adequate knowledge representation methodologies for dynamic processes. Knowledge bases composed mainly of rules have disadvantages when applied to dynamic processes and real-time data. This paper describes a methodology for the development of qualitative causal models that can be used as knowledge bases for reasoning about process dynamic behavior. These models provide a systematic method for knowledge base construction, considerably reducing the engineering effort required. They also offer much better opportunities for verification and validation of the knowledge base, thus increasing the possibility of the application of expert systems to reasoning about mission critical systems. Starting with the Signed Directed Graph (SDG) method that has been successfully applied to describe the behavior of diverse dynamic processes, the paper shows how certain non-physical behaviors that result from abstraction may be eliminated by applying causal constraint to the models. The resulting Extended Signed Directed Graph (ESDG) may then be compiled to produce a model for use in process fault diagnosis. This model based reasoning methodology is used in the MOBIAS system being developed by Duke Power Company under EPRI sponsorship. 15 refs., 4 figs

Information systems outsourcing reasons and risks: a new assessment

OpenAIRE

González Ramírez, María Reyes; Gascó Gascó, José Luis; Llopis Taverner, Juan

2010-01-01

Outsourcing is currently going through a stage of unstoppable growth. This paper makes a proposal about the main reasons which may lead firms to adopt Outsourcing in Information Systems services. It will equally analyse the potential risks that IS clients are likely to face. An additional objective is to assess these reasons and risks in the case of large Spanish firms, while simultaneously examining their evolution over time. This study of outsourcing reasons and risks has been carried out f...

Reflexive reasoning for distributed real-time systems

Science.gov (United States)

Goldstein, David

1994-01-01

This paper discusses the implementation and use of reflexive reasoning in real-time, distributed knowledge-based applications. Recently there has been a great deal of interest in agent-oriented systems. Implementing such systems implies a mechanism for sharing knowledge, goals and other state information among the agents. Our techniques facilitate an agent examining both state information about other agents and the parameters of the knowledge-based system shell implementing its reasoning algorithms. The shell implementing the reasoning is the Distributed Artificial Intelligence Toolkit, which is a derivative of CLIPS.

Inverse reasoning processes in obsessive-compulsive disorder.

Science.gov (United States)

Wong, Shiu F; Grisham, Jessica R

2017-04-01

The inference-based approach (IBA) is one cognitive model that aims to explain the aetiology and maintenance of obsessive-compulsive disorder (OCD). The model proposes that certain reasoning processes lead an individual with OCD to confuse an imagined possibility with an actual probability, a state termed inferential confusion. One such reasoning process is inverse reasoning, in which hypothetical causes form the basis of conclusions about reality. Although previous research has found associations between a self-report measure of inferential confusion and OCD symptoms, evidence of a specific association between inverse reasoning and OCD symptoms is lacking. In the present study, we developed a task-based measure of inverse reasoning in order to investigate whether performance on this task is associated with OCD symptoms in an online sample. The results provide some evidence for the IBA assertion: greater endorsement of inverse reasoning was significantly associated with OCD symptoms, even when controlling for general distress and OCD-related beliefs. Future research is needed to replicate this result in a clinical sample and to investigate a potential causal role for inverse reasoning in OCD. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Effect of Origami-Based Instruction on Spatial Visualization, Geometry Achievement, and Geometric Reasoning

Science.gov (United States)

Arici, Sevil; Aslan-Tutak, Fatma

2015-01-01

This research study examined the effect of origami-based geometry instruction on spatial visualization, geometry achievement, and geometric reasoning of tenth-grade students in Turkey. The sample ("n" = 184) was chosen from a tenth-grade population of a public high school in Turkey. It was a quasi-experimental pretest/posttest design. A…

Performance-based assessment of scientific reasoning in children

NARCIS (Netherlands)

Lazonder, A.W.; Janssen, N.

2017-01-01

Recent longitudinal and cross-sectional studies have examined how scientific reasoning skills such as experimenting, making inferences and evaluating evidence develop in young science learners. Results, although informative, likely underestimate children’s true capabilities because data in these

Quantitative Reasoning and the Sine Function: The Case of Zac

Science.gov (United States)

Moore, Kevin C.

2014-01-01

A growing body of literature has identified quantitative and covariational reasoning as critical for secondary and undergraduate student learning, particularly for topics that require students to make sense of relationships between quantities. The present study extends this body of literature by characterizing an undergraduate precalculus…

CONFLICTING REASONS

OpenAIRE

Parfit, Derek

2016-01-01

Sidgwick believed that, when impartial reasons conflict with self-interested reasons, there are no truths about their relative strength. There are such truths, I claim, but these truths are imprecise. Many self-interested reasons are decisively outweighed by conflicting impar-tial moral reasons. But we often have sufficient self-interested reasons to do what would make things go worse, and we sometimes have sufficient self-interested reasons to act wrongly. If we reject Act Consequentialism, ...

Development and necessary norms of reasoning

Science.gov (United States)

Markovits, Henry

2014-01-01

The question of whether reasoning can, or should, be described by a single normative model is an important one. In the following, I combine epistemological considerations taken from Piaget’s notion of genetic epistemology, a hypothesis about the role of reasoning in communication and developmental data to argue that some basic logical principles are in fact highly normative. I argue here that explicit, analytic human reasoning, in contrast to intuitive reasoning, uniformly relies on a form of validity that allows distinguishing between valid and invalid arguments based on the existence of counterexamples to conclusions. PMID:24904501

Speed of reasoning and its relation to reasoning ability

NARCIS (Netherlands)

Goldhammer, F.; Klein Entink, R.H.

2011-01-01

The study investigates empirical properties of reasoning speed which is conceived as the fluency of solving reasoning problems. Responses and response times in reasoning tasks are modeled jointly to clarify the covariance structure of reasoning speed and reasoning ability. To determine underlying

Adult Gesture in Collaborative Mathematics Reasoning in Different Ages

Science.gov (United States)

Noto, M. S.; Harisman, Y.; Harun, L.; Amam, A.; Maarif, S.

2017-09-01

This article describes the case study on postgraduate students by using descriptive method. A problem is designed to facilitate the reasoning in the topic of Chi-Square test. The problem was given to two male students with different ages to investigate the gesture pattern and it will be related to their reasoning process. The indicators in reasoning problem can obtain the conclusion of analogy and generalization, and arrange the conjectures. This study refers to some questions—whether unique gesture is for every individual or to identify the pattern of the gesture used by the students with different ages. Reasoning problem was employed to collect the data. Two students were asked to collaborate to reason the problem. The discussion process recorded in using video tape to observe the gestures. The video recorded are explained clearly in this writing. Prosodic cues such as time, conversation text, gesture that appears, might help in understanding the gesture. The purpose of this study is to investigate whether different ages influences the maturity in collaboration observed from gesture perspective. The finding of this study shows that age is not a primary factor that influences the gesture in that reasoning process. In this case, adult gesture or gesture performed by order student does not show that he achieves, maintains, and focuses on the problem earlier on. Adult gesture also does not strengthen and expand the meaning if the student’s words or the language used in reasoning is not familiar for younger student. Adult gesture also does not affect cognitive uncertainty in mathematics reasoning. The future research is suggested to take more samples to find the consistency from that statement.

Applications of Case Based Organizational Memory Supported by the PAbMM Architecture

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Martín

2017-04-01

Full Text Available In the aim to manage and retrieve the organizational knowledge, in the last years numerous proposals of models and tools for knowledge management and knowledge representation have arisen. However, most of them store knowledge in a non-structured or semi-structured way, hindering the semantic and automatic processing of this knowledge. In this paper we present a more detailed case-based organizational memory ontology, which aims at contributing to the design of an organizational memory based on cases, so that it can be used to learn, reasoning, solve problems, and as support to better decision making as well. The objective of this Organizational Memory is to serve as base for the organizational knowledge exchange in a processing architecture specialized in the measurement and evaluation. In this way, our processing architecture is based on the C-INCAMI framework (Context-Information Need, Concept model, Attribute, Metric and Indicator for defining the measurement projects. Additionally, the proposal architecture uses a big data repository to make available the data for consumption and to manage the Organizational Memory, which allows a feedback mechanism in relation with online processing. In order to illustrate its utility, two practical cases are explained: A pasture predictor system, using the data of the weather radar (WR of the Experimental Agricultural Station (EAS INTA Anguil (La Pampa State, Argentina and an outpatient monitoring scenario. Future trends and concluding remarks are extended.

Elements Explaining Learning Clinical Reasoning Using Simulation Games

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Jaana-Maija Koivisto

2016-12-01

Full Text Available This article presents the findings on which elements in a game-based simulation affect learning clinical reasoning in nursing education. By using engaging gaming elements in virtual simulations and integrating the clinical reasoning process into game mechanics, games can enhance learning clinical reasoning and offer meaningful learning experiences. The study was designed to explore how nursing students experience gaming and learning when playing a simulation game, as well as which gaming elements explain learning clinical reasoning. The data was collected by questionnaire from nursing students (N = 166 in autumn 2014 over thirteen gaming sessions. The findings showed that usability, application of nursing knowledge, and exploration have the most impact on learning clinical reasoning when playing simulation games. Findings also revealed that authentic patient-related experiences, feedback, and reflection have an indirect effect on learning clinical reasoning. Based on these results, more efficient simulation games to improve clinical reasoning may be developed.   

The Development of Psychosomatic Reasoning in General Practitioners: An Empirical Study

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Alireza Monajemi

2017-08-01

Full Text Available Background: Monajemi, Goli, and Scheidt (2014 proposed a theory of development of psychosomatic (PSM reasoning. They hypothesized that the integration of psychosocial knowledge with biomedical (BM knowledge may have started at the level of GPs. An experimental study was conducted to explore and compare junior and senior practitioners regarding their shift from BM to PSM in terms of their decision-making.Methods: Two cases were presented to GPs in a sequential manner based on the reports of different settings (inpatient vs. outpatient. Each participant read each part of the case carefully in order to provide the management plan (Mx, determine which parts of the scenario were the most important, and write down, first, an explanatory model, and then, the management plan for the patient. The accuracy of item selection, explanatory models, and management plans were analysed.Results: GPs have already acquired some PSM knowledge, and thus, they will be able to differentiate between the two focuses (i.e., BM and PSM, but are not yet proficient enough to deal with a case in a PSM focus efficiently. This results in ineffective judgment. In other words, GPs discern the importance that should be given to psychosocial factors when examining their patients; however, they do not take into consideration such factors in the management plan.Conclusion: The results were largely in line with our assumptions based on the theory of the development of PSM reasoning; however, there is a definite need for more experimental studies here to support this argument.

Connecting Mathematics Learning through Spatial Reasoning

Science.gov (United States)

Mulligan, Joanne; Woolcott, Geoffrey; Mitchelmore, Michael; Davis, Brent

2018-01-01

Spatial reasoning, an emerging transdisciplinary area of interest to mathematics education research, is proving integral to all human learning. It is particularly critical to science, technology, engineering and mathematics (STEM) fields. This project will create an innovative knowledge framework based on spatial reasoning that identifies new…

A Framework of Mathematics Inductive Reasoning

Science.gov (United States)

Christou, Constantinos; Papageorgiou, Eleni

2007-01-01

Based on a synthesis of the literature in inductive reasoning, a framework for prescribing and assessing mathematics inductive reasoning of primary school students was formulated and validated. The major constructs incorporated in this framework were students' cognitive abilities of finding similarities and/or dissimilarities among attributes and…

Reason and Less

Directory of Open Access Journals (Sweden)

Vinod eGoel

2014-08-01

Full Text Available We consider ourselves to be rational beings. We feel that our choices, decisions, and actions are selected from a flexible array of possibilities, based upon reasons. When we vote for a political candidate, it is because they share our views on certain critical issues. When we hire an individual for a job, it is be-cause they are the best qualified. However, if this is true, why does an analysis of the direction of shift in the timbre of the voice of political candidates during an exchange or debate, predict the winner of American presidential elections? Why is it that while only 3% of the American population consists of white men over 6'4 tall, 30% of the CEOs of Fortune 500 companies are white men over 6'4 tall? These are examples of instinctual biases affecting or modulating rational thought processes. I argue that existing theories of reasoning cannot substantively accommodate these ubiquitous, real-world phe-nomena. Failure to recognize and incorporate these types of phenomena into the study of human reasoning results in a distorted understanding of rationality. The goal of the article is to draw attention to these types of phenomena and propose an adulterated rationality account of reasoning to explain them.

Reason and less.

Science.gov (United States)

Goel, Vinod

2014-01-01

We consider ourselves to be rational beings. We feel that our choices, decisions, and actions are selected from a flexible array of possibilities, based upon reasons. When we vote for a political candidate, it is because they share our views on certain critical issues. When we hire an individual for a job, it is because they are the best qualified. However, if this is true, why does an analysis of the direction of shift in the timbre of the voice of political candidates during an exchange or debate, predict the winner of American presidential elections? Why is it that while only 3% of the American population consists of white men over 6'4″ tall, 30% of the CEOs of Fortune 500 companies are white men over 6'4″ tall? These are examples of "instinctual biases" affecting or modulating rational thought processes. I argue that existing theories of reasoning cannot substantively accommodate these ubiquitous, real-world phenomena. Failure to recognize and incorporate these types of phenomena into the study of human reasoning results in a distorted understanding of rationality. The goal of this article is to draw attention to these types of phenomena and propose an "adulterated rationality" account of reasoning as a first step in trying to explain them.

Problem based learning (PBL) vs. Case based curriculum in clinical clerkship, Internal Medicine innovated Curriculum, Student prospective.

Science.gov (United States)

Aljarallah, Badr; Hassan, Mohammad Saleh

2015-04-01

The vast majority of PBL experience is in basic science courses. Application of classic Problem based learning in clerkship phase is challenging. Although the clinical case is considered a problem, yet solving this problem following the burrow's law has faced hurdles. The difficulties are facing the learner, the teacher and curricula. We implement innovative curriculum for the clerkship year in internal medicine course. We surveyed the student just before coming to an internal medicine course to ask them about continuing PBL or other types of learning in clinical years. A committee was created to study the possible ways to integrate PBL in the course. After multiple brainstorming meeting, an innovated curriculum was implemented. Student surveyed again after they completed their course. The survey is asking them about what is the effect of the implemented curriculum in their skills, attitude, and knowledge. 70% of Students, who finished their basic science in PBL, preferred not to have classical PBL, but more a clinical oriented case based curriculum in the clinical years. After this innovated curriculum, 50-60 % of students who completed it showed a positive response in all aspects of effects including skill, attitude, and knowledge. The Innovated curriculum includes daily morning report, 3 bedside teaching, investigation session, and clinical reasoning weekly, and Lectures up to twice a week. We suggest implementing a curriculum with PBL and case-based criteria in clinical phase are feasible, we are providing a framework with this innovated curriculum.

Argumentation, rationality, and psychology of reasoning

Directory of Open Access Journals (Sweden)

David Godden

2015-05-01

Full Text Available This paper explicates an account of argumentative rationality by articulating the common, basic idea of its nature, and then identifying a collection of assumptions inherent in it. Argumentative rationality is then contrasted with dual-process theories of reasoning and rationality prevalent in the psychology of reasoning. It is argued that argumentative rationality properly corresponds only with system-2 reasoning in dual-process theories. This result challenges the prescriptive force of argumentative norms derives if they derive at all from their descriptive accuracy of our cognitive capacities. In response, I propose an activity-based account of reasoning which retains the assumptions of argumentative rationality while recontextualizing the relationship between reasoning as a justificatory activity and the psychological states and processes underlying that activity.

Improving global health: counting reasons why.

Science.gov (United States)

Selgelid, Michael J

2008-08-01

This paper examines cumulative ethical and self-interested reasons why wealthy developed nations should be motivated to do more to improve health care in developing countries. Egalitarian and human rights reasons why wealthy nations should do more to improve global health are that doing so would (1) promote equality of opportunity (2) improve the situation of the worst-off, (3) promote respect of the human right to have one's most basic needs met, and (4) reduce undeserved inequalities in well-being. Utilitarian reasons for improving global health are that this would (5) promote the greater good of humankind, and (6) achieve enormous benefits while requiring only small sacrifices. Libertarian reasons are that this would (7) amend historical injustices and (8) meet the obligation to amend injustices that developed world countries have contributed to. Self-interested reasons why wealthy nations should do more to improve global health are that doing so would (9) reduce the threat of infectious diseases to developed countries, (10) promote developed countries' economic interests, and (11) promote global security. All of these reasons count, and together they add up to make an overwhelmingly powerful case for change. Those opposed to wealthy government funding of developing world health improvement would most likely appeal, implicitly or explicitly to the idea that coercive taxation for redistributive purposes would violate the right of an individual to keep his hard-earned income. The idea that this reason not to improve global health should outweigh the combination of rights and values embodied in the eleven reasons enumerated above, however is implausibly extreme, morally repugnant and perhaps imprudent.

A Reasoning And Hypothesis-Generation Framework Based On Scalable Graph Analytics

Energy Technology Data Exchange (ETDEWEB)

Sukumar, Sreenivas Rangan [ORNL

2016-01-01

Finding actionable insights from data has always been difficult. As the scale and forms of data increase tremendously, the task of finding value becomes even more challenging. Data scientists at Oak Ridge National Laboratory are leveraging unique leadership infrastructure (e.g. Urika-XA and Urika-GD appliances) to develop scalable algorithms for semantic, logical and statistical reasoning with unstructured Big Data. We present the deployment of such a framework called ORiGAMI (Oak Ridge Graph Analytics for Medical Innovations) on the National Library of Medicine s SEMANTIC Medline (archive of medical knowledge since 1994). Medline contains over 70 million knowledge nuggets published in 23.5 million papers in medical literature with thousands more added daily. ORiGAMI is available as an open-science medical hypothesis generation tool - both as a web-service and an application programming interface (API) at http://hypothesis.ornl.gov . Since becoming an online service, ORIGAMI has enabled clinical subject-matter experts to: (i) discover the relationship between beta-blocker treatment and diabetic retinopathy; (ii) hypothesize that xylene is an environmental cancer-causing carcinogen and (iii) aid doctors with diagnosis of challenging cases when rare diseases manifest with common symptoms. In 2015, ORiGAMI was featured in the Historical Clinical Pathological Conference in Baltimore as a demonstration of artificial intelligence to medicine, IEEE/ACM Supercomputing and recognized as a Centennial Showcase Exhibit at the Radiological Society of North America (RSNA) Conference in Chicago. The final paper will describe the workflow built for the Cray Urika-XA and Urika-GD appliances that is able to reason with the knowledge of every published medical paper every time a clinical researcher uses the tool.

Internet-based Advertising Claims and Consumer Reasons for Using Electronic Cigarettes by Device Type in the US.

Science.gov (United States)

Pulvers, Kim; Sun, Jessica Y; Zhuang, Yue-Lin; Holguin, Gabriel; Zhu, Shu-Hong

2017-10-01

Important differences exist between closed-system and open-system e-cigarettes, but it is unknown whether online companies are marketing these devices differently and whether consumer reasons for using e-cigarettes vary by device type. This paper compares Internet-based advertising claims of closed- versus open-system products, and evaluates US consumers' reasons for using closed- versus open-system e-cigarettes. Internet sites selling exclusively closed (N = 130) or open (N = 129) e-cigarettes in December 2013-January 2014 were coded for advertising claims. Current users (≥18 years old) of exclusively closed or open e-cigarettes (N = 860) in a nationally representative online survey in February-March 2014 provided their main reason for using e-cigarettes. Internet sites that exclusively sold closed-system e-cigarettes were more likely to make cigarette-related claims such as e-cigarettes being healthier and cheaper than cigarettes (ps < .0001) compared to sites selling open systems. Many sites implied their products could help smokers quit. Exclusive users of both systems endorsed cessation as their top reason. Closed-system users were more likely to report their reason as "use where smoking is banned." Although promotion of e-cigarettes as cessation aids is prohibited, consumers of both systems endorsed smoking cessation as their top reason for using e-cigarettes.