Physiological sensor signals classification for healthcare using sensor data fusion and case-based reasoning.

PubMed

Begum, Shahina; Barua, Shaibal; Ahmed, Mobyen Uddin

2014-07-03

Today, clinicians often do diagnosis and classification of diseases based on information collected from several physiological sensor signals. However, sensor signal could easily be vulnerable to uncertain noises or interferences and due to large individual variations sensitivity to different physiological sensors could also vary. Therefore, multiple sensor signal fusion is valuable to provide more robust and reliable decision. This paper demonstrates a physiological sensor signal classification approach using sensor signal fusion and case-based reasoning. The proposed approach has been evaluated to classify Stressed or Relaxed individuals using sensor data fusion. Physiological sensor signals i.e., Heart Rate (HR), Finger Temperature (FT), Respiration Rate (RR), Carbon dioxide (CO2) and Oxygen Saturation (SpO2) are collected during the data collection phase. Here, sensor fusion has been done in two different ways: (i) decision-level fusion using features extracted through traditional approaches; and (ii) data-level fusion using features extracted by means of Multivariate Multiscale Entropy (MMSE). Case-Based Reasoning (CBR) is applied for the classification of the signals. The experimental result shows that the proposed system could classify Stressed or Relaxed individual 87.5% accurately compare to an expert in the domain. So, it shows promising result in the psychophysiological domain and could be possible to adapt this approach to other relevant healthcare systems.

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

ERIC Educational Resources Information Center

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…

Combining knowledge discovery from databases (KDD) and case-based reasoning (CBR) to support diagnosis of medical images

NASA Astrophysics Data System (ADS)

Stranieri, Andrew; Yearwood, John; Pham, Binh

1999-07-01

The development of data warehouses for the storage and analysis of very large corpora of medical image data represents a significant trend in health care and research. Amongst other benefits, the trend toward warehousing enables the use of techniques for automatically discovering knowledge from large and distributed databases. In this paper, we present an application design for knowledge discovery from databases (KDD) techniques that enhance the performance of the problem solving strategy known as case- based reasoning (CBR) for the diagnosis of radiological images. The problem of diagnosing the abnormality of the cervical spine is used to illustrate the method. The design of a case-based medical image diagnostic support system has three essential characteristics. The first is a case representation that comprises textual descriptions of the image, visual features that are known to be useful for indexing images, and additional visual features to be discovered by data mining many existing images. The second characteristic of the approach presented here involves the development of a case base that comprises an optimal number and distribution of cases. The third characteristic involves the automatic discovery, using KDD techniques, of adaptation knowledge to enhance the performance of the case based reasoner. Together, the three characteristics of our approach can overcome real time efficiency obstacles that otherwise mitigate against the use of CBR to the domain of medical image analysis.

Case-Based Web Learning Versus Face-to-Face Learning: A Mixed-Method Study on University Nursing Students.

PubMed

Chan, Aileen Wai-Kiu; Chair, Sek-Ying; Sit, Janet Wing-Hung; Wong, Eliza Mi-Ling; Lee, Diana Tze-Fun; Fung, Olivia Wai-Man

2016-03-01

Case-based learning (CBL) is an effective educational method for improving the learning and clinical reasoning skills of students. Advances in e-learning technology have supported the development of the Web-based CBL approach to teaching as an alternative or supplement to the traditional classroom approach. This study aims to examine the CBL experience of Hong Kong students using both traditional classroom and Web-based approaches in undergraduate nursing education. This experience is examined in terms of the perceived self-learning ability, clinical reasoning ability, and satisfaction in learning of these students. A mixture of quantitative and qualitative approaches was adopted. All Year-3 undergraduate nursing students were recruited. CBL was conducted using the traditional classroom approach in Semester 1, and the Web-based approach was conducted in Semester 2. Student evaluations were collected at the end of each semester using a self-report questionnaire. In-depth, focus-group interviews were conducted at the end of Semester 2. One hundred twenty-two students returned their questionnaires. No difference between the face-to-face and Web-based approaches was found in terms of self-learning ability (p = .947), clinical reasoning ability (p = .721), and satisfaction (p = .083). Focus group interview findings complemented survey findings and revealed five themes that reflected the CBL learning experience of Hong Kong students. These themes were (a) the structure of CBL, (b) the learning environment of Web-based CBL, (c) critical thinking and problem solving, (d) cultural influence on CBL learning experience, and (e) student-centered and teacher-centered learning. The Web-based CBL approach was comparable but not superior to the traditional classroom CBL approach. The Web-based CBL experience of these students sheds light on the impact of Chinese culture on student learning behavior and preferences.

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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

2014-01-01

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 construction.

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

PubMed Central

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

2014-01-01

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 construction. PMID:25518871

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

PubMed

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.

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

PubMed Central

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. Images Figure 6 Figure 7 PMID:9929346

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

PubMed

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.

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

PubMed

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.

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

NASA Astrophysics Data System (ADS)

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

2010-05-01

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.

Purpose, Processes, Partnerships, and Products: 4Ps to advance Participatory Socio-Environmental Modeling

NASA Astrophysics Data System (ADS)

Gray, S. G.; Voinov, A. A.; Jordan, R.; Paolisso, M.

2016-12-01

Model-based reasoning is a basic part of human understanding, decision-making, and communication. Including stakeholders in environmental model building and analysis is an increasingly popular approach to understanding environmental change since stakeholders often hold valuable knowledge about socio-environmental dynamics and since collaborative forms of modeling produce important boundary objects used to collectively reason about environmental problems. Although the number of participatory modeling (PM) case studies and the number of researchers adopting these approaches has grown in recent years, the lack of standardized reporting and limited reproducibility have prevented PM's establishment and advancement as a cohesive field of study. We suggest a four dimensional framework that includes reporting on dimensions of: (1) the Purpose for selecting a PM approach (the why); (2) the Process by which the public was involved in model building or evaluation (the how); (3) the Partnerships formed (the who); and (4) the Products that resulted from these efforts (the what). We highlight four case studies that use common PM software-based approaches (fuzzy cognitive mapping, agent-based modeling, system dynamics, and participatory geospatial modeling) to understand human-environment interactions and the consequences of environmental changes, including bushmeat hunting in Tanzania and Cameroon, agricultural production and deforestation in Zambia, and groundwater management in India. We demonstrate how standardizing communication about PM case studies can lead to innovation and new insights about model-based reasoning in support of environmental policy development. We suggest that our 4P framework and reporting approach provides a way for new hypotheses to be identified and tested in the growing field of PM.

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

PubMed

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.

Differences in clinical reasoning among nurses working in highly specialised paediatric care.

PubMed

Andersson, Nina; Klang, Birgitta; Petersson, Gunilla

2012-03-01

The aim of the study was to examine differences in clinical reasoning among novice, experienced and specialist paediatric nurses. Highly specialised paediatric care requires specific knowledge and ongoing skill performance of the nurses employed. There is a lack of research in how paediatric nurses manage the daily care problems they encounter and how they acquire the skills required to give patients the best possible care. More knowledge is needed about how paediatric nurses with different experience and education reason and communicate about paediatric patient situations. The study was based on six recorded group discussions of a fictitious, but realistic paediatric case. Three categories of nurses: novices (n = 7), experienced (n = 7) and specialists (n = 7) from a paediatric hospital participated. A qualitative content analysis approach was chosen to examine differences in clinical reasoning. Several themes were uncovered: child's social situation, child abuse and the child's illness, qualitative differences emerged in how the nurses discussed the case. Three approaches were identified: a task-oriented approach (novices and experienced), an action-oriented approach (novices and experienced) and hypothesis-oriented approach (specialists) while discussing the case. When comparing nurses in three competence groups, it was established that the groups with extensive experience and specialist education reasoned differently than the other groups. Between the novice and experienced groups, no obvious differences were found. Thus, the importance of experience alone for the development of competence is still an open question. Experience combined with further education appears important for developing professional competence in paediatric care. Nurses' reasoning in clinical paediatric care is related to experience and training. © 2012 Blackwell Publishing Ltd.

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

NASA Astrophysics Data System (ADS)

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

Case based reasoning in criminal intelligence using forensic case data.

PubMed

Ribaux, O; Margot, P

2003-01-01

A model that is based on the knowledge of experienced investigators in the analysis of serial crime is suggested to bridge a gap between technology and methodology. Its purpose is to provide a solid methodology for the analysis of serial crimes that supports decision making in the deployment of resources, either by guiding proactive policing operations or helping the investigative process. Formalisation has helped to derive a computerised system that efficiently supports the reasoning processes in the analysis of serial crime. This novel approach fully integrates forensic science data.

Using Psychometric Technology in Educational Assessment: The Case of a Schema-Based Isomorphic Approach to the Automatic Generation of Quantitative Reasoning Items

ERIC Educational Resources Information Center

Arendasy, Martin; Sommer, Markus

2007-01-01

This article deals with the investigation of the psychometric quality and constructs validity of algebra word problems generated by means of a schema-based version of the automatic min-max approach. Based on review of the research literature in algebra word problem solving and automatic item generation this new approach is introduced as a…

Development of decision support systems for real-time freeway traffic routing : volume II.

DOT National Transportation Integrated Search

1998-01-01

Real-time traffic flow routing is a promising approach to alleviating congestion. Existing approaches to developing real-time routing strategies, however, have limitations. This study explored the potential for using case-based reasoning (CBR), an em...

Ontology-Based Method for Fault Diagnosis of Loaders.

PubMed

Xu, Feixiang; Liu, Xinhui; Chen, Wei; Zhou, Chen; Cao, Bingwei

2018-02-28

This paper proposes an ontology-based fault diagnosis method which overcomes the difficulty of understanding complex fault diagnosis knowledge of loaders and offers a universal approach for fault diagnosis of all loaders. This method contains the following components: (1) An ontology-based fault diagnosis model is proposed to achieve the integrating, sharing and reusing of fault diagnosis knowledge for loaders; (2) combined with ontology, CBR (case-based reasoning) is introduced to realize effective and accurate fault diagnoses following four steps (feature selection, case-retrieval, case-matching and case-updating); and (3) in order to cover the shortages of the CBR method due to the lack of concerned cases, ontology based RBR (rule-based reasoning) is put forward through building SWRL (Semantic Web Rule Language) rules. An application program is also developed to implement the above methods to assist in finding the fault causes, fault locations and maintenance measures of loaders. In addition, the program is validated through analyzing a case study.

Ontology-Based Method for Fault Diagnosis of Loaders

PubMed Central

Liu, Xinhui; Chen, Wei; Zhou, Chen; Cao, Bingwei

2018-01-01

This paper proposes an ontology-based fault diagnosis method which overcomes the difficulty of understanding complex fault diagnosis knowledge of loaders and offers a universal approach for fault diagnosis of all loaders. This method contains the following components: (1) An ontology-based fault diagnosis model is proposed to achieve the integrating, sharing and reusing of fault diagnosis knowledge for loaders; (2) combined with ontology, CBR (case-based reasoning) is introduced to realize effective and accurate fault diagnoses following four steps (feature selection, case-retrieval, case-matching and case-updating); and (3) in order to cover the shortages of the CBR method due to the lack of concerned cases, ontology based RBR (rule-based reasoning) is put forward through building SWRL (Semantic Web Rule Language) rules. An application program is also developed to implement the above methods to assist in finding the fault causes, fault locations and maintenance measures of loaders. In addition, the program is validated through analyzing a case study. PMID:29495646

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.

PubMed

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.

Reflexive Principlism as an Effective Approach for Developing Ethical Reasoning in Engineering.

PubMed

Beever, Jonathan; Brightman, Andrew O

2016-02-01

An important goal of teaching ethics to engineering students is to enhance their ability to make well-reasoned ethical decisions in their engineering practice: a goal in line with the stated ethical codes of professional engineering organizations. While engineering educators have explored a wide range of methodologies for teaching ethics, a satisfying model for developing ethical reasoning skills has not been adopted broadly. In this paper we argue that a principlist-based approach to ethical reasoning is uniquely suited to engineering ethics education. Reflexive Principlism is an approach to ethical decision-making that focuses on internalizing a reflective and iterative process of specification, balancing, and justification of four core ethical principles in the context of specific cases. In engineering, that approach provides structure to ethical reasoning while allowing the flexibility for adaptation to varying contexts through specification. Reflexive Principlism integrates well with the prevalent and familiar methodologies of reasoning within the engineering disciplines as well as with the goals of engineering ethics education.

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

NASA Technical Reports Server (NTRS)

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.

A Novel Method of Case Representation and Retrieval in CBR for E-Learning

ERIC Educational Resources Information Center

Khamparia, Aditya; Pandey, Babita

2017-01-01

In this paper we have discussed a novel method which has been developed for representation and retrieval of cases in case based reasoning (CBR) as a part of e-learning system which is based on various student features. In this approach we have integrated Artificial Neural Network (ANN) with Data mining (DM) and CBR. ANN is used to find the…

CABINS: Case-based interactive scheduler

NASA Technical Reports Server (NTRS)

Miyashita, Kazuo; Sycara, Katia

1992-01-01

In this paper we discuss the need for interactive factory schedule repair and improvement, and we identify case-based reasoning (CBR) as an appropriate methodology. Case-based reasoning is the problem solving paradigm that relies on a memory for past problem solving experiences (cases) to guide current problem solving. Cases similar to the current case are retrieved from the case memory, and similarities and differences of the current case to past cases are identified. Then a best case is selected, and its repair plan is adapted to fit the current problem description. If a repair solution fails, an explanation for the failure is stored along with the case in memory, so that the user can avoid repeating similar failures in the future. So far we have identified a number of repair strategies and tactics for factory scheduling and have implemented a part of our approach in a prototype system, called CABINS. As a future work, we are going to scale up CABINS to evaluate its usefulness in a real manufacturing environment.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

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

2010-05-21

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 maintenancemore » (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.« less

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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.

Irrelevance Reasoning in Knowledge Based Systems

NASA Technical Reports Server (NTRS)

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.

Diagnosis support system based on clinical guidelines: comparison between case-based fuzzy cognitive maps and Bayesian networks.

PubMed

Douali, Nassim; Csaba, Huszka; De Roo, Jos; Papageorgiou, Elpiniki I; Jaulent, Marie-Christine

2014-01-01

Several studies have described the prevalence and severity of diagnostic errors. Diagnostic errors can arise from cognitive, training, educational and other issues. Examples of cognitive issues include flawed reasoning, incomplete knowledge, faulty information gathering or interpretation, and inappropriate use of decision-making heuristics. We describe a new approach, case-based fuzzy cognitive maps, for medical diagnosis and evaluate it by comparison with Bayesian belief networks. We created a semantic web framework that supports the two reasoning methods. We used database of 174 anonymous patients from several European hospitals: 80 of the patients were female and 94 male with an average age 45±16 (average±stdev). Thirty of the 80 female patients were pregnant. For each patient, signs/symptoms/observables/age/sex were taken into account by the system. We used a statistical approach to compare the two methods. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

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

PubMed

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.

The application of hybrid artificial intelligence systems for forecasting

NASA Astrophysics Data System (ADS)

Lees, Brian; Corchado, Juan

1999-03-01

The results to date are presented from an ongoing investigation, in which the aim is to combine the strengths of different artificial intelligence methods into a single problem solving system. The premise underlying this research is that a system which embodies several cooperating problem solving methods will be capable of achieving better performance than if only a single method were employed. The work has so far concentrated on the combination of case-based reasoning and artificial neural networks. The relative merits of artificial neural networks and case-based reasoning problem solving paradigms, and their combination are discussed. The integration of these two AI problem solving methods in a hybrid systems architecture, such that the neural network provides support for learning from past experience in the case-based reasoning cycle, is then presented. The approach has been applied to the task of forecasting the variation of physical parameters of the ocean. Results obtained so far from tests carried out in the dynamic oceanic environment are presented.

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

PubMed

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.

Applying temporal abstraction and case-based reasoning to predict approaching influenza waves.

PubMed

Schmidt, Rainer; Gierl, Lothar

2002-01-01

The goal of the TeCoMed project is to send early warnings against forthcoming waves or even epidemics of infectious diseases, especially of influenza, to interested practitioners, pharmacists etc. in the German federal state Mecklenburg-Western Pomerania. The forecast of these waves is based on written confirmations of unfitness for work of the main German health insurance company. Since influenza waves are difficult to predict because of their cyclic but not regular behaviour, statistical methods based on the computation of mean values are not helpful. Instead, we have developed a prognostic model that makes use of similar former courses. Our method combines Case-based Reasoning with Temporal Abstraction to decide whether early warning is appropriate.

Process-Based Governance in Public Administrations Using Activity-Based Costing

NASA Astrophysics Data System (ADS)

Becker, Jörg; Bergener, Philipp; Räckers, Michael

Decision- and policy-makers in public administrations currently lack on missing relevant information for sufficient governance. In Germany the introduction of New Public Management and double-entry accounting enable public administrations to get the opportunity to use cost-centered accounting mechanisms to establish new governance mechanisms. Process modelling in this case can be a useful instrument to help the public administrations decision- and policy-makers to structure their activities and capture relevant information. In combination with approaches like Activity-Based Costing, higher management level can be supported with a reasonable data base for fruitful and reasonable governance approaches. Therefore, the aim of this article is combining the public sector domain specific process modelling method PICTURE and concept of activity-based costing for supporting Public Administrations in process-based Governance.

Case-based reasoning for space applications: Utilization of prior experience in knowledge-based systems

NASA Technical Reports Server (NTRS)

King, James A.

1987-01-01

The goal is to explain Case-Based Reasoning as a vehicle to establish knowledge-based systems based on experimental reasoning for possible space applications. This goal will be accomplished through an examination of reasoning based on prior experience in a sample domain, and also through a presentation of proposed space applications which could utilize Case-Based Reasoning techniques.

Introduction of a computer-based surgical platform in the surgical care of patients with newly diagnosed uterine cancer: outcomes and impact on approach.

PubMed

Leitao, Mario M; Briscoe, Gabriel; Santos, Kevin; Winder, Abigail; Jewell, Elizabeth L; Hoskins, William J; Chi, Dennis S; Abu-Rustum, Nadeem R; Sonoda, Yukio; Brown, Carol L; Levine, Douglas A; Barakat, Richard R; Gardner, Ginger J

2012-05-01

To assess the introduction of computer-based surgery (ie, robotic surgery [RBT]) in the treatment of patients with newly diagnosed uterine cancer. We identified all patients who presented to our institution for initial surgical care of newly diagnosed uterine cancer from 5/1/07-12/31/10. Perioperative outcomes of laparotomy cases were compared to those of laparoscopic (LSC) or RBT cases. Complications within 30 days of surgery were graded. Of 752 patients, the planned approach was laparotomy in 103 (14%), LSC in 302 (40%), and RBT in 347 (46%). The rate of laparotomy for any reason (planned or converted) was 39% in 2007 compared to 18% in 2010 (P<0.001). Preoperative characteristics for LSC and RBT cases were similar, except 10% versus 15%, respectively, were morbidly obese (P=0.049). The extent of procedure, total nodal counts, and overall complications were similar between the LSC and RBT cases. The median length of stay was shorter for RBT cases (P<0.001). The median total room and operative times were longer for RBT cases (P<0.001), mainly due to cases in which the surgeon had less than ~40 RBT cases of experience. Robotics can be efficiently introduced into the surgical care of patients with newly diagnosed uterine cancers. RBT cases require the same operative times as LSC cases after accounting for the 40-case learning curve. Both approaches result in similar excellent patient outcomes and remain reasonable approaches for this disease. The introduction of robotics may lead to further reduction in the rate of laparotomy. Copyright © 2012 Elsevier Inc. All rights reserved.

Building Better Decision-Support by Using Knowledge Discovery.

ERIC Educational Resources Information Center

Jurisica, Igor

2000-01-01

Discusses knowledge-based decision-support systems that use artificial intelligence approaches. Addresses the issue of how to create an effective case-based reasoning system for complex and evolving domains, focusing on automated methods for system optimization and domain knowledge evolution that can supplement knowledge acquired from domain…

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

ERIC Educational Resources Information Center

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,…

A case-based assistant for clinical psychiatry expertise.

PubMed

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.

Towards a computational- and algorithmic-level account of concept blending using analogies and amalgams

NASA Astrophysics Data System (ADS)

Besold, Tarek R.; Kühnberger, Kai-Uwe; Plaza, Enric

2017-10-01

Concept blending - a cognitive process which allows for the combination of certain elements (and their relations) from originally distinct conceptual spaces into a new unified space combining these previously separate elements, and enables reasoning and inference over the combination - is taken as a key element of creative thought and combinatorial creativity. In this article, we summarise our work towards the development of a computational-level and algorithmic-level account of concept blending, combining approaches from computational analogy-making and case-based reasoning (CBR). We present the theoretical background, as well as an algorithmic proposal integrating higher-order anti-unification matching and generalisation from analogy with amalgams from CBR. The feasibility of the approach is then exemplified in two case studies.

Digital Tools to Enhance Clinical Reasoning.

PubMed

Manesh, Reza; Dhaliwal, Gurpreet

2018-05-01

Physicians can improve their diagnostic acumen by adopting a simulation-based approach to analyzing published cases. The tight coupling of clinical problems and their solutions affords physicians the opportunity to efficiently upgrade their illness scripts (structured knowledge of a specific disease) and schemas (structured frameworks for common problems). The more times clinicians practice accessing and applying those knowledge structures through published cases, the greater the odds that they will have an enhanced approach to similar patient-cases in the future. This article highlights digital resources that increase the number of cases a clinician experiences and learns from. Copyright © 2017 Elsevier Inc. All rights reserved.

A Logic-Based Psychotherapy Approach to Treating Patients Which Focuses on Faultless Logical Functioning: A Case Study Method

PubMed Central

Almeida, Fernando; Moreira, Diana

2017-01-01

Many clinical patients present to mental health clinics with depressive symptoms, anxiety, psychosomatic complaints, and sleeping problems. These symptoms which originated may originate from marital problems, conflictual interpersonal relationships, problems in securing work, and housing issues, among many others. These issues might interfere which underlie the difficulties that with the ability of the patients face in maintaining faultless logical reasoning (FLR) and faultless logical functioning (FLF). FLR implies to assess correctly premises, rules, and conclusions. And FLF implies assessing not only FLR, but also the circumstances, life experience, personality, events that validate a conclusion. Almost always, the symptomatology is accompanied by intense emotional changes. Clinical experience shows that a logic-based psychotherapy (LBP) approach is not practiced, and that therapists’ resort to psychopharmacotherapy or other types of psychotherapeutic approaches that are not focused on logical reasoning and, especially, logical functioning. Because of this, patients do not learn to overcome their reasoning and functioning errors. The aim of this work was to investigate how LBP works to improve the patients’ ability to think and function in a faultless logical way. This work describes the case studies of three patients. For this purpose we described the treatment of three patients. With this psychotherapeutic approach, patients gain knowledge that can then be applied not only to the issues that led them to the consultation, but also to other problems they have experienced, thus creating a learning experience and helping to prevent such patients from becoming involved in similar problematic situations. This highlights that LBP is a way of treating symptoms that interfere on some level with daily functioning. This psychotherapeutic approach is relevant for improving patients’ quality of life, and it fills a gap in the literature by describing original case analyses. PMID:29312088

Discovering relevance knowledge in data: a growing cell structures approach.

PubMed

Azuaje, F; Dubitzky, W; Black, N; Adamson, K

2000-01-01

Both information retrieval and case-based reasoning systems rely on effective and efficient selection of relevant data. Typically, relevance in such systems is approximated by similarity or indexing models. However, the definition of what makes data items similar or how they should be indexed is often nontrivial and time-consuming. Based on growing cell structure artificial neural networks, this paper presents a method that automatically constructs a case retrieval model from existing data. Within the case-based reasoning (CBR) framework, the method is evaluated for two medical prognosis tasks, namely, colorectal cancer survival and coronary heart disease risk prognosis. The results of the experiments suggest that the proposed method is effective and robust. To gain a deeper insight and understanding of the underlying mechanisms of the proposed model, a detailed empirical analysis of the models structural and behavioral properties is also provided.

Patients who make terrible therapeutic choices.

PubMed

Curzer, Howard J

2014-01-01

The traditional approaches to dental ethics include appeals to principles, duties (deontology), and consequences (utilitarianism). These approaches are often inadequate when faced with the case of a patient who refuses reasonable treatment and does not share the same ethical framework the dentist is using. An approach based on virtue ethics may be helpful in this and other cases. Virtue ethics is a tradition going back to Plato and Aristotle. It depends on forming a holistic character supporting general appropriate behavior. By correctly diagnosing the real issues at stake in a patient's inappropriate oral health choices and working to build effective habits, dentists can sometimes respond to ethical challenges that remain intractable given rule-based methods.

Finding clusters of similar events within clinical incident reports: a novel methodology combining case based reasoning and information retrieval

PubMed Central

Tsatsoulis, C; Amthauer, H

2003-01-01

A novel methodological approach for identifying clusters of similar medical incidents by analyzing large databases of incident reports is described. The discovery of similar events allows the identification of patterns and trends, and makes possible the prediction of future events and the establishment of barriers and best practices. Two techniques from the fields of information science and artificial intelligence have been integrated—namely, case based reasoning and information retrieval—and very good clustering accuracies have been achieved on a test data set of incident reports from transfusion medicine. This work suggests that clustering should integrate the features of an incident captured in traditional form based records together with the detailed information found in the narrative included in event reports. PMID:14645892

Design of Composite Structures Using Knowledge-Based and Case Based Reasoning

NASA Technical Reports Server (NTRS)

Lambright, Jonathan Paul

1996-01-01

A method of using knowledge based and case based reasoning to assist designers during conceptual design tasks of composite structures was proposed. The cooperative use of heuristics, procedural knowledge, and previous similar design cases suggests a potential reduction in design cycle time and ultimately product lead time. The hypothesis of this work is that the design process of composite structures can be improved by using Case-Based Reasoning (CBR) and Knowledge-Based (KB) reasoning in the early design stages. The technique of using knowledge-based and case-based reasoning facilitates the gathering of disparate information into one location that is easily and readily available. The method suggests that the inclusion of downstream life-cycle issues into the conceptual design phase reduces potential of defective, and sub-optimal composite structures. Three industry experts were interviewed extensively. The experts provided design rules, previous design cases, and test problems. A Knowledge Based Reasoning system was developed using the CLIPS (C Language Interpretive Procedural System) environment and a Case Based Reasoning System was developed using the Design Memory Utility For Sharing Experiences (MUSE) xviii environment. A Design Characteristic State (DCS) was used to document the design specifications, constraints, and problem areas using attribute-value pair relationships. The DCS provided consistent design information between the knowledge base and case base. Results indicated that the use of knowledge based and case based reasoning provided a robust design environment for composite structures. The knowledge base provided design guidance from well defined rules and procedural knowledge. The case base provided suggestions on design and manufacturing techniques based on previous similar designs and warnings of potential problems and pitfalls. The case base complemented the knowledge base and extended the problem solving capability beyond the existence of limited well defined rules. The findings indicated that the technique is most effective when used as a design aid and not as a tool to totally automate the composites design process. Other areas of application and implications for future research are discussed.

Evicase: an evidence-based case structuring approach for personalized healthcare.

PubMed

Carmeli, Boaz; Casali, Paolo; Goldbraich, Anna; Goldsteen, Abigail; Kent, Carmel; Licitra, Lisa; Locatelli, Paolo; Restifo, Nicola; Rinott, Ruty; Sini, Elena; Torresani, Michele; Waks, Zeev

2012-01-01

The personalized medicine era stresses a growing need to combine evidence-based medicine with case based reasoning in order to improve the care process. To address this need we suggest a framework to generate multi-tiered statistical structures we call Evicases. Evicase integrates established medical evidence together with patient cases from the bedside. It then uses machine learning algorithms to produce statistical results and aggregators, weighted predictions, and appropriate recommendations. Designed as a stand-alone structure, Evicase can be used for a range of decision support applications including guideline adherence monitoring and personalized prognostic predictions.

Case-based reasoning in design: An apologia

NASA Technical Reports Server (NTRS)

Pulaski, Kirt

1990-01-01

Three positions are presented and defended: the process of generating solutions in problem solving is viewable as a design task; case-based reasoning is a strong method of problem solving; and a synergism exists between case-based reasoning and design problem solving.

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

PubMed

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/.

Purpose, processes, partnerships, and products: four Ps to advance participatory socio-environmental modeling

USGS Publications Warehouse

Gray, Steven; Voinov, Alexey; Paolisso, Michael; Jordan, Rebecca; BenDor, Todd; Bommel, Pierre; Glynn, Pierre D.; Hedelin, Beatrice; Hubacek, Klaus; Introne, Josh; Kolagani, Nagesh; Laursen, Bethany; Prell, Christina; Schmitt-Olabisi, Laura; Singer, Alison; Sterling, Eleanor J.; Zellner, Moira

2018-01-01

Including stakeholders in environmental model building and analysis is an increasingly popular approach to understanding ecological change. This is because stakeholders often hold valuable knowledge about socio-environmental dynamics and collaborative forms of modeling produce important boundary objects used to collectively reason about environmental problems. Although the number of participatory modeling (PM) case studies and the number of researchers adopting these approaches has grown in recent years, the lack of standardized reporting and limited reproducibility have prevented PM's establishment and advancement as a cohesive field of study. We suggest a four-dimensional framework (4P) that includes reporting on dimensions of (1) the Purpose for selecting a PM approach (the why); (2) the Process by which the public was involved in model building or evaluation (the how); (3) the Partnerships formed (the who); and (4) the Products that resulted from these efforts (the what). We highlight four case studies that use common PM software-based approaches (fuzzy cognitive mapping, agent-based modeling, system dynamics, and participatory geospatial modeling) to understand human–environment interactions and the consequences of ecological changes, including bushmeat hunting in Tanzania and Cameroon, agricultural production and deforestation in Zambia, and groundwater management in India. We demonstrate how standardizing communication about PM case studies can lead to innovation and new insights about model-based reasoning in support of ecological policy development. We suggest that our 4P framework and reporting approach provides a way for new hypotheses to be identified and tested in the growing field of PM.

Purpose, processes, partnerships, and products: four Ps to advance participatory socio-environmental modeling.

PubMed

Gray, Steven; Voinov, Alexey; Paolisso, Michael; Jordan, Rebecca; BenDor, Todd; Bommel, Pierre; Glynn, Pierre; Hedelin, Beatrice; Hubacek, Klaus; Introne, Josh; Kolagani, Nagesh; Laursen, Bethany; Prell, Christina; Schmitt Olabisi, Laura; Singer, Alison; Sterling, Eleanor; Zellner, Moira

2018-01-01

Including stakeholders in environmental model building and analysis is an increasingly popular approach to understanding ecological change. This is because stakeholders often hold valuable knowledge about socio-environmental dynamics and collaborative forms of modeling produce important boundary objects used to collectively reason about environmental problems. Although the number of participatory modeling (PM) case studies and the number of researchers adopting these approaches has grown in recent years, the lack of standardized reporting and limited reproducibility have prevented PM's establishment and advancement as a cohesive field of study. We suggest a four-dimensional framework (4P) that includes reporting on dimensions of (1) the Purpose for selecting a PM approach (the why); (2) the Process by which the public was involved in model building or evaluation (the how); (3) the Partnerships formed (the who); and (4) the Products that resulted from these efforts (the what). We highlight four case studies that use common PM software-based approaches (fuzzy cognitive mapping, agent-based modeling, system dynamics, and participatory geospatial modeling) to understand human-environment interactions and the consequences of ecological changes, including bushmeat hunting in Tanzania and Cameroon, agricultural production and deforestation in Zambia, and groundwater management in India. We demonstrate how standardizing communication about PM case studies can lead to innovation and new insights about model-based reasoning in support of ecological policy development. We suggest that our 4P framework and reporting approach provides a way for new hypotheses to be identified and tested in the growing field of PM. © 2017 by the Ecological Society of America.

Faith and reason and physician-assisted suicide.

PubMed

Kaczor, Christopher

1998-08-01

Aquinas's conception of the relationship of faith and reason calls into question the arguments and some of the conclusions advanced in contributions to the debate on physician-assisted suicide by David Thomasma and H. Tristram Engelhardt. An understanding of the nature of theology as based on revelation calls into question Thomasma's theological argument in favor of physician-assisted suicide based on the example of Christ and the martyrs. On the other hand, unaided reason calls into question his assumptions about the nature of death as in some cases a good for the human person. Finally, if Aquinas is right about the relationship of faith and reason, Engelhardt's sharp contrast between "Christian" and "secular" approaches to physician-assisted suicide needs reconsideration, although his conclusions about physician-assisted suicide would find support.

The Pacor 2 expert system: A case-based reasoning approach to troubleshooting

NASA Technical Reports Server (NTRS)

Sary, Charisse

1994-01-01

The Packet Processor 2 (Pacor 2) Data Capture Facility (DCF) acquires, captures, and performs level-zero processing of packet telemetry for spaceflight missions that adhere to communication services recommendations established by the Consultative Committee for Space Data Systems (CCSDS). A major goal of this project is to reduce life-cycle costs. One way to achieve this goal is to increase automation. Through automation, using expert systems, and other technologies, staffing requirements will remain static, which will enable the same number of analysts to support more missions. Analysts provide packet telemetry data evaluation and analysis services for all data received. Data that passes this evaluation is forwarded to the Data Distribution Facility (DDF) and released to scientists. Through troubleshooting, data that fails this evaluation is dumped and analyzed to determine if its quality can be improved before it is released. This paper describes a proof-of-concept prototype that troubleshoots data quality problems. The Pacor 2 expert system prototype uses the case-based reasoning (CBR) approach to development, an alternative to a rule-based approach. Because Pacor 2 is not operational, the prototype has been developed using cases that describe existing troubleshooting experience from currently operating missions. Through CBR, this experience will be available to analysts when Pacor 2 becomes operational. As Pacor 2 unique experience is gained, analysts will update the case base. In essence, analysts are training the system as they learn. Once the system has learned the cases most likely to recur, it can serve as an aide to inexperienced analysts, a refresher to experienced analysts for infrequently occurring problems, or a training tool for new analysts. The Expert System Development Methodology (ESDM) is being used to guide development.

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

PubMed

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.

A case-based reasoning view of thrombophilia risk.

PubMed

Vilhena, João; Vicente, Henrique; Martins, M Rosário; Grañeda, José M; Caldeira, Filomena; Gusmão, Rodrigo; Neves, João; Neves, José

2016-08-01

Thrombophilia stands for a genetic or an acquired tendency to hypercoagulable states that increase the risk of venous and arterial thromboses. Indeed, venous thromboembolism is often a chronic illness, mainly in deep venous thrombosis and pulmonary embolism, requiring lifelong prevention strategies. Therefore, it is crucial to identify the cause of the disease, the most appropriate treatment, the length of treatment or prevent a thrombotic recurrence. Thus, this work will focus on the development of a diagnosis decision support system in terms of a formal agenda built on a logic programming approach to knowledge representation and reasoning, complemented with a case-based approach to computing. The proposed model has been quite accurate in the assessment of thrombophilia predisposition risk, since the overall accuracy is higher than 90% and sensitivity ranging in the interval [86.5%, 88.1%]. The main strength of the proposed solution is the ability to deal explicitly with incomplete, unknown, or even self-contradictory information. Copyright © 2016 Elsevier Inc. All rights reserved.

Script-theory virtual case: A novel tool for education and research.

PubMed

Hayward, Jake; Cheung, Amandy; Velji, Alkarim; Altarejos, Jenny; Gill, Peter; Scarfe, Andrew; Lewis, Melanie

2016-11-01

Context/Setting: The script theory of diagnostic reasoning proposes that clinicians evaluate cases in the context of an "illness script," iteratively testing internal hypotheses against new information eventually reaching a diagnosis. We present a novel tool for teaching diagnostic reasoning to undergraduate medical students based on an adaptation of script theory. We developed a virtual patient case that used clinically authentic audio and video, interactive three-dimensional (3D) body images, and a simulated electronic medical record. Next, we used interactive slide bars to record respondents' likelihood estimates of diagnostic possibilities at various stages of the case. Responses were dynamically compared to data from expert clinicians and peers. Comparative frequency distributions were presented to the learner and final diagnostic likelihood estimates were analyzed. Detailed student feedback was collected. Over two academic years, 322 students participated. Student diagnostic likelihood estimates were similar year to year, but were consistently different from expert clinician estimates. Student feedback was overwhelmingly positive: students found the case was novel, innovative, clinically authentic, and a valuable learning experience. We demonstrate the successful implementation of a novel approach to teaching diagnostic reasoning. Future study may delineate reasoning processes associated with differences between novice and expert responses.

Applications of artificial intelligence 1993: Knowledge-based systems in aerospace and industry; Proceedings of the Meeting, Orlando, FL, Apr. 13-15, 1993

NASA Technical Reports Server (NTRS)

Fayyad, Usama M. (Editor); Uthurusamy, Ramasamy (Editor)

1993-01-01

The present volume on applications of artificial intelligence with regard to knowledge-based systems in aerospace and industry discusses machine learning and clustering, expert systems and optimization techniques, monitoring and diagnosis, and automated design and expert systems. Attention is given to the integration of AI reasoning systems and hardware description languages, care-based reasoning, knowledge, retrieval, and training systems, and scheduling and planning. Topics addressed include the preprocessing of remotely sensed data for efficient analysis and classification, autonomous agents as air combat simulation adversaries, intelligent data presentation for real-time spacecraft monitoring, and an integrated reasoner for diagnosis in satellite control. Also discussed are a knowledge-based system for the design of heat exchangers, reuse of design information for model-based diagnosis, automatic compilation of expert systems, and a case-based approach to handling aircraft malfunctions.

The Special Place Project: Efficacy of a Place-Based Case Study Approach for Teaching Geoscience

NASA Astrophysics Data System (ADS)

Moosavi, Sadredin

2014-05-01

Achieving geoscience literacy of the general population has become increasingly important world wide as ever more connected and growing societies depend more and more on our planet's limited natural resource base. Building citizen understanding of their dependence on the local environment, and the geologic processes which created and continue to change it, has become a great challenge to educators at all levels of the education system. The Special Place Project described in this presentation explores use of a place-based case study approach combining instruction in geoscience content with development of observation, reasoning, writing and presentation skills. The approach allows students to select the locations for their individual case studies affording development of personal connections between the learner and his environment. The approach gives instructors at many grade levels the ability to develop core pedagogical content and skills while exploring the unique geologic environments relevant to the local population including such critical issues as land use, resource depletion, energy, climate change and the future of communities in a changing world. The geologic reasons for the location of communities and key events in their histories can be incorporated into the students' case studies as appropriate. The project is unique in placing all course instruction in the context of the quest to explore and gain understanding of the student's chosen location by using the inherently more generalized course content required by the curriculum. By modeling how scientists approach their research questions, this pedagogical technique not only integrates knowledge and skills from across the curriculum, it captures the excitement of scientific thinking on real world questions directly relevant to students' lives, increasing student engagement and depth of learning as demonstrated in the case study reports crafted by the students and exam results. Student learning of topics directly touched upon by the case study, such as geomorphologic features and processes observable at Earth's surface, is compared to learning on more abstract topics, such as subsurface Earth structure and tectonic processes, to provide a quantitative assessment of this pedagogical approach.

Human Rights-Based Approaches to Mental Health

PubMed Central

Bradley, Valerie J.; Sahakian, Barbara J.

2016-01-01

Abstract The incidence of human rights violations in mental health care across nations has been described as a “global emergency” and an “unresolved global crisis.” The relationship between mental health and human rights is complex and bidirectional. Human rights violations can negatively impact mental health. Conversely, respecting human rights can improve mental health. This article reviews cases where an explicitly human rights-based approach was used in mental health care settings. Although the included studies did not exhibit a high level of methodological rigor, the qualitative information obtained was considered useful and informative for future studies. All studies reviewed suggest that human-rights based approaches can lead to clinical improvements at relatively low costs. Human rights-based approaches should be utilized for legal and moral reasons, since human rights are fundamental pillars of justice and civilization. The fact that such approaches can contribute to positive therapeutic outcomes and, potentially, cost savings, is additional reason for their implementation. However, the small sample size and lack of controlled, quantitative measures limit the strength of conclusions drawn from included studies. More objective, high quality research is needed to ascertain the true extent of benefits to service users and providers. PMID:27781015

Human Rights-Based Approaches to Mental Health: A Review of Programs.

PubMed

Porsdam Mann, Sebastian; Bradley, Valerie J; Sahakian, Barbara J

2016-06-01

The incidence of human rights violations in mental health care across nations has been described as a "global emergency" and an "unresolved global crisis." The relationship between mental health and human rights is complex and bidirectional. Human rights violations can negatively impact mental health. Conversely, respecting human rights can improve mental health. This article reviews cases where an explicitly human rights-based approach was used in mental health care settings. Although the included studies did not exhibit a high level of methodological rigor, the qualitative information obtained was considered useful and informative for future studies. All studies reviewed suggest that human-rights based approaches can lead to clinical improvements at relatively low costs. Human rights-based approaches should be utilized for legal and moral reasons, since human rights are fundamental pillars of justice and civilization. The fact that such approaches can contribute to positive therapeutic outcomes and, potentially, cost savings, is additional reason for their implementation. However, the small sample size and lack of controlled, quantitative measures limit the strength of conclusions drawn from included studies. More objective, high quality research is needed to ascertain the true extent of benefits to service users and providers.

Research of Litchi Diseases Diagnosis Expertsystem Based on Rbr and Cbr

NASA Astrophysics Data System (ADS)

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.

Clinical Reasoning Tasks and Resident Physicians: What Do They Reason About?

PubMed

McBee, Elexis; Ratcliffe, Temple; Goldszmidt, Mark; Schuwirth, Lambert; Picho, Katherine; Artino, Anthony R; Masel, Jennifer; Durning, Steven J

2016-07-01

A framework of clinical reasoning tasks thought to occur in a clinical encounter was recently developed. It proposes that diagnostic and therapeutic reasoning comprise 24 tasks. The authors of this current study used this framework to investigate what internal medicine residents reason about when they approach straightforward clinical cases. Participants viewed three video-recorded clinical encounters portraying common diagnoses. After each video, participants completed a post encounter form and think-aloud protocol. Two authors analyzed transcripts from the think-aloud protocols using a constant comparative approach. They conducted iterative coding of the utterances, classifying each according to the framework of clinical reasoning tasks. They evaluated the type, number, and sequence of tasks the residents used. Ten residents participated in the study in 2013-2014. Across all three cases, the residents employed 14 clinical reasoning tasks. Nearly all coded tasks were associated with framing the encounter or diagnosis. The order in which residents used specific tasks varied. The average number of tasks used per case was as follows: Case 1, 4.4 (range 1-10); Case 2, 4.6 (range 1-6); and Case 3, 4.7 (range 1-7). The residents used some tasks repeatedly; the average number of task utterances was 11.6, 13.2, and 14.7 for, respectively, Case 1, 2, and 3. Results suggest that the use of clinical reasoning tasks occurs in a varied, not sequential, process. The authors provide suggestions for strengthening the framework to more fully encompass the spectrum of reasoning tasks that occur in residents' clinical encounters.

Exploring a New Simulation Approach to Improve Clinical Reasoning Teaching and Assessment: Randomized Trial Protocol

PubMed Central

Moussa, Ahmed; Loye, Nathalie; Charlin, Bernard; Audétat, Marie-Claude

2016-01-01

Background Helping trainees develop appropriate clinical reasoning abilities is a challenging goal in an environment where clinical situations are marked by high levels of complexity and unpredictability. The benefit of simulation-based education to assess clinical reasoning skills has rarely been reported. More specifically, it is unclear if clinical reasoning is better acquired if the instructor's input occurs entirely after or is integrated during the scenario. Based on educational principles of the dual-process theory of clinical reasoning, a new simulation approach called simulation with iterative discussions (SID) is introduced. The instructor interrupts the flow of the scenario at three key moments of the reasoning process (data gathering, integration, and confirmation). After each stop, the scenario is continued where it was interrupted. Finally, a brief general debriefing ends the session. System-1 process of clinical reasoning is assessed by verbalization during management of the case, and System-2 during the iterative discussions without providing feedback. Objective The aim of this study is to evaluate the effectiveness of Simulation with Iterative Discussions versus the classical approach of simulation in developing reasoning skills of General Pediatrics and Neonatal-Perinatal Medicine residents. Methods This will be a prospective exploratory, randomized study conducted at Sainte-Justine hospital in Montreal, Qc, between January and March 2016. All post-graduate year (PGY) 1 to 6 residents will be invited to complete one SID or classical simulation 30 minutes audio video-recorded complex high-fidelity simulations covering a similar neonatology topic. Pre- and post-simulation questionnaires will be completed and a semistructured interview will be conducted after each simulation. Data analyses will use SPSS and NVivo softwares. Results This study is in its preliminary stages and the results are expected to be made available by April, 2016. Conclusions This will be the first study to explore a new simulation approach designed to enhance clinical reasoning. By assessing more closely reasoning processes throughout a simulation session, we believe that Simulation with Iterative Discussions will be an interesting and more effective approach for students. The findings of the study will benefit medical educators, education programs, and medical students. PMID:26888076

Exploring a New Simulation Approach to Improve Clinical Reasoning Teaching and Assessment: Randomized Trial Protocol.

PubMed

Pennaforte, Thomas; Moussa, Ahmed; Loye, Nathalie; Charlin, Bernard; Audétat, Marie-Claude

2016-02-17

Helping trainees develop appropriate clinical reasoning abilities is a challenging goal in an environment where clinical situations are marked by high levels of complexity and unpredictability. The benefit of simulation-based education to assess clinical reasoning skills has rarely been reported. More specifically, it is unclear if clinical reasoning is better acquired if the instructor's input occurs entirely after or is integrated during the scenario. Based on educational principles of the dual-process theory of clinical reasoning, a new simulation approach called simulation with iterative discussions (SID) is introduced. The instructor interrupts the flow of the scenario at three key moments of the reasoning process (data gathering, integration, and confirmation). After each stop, the scenario is continued where it was interrupted. Finally, a brief general debriefing ends the session. System-1 process of clinical reasoning is assessed by verbalization during management of the case, and System-2 during the iterative discussions without providing feedback. The aim of this study is to evaluate the effectiveness of Simulation with Iterative Discussions versus the classical approach of simulation in developing reasoning skills of General Pediatrics and Neonatal-Perinatal Medicine residents. This will be a prospective exploratory, randomized study conducted at Sainte-Justine hospital in Montreal, Qc, between January and March 2016. All post-graduate year (PGY) 1 to 6 residents will be invited to complete one SID or classical simulation 30 minutes audio video-recorded complex high-fidelity simulations covering a similar neonatology topic. Pre- and post-simulation questionnaires will be completed and a semistructured interview will be conducted after each simulation. Data analyses will use SPSS and NVivo softwares. This study is in its preliminary stages and the results are expected to be made available by April, 2016. This will be the first study to explore a new simulation approach designed to enhance clinical reasoning. By assessing more closely reasoning processes throughout a simulation session, we believe that Simulation with Iterative Discussions will be an interesting and more effective approach for students. The findings of the study will benefit medical educators, education programs, and medical students.

Interpreting Data: The Hybrid Mind

ERIC Educational Resources Information Center

Heisterkamp, Kimberly; Talanquer, Vicente

2015-01-01

The central goal of this study was to characterize major patterns of reasoning exhibited by college chemistry students when analyzing and interpreting chemical data. Using a case study approach, we investigated how a representative student used chemical models to explain patterns in the data based on structure-property relationships. Our results…

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

PubMed

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.

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

PubMed

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.

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

NASA Astrophysics Data System (ADS)

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 minority samples and generated high total accuracy meanwhile. The proposed approach makes CBR useful in imbalanced forecasting.

Closed-loop, pilot/vehicle analysis of the approach and landing task

NASA Technical Reports Server (NTRS)

Anderson, M. R.; Schmidt, D. K.

1986-01-01

In the case of approach and landing, it is universally accepted that the pilot uses more than one vehicle response, or output, to close his control loops. Therefore, to model this task, a multi-loop analysis technique is required. The analysis problem has been in obtaining reasonable analytic estimates of the describing functions representing the pilot's loop compensation. Once these pilot describing functions are obtained, appropriate performance and workload metrics must then be developed for the landing task. The optimal control approach provides a powerful technique for obtaining the necessary describing functions, once the appropriate task objective is defined in terms of a quadratic objective function. An approach is presented through the use of a simple, reasonable objective function and model-based metrics to evaluate loop performance and pilot workload. The results of an analysis of the LAHOS (Landing and Approach of Higher Order Systems) study performed by R.E. Smith is also presented.

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

PubMed Central

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

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

PubMed

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.

A Review of Diagnostic Techniques for ISHM Applications

NASA Technical Reports Server (NTRS)

Patterson-Hine, Ann; Biswas, Gautam; Aaseng, Gordon; Narasimhan, Sriam; Pattipati, Krishna

2005-01-01

System diagnosis is an integral part of any Integrated System Health Management application. Diagnostic applications make use of system information from the design phase, such as safety and mission assurance analysis, failure modes and effects analysis, hazards analysis, functional models, fault propagation models, and testability analysis. In modern process control and equipment monitoring systems, topological and analytic , models of the nominal system, derived from design documents, are also employed for fault isolation and identification. Depending on the complexity of the monitored signals from the physical system, diagnostic applications may involve straightforward trending and feature extraction techniques to retrieve the parameters of importance from the sensor streams. They also may involve very complex analysis routines, such as signal processing, learning or classification methods to derive the parameters of importance to diagnosis. The process that is used to diagnose anomalous conditions from monitored system signals varies widely across the different approaches to system diagnosis. Rule-based expert systems, case-based reasoning systems, model-based reasoning systems, learning systems, and probabilistic reasoning systems are examples of the many diverse approaches ta diagnostic reasoning. Many engineering disciplines have specific approaches to modeling, monitoring and diagnosing anomalous conditions. Therefore, there is no "one-size-fits-all" approach to building diagnostic and health monitoring capabilities for a system. For instance, the conventional approaches to diagnosing failures in rotorcraft applications are very different from those used in communications systems. Further, online and offline automated diagnostic applications are integrated into an operations framework with flight crews, flight controllers and maintenance teams. While the emphasis of this paper is automation of health management functions, striking the correct balance between automated and human-performed tasks is a vital concern.

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

NASA Astrophysics Data System (ADS)

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.

Patterns of Clinical Reasoning in Physical Therapist Students.

PubMed

Gilliland, Sarah; Wainwright, Susan Flannery

2017-05-01

Clinical reasoning is a complex, nonlinear problem-solving process that is influenced by models of practice. The development of physical therapists' clinical reasoning abilities is a crucial yet underresearched aspect of entry-level (professional) physical therapist education. The purpose of this qualitative study was to examine the types of clinical reasoning strategies physical therapist students engage in during a patient encounter. A qualitative descriptive case study design involving within and across case analysis was used. Eight second-year, professional physical therapist students from 2 different programs completed an evaluation and initial intervention for a standardized patient followed by a retrospective think-aloud interview to explicate their reasoning processes. Participants' clinical reasoning strategies were examined using a 2-stage qualitative method of thematic analysis. Participants demonstrated consistent signs of development of physical therapy-specific reasoning processes, yet varied in their approach to the case and use of reflection. Participants who gave greater attention to patient education and empowerment also demonstrated greater use of reflection-in-action during the patient encounter. One negative case illustrates the variability in the rate at which students may develop these abilities. Participants demonstrated development toward physical therapist--specific clinical reasoning, yet demonstrated qualitatively different approaches to the patient encounter. Multiple factors, including the use of reflection-in-action, may enable students to develop greater flexibility in their reasoning processes. © 2017 American Physical Therapy Association

How to improve the teaching of clinical reasoning: a narrative review and a proposal.

PubMed

Schmidt, Henk G; Mamede, Sílvia

2015-10-01

The development of clinical reasoning (CR) in students has traditionally been left to clinical rotations, which, however, often offer limited practice and suboptimal supervision. Medical schools begin to address these limitations by organising pre-clinical CR courses. The purpose of this paper is to review the variety of approaches employed in the teaching of CR and to present a proposal to improve these practices. We conducted a narrative review of the literature on teaching CR. To that end, we searched PubMed and Web of Science for papers published until June 2014. Additional publications were identified in the references cited in the initial papers. We used theoretical considerations to characterise approaches and noted empirical findings, when available. Of the 48 reviewed papers, only 24 reported empirical findings. The approaches to teaching CR were shown to vary on two dimensions. The first pertains to the way the case information is presented. The case is either unfolded to students gradually - the 'serial-cue' approach - or is presented in a 'whole-case' format. The second dimension concerns the purpose of the exercise: is its aim to help students acquire or apply knowledge, or is its purpose to teach students a way of thinking? The most prevalent approach is the serial-cue approach, perhaps because it tries to directly simulate the diagnostic activities of doctors. Evidence supporting its effectiveness is, however, lacking. There is some empirical evidence that whole-case, knowledge-oriented approaches contribute to the improvement of students' CR. However, thinking process-oriented approaches were shown to be largely ineffective. Based on research on how expertise develops in medicine, we argue that students in different phases of their training may benefit from different approaches to the teaching of CR. © 2015 John Wiley & Sons Ltd.

Building a case-based diet recommendation system without a knowledge engineer.

PubMed

Khan, Abdus Salam; Hoffmann, Achim

2003-02-01

We present a new approach to the effective development of menu construction systems that allow to automatically construct a menu that is strongly tailored to the individual requirements and food preferences of a client. In hospitals and other health care institutions dietitians develop diets for clients which need to change their eating habits. Many clients have special needs in regards to their medical conditions, cultural backgrounds, or special levels of nutrient requirements for better recovery from diseases or surgery, etc. Existing computer support for this task is insufficient-many diets are not specifically tailored for the client's needs or require substantial time of a dietitian to be manually developed. Our approach is based on case-based reasoning, an artificial intelligence technique that finds increasing entry into industrial practice. Our approach goes beyond the traditional case-based reasoning (CBR) approach by allowing an incremental improvement of the system's competency during routine use of the system. The improvement of the system takes place through a direct expert user-system interaction while the expert is accomplishing their tasks of constructing a diet for a given client. Whenever the system performs unsatisfactorily, the expert will need to modify the system-produced diet 'manually', i.e. by entering the desired modifications into the system. Our implemented system, menu construction using an incremental knowledge acquisition system (MIKAS), asks the expert for simple explanations for each of the manual actions he/she takes and incorporates the explanations automatically into its knowledge base (KB) so that the system will perform these manually conducted actions automatically at the next occasion. We present MIKAS and discuss the results of our case study. While still being a prototype, the senior clinical dietitian involved in our evaluation studies judges the approach to have considerable potential to improve the daily routine of hospital dietitians as well as to improve the average quality of the dietary advice given to patients within the limited available time for dietary consultations. Our approach opens up a new avenue towards building highly specialised CBR systems in a more cost-effective way. Hence, our approach promises to allow a significantly more widespread development and practical deployment of CBR systems in a large variety of application domains including many medical applications.

Faultfinder: A diagnostic expert system with graceful degradation for onboard aircraft applications

NASA Technical Reports Server (NTRS)

Abbott, Kathy H.; Schutte, Paul C.; Palmer, Michael T.; Ricks, Wendell R.

1988-01-01

A research effort was conducted to explore the application of artificial intelligence technology to automation of fault monitoring and diagnosis as an aid to the flight crew. Human diagnostic reasoning was analyzed and actual accident and incident cases were reconstructed. Based on this analysis and reconstruction, diagnostic concepts were conceived and implemented for an aircraft's engine and hydraulic subsystems. These concepts are embedded within a multistage approach to diagnosis that reasons about time-based, causal, and qualitative information, and enables a certain amount of graceful degradation. The diagnostic concepts are implemented in a computer program called Faultfinder that serves as a research prototype.

Integration of Optimal Scheduling with Case-Based Planning.

DTIC Science & Technology

1995-08-01

integrates Case-Based Reasoning (CBR) and Rule-Based Reasoning (RBR) systems. ’ Tachyon : A Constraint-Based Temporal Reasoning Model and Its...Implementation’ provides an overview of the Tachyon temporal’s reasoning system and discusses its possible applications. ’Dual-Use Applications of Tachyon : From...Force Structure Modeling to Manufacturing Scheduling’ discusses the application of Tachyon to real world problems, specifically military force deployment and manufacturing scheduling.

Formalization and Analysis of Reasoning by Assumption

ERIC Educational Resources Information Center

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

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…

Case-based reasoning: The marriage of knowledge base and data base

NASA Technical Reports Server (NTRS)

Pulaski, Kirt; Casadaban, Cyprian

1988-01-01

The coupling of data and knowledge has a synergistic effect when building an intelligent data base. The goal is to integrate the data and knowledge almost to the point of indistinguishability, permitting them to be used interchangeably. Examples given in this paper suggest that Case-Based Reasoning is a more integrated way to link data and knowledge than pure rule-based reasoning.

Absolute order-of-magnitude reasoning applied to a social multi-criteria evaluation framework

NASA Astrophysics Data System (ADS)

Afsordegan, A.; Sánchez, M.; Agell, N.; Aguado, J. C.; Gamboa, G.

2016-03-01

A social multi-criteria evaluation framework for solving a real-case problem of selecting a wind farm location in the regions of Urgell and Conca de Barberá in Catalonia (northeast of Spain) is studied. This paper applies a qualitative multi-criteria decision analysis approach based on linguistic labels assessment able to address uncertainty and deal with different levels of precision. This method is based on qualitative reasoning as an artificial intelligence technique for assessing and ranking multi-attribute alternatives with linguistic labels in order to handle uncertainty. This method is suitable for problems in the social framework such as energy planning which require the construction of a dialogue process among many social actors with high level of complexity and uncertainty. The method is compared with an existing approach, which has been applied previously in the wind farm location problem. This approach, consisting of an outranking method, is based on Condorcet's original method. The results obtained by both approaches are analysed and their performance in the selection of the wind farm location is compared in aggregation procedures. Although results show that both methods conduct to similar alternatives rankings, the study highlights both their advantages and drawbacks.

Some Simple Solutions to the Problem of Predicting Boundary-Layer Self-Induced Pressures

NASA Technical Reports Server (NTRS)

Bertram, Mitchel H.; Blackstock, Thomas A.

1961-01-01

Simplified theoretical approaches are shown, based on hypersonic similarity boundary-layer theory, which allow reasonably accurate estimates to be made of the surface pressures on plates on which viscous effects are important. The consideration of viscous effects includes the cases where curved surfaces, stream pressure gradients, and leadingedge bluntness are important factors.

Do Expert Clinical Teachers Have a Shared Understanding of What Constitutes a Competent Reasoning Performance in Case-Based Teaching?

ERIC Educational Resources Information Center

Gauthier, Geneviève; Lajoie, Susanne P.

2014-01-01

To explore the assessment challenge related to case based learning we study how experienced clinical teachers--i.e., those who regularly teach and assess case-based learning--conceptualize the notion of competent reasoning performance for specific teaching cases. Through an in-depth qualitative case study of five expert teachers, we investigate…

Elective Self-Care Course Emphasizing Critical Reasoning Principles

PubMed Central

2011-01-01

Objectives. To create, implement, and assess a self-directed online course based on 3 critical reasoning principles to develop pharmacy students’ skills in literature appraisal, content, metacognition, and assessment. Design. Students completed 3 assignments for the course: compile a literature appraisal on a healthcare topic; plan learning objectives and meta-cognitive skills for a learning module; and create a case-based online lesson with multi-structured feedback. Assessment. An online exit survey evaluated students’ perceptions regarding development of ACE (agency, collaboration, expertise) principles and preparation for competency. Students reported acquisition of ACE principles and noted improvements in their learning approaches, sense of responsibility for individual and community learning, skills, and confidence. Conclusions. An online elective course in self-care addressed practice standards for patient safety, maintenance of competency, and interprofessional education by emphasizing critical reasoning skills. PMID:22171110

Teaching and Assessing Clinical Reasoning Skills.

PubMed

Modi, Jyoti Nath; Anshu; Gupta, Piyush; Singh, Tejinder

2015-09-01

Clinical reasoning is a core competency expected to be acquired by all clinicians. It is the ability to integrate and apply different types of knowledge, weigh evidence critically and reflect upon the process used to arrive at a diagnosis. Problems with clinical reasoning often occur because of inadequate knowledge, flaws in data gathering and improper approach to information processing. Some of the educational strategies which can be used to encourage acquisition of clinical reasoning skills are: exposure to a wide variety of clinical cases, activation of previous knowledge, development of illness scripts, sharing expert strategies to arrive at a diagnosis, forcing students to prioritize differential diagnoses; and encouraging reflection, metacognition, deliberate practice and availability of formative feedback. Assessment of clinical reasoning abilities should be done throughout the training course in diverse settings. Use of scenario based multiple choice questions, key feature test and script concordance test are some ways of theoretically assessing clinical reasoning ability. In the clinical setting, these skills can be tested in most forms of workplace based assessment. We recommend that clinical reasoning must be taught at all levels of medical training as it improves clinician performance and reduces cognitive errors.

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

NASA Astrophysics Data System (ADS)

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.

Circle of care modelling: an approach to assist in reasoning about healthcare change using a patient-centric system.

PubMed

Price, Morgan

2016-10-04

Many health system and health Information and Communication Technology (ICT) projects do not achieve their expected benefits. This paper presents an approach to exploring changes in the healthcare system to better understand the expected improvements and other changes by using a patient-centric modelling approach. Circle of care modeling (CCM) was designed to assist stakeholders in considering healthcare system changes using a patient centric approach. The CCM approach is described. It includes four steps, based on soft systems methodology: finding out, conceptual modelling, structured discussion, and describing potential improvements. There are four visualizations that are used though this process: patient-persona based rich pictures of care flows (as part of finding out), and three models: provider view, communication view, and information repository view (as part of conceptual modelling). Three case studies are presented where CCM was applied to different real-world healthcare problems: 1. Seeking improvements in continuity of care for end of life patients. 2. Exploring current practices for medication communication for ambulatory patients prior to an update of a jurisdictional drug information system. 3. Deciding how to improve attachment of patients to primary care. The cases illustrate how CCM helped stakeholders reason from a patient centered approach about gaps and improvements in care such as: data fragmentation (in 1), coordination efforts of medication management (in 2), and deciding to support a community health centre for unattached patients (in 3). The circle of care modelling approach has proved to be a useful tool in assisting stakeholders explore health system change in a patient centric approach. It is one way to instantiate the important principle of being patient centered into practice when considering health system changes.

Towards Measurement of Confidence in Safety Cases

NASA Technical Reports Server (NTRS)

Denney, Ewen; Paim Ganesh J.; Habli, Ibrahim

2011-01-01

Arguments in safety cases are predominantly qualitative. This is partly attributed to the lack of sufficient design and operational data necessary to measure the achievement of high-dependability targets, particularly for safety-critical functions implemented in software. The subjective nature of many forms of evidence, such as expert judgment and process maturity, also contributes to the overwhelming dependence on qualitative arguments. However, where data for quantitative measurements is systematically collected, quantitative arguments provide far more benefits over qualitative arguments, in assessing confidence in the safety case. In this paper, we propose a basis for developing and evaluating integrated qualitative and quantitative safety arguments based on the Goal Structuring Notation (GSN) and Bayesian Networks (BN). The approach we propose identifies structures within GSN-based arguments where uncertainties can be quantified. BN are then used to provide a means to reason about confidence in a probabilistic way. We illustrate our approach using a fragment of a safety case for an unmanned aerial system and conclude with some preliminary observations

Conceptualizing Rolling Motion through an Extreme Case Reasoning Approach

ERIC Educational Resources Information Center

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…

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

PubMed

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.

Formalization and analysis of reasoning by assumption.

PubMed

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.

Hybrid approach for robust diagnostics of cutting tools

NASA Astrophysics Data System (ADS)

Ramamurthi, K.; Hough, C. L., Jr.

1994-03-01

A new multisensor based hybrid technique has been developed for robust diagnosis of cutting tools. The technique combines the concepts of pattern classification and real-time knowledge based systems (RTKBS) and draws upon their strengths; learning facility in the case of pattern classification and a higher level of reasoning in the case of RTKBS. It eliminates some of their major drawbacks: false alarms or delayed/lack of diagnosis in case of pattern classification and tedious knowledge base generation in case of RTKBS. It utilizes a dynamic distance classifier, developed upon a new separability criterion and a new definition of robust diagnosis for achieving these benefits. The promise of this technique has been proven concretely through an on-line diagnosis of drill wear. Its suitability for practical implementation is substantiated by the use of practical, inexpensive, machine-mounted sensors and low-cost delivery systems.

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

PubMed

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.

Risk-based corrective action and brownfields restorations. Geotechnical special publication No. 82

DOE Office of Scientific and Technical Information (OSTI.GOV)

Benson, C.H.; Meegoda, J.N.; Gilbert, R.G.

Risk-based corrective action (RBCA) and brownfields restoration now play a significant role in contaminated site remediation. RBCA provides the necessary framework for balancing health and environmental risks with costs while targeting the ultimate objective of sensible remediation. Brownfields is a reasonable, economical approach for remediating contaminated land intended for industrial use. This book describes the tools and methods employed in RBCA, and provides illustrative examples through case histories with emphasis on brownfields restorations.

Recurrent Pneumonia in Children: A Reasoned Diagnostic Approach and a Single Centre Experience.

PubMed

Montella, Silvia; Corcione, Adele; Santamaria, Francesca

2017-01-29

Recurrent pneumonia (RP), i.e., at least two episodes of pneumonia in one year or three episodes ever with intercritical radiographic clearing of densities, occurs in 7.7%-9% of children with community-acquired pneumonia. In RP, the challenge is to discriminate between children with self-limiting or minor problems, that do not require a diagnostic work-up, and those with an underlying disease. The aim of the current review is to discuss a reasoned diagnostic approach to RP in childhood. Particular emphasis has been placed on which children should undergo a diagnostic work-up and which tests should be performed. A pediatric case series is also presented, in order to document a single centre experience of RP. A management algorithm for the approach to children with RP, based on the evidence from a literature review, is proposed. Like all algorithms, it is not meant to replace clinical judgment, but it should drive physicians to adopt a systematic approach to pediatric RP and provide a useful guide to the clinician.

A structured framework for assessing sensitivity to missing data assumptions in longitudinal clinical trials.

PubMed

Mallinckrodt, C H; Lin, Q; Molenberghs, M

2013-01-01

The objective of this research was to demonstrate a framework for drawing inference from sensitivity analyses of incomplete longitudinal clinical trial data via a re-analysis of data from a confirmatory clinical trial in depression. A likelihood-based approach that assumed missing at random (MAR) was the primary analysis. Robustness to departure from MAR was assessed by comparing the primary result to those from a series of analyses that employed varying missing not at random (MNAR) assumptions (selection models, pattern mixture models and shared parameter models) and to MAR methods that used inclusive models. The key sensitivity analysis used multiple imputation assuming that after dropout the trajectory of drug-treated patients was that of placebo treated patients with a similar outcome history (placebo multiple imputation). This result was used as the worst reasonable case to define the lower limit of plausible values for the treatment contrast. The endpoint contrast from the primary analysis was - 2.79 (p = .013). In placebo multiple imputation, the result was - 2.17. Results from the other sensitivity analyses ranged from - 2.21 to - 3.87 and were symmetrically distributed around the primary result. Hence, no clear evidence of bias from missing not at random data was found. In the worst reasonable case scenario, the treatment effect was 80% of the magnitude of the primary result. Therefore, it was concluded that a treatment effect existed. The structured sensitivity framework of using a worst reasonable case result based on a controlled imputation approach with transparent and debatable assumptions supplemented a series of plausible alternative models under varying assumptions was useful in this specific situation and holds promise as a generally useful framework. Copyright © 2012 John Wiley & Sons, Ltd.

What Physicians Reason about during Admission Case Review

ERIC Educational Resources Information Center

Juma, Salina; Goldszmidt, Mark

2017-01-01

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…

Using computer aided case based reasoning to support clinical reasoning in community occupational therapy.

PubMed

Taylor, Bruce; Robertson, David; Wiratunga, Nirmalie; Craw, Susan; Mitchell, Dawn; Stewart, Elaine

2007-08-01

Community occupational therapists have long been involved in the provision of environmental control systems. Diverse electronic technologies with the potential to improve the health and quality of life of selected clients have developed rapidly in recent years. Occupational therapists employ clinical reasoning in order to determine the most appropriate technology to meet the needs of individual clients. This paper describes a number of the drivers that may increase the adoption of information and communication technologies in the occupational therapy profession. It outlines case based reasoning as understood in the domains of expert systems and knowledge management and presents the preliminary results of an ongoing investigation into the potential of a prototype computer aided case based reasoning tool to support the clinical reasoning of community occupational therapists in the process of assisting clients to choose home electronic assistive or smart house technology.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

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

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 evidentialmore » 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.« less

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

ERIC Educational Resources Information Center

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…

A Case-Based Reasoning Method with Rank Aggregation

NASA Astrophysics Data System (ADS)

Sun, Jinhua; Du, Jiao; Hu, Jian

2018-03-01

In order to improve the accuracy of case-based reasoning (CBR), this paper addresses a new CBR framework with the basic principle of rank aggregation. First, the ranking methods are put forward in each attribute subspace of case. The ordering relation between cases on each attribute is got between cases. Then, a sorting matrix is got. Second, the similar case retrieval process from ranking matrix is transformed into a rank aggregation optimal problem, which uses the Kemeny optimal. On the basis, a rank aggregation case-based reasoning algorithm, named RA-CBR, is designed. The experiment result on UCI data sets shows that case retrieval accuracy of RA-CBR algorithm is higher than euclidean distance CBR and mahalanobis distance CBR testing.So we can get the conclusion that RA-CBR method can increase the performance and efficiency of CBR.

[Communication management of collaborative networks of science, technology and innovation in health].

PubMed

Martins, Wagner de Jesus; Artmann, Elizabeth; Rivera, Francisco Javier Uribe

2012-12-01

The objective of the article was to propose a model of communication management of networks for the Health Innovation System in Brazil. The health production complex and its relationship with the nation's development are addressed and some suggestions for operationalization of the proposed model are also presented. The discussion is based on Habermas' theory and similar cases from other countries. Communication strategies and approaches to commitment dialogue for concerted actions and consensus-building based on critical reasoning may help strengthen democratic networks.

Reasoning over Taxonomic Change: Exploring Alignments for the Perelleschus Use Case

PubMed Central

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. PMID:25700173

Faculty Development for Fostering Clinical Reasoning Skills in Early Medical Students Using a Modified Bayesian Approach.

PubMed

Addy, Tracie Marcella; Hafler, Janet; Galerneau, France

2016-01-01

Clinical reasoning is a necessary skill for medical students to acquire in the course of their education, and there is evidence that they can start this process at the undergraduate level. However, physician educators who are experts in their given fields may have difficulty conveying their complex thought processes to students. Providing faculty development that equips educators with tools to teach clinical reasoning may support skill development in early medical students. We provided faculty development on a modified Bayesian method of teaching clinical reasoning to clinician educators who facilitated small-group, case-based workshops with 2nd-year medical students. We interviewed them before and after the module regarding their perceptions on teaching clinical reasoning. We solicited feedback from the students about the effectiveness of the method in developing their clinical reasoning skills. We carried out this project during an institutional curriculum rebuild where clinical reasoning was a defined goal. At the time of the intervention, there was also increased involvement of the Teaching and Learning Center in elevating the status of teaching and learning. There was high overall satisfaction with the faculty development program. Both the faculty and the students described the modified Bayesian approach as effective in fostering the development of clinical reasoning skills. Through this work, we learned how to form a beneficial partnership between a clinician educator and Teaching and Learning Center to promote faculty development on a clinical reasoning teaching method for early medical students. We uncovered challenges faced by both faculty and early learners in this study. We observed that our faculty chose to utilize the method of teaching clinical reasoning in a variety of manners in the classroom. Despite obstacles and differing approaches utilized, we believe that this model can be emulated at other institutions to foster the development of clinical reasoning skills in preclerkship students.

Massively parallel support for a case-based planning system

NASA Technical Reports Server (NTRS)

Kettler, Brian P.; Hendler, James A.; Anderson, William A.

1993-01-01

Case-based planning (CBP), a kind of case-based reasoning, is a technique in which previously generated plans (cases) are stored in memory and can be reused to solve similar planning problems in the future. CBP can save considerable time over generative planning, in which a new plan is produced from scratch. CBP thus offers a potential (heuristic) mechanism for handling intractable problems. One drawback of CBP systems has been the need for a highly structured memory to reduce retrieval times. This approach requires significant domain engineering and complex memory indexing schemes to make these planners efficient. In contrast, our CBP system, CaPER, uses a massively parallel frame-based AI language (PARKA) and can do extremely fast retrieval of complex cases from a large, unindexed memory. The ability to do fast, frequent retrievals has many advantages: indexing is unnecessary; very large case bases can be used; memory can be probed in numerous alternate ways; and queries can be made at several levels, allowing more specific retrieval of stored plans that better fit the target problem with less adaptation. In this paper we describe CaPER's case retrieval techniques and some experimental results showing its good performance, even on large case bases.

On-Line Modal State Monitoring of Slowly Time-Varying Structures

NASA Technical Reports Server (NTRS)

Johnson, Erik A.; Bergman, Lawrence A.; Voulgaris, Petros G.

1997-01-01

Monitoring the dynamic response of structures is often performed for a variety of reasons. These reasons include condition-based maintenance, health monitoring, performance improvements, and control. In many cases the data analysis that is performed is part of a repetitive decision-making process, and in these cases the development of effective on-line monitoring schemes help to speed the decision-making process and reduce the risk of erroneous decisions. This report investigates the use of spatial modal filters for tracking the dynamics of slowly time-varying linear structures. The report includes an overview of modal filter theory followed by an overview of several structural system identification methods. Included in this discussion and comparison are H-infinity, eigensystem realization, and several time-domain least squares approaches. Finally, a two-stage adaptive on-line monitoring scheme is developed and evaluated.

Case-based medical informatics

PubMed Central

Pantazi, Stefan V; Arocha, José F; Moehr, Jochen R

2004-01-01

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 of problem-solving and powerful case matching mechanisms), technical solutions are challenging. Finally, we discuss the major challenges for a technical solution: case record comprehensiveness, organization of information on similarity principles, development of pattern recognition and solving ethical issues. Summary Medical Informatics is an applied science that should be committed to advancing patient-centered medicine through individual knowledge processing. Case-based reasoning is the technical solution that enables a continuous individual knowledge processing and could be applied providing that challenges and ethical issues arising are addressed appropriately. PMID:15533257

The role of professional knowledge in case-based reasoning in practical ethics.

PubMed

Pinkus, Rosa Lynn; Gloeckner, Claire; Fortunato, Angela

2015-06-01

The use of case-based reasoning in teaching professional ethics has come of age. The fields of medicine, engineering, and business all have incorporated ethics case studies into leading textbooks and journal articles, as well as undergraduate and graduate professional ethics courses. The most recent guidelines from the National Institutes of Health recognize case studies and face-to-face discussion as best practices to be included in training programs for the Responsible Conduct of Research. While there is a general consensus that case studies play a central role in the teaching of professional ethics, there is still much to be learned regarding how professionals learn ethics using case-based reasoning. Cases take many forms, and there are a variety of ways to write them and use them in teaching. This paper reports the results of a study designed to investigate one of the issues in teaching case-based ethics: the role of one's professional knowledge in learning methods of moral reasoning. Using a novel assessment instrument, we compared case studies written and analyzed by three groups of students whom we classified as: (1) Experts in a research domain in bioengineering. (2) Novices in a research domain in bioengineering. (3) The non-research group--students using an engineering domain in which they were interested but had no in-depth knowledge. This study demonstrates that a student's level of understanding of a professional knowledge domain plays a significant role in learning moral reasoning skills.

Data Clustering and Evolving Fuzzy Decision Tree for Data Base Classification Problems

NASA Astrophysics Data System (ADS)

Chang, Pei-Chann; Fan, Chin-Yuan; Wang, Yen-Wen

Data base classification suffers from two well known difficulties, i.e., the high dimensionality and non-stationary variations within the large historic data. This paper presents a hybrid classification model by integrating a case based reasoning technique, a Fuzzy Decision Tree (FDT), and Genetic Algorithms (GA) to construct a decision-making system for data classification in various data base applications. The model is major based on the idea that the historic data base can be transformed into a smaller case-base together with a group of fuzzy decision rules. As a result, the model can be more accurately respond to the current data under classifying from the inductions by these smaller cases based fuzzy decision trees. Hit rate is applied as a performance measure and the effectiveness of our proposed model is demonstrated by experimentally compared with other approaches on different data base classification applications. The average hit rate of our proposed model is the highest among others.

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

PubMed

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 patient cases treated with three-dimensional (3D)-conformal radiotherapy. Neural networks-based adaptation improved the success rate of the CBR system with no adaptation by 12%. However, naive Bayes classifier did not improve the current retrieval results as it did not consider the interplay among attributes. The adaptation-guided retrieval of the case for beam number improved the success rate of the CBR system by 29%. However, it did not demonstrate good performance for the beam angle adaptation. Its success rate was 29% versus 39% when no adaptation was performed. The obtained empirical results demonstrate that the proposed adaptation methods improve the performance of the existing CBR system in recommending the number of beams to use. However, we also conclude that to be effective, the proposed adaptation of beam angles requires a large number of relevant cases in the case base. Copyright © 2016 Elsevier B.V. All rights reserved.

Using Bayesian networks to guide the assessment of new evidence in an appeal case

PubMed Central

Smit, Nadine M.; Lagnado, David A.; Morgan, Ruth M.; Fenton, Norman E.

2016-01-01

When new forensic evidence becomes available after a conviction there is no systematic framework to help lawyers to determine whether it raises sufficient questions about the verdict in order to launch an appeal. This paper presents such a framework driven by a recent case, in which a defendant was convicted primarily on the basis of audio evidence, but where subsequent analysis of the evidence revealed additional sounds that were not considered during the trial. The framework is intended to overcome the gap between what is generally known from scientific analyses and what is hypothesized in a legal setting. It is based on Bayesian networks (BNs) which have the potential to be a structured and understandable way to evaluate the evidence in a specific case context. However, BN methods suffered a setback with regards to the use in court due to the confusing way they have been used in some legal cases in the past. To address this concern, we show the extent to which the reasoning and decisions within the particular case can be made explicit and transparent. The BN approach enables us to clearly define the relevant propositions and evidence, and uses sensitivity analysis to assess the impact of the evidence under different assumptions. The results show that such a framework is suitable to identify information that is currently missing, yet clearly crucial for a valid and complete reasoning process. Furthermore, a method is provided whereby BNs can serve as a guide to not only reason with incomplete evidence in forensic cases, but also identify very specific research questions that should be addressed to extend the evidence base and solve similar issues in the future. PMID:27376015

Using Bayesian networks to guide the assessment of new evidence in an appeal case.

PubMed

Smit, Nadine M; Lagnado, David A; Morgan, Ruth M; Fenton, Norman E

2016-05-25

When new forensic evidence becomes available after a conviction there is no systematic framework to help lawyers to determine whether it raises sufficient questions about the verdict in order to launch an appeal. This paper presents such a framework driven by a recent case, in which a defendant was convicted primarily on the basis of audio evidence, but where subsequent analysis of the evidence revealed additional sounds that were not considered during the trial. The framework is intended to overcome the gap between what is generally known from scientific analyses and what is hypothesized in a legal setting. It is based on Bayesian networks (BNs) which have the potential to be a structured and understandable way to evaluate the evidence in a specific case context. However, BN methods suffered a setback with regards to the use in court due to the confusing way they have been used in some legal cases in the past. To address this concern, we show the extent to which the reasoning and decisions within the particular case can be made explicit and transparent. The BN approach enables us to clearly define the relevant propositions and evidence, and uses sensitivity analysis to assess the impact of the evidence under different assumptions. The results show that such a framework is suitable to identify information that is currently missing, yet clearly crucial for a valid and complete reasoning process. Furthermore, a method is provided whereby BNs can serve as a guide to not only reason with incomplete evidence in forensic cases, but also identify very specific research questions that should be addressed to extend the evidence base and solve similar issues in the future.

Feasibility of Self-Reflection as a Tool to Balance Clinical Reasoning Strategies

ERIC Educational Resources Information Center

Sibbald, Matthew; de Bruin, Anique B. H.

2012-01-01

Clinicians are believed to use two predominant reasoning strategies: system 1 based pattern recognition, and system 2 based analytical reasoning. Balancing these cognitive reasoning strategies is widely believed to reduce diagnostic error. However, clinicians approach different problems with different reasoning strategies. This study explores…

Ontology-Based Exchange and Immediate Application of Business Calculation Definitions for Online Analytical Processing

NASA Astrophysics Data System (ADS)

Kehlenbeck, Matthias; Breitner, Michael H.

Business users define calculated facts based on the dimensions and facts contained in a data warehouse. These business calculation definitions contain necessary knowledge regarding quantitative relations for deep analyses and for the production of meaningful reports. The business calculation definitions are implementation and widely organization independent. But no automated procedures facilitating their exchange across organization and implementation boundaries exist. Separately each organization currently has to map its own business calculations to analysis and reporting tools. This paper presents an innovative approach based on standard Semantic Web technologies. This approach facilitates the exchange of business calculation definitions and allows for their automatic linking to specific data warehouses through semantic reasoning. A novel standard proxy server which enables the immediate application of exchanged definitions is introduced. Benefits of the approach are shown in a comprehensive case study.

Computer aided fixture design - A case based approach

NASA Astrophysics Data System (ADS)

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.

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

ERIC Educational Resources Information Center

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…

Extending Case-Based Reasoning (CBR) Approaches to Semi-automated Network Alert Reporting

DTIC Science & Technology

2013-04-01

connecting to the domain is likely infected with malware, or may have been exposed to malicious code. -- Detailed Information: The Sourcefire VRT ...to be generated by malware. After applying an extensive whitelist, the VRT pulls out the most commonly visited domains and adds them to its...malicious software. The VRT recommends ClamAV for Windows 3.0. 39 -- Contributors: Sourcefire Vulnerability Research Team -- Additional

An Automated Approach to Reasoning Under Multiple Perspectives

NASA Technical Reports Server (NTRS)

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 (focusing on "perhaps"). Any conclusion reached under a line of reasoning that employs such an assertion or its associated implications should somehow reflect the employed perspectives. The investigators made significant progress in developing an approach that would enable a system to conduct reasoning operations over assertions of this kind while maintaining consistency in its knowledge bases. Significant accomplishments were made in the areas of: 1) integration and inferencing; 2) generation of perspectives, including wholistic ad composite views; and 3) consistency maintenance.

A dynamic case-based planning system for space station application

NASA Technical Reports Server (NTRS)

Oppacher, F.; Deugo, D.

1988-01-01

We are currently investigating the use of a case-based reasoning approach to develop a dynamic planning system. The dynamic planning system (DPS) is designed to perform resource management, i.e., to efficiently schedule tasks both with and without failed components. This approach deviates from related work on scheduling and on planning in AI in several aspects. In particular, an attempt is made to equip the planner with an ability to cope with a changing environment by dynamic replanning, to handle resource constraints and feedback, and to achieve some robustness and autonomy through plan learning by dynamic memory techniques. We briefly describe the proposed architecture of DPS and its four major components: the PLANNER, the plan EXECUTOR, the dynamic REPLANNER, and the plan EVALUATOR. The planner, which is implemented in Smalltalk, is being evaluated for use in connection with the Space Station Mobile Service System (MSS).

Prognostics of Lithium-Ion Batteries Based on Wavelet Denoising and DE-RVM

PubMed Central

Zhang, Chaolong; He, Yigang; Yuan, Lifeng; Xiang, Sheng; Wang, Jinping

2015-01-01

Lithium-ion batteries are widely used in many electronic systems. Therefore, it is significantly important to estimate the lithium-ion battery's remaining useful life (RUL), yet very difficult. One important reason is that the measured battery capacity data are often subject to the different levels of noise pollution. In this paper, a novel battery capacity prognostics approach is presented to estimate the RUL of lithium-ion batteries. Wavelet denoising is performed with different thresholds in order to weaken the strong noise and remove the weak noise. Relevance vector machine (RVM) improved by differential evolution (DE) algorithm is utilized to estimate the battery RUL based on the denoised data. An experiment including battery 5 capacity prognostics case and battery 18 capacity prognostics case is conducted and validated that the proposed approach can predict the trend of battery capacity trajectory closely and estimate the battery RUL accurately. PMID:26413090

Assessing the Effectiveness of Problem-Based Learning as a New Approach on Health Care Provider Ethical Reasoning Development in Shiraz University of Medical Sciences.

PubMed

Bazrafcan, Leila; Takmil, Farnaz; Shokrpour, Nasrin

2018-06-18

Problem-based learning (PBL) has become a distinct approach in learning. To assess the effectiveness of PBL in teaching ethics to medical students and the effect it has on their ethical reasoning, we decided to hold a PBL ethics workshop and then evaluate them based on pretest and posttest. This quasi-experimental comparative study in Shiraz University of Medical Sciences was designed based on pretest-posttest nonequivalent groups. After obtaining their consent, 120 health care providers were randomly selected and assigned in 4 groups and then asked to attend the ethics workshop. For measuring the participants' ethical reasoning through pretesting and posttesting, a case study consisting of 21 multiple-choice questions (cognitive domain-apply level) was performed. Data were then collected using a questionnaire, which was completed by the participants and analyzed using SPSS software (version 17). The comparison between the participants' attitude and knowledge toward ethics before and after the workshop revealed that all indices in the cognitive domain were changed (P < .001). The scores of pretest and posttest were significantly different. As to the results of our study, the PBL groups showed a more positive learning attitude and higher motivation in comparison with the control group who were subjected to traditional-based method of learning. The result of our study suggests that PBL can and should be used as an alternative method in teaching ethics in medical students because it is more effective and motivates the students.

A General Safety Assessment for Purified Food Ingredients Derived From Biotechnology Crops: Case Study of Brazilian Sugar and Beverages Produced From Insect-Protected Sugarcane.

PubMed

Kennedy, Reese D; Cheavegatti-Gianotto, Adriana; de Oliveira, Wladecir S; Lirette, Ronald P; Hjelle, Jerry J

2018-01-01

Insect-protected sugarcane that expresses Cry1Ab has been developed in Brazil. Analysis of trade information has shown that effectively all the sugarcane-derived Brazilian exports are raw or refined sugar and ethanol. The fact that raw and refined sugar are highly purified food ingredients, with no detectable transgenic protein, provides an interesting case study of a generalized safety assessment approach. In this study, both the theoretical protein intakes and safety assessments of Cry1Ab, Cry1Ac, NPTII, and Bar proteins used in insect-protected biotechnology crops were examined. The potential consumption of these proteins was examined using local market research data of average added sugar intakes in eight diverse and representative Brazilian raw and refined sugar export markets (Brazil, Canada, China, Indonesia, India, Japan, Russia, and the USA). The average sugar intakes, which ranged from 5.1 g of added sugar/person/day (India) to 126 g sugar/p/day (USA) were used to calculated possible human exposure. The theoretical protein intake estimates were carried out in the "Worst-case" scenario, assumed that 1 μg of newly-expressed protein is detected/g of raw or refined sugar; and the "Reasonable-case" scenario assumed 1 ng protein/g sugar. The "Worst-case" scenario was based on results of detailed studies of sugarcane processing in Brazil that showed that refined sugar contains less than 1 μg of total plant protein /g refined sugar. The "Reasonable-case" scenario was based on assumption that the expression levels in stalk of newly-expressed proteins were less than 0.1% of total stalk protein. Using these calculated protein intake values from the consumption of sugar, along with the accepted NOAEL levels of the four representative proteins we concluded that safety margins for the "Worst-case" scenario ranged from 6.9 × 10 5 to 5.9 × 10 7 and for the "Reasonable-case" scenario ranged from 6.9 × 10 8 to 5.9 × 10 10 . These safety margins are very high due to the extremely low possible exposures and the high NOAELs for these non-toxic proteins. This generalized approach to the safety assessment of highly purified food ingredients like sugar illustrates that sugar processed from Brazilian GM varieties are safe for consumption in representative markets globally.

The prediction of breast cancer biopsy outcomes using two CAD approaches that both emphasize an intelligible decision process

DOE Office of Scientific and Technical Information (OSTI.GOV)

Elter, M.; Schulz-Wendtland, R.; Wittenberg, T.

2007-11-15

Mammography is the most effective method for breast cancer screening available today. However, the low positive predictive value of breast biopsy resulting from mammogram interpretation leads to approximately 70% unnecessary biopsies with benign outcomes. To reduce the high number of unnecessary breast biopsies, several computer-aided diagnosis (CAD) systems have been proposed in the last several years. These systems help physicians in their decision to perform a breast biopsy on a suspicious lesion seen in a mammogram or to perform a short term follow-up examination instead. We present two novel CAD approaches that both emphasize an intelligible decision process to predictmore » breast biopsy outcomes from BI-RADS findings. An intelligible reasoning process is an important requirement for the acceptance of CAD systems by physicians. The first approach induces a global model based on decison-tree learning. The second approach is based on case-based reasoning and applies an entropic similarity measure. We have evaluated the performance of both CAD approaches on two large publicly available mammography reference databases using receiver operating characteristic (ROC) analysis, bootstrap sampling, and the ANOVA statistical significance test. Both approaches outperform the diagnosis decisions of the physicians. Hence, both systems have the potential to reduce the number of unnecessary breast biopsies in clinical practice. A comparison of the performance of the proposed decision tree and CBR approaches with a state of the art approach based on artificial neural networks (ANN) shows that the CBR approach performs slightly better than the ANN approach, which in turn results in slightly better performance than the decision-tree approach. The differences are statistically significant (p value <0.001). On 2100 masses extracted from the DDSM database, the CRB approach for example resulted in an area under the ROC curve of A(z)=0.89{+-}0.01, the decision-tree approach in A(z)=0.87{+-}0.01, and the ANN approach in A(z)=0.88{+-}0.01.« less

Properties of inductive reasoning.

PubMed

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.

Deriving Safety Cases from Automatically Constructed Proofs

NASA Technical Reports Server (NTRS)

Basir, Nurlida; Denney, Ewen; Fischer, Bernd

2009-01-01

Formal proofs provide detailed justification for the validity of claims and are widely used in formal software development methods. However, they are often complex and difficult to understand, because the formalism in which they are constructed and encoded is usually machine-oriented, and they may also be based on assumptions that are not justified. This causes concerns about the trustworthiness of using formal proofs as arguments in safety-critical applications. Here, we present an approach to develop safety cases that correspond to formal proofs found by automated theorem provers and reveal the underlying argumentation structure and top-level assumptions. We concentrate on natural deduction style proofs, which are closer to human reasoning than resolution proofs, and show how to construct the safety cases by covering the natural deduction proof tree with corresponding safety case fragments. We also abstract away logical book-keeping steps, which reduces the size of the constructed safety cases. We show how the approach can be applied to the proofs found by the Muscadet prover.

Tool use and affordance: Manipulation-based versus reasoning-based approaches.

PubMed

Osiurak, François; Badets, Arnaud

2016-10-01

Tool use is a defining feature of human species. Therefore, a fundamental issue is to understand the cognitive bases of human tool use. Given that people cannot use tools without manipulating them, proponents of the manipulation-based approach have argued that tool use might be supported by the simulation of past sensorimotor experiences, also sometimes called affordances. However, in the meanwhile, evidence has been accumulated demonstrating the critical role of mechanical knowledge in tool use (i.e., the reasoning-based approach). The major goal of the present article is to examine the validity of the assumptions derived from the manipulation-based versus the reasoning-based approach. To do so, we identified 3 key issues on which the 2 approaches differ, namely, (a) the reference frame issue, (b) the intention issue, and (c) the action domain issue. These different issues will be addressed in light of studies in experimental psychology and neuropsychology that have provided valuable contributions to the topic (i.e., tool-use interaction, orientation effect, object-size effect, utilization behavior and anarchic hand, tool use and perception, apraxia of tool use, transport vs. use actions). To anticipate our conclusions, the reasoning-based approach seems to be promising for understanding the current literature, even if it is not fully satisfactory because of a certain number of findings easier to interpret with regard to the manipulation-based approach. A new avenue for future research might be to develop a framework accommodating both approaches, thereby shedding a new light on the cognitive bases of human tool use and affordances. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

MapReduce Based Parallel Bayesian Network for Manufacturing Quality Control

NASA Astrophysics Data System (ADS)

Zheng, Mao-Kuan; Ming, Xin-Guo; Zhang, Xian-Yu; Li, Guo-Ming

2017-09-01

Increasing complexity of industrial products and manufacturing processes have challenged conventional statistics based quality management approaches in the circumstances of dynamic production. A Bayesian network and big data analytics integrated approach for manufacturing process quality analysis and control is proposed. Based on Hadoop distributed architecture and MapReduce parallel computing model, big volume and variety quality related data generated during the manufacturing process could be dealt with. Artificial intelligent algorithms, including Bayesian network learning, classification and reasoning, are embedded into the Reduce process. Relying on the ability of the Bayesian network in dealing with dynamic and uncertain problem and the parallel computing power of MapReduce, Bayesian network of impact factors on quality are built based on prior probability distribution and modified with posterior probability distribution. A case study on hull segment manufacturing precision management for ship and offshore platform building shows that computing speed accelerates almost directly proportionally to the increase of computing nodes. It is also proved that the proposed model is feasible for locating and reasoning of root causes, forecasting of manufacturing outcome, and intelligent decision for precision problem solving. The integration of bigdata analytics and BN method offers a whole new perspective in manufacturing quality control.

An Analysis of Machine- and Human-Analytics in Classification.

PubMed

Tam, Gary K L; Kothari, Vivek; Chen, Min

2017-01-01

In this work, we present a study that traces the technical and cognitive processes in two visual analytics applications to a common theoretic model of soft knowledge that may be added into a visual analytics process for constructing a decision-tree model. Both case studies involved the development of classification models based on the "bag of features" approach. Both compared a visual analytics approach using parallel coordinates with a machine-learning approach using information theory. Both found that the visual analytics approach had some advantages over the machine learning approach, especially when sparse datasets were used as the ground truth. We examine various possible factors that may have contributed to such advantages, and collect empirical evidence for supporting the observation and reasoning of these factors. We propose an information-theoretic model as a common theoretic basis to explain the phenomena exhibited in these two case studies. Together we provide interconnected empirical and theoretical evidence to support the usefulness of visual analytics.

[Behavioral phenotypes: cognitive and emotional explanation].

PubMed

Pérez-Alvarez, F; Timoneda-Gallart, C

We present a series of Behavioural phenotypes treated with neurocognitive and neuroemotional procedure. A sample of 26 cases were selected according to qualitative methodology from neuropediatric patients. The method was based on using the PASS theory of intelligence to approach the cognitive problem and the theory of masquerade behaviour as self-defence to solve the emotional problem. Both theories have neurological bases. DN:CAS battery was utilized for assessment of cognitive processes. On the other hand, analysis of cases was carried out doing data analysis with video recorder device. All cases were considered responder cases although in different degree. The responder was defined as the patient which reached better intellectual achievement with respect to cognitive function and which gave up, at least partially, masquerade Behaviour with respect to emotional function. The Behaviour of the Behavioural phenotypes has neurological rationale. The PASS theory and the planning, in particular, supported by prefrontal cortex justifies consistently some behaviours. The masquerade Behaviour theory is explained by the fear emotional response mechanism which means emotion is a cerebral processing with neurological rationale. The Behavioural phenotypes are Behaviours and every Behaviour can be explained by neurological reasons both cognitive and emotional reasons. So, they can be treated by a cognitive and emotional procedure understood in the light of the neurology.

A public health decision support system model using reasoning methods.

PubMed

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.

Probabilistic self-localisation on a qualitative map based on occlusions

NASA Astrophysics Data System (ADS)

Santos, Paulo E.; Martins, Murilo F.; Fenelon, Valquiria; Cozman, Fabio G.; Dee, Hannah M.

2016-09-01

Spatial knowledge plays an essential role in human reasoning, permitting tasks such as locating objects in the world (including oneself), reasoning about everyday actions and describing perceptual information. This is also the case in the field of mobile robotics, where one of the most basic (and essential) tasks is the autonomous determination of the pose of a robot with respect to a map, given its perception of the environment. This is the problem of robot self-localisation (or simply the localisation problem). This paper presents a probabilistic algorithm for robot self-localisation that is based on a topological map constructed from the observation of spatial occlusion. Distinct locations on the map are defined by means of a classical formalism for qualitative spatial reasoning, whose base definitions are closer to the human categorisation of space than traditional, numerical, localisation procedures. The approach herein proposed was systematically evaluated through experiments using a mobile robot equipped with a RGB-D sensor. The results obtained show that the localisation algorithm is successful in locating the robot in qualitatively distinct regions.

Uncertainty management by relaxation of conflicting constraints in production process scheduling

NASA Technical Reports Server (NTRS)

Dorn, Juergen; Slany, Wolfgang; Stary, Christian

1992-01-01

Mathematical-analytical methods as used in Operations Research approaches are often insufficient for scheduling problems. This is due to three reasons: the combinatorial complexity of the search space, conflicting objectives for production optimization, and the uncertainty in the production process. Knowledge-based techniques, especially approximate reasoning and constraint relaxation, are promising ways to overcome these problems. A case study from an industrial CIM environment, namely high-grade steel production, is presented to demonstrate how knowledge-based scheduling with the desired capabilities could work. By using fuzzy set theory, the applied knowledge representation technique covers the uncertainty inherent in the problem domain. Based on this knowledge representation, a classification of jobs according to their importance is defined which is then used for the straightforward generation of a schedule. A control strategy which comprises organizational, spatial, temporal, and chemical constraints is introduced. The strategy supports the dynamic relaxation of conflicting constraints in order to improve tentative schedules.

Performance of Case-Based Reasoning Retrieval Using Classification Based on Associations versus Jcolibri and FreeCBR: A Further Validation Study

NASA Astrophysics Data System (ADS)

Aljuboori, Ahmed S.; Coenen, Frans; Nsaif, Mohammed; Parsons, David J.

2018-05-01

Case-Based Reasoning (CBR) plays a major role in expert system research. However, a critical problem can be met when a CBR system retrieves incorrect cases. Class Association Rules (CARs) have been utilized to offer a potential solution in a previous work. The aim of this paper was to perform further validation of Case-Based Reasoning using a Classification based on Association Rules (CBRAR) to enhance the performance of Similarity Based Retrieval (SBR). The CBRAR strategy uses a classed frequent pattern tree algorithm (FP-CAR) in order to disambiguate wrongly retrieved cases in CBR. The research reported in this paper makes contributions to both fields of CBR and Association Rules Mining (ARM) in that full target cases can be extracted from the FP-CAR algorithm without invoking P-trees and union operations. The dataset used in this paper provided more efficient results when the SBR retrieves unrelated answers. The accuracy of the proposed CBRAR system outperforms the results obtained by existing CBR tools such as Jcolibri and FreeCBR.

A hybrid intelligence approach to artifact recognition in digital publishing

NASA Astrophysics Data System (ADS)

Vega-Riveros, J. Fernando; Santos Villalobos, Hector J.

2006-02-01

The system presented integrates rule-based and case-based reasoning for artifact recognition in Digital Publishing. In Variable Data Printing (VDP) human proofing could result prohibitive since a job could contain millions of different instances that may contain two types of artifacts: 1) evident defects, like a text overflow or overlapping 2) style-dependent artifacts, subtle defects that show as inconsistencies with regard to the original job design. We designed a Knowledge-Based Artifact Recognition tool for document segmentation, layout understanding, artifact detection, and document design quality assessment. Document evaluation is constrained by reference to one instance of the VDP job proofed by a human expert against the remaining instances. Fundamental rules of document design are used in the rule-based component for document segmentation and layout understanding. Ambiguities in the design principles not covered by the rule-based system are analyzed by case-based reasoning, using the Nearest Neighbor Algorithm, where features from previous jobs are used to detect artifacts and inconsistencies within the document layout. We used a subset of XSL-FO and assembled a set of 44 document samples. The system detected all the job layout changes, while obtaining an overall average accuracy of 84.56%, with the highest accuracy of 92.82%, for overlapping and the lowest, 66.7%, for the lack-of-white-space.

Application of the critical pathway and integrated case teaching method to nursing orientation.

PubMed

Goodman, D

1997-01-01

Nursing staff development programs must be responsive to current changes in healthcare. New nursing staff must be prepared to manage continuous change and to function competently in clinical practice. The orientation pathway, based on a case management model, is used as a structure for the orientation phase of staff development. The integrated case is incorporated as a teaching strategy in orientation. The integrated case method is based on discussion and analysis of patient situations with emphasis on role modeling and integration of theory and skill. The orientation pathway and integrated case teaching method provide a useful framework for orientation of new staff. Educators, preceptors and orientees find the structure provided by the orientation pathway very useful. Orientation that is developed, implemented and evaluated based on a case management model with the use of an orientation pathway and incorporation of an integrated case teaching method provides a standardized structure for orientation of new staff. This approach is designed for the adult learner, promotes conceptual reasoning, and encourages the social and contextual basis for continued learning.

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

NASA Astrophysics Data System (ADS)

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 that instructors create more opportunities for students to explore model-based reasoning, and to create opportunities for students to be able to co-construct in a collaborative manner within the context of their organic chemistry course.

An approach to combining heuristic and qualitative reasoning in an expert system

NASA Technical Reports Server (NTRS)

Jiang, Wei-Si; Han, Chia Yung; Tsai, Lian Cheng; Wee, William G.

1988-01-01

An approach to combining the heuristic reasoning from shallow knowledge and the qualitative reasoning from deep knowledge is described. The shallow knowledge is represented in production rules and under the direct control of the inference engine. The deep knowledge is represented in frames, which may be put in a relational DataBase Management System. This approach takes advantage of both reasoning schemes and results in improved efficiency as well as expanded problem solving ability.

A new scenario-based approach to damage detection using operational modal parameter estimates

NASA Astrophysics Data System (ADS)

Hansen, J. B.; Brincker, R.; López-Aenlle, M.; Overgaard, C. F.; Kloborg, K.

2017-09-01

In this paper a vibration-based damage localization and quantification method, based on natural frequencies and mode shapes, is presented. The proposed technique is inspired by a damage assessment methodology based solely on the sensitivity of mass-normalized experimental determined mode shapes. The present method differs by being based on modal data extracted by means of Operational Modal Analysis (OMA) combined with a reasonable Finite Element (FE) representation of the test structure and implemented in a scenario-based framework. Besides a review of the basic methodology this paper addresses fundamental theoretical as well as practical considerations which are crucial to the applicability of a given vibration-based damage assessment configuration. Lastly, the technique is demonstrated on an experimental test case using automated OMA. Both the numerical study as well as the experimental test case presented in this paper are restricted to perturbations concerning mass change.

Feet and syllables in elephants and missiles: a reappraisal.

PubMed

Zonneveld, Wim; van der Pas, Brigit; de Bree, Elise

2007-01-01

Using data from a case study presented in Chiat (1989), Marshall and Chiat (2003) compare two different approaches to account for the realization of intervocalic consonants in child phonology: "coda capture theory" and the "foot domain account". They argue in favour of the latter account. In this note, we present a reappraisal of this argument using the same data. We conclude that acceptance of the foot domain account, in the specific way developed by the authors, is unmotivated for both theoretical and empirical reasons. We maintain that syllable-based coda capture is (still) the better approach to account for the relevant facts.

Evidence Arguments for Using Formal Methods in Software Certification

NASA Technical Reports Server (NTRS)

Denney, Ewen W.; Pai, Ganesh

2013-01-01

We describe a generic approach for automatically integrating the output generated from a formal method/tool into a software safety assurance case, as an evidence argument, by (a) encoding the underlying reasoning as a safety case pattern, and (b) instantiating it using the data produced from the method/tool. We believe this approach not only improves the trustworthiness of the evidence generated from a formal method/tool, by explicitly presenting the reasoning and mechanisms underlying its genesis, but also provides a way to gauge the suitability of the evidence in the context of the wider assurance case. We illustrate our work by application to a real example-an unmanned aircraft system- where we invoke a formal code analysis tool from its autopilot software safety case, automatically transform the verification output into an evidence argument, and then integrate it into the former.

Enhancing Learning Outcomes with an Interactive Knowledge-Based Learning Environment Providing Narrative Feedback

ERIC Educational Resources Information Center

Stranieri, Andrew; Yearwood, John

2008-01-01

This paper describes a narrative-based interactive learning environment which aims to elucidate reasoning using interactive scenarios that may be used in training novices in decision-making. Its design is based on an approach to generating narrative from knowledge that has been modelled in specific decision/reasoning domains. The approach uses a…

An evidence-based concept of implant dentistry. Utilization of short and narrow platform implants.

PubMed

Ruiz, Jose-Luis

2012-09-01

As a profession, we must remember that tooth replacement is not a luxury; it is often a necessity for health reasons. Although bone augmentation and CBCT and expensive surgical guides are often indicated for complex cases, they are being overused. Simple or straightforward implant cases, when there is sufficient natural bone for narrow or shorter implant, can be predictable performed by well-trained GPs and other trained specialists. Complex cases requiring bone augmentation and other complexities as described herein, should be referred to a surgical specialist. Implant courses and curricula have to be based on the level of complexity of implant surgery that each clinician wishes to provide to his or her patients. Using a "logical approach" to implant dentistry keeps cases simple or straightforward, and more accessible to patients by the correct use of narrow and shorter implants.

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

PubMed

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%, and 20% of missing values. This expansion in the KB coverage allowed solving complex disease diagnostic queries that were previously unresolvable, without losing the correctness of the answers. However, compared to deductive reasoning, data-intensive plausible reasoning mechanisms yield a significant performance overhead. We observed that plausible reasoning approaches, by generating tentative inferences and leveraging domain knowledge of experts, allow us to extend the coverage of medical knowledge bases, resulting in improved clinical decision support. Second, by leveraging OWL ontological knowledge, we are able to increase the expressivity and accuracy of plausible reasoning methods. Third, our approach is applicable to clinical decision support systems for a range of chronic diseases.

The Effect of a Case-Based Reasoning Instructional Model on Korean High School Students' Awareness in Climate Change Unit

ERIC Educational Resources Information Center

Jeong, Jinwoo; Kim, Hyoungbum; Chae, Dong-hyun; Kim, Eunjeong

2014-01-01

The purpose of this study is to investigate the effects of the case-based reasoning instructional model on learning about climate change unit. Results suggest that students showed interest because it allowed them to find the solution to the problem and solve the problem for themselves by analogy from other cases such as crossword puzzles in an…

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

NASA Astrophysics Data System (ADS)

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.

MapReduce in the Cloud: A Use Case Study for Efficient Co-Occurrence Processing of MEDLINE Annotations with MeSH.

PubMed

Kreuzthaler, Markus; Miñarro-Giménez, Jose Antonio; Schulz, Stefan

2016-01-01

Big data resources are difficult to process without a scaled hardware environment that is specifically adapted to the problem. The emergence of flexible cloud-based virtualization techniques promises solutions to this problem. This paper demonstrates how a billion of lines can be processed in a reasonable amount of time in a cloud-based environment. Our use case addresses the accumulation of concept co-occurrence data in MEDLINE annotation as a series of MapReduce jobs, which can be scaled and executed in the cloud. Besides showing an efficient way solving this problem, we generated an additional resource for the scientific community to be used for advanced text mining approaches.

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

PubMed

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.

SOMWeb: a semantic web-based system for supporting collaboration of distributed medical communities of practice.

PubMed

Falkman, Göran; Gustafsson, Marie; Jontell, Mats; Torgersson, Olof

2008-08-26

Information technology (IT) support for remote collaboration of geographically distributed communities of practice (CoP) in health care must deal with a number of sociotechnical aspects of communication within the community. In the mid-1990s, participants of the Swedish Oral Medicine Network (SOMNet) began discussing patient cases in telephone conferences. The cases were distributed prior to the conferences using PowerPoint and email. For the technical support of online CoP, Semantic Web technologies can potentially fulfill needs of knowledge reuse, data exchange, and reasoning based on ontologies. However, more research is needed on the use of Semantic Web technologies in practice. The objectives of this research were to (1) study the communication of distributed health care professionals in oral medicine; (2) apply Semantic Web technologies to describe community data and oral medicine knowledge; (3) develop an online CoP, Swedish Oral Medicine Web (SOMWeb), centered on user-contributed case descriptions and meetings; and (4) evaluate SOMWeb and study how work practices change with IT support. Based on Java, and using the Web Ontology Language and Resource Description Framework for handling community data and oral medicine knowledge, SOMWeb was developed using a user-centered and iterative approach. For studying the work practices and evaluating the system, a mixed-method approach of interviews, observations, and a questionnaire was used. By May 2008, there were 90 registered users of SOMWeb, 93 cases had been added, and 18 meetings had utilized the system. The introduction of SOMWeb has improved the structure of meetings and their discussions, and a tenfold increase in the number of participants has been observed. Users submit cases to seek advice on diagnosis or treatment, to show an unusual case, or to create discussion. Identified barriers to submitting cases are lack of time, concern about whether the case is interesting enough, and showing gaps in one's own knowledge. Three levels of member participation are discernable: a core group that contributes most cases and most meeting feedback; an active group that participates often but only sometimes contribute cases and feedback; and a large peripheral group that seldom or never contribute cases or feedback. SOMWeb is beneficial for individual clinicians as well as for the SOMNet community. The system provides an opportunity for its members to share both high quality clinical practice knowledge and external evidence related to complex oral medicine cases. The foundation in Semantic Web technologies enables formalization and structuring of case data that can be used for further reasoning and research. Main success factors are the long history of collaboration between different disciplines, the user-centered development approach, the existence of a "champion" within the field, and nontechnical community aspects already being in place.

SOMWeb: A Semantic Web-Based System for Supporting Collaboration of Distributed Medical Communities of Practice

PubMed Central

Gustafsson, Marie; Jontell, Mats; Torgersson, Olof

2008-01-01

Background Information technology (IT) support for remote collaboration of geographically distributed communities of practice (CoP) in health care must deal with a number of sociotechnical aspects of communication within the community. In the mid-1990s, participants of the Swedish Oral Medicine Network (SOMNet) began discussing patient cases in telephone conferences. The cases were distributed prior to the conferences using PowerPoint and email. For the technical support of online CoP, Semantic Web technologies can potentially fulfill needs of knowledge reuse, data exchange, and reasoning based on ontologies. However, more research is needed on the use of Semantic Web technologies in practice. Objectives The objectives of this research were to (1) study the communication of distributed health care professionals in oral medicine; (2) apply Semantic Web technologies to describe community data and oral medicine knowledge; (3) develop an online CoP, Swedish Oral Medicine Web (SOMWeb), centered on user-contributed case descriptions and meetings; and (4) evaluate SOMWeb and study how work practices change with IT support. Methods Based on Java, and using the Web Ontology Language and Resource Description Framework for handling community data and oral medicine knowledge, SOMWeb was developed using a user-centered and iterative approach. For studying the work practices and evaluating the system, a mixed-method approach of interviews, observations, and a questionnaire was used. Results By May 2008, there were 90 registered users of SOMWeb, 93 cases had been added, and 18 meetings had utilized the system. The introduction of SOMWeb has improved the structure of meetings and their discussions, and a tenfold increase in the number of participants has been observed. Users submit cases to seek advice on diagnosis or treatment, to show an unusual case, or to create discussion. Identified barriers to submitting cases are lack of time, concern about whether the case is interesting enough, and showing gaps in one’s own knowledge. Three levels of member participation are discernable: a core group that contributes most cases and most meeting feedback; an active group that participates often but only sometimes contribute cases and feedback; and a large peripheral group that seldom or never contribute cases or feedback. Conclusions SOMWeb is beneficial for individual clinicians as well as for the SOMNet community. The system provides an opportunity for its members to share both high quality clinical practice knowledge and external evidence related to complex oral medicine cases. The foundation in Semantic Web technologies enables formalization and structuring of case data that can be used for further reasoning and research. Main success factors are the long history of collaboration between different disciplines, the user-centered development approach, the existence of a “champion” within the field, and nontechnical community aspects already being in place. PMID:18725355

ED-WAVE tool design approach: Case of a textile wastewater treatment plant in Blantyre, Malawi

NASA Astrophysics Data System (ADS)

Chipofya, V.; Kraslawski, A.; Avramenko, Y.

The ED-WAVE tool is a PC based package for imparting training on wastewater treatment technologies. The system consists of four modules viz. Reference Library, Process Builder, Case Study Manager, and Treatment Adviser. The principles of case-based design and case-based reasoning as applied in the ED-WAVE tool are utilised in this paper to evaluate the design approach of the wastewater treatment plant at Mapeto David Whitehead & Sons (MDW&S) textile and garments factory, Blantyre, Malawi. The case being compared with MDW&S in the ED-WAVE tool is Textile Case 4 in Sri Lanka (2003). Equalisation, coagulation and rotating biological contactors is the sequencing of treatment units at Textile Case 4 in Sri Lanka. Screening, oxidation ditches and sedimentation is the sequencing of treatment units at MDW&S textile and garments factory. The study suggests that aerobic biological treatment is necessary in the treatment of wastewater from a textile and garments factory. MDW&S incorporates a sedimentation process which is necessary for the removal of settleable matter before the effluent is discharged to the municipal wastewater treatment plant. The study confirmed the practical use of the ED-WAVE tool in the design of wastewater treatment systems, where after encountering a new situation; already collected decision scenarios (cases) are invoked and modified in order to arrive at a particular design alternative. What is necessary, however, is to appropriately modify the case arrived at through the Case Study Manager in order to come up with a design appropriate to the local situation taking into account technical, socio-economic and environmental aspects.

A Wireless Sensor Network-Based Approach with Decision Support for Monitoring Lake Water Quality.

PubMed

Huang, Xiaoci; Yi, Jianjun; Chen, Shaoli; Zhu, Xiaomin

2015-11-19

Online monitoring and water quality analysis of lakes are urgently needed. A feasible and effective approach is to use a Wireless Sensor Network (WSN). Lake water environments, like other real world environments, present many changing and unpredictable situations. To ensure flexibility in such an environment, the WSN node has to be prepared to deal with varying situations. This paper presents a WSN self-configuration approach for lake water quality monitoring. The approach is based on the integration of a semantic framework, where a reasoner can make decisions on the configuration of WSN services. We present a WSN ontology and the relevant water quality monitoring context information, which considers its suitability in a pervasive computing environment. We also propose a rule-based reasoning engine that is used to conduct decision support through reasoning techniques and context-awareness. To evaluate the approach, we conduct usability experiments and performance benchmarks.

Performance-based classrooms: A case study of two elementary teachers of mathematics and science

NASA Astrophysics Data System (ADS)

Jones, Kenneth W.

This case study depicts how two elementary teachers develop classrooms devoted to performance-based instruction in mathematics and science. The purpose is to develop empirical evidence of classroom practices that leads to a conceptual framework about the nature of performance-based instruction. Performance-based assessment and instruction are defined from the literature to entail involving students in tasks that are complex and engaging, requiring them to apply knowledge and skills in authentic contexts. In elementary mathematics and science, such an approach emphasizes problem solving, exploration, inquiry, and reasoning. The body of the work examines teacher beliefs, curricular orientations, instructional strategies, assessment approaches, management and organizational skills, and interpersonal relationships. The focus throughout is on those aspects that foster student performance in elementary mathematics and science. The resulting framework describes five characteristics that contribute to performance-based classrooms: a caring classroom community, a connectionist learning theory, a thinking and doing curriculum, diverse opportunities for learning, and ongoing assessment, feedback, and adjustment. The conclusion analyzes factors external to the classroom that support or constrain the development of performance-based classrooms and discusses the implications for educational policy and further research.

Integrating a Moral Reasoning Game in a Blended Learning Setting: Effects on Students' Interest and Performance

ERIC Educational Resources Information Center

Hong, Jon-Chao; Hwang, Ming-Yueh; Wu, Nien-Chen; Huang, Ying-Luan; Lin, Pei-Hsin; Chen, Yi-Ling

2016-01-01

A new approach to moral education using blended learning has been developed. This approach involves 10 scenarios that are designed as a web-based game and serves as a basis for group moral-consequence-based reasoning, which is developed based on a hypothetical-deductive model. The aim of the study was to examine the changes in students' blended…

Learning, remembering, and predicting how to use tools: Distributed neurocognitive mechanisms

PubMed Central

Buxbaum, Laurel J.

2016-01-01

The reasoning-based approach championed by Francois Osiurak and Arnaud Badets (Osiurak & Badets, 2016) denies the existence of sensory-motor memories of tool use except in limited circumstances, and suggests instead that most tool use is subserved solely by online technical reasoning about tool properties. In this commentary, I highlight the strengths and limitations of the reasoning-based approach and review a number of lines of evidence that manipulation knowledge is in fact used in tool action tasks. In addition, I present a “two route” neurocognitive model of tool use called the “Two Action Systems Plus (2AS+)” framework that posits a complementary role for online and stored information and specifies the neurocognitive substrates of task-relevant action selection. This framework, unlike the reasoning based approach, has the potential to integrate the existing psychological and functional neuroanatomic data in the tool use domain. PMID:28358565

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

NASA Astrophysics Data System (ADS)

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 presents case studies of three secondary science teachers within three high schools located along the Minnesota River Basin. The findings of this study documented the experiences of the participant teachers, as well as the contextual influences on those experiences. The second paper presents a case study of a science teacher and a social studies teacher which describes how these two teachers collaboratively designed and taught an environmental ethics class. The results of this study documented teachers' ways of sharing responsibilities, bringing their content and pedagogical expertise, and promoting the agency of their students in the environmental ethics class. The final paper in this dissertation presents case studies of secondary school students who were the participants in the SSI-based science classes described in the first two studies. The results of this study provided evidence for participant students' understanding of science and their socioscientific reasoning, as well as how they were influenced by the instructional decisions their teachers made.

Prediction of shallow landslide occurrence: Validation of a physically-based approach through a real case study.

PubMed

Schilirò, Luca; Montrasio, Lorella; Scarascia Mugnozza, Gabriele

2016-11-01

In recent years, physically-based numerical models have frequently been used in the framework of early-warning systems devoted to rainfall-induced landslide hazard monitoring and mitigation. For this reason, in this work we describe the potential of SLIP (Shallow Landslides Instability Prediction), a simplified physically-based model for the analysis of shallow landslide occurrence. In order to test the reliability of this model, a back analysis of recent landslide events occurred in the study area (located SW of Messina, northeastern Sicily, Italy) on October 1st, 2009 was performed. The simulation results have been compared with those obtained for the same event by using TRIGRS, another well-established model for shallow landslide prediction. Afterwards, a simulation over a 2-year span period has been performed for the same area, with the aim of evaluating the performance of SLIP as early warning tool. The results confirm the good predictive capability of the model, both in terms of spatial and temporal prediction of the instability phenomena. For this reason, we recommend an operating procedure for the real-time definition of shallow landslide triggering scenarios at the catchment scale, which is based on the use of SLIP calibrated through a specific multi-methodological approach. Copyright © 2016 Elsevier B.V. All rights reserved.

A "Bioethics" Approach to Teaching Health Law.

ERIC Educational Resources Information Center

Capron, Alexander Morgan

1988-01-01

The reasons for offering a course in bioethics to law students and some approaches to take in addressing controversial issues are examined. The use of hypothetical vs. real cases, emphasis on clinical problems, and overall course objectives are discussed. (MSE)

Islam, brain death, and transplantation: culture, faith, and jurisprudence.

PubMed

Arbour, Richard; AlGhamdi, Hanan Mesfer Saad; Peters, Linda

2012-01-01

A significant gap exists between availability of organs for transplant and patients with end-stage organ failure for whom organ transplantation is the last treatment option. Reasons for this mismatch include inadequate approach to potential donor families and donor loss as a result of refractory cardiopulmonary instability during and after brainstem herniation. Other reasons include inadequate cultural competence and sensitivity when communicating with potential donor families. Clinicians may not have an understanding of the cultural and religious perspectives of Muslim families of critically ill patients who may be approached about brain death and organ donation. This review analyzes Islamic cultural and religious perspectives on organ donation, transplantation, and brain death, including faith-based directives from Islamic religious authorities, definitions of death in Islam, and communication strategies when discussing brain death and organ donation with Muslim families. Optimal family care and communication are highlighted using case studies and backgrounds illustrating barriers and approaches with Muslim families in the United States and in the Kingdom of Saudi Arabia that can improve cultural competence and family care as well as increase organ availability within the Muslim population and beyond.

Secondary School Students' Understanding of Science and Their Socioscientific Reasoning

NASA Astrophysics Data System (ADS)

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.

Rough case-based reasoning system for continues casting

NASA Astrophysics Data System (ADS)

Su, Wenbin; Lei, Zhufeng

2018-04-01

The continuous casting occupies a pivotal position in the iron and steel industry. The rough set theory and the CBR (case based reasoning, CBR) were combined in the research and implementation for the quality assurance of continuous casting billet to improve the efficiency and accuracy in determining the processing parameters. According to the continuous casting case, the object-oriented method was applied to express the continuous casting cases. The weights of the attributes were calculated by the algorithm which was based on the rough set theory and the retrieval mechanism for the continuous casting cases was designed. Some cases were adopted to test the retrieval mechanism, by analyzing the results, the law of the influence of the retrieval attributes on determining the processing parameters was revealed. A comprehensive evaluation model was established by using the attribute recognition theory. According to the features of the defects, different methods were adopted to describe the quality condition of the continuous casting billet. By using the system, the knowledge was not only inherited but also applied to adjust the processing parameters through the case based reasoning method as to assure the quality of the continuous casting and improve the intelligent level of the continuous casting.

'Vague Oviedo': autonomy, culture and the case of previously competent patients.

PubMed

Pascalev, Assya; Vidalis, Takis

2010-03-01

The paper examines the ethical and legal challenges of making decisions for previously competent patients and the role of advance directives and legal representatives in light of the Oviedo Convention. The paper identifies gaps in the Convention that result in conflicting instructions in cases of a disagreement between the expressed prior wishes of a patient, and the legal representative. The authors also examine the legal and moral status of informally expressed prior wishes of patients unable to consent. The authors argue that positivist legal reasoning is insufficient for a consistent interpretation of the relevant provisions of the Convention and argue that ethical argumentation is needed to provide guidance in such cases. Based on the ethical arguments, the authors propose a way of reconciling the apparent inconsistencies in the Oviedo Convention. They advance a culturally sensitive approach to the application of the Convention at the national level. This approach understands autonomy as a broader, relational consent and emphasizes the social and cultural embeddedness of the individual. Based on their approach, the authors argue that there exists a moral obligation to respect the prior wishes of the patient even in countries without advance directives. Yet it should be left to the national legislations to determine the extent of this obligation and its concrete forms.

Clinical reasoning of Filipino physical therapists: Experiences in a developing nation.

PubMed

Rotor, Esmerita R; Capio, Catherine M

2018-03-01

Clinical reasoning is essential for physical therapists to engage in the process of client care, and has been known to contribute to professional development. The literature on clinical reasoning and experiences have been based on studies from Western and developed nations, from which multiple influencing factors have been found. A developing nation, the Philippines, has distinct social, economic, political, and cultural circumstances. Using a phenomenological approach, this study explored experiences of Filipino physical therapists on clinical reasoning. Ten therapists working in three settings: 1) hospital; 2) outpatient clinic; and 3) home health were interviewed. Major findings were: a prescription-based referral system limited clinical reasoning; procedural reasoning was a commonly experienced strategy while diagnostic and predictive reasoning were limited; factors that influenced clinical reasoning included practice setting and the professional relationship with the referring physician. Physical therapists' responses suggested a lack of autonomy in practice that appeared to stifle clinical reasoning. Based on our findings, we recommend that the current regulations governing PT practice in the Philippines may be updated, and encourage educators to strengthen teaching approaches and strategies that support clinical reasoning. These recommendations are consistent with the global trend toward autonomous practice.

Nutrition meets heredity: a case of RNA-mediated transmission of acquired characters.

PubMed

Rassoulzadegan, Minoo; Cuzin, François

2018-04-01

RNA-based inheritance provides a reasonable hypothesis to explain multigenerational maintenance of the disease in the progeny of either a male or female parent suffering from the metabolic syndrome (obesity and type 2 diabetes) induced by abnormal diet. Although, it is still difficult to formulate a complete rational mechanism, study of inheritance is a most direct way to learn about the epigenetic control of gene expression and we wished to summarised our current approach along this line.

Minimally inconsistent reasoning in Semantic Web.

PubMed

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.

Minimally inconsistent reasoning in Semantic Web

PubMed Central

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. PMID:28750030

Clinical Reasoning in the Assessment and Intervention Planning for a Reading Disability

ERIC Educational Resources Information Center

Sotelo-Dynega, Marlene

2017-01-01

The purpose of this article is to provide the reader with insight into the clinical reasoning process involved in the assessment and intervention planning for a child with a reading disability. A Cattell-Horn-Carroll (CHC) theoretical/neuropsychological approach shall serve as the foundational theoretical framework for this case study, and…

Validity of a family-centered approach for assessing infants' social-emotional wellbeing and their developmental context: a prospective cohort study.

PubMed

Hielkema, Margriet; De Winter, Andrea F; Reijneveld, Sijmen A

2017-06-15

Family-centered care seems promising in preventive pediatrics, but evidence is lacking as to whether this type of care is also valid as a means to identify risks to infants' social-emotional development. We aimed to examine the validity of such a family-centered approach. We conducted a prospective cohort study. During routine well-child visits (2-15 months), Preventive Child Healthcare (PCH) professionals used a family-centered approach, assessing domains as parents' competence, role of the partner, social support, barriers within the care-giving context, and child's wellbeing for 2976 children as protective, indistinct or a risk. If, based on the overall assessment (the families were labeled as "cases", N = 87), an intervention was considered necessary, parents filled in validated questionnaires covering the aforementioned domains. These questionnaires served as gold standards. For each case, two controls, matched by child-age and gender, also filled in questionnaires (N = 172). We compared PCH professionals' assessments with the parent-reported gold standards. Moreover, we evaluated which domain mostly contributed to the overall assessment. Spearman's rank correlation coefficients between PCH professionals' assessments and gold standards were overall reasonable (Spearman's rho 0.17-0.39) except for the domain barriers within the care-giving context. Scores on gold standards were significantly higher when PCH assessments were rated as "at risk" (overall and per domain).We found reasonable to excellent agreement regarding the absence of risk factors (negative agreement rate: 0.40-0.98), but lower agreement regarding the presence of risk factors (positive agreement rate: 0.00-0.67). An "at risk" assessment for the domain Barriers or life events within the care-giving context contributed most to being overall at risk, i.e. a case, odds ratio 100.1, 95%-confidence interval: 22.6 - infinity. Findings partially support the convergent validity of a family-centered approach in well-child care to assess infants' social-emotional wellbeing and their developmental context. Agreement was reasonable to excellent regarding protective factors, but lower regarding risk factors. Netherlands Trialregister, NTR2681. Date of registration: 05-01-2011, URL: http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=2681 .

Application of plausible reasoning to AI-based control systems

NASA Technical Reports Server (NTRS)

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.

A design of experiments approach to validation sampling for logistic regression modeling with error-prone medical records.

PubMed

Ouyang, Liwen; Apley, Daniel W; Mehrotra, Sanjay

2016-04-01

Electronic medical record (EMR) databases offer significant potential for developing clinical hypotheses and identifying disease risk associations by fitting statistical models that capture the relationship between a binary response variable and a set of predictor variables that represent clinical, phenotypical, and demographic data for the patient. However, EMR response data may be error prone for a variety of reasons. Performing a manual chart review to validate data accuracy is time consuming, which limits the number of chart reviews in a large database. The authors' objective is to develop a new design-of-experiments-based systematic chart validation and review (DSCVR) approach that is more powerful than the random validation sampling used in existing approaches. The DSCVR approach judiciously and efficiently selects the cases to validate (i.e., validate whether the response values are correct for those cases) for maximum information content, based only on their predictor variable values. The final predictive model will be fit using only the validation sample, ignoring the remainder of the unvalidated and unreliable error-prone data. A Fisher information based D-optimality criterion is used, and an algorithm for optimizing it is developed. The authors' method is tested in a simulation comparison that is based on a sudden cardiac arrest case study with 23 041 patients' records. This DSCVR approach, using the Fisher information based D-optimality criterion, results in a fitted model with much better predictive performance, as measured by the receiver operating characteristic curve and the accuracy in predicting whether a patient will experience the event, than a model fitted using a random validation sample. The simulation comparisons demonstrate that this DSCVR approach can produce predictive models that are significantly better than those produced from random validation sampling, especially when the event rate is low. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Influences on Personal Understanding: Intentions, Approaches to Learning, Perceptions of Assessment, and a "Meeting of Minds"

ERIC Educational Resources Information Center

Karagiannopoulou, Evangelia; Entwistle, Noel

2013-01-01

Using a case-study approach, interviews with four final-year psychology students showed different approaches to learning and varying experiences of teaching in courses assessed through open-book exams. Analysis of their experiences, supported by previous research findings, provided insights into the reasons for the contrasting approaches being…

E-Beam Capture Aid Drawing Based Modelling on Cell Biology

NASA Astrophysics Data System (ADS)

Hidayat, T.; Rahmat, A.; Redjeki, S.; Rahman, T.

2017-09-01

The objectives of this research are to find out how far Drawing-based Modeling assisted with E-Beam Capture could support student’s scientific reasoning skill using Drawing - based Modeling approach assisted with E-Beam Capture. The research design that is used for this research is the Pre-test and Post-test Design. The data collection of scientific reasoning skills is collected by giving multiple choice questions before and after the lesson. The data analysis of scientific reasoning skills is using scientific reasoning assessment rubric. The results show an improvement of student’s scientific reasoning in every indicator; an improvement in generativity which shows 2 students achieving high scores, 3 students in elaboration reasoning, 4 students in justification, 3 students in explanation, 3 students in logic coherency, 2 students in synthesis. The research result in student’s explanation reasoning has the highest number of students with high scores, which shows 20 students with high scores in the pre-test and 23 students in post-test and synthesis reasoning shows the lowest number, which shows 1 student in the pretest and 3 students in posttest. The research result gives the conclusion that Drawing-based Modeling approach assisted with E-Beam Capture could not yet support student’s scientific reasoning skills comprehensively.

Using STEM Approach to Develop Visual Reasoning and Learning Independence for Preparatory Stage Students

ERIC Educational Resources Information Center

Abbas, Rasha Al-Sayed Sabry

2017-01-01

This research aimed at investigating the effectiveness of STEM approach in developing visual reasoning and learning independence for preparatory stage students. To achieve this aim, the researcher designed a program based on STEM approach in light of the principles of nanotechnology. Twenty one preparatory stage students participated in the…

The Principle-Based Method of Practical Ethics.

PubMed

Spielthenner, Georg

2017-09-01

This paper is about the methodology of doing practical ethics. There is a variety of methods employed in ethics. One of them is the principle-based approach, which has an established place in ethical reasoning. In everyday life, we often judge the rightness and wrongness of actions by their conformity to principles, and the appeal to principles plays a significant role in practical ethics, too. In this paper, I try to provide a better understanding of the nature of principle-based reasoning. To accomplish this, I show in the first section that these principles can be applied to cases in a meaningful and sufficiently precise way. The second section discusses the question how relevant applying principles is to the resolution of ethical issues. This depends on their nature. I argue that the principles under consideration in this paper should be interpreted as presumptive principles and I conclude that although they cannot be expected to bear the weight of definitely resolving ethical problems, these principles can nevertheless play a considerable role in ethical research.

Using an Evidential Reasoning Approach for Portfolio Assessments in a Project-Based Learning Engineering Design Course

ERIC Educational Resources Information Center

Jaeger, Martin; Adair, Desmond

2015-01-01

The purpose of this study is to analyse the feasibility of an evidential reasoning (ER) method for portfolio assessments and comparison of the results found with those based on a traditional holistic judgement. An ER approach has been incorporated into portfolio assessment of an undergraduate engineering design course delivered as a project-based…

Geometrical eigen-subspace framework based molecular conformation representation for efficient structure recognition and comparison

NASA Astrophysics Data System (ADS)

Li, Xiao-Tian; Yang, Xiao-Bao; Zhao, Yu-Jun

2017-04-01

We have developed an extended distance matrix approach to study the molecular geometric configuration through spectral decomposition. It is shown that the positions of all atoms in the eigen-space can be specified precisely by their eigen-coordinates, while the refined atomic eigen-subspace projection array adopted in our approach is demonstrated to be a competent invariant in structure comparison. Furthermore, a visual eigen-subspace projection function (EPF) is derived to characterize the surrounding configuration of an atom naturally. A complete set of atomic EPFs constitute an intrinsic representation of molecular conformation, based on which the interatomic EPF distance and intermolecular EPF distance can be reasonably defined. Exemplified with a few cases, the intermolecular EPF distance shows exceptional rationality and efficiency in structure recognition and comparison.

SU-F-R-10: Selecting the Optimal Solution for Multi-Objective Radiomics Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Z; Folkert, M; Wang, J

2016-06-15

Purpose: To develop an evidential reasoning approach for selecting the optimal solution from a Pareto solution set obtained by a multi-objective radiomics model for predicting distant failure in lung SBRT. Methods: In the multi-objective radiomics model, both sensitivity and specificity are considered as the objective functions simultaneously. A Pareto solution set with many feasible solutions will be resulted from the multi-objective optimization. In this work, an optimal solution Selection methodology for Multi-Objective radiomics Learning model using the Evidential Reasoning approach (SMOLER) was proposed to select the optimal solution from the Pareto solution set. The proposed SMOLER method used the evidentialmore » reasoning approach to calculate the utility of each solution based on pre-set optimal solution selection rules. The solution with the highest utility was chosen as the optimal solution. In SMOLER, an optimal learning model coupled with clonal selection algorithm was used to optimize model parameters. In this study, PET, CT image features and clinical parameters were utilized for predicting distant failure in lung SBRT. Results: Total 126 solution sets were generated by adjusting predictive model parameters. Each Pareto set contains 100 feasible solutions. The solution selected by SMOLER within each Pareto set was compared to the manually selected optimal solution. Five-cross-validation was used to evaluate the optimal solution selection accuracy of SMOLER. The selection accuracies for five folds were 80.00%, 69.23%, 84.00%, 84.00%, 80.00%, respectively. Conclusion: An optimal solution selection methodology for multi-objective radiomics learning model using the evidential reasoning approach (SMOLER) was proposed. Experimental results show that the optimal solution can be found in approximately 80% cases.« less

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

ERIC Educational Resources Information Center

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…

Objective structured clinical examination "Death Certificate" station - Computer-based versus conventional exam format.

PubMed

Biolik, A; Heide, S; Lessig, R; Hachmann, V; Stoevesandt, D; Kellner, J; Jäschke, C; Watzke, S

2018-04-01

One option for improving the quality of medical post mortem examinations is through intensified training of medical students, especially in countries where such a requirement exists regardless of the area of specialisation. For this reason, new teaching and learning methods on this topic have recently been introduced. These new approaches include e-learning modules or SkillsLab stations; one way to objectify the resultant learning outcomes is by means of the OSCE process. However, despite offering several advantages, this examination format also requires considerable resources, in particular in regards to medical examiners. For this reason, many clinical disciplines have already implemented computer-based OSCE examination formats. This study investigates whether the conventional exam format for the OSCE forensic "Death Certificate" station could be replaced with a computer-based approach in future. For this study, 123 students completed the OSCE "Death Certificate" station, using both a computer-based and conventional format, half starting with the Computer the other starting with the conventional approach in their OSCE rotation. Assignment of examination cases was random. The examination results for the two stations were compared and both overall results and the individual items of the exam checklist were analysed by means of inferential statistics. Following statistical analysis of examination cases of varying difficulty levels and correction of the repeated measures effect, the results of both examination formats appear to be comparable. Thus, in the descriptive item analysis, while there were some significant differences between the computer-based and conventional OSCE stations, these differences were not reflected in the overall results after a correction factor was applied (e.g. point deductions for assistance from the medical examiner was possible only at the conventional station). Thus, we demonstrate that the computer-based OSCE "Death Certificate" station is a cost-efficient and standardised format for examination that yields results comparable to those from a conventional format exam. Moreover, the examination results also indicate the need to optimize both the test itself (adjusting the degree of difficulty of the case vignettes) and the corresponding instructional and learning methods (including, for example, the use of computer programmes to complete the death certificate in small group formats in the SkillsLab). Copyright © 2018 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

A Semantic Approach with Decision Support for Safety Service in Smart Home Management

PubMed Central

Huang, Xiaoci; Yi, Jianjun; Zhu, Xiaomin; Chen, Shaoli

2016-01-01

Research on smart homes (SHs) has increased significantly in recent years because of the convenience provided by having an assisted living environment. The functions of SHs as mentioned in previous studies, particularly safety services, are seldom discussed or mentioned. Thus, this study proposes a semantic approach with decision support for safety service in SH management. The focus of this contribution is to explore a context awareness and reasoning approach for risk recognition in SH that enables the proper decision support for flexible safety service provision. The framework of SH based on a wireless sensor network is described from the perspective of neighbourhood management. This approach is based on the integration of semantic knowledge in which a reasoner can make decisions about risk recognition and safety service. We present a management ontology for a SH and relevant monitoring contextual information, which considers its suitability in a pervasive computing environment and is service-oriented. We also propose a rule-based reasoning method to provide decision support through reasoning techniques and context-awareness. A system prototype is developed to evaluate the feasibility, time response and extendibility of the approach. The evaluation of our approach shows that it is more effective in daily risk event recognition. The decisions for service provision are shown to be accurate. PMID:27527170

A Semantic Approach with Decision Support for Safety Service in Smart Home Management.

PubMed

Huang, Xiaoci; Yi, Jianjun; Zhu, Xiaomin; Chen, Shaoli

2016-08-03

Research on smart homes (SHs) has increased significantly in recent years because of the convenience provided by having an assisted living environment. The functions of SHs as mentioned in previous studies, particularly safety services, are seldom discussed or mentioned. Thus, this study proposes a semantic approach with decision support for safety service in SH management. The focus of this contribution is to explore a context awareness and reasoning approach for risk recognition in SH that enables the proper decision support for flexible safety service provision. The framework of SH based on a wireless sensor network is described from the perspective of neighbourhood management. This approach is based on the integration of semantic knowledge in which a reasoner can make decisions about risk recognition and safety service. We present a management ontology for a SH and relevant monitoring contextual information, which considers its suitability in a pervasive computing environment and is service-oriented. We also propose a rule-based reasoning method to provide decision support through reasoning techniques and context-awareness. A system prototype is developed to evaluate the feasibility, time response and extendibility of the approach. The evaluation of our approach shows that it is more effective in daily risk event recognition. The decisions for service provision are shown to be accurate.

How clinical reasoning is taught and learned: Cultural perspectives from the University of Melbourne and Universitas Indonesia.

PubMed

Findyartini, Ardi; Hawthorne, Lesleyanne; McColl, Geoff; Chiavaroli, Neville

2016-07-21

The majority of schools in the Asia-Pacific region have adopted medical curricula based on western pedagogy. However to date there has been minimal exploration of the influence of the culture of learning on the teaching and learning process. This paper explores this issue in relation to clinical reasoning. A comparative case study was conducted in 2 medical schools in Australia (University of Melbourne) and Asia (Universitas Indonesia). It involved assessment of medical students' attitudes to clinical reasoning through administration of the Diagnostic Thinking Inventory (DTI), followed by qualitative interviews which explored related cultural issues. A total of 11 student focus group discussions (45 students) and 24 individual medical teacher interviews were conducted, followed by thematic analysis. Students from Universitas Indonesia were found to score lower on the Flexibility in Thinking subscale of the DTI. Qualitative data analysis based on Hofstede's theoretical constructs concerning the culture of learning also highlighted clear differences in relation to attitudes to authority and uncertainty avoidance, with potential impacts on attitudes to teaching and learning of clinical reasoning in undergraduate medical education. Different attitudes to teaching and learning clinical reasoning reflecting western and Asian cultures of learning were identified in this study. The potential impact of cultural differences should be understood when planning how clinical reasoning can be best taught and learned in the changing global contexts of medical education, especially when the western medical education approach is implemented in Asian contexts.

Towards a Compositional SPIN

NASA Technical Reports Server (NTRS)

Pasareanu, Corina S.; Giannakopoulou, Dimitra

2006-01-01

This paper discusses our initial experience with introducing automated assume-guarantee verification based on learning in the SPIN tool. We believe that compositional verification techniques such as assume-guarantee reasoning could complement the state-reduction techniques that SPIN already supports, thus increasing the size of systems that SPIN can handle. We present a "light-weight" approach to evaluating the benefits of learning-based assume-guarantee reasoning in the context of SPIN: we turn our previous implementation of learning for the LTSA tool into a main program that externally invokes SPIN to provide the model checking-related answers. Despite its performance overheads (which mandate a future implementation within SPIN itself), this approach provides accurate information about the savings in memory. We have experimented with several versions of learning-based assume guarantee reasoning, including a novel heuristic introduced here for generating component assumptions when their environment is unavailable. We illustrate the benefits of learning-based assume-guarantee reasoning in SPIN through the example of a resource arbiter for a spacecraft. Keywords: assume-guarantee reasoning, model checking, learning.

Recruitment of participants through community pharmacies for a pharmacogenetic study of antihypertensive drug treatment.

PubMed

van Wieren-de Wijer, Diane B M A; Maitland-van der Zee, Anke-Hilse; de Boer, Anthonius; Stricker, Bruno H Ch; Kroon, Abraham A; de Leeuw, Peter W; Bozkurt, O; Klungel, Olaf H

2009-04-01

To describe the design, recruitment and baseline characteristics of participants in a community pharmacy based pharmacogenetic study of antihypertensive drug treatment. Participants enrolled from the population-based Pharmaco-Morbidity Record Linkage System. We designed a nested case-control study in which we will assess whether specific genetic polymorphisms modify the effect of antihypertensive drugs on the risk of myocardial infarction. In this study, cases (myocardial infarction) and controls were recruited through community pharmacies that participate in PHARMO. The PHARMO database comprises drug dispensing histories of about 2,000,000 subjects from a representative sample of Dutch community pharmacies linked to the national registrations of hospital discharges. In total we selected 31010 patients (2777 cases and 28233 controls) from the PHARMO database, of whom 15973 (1871 cases, 14102 controls) were approached through their community pharmacy. Overall response rate was 36.3% (n = 5791, 794 cases, 4997 controls), whereas 32.1% (n = 5126, 701 cases, 4425 controls) gave informed consent to genotype their DNA. As expected, several cardiovascular risk factors such as smoking, body mass index, hypercholesterolemia, and diabetes mellitus were more common in cases than in controls. Furthermore, cases more often used beta-blockers and calcium-antagonists, whereas controls more often used thiazide diuretics, ACE-inhibitors, and angiotensin-II receptor blockers. We have demonstrated that it is feasible to select patients from a coded database for a pharmacogenetic study and to approach them through community pharmacies, achieving reasonable response rates and without violating privacy rules.

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

PubMed

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.

Heuristic Reasoning and Beliefs on Immigration: An Approach to an Intercultural Education Programme

ERIC Educational Resources Information Center

Navarro, Santiago Palacios; Lopez de Arechavaleta, Blanca Olalde

2010-01-01

People use mental shortcuts to simplify the amount of information they receive from the environment. Heuristic reasoning can be included among these mental shortcuts. In general, heuristics is useful for making fast decisions and judgements, but in certain cases, it may lead to systematic errors because some relevant aspects presented in the given…

Reasons Preventing Teachers from Acting within the Framework of Ethical Principles

ERIC Educational Resources Information Center

Dag, Nilgün; Arslantas, Halis Adnan

2015-01-01

This study aims at putting forth the reasons preventing teachers from acting ethically, acting within the framework of ethical principles and having an ethical tendency. This study featuring a qualitative research model taking as a basis the case study approach followed a path of selecting people that can be a rich source of information for…

Development of Probabilistic and Possebilistic Approaches to Approximate Reasoning and Its Applications

DTIC Science & Technology

1989-10-31

fo tmaa OmfuogeM ara Mmi. fal in fM?05V~ ~ ~ ~ ~ ~ A D A 2 4 0409"~ n ugt Psoo,@’ oducbof Proton (07044 136M. WagaWapN. DC 20141 T1 3. REPORT TYPE...Al (circumscription, non- monotonic reasoning, and default reasoning), our approach is based on fuzzy logic and, more specifically, on the theory of

CDMBE: A Case Description Model Based on Evidence

PubMed Central

Zhu, Jianlin; Yang, Xiaoping; Zhou, Jing

2015-01-01

By combining the advantages of argument map and Bayesian network, a case description model based on evidence (CDMBE), which is suitable to continental law system, is proposed to describe the criminal cases. The logic of the model adopts the credibility logical reason and gets evidence-based reasoning quantitatively based on evidences. In order to consist with practical inference rules, five types of relationship and a set of rules are defined to calculate the credibility of assumptions based on the credibility and supportability of the related evidences. Experiments show that the model can get users' ideas into a figure and the results calculated from CDMBE are in line with those from Bayesian model. PMID:26421006

Public-Interest and Level-of-Evidence Considerations in Cold Fusion Public Policy

NASA Astrophysics Data System (ADS)

Grinshaw, Thomas

2008-03-01

Cold fusion (CF) protagonists and antagonists would no doubt agree that scientific processes have been challenged in the CF case. The public interest in CF turns on two questions: What are the potential benefits? What is the probability that CF is ``real''? Potential benefits have been agreed on since CF announcement in 1989. The probability of CF reality may be assessed based on level of evidence (LoE): preponderance of evidence (PoE); clear and convincing evidence (CCE); and beyond a reasonable doubt (BRD). PoE, from civil law, indicates a probability of 50% or higher. BRD, from criminal law, has a probability approaching 90%. CCE, in between, thus has a 70-75% probability. CF experimental evidence, based on: 1) initial affirmations, 2) the large number of corroborations since marginalization, and 3) particularly demonstrative experiments, reasonably indicates at least a PoE level of evidence for excess heat. A case can also be made for a CCE (but probably not for a BRD) LoE. In either the PoE or CCE scenario a clear need is demonstrated for change in policy toward CR, given its potential benefits to humanity.

Cognition of an expert tackling an unfamiliar conceptual physics problem

NASA Astrophysics Data System (ADS)

Schuster, David; Undreiu, Adriana

2009-11-01

We have investigated and analyzed the cognition of an expert tackling a qualitative conceptual physics problem of an unfamiliar type. Our goal was to elucidate the detailed cognitive processes and knowledge elements involved, irrespective of final solution form, and consider implications for instruction. The basic but non-trivial problem was to find qualitatively the direction of acceleration of a pendulum bob at various stages of its motion, a problem originally studied by Reif and Allen. Methodology included interviews, introspection, retrospection and self-reported metacognition. Multiple facets of cognition were revealed, with different reasoning strategies used at different stages and for different points on the path. An account is given of the zigzag thinking paths and interplay of reasoning modes and schema elements involved. We interpret the cognitive processes in terms of theoretical concepts that emerged, namely: case-based, principle-based, experiential-intuitive and practical-heuristic reasoning; knowledge elements and schemata; activation; metacognition and epistemic framing. The complexity of cognition revealed in this case study contrasts with the tidy principle-based solutions we present to students. The pervasive role of schemata, case-based reasoning, practical heuristic strategies, and their interplay with physics principles is noteworthy, since these aspects of cognition are generally neither recognized nor taught. The schema/reasoning-mode perspective has direct application in science teaching, learning and problem-solving.

Intelligent design of permanent magnet synchronous motor based on CBR

NASA Astrophysics Data System (ADS)

Li, Cong; Fan, Beibei

2018-05-01

Aiming at many problems in the design process of Permanent magnet synchronous motor (PMSM), such as the complexity of design process, the over reliance on designers' experience and the lack of accumulation and inheritance of design knowledge, a design method of PMSM Based on CBR is proposed in order to solve those problems. In this paper, case-based reasoning (CBR) methods of cases similarity calculation is proposed for reasoning suitable initial scheme. This method could help designers, by referencing previous design cases, to make a conceptual PMSM solution quickly. The case retain process gives the system self-enrich function which will improve the design ability of the system with the continuous use of the system.

[AGAINST PATERNALISTIC VIEWS ON NEUROENHANCEMENT: A LIBERTARIAN EVOLUTIONARY ACCOUNT].

PubMed

Corbellini, Gilberto; Sirgiovanni, Elisabetta

2015-01-01

The term "enhancement" has come to represent a very precise form of improving individual skills. By means of pharmaceutics, surgery, and reproductive technology, all originally intended for clinical use, healthy individuals may improve their cognitive and emotional capacities for many reasons, such as to gain a competitive edge. In today's society, cognitive performance and mood assume a more relevant role than physical ability if one aspires to emerge above the average. In this paper, we present and discuss common views on "neuroenhancement," a term often used to describe the use of artificial means that interfer with brain function to improve cognitive skills. Most philosophical arguments and beliefs on the topic are based on some inappropriate distinctions and definitions which favour unfruitful alarmist attitudes and may obscure the complexity of the issue. In particular we point out that both radical prohibitionist and libertarian approaches are affected by paternalistic ideas which we refute. We also show that even though enhancement nowadays is occurring at an impressive rate, we cannot infer that it is a present-day phenomenon, because enhancement is a human disposition, shared between most species and has always existed. We argue against moralistic views on neuroenhancement and defend a reasoned libertarian perspective. We believe that case-by-case evolutionary-medical heuristics is the best approach to help individuals in their autonomous choices.

Physical Therapy in the Treatment of Central Pain Mechanisms for Female Sexual Pain.

PubMed

Vandyken, Carolyn; Hilton, Sandra

2017-01-01

The complexity of female sexual pain requires an interdisciplinary approach. Physical therapists trained in pelvic health conditions are well positioned to be active members of an interdisciplinary team addressing the assessment and treatment of female sexual pain. Changes within physical therapy practice in the last ten years have resulted in significant utilization of pelvic floor muscle relaxation and manual therapy techniques to address a variety of pelvic pain conditions, including female sexual pain. However, sexual pain is a complex issue giving credence to the necessity of addressing all of the drivers of the pain experience- biological, psychological and social. This review aims to reconcile current pain science with a plan for integrating a biopsychosocial approach into the evaluation and subsequent treatment for female sexual pain for physical therapists. A literature review of the important components of skilled physical therapy interventions is presented including the physical examination, pain biology education, cognitive behavioral influences in treatment design, motivational interviewing as an adjunct to empathetic practice, and the integration of non-threatening movement and mindfulness into treatment. A single case study is used to demonstrate the biopsychosocial framework utilized in this approach. Appropriate measures for assessing psychosocial factors are readily available and inform a reasoned approach for physical therapy design that addresses both peripheral and central pain mechanisms. Decades of research support the integration of a biopsychosocial approach in the treatment of complex pain, including female sexual pain. It is reasonable for physical therapists to utilize evidence based strategies such as CBT, pain biology education, Mindfulness Based Stress Reduction (MBSR), yoga and imagery based exercises to address the biopsychosocial components of female sexual pain. Copyright © 2016 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

An experiment-based comparative study of fuzzy logic control

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.; Chen, Yung-Yaw; Lee, Chuen-Chein; Murugesan, S.; Jang, Jyh-Shing

1989-01-01

An approach is presented to the control of a dynamic physical system through the use of approximate reasoning. The approach has been implemented in a program named POLE, and the authors have successfully built a prototype hardware system to solve the cartpole balancing problem in real-time. The approach provides a complementary alternative to the conventional analytical control methodology and is of substantial use when a precise mathematical model of the process being controlled is not available. A set of criteria for comparing controllers based on approximate reasoning and those based on conventional control schemes is furnished.

A framework for the social valuation of ecosystem services.

PubMed

Felipe-Lucia, María R; Comín, Francisco A; Escalera-Reyes, Javier

2015-05-01

Methods to assess ecosystem services using ecological or economic approaches are considerably better defined than methods for the social approach. To identify why the social approach remains unclear, we reviewed current trends in the literature. We found two main reasons: (i) the cultural ecosystem services are usually used to represent the whole social approach, and (ii) the economic valuation based on social preferences is typically included in the social approach. Next, we proposed a framework for the social valuation of ecosystem services that provides alternatives to economics methods, enables comparison across studies, and supports decision-making in land planning and management. The framework includes the agreements emerged from the review, such as considering spatial-temporal flows, including stakeholders from all social ranges, and using two complementary methods to value ecosystem services. Finally, we provided practical recommendations learned from the application of the proposed framework in a case study.

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

PubMed

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.

A Worksheet for Ethics Instruction and Exercises in Reason.

ERIC Educational Resources Information Center

Bivins, Thomas H.

1993-01-01

Argues that teaching applied mass media ethics requires two vital components: a grounding in the relevant ethical theories, and a structured approach to analyzing the issues in case-study format. Presents a worksheet model that provides such an approach over a wide range of issues. (SR)

Mental Insanity Assessment of Pedophilia: The Importance of the Trans-Disciplinary Approach. Reflections on Two Cases.

PubMed

Scarpazza, Cristina; Pennati, Ambrogio; Sartori, Giuseppe

2018-01-01

A 60 plus-year-old male was charged with pedophilia for forcing a child to touch him inappropriately near a primary school fence. In another case, a 70 plus-year-old male was charged with pedophilia for intimately touching a boy in a cinema. What led them to manifest this socially-inappropriate and legally-relevant behavior? Is there an explanation for the sexually-related behavioral changes emerging late in life of these two men? Indeed, a common point exists between the two men: both were found to suffer from highly-disabling neurological conditions, known to have a potential effect on social behavior. Specifically, a large right frontoparietal meningioma was found to have important influence on the first man's cognition and control inhibition, whereas frontotemporal dementia prevented the second man from understanding the moral disvalue of his sexually-inappropriate behavior and controlling his sexual impulses. In the current presentation, particular emphasis is placed on the logical reasoning supporting the conclusions that both the pedophiles should be considered not guilty by reason of insanity. Furthermore, experimental methods have been used to explore both cases, which rely on the existence of cognitive models for the phenomena under study, the integration of insights offered by different disciplines and the application of a variety of tools and approaches that follow the "convergence of evidence" principle, which could be safely used in court to support a mental insanity claim. Here, we describe how the use of the experimental method could become useful to reduce the uncertainty in mental insanity assessments. The use of a transdisciplinary, scientifically-grounded approach can help to change the way legal phenomena are interpreted. For instance, when assessing mental insanity, consultants should not only investigate the eventual existence of a diagnosis, but should assess the cognitive/affective abilities that are necessary to understand our own behavior and emotions as well as those of others. The criteria for responsibility should be symptoms-based and not diagnosis-based. Since pedophilia is among the most hideous behaviors condemned by society, a more comprehensive and transdisciplinary approach is recommended in court.

16 CFR 306.5 - Automotive fuel rating.

Code of Federal Regulations, 2010 CFR

2010-01-01

... fuels other than biodiesel blends and biomass-based diesel blends, you must possess a reasonable basis... the fuel, and in the case of biomass-based diesel blends, you must possess a reasonable basis, consisting of competent and reliable evidence, for the percentage of biomass-based diesel contained in the...

Human Benchmarking of Expert Systems. Literature Review

DTIC Science & Technology

1990-01-01

effetiveness of the development procedures used in order to predict whether the aplication of similar approaches will likely have effective and...they used in their learning and problem solving. We will describe these approaches later. Reasoning. Reasoning usually includes inference. Because to ... in the software engineering process. For example, existing approaches to software evaluation in the military are based on a model of conventional

Moving Perspectives on Patient Competence: A Naturalistic Case Study in Psychiatry.

PubMed

Ruissen, A M; Abma, T A; Van Balkom, A J L M; Meynen, G; Widdershoven, G A M

2016-03-01

Patient competence, defined as the ability to reason, appreciate, understand, and express a choice is rarely discussed in patients with obsessive compulsive disorder (OCD), and coercive measures are seldom used. Nevertheless, a psychiatrist of psychologist may doubt whether OCD patients who refuse treatment understand their disease and the consequences of not being treated, which could result in tension between respecting the patient's autonomy and beneficence. The purpose of this article is to develop a notion of competence that is grounded in clinical practice and corresponds with the experiences of patients with obsessions and/or compulsions. We present a naturalistic case study giving both the patient's and the therapist's perspective based on in-depth interviews and a narrative analysis. The case study shows that competence is not merely an assessment by a therapist, but also a co-constructed reality shaped by the experiences and stories of patient and therapist. The patient, a medical student, initially told her story in a restitution narrative, focusing on cognitive rationality. Reconstructing the history of her disease, her story changed into a quest narrative where there was room for emotions, values and moral learning. This fitted well with the therapist's approach, who used motivational interventions with a view to appealing to the patient's responsibility to deal with her condition. We conclude that in practice both the patient and therapist used a quest narrative, approaching competence as the potential for practical reasoning to incorporate values and emotions.

Teaching Statistics in Middle School Mathematics Classrooms: Making Links with Mathematics but Avoiding Statistical Reasoning

ERIC Educational Resources Information Center

Savard, Annie; Manuel, Dominic

2015-01-01

Statistics is a domain that is taught in Mathematics in all school levels. We suggest a potential in using an interdisciplinary approach with this concept. Thus the development of the understanding of a situation might mean to use both mathematical and statistical reasoning. In this paper, we present two case studies where two middle school…

Tool use in left-brain-damaged patients: Difficulties in reasoning but not in estimating the physical properties of objects.

PubMed

Faye, Alexandrine; Jacquin-Courtois, Sophie; Osiurak, François

2018-03-01

The purpose of this study was to deepen our understanding of the cognitive bases of human tool use based on the technical reasoning hypothesis (i.e., the reasoning-based approach). This approach assumes that tool use is supported by the ability to reason about an object's physical properties (e.g., length, weight, strength, etc.) to perform mechanical actions (e.g., lever). In this framework, an important issue is to understand whether left-brain-damaged (LBD) individuals with tool-use deficits are still able to estimate the physical object's properties necessary to use the tool. Eleven LBD patients and 12 control participants performed 3 original experimental tasks: Use-Length (visual evaluation of the length of a stick to bring down a target), Visual-Length (to visually compare objects of different lengths) and Addition-Length (to visually compare added lengths). Participants were also tested on conventional tasks: Familiar Tool Use and Mechanical Problem-Solving (novel tools). LBD patients had more difficulties than controls on both conventional tasks. No significant differences were observed for the 3 experimental tasks. These results extend the reasoning-based approach, stressing that it might not be the representation of length that is impaired in LBD patients, but rather the ability to generate mechanical actions based on physical object properties. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Sketching the Invisible to Predict the Visible: From Drawing to Modeling in Chemistry.

PubMed

Cooper, Melanie M; Stieff, Mike; DeSutter, Dane

2017-10-01

Sketching as a scientific practice goes beyond the simple act of inscribing diagrams onto paper. Scientists produce a wide range of representations through sketching, as it is tightly coupled to model-based reasoning. Chemists in particular make extensive use of sketches to reason about chemical phenomena and to communicate their ideas. However, the chemical sciences have a unique problem in that chemists deal with the unseen world of the atomic-molecular level. Using sketches, chemists strive to develop causal mechanisms that emerge from the structure and behavior of molecular-level entities, to explain observations of the macroscopic visible world. Interpreting these representations and constructing sketches of molecular-level processes is a crucial component of student learning in the modern chemistry classroom. Sketches also serve as an important component of assessment in the chemistry classroom as student sketches give insight into developing mental models, which allows instructors to observe how students are thinking about a process. In this paper we discuss how sketching can be used to promote such model-based reasoning in chemistry and discuss two case studies of curricular projects, CLUE and The Connected Chemistry Curriculum, that have demonstrated a benefit of this approach. We show how sketching activities can be centrally integrated into classroom norms to promote model-based reasoning both with and without component visualizations. Importantly, each of these projects deploys sketching in support of other types of inquiry activities, such as making predictions or depicting models to support a claim; sketching is not an isolated activity but is used as a tool to support model-based reasoning in the discipline. Copyright © 2017 Cognitive Science Society, Inc.

Developing integrated clinical reasoning competencies in dental students using scaffolded case-based learning - empirical evidence.

PubMed

Postma, T C; White, J G

2016-08-01

This study provides empirical evidence of the development of integrated clinical reasoning in the discipline-based School of Dentistry, University of Pretoria, South Africa. Students were exposed to case-based learning in comprehensive patient care (CPC) in the preclinical year of study, scaffolded by means of the four-component instructional design model for complex learning. Progress test scores of third- to fifth-year dental students, who received case-based teaching and learning in the third year (2009-2011), were compared to the scores of preceding fourth- and fifth-year cohorts. These fourth- and fifth-year cohorts received content-based teaching concurrently with their clinical training in CPC. The progress test consisted of a complex case study and 32 MCQs on tracer conditions. Students had to gather the necessary information and had to make diagnostic and treatment-planning decisions. Preclinical students who participated in the case-based teaching and learning achieved similar scores compared to final-year students who received lecture-based teaching and learning. Final-year students who participated in the case-based learning made three more correct clinical decisions per student, compared to those who received content-based teaching. Students struggled more with treatment-planning than with diagnostic decisions. The scaffolded case-based learning appears to contribute to accurate clinical decisions when compared to lecture-based teaching. It is suggested that the development of integrated reasoning competencies starts as early as possible in a dental curriculum, perhaps even in the preclinical year of study. Treatment-planning should receive particular attention. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Improvement of Automated POST Case Success Rate Using Support Vector Machines

NASA Technical Reports Server (NTRS)

Zwack, Matthew R.; Dees, Patrick D.

2017-01-01

During early conceptual design of complex systems, concept down selection can have a large impact upon program life-cycle cost. Therefore, any concepts selected during early design will inherently commit program costs and affect the overall probability of program success. For this reason it is important to consider as large a design space as possible in order to better inform the down selection process. For conceptual design of launch vehicles, trajectory analysis and optimization often presents the largest obstacle to evaluating large trade spaces. This is due to the sensitivity of the trajectory discipline to changes in all other aspects of the vehicle design. Small deltas in the performance of other subsystems can result in relatively large fluctuations in the ascent trajectory because the solution space is non-linear and multi-modal [1]. In order to help capture large design spaces for new launch vehicles, the authors have performed previous work seeking to automate the execution of the industry standard tool, Program to Optimize Simulated Trajectories (POST). This work initially focused on implementation of analyst heuristics to enable closure of cases in an automated fashion, with the goal of applying the concepts of design of experiments (DOE) and surrogate modeling to enable near instantaneous throughput of vehicle cases [2]. Additional work was then completed to improve the DOE process by utilizing a graph theory based approach to connect similar design points [3]. The conclusion of the previous work illustrated the utility of the graph theory approach for completing a DOE through POST. However, this approach was still dependent upon the use of random repetitions to generate seed points for the graph. As noted in [3], only 8% of these random repetitions resulted in converged trajectories. This ultimately affects the ability of the random reps method to confidently approach the global optima for a given vehicle case in a reasonable amount of time. With only an 8% pass rate, tens or hundreds of thousands of reps may be needed to be confident that the best repetition is at least close to the global optima. However, typical design study time constraints require that fewer repetitions be attempted, sometimes resulting in seed points that have only a handful of successful completions. If a small number of successful repetitions are used to generate a seed point, the graph method may inherit some inaccuracies as it chains DOE cases from the non-global-optimal seed points. This creates inherent noise in the graph data, which can limit the accuracy of the resulting surrogate models. For this reason, the goal of this work is to improve the seed point generation method and ultimately the accuracy of the resulting POST surrogate model. The work focuses on increasing the case pass rate for seed point generation.

Ontology Performance Profiling and Model Examination: First Steps

NASA Astrophysics Data System (ADS)

Wang, Taowei David; Parsia, Bijan

"[Reasoner] performance can be scary, so much so, that we cannot deploy the technology in our products." - Michael Shepard. What are typical OWL users to do when their favorite reasoner never seems to return? In this paper, we present our first steps considering this problem. We describe the challenges and our approach, and present a prototype tool to help users identify reasoner performance bottlenecks with respect to their ontologies. We then describe 4 case studies on synthetic and real-world ontologies. While the anecdotal evidence suggests that the service can be useful for both ontology developers and reasoner implementors, much more is desired.

Case-Based Policy and Goal Recognition

DTIC Science & Technology

2015-09-30

or noisy. Ontanón et al. [8] use case-based reasoning (CBR) to model human driving vehicle control behaviors and skill level to reduce teen crash...Snodgrass, S., Bonfiglio, D., Winston, F.K., McDonald, C., Gonzalez, A.J.: Case-based prediction of teen driver behavior and skill. In: Pro- ceedings

Overview of psychiatric ethics IV: the method of casuistry.

PubMed

Robertson, Michael; Ryan, Christopher; Walter, Garry

2007-08-01

The aim of this paper is to describe the method of ethical analysis known as casuistry and consider its merits as a basis of ethical deliberation in psychiatry. Casuistry approximates the legal arguments of common law. It examines ethical dilemmas by adopting a taxonomic approach to 'paradigm' cases, using a technique akin to that of normative analogical reasoning. Casuistry offers a useful method in ethical reasoning through providing a practical means of evaluating the merits of a particular course of action in a particular clinical situation. As a method ethical moral reasoning in psychiatry, casuistry suffers from a paucity of paradigm cases and its failure to fully contextualize ethical dilemmas by relying on common morality theory as its basis.

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

PubMed

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.

Screening for cerebrovascular disease in microcephalic osteodysplastic primordial dwarfism type II (MOPD II): an evidence-based proposal.

PubMed

Perry, Luke D; Robertson, Fergus; Ganesan, Vijeya

2013-04-01

Microcephalic osteodysplastic primordial dwarfism type II (OMIM 210720) is a rare autosomal recessive condition frequently associated with early-onset cerebrovascular disease. Presymptomatic detection and intervention could prevent the adverse consequences associated with this. We reviewed published cases of microcephalic osteodysplastic primordial dwarfism type II to ascertain prevalence and characteristics of cerebrovascular disease and use these data to propose an evidence-based approach to cerebrovascular screening. Of 147 cases identified, 47 had cerebrovascular disease (32%), including occlusive arteriopathy (including moyamoya) and cerebral aneurysmal disease. Occlusive disease occurred in younger individuals, and progression can be both rapid and clinically silent. A reasonable screening approach would be magnetic resonance imaging and angiography of the cervical and intracranial circulation at diagnosis, repeated at yearly intervals until 10 years, and every 2 years thereafter, unless clinical concerns occur earlier. At present it would appear that this needs to be life-long. Families and professionals should be alerted to the potential significance of neurologic symptoms and measures should be taken to maintain good vascular health in affected individuals. Copyright © 2013 Elsevier Inc. All rights reserved.

Newly developed liquid-based cytology. TACAS™: cytological appearance and HPV testing using liquid-based sample.

PubMed

Kubushiro, Kaneyuki; Taoka, Hideki; Sakurai, Nobuyuki; Yamamoto, Yasuhiro; Kurasaki, Akiko; Asakawa, Yasuyuki; Iwahara, Minoru; Takahashi, Kei

2011-09-01

Cell profiles determined by the thin-layer advanced cytology assay system (TACAS™), a liquid-based cytology technique newly developed in Japan, were analyzed in this study. Hybrid capture 2 (HC-2) was also performed using the liquid-based samples prepared by TACAS to ascertain its ability to detect human papillomavirus (HPV). Cell collection samples from uterine cervix were obtained from 359 patients and examined cytologically. A HC-2 assay for HPV was carried out in the cell specimens. All specimens were found to show background factors such as leukocytes. After excluding the 5 unsatisfactory cases from the total 354 cases, 82 cases (23.2%) were positive and 272 cases (76.8%) were negative for HPV. Cell specimens from 30 HPV-positive cases and 166 HPV-negative cases were subjected to 4 weeks of preservation at room temperature. Then, when subsequently re-assayed, 28 cases (93.3%) in the former group were found to be HPV positive and 164 cases (98.8%) in the latter group were found to be HPV negative. These results supported the excellent reproducibility of TACAS for HPV testing. A reasonable inference from the foregoing analysis is that TACAS may be distinguished from other liquid-based cytological approaches, such as ThinPrep and SurePath, in that it can retain the cell backgrounds. Furthermore, this study raises the possibility that cell specimens prepared using TACAS could be preserved for at least 4 weeks prior to carrying out a HC-2 assay for HPV.

34 CFR Appendix D to Part 682 - Policy for Waiving the Secretary's Right To Recover or Refuse To Pay Interest Benefits, Special...

Code of Federal Regulations, 2014 CFR

2014-07-01

... following approaches to its enforcement of its own due diligence and timely filing rules for violations... engaged in, and documented, a case-by-case exercise of reasonable discretion allowing for guarantee... payments in accordance with the original repayment schedule or agreement.) In the case of a payment made by...

34 CFR Appendix D to Part 682 - Policy for Waiving the Secretary's Right To Recover or Refuse To Pay Interest Benefits, Special...

Code of Federal Regulations, 2013 CFR

2013-07-01

... following approaches to its enforcement of its own due diligence and timely filing rules for violations... engaged in, and documented, a case-by-case exercise of reasonable discretion allowing for guarantee... payments in accordance with the original repayment schedule or agreement.) In the case of a payment made by...

34 CFR Appendix D to Part 682 - Policy for Waiving the Secretary's Right To Recover or Refuse To Pay Interest Benefits, Special...

Code of Federal Regulations, 2011 CFR

2011-07-01

... following approaches to its enforcement of its own due diligence and timely filing rules for violations... engaged in, and documented, a case-by-case exercise of reasonable discretion allowing for guarantee... payments in accordance with the original repayment schedule or agreement.) In the case of a payment made by...

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

PubMed

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 the ethically difficult patient situation.

Articular dysfunction patterns in patients with mechanical neck pain: a clinical algorithm to guide specific mobilization and manipulation techniques.

PubMed

Dewitte, Vincent; Beernaert, Axel; Vanthillo, Bart; Barbe, Tom; Danneels, Lieven; Cagnie, Barbara

2014-02-01

In view of a didactical approach for teaching cervical mobilization and manipulation techniques to students as well as their use in daily practice, it is mandatory to acquire sound clinical reasoning to optimally apply advanced technical skills. The aim of this Masterclass is to present a clinical algorithm to guide (novice) therapists in their clinical reasoning to identify patients who are likely to respond to mobilization and/or manipulation. The presented clinical reasoning process is situated within the context of pain mechanisms and is narrowed to and applicable in patients with a dominant input pain mechanism. Based on key features in subjective and clinical examination, patients with mechanical nociceptive pain probably arising from articular structures can be categorized into specific articular dysfunction patterns. Pending on these patterns, specific mobilization and manipulation techniques are warranted. The proposed patterns are illustrated in 3 case studies. This clinical algorithm is the corollary of empirical expertise and is complemented by in-depth discussions and knowledge exchange with international colleagues. Consequently, it is intended that a carefully targeted approach contributes to an increase in specificity and safety in the use of cervical mobilizations and manipulation techniques as valuable adjuncts to other manual therapy modalities. Copyright © 2013 Elsevier Ltd. All rights reserved.

A genetic algorithm for dynamic inbound ordering and outbound dispatching problem with delivery time windows

NASA Astrophysics Data System (ADS)

Kim, Byung Soo; Lee, Woon-Seek; Koh, Shiegheun

2012-07-01

This article considers an inbound ordering and outbound dispatching problem for a single product in a third-party warehouse, where the demands are dynamic over a discrete and finite time horizon, and moreover, each demand has a time window in which it must be satisfied. Replenishing orders are shipped in containers and the freight cost is proportional to the number of containers used. The problem is classified into two cases, i.e. non-split demand case and split demand case, and a mathematical model for each case is presented. An in-depth analysis of the models shows that they are very complicated and difficult to find optimal solutions as the problem size becomes large. Therefore, genetic algorithm (GA) based heuristic approaches are designed to solve the problems in a reasonable time. To validate and evaluate the algorithms, finally, some computational experiments are conducted.

REASONS FOR ELECTRONIC CIGARETTE USE BEYOND CIGARETTE SMOKING CESSATION: A CONCEPT MAPPING APPROACH

PubMed Central

Soule, Eric K.; Rosas, Scott R.; Nasim, Aashir

2016-01-01

Introduction Electronic cigarettes (ECIGs) continue to grow in popularity, however, limited research has examined reasons for ECIG use. Methods This study used an integrated, mixed-method participatory research approach called concept mapping (CM) to characterize and describe adults’ reasons for using ECIGs. A total of 108 adults completed a multi-module online CM study that consisted of brainstorming statements about their reasons for ECIG use, sorting each statement into conceptually similar categories, and then rating each statement based on whether it represented a reason why they have used an ECIG in the past month. Results Participants brainstormed a total of 125 unique statements related to their reasons for ECIG use. Multivariate analyses generated a map revealing 11, interrelated components or domains that characterized their reasons for use. Importantly, reasons related to Cessation Methods, Perceived Health Benefits, Private Regard, Convenience and Conscientiousness were rated significantly higher than other categories/types of reasons related to ECIG use (p<.05). There also were significant model differences in participants’ endorsement of reasons based on their demography and ECIG behaviors. Conclusions This study shows that ECIG users are motivated to use ECIGs for many reasons. ECIG regulations should address these reasons for ECIG use in addition to smoking cessation. PMID:26803400

Reasons for electronic cigarette use beyond cigarette smoking cessation: A concept mapping approach.

PubMed

Soule, Eric K; Rosas, Scott R; Nasim, Aashir

2016-05-01

Electronic cigarettes (ECIGs) continue to grow in popularity, however, limited research has examined reasons for ECIG use. This study used an integrated, mixed-method participatory research approach called concept mapping (CM) to characterize and describe adults' reasons for using ECIGs. A total of 108 adults completed a multi-module online CM study that consisted of brainstorming statements about their reasons for ECIG use, sorting each statement into conceptually similar categories, and then rating each statement based on whether it represented a reason why they have used an ECIG in the past month. Participants brainstormed a total of 125 unique statements related to their reasons for ECIG use. Multivariate analyses generated a map revealing 11, interrelated components or domains that characterized their reasons for use. Importantly, reasons related to Cessation Methods, Perceived Health Benefits, Private Regard, Convenience and Conscientiousness were rated significantly higher than other categories/types of reasons related to ECIG use (p<.05). There also were significant model differences in participants' endorsement of reasons based on their demography and ECIG behaviors. This study shows that ECIG users are motivated to use ECIGs for many reasons. ECIG regulations should address these reasons for ECIG use in addition to smoking cessation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Comparison of ethical judgments exhibited by clients and ethics consultants in Japan.

PubMed

Nagao, Noriko; Kadooka, Yasuhiro; Asai, Atsushi

2014-03-04

Healthcare professionals must make decisions for patients based on ethical considerations. However, they rely on clinical ethics consultations (CEC) to review ethical justifications of their decisions. CEC consultants support the cases reviewed and guide medical care. When both healthcare professionals and CEC consultants face ethical problems in medical care, how is their judgment derived? How do medical judgments differ from the ethical considerations of CECs? This study examines CECs in Japan to identify differences in the ethical judgment of clients and CEC consultants. The CEC request and response documents of all 60 cases reviewed across Japan between October 2006 and the end of October 2011 were classified in terms of the presence of decisional capacity in the patient. We conducted a qualitative content analysis of the differences in reasoning between client and CEC consultants. Reasoned judgments were verified in individual cases to classify the similarities or differences of opinion between CEC clients and teams. As the result of classification of the decisional capacity and the difference of opinion regarding medical care, the most frequent category was 25 cases (41.7%) of "uncertain decisional capacity," and 23 cases (38.3%) of "withholding of decision-making." A chi-square analysis was performed on presence of decisional capacity and agreement in decision-making, yielding a statistically significant difference (p < 0.05). The CEC consultants' reasoning was based on "patient's preference was ambiguous," "validity of family as a surrogate," "estimation of patient preference," and "patient's best interest," whereas the CEC client's reasoning was based on "consistent family preference was shown/not shown" and "appropriate therapeutic methods to manage patient safety." Differences in opinions were found in cases classified according to decisional capacity. Furthermore, the reasoning behind judgments differed between CEC clients and CEC consultants. The reasoning of CEC consultants was critical and reflective, while for clients it was situational and pragmatic.

Joint sparsity based heterogeneous data-level fusion for target detection and estimation

NASA Astrophysics Data System (ADS)

Niu, Ruixin; Zulch, Peter; Distasio, Marcello; Blasch, Erik; Shen, Dan; Chen, Genshe

2017-05-01

Typical surveillance systems employ decision- or feature-level fusion approaches to integrate heterogeneous sensor data, which are sub-optimal and incur information loss. In this paper, we investigate data-level heterogeneous sensor fusion. Since the sensors monitor the common targets of interest, whose states can be determined by only a few parameters, it is reasonable to assume that the measurement domain has a low intrinsic dimensionality. For heterogeneous sensor data, we develop a joint-sparse data-level fusion (JSDLF) approach based on the emerging joint sparse signal recovery techniques by discretizing the target state space. This approach is applied to fuse signals from multiple distributed radio frequency (RF) signal sensors and a video camera for joint target detection and state estimation. The JSDLF approach is data-driven and requires minimum prior information, since there is no need to know the time-varying RF signal amplitudes, or the image intensity of the targets. It can handle non-linearity in the sensor data due to state space discretization and the use of frequency/pixel selection matrices. Furthermore, for a multi-target case with J targets, the JSDLF approach only requires discretization in a single-target state space, instead of discretization in a J-target state space, as in the case of the generalized likelihood ratio test (GLRT) or the maximum likelihood estimator (MLE). Numerical examples are provided to demonstrate that the proposed JSDLF approach achieves excellent performance with near real-time accurate target position and velocity estimates.

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

PubMed

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.

Verifying Hybrid Systems Modeled as Timed Automata: A Case Study

DTIC Science & Technology

1997-03-01

Introduction Researchers have proposed many innovative formal methods for developing real - time systems [9]. Such methods can give system developers and...customers greater con dence that real - time systems satisfy their requirements, especially their crit- ical requirements. However, applying formal methods...specifying and reasoning about real - time systems that is designed to address these challenging problems. Our approach is to build formal reasoning tools

A state-based approach to trend recognition and failure prediction for the Space Station Freedom

NASA Technical Reports Server (NTRS)

Nelson, Kyle S.; Hadden, George D.

1992-01-01

A state-based reasoning approach to trend recognition and failure prediction for the Altitude Determination, and Control System (ADCS) of the Space Station Freedom (SSF) is described. The problem domain is characterized by features (e.g., trends and impending failures) that develop over a variety of time spans, anywhere from several minutes to several years. Our state-based reasoning approach, coupled with intelligent data screening, allows features to be tracked as they develop in a time-dependent manner. That is, each state machine has the ability to encode a time frame for the feature it detects. As features are detected, they are recorded and can be used as input to other state machines, creating a hierarchical feature recognition scheme. Furthermore, each machine can operate independently of the others, allowing simultaneous tracking of features. State-based reasoning was implemented in the trend recognition and the prognostic modules of a prototype Space Station Freedom Maintenance and Diagnostic System (SSFMDS) developed at Honeywell's Systems and Research Center.

Describing content in middle school science curricula

NASA Astrophysics Data System (ADS)

Schwarz-Ballard, Jennifer A.

As researchers and designers, we intuitively recognize differences between curricula and describe them in terms of design strategy: project-based, laboratory-based, modular, traditional, and textbook, among others. We assume that practitioners recognize the differences in how each requires that students use knowledge, however these intuitive differences have not been captured or systematically described by the existing languages for describing learning goals. In this dissertation I argue that we need new ways of capturing relationships among elements of content, and propose a theory that describes some of the important differences in how students reason in differently designed curricula and activities. Educational researchers and curriculum designers have taken a variety of approaches to laying out learning goals for science. Through an analysis of existing descriptions of learning goals I argue that to describe differences in the understanding students come away with, they need to (1) be specific about the form of knowledge, (2) incorporate both the processes through which knowledge is used and its form, and (3) capture content development across a curriculum. To show the value of inquiry curricula, learning goals need to incorporate distinctions among the variety of ways we ask students to use knowledge. Here I propose the Epistemic Structures Framework as one way to describe differences in students reasoning that are not captured by existing descriptions of learning goals. The usefulness of the Epistemic Structures framework is demonstrated in the four curriculum case study examples in Part II of this work. The curricula in the case studies represent a range of content coverage, curriculum structure, and design rationale. They serve both to illustrate the Epistemic Structures analysis process and make the case that it does in fact describe learning goals in a way that captures important differences in students reasoning in differently designed curricula. Describing learning goals in terms of Epistemic Structures provides one way to define what we mean when we talk about "project-based" curricula and demonstrate its "value added" to educators, administrators and policy makers.

A National Evaluation of the Conservative Management of Uncomplicated Acute Appendicitis: How Common Is This and What Are the Issues.

PubMed

Kelly, Michael E; Khan, Asif; Ur Rehman, Jameel; Waldron, Ronan M; Khan, Waqar; Barry, Kevin; Khan, Iqbal Z

2015-01-01

The management approach for acute appendicitis has been challenged in recent years, with numerous randomized controlled trials demonstrating that antibiotics/conservative management is an efficacious treatment, with lower complication rates. A national survey of all consultant general surgeons evaluating their practices was performed. Reasons for changed practices, choice of antibiotics and follow-up investigations were evaluated. In addition, the role of interval appendicectomy and conservative management in the pediatric population was also assessed. The response rate for this survey was 74.7% (n = 74/99). Over one-fifth (n = 17, 22.9%) routinely treat acute appendicitis conservatively, while another 14.8% (n = 11) consider this approach in selected cases. Main reasons for modified practices included the presence of inflammatory phlegmon (75%), delayed presentation (64%), and recent evidence-based medicine developments (46%). Co-amoxiclav/clavulanic acid was the most popular antibiotic for conservative management (53%). Alternatively, combinations of antibiotics were also utilized. One-third felt interval appendicectomy was warranted, while one-fifth supported conservative management in the paediatric setting. The overwhelming majority (>95%) advocate follow-up colonoscopy ± computed tomography in any patient aged >40 years managed conservatively. Considerable variation in management of uncomplicated appendicitis remains in Ireland despite growing evidence suggesting that the non-operative approach is safe. Reasons for adopting a conservative management practice have been identified and reflect the expanding literature on this subject. © 2015 S. Karger AG, Basel.

[Teaching of clinical reasoning to medical students using prototypical clinical cases].

PubMed

Montaldo L, Gustavo; Herskovic L, Pedro

2013-07-01

Clinical reasoning is the most important competente in the training process of a physician. To develop a method for teaching clinical reasoning based on prototypes of clinical cases. The study was conducted on sixty-four third year medical students. The study and control groups attended lectures and tutorial sessions with patients. The study group attended additionally discussion seminars of prototypical clinical cases. A clinical reasoning test was applied at the start and end of the learning period to both groups. At the end of the study, the opinions of students of the study group were collected in a focus group. After the learning period, both groups significantly increased their clinical reasoning skills. However, the improvement in the study group was more than double than that of the control group. The absolute improvement in the study group was 30.9%. Students interviewed in the focus group were unanimous in expressing their satisfaction in each and every aspect discussed. The teaching of clinical reasoning to third year medical students by means of pattern recognition in seminars with clinical cases improved significantly their skills.

TuMore: generation of synthetic brain tumor MRI data for deep learning based segmentation approaches

NASA Astrophysics Data System (ADS)

Lindner, Lydia; Pfarrkirchner, Birgit; Gsaxner, Christina; Schmalstieg, Dieter; Egger, Jan

2018-03-01

Accurate segmentation and measurement of brain tumors plays an important role in clinical practice and research, as it is critical for treatment planning and monitoring of tumor growth. However, brain tumor segmentation is one of the most challenging tasks in medical image analysis. Since manual segmentations are subjective, time consuming and neither accurate nor reliable, there exists a need for objective, robust and fast automated segmentation methods that provide competitive performance. Therefore, deep learning based approaches are gaining interest in the field of medical image segmentation. When the training data set is large enough, deep learning approaches can be extremely effective, but in domains like medicine, only limited data is available in the majority of cases. Due to this reason, we propose a method that allows to create a large dataset of brain MRI (Magnetic Resonance Imaging) images containing synthetic brain tumors - glioblastomas more specifically - and the corresponding ground truth, that can be subsequently used to train deep neural networks.

A variation-perturbation method for atomic and molecular interactions. I - Theory. II - The interaction potential and van der Waals molecule for Ne-HF

NASA Astrophysics Data System (ADS)

Gallup, G. A.; Gerratt, J.

1985-09-01

The van der Waals energy between the two parts of a system is a very small fraction of the total electronic energy. In such cases, calculations have been based on perturbation theory. However, such an approach involves certain difficulties. For this reason, van der Waals energies have also been directly calculated from total energies. But such a method has definite limitations as to the size of systems which can be treated, and recently ab initio calculations have been combined with damped semiempirical long-range dispersion potentials to treat larger systems. In this procedure, large basis set superposition errors occur, which must be removed by the counterpoise method. The present investigation is concerned with an approach which is intermediate between the previously considered procedures. The first step in the new approach involves a variational calculation based upon valence bond functions. The procedure includes also the optimization of excited orbitals, and an approximation of atomic integrals and Hamiltonian matrix elements.

ROENTGEN: case-based reasoning and radiation therapy planning.

PubMed Central

Berger, J.

1992-01-01

ROENTGEN is a design assistant for radiation therapy planning which uses case-based reasoning, an artificial intelligence technique. It learns both from specific problem-solving experiences and from direct instruction from the user. The first sort of learning is the normal case-based method of storing problem solutions so that they can be reused. The second sort is necessary because ROENTGEN does not, initially, have an internal model of the physics of its problem domain. This dependence on explicit user instruction brings to the forefront representational questions regarding indexing, failure definition, failure explanation and repair. This paper presents the techniques used by ROENTGEN in its knowledge acquisition and design activities. PMID:1482869

Knowledge-based support for the participatory design and implementation of shift systems.

PubMed

Gissel, A; Knauth, P

1998-01-01

This study developed a knowledge-based software system to support the participatory design and implementation of shift systems as a joint planning process including shift workers, the workers' committee, and management. The system was developed using a model-based approach. During the 1st phase, group discussions were repeatedly conducted with 2 experts. Thereafter a structure model of the process was generated and subsequently refined by the experts in additional semistructured interviews. Next, a factual knowledge base of 1713 relevant studies was collected on the effects of shift work. Finally, a prototype of the knowledge-based system was tested on 12 case studies. During the first 2 phases of the system, important basic information about the tasks to be carried out is provided for the user. During the 3rd phase this approach uses the problem-solving method of case-based reasoning to determine a shift rota which has already proved successful in other applications. It can then be modified in the 4th phase according to the shift workers' preferences. The last 2 phases support the final testing and evaluation of the system. The application of this system has shown that it is possible to obtain shift rotas suitable to actual problems and representative of good ergonomic solutions. A knowledge-based approach seems to provide valuable support for the complex task of designing and implementing a new shift system. The separation of the task into several phases, the provision of information at all stages, and the integration of all parties concerned seem to be essential factors for the success of the application.

Transforming Engagement: A Case Study of Building Intrinsic Motivation in a Child with Autism

ERIC Educational Resources Information Center

Dearden, Jackie; Emerson, Anne; Lewis, Tom; Papp, Rebecca

2017-01-01

This longitudinal case study of a 10-year-old girl with autism and severe communication impairment measures the impact of the MORE (Means, Opportunities, Reasons and Expectations) approach to enhancing engagement and communication. Through detailed observation of video data over a period of 28 months, engagement behaviours including interaction…

Case-based reasoning emulation of persons for wheelchair navigation.

PubMed

Peula, Jose Manuel; Urdiales, Cristina; Herrero, Ignacio; Fernandez-Carmona, Manuel; Sandoval, Francisco

2012-10-01

Testing is a key stage in system development, particularly in systems such as a wheelchair, in which the final user is typically a disabled person. These systems have stringent safety requirements, requiring major testing with many different individuals. The best would be to have the wheelchair tested by many different end users, as each disability affects driving skills in a different way. Unfortunately, from a practical point of view it is difficult to engage end users as beta testers. Hence, testing often relies on simulations. Naturally, these simulations need to be as realistic as possible to make the system robust and safe before real tests can be accomplished. This work presents a tool to automatically test wheelchairs through realistic emulation of different wheelchair users. Our approach is based on extracting meaningful data from real users driving a power wheelchair autonomously. This data is then used to train a case-based reasoning (CBR) system that captures the specifics of the driver via learning. The resulting case-base is then used to emulate the driving behavior of that specific person in more complex situations or when a new assistive algorithm needs to be tested. CBR returns user's motion commands appropriate for each specific situation to add the human component to shared control systems. The proposed system has been used to emulate several power wheelchair users presenting different disabilities. Data to create this emulation was obtained from previous wheelchair navigation experiments with 35 volunteer in-patients presenting different degrees of disability. CBR was trained with a limited number of scenarios for each volunteer. Results proved that: (i) emulated and real users returned similar paths in the same scenario (maximum and mean path deviations are equal to 23 and 10cm, respectively) and similar efficiency; (ii) we established the generality of our approach taking a new path not present in the training traces; (iii) the emulated user is more realistic - path and efficiency are less homogeneous and smooth - than potential field approaches; and (iv) the system adequately emulates in-patients - maximum and mean path deviations are equal to 19 and 8.3cm approximately and efficiencies are similar - with specific disabilities (apraxia and dementia) obtaining different behaviors during emulation for each of the in-patients, as expected. The proposed system adequately emulates the driving behavior of people with different disabilities in indoor scenarios. This approach is suitable to emulate real users' driving behaviors for early testing stages of assistive navigation systems. Copyright © 2012 Elsevier B.V. All rights reserved.

Combating weight-based bullying in schools: is there public support for the use of litigation?

PubMed

Puhl, Rebecca; Luedicke, Joerg; King, Kelly M

2015-06-01

Bullying litigation is an emerging area of law that has increased in response to serious cases of bullying at school. Weight-based bullying is prevalent at school, but no research has examined the use of litigation to address this problem. We assessed public support for litigation approaches to address weight-based bullying at school, and whether support for litigation varies according to the reason why a student is bullied. A national sample of 994 adults (49% parents) completed an online questionnaire assessing their support for litigation approaches in response to hypothetical incidents of youth bullying. As many as two thirds of participants supported litigation against schools for failing to intervene and protect students from weight-based bullying. Litigation remedies received slightly higher support in response to bullying due to race or sexual orientation compared to body weight. Participants favored litigation approaches that target schools for inadequate intervention or a bully's parents on behalf of their child's actions. Our study offers novel findings about public and parental views of litigation as a potential approach to address weight-based (and other forms of) bullying, and introduces considerations about the potential role of litigation as part of broader remedies to address youth bullying. © 2015, American School Health Association.

Towards evidence-based practice in medical training: making evaluations more meaningful.

PubMed

Drescher, Uta; Warren, Fiona; Norton, Kingsley

2004-12-01

The evaluation of training is problematic and the evidence base inconclusive. This situation may arise for 2 main reasons: training is not understood as a complex intervention and, related to this, the evaluation methods applied are often overly simplistic. This paper makes the case for construing training, especially in the field of specialist medical education, as a complex intervention. It also selectively reviews the available literature in order to match evaluative techniques with the demonstrated complexity. Construing training as a complex intervention can provide a framework for selecting the most appropriate methodology to evaluate a given training intervention and to appraise the evidence base for training fairly, choosing from among both quantitative and qualitative approaches and applying measurement at multiple levels of training impact.

Overcoming limitations of model-based diagnostic reasoning systems

NASA Technical Reports Server (NTRS)

Holtzblatt, Lester J.; Marcotte, Richard A.; Piazza, Richard L.

1989-01-01

The development of a model-based diagnostic system to overcome the limitations of model-based reasoning systems is discussed. It is noted that model-based reasoning techniques can be used to analyze the failure behavior and diagnosability of system and circuit designs as part of the system process itself. One goal of current research is the development of a diagnostic algorithm which can reason efficiently about large numbers of diagnostic suspects and can handle both combinational and sequential circuits. A second goal is to address the model-creation problem by developing an approach for using design models to construct the GMODS model in an automated fashion.

Justifying The Arts: Drama and Intercultural Education

ERIC Educational Resources Information Center

Fleming, Mike

2005-01-01

This essay describes five approaches to the question of justifying the arts before examining the specific case of drama and intercultural education. Providing a list of reasons for teaching the arts is one approach but not the only one. Instead, looking for broader categories of justification within possible lists (e.g., between art and…

Priority setting at the micro-, meso- and macro-levels in Canada, Norway and Uganda.

PubMed

Kapiriri, Lydia; Norheim, Ole Frithjof; Martin, Douglas K

2007-06-01

The objectives of this study were (1) to describe the process of healthcare priority setting in Ontario-Canada, Norway and Uganda at the three levels of decision-making; (2) to evaluate the description using the framework for fair priority setting, accountability for reasonableness; so as to identify lessons of good practices. We carried out case studies involving key informant interviews, with 184 health practitioners and health planners from the macro-level, meso-level and micro-level from Canada-Ontario, Norway and Uganda (selected by virtue of their varying experiences in priority setting). Interviews were audio-recorded, transcribed and analyzed using a modified thematic approach. The descriptions were evaluated against the four conditions of "accountability for reasonableness", relevance, publicity, revisions and enforcement. Areas of adherence to these conditions were identified as lessons of good practices; areas of non-adherence were identified as opportunities for improvement. (i) at the macro-level, in all three countries, cabinet makes most of the macro-level resource allocation decisions and they are influenced by politics, public pressure, and advocacy. Decisions within the ministries of health are based on objective formulae and evidence. International priorities influenced decisions in Uganda. Some priority-setting reasons are publicized through circulars, printed documents and the Internet in Canada and Norway. At the meso-level, hospital priority-setting decisions were made by the hospital managers and were based on national priorities, guidelines, and evidence. Hospital departments that handle emergencies, such as surgery, were prioritized. Some of the reasons are available on the hospital intranet or presented at meetings. Micro-level practitioners considered medical and social worth criteria. These reasons are not publicized. Many practitioners lacked knowledge of the macro- and meso-level priority-setting processes. (ii) Evaluation-relevance: medical evidence and economic criteria were thought to be relevant, but lobbying was thought to be irrelevant. Publicity: all cases lacked clear and effective mechanisms for publicity. REVISIONS: formal mechanisms, following the planning hierarchy, were considered less effective, informal political mechanisms were considered more effective. Canada and Norway had patients' relations officers to deal with patients' dissensions; however, revisions were more difficult in Uganda. Enforcement: leadership for ensuring decision-making fairness was not apparent. The different levels of priority setting in the three countries fulfilled varying conditions of accountability for reasonableness, none satisfied all the four conditions. To improve, decision makers at the three levels in all three cases should engage frontline practitioners, develop more effectively publicized reasons, and develop formal mechanisms for challenging and revising decisions.

Is there a role for assent or dissent in animal research?

PubMed

Kantin, Holly; Wendler, David

2015-10-01

Current regulations and widely accepted principles for animal research focus on minimizing the burdens and harms of research on animals. However, these regulations and principles do not consider a possible role for assent or dissent in animal research. Should investigators solicit the assent or respect the dissent of animals who are used in research, and, if so, under what circumstances? In this article we pursue this question and outline the relevant issues that bear on the answer. We distinguish two general reasons for respecting the preferences of research participants regarding whether they participate in research-welfare-based reasons and agency-based reasons. We argue that there are welfare-based reasons for researchers to consider, and in some cases respect, the dissent of all animals used in research. After providing a brief account of the nature of agency-based reasons, we argue that there is good reason to think that these reasons apply to at least chimpanzees. We argue that there is an additional reason for researchers to respect the dissent-and, when possible, solicit the assent-of any animal to whom agency-based reasons apply.

Fracture Analyses of Cracked Delta Eye Plates in Ship Towing

NASA Astrophysics Data System (ADS)

Huang, Xiangbing; Huang, Xingling; Sun, Jizheng

2018-01-01

Based on fracture mechanics, a safety analysis approach is proposed for cracked delta eye plates in ship towing. The static analysis model is presented when the delta eye plate is in service, and the fracture criterion is introduced on basis of stress intensity factor, which is estimated with domain integral method. Subsequently, three-dimensional finite element analyses are carried out to obtain the effective stress intensity factors, and a case is studied to demonstrate the reasonability of the approach. The results show that the classical strength theory is not applicable to evaluate the cracked plate while fracture mechanics can solve the problem very well, and the load level, which a delta eye plate can carry on, decreases evidently when it is damaged.

A case study for a psychographic-behavioral segmentation approach for targeted demand generation in voluntary medical male circumcision.

PubMed

Sgaier, Sema K; Eletskaya, Maria; Engl, Elisabeth; Mugurungi, Owen; Tambatamba, Bushimbwa; Ncube, Gertrude; Xaba, Sinokuthemba; Nanga, Alice; Gogolina, Svetlana; Odawo, Patrick; Gumede-Moyo, Sehlulekile; Kretschmer, Steve

2017-09-13

Public health programs are starting to recognize the need to move beyond a one-size-fits-all approach in demand generation, and instead tailor interventions to the heterogeneity underlying human decision making. Currently, however, there is a lack of methods to enable such targeting. We describe a novel hybrid behavioral-psychographic segmentation approach to segment stakeholders on potential barriers to a target behavior. We then apply the method in a case study of demand generation for voluntary medical male circumcision (VMMC) among 15-29 year-old males in Zambia and Zimbabwe. Canonical correlations and hierarchical clustering techniques were applied on representative samples of men in each country who were differentiated by their underlying reasons for their propensity to get circumcised. We characterized six distinct segments of men in Zimbabwe, and seven segments in Zambia, according to their needs, perceptions, attitudes and behaviors towards VMMC, thus highlighting distinct reasons for a failure to engage in the desired behavior.

A case study for a psychographic-behavioral segmentation approach for targeted demand generation in voluntary medical male circumcision

PubMed Central

Eletskaya, Maria; Engl, Elisabeth; Mugurungi, Owen; Tambatamba, Bushimbwa; Ncube, Gertrude; Xaba, Sinokuthemba; Nanga, Alice; Gogolina, Svetlana; Odawo, Patrick; Gumede-Moyo, Sehlulekile; Kretschmer, Steve

2017-01-01

Public health programs are starting to recognize the need to move beyond a one-size-fits-all approach in demand generation, and instead tailor interventions to the heterogeneity underlying human decision making. Currently, however, there is a lack of methods to enable such targeting. We describe a novel hybrid behavioral-psychographic segmentation approach to segment stakeholders on potential barriers to a target behavior. We then apply the method in a case study of demand generation for voluntary medical male circumcision (VMMC) among 15–29 year-old males in Zambia and Zimbabwe. Canonical correlations and hierarchical clustering techniques were applied on representative samples of men in each country who were differentiated by their underlying reasons for their propensity to get circumcised. We characterized six distinct segments of men in Zimbabwe, and seven segments in Zambia, according to their needs, perceptions, attitudes and behaviors towards VMMC, thus highlighting distinct reasons for a failure to engage in the desired behavior. PMID:28901285

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

ERIC Educational Resources Information Center

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…

Case Study on Optimal Routing in Logistics Network by Priority-based Genetic Algorithm

NASA Astrophysics Data System (ADS)

Wang, Xiaoguang; Lin, Lin; Gen, Mitsuo; Shiota, Mitsushige

Recently, research on logistics caught more and more attention. One of the important issues on logistics system is to find optimal delivery routes with the least cost for products delivery. Numerous models have been developed for that reason. However, due to the diversity and complexity of practical problem, the existing models are usually not very satisfying to find the solution efficiently and convinently. In this paper, we treat a real-world logistics case with a company named ABC Co. ltd., in Kitakyusyu Japan. Firstly, based on the natures of this conveyance routing problem, as an extension of transportation problem (TP) and fixed charge transportation problem (fcTP) we formulate the problem as a minimum cost flow (MCF) model. Due to the complexity of fcTP, we proposed a priority-based genetic algorithm (pGA) approach to find the most acceptable solution to this problem. In this pGA approach, a two-stage path decoding method is adopted to develop delivery paths from a chromosome. We also apply the pGA approach to this problem, and compare our results with the current logistics network situation, and calculate the improvement of logistics cost to help the management to make decisions. Finally, in order to check the effectiveness of the proposed method, the results acquired are compared with those come from the two methods/ software, such as LINDO and CPLEX.

Transformation based endorsement systems

NASA Technical Reports Server (NTRS)

Sudkamp, Thomas

1988-01-01

Evidential reasoning techniques classically represent support for a hypothesis by a numeric value or an evidential interval. The combination of support is performed by an arithmetic rule which often requires restrictions to be placed on the set of possibilities. These assumptions usually require the hypotheses to be exhausitive and mutually exclusive. Endorsement based classification systems represent support for the alternatives symbolically rather than numerically. A framework for constructing endorsement systems is presented in which transformations are defined to generate and update the knowledge base. The interaction of the knowledge base and transformations produces a non-monotonic reasoning system. Two endorsement based reasoning systems are presented to demonstrate the flexibility of the transformational approach for reasoning with ambiguous and inconsistent information.

Risk Assessment in Underground Coalmines Using Fuzzy Logic in the Presence of Uncertainty

NASA Astrophysics Data System (ADS)

Tripathy, Debi Prasad; Ala, Charan Kumar

2018-04-01

Fatal accidents are occurring every year as regular events in Indian coal mining industry. To increase the safety conditions, it has become a prerequisite to performing a risk assessment of various operations in mines. However, due to uncertain accident data, it is hard to conduct a risk assessment in mines. The object of this study is to present a method to assess safety risks in underground coalmines. The assessment of safety risks is based on the fuzzy reasoning approach. Mamdani fuzzy logic model is developed in the fuzzy logic toolbox of MATLAB. A case study is used to demonstrate the applicability of the developed model. The summary of risk evaluation in case study mine indicated that mine fire has the highest risk level among all the hazard factors. This study could help the mine management to prepare safety measures based on the risk rankings obtained.

Local electric dipole moments: A generalized approach.

PubMed

Groß, Lynn; Herrmann, Carmen

2016-09-30

We present an approach for calculating local electric dipole moments for fragments of molecular or supramolecular systems. This is important for understanding chemical gating and solvent effects in nanoelectronics, atomic force microscopy, and intensities in infrared spectroscopy. Owing to the nonzero partial charge of most fragments, "naively" defined local dipole moments are origin-dependent. Inspired by previous work based on Bader's atoms-in-molecules (AIM) partitioning, we derive a definition of fragment dipole moments which achieves origin-independence by relying on internal reference points. Instead of bond critical points (BCPs) as in existing approaches, we use as few reference points as possible, which are located between the fragment and the remainder(s) of the system and may be chosen based on chemical intuition. This allows our approach to be used with AIM implementations that circumvent the calculation of critical points for reasons of computational efficiency, for cases where no BCPs are found due to large interfragment distances, and with local partitioning schemes other than AIM which do not provide BCPs. It is applicable to both covalently and noncovalently bound systems. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

A new approach on seismic mortality estimations based on average population density

NASA Astrophysics Data System (ADS)

Zhu, Xiaoxin; Sun, Baiqing; Jin, Zhanyong

2016-12-01

This study examines a new methodology to predict the final seismic mortality from earthquakes in China. Most studies established the association between mortality estimation and seismic intensity without considering the population density. In China, however, the data are not always available, especially when it comes to the very urgent relief situation in the disaster. And the population density varies greatly from region to region. This motivates the development of empirical models that use historical death data to provide the path to analyze the death tolls for earthquakes. The present paper employs the average population density to predict the final death tolls in earthquakes using a case-based reasoning model from realistic perspective. To validate the forecasting results, historical data from 18 large-scale earthquakes occurred in China are used to estimate the seismic morality of each case. And a typical earthquake case occurred in the northwest of Sichuan Province is employed to demonstrate the estimation of final death toll. The strength of this paper is that it provides scientific methods with overall forecast errors lower than 20 %, and opens the door for conducting final death forecasts with a qualitative and quantitative approach. Limitations and future research are also analyzed and discussed in the conclusion.

Teaching nutrition to medical students: a community-based problem-solving approach.

PubMed

Bhattacharji, S; Joseph, A; Abraham, S; Muliyil, J; John, K R; Ethirajan, N

1990-01-01

This paper presents a community-based problem-solving educational programme which aims at teaching medical and other health science students the importance of nutrition and its application. Through community surveys students assess the nutritional status of children under five using different anthropometric methods. They understand the cultural beliefs and customs related to food fads and the reasons for them. They also acquire the skill to educate the community using the information gathered. They use epidemiological methods such as case control study to find associations between malnutrition and other causative factors. Feedback from students has been positive and evaluation of students' knowledge before and after the programme has shown significant improvement.

Conditional Outlier Detection for Clinical Alerting

PubMed Central

Hauskrecht, Milos; Valko, Michal; Batal, Iyad; Clermont, Gilles; Visweswaran, Shyam; Cooper, Gregory F.

2010-01-01

We develop and evaluate a data-driven approach for detecting unusual (anomalous) patient-management actions using past patient cases stored in an electronic health record (EHR) system. Our hypothesis is that patient-management actions that are unusual with respect to past patients may be due to a potential error and that it is worthwhile to raise an alert if such a condition is encountered. We evaluate this hypothesis using data obtained from the electronic health records of 4,486 post-cardiac surgical patients. We base the evaluation on the opinions of a panel of experts. The results support that anomaly-based alerting can have reasonably low false alert rates and that stronger anomalies are correlated with higher alert rates. PMID:21346986

Conditional outlier detection for clinical alerting.

PubMed

Hauskrecht, Milos; Valko, Michal; Batal, Iyad; Clermont, Gilles; Visweswaran, Shyam; Cooper, Gregory F

2010-11-13

We develop and evaluate a data-driven approach for detecting unusual (anomalous) patient-management actions using past patient cases stored in an electronic health record (EHR) system. Our hypothesis is that patient-management actions that are unusual with respect to past patients may be due to a potential error and that it is worthwhile to raise an alert if such a condition is encountered. We evaluate this hypothesis using data obtained from the electronic health records of 4,486 post-cardiac surgical patients. We base the evaluation on the opinions of a panel of experts. The results support that anomaly-based alerting can have reasonably low false alert rates and that stronger anomalies are correlated with higher alert rates.

A four-tier problem-solving scaffold to teach pain management in dental school.

PubMed

Ivanoff, Chris S; Hottel, Timothy L

2013-06-01

Pain constitutes a major reason patients pursue dental treatment. This article presents a novel curriculum to provide dental students comprehensive training in the management of pain. The curriculum's four-tier scaffold combines traditional and problem-based learning to improve students' diagnostic, pharmacotherapeutic, and assessment skills to optimize decision making when treating pain. Tier 1 provides underpinning knowledge of pain mechanisms with traditional and contextualized instruction by integrating clinical correlations and studying worked cases that stimulate clinical thinking. Tier 2 develops critical decision making skills through self-directed learning and actively solving problem-based cases. Tier 3 exposes students to management approaches taken in allied health fields and cultivates interdisciplinary communication skills. Tier 4 provides a "knowledge and experience synthesis" by rotating students through community pain clinics to practice their assessment skills. This combined teaching approach aims to increase critical thinking and problem-solving skills to assist dental graduates in better management of pain throughout their careers. Dental curricula that have moved to comprehensive care/private practice models are well-suited for this educational approach. The goal of this article is to encourage dental schools to integrate pain management into their curricula, to develop pain management curriculum resources for dental students, and to provide leadership for change in pain management education.

Renewable portfolio standards: still No good reasons

DOE Office of Scientific and Technical Information (OSTI.GOV)

Michaels, Robert J.

2008-10-15

The rebuttals by Christopher Cooper and Benjamin K. Sovacool to my article questioning the need for a national RPS leave their case as weak as ever. They provide no model that might help readers approach the foundational question: why should Congress enact this economically inefficient environmental policy when wide-ranging regulations, implementation plans, and emissions markets are in place, functioning reasonably well, and can be modified as new information arrives? (author)

An investigative framework to facilitate epidemiological thinking during herd problem-solving.

PubMed

More, Simon J; Doherty, Michael L; O'Grady, Luke

2017-01-01

Veterinary clinicians and students commonly use diagnostic approaches appropriate for individual cases when conducting herd problem-solving. However, these approaches can be problematic, in part because they make limited use of epidemiological principles and methods, which has clear application during the investigation of herd problems. In this paper, we provide an overview of diagnostic approaches that are used when investigating individual animal cases, and the challenges faced when these approaches are directly translated from the individual to the herd. Further, we propose an investigative framework to facilitate epidemiological thinking during herd problem-solving. A number of different approaches are used when making a diagnosis on an individual animal, including pattern recognition, hypothetico-deductive reasoning, and the key abnormality method. Methods commonly applied to individuals are often adapted for herd problem-solving: 'comparison with best practice' being a herd-level adaptation of pattern recognition, and 'differential diagnoses' a herd-level adaptation of hypothetico-deductive reasoning. These approaches can be effective, however, challenges can arise. Herds are complex; a collection of individual cows, but also additional layers relating to environment, management, feeding etc. It is unrealistic to expect seamless translation of diagnostic approaches from the individual to the herd. Comparison with best practice is time-consuming and prioritisation of actions can be problematic, whereas differential diagnoses can lead to 'pathogen hunting', particularly in complex cases. Epidemiology is the science of understanding disease in populations. The focus is on the population, underpinned by principles and utilising methods that seek to allow us to generate solid conclusions from apparently uncontrolled situations. In this paper, we argue for the inclusion of epidemiological principles and methods as an additional tool for herd problem-solving, and outline an investigative framework, with examples, to effectively incorporate these principles and methods with other diagnostic approaches during herd problem-solving. Relevant measures of performance are identified, and measures of case frequencies are calculated and compared across time, in space and among animal groupings, to identify patterns, clues and plausible hypotheses, consistent with potential biological processes. With this knowledge, the subsequent investigation (relevant on-farm activities, diagnostic testing and other examinations) can be focused, and actions prioritised (specifically, those actions that are likely to make the greatest difference in addressing the problem if enacted). In our experience, this investigative framework is an effective teaching tool, facilitating epidemiological thinking among students during herd problem-solving. It is a generic and robust process, suited to many herd-based problems.

Supervised machine learning algorithms to diagnose stress for vehicle drivers based on physiological sensor signals.

PubMed

Barua, Shaibal; Begum, Shahina; Ahmed, Mobyen Uddin

2015-01-01

Machine learning algorithms play an important role in computer science research. Recent advancement in sensor data collection in clinical sciences lead to a complex, heterogeneous data processing, and analysis for patient diagnosis and prognosis. Diagnosis and treatment of patients based on manual analysis of these sensor data are difficult and time consuming. Therefore, development of Knowledge-based systems to support clinicians in decision-making is important. However, it is necessary to perform experimental work to compare performances of different machine learning methods to help to select appropriate method for a specific characteristic of data sets. This paper compares classification performance of three popular machine learning methods i.e., case-based reasoning, neutral networks and support vector machine to diagnose stress of vehicle drivers using finger temperature and heart rate variability. The experimental results show that case-based reasoning outperforms other two methods in terms of classification accuracy. Case-based reasoning has achieved 80% and 86% accuracy to classify stress using finger temperature and heart rate variability. On contrary, both neural network and support vector machine have achieved less than 80% accuracy by using both physiological signals.

Clinical judgement in the era of big data and predictive analytics.

PubMed

Chin-Yee, Benjamin; Upshur, Ross

2018-06-01

Clinical judgement is a central and longstanding issue in the philosophy of medicine which has generated significant interest over the past few decades. In this article, we explore different approaches to clinical judgement articulated in the literature, focusing in particular on data-driven, mathematical approaches which we contrast with narrative, virtue-based approaches to clinical reasoning. We discuss the tension between these different clinical epistemologies and further explore the implications of big data and machine learning for a philosophy of clinical judgement. We argue for a pluralistic, integrative approach, and demonstrate how narrative, virtue-based clinical reasoning will remain indispensable in an era of big data and predictive analytics. © 2017 John Wiley & Sons, Ltd.

Understanding clinical reasoning in osteopathy: a qualitative research approach.

PubMed

Grace, Sandra; Orrock, Paul; Vaughan, Brett; Blaich, Raymond; Coutts, Rosanne

2016-01-01

Clinical reasoning has been described as a process that draws heavily on the knowledge, skills and attributes that are particular to each health profession. However, the clinical reasoning processes of practitioners of different disciplines demonstrate many similarities, including hypothesis generation and reflective practice. The aim of this study was to understand clinical reasoning in osteopathy from the perspective of osteopathic clinical educators and the extent to which it was similar or different from clinical reasoning in other health professions. This study was informed by constructivist grounded theory. Participants were clinical educators in osteopathic teaching institutions in Australia, New Zealand and the UK. Focus groups and written critical reflections provided a rich data set. Data were analysed using constant comparison to develop inductive categories. According to participants, clinical reasoning in osteopathy is different from clinical reasoning in other health professions. Osteopaths use a two-phase approach: an initial biomedical screen for serious pathology, followed by use of osteopathic reasoning models that are based on the relationship between structure and function in the human body. Clinical reasoning in osteopathy was also described as occurring in a number of contexts (e.g. patient, practitioner and community) and drawing on a range of metaskills (e.g. hypothesis generation and reflexivity) that have been described in other health professions. The use of diagnostic reasoning models that are based on the relationship between structure and function in the human body differentiated clinical reasoning in osteopathy. These models were not used to name a medical condition but rather to guide the selection of treatment approaches. If confirmed by further research that clinical reasoning in osteopathy is distinct from clinical reasoning in other health professions, then osteopaths may have a unique perspective to bring to multidisciplinary decision-making and potentially enhance the quality of patient care. Where commonalities exist in the clinical reasoning processes of osteopathy and other health professions, shared learning opportunities may be available, including the exchange of scaffolded clinical reasoning exercises and assessment practices among health disciplines.

Teaching clinical reasoning by making thinking visible: an action research project with allied health clinical educators.

PubMed

Delany, Clare; Golding, Clinton

2014-01-30

Clinical reasoning is fundamental to all forms of professional health practice, however it is also difficult to teach and learn because it is complex, tacit, and effectively invisible for students. In this paper we present an approach for teaching clinical reasoning based on making expert thinking visible and accessible to students. Twenty-one experienced allied health clinical educators from three tertiary Australian hospitals attended up to seven action research discussion sessions, where they developed a tentative heuristic of their own clinical reasoning, trialled it with students, evaluated if it helped their students to reason clinically, and then refined it so the heuristic was targeted to developing each student's reasoning skills. Data included participants' written descriptions of the thinking routines they developed and trialed with their students and the transcribed action research discussion sessions. Content analysis was used to summarise this data and categorise themes about teaching and learning clinical reasoning. Two overriding themes emerged from participants' reports about using the 'making thinking visible approach'. The first was a specific focus by participating educators on students' understanding of the reasoning process and the second was heightened awareness of personal teaching styles and approaches to teaching clinical reasoning. We suggest that the making thinking visible approach has potential to assist educators to become more reflective about their clinical reasoning teaching and acts as a scaffold to assist them to articulate their own expert reasoning and for students to access and use.

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

ERIC Educational Resources Information Center

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.…

Teaching clinical reasoning: case-based and coached.

PubMed

Kassirer, Jerome P

2010-07-01

Optimal medical care is critically dependent on clinicians' skills to make the right diagnosis and to recommend the most appropriate therapy, and acquiring such reasoning skills is a key requirement at every level of medical education. Teaching clinical reasoning is grounded in several fundamental principles of educational theory. Adult learning theory posits that learning is best accomplished by repeated, deliberate exposure to real cases, that case examples should be selected for their reflection of multiple aspects of clinical reasoning, and that the participation of a coach augments the value of an educational experience. The theory proposes that memory of clinical medicine and clinical reasoning strategies is enhanced when errors in information, judgment, and reasoning are immediately pointed out and discussed. Rather than using cases artificially constructed from memory, real cases are greatly preferred because they often reflect the false leads, the polymorphisms of actual clinical material, and the misleading test results encountered in everyday practice. These concepts foster the teaching and learning of the diagnostic process, the complex trade-offs between the benefits and risks of diagnostic tests and treatments, and cognitive errors in clinical reasoning. The teaching of clinical reasoning need not and should not be delayed until students gain a full understanding of anatomy and pathophysiology. Concepts such as hypothesis generation, pattern recognition, context formulation, diagnostic test interpretation, differential diagnosis, and diagnostic verification provide both the language and the methods of clinical problem solving. Expertise is attainable even though the precise mechanisms of achieving it are not known.

Identifying novel drug indications through automated reasoning.

PubMed

Tari, Luis; Vo, Nguyen; Liang, Shanshan; Patel, Jagruti; Baral, Chitta; Cai, James

2012-01-01

With the large amount of pharmacological and biological knowledge available in literature, finding novel drug indications for existing drugs using in silico approaches has become increasingly feasible. Typical literature-based approaches generate new hypotheses in the form of protein-protein interactions networks by means of linking concepts based on their cooccurrences within abstracts. However, this kind of approaches tends to generate too many hypotheses, and identifying new drug indications from large networks can be a time-consuming process. In this work, we developed a method that acquires the necessary facts from literature and knowledge bases, and identifies new drug indications through automated reasoning. This is achieved by encoding the molecular effects caused by drug-target interactions and links to various diseases and drug mechanism as domain knowledge in AnsProlog, a declarative language that is useful for automated reasoning, including reasoning with incomplete information. Unlike other literature-based approaches, our approach is more fine-grained, especially in identifying indirect relationships for drug indications. To evaluate the capability of our approach in inferring novel drug indications, we applied our method to 943 drugs from DrugBank and asked if any of these drugs have potential anti-cancer activities based on information on their targets and molecular interaction types alone. A total of 507 drugs were found to have the potential to be used for cancer treatments. Among the potential anti-cancer drugs, 67 out of 81 drugs (a recall of 82.7%) are indeed known cancer drugs. In addition, 144 out of 289 drugs (a recall of 49.8%) are non-cancer drugs that are currently tested in clinical trials for cancer treatments. These results suggest that our method is able to infer drug indications (original or alternative) based on their molecular targets and interactions alone and has the potential to discover novel drug indications for existing drugs.

Decision Tree based Prediction and Rule Induction for Groundwater Trichloroethene (TCE) Pollution Vulnerability

NASA Astrophysics Data System (ADS)

Park, J.; Yoo, K.

2013-12-01

For groundwater resource conservation, it is important to accurately assess groundwater pollution sensitivity or vulnerability. In this work, we attempted to use data mining approach to assess groundwater pollution vulnerability in a TCE (trichloroethylene) contaminated Korean industrial site. The conventional DRASTIC method failed to describe TCE sensitivity data with a poor correlation with hydrogeological properties. Among the different data mining methods such as Artificial Neural Network (ANN), Multiple Logistic Regression (MLR), Case Base Reasoning (CBR), and Decision Tree (DT), the accuracy and consistency of Decision Tree (DT) was the best. According to the following tree analyses with the optimal DT model, the failure of the conventional DRASTIC method in fitting with TCE sensitivity data may be due to the use of inaccurate weight values of hydrogeological parameters for the study site. These findings provide a proof of concept that DT based data mining approach can be used in predicting and rule induction of groundwater TCE sensitivity without pre-existing information on weights of hydrogeological properties.

StarPlan: A model-based diagnostic system for spacecraft

NASA Technical Reports Server (NTRS)

Heher, Dennis; Pownall, Paul

1990-01-01

The Sunnyvale Division of Ford Aerospace created a model-based reasoning capability for diagnosing faults in space systems. The approach employs reasoning about a model of the domain (as it is designed to operate) to explain differences between expected and actual telemetry; i.e., to identify the root cause of the discrepancy (at an appropriate level of detail) and determine necessary corrective action. A development environment, named Paragon, was implemented to support both model-building and reasoning. The major benefit of the model-based approach is the capability for the intelligent system to handle faults that were not anticipated by a human expert. The feasibility of this approach for diagnosing problems in a spacecraft was demonstrated in a prototype system, named StarPlan. Reasoning modules within StarPlan detect anomalous telemetry, establish goals for returning the telemetry to nominal values, and create a command plan for attaining the goals. Before commands are implemented, their effects are simulated to assure convergence toward the goal. After the commands are issued, the telemetry is monitored to assure that the plan is successful. These features of StarPlan, along with associated concerns, issues and future directions, are discussed.

34 CFR Appendix D to Part 682 - Policy for Waiving the Secretary's Right To Recover or Refuse To Pay Interest Benefits, Special...

Code of Federal Regulations, 2010 CFR

2010-07-01

... agency to do so, the Secretary will permit an agency to take either of the following approaches to its... documented, a case-by-case exercise of reasonable discretion allowing for guarantee coverage to be continued... repayment schedule or agreement.) In the case of a payment made by cash, money order, or other means that do...

An efficient multi-resolution GA approach to dental image alignment

NASA Astrophysics Data System (ADS)

Nassar, Diaa Eldin; Ogirala, Mythili; Adjeroh, Donald; Ammar, Hany

2006-02-01

Automating the process of postmortem identification of individuals using dental records is receiving an increased attention in forensic science, especially with the large volume of victims encountered in mass disasters. Dental radiograph alignment is a key step required for automating the dental identification process. In this paper, we address the problem of dental radiograph alignment using a Multi-Resolution Genetic Algorithm (MR-GA) approach. We use location and orientation information of edge points as features; we assume that affine transformations suffice to restore geometric discrepancies between two images of a tooth, we efficiently search the 6D space of affine parameters using GA progressively across multi-resolution image versions, and we use a Hausdorff distance measure to compute the similarity between a reference tooth and a query tooth subject to a possible alignment transform. Testing results based on 52 teeth-pair images suggest that our algorithm converges to reasonable solutions in more than 85% of the test cases, with most of the error in the remaining cases due to excessive misalignments.

Indicators that influence prospective mathematics teachers representational and reasoning abilities

NASA Astrophysics Data System (ADS)

Darta; Saputra, J.

2018-01-01

Representational and mathematical reasoning ability are very important ability as basic in mathematics learning process. The 2013 curriculum suggests that the use of a scientific approach emphasizes higher order thinking skills. Therefore, a scientific approach is required in mathematics learning to improve ability of representation and mathematical reasoning. The objectives of this research are: (1) to analyze representational and reasoning abilities, (2) to analyze indicators affecting the ability of representation and mathematical reasoning, (3) to analyze scientific approaches that can improve the ability of representation and mathematical reasoning. The subject of this research is the students of mathematics prospective teachers in the first semester at Private Higher Education of Bandung City. The research method of this research was descriptive analysis. The research data were collected using reasoning and representation tests on sixty-one students. Data processing was done by descriptive analysis specified based on the indicators of representation ability and mathematical reasoning that influenced it. The results of this first-year study showed that students still had many weaknesses in reasoning and mathematical representation that were influenced by the ability to understand the indicators of both capabilities. After observing the results of the first-year research, then in the second and third year, the development of teaching materials with a scientific approach in accordance with the needs of prospective students was planned.

38 CFR 36.4279 - Extensions and reamortizations.

Code of Federal Regulations, 2010 CFR

2010-07-01

.... (a) Provided the debtor(s) is (are) a reasonable credit risk(s), as determined by the holder based... debtor(s), be extended in the event of default, to avoid imminent default, or in any other case where the...) is (are) a reasonable credit risk(s), as determined by the holder based upon review of the debtor's...

[Metabolic acidosis].

PubMed

Regolisti, Giuseppe; Fani, Filippo; Antoniotti, Riccardo; Castellano, Giuseppe; Cremaschi, Elena; Greco, Paolo; Parenti, Elisabetta; Morabito, Santo; Sabatino, Alice; Fiaccadori, Enrico

2016-01-01

Metabolic acidosis is frequently observed in clinical practice, especially among critically ill patients and/or in the course of renal failure. Complex mechanisms are involved, in most cases identifiable by medical history, pathophysiology-based diagnostic reasoning and measure of some key acid-base parameters that are easily available or calculable. On this basis the bedside differential diagnosis of metabolic acidosis should be started from the identification of the two main subtypes of metabolic acidosis: the high anion gap metabolic acidosis and the normal anion gap (or hyperchloremic) metabolic acidosis. Metabolic acidosis, especially in its acute forms with elevated anion gap such as is the case of lactic acidosis, diabetic and acute intoxications, may significantly affect metabolic body homeostasis and patients hemodynamic status, setting the stage for true medical emergencies. The therapeutic approach should be first aimed at early correction of concurrent clinical problems (e.g. fluids and hemodynamic optimization in case of shock, mechanical ventilation in case of concomitant respiratory failure, hemodialysis for acute intoxications etc.), in parallel to the formulation of a diagnosis. In case of severe acidosis, the administration of alkalizing agents should be carefully evaluated, taking into account the risk of side effects, as well as the potential need of renal replacement therapy.

Case-Based Multi-Sensor Intrusion Detection

NASA Astrophysics Data System (ADS)

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.

Knowledge acquisition and representation using fuzzy evidential reasoning and dynamic adaptive fuzzy Petri nets.

PubMed

Liu, Hu-Chen; Liu, Long; Lin, Qing-Lian; Liu, Nan

2013-06-01

The two most important issues of expert systems are the acquisition of domain experts' professional knowledge and the representation and reasoning of the knowledge rules that have been identified. First, during expert knowledge acquisition processes, the domain expert panel often demonstrates different experience and knowledge from one another and produces different types of knowledge information such as complete and incomplete, precise and imprecise, and known and unknown because of its cross-functional and multidisciplinary nature. Second, as a promising tool for knowledge representation and reasoning, fuzzy Petri nets (FPNs) still suffer a couple of deficiencies. The parameters in current FPN models could not accurately represent the increasingly complex knowledge-based systems, and the rules in most existing knowledge inference frameworks could not be dynamically adjustable according to propositions' variation as human cognition and thinking. In this paper, we present a knowledge acquisition and representation approach using the fuzzy evidential reasoning approach and dynamic adaptive FPNs to solve the problems mentioned above. As is illustrated by the numerical example, the proposed approach can well capture experts' diversity experience, enhance the knowledge representation power, and reason the rule-based knowledge more intelligently.

A novel anisotropic inversion approach for magnetotelluric data from subsurfaces with orthogonal geoelectric strike directions

NASA Astrophysics Data System (ADS)

Schmoldt, Jan-Philipp; Jones, Alan G.

2013-12-01

The key result of this study is the development of a novel inversion approach for cases of orthogonal, or close to orthogonal, geoelectric strike directions at different depth ranges, for example, crustal and mantle depths. Oblique geoelectric strike directions are a well-known issue in commonly employed isotropic 2-D inversion of MT data. Whereas recovery of upper (crustal) structures can, in most cases, be achieved in a straightforward manner, deriving lower (mantle) structures is more challenging with isotropic 2-D inversion in the case of an overlying region (crust) with different geoelectric strike direction. Thus, investigators may resort to computationally expensive and more limited 3-D inversion in order to derive the electric resistivity distribution at mantle depths. In the novel approaches presented in this paper, electric anisotropy is used to image 2-D structures in one depth range, whereas the other region is modelled with an isotropic 1-D or 2-D approach, as a result significantly reducing computational costs of the inversion in comparison with 3-D inversion. The 1- and 2-D versions of the novel approach were tested using a synthetic 3-D subsurface model with orthogonal strike directions at crust and mantle depths and their performance was compared to results of isotropic 2-D inversion. Structures at crustal depths were reasonably well recovered by all inversion approaches, whereas recovery of mantle structures varied significantly between the different approaches. Isotropic 2-D inversion models, despite decomposition of the electric impedance tensor and using a wide range of inversion parameters, exhibited severe artefacts thereby confirming the requirement of either an enhanced or a higher dimensionality inversion approach. With the anisotropic 1-D inversion approach, mantle structures of the synthetic model were recovered reasonably well with anisotropy values parallel to the mantle strike direction (in this study anisotropy was assigned to the mantle region), indicating applicability of the novel approach for basic subsurface cases. For the more complex subsurface cases, however, the anisotropic 1-D inversion approach is likely to yield implausible models of the electric resistivity distribution due to inapplicability of the 1-D approximation. Owing to the higher number of degrees of freedom, the anisotropic 2-D inversion approach can cope with more complex subsurface cases and is the recommended tool for real data sets recorded in regions with orthogonal geoelectric strike directions.

Valuing the benefits of creek rehabilitation: building a business case for public investments in urban green infrastructure.

PubMed

Mekala, Gayathri Devi; Jones, Roger N; MacDonald, Darla Hatton

2015-06-01

In an effort to increase the livability of its cities, public agencies in Australia are investing in green infrastructure to improve public health, reduce heat island effects and transition toward water sensitive urban design. In this paper, we present a simple and replicable approach to building a business case for green infrastructure. This approach requires much less time and resources compared to other methods for estimating the social and economic returns to society from such investments. It is a pragmatic, reasonably comprehensive approach that includes socio-demographic profile of potential users and catchment analysis to assess the economic value of community benefits of the investment. The approach has been applied to a case study area in the City of Brimbank, a western suburb of Greater Melbourne. We find that subject to a set of assumptions, a reasonable business case can be made. We estimate potential public benefits of avoided health costs of about AU$75,049 per annum and potential private benefits of AU$3.9 million. The project area is one of the most poorly serviced areas in the municipality in terms of quality open spaces and the potential beneficiaries are from relatively low income households with less than average health status and education levels. The values of cultural (recreational benefits, avoided health costs, and increased property values) and regulating (reduction in heat island effect and carbon sequestration) ecosystem services were quantified that can potentially offset annual maintenance costs.

Valuing the Benefits of Creek Rehabilitation: Building a Business Case for Public Investments in Urban Green Infrastructure

NASA Astrophysics Data System (ADS)

Mekala, Gayathri Devi; Jones, Roger N.; MacDonald, Darla Hatton

2015-06-01

In an effort to increase the livability of its cities, public agencies in Australia are investing in green infrastructure to improve public health, reduce heat island effects and transition toward water sensitive urban design. In this paper, we present a simple and replicable approach to building a business case for green infrastructure. This approach requires much less time and resources compared to other methods for estimating the social and economic returns to society from such investments. It is a pragmatic, reasonably comprehensive approach that includes socio-demographic profile of potential users and catchment analysis to assess the economic value of community benefits of the investment. The approach has been applied to a case study area in the City of Brimbank, a western suburb of Greater Melbourne. We find that subject to a set of assumptions, a reasonable business case can be made. We estimate potential public benefits of avoided health costs of about AU75,049 per annum and potential private benefits of AU3.9 million. The project area is one of the most poorly serviced areas in the municipality in terms of quality open spaces and the potential beneficiaries are from relatively low income households with less than average health status and education levels. The values of cultural (recreational benefits, avoided health costs, and increased property values) and regulating (reduction in heat island effect and carbon sequestration) ecosystem services were quantified that can potentially offset annual maintenance costs.

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

PubMed

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.

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

PubMed Central

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. Images Figure 3 PMID:9929335

Creation and pilot testing of cases for case-based learning: A pedagogical approach for pathology cancer diagnosis.

PubMed

Sayed, Shahin; Lester, Susan C; Wilson, Michael; Berney, Daniel; Masia, Ricard; Moloo, Zahir; Stall, Jennifer; Eslan, Alexia; Ayers, Stephanie; Mutuku, Angela; Guarner, Jeannette

2017-01-01

Case-based learning (CBL) is an established pedagogical active learning method used in various disciplines and defined based on the field of study and type of case. The utility of CBL for teaching specific aspects of cancer diagnosis to practising pathologists has not been previously studied in sub-Saharan Africa. We aimed to pilot test standardised cancer cases on a group of practising pathologists in sub-Saharan Africa to evaluate case content, clarity of questions and delivery of content. Expert faculty created cases for the four most commonly diagnosed cancers. The format included mini-cases and bullet cases which were all open-ended. The questions dealt with interpretation of clinical information, gross specimen examination, morphologic characteristics of tumours, ancillary testing, reporting and appropriate communication to clinicians. Cases on breast, cervical, prostate and colorectal cancers were tested on seven practising pathologists. Each case took an average of 45-90 min to complete.Questions that were particularly challenging to testers were on: Specimens they should have been but for some reason were not exposed to in routine practice.Ancillary testing and appropriate tumour staging.New knowledge gained included tumour grading and assessment of radial margins. Revisions to cases were made based on testers' feedback, which included rewording of questions to reduce ambiguity and adding of tables to clarify concepts. Cases were created for CBL in Kenya, but these are applicable elsewhere in Africa and beyond to teach cancer diagnosis. The pilot testing of cases prepared faculty for the actual CBL course and feedback provided by the testers assisted in improving the questions and impact on day-to-day practice.

Creation and pilot testing of cases for case-based learning: A pedagogical approach for pathology cancer diagnosis

PubMed Central

Wilson, Michael; Masia, Ricard; Moloo, Zahir; Stall, Jennifer; Eslan, Alexia; Ayers, Stephanie; Mutuku, Angela

2017-01-01

Background Case-based learning (CBL) is an established pedagogical active learning method used in various disciplines and defined based on the field of study and type of case. The utility of CBL for teaching specific aspects of cancer diagnosis to practising pathologists has not been previously studied in sub-Saharan Africa. Objectives We aimed to pilot test standardised cancer cases on a group of practising pathologists in sub-Saharan Africa to evaluate case content, clarity of questions and delivery of content. Methods Expert faculty created cases for the four most commonly diagnosed cancers. The format included mini-cases and bullet cases which were all open-ended. The questions dealt with interpretation of clinical information, gross specimen examination, morphologic characteristics of tumours, ancillary testing, reporting and appropriate communication to clinicians. Results Cases on breast, cervical, prostate and colorectal cancers were tested on seven practising pathologists. Each case took an average of 45–90 min to complete. Questions that were particularly challenging to testers were on: Specimens they should have been but for some reason were not exposed to in routine practice.Ancillary testing and appropriate tumour staging. New knowledge gained included tumour grading and assessment of radial margins. Revisions to cases were made based on testers’ feedback, which included rewording of questions to reduce ambiguity and adding of tables to clarify concepts. Conclusion Cases were created for CBL in Kenya, but these are applicable elsewhere in Africa and beyond to teach cancer diagnosis. The pilot testing of cases prepared faculty for the actual CBL course and feedback provided by the testers assisted in improving the questions and impact on day-to-day practice. PMID:29147646

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

PubMed

Bateman, James; Allen, Maggie E; Kidd, Jane; Parsons, Nick; Davies, David

2012-08-01

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). This is a multi-centre randomised 2 x 2 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 both primary outcomes. This trial will provide robust evidence to support the effectiveness of different designs of virtual patients, based on student performance and evaluation. The cases and all learning materials will be open access and available on a Creative Commons Attribution-Share-Alike license.

Benefit-based tree valuation

Treesearch

E.G. McPherson

2007-01-01

Benefit-based tree valuation provides alternative estimates of the fair and reasonable value of trees while illustrating the relative contribution of different benefit types. This study compared estimates of tree value obtained using cost- and benefit-based approaches. The cost-based approach used the Council of Landscape and Tree Appraisers trunk formula method, and...

A Rawlsian approach to distribute responsibilities in networks.

PubMed

Doorn, Neelke

2010-06-01

Due to their non-hierarchical structure, socio-technical networks are prone to the occurrence of the problem of many hands. In the present paper an approach is introduced in which people's opinions on responsibility are empirically traced. The approach is based on the Rawlsian concept of Wide Reflective Equilibrium (WRE) in which people's considered judgments on a case are reflectively weighed against moral principles and background theories, ideally leading to a state of equilibrium. Application of the method to a hypothetical case with an artificially constructed network showed that it is possible to uncover the relevant data to assess a consensus amongst people in terms of their individual WRE. It appeared that the moral background theories people endorse are not predictive for their actual distribution of responsibilities but that they indicate ways of reasoning and justifying outcomes. Two ways of ascribing responsibilities were discerned, corresponding to two requirements of a desirable responsibility distribution: fairness and completeness. Applying the method triggered learning effects, both with regard to conceptual clarification and moral considerations, and in the sense that it led to some convergence of opinions. It is recommended to apply the method to a real engineering case in order to see whether this approach leads to an overlapping consensus on a responsibility distribution which is justifiable to all and in which no responsibilities are left unfulfilled, therewith trying to contribute to the solution of the problem of many hands.

Ethics consultation on demand: concepts, practical experiences and a case study.

PubMed

Reiter-Theil, S

2000-06-01

Despite the increasing interest in clinical ethics, ethics consultation as a professional service is still rare in Europe. In this paper I refer to examples in the United States. In Germany, university hospitals and medical faculties are still hesitant about establishing yet another "committee". One of the reasons for this hesitation lies in the ignorance that exists here about how to provide medical ethics services; another reason is that medical ethics itself is not yet institutionalised at many German universities. The most important obstacle, however, may be that medical ethics has not yet demonstrated its relevance to the needs of those caring for patients. The Centre for Ethics and Law, Freiburg, has therefore taken a different approach from that offered elsewhere: clinical ethics consultation is offered on demand, the consultation being available to clinician(s) in different forms. This paper describes our experiences with this approach; practical issues are illustrated by a case study.

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

PubMed

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.

Emotional reasoning and parent-based reasoning in normal children.

PubMed

Morren, Mattijn; Muris, Peter; Kindt, Merel

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 anxiety-response. The present study further examined emotional reasoning in children aged 7-13 years (N = 508). In addition, it was investigated whether children also show parent-based reasoning, which can be defined as the tendency to rely on anxiety-responses that can be observed in parents. Children completed self-report questionnaires of anxiety, depression, and emotional and parent-based reasoning. Evidence was found for both emotional and parent-based reasoning effects. More specifically, children's danger ratings were not only affected by objective danger information, but also by anxiety-response information in both objective danger and safety stories. High levels of anxiety and depression were significantly associated with the tendency to rely on anxiety-response information, but only in the case of safety scripts.

The Development of Dalton's Atomic Theory as a Case Study in the History of Science: Reflections for Educators in Chemistry

NASA Astrophysics Data System (ADS)

Viana, Hélio Elael Bonini; Porto, Paulo Alves

2010-01-01

The inclusion of the history of science in science curricula—and specially, in the curricula of science teachers—is a trend that has been followed in several countries. The reasons advanced for the study of the history of science are manifold. This paper presents a case study in the history of chemistry, on the early developments of John Dalton’s atomic theory. Based on the case study, several questions that are worth discussing in educational contexts are pointed out. It is argued that the kind of history of science that was made in the first decades of the twentieth century (encyclopaedic, continuist, essentially anachronistic) is not appropriate for the development of the competences that are expected from the students of sciences in the present. Science teaching for current days will benefit from the approach that may be termed the “new historiography of science”.

The Hidden Reason Behind Children's Misbehavior.

ERIC Educational Resources Information Center

Nystul, Michael S.

1986-01-01

Discusses hidden reason theory based on the assumptions that: (1) the nature of people is positive; (2) a child's most basic psychological need is involvement; and (3) a child has four possible choices in life (good somebody, good nobody, bad somebody, or severely mentally ill.) A three step approach for implementing hidden reason theory is…

Comparison of ethical judgments exhibited by clients and ethics consultants in Japan

PubMed Central

2014-01-01

Background Healthcare professionals must make decisions for patients based on ethical considerations. However, they rely on clinical ethics consultations (CEC) to review ethical justifications of their decisions. CEC consultants support the cases reviewed and guide medical care. When both healthcare professionals and CEC consultants face ethical problems in medical care, how is their judgment derived? How do medical judgments differ from the ethical considerations of CECs? This study examines CECs in Japan to identify differences in the ethical judgment of clients and CEC consultants. Methods The CEC request and response documents of all 60 cases reviewed across Japan between October 2006 and the end of October 2011 were classified in terms of the presence of decisional capacity in the patient. We conducted a qualitative content analysis of the differences in reasoning between client and CEC consultants. Reasoned judgments were verified in individual cases to classify the similarities or differences of opinion between CEC clients and teams. Results As the result of classification of the decisional capacity and the difference of opinion regarding medical care, the most frequent category was 25 cases (41.7%) of “uncertain decisional capacity,” and 23 cases (38.3%) of “withholding of decision-making.” A chi-square analysis was performed on presence of decisional capacity and agreement in decision-making, yielding a statistically significant difference (p < 0.05). The CEC consultants’ reasoning was based on “patient’s preference was ambiguous,” “validity of family as a surrogate,” “estimation of patient preference,” and “patient’s best interest,” whereas the CEC client’s reasoning was based on “consistent family preference was shown/not shown” and “appropriate therapeutic methods to manage patient safety.” Conclusion Differences in opinions were found in cases classified according to decisional capacity. Furthermore, the reasoning behind judgments differed between CEC clients and CEC consultants. The reasoning of CEC consultants was critical and reflective, while for clients it was situational and pragmatic. PMID:24592932

Patterns of informal reasoning in the context of socioscientific decision making

NASA Astrophysics Data System (ADS)

Sadler, Troy D.; Zeidler, Dana L.

2005-01-01

The purpose of this study is to contribute to a theoretical knowledge base through research by examining factors salient to science education reform and practice in the context of socioscientific issues. The study explores how individuals negotiate and resolve genetic engineering dilemmas. A qualitative approach was used to examine patterns of informal reasoning and the role of morality in these processes. Thirty college students participated individually in two semistructured interviews designed to explore their informal reasoning in response to six genetic engineering scenarios. Students demonstrated evidence of rationalistic, emotive, and intuitive forms of informal reasoning. Rationalistic informal reasoning described reason-based considerations; emotive informal reasoning described care-based considerations; and intuitive reasoning described considerations based on immediate reactions to the context of a scenario. Participants frequently relied on combinations of these reasoning patterns as they worked to resolve individual socioscientific scenarios. Most of the participants appreciated at least some of the moral implications of their decisions, and these considerations were typically interwoven within an overall pattern of informal reasoning. These results highlight the need to ensure that science classrooms are environments in which intuition and emotion in addition to reason are valued. Implications and recommendations for future research are discussed.

Generic Reflective Feedback: An Effective Approach to Developing Clinical Reasoning Skills

ERIC Educational Resources Information Center

Wojcikowski, K.; Brownie, S.

2013-01-01

Problem-based learning can be an effective tool to develop clinical reasoning skills. However, it traditionally takes place in tutorial groups, giving students little flexibility in how and when they learn. This pilot study compared the effectiveness of generic reflective feedback (GRF) with tutorial-based reflective feedback on the development of…

Improving Moral Reasoning among College Students: A Game-Based Learning Approach

ERIC Educational Resources Information Center

Huang, Wenyeh; Ho, Jonathan C.

2018-01-01

Considering a company's limited time and resources, an effective training method that improves employees' ability to make ethical decision is needed. Based on social cognitive theory, this study proposes that employing games in an ethics training program can help improve moral reasoning through actively engaging learners. The experimental design…

SSME fault monitoring and diagnosis expert system

NASA Technical Reports Server (NTRS)

Ali, Moonis; Norman, Arnold M.; Gupta, U. K.

1989-01-01

An expert system, called LEADER, has been designed and implemented for automatic learning, detection, identification, verification, and correction of anomalous propulsion system operations in real time. LEADER employs a set of sensors to monitor engine component performance and to detect, identify, and validate abnormalities with respect to varying engine dynamics and behavior. Two diagnostic approaches are adopted in the architecture of LEADER. In the first approach fault diagnosis is performed through learning and identifying engine behavior patterns. LEADER, utilizing this approach, generates few hypotheses about the possible abnormalities. These hypotheses are then validated based on the SSME design and functional knowledge. The second approach directs the processing of engine sensory data and performs reasoning based on the SSME design, functional knowledge, and the deep-level knowledge, i.e., the first principles (physics and mechanics) of SSME subsystems and components. This paper describes LEADER's architecture which integrates a design based reasoning approach with neural network-based fault pattern matching techniques. The fault diagnosis results obtained through the analyses of SSME ground test data are presented and discussed.

Inductive reasoning 2.0.

PubMed

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.

Physical examination of the respiratory system.

PubMed

Sharp, Claire R; Rozanski, Elizabeth A

2013-08-01

This article reviews the approach to a patient with respiratory distress, with a focus on clues obtained from the physical examination. Respiratory distress is a common reason for presentation of a companion animal to a veterinarian on an emergency basis, and thus the clinician should have a comfort level with the approach to these patients. Our discussion includes a basic review of respiratory pathophysiology and the differential diagnoses for hypoxemia. In the majority of cases, physical examination should allow localization of the cause of the respiratory problem to the upper airways, lower airways, pleural space, or pulmonary parenchyma. Such localization, coupled with signalment and historical clues, guides additional diagnostics and therapeutics based on the most likely differential diagnoses. Although managing a patient with respiratory distress can be challenging, a systematic approach such as the one presented here should ensure appropriate intervention in a timely fashion and maximize the chance of a good outcome. © 2013 Published by Elsevier Inc.

Designing for emotion (among other things)

PubMed Central

Gaver, William

2009-01-01

Using computational approaches to emotion in design appears problematic for a range of technical, cultural and aesthetic reasons. After introducing some of the reasons as to why I am sceptical of such approaches, I describe a prototype we built that tried to address some of these problems, using sensor-based inferencing to comment upon domestic ‘well-being’ in ways that encouraged users to take authority over the emotional judgements offered by the system. Unfortunately, over two iterations we concluded that the prototype we built was a failure. I discuss the possible reasons for this and conclude that many of the problems we found are relevant more generally for designs based on computational approaches to emotion. As an alternative, I advocate a broader view of interaction design in which open-ended designs serve as resources for individual appropriation, and suggest that emotional experiences become one of several outcomes of engaging with them. PMID:19884154

Case-Based Plan Recognition Using Action Sequence Graphs

DTIC Science & Technology

2014-10-01

resized as necessary. Similarly, trace- based reasoning (Zarka et al., 2013) and episode -based reasoning (Sánchez-Marré, 2005) store fixed-length...is a goal state of Π, where satisfies has the same semantics as originally laid out in Ghallab, Nau & Traverso (2004). Action 0 is ...Although there are syntactic similarities between planning encoding graphs and action sequence graphs, important semantic differences exist because the

Evaluation of a threshold-based model of fatigue in gamma titanium aluminide following impact damage

NASA Astrophysics Data System (ADS)

Harding, Trevor Scott

2000-10-01

Recent interest in gamma titanium aluminide (gamma-TiAl) for use in gas turbine engine applications has centered on the low density and good elevated temperature strength retention of gamma-TiAl compared to current materials. However, the relatively low ductility and fracture toughness of gamma-TiAl leads to serious concerns regarding its ability to resist impact damage. Furthermore, the limited fatigue crack growth resistance of gamma-TiAl means that the potential for fatigue failures resulting from impact damage is real if a damage tolerant design approach is used. A threshold-based design approach may be required if fatigue crack growth from potential impact sites is to be avoided. The objective of the present research is to examine the feasibility of a threshold-based approach for the design of a gamma-TiAl low-pressure turbine blade subjected to both assembly-related impact damage and foreign object damage. Specimens of three different gamma-TiAl alloys were damaged in such a way as to simulate anticipated impact damage for a turbine blade. Step-loading fatigue tests were conducted at both room temperature and 600°C. In terms of the assembly-related impact damage, the results indicate that there is reasonably good agreement between the threshold-based predictions of the fatigue strength of damaged specimens and the measured data. However, some discrepancies do exist. In the case of very lightly damaged specimens, prediction of the resulting fatigue strength requires that a very conservative small-crack fatigue threshold be used. Consequently, the allowable design conditions are significantly reduced. For severely damaged specimens, an analytical approach found that the potential effects of residual stresses may be related to the discrepancies observed between the threshold-based model and measured fatigue strength data. In the case of foreign object damage, a good correlation was observed between impacts resulting in large cracks and a long-crack threshold-based approximation of the fatigue strength. However, in the case of smaller impact sites, a lower small-crack threshold appears to be more appropriate. In some cases, a complete perforation of the material, or blowout, would result from the impact. Prediction of the reduction in fatigue strength resulting from this form of damage required the use of a stress concentration factor, rather than a threshold-based prediction.

Modular expert system for the diagnosis of operating conditions of industrial anaerobic digestion plants.

PubMed

Lardon, L; Puñal, A; Martinez, J A; Steyer, J P

2005-01-01

Anaerobic digestion (AD) plants are highly efficient wastewater treatment processes with possible energetic valorisation. Despite these advantages, many industries are still reluctant to use them because of their instability in the face of changes in operating conditions. To the face this drawback and to enhance the industrial use of anaerobic digestion, one solution is to develop and to implement knowledge base (KB) systems that are able to detect and to assess in real-time the quality of operating conditions of the processes. Case-based techniques and heuristic approaches have been already tested and validated on AD processes but two major properties were lacking: modularity of the system (the knowledge base system should be easily tuned on a new process and should still work if one or more sensors are added or removed) and uncertainty management (the assessment of the KB system should remain relevant even in the case of too poor or conflicting information sources). This paper addresses these two points and presents a modular KB system where an uncertain reasoning formalism is used to combine partial and complementary fuzzy diagnosis modules. Demonstration of the interest of the approach is provided from real-life experiments performed on an industrial 2,000 m3 CSTR anaerobic digester.

An assessment of environmental and toxicological risk to pesticide exposure based on a case-based approach to computing

NASA Astrophysics Data System (ADS)

Coelho, Cristina; Vicente, Henrique; Rosário Martins, M.; Lima, Nelson; Neves, Mariana; Neves, José

2017-01-01

Pesticide environmental fate and toxicity depends on its physical and chemical features, the soil composition, soil adsorption, as well as residues that may be found in different soil slots. Indeed, pesticide degradation in soil may be influenced by either biotic or abiotic factors. In addition, the toxicity of pesticides for living organisms depends on their adsorption, distribution, biotransformation, dissemination of metabolites together with interaction with cellular macromolecules and excretion. Biotransformation may result in the formation of less toxic and/or more toxic metabolites, while other processes determine the balance between toxic and a nontoxic upcoming. Aggregate exposure and risk assessment involve multiple pathways and routes, including the potential for pesticide residues in food and drinking water, in addition to residues from pesticide use in residential and non-occupational environments. Therefore, this work will focus on the development of a decision support system to assess the environmental and toxicological risk to pesticide exposure, built on top of a Logic Programming approach to Knowledge Representation and Reasoning, complemented with a Case Based attitude to computing. The proposed solution is unique in itself, once it caters for the explicit treatment of incomplete, unknown, or even self-contradictory information, either in terms of a qualitative or quantitative setting.

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

PubMed

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.

The case of value-based healthcare for people living with complex long-term conditions.

PubMed

Elf, Marie; Flink, Maria; Nilsson, Marie; Tistad, Malin; von Koch, Lena; Ytterberg, Charlotte

2017-01-11

There is a trend towards value-based health service, striving to cut costs while generating value for the patient. The overall objective comprises higher-quality health services and improved patient safety and cost efficiency. The approach could align with patient-centred care, as it entails a focus on the patient's experience of her or his entire cycle of care, including the use of well-defined outcome measurements. Challenges arise when the approach is applied to health services for people living with long-term complex conditions that require support from various healthcare services. The aim of this work is to critically discuss the value-based approach and its implications for patients with long-term complex conditions. Two cases from clinical practice and research form the foundation for our reasoning, illustrating several challenges regarding value-based health services for people living with long-term complex conditions. Achieving value-based health services that provide the health outcomes that matter to patients and providing greater patient-centredness will place increased demands on the healthcare system. Patients and their informal caregivers must be included in the development and establishment of outcome measures. The outcome measures must be standardized to allow evaluation of specific conditions at an aggregated level, but they must also be sensitive enough to capture each patient's individual needs and goals. Healthcare systems that strive to establish value-based services must collaborate beyond the organizational boundaries to create clear patient trajectories in order to avoid fragmentation. The shift towards value-based health services has the potential to align healthcare-service delivery with patient-centred care if serious efforts to take the patient's perspective into account are made. This is especially challenging in fragmented healthcare systems and for patients with long-term- and multi-setting-care needs.

Innovative Product Design Based on Comprehensive Customer Requirements of Different Cognitive Levels

PubMed Central

Zhao, Wu; Zheng, Yake; Wang, Rui; Wang, Chen

2014-01-01

To improve customer satisfaction in innovative product design, a topology structure of customer requirements is established and an innovative product approach is proposed. The topology structure provides designers with reasonable guidance to capture the customer requirements comprehensively. With the aid of analytic hierarchy process (AHP), the importance of the customer requirements is evaluated. Quality function deployment (QFD) is used to translate customer requirements into product and process design demands and pick out the technical requirements which need urgent improvement. In this way, the product is developed in a more targeted way to satisfy the customers. the theory of innovative problems solving (TRIZ) is used to help designers to produce innovative solutions. Finally, a case study of automobile steering system is used to illustrate the application of the proposed approach. PMID:25013862

Innovative product design based on comprehensive customer requirements of different cognitive levels.

PubMed

Li, Xiaolong; Zhao, Wu; Zheng, Yake; Wang, Rui; Wang, Chen

2014-01-01

To improve customer satisfaction in innovative product design, a topology structure of customer requirements is established and an innovative product approach is proposed. The topology structure provides designers with reasonable guidance to capture the customer requirements comprehensively. With the aid of analytic hierarchy process (AHP), the importance of the customer requirements is evaluated. Quality function deployment (QFD) is used to translate customer requirements into product and process design demands and pick out the technical requirements which need urgent improvement. In this way, the product is developed in a more targeted way to satisfy the customers. the theory of innovative problems solving (TRIZ) is used to help designers to produce innovative solutions. Finally, a case study of automobile steering system is used to illustrate the application of the proposed approach.

An ontological case base engineering methodology for diabetes management.

PubMed

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.

Defining the Correctness of a Diagnosis: Differential Judgments and Expert Knowledge

ERIC Educational Resources Information Center

Kanter, Steven L.; Brosenitsch, Teresa A.; Mahoney, John F.; Staszewski, James

2010-01-01

Approaches that use a simulated patient case to study and assess diagnostic reasoning usually use the correct diagnosis of the case as a measure of success and as an anchor for other measures. Commonly, the correctness of a diagnosis is determined by the judgment of one or more experts. In this study, the consistency of experts' judgments of the…

Evaluating model accuracy for model-based reasoning

NASA Technical Reports Server (NTRS)

Chien, Steve; Roden, Joseph

1992-01-01

Described here is an approach to automatically assessing the accuracy of various components of a model. In this approach, actual data from the operation of a target system is used to drive statistical measures to evaluate the prediction accuracy of various portions of the model. We describe how these statistical measures of model accuracy can be used in model-based reasoning for monitoring and design. We then describe the application of these techniques to the monitoring and design of the water recovery system of the Environmental Control and Life Support System (ECLSS) of Space Station Freedom.

SEE: structured representation of scientific evidence in the biomedical domain using Semantic Web techniques

PubMed Central

2014-01-01

Background Accounts of evidence are vital to evaluate and reproduce scientific findings and integrate data on an informed basis. Currently, such accounts are often inadequate, unstandardized and inaccessible for computational knowledge engineering even though computational technologies, among them those of the semantic web, are ever more employed to represent, disseminate and integrate biomedical data and knowledge. Results We present SEE (Semantic EvidencE), an RDF/OWL based approach for detailed representation of evidence in terms of the argumentative structure of the supporting background for claims even in complex settings. We derive design principles and identify minimal components for the representation of evidence. We specify the Reasoning and Discourse Ontology (RDO), an OWL representation of the model of scientific claims, their subjects, their provenance and their argumentative relations underlying the SEE approach. We demonstrate the application of SEE and illustrate its design patterns in a case study by providing an expressive account of the evidence for certain claims regarding the isolation of the enzyme glutamine synthetase. Conclusions SEE is suited to provide coherent and computationally accessible representations of evidence-related information such as the materials, methods, assumptions, reasoning and information sources used to establish a scientific finding by adopting a consistently claim-based perspective on scientific results and their evidence. SEE allows for extensible evidence representations, in which the level of detail can be adjusted and which can be extended as needed. It supports representation of arbitrary many consecutive layers of interpretation and attribution and different evaluations of the same data. SEE and its underlying model could be a valuable component in a variety of use cases that require careful representation or examination of evidence for data presented on the semantic web or in other formats. PMID:25093070

SEE: structured representation of scientific evidence in the biomedical domain using Semantic Web techniques.

PubMed

Bölling, Christian; Weidlich, Michael; Holzhütter, Hermann-Georg

2014-01-01

Accounts of evidence are vital to evaluate and reproduce scientific findings and integrate data on an informed basis. Currently, such accounts are often inadequate, unstandardized and inaccessible for computational knowledge engineering even though computational technologies, among them those of the semantic web, are ever more employed to represent, disseminate and integrate biomedical data and knowledge. We present SEE (Semantic EvidencE), an RDF/OWL based approach for detailed representation of evidence in terms of the argumentative structure of the supporting background for claims even in complex settings. We derive design principles and identify minimal components for the representation of evidence. We specify the Reasoning and Discourse Ontology (RDO), an OWL representation of the model of scientific claims, their subjects, their provenance and their argumentative relations underlying the SEE approach. We demonstrate the application of SEE and illustrate its design patterns in a case study by providing an expressive account of the evidence for certain claims regarding the isolation of the enzyme glutamine synthetase. SEE is suited to provide coherent and computationally accessible representations of evidence-related information such as the materials, methods, assumptions, reasoning and information sources used to establish a scientific finding by adopting a consistently claim-based perspective on scientific results and their evidence. SEE allows for extensible evidence representations, in which the level of detail can be adjusted and which can be extended as needed. It supports representation of arbitrary many consecutive layers of interpretation and attribution and different evaluations of the same data. SEE and its underlying model could be a valuable component in a variety of use cases that require careful representation or examination of evidence for data presented on the semantic web or in other formats.

Conceptual modelling to predict unobserved system states - the case of groundwater flooding in the UK Chalk

NASA Astrophysics Data System (ADS)

Hartmann, A. J.; Ireson, A. M.

2017-12-01

Chalk aquifers represent an important source of drinking water in the UK. Due to its fractured-porous structure, Chalk aquifers are characterized by highly dynamic groundwater fluctuations that enhance the risk of groundwater flooding. The risk of groundwater flooding can be assessed by physically-based groundwater models. But for reliable results, a-priori information about the distribution of hydraulic conductivities and porosities is necessary, which is often not available. For that reason, conceptual simulation models are often used to predict groundwater behaviour. They commonly require calibration by historic groundwater observations. Consequently, their prediction performance may reduce significantly, when it comes to system states that did not occur within the calibration time series. In this study, we calibrate a conceptual model to the observed groundwater level observations at several locations within a Chalk system in Southern England. During the calibration period, no groundwater flooding occurred. We then apply our model to predict the groundwater dynamics of the system at a time that includes a groundwater flooding event. We show that the calibrated model provides reasonable predictions before and after the flooding event but it over-estimates groundwater levels during the event. After modifying the model structure to include topographic information, the model is capable of prediction the groundwater flooding event even though groundwater flooding never occurred in the calibration period. Although straight forward, our approach shows how conceptual process-based models can be applied to predict system states and dynamics that did not occur in the calibration period. We believe such an approach can be transferred to similar cases, especially to regions where rainfall intensities are expected to trigger processes and system states that may have not yet been observed.

Multimodal hybrid reasoning methodology for personalized wellbeing services.

PubMed

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 modified-RBR and baseline-RBR systems. Hybrid-CBR yields a 0.94% recall, a 0.97% precision, a 0.95% f-score, and low Type I and Type II errors. Copyright © 2015 Elsevier Ltd. All rights reserved.

What physicians reason about during admission case review.

PubMed

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 is needed to explore how physicians decide why a supporting task is required in a particular context.

Reasonable Accommodation Information Tracking System

EPA Pesticide Factsheets

The Reasonable Accommodation Information Tracking System (RAITS) is a case management system that allows the National Reasonable Accommodation Coordinator (NRAC) and the Local Reasonable Accommodation Coordinators (LORAC) to manage information related to Reasonable Accommodation (RA) requests. It provides a data base system in compliance with Executive Order 13164 and required by the Equal Employment Opportunity Commission (EEOC) Regulations and American Federation of Government Employees (AFGE) Bargaining Unit as described in the AFGE National Reasonable Accommodation Procedures. It is a tool that was internally developed in Lotus Notes to track requests for reasonable accommodation and was custom-configured to meet EPA's specific needs and infrastructure.

Characterization of Model-Based Reasoning Strategies for Use in IVHM Architectures

NASA Technical Reports Server (NTRS)

Poll, Scott; Iverson, David; Patterson-Hine, Ann

2003-01-01

Open architectures are gaining popularity for Integrated Vehicle Health Management (IVHM) applications due to the diversity of subsystem health monitoring strategies in use and the need to integrate a variety of techniques at the system health management level. The basic concept of an open architecture suggests that whatever monitoring or reasoning strategy a subsystem wishes to deploy, the system architecture will support the needs of that subsystem and will be capable of transmitting subsystem health status across subsystem boundaries and up to the system level for system-wide fault identification and diagnosis. There is a need to understand the capabilities of various reasoning engines and how they, coupled with intelligent monitoring techniques, can support fault detection and system level fault management. Researchers in IVHM at NASA Ames Research Center are supporting the development of an IVHM system for liquefying-fuel hybrid rockets. In the initial stage of this project, a few readily available reasoning engines were studied to assess candidate technologies for application in next generation launch systems. Three tools representing the spectrum of model-based reasoning approaches, from a quantitative simulation based approach to a graph-based fault propagation technique, were applied to model the behavior of the Hybrid Combustion Facility testbed at Ames. This paper summarizes the characterization of the modeling process for each of the techniques.

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

PubMed

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 Architecture Management System (BAMS).

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

PubMed Central

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 bioinformatics system: the Brain Architecture Management System (BAMS). PMID:21859449

Précis of bayesian rationality: The probabilistic approach to human reasoning.

PubMed

Oaksford, Mike; Chater, Nick

2009-02-01

According to Aristotle, humans are the rational animal. The borderline between rationality and irrationality is fundamental to many aspects of human life including the law, mental health, and language interpretation. But what is it to be rational? One answer, deeply embedded in the Western intellectual tradition since ancient Greece, is that rationality concerns reasoning according to the rules of logic--the formal theory that specifies the inferential connections that hold with certainty between propositions. Piaget viewed logical reasoning as defining the end-point of cognitive development; and contemporary psychology of reasoning has focussed on comparing human reasoning against logical standards. Bayesian Rationality argues that rationality is defined instead by the ability to reason about uncertainty. Although people are typically poor at numerical reasoning about probability, human thought is sensitive to subtle patterns of qualitative Bayesian, probabilistic reasoning. In Chapters 1-4 of Bayesian Rationality (Oaksford & Chater 2007), the case is made that cognition in general, and human everyday reasoning in particular, is best viewed as solving probabilistic, rather than logical, inference problems. In Chapters 5-7 the psychology of "deductive" reasoning is tackled head-on: It is argued that purportedly "logical" reasoning problems, revealing apparently irrational behaviour, are better understood from a probabilistic point of view. Data from conditional reasoning, Wason's selection task, and syllogistic inference are captured by recasting these problems probabilistically. The probabilistic approach makes a variety of novel predictions which have been experimentally confirmed. The book considers the implications of this work, and the wider "probabilistic turn" in cognitive science and artificial intelligence, for understanding human rationality.

A unified framework for the evaluation of surrogate endpoints in mental-health clinical trials.

PubMed

Molenberghs, Geert; Burzykowski, Tomasz; Alonso, Ariel; Assam, Pryseley; Tilahun, Abel; Buyse, Marc

2010-06-01

For a number of reasons, surrogate endpoints are considered instead of the so-called true endpoint in clinical studies, especially when such endpoints can be measured earlier, and/or with less burden for patient and experimenter. Surrogate endpoints may occur more frequently than their standard counterparts. For these reasons, it is not surprising that the use of surrogate endpoints in clinical practice is increasing. Building on the seminal work of Prentice(1) and Freedman et al.,(2) Buyse et al. (3) framed the evaluation exercise within a meta-analytic setting, in an effort to overcome difficulties that necessarily surround evaluation efforts based on a single trial. In this article, we review the meta-analytic approach for continuous outcomes, discuss extensions to non-normal and longitudinal settings, as well as proposals to unify the somewhat disparate collection of validation measures currently on the market. Implications for design and for predicting the effect of treatment in a new trial, based on the surrogate, are discussed. A case study in schizophrenia is analysed.

On the integration of reinforcement learning and approximate reasoning for control

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1991-01-01

The author discusses the importance of strengthening the knowledge representation characteristic of reinforcement learning techniques using methods such as approximate reasoning. The ARIC (approximate reasoning-based intelligent control) architecture is an example of such a hybrid approach in which the fuzzy control rules are modified (fine-tuned) using reinforcement learning. ARIC also demonstrates that it is possible to start with an approximately correct control knowledge base and learn to refine this knowledge through further experience. On the other hand, techniques such as the TD (temporal difference) algorithm and Q-learning establish stronger theoretical foundations for their use in adaptive control and also in stability analysis of hybrid reinforcement learning and approximate reasoning-based controllers.

Automated high-grade prostate cancer detection and ranking on whole slide images

NASA Astrophysics Data System (ADS)

Huang, Chao-Hui; Racoceanu, Daniel

2017-03-01

Recently, digital pathology (DP) has been largely improved due to the development of computer vision and machine learning. Automated detection of high-grade prostate carcinoma (HG-PCa) is an impactful medical use-case showing the paradigm of collaboration between DP and computer science: given a field of view (FOV) from a whole slide image (WSI), the computer-aided system is able to determine the grade by classifying the FOV. Various approaches have been reported based on this approach. However, there are two reasons supporting us to conduct this work: first, there is still room for improvement in terms of detection accuracy of HG-PCa; second, a clinical practice is more complex than the operation of simple image classification. FOV ranking is also an essential step. E.g., in clinical practice, a pathologist usually evaluates a case based on a few FOVs from the given WSI. Then, makes decision based on the most severe FOV. This important ranking scenario is not yet being well discussed. In this work, we introduce an automated detection and ranking system for PCa based on Gleason pattern discrimination. Our experiments suggested that the proposed system is able to perform high-accuracy detection ( 95:57% +/- 2:1%) and excellent performance of ranking. Hence, the proposed system has a great potential to support the daily tasks in the medical routine of clinical pathology.

GoWeb: a semantic search engine for the life science web.

PubMed

Dietze, Heiko; Schroeder, Michael

2009-10-01

Current search engines are keyword-based. Semantic technologies promise a next generation of semantic search engines, which will be able to answer questions. Current approaches either apply natural language processing to unstructured text or they assume the existence of structured statements over which they can reason. Here, we introduce a third approach, GoWeb, which combines classical keyword-based Web search with text-mining and ontologies to navigate large results sets and facilitate question answering. We evaluate GoWeb on three benchmarks of questions on genes and functions, on symptoms and diseases, and on proteins and diseases. The first benchmark is based on the BioCreAtivE 1 Task 2 and links 457 gene names with 1352 functions. GoWeb finds 58% of the functional GeneOntology annotations. The second benchmark is based on 26 case reports and links symptoms with diseases. GoWeb achieves 77% success rate improving an existing approach by nearly 20%. The third benchmark is based on 28 questions in the TREC genomics challenge and links proteins to diseases. GoWeb achieves a success rate of 79%. GoWeb's combination of classical Web search with text-mining and ontologies is a first step towards answering questions in the biomedical domain. GoWeb is online at: http://www.gopubmed.org/goweb.

Is Mistletoe Treatment Beneficial in Invasive Breast Cancer? A New Approach to an Unresolved Problem.

PubMed

Fritz, Peter; Dippon, Jürgen; Müller, Simon; Goletz, Sven; Trautmann, Christian; Pappas, Xenophon; Ott, German; Brauch, Hiltrud; Schwab, Matthias; Winter, Stefan; Mürdter, Thomas; Brinkmann, Friedhelm; Faisst, Simone; Rössle, Susanne; Gerteis, Andreas; Friedel, Godehard

2018-03-01

In this retrospective study, we compared breast cancer patients treated with and without mistletoe lectin I (ML-I) in addition to standard breast cancer treatment in order to determine a possible effect of this complementary treatment. This study included 18,528 patients with invasive breast cancer. Data on additional ML-I treatments were reported for 164 patients. We developed a "similar case" method with a distance measure retrieved from the beta variable in Cox regression to compare these patients, after stage adjustment, with their non-ML-1 treated counterparts in order to answer three hypotheses concerning overall survival, recurrence free survival and life quality. Raw data analysis of an additional ML-I treatment yielded a worse outcome (p=0.02) for patients with ML treatment, possibly due to a bias inherent in the ML-I-treated patients. Using the "similar case" method (a case-based reasoning approach) we could not confirm this harm for patients using ML-I. Analysis of life quality data did not demonstrate reliable differences between patients treated with ML-I treatment and those without proven ML-I treatment. Based on a "similar case" model we did not observe any differences in the overall survival (OS), recurrence-free survival (RFS), and quality of life data between breast cancer patients with standard treatment and those who in addition to standard treatment received ML-I treatment. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

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.

PubMed

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" (p<0.05). The greatest increase occurred in the skill to recognize typical cognitive errors in medicine and to identify risk situations for their occurrence (pre: 2.98±0.92 and retro-pre: 2.64±1.01, respectively, versus post: 4.38±0.88). Based on the ratio of number of words used per keywords used the problem presentation 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 curriculum seems to be desirable. Faculty training would be useful to implement the concept as standardized as possible.

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

PubMed

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 < 0.05). The results of our feasibility 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 development of clinical reasoning skills.

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

PubMed Central

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

2018-01-01

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 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 < 0.05). Conclusion The results of our feasibility 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 development of clinical reasoning skills. PMID:29692641

The disease management approach to cost containment.

PubMed

Goldstein, R

1998-01-01

Disease management has been around a long time, certainly since Pasteur. Its initial focus was to eliminate or contain epidemics. In the 20th century, American public health scientists and officials have used disease management to address a high-risk, often poor population. Currently, the population-based principles of disease management, including disease prevention activities, are being applied to noninfectious diseases. Two examples of public health disease prevention strategies are vaccinations and chlorination of water. Hospitals are now providing post-hospital disease management programs for selected chronic conditions that account for a high volume of repeat admissions or emergency department visits, such as chronic heart failure, asthma, and cancer. In other words, hospitals are spending money on a program that, if done right, will reduce their inpatient revenues. They are doing so for various reasons (e.g., because they have established at-risk financial partnerships with their physicians, or possibly because other area hospitals are doing it, or possibly because they want to keep the ancillaries [x-rays, laboratory, pharmacy, ambulatory surgery, etc]). Regardless of the reasons, hospital case managers will be charged with referring qualified patients to both hospital-based and provider-based disease management programs.

Adapting Surface Ground Motion Relations to Underground conditions: A case study for the Sudbury Neutrino Observatory in Sudbury, Ontario, Canada

NASA Astrophysics Data System (ADS)

Babaie Mahani, A.; Eaton, D. W.

2013-12-01

Ground Motion Prediction Equations (GMPEs) are widely used in Probabilistic Seismic Hazard Assessment (PSHA) to estimate ground-motion amplitudes at Earth's surface as a function of magnitude and distance. Certain applications, such as hazard assessment for caprock integrity in the case of underground storage of CO2, waste disposal sites, and underground pipelines, require subsurface estimates of ground motion; at present, such estimates depend upon theoretical modeling and simulations. The objective of this study is to derive correction factors for GMPEs to enable estimation of amplitudes in the subsurface. We use a semi-analytic approach along with finite-difference simulations of ground-motion amplitudes for surface and underground motions. Spectral ratios of underground to surface motions are used to calculate the correction factors. Two predictive methods are used. The first is a semi-analytic approach based on a quarter-wavelength method that is widely used for earthquake site-response investigations; the second is a numerical approach based on elastic finite-difference simulations of wave propagation. Both methods are evaluated using recordings of regional earthquakes by broadband seismometers installed at the surface and at depths of 1400 m and 2100 m in the Sudbury Neutrino Observatory, Canada. Overall, both methods provide a reasonable fit to the peaks and troughs observed in the ratios of real data. The finite-difference method, however, has the capability to simulate ground motion ratios more accurately than the semi-analytic approach.

Design a Fuzzy Rule-based Expert System to Aid Earlier Diagnosis of Gastric Cancer.

PubMed

Safdari, Reza; Arpanahi, Hadi Kazemi; Langarizadeh, Mostafa; Ghazisaiedi, Marjan; Dargahi, Hossein; Zendehdel, Kazem

2018-01-01

Screening and health check-up programs are most important sanitary priorities, that should be undertaken to control dangerous diseases such as gastric cancer that affected by different factors. More than 50% of gastric cancer diagnoses are made during the advanced stage. Currently, there is no systematic approach for early diagnosis of gastric cancer. to develop a fuzzy expert system that can identify gastric cancer risk levels in individuals. This system was implemented in MATLAB software, Mamdani inference technique applied to simulate reasoning of experts in the field, a total of 67 fuzzy rules extracted as a rule-base based on medical expert's opinion. 50 case scenarios were used to evaluate the system, the information of case reports is given to the system to find risk level of each case report then obtained results were compared with expert's diagnosis. Results revealed that sensitivity was 92.1% and the specificity was 83.1%. The results show that is possible to develop a system that can identify High risk individuals for gastric cancer. The system can lead to earlier diagnosis, this may facilitate early treatment and reduce gastric cancer mortality rate.

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

PubMed

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.

"First, know thyself": cognition and error in medicine.

PubMed

Elia, Fabrizio; Aprà, Franco; Verhovez, Andrea; Crupi, Vincenzo

2016-04-01

Although error is an integral part of the world of medicine, physicians have always been little inclined to take into account their own mistakes and the extraordinary technological progress observed in the last decades does not seem to have resulted in a significant reduction in the percentage of diagnostic errors. The failure in the reduction in diagnostic errors, notwithstanding the considerable investment in human and economic resources, has paved the way to new strategies which were made available by the development of cognitive psychology, the branch of psychology that aims at understanding the mechanisms of human reasoning. This new approach led us to realize that we are not fully rational agents able to take decisions on the basis of logical and probabilistically appropriate evaluations. In us, two different and mostly independent modes of reasoning coexist: a fast or non-analytical reasoning, which tends to be largely automatic and fast-reactive, and a slow or analytical reasoning, which permits to give rationally founded answers. One of the features of the fast mode of reasoning is the employment of standardized rules, termed "heuristics." Heuristics lead physicians to correct choices in a large percentage of cases. Unfortunately, cases exist wherein the heuristic triggered fails to fit the target problem, so that the fast mode of reasoning can lead us to unreflectively perform actions exposing us and others to variable degrees of risk. Cognitive errors arise as a result of these cases. Our review illustrates how cognitive errors can cause diagnostic problems in clinical practice.

Mapping student thinking in chemical synthesis

NASA Astrophysics Data System (ADS)

Weinrich, Melissa

In order to support the development of learning progressions about central ideas and practices in different disciplines, we need detailed analyses of the implicit assumptions and reasoning strategies that guide students' thinking at different educational levels. In the particular case of chemistry, understanding how new chemical substances are produced (chemical synthesis) is of critical importance. Thus, we have used a qualitative research approach based on individual interviews with first semester general chemistry students (n = 16), second semester organic chemistry students (n = 15), advanced undergraduates (n = 9), first year graduate students (n = 15), and PhD candidates (n = 16) to better characterize diverse students' underlying cognitive elements (conceptual modes and modes of reasoning) when thinking about chemical synthesis. Our results reveal a great variability in the cognitive resources and strategies used by students with different levels of training in the discipline to make decisions, particularly at intermediate levels of expertise. The specific nature of the task had a strong influence on the conceptual sophistication and mode of reasoning that students exhibited. Nevertheless, our data analysis has allowed us to identify common modes of reasoning and assumptions that seem to guide students' thinking at different educational levels. Our results should facilitate the development of learning progressions that help improve chemistry instruction, curriculum, and assessment.

Risk factors and consequences of unexpected trapping for ruptured anterior communicating artery aneurysms

PubMed Central

Fukuda, Hitoshi; Iwasaki, Koichi; Murao, Kenichi; Yamagata, Sen; Lo, Benjamin W.Y.; Macdonald, R. Loch

2014-01-01

Background: While clipping cerebral aneurysms at the neck is optimal, in some cases this is not possible and other strategies are necessary. The purpose of this study was to describe the incidence, risk factors, and outcomes for inability to clip reconstruct ruptured anterior communicating artery (ACoA) aneurysms. Methods: Of the 70 cases of ruptured ACoA aneurysms between January 2006 and December 2013, our institutional experience revealed four cases of small ACoA aneurysms that had been considered clippable prior to operation but required trapping. When a unilateral A2 segment of anterior cerebral artery (ACA) was compromised by trapping, revascularization was performed by bypass surgery. Clinical presentation, angiographic characteristics, operative approach, intraoperative findings, and treatment outcomes were assessed. Results: Very small aneurysm under 3 mm was a risk factor for unexpected trapping. The reason for unexpected trapping was laceration of the aneurysmal neck in two cases, and lack of clippaple component due to disintegration of entire aneurysmal wall at the time of rupture in the others. Aneurysms with bilateral A1 were treated with sole trapping through pterional approach in two cases. The other two cases had hypoplastic unilateral A1 segment of ACA and were treated with combination of aneurysm trapping and revascularization of A2 segment of ACA through interhemispheric approach. No patients had new cerebral infarctions of cortical ACA territory from surgery. Cognitive dysfunction was observed in three cases, but all patients became independent at 12-month follow up. Conclusions: Unexpected trapping was performed when ruptured ACoA aneurysms were unclippable. Trapping with or without bypass can result in reasonable outcomes, with acceptable risk of cognitive dysfunction. PMID:25101201

"For Some Reason, I'm Just Tired": Women Domestic Workers Persisting in Community-Based Programmes

ERIC Educational Resources Information Center

Cuban, Sondra

2007-01-01

A study of women migrant domestic workers in the USA and their reasons for participating and persisting in community-based literacy and ESOL programmes is presented. Case studies and themes were developed about the women's experiences of work life and how it connected to their programme participation. The findings revealed that the women had…

Active Ambiguity Reduction: An Experiment Design Approach to Tractable Qualitative Reasoning.

DTIC Science & Technology

1987-04-20

Approach to Tractable Qualitative Reasoning Shankar A. Rajamoney t [ For Gerald F. DeJong Artificial Intelligence Research Group Coordinated Science...Representations of Knowledge in a Mechanics Problem- Solver." Proceedings of the Fifth International Joint Conference on Artificial Intelligence. Cambridge. MIA...International Joint Conference on Artificial Intelligence. Tokyo. Japan. 1979. [de Kleer84] J. de Kleer and J. S. Brown. "A Qualitative Physics Based on

Blind deconvolution of 2-D and 3-D fluorescent micrographs

NASA Astrophysics Data System (ADS)

Krishnamurthi, Vijaykumar; Liu, Yi-Hwa; Holmes, Timothy J.; Roysam, Badrinath; Turner, James N.

1992-06-01

This paper presents recent results of our reconstructions of 3-D data from Drosophila chromosomes as well as our simulations with a refined version of the algorithm used in the former. It is well known that the calibration of the point spread function (PSF) of a fluorescence microscope is a tedious process and involves esoteric techniques in most cases. This problem is further compounded in the case of confocal microscopy where the measured intensities are usually low. A number of techniques have been developed to solve this problem, all of which are methods in blind deconvolution. These are so called because the measured PSF is not required in the deconvolution of degraded images from any optical system. Our own efforts in this area involved the maximum likelihood (ML) method, the numerical solution to which is obtained by the expectation maximization (EM) algorithm. Based on the reasonable early results obtained during our simulations with 2-D phantoms, we carried out experiments with real 3-D data. We found that the blind deconvolution method using the ML approach gave reasonable reconstructions. Next we tried to perform the reconstructions using some 2-D data, but we found that the results were not encouraging. We surmised that the poor reconstructions were primarily due to the large values of dark current in the input data. This, coupled with the fact that we are likely to have similar data with considerable dark current from a confocal microscope prompted us to look into ways of constraining the solution of the PSF. We observed that in the 2-D case, the reconstructed PSF has a tendency to retain values larger than those of the theoretical PSF in regions away from the center (outside of those we considered to be its region of support). This observation motivated us to apply an upper bound constraint on the PSF in these regions. Furthermore, we constrain the solution of the PSF to be a bandlimited function, as in the case in the true situation. We have derived two separate approaches for implementing the constraint. One approach involves the mathematical rigors of Lagrange multipliers. This approach is discussed in another paper. The second approach involves an adaptation of the Gershberg Saxton algorithm, which ensures bandlimitedness and non-negativity of the PSF. Although the latter approach is mathematically less rigorous than the former, we currently favor it because it has a simpler implementation on a computer and has smaller memory requirements. The next section describes briefly the theory and derivation of these constraint equations using Lagrange multipliers.

Model-Based Compositional Reasoning for Complex Systems of Systems (SoS)

DTIC Science & Technology

2016-11-01

more structured approach for finding flaws /weaknesses in the systems . As the system is updated, either in response to a found flaw or new...AFRL-RQ-WP-TR-2016-0172 MODEL-BASED COMPOSITIONAL REASONING FOR COMPLEX SYSTEMS OF SYSTEMS (SoS) M. Anthony Aiello, Benjamin D. Rodes...LABORATORY AEROSPACE SYSTEMS DIRECTORATE WRIGHT-PATTERSON AIR FORCE BASE, OH 45433-7541 AIR FORCE MATERIEL COMMAND UNITED STATES AIR FORCE NOTICE

A knowledge-based system for prototypical reasoning

NASA Astrophysics Data System (ADS)

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.

Provider biases and choices: the role of gender.

PubMed

Wertz, D C

1993-09-01

Genetic counseling provides a unique opportunity to test the influence of gender on moral reasoning. The theories of Carol Gilligan on women's "relationship based" framework for ethical decision making were contrasted with Kohlberg's research on men's resolution of conflicts based on abstract, universal principles in an impersonal and fair manner. Discussion also focussed on the theories of sociologists, such as Kanter's that a profession prestige and income as well as the proportion of women in profession determine the approach to ethical problems. This study reports on survey data in 1985 and 1986 collected from medical geneticists in 19 countries that had at least 10 medical geneticists, with at least one available to distribute questionnaires, and the appropriate geographic distribution. The survey did not include genetic counselors and allied professionals. The questionnaire asked for responses to 14 case studies, 4 questions on genetic screening and access to test results, and 12 questions on the goals and conduct of genetic counseling. 62% responded. Sociodemographic data were also collected and analyzed in stepwise logistic regressions. THe results showed that gender was the single most important determinant of ethical decision making and ethical reasoning. There were gender differences in responses to 6 of the 14 cases and, in the US, for a 7th case: sex selection. In the US, women were 4.4 times more likely to counsel indirectly about XYY fetuses and 3.6 more likely to bring up issues like false paternity or genetic carriers in other family members. Patient autonomy was an issued in a case involving a 25-year-old woman who demanded prenatal diagnosis with no genetic or medical indications and another case involving a couple desiring a son after having 4 daughters. Rights based responses were provided by 49% and relationship based responses by 44%. Gilligan's hypothesis was not supported. Similar results were found in a survey of genetic counselors, who were 94% women. A summary of other studies involving actual practices was given. Further research is needed to determine the processes of professionals' self definition, ethical views, and extent to which views and practices are gender or profession related; training programs may affect provider attitudes.

The Northern Ireland Early Onset Psychosis Study: Phenomenology and Co-Morbidity in the First 25 Cases

ERIC Educational Resources Information Center

Fulton, Karen; Short, Mary; Harvey-Smith, Diane; Rushe, Teresa M.; Mulholland, Ciaran

2008-01-01

Diagnosing psychotic disorders in young people is difficult. High rates of co-morbidity may be one reason for this difficulty, but it may also be the case that current diagnostic categories are not the most useful when approaching the care of young people with psychotic symptoms. The Northern Ireland Early Onset Psychosis Study is the first study…

Why Children Join and Stay in Sports Clubs: Case Studies in Australian, French and German Swimming Clubs

ERIC Educational Resources Information Center

Light, Richard L.; Harvey, Stephen; Memmert, Daniel

2013-01-01

This article builds upon research on youth sport clubs conducted from a socio-cultural perspective by reporting on a study that inquired into the reasons why children aged 9-12 joined swimming clubs in France, Germany and Australia. Comprising three case studies it employed a mixed method approach with results considered within the framework of…

Practical and generalizable architecture for an intelligent tutoring system

NASA Astrophysics Data System (ADS)

Kaplan, Randy M.; Trenholm, Harriet

1993-03-01

In this paper we describe an intelligent tutoring system (ITS) called HYDRIVE (hydraulics interactive video experience). This system is built using several novel approaches to intelligent tutoring. The underlying rationale for HYDRIVE is based on the results of a cognitive task analysis. The reasoning component of the system makes extensive use of a hierarchical knowledge representation. Reasoning within the system is accomplished using a logic-based approach and is linked to a highly interactive interface using multimedia. The knowledge representation contains information that drives the multimedia elements of the system, and the reasoning components select the appropriate information to assess student knowledge or guide the student at any particular moment. As this system will be deployed throughout the Air Force maintenance function, the implementation platform is the IBM PC.

An Algorithm Using Twelve Properties of Antibiotics to Find the Recommended Antibiotics, as in CPGs.

PubMed

Tsopra, R; Venot, A; Duclos, C

2014-01-01

Clinical Decision Support Systems (CDSS) incorporating justifications, updating and adjustable recommendations can considerably improve the quality of healthcare. We propose a new approach to the design of CDSS for empiric antibiotic prescription, based on implementation of the deeper medical reasoning used by experts in the development of clinical practice guidelines (CPGs), to deduce the recommended antibiotics. We investigated two methods ("exclusion" versus "scoring") for reproducing this reasoning based on antibiotic properties. The "exclusion" method reproduced expert reasoning the more accurately, retrieving the full list of recommended antibiotics for almost all clinical situations. This approach has several advantages: (i) it provides convincing explanations for physicians; (ii) updating could easily be incorporated into the CDSS; (iii) it can provide recommendations for clinical situations missing from CPGs.

Paraconsistent Reasoning for OWL 2

NASA Astrophysics Data System (ADS)

Ma, Yue; Hitzler, Pascal

A four-valued description logic has been proposed to reason with description logic based inconsistent knowledge bases. This approach has a distinct advantage that it can be implemented by invoking classical reasoners to keep the same complexity as under the classical semantics. However, this approach has so far only been studied for the basic description logic mathcal{ALC}. In this paper, we further study how to extend the four-valued semantics to the more expressive description logic mathcal{SROIQ} which underlies the forthcoming revision of the Web Ontology Language, OWL 2, and also investigate how it fares when adapted to tractable description logics including mathcal{EL++}, DL-Lite, and Horn-DLs. We define the four-valued semantics along the same lines as for mathcal{ALC} and show that we can retain most of the desired properties.

Students' self-explanations while solving unfamiliar cases: the role of biomedical knowledge.

PubMed

Chamberland, Martine; Mamede, Sílvia; St-Onge, Christina; Rivard, Marc-Antoine; Setrakian, Jean; Lévesque, Annie; Lanthier, Luc; Schmidt, Henk G; Rikers, Remy M J P

2013-11-01

General guidelines for teaching clinical reasoning have received much attention, despite a paucity of instructional approaches with demonstrated effectiveness. As suggested in a recent experimental study, self-explanation while solving clinical cases may be an effective strategy to foster reasoning in clinical clerks dealing with less familiar cases. However, the mechanisms that mediate this benefit have not been specifically investigated. The aim of this study was to explore the types of knowledge used by students when solving familiar and less familiar clinical cases with self-explanation. In a previous study, 36 third-year medical students diagnosed familiar and less familiar clinical cases either by engaging in self-explanation or not. Based on an analysis of previously collected data, the present study compared the content of self-explanation protocols generated by seven randomly selected students while solving four familiar and four less familiar cases. In total, 56 verbal protocols (28 familiar and 28 less familiar) were segmented and coded using the following categories: paraphrases, biomedical inferences, clinical inferences, monitoring statements and errors. Students provided more self-explanation segments from less familiar cases (M = 275.29) than from familiar cases (M = 248.71, p = 0.046). They provided significantly more paraphrases (p = 0.001) and made more errors (p = 0.008). A significant interaction was found between familiarity and the type of inferences (biomedical versus clinical, p = 0.016). When self-explaining less familiar cases, students provided significantly more biomedical inferences than familiar cases. Lack of familiarity with a case seems to stimulate medical students to engage in more extensive thinking during self-explanation. Less familiar cases seem to activate students' biomedical knowledge, which in turn helps them to create new links between biomedical and clinical knowledge, and eventually construct a more coherent mental representation of diseases. This may clarify the previously found positive effect that self-explanation has on the diagnosis of unfamiliar cases. © 2013 John Wiley & Sons Ltd.

A Sampled Literature Review of Design-Based Learning Approaches: A Search for Key Characteristics

ERIC Educational Resources Information Center

Gómez Puente, Sonia M.; van Eijck, Michiel; Jochems, Wim

2013-01-01

Design-based learning (DBL) is an educational approach grounded in the processes of inquiry and reasoning towards generating innovative artifacts, systems and solutions. The approach is well characterized in the context of learning natural sciences in secondary education. Less is known, however, of its characteristics in the context of higher…

Enhancing Critical Thinking Via a Clinical Scholar Approach.

PubMed

Simpson, Vicki; McComb, Sara A; Kirkpatrick, Jane M

2017-11-01

Safety, quality improvement, and a systems perspective are vital for nurses to provide quality evidence-based care. Responding to the call to prepare nurses with these perspectives, one school of nursing used a clinical scholar approach, enhanced by systems engineering to more intentionally develop the ability to clinically reason and apply evidence-based practice. A two-group, repeated-measures control trial was used to determine the effects of systems engineering content and support on nursing students' clinical judgment and critical thinking skills. Findings indicated this approach had a positive effects on student's clinical judgment and clinical reasoning skills. This approach helped students view health care issues from a broader perspective and use evidence to guide solution development, enhancing the focus on evidence-based practice, and quality improvement. Intentional integration of an evidence-based, systems perspective by nursing faculty supports development of nurses who can function safely and effectively in the current health care system. [J Nurs Educ. 2017;56(11):679-682.]. Copyright 2017, SLACK Incorporated.

Implicit Schemata and Categories in Memory-Based Language Processing

ERIC Educational Resources Information Center

van den Bosch, Antal; Daelemans, Walter

2013-01-01

Memory-based language processing (MBLP) is an approach to language processing based on exemplar storage during learning and analogical reasoning during processing. From a cognitive perspective, the approach is attractive as a model for human language processing because it does not make any assumptions about the way abstractions are shaped, nor any…

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

PubMed

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.

Expert system for web based collaborative CAE

NASA Astrophysics Data System (ADS)

Hou, Liang; Lin, Zusheng

2006-11-01

An expert system for web based collaborative CAE was developed based on knowledge engineering, relational database and commercial FEA (Finite element analysis) software. The architecture of the system was illustrated. In this system, the experts' experiences, theories and typical examples and other related knowledge, which will be used in the stage of pre-process in FEA, were categorized into analysis process and object knowledge. Then, the integrated knowledge model based on object-oriented method and rule based method was described. The integrated reasoning process based on CBR (case based reasoning) and rule based reasoning was presented. Finally, the analysis process of this expert system in web based CAE application was illustrated, and an analysis example of a machine tool's column was illustrated to prove the validity of the system.

An Analysis of Categorical and Quantitative Methods for Planning Under Uncertainty

PubMed Central

Langlotz, Curtis P.; Shortliffe, Edward H.

1988-01-01

Decision theory and logical reasoning are both methods for representing and solving medical decision problems. We analyze the usefulness of these two approaches to medical therapy planning by establishing a simple correspondence between decision theory and non-monotonic logic, a formalization of categorical logical reasoning. The analysis indicates that categorical approaches to planning can be viewed as comprising two decision-theoretic concepts: probabilities (degrees of belief in planning hypotheses) and utilities (degrees of desirability of planning outcomes). We present and discuss examples of the following lessons from this decision-theoretic view of categorical (nonmonotonic) reasoning: (1) Decision theory and artificial intelligence techniques are intended to solve different components of the planning problem. (2) When considered in the context of planning under uncertainty, nonmonotonic logics do not retain the domain-independent characteristics of classical logical reasoning for planning under certainty. (3) Because certain nonmonotonic programming paradigms (e.g., frame-based inheritance, rule-based planning, protocol-based reminders) are inherently problem-specific, they may be inappropriate to employ in the solution of certain types of planning problems. We discuss how these conclusions affect several current medical informatics research issues, including the construction of “very large” medical knowledge bases.

Structure-based classification and ontology in chemistry

PubMed Central

2012-01-01

Background Recent years have seen an explosion in the availability of data in the chemistry domain. With this information explosion, however, retrieving relevant results from the available information, and organising those results, become even harder problems. Computational processing is essential to filter and organise the available resources so as to better facilitate the work of scientists. Ontologies encode expert domain knowledge in a hierarchically organised machine-processable format. One such ontology for the chemical domain is ChEBI. ChEBI provides a classification of chemicals based on their structural features and a role or activity-based classification. An example of a structure-based class is 'pentacyclic compound' (compounds containing five-ring structures), while an example of a role-based class is 'analgesic', since many different chemicals can act as analgesics without sharing structural features. Structure-based classification in chemistry exploits elegant regularities and symmetries in the underlying chemical domain. As yet, there has been neither a systematic analysis of the types of structural classification in use in chemistry nor a comparison to the capabilities of available technologies. Results We analyze the different categories of structural classes in chemistry, presenting a list of patterns for features found in class definitions. We compare these patterns of class definition to tools which allow for automation of hierarchy construction within cheminformatics and within logic-based ontology technology, going into detail in the latter case with respect to the expressive capabilities of the Web Ontology Language and recent extensions for modelling structured objects. Finally we discuss the relationships and interactions between cheminformatics approaches and logic-based approaches. Conclusion Systems that perform intelligent reasoning tasks on chemistry data require a diverse set of underlying computational utilities including algorithmic, statistical and logic-based tools. For the task of automatic structure-based classification of chemical entities, essential to managing the vast swathes of chemical data being brought online, systems which are capable of hybrid reasoning combining several different approaches are crucial. We provide a thorough review of the available tools and methodologies, and identify areas of open research. PMID:22480202

An Intelligent Case-Based Help Desk Providing Web-Based Support for EOSDIS Customers

NASA Technical Reports Server (NTRS)

Mitchell, Christine M.; Thurman, David A.

1998-01-01

This paper describes a project that extends the concept of help desk automation by offering World Wide Web access to a case-based help desk. It explores the use of case-based reasoning and cognitive engineering models to create an 'intelligent' help desk system, one that learns. It discusses the AutoHelp architecture for such a help desk and summarizes the technologies used to create a help desk for NASA data users.

Model-based diagnostics for Space Station Freedom

NASA Technical Reports Server (NTRS)

Fesq, Lorraine M.; Stephan, Amy; Martin, Eric R.; Lerutte, Marcel G.

1991-01-01

An innovative approach to fault management was recently demonstrated for the NASA LeRC Space Station Freedom (SSF) power system testbed. This project capitalized on research in model-based reasoning, which uses knowledge of a system's behavior to monitor its health. The fault management system (FMS) can isolate failures online, or in a post analysis mode, and requires no knowledge of failure symptoms to perform its diagnostics. An in-house tool called MARPLE was used to develop and run the FMS. MARPLE's capabilities are similar to those available from commercial expert system shells, although MARPLE is designed to build model-based as opposed to rule-based systems. These capabilities include functions for capturing behavioral knowledge, a reasoning engine that implements a model-based technique known as constraint suspension, and a tool for quickly generating new user interfaces. The prototype produced by applying MARPLE to SSF not only demonstrated that model-based reasoning is a valuable diagnostic approach, but it also suggested several new applications of MARPLE, including an integration and testing aid, and a complement to state estimation.

GeneCOST: a novel scoring-based prioritization framework for identifying disease causing genes.

PubMed

Ozer, Bugra; Sağıroğlu, Mahmut; Demirci, Hüseyin

2015-11-15

Due to the big data produced by next-generation sequencing studies, there is an evident need for methods to extract the valuable information gathered from these experiments. In this work, we propose GeneCOST, a novel scoring-based method to evaluate every gene for their disease association. Without any prior filtering and any prior knowledge, we assign a disease likelihood score to each gene in correspondence with their variations. Then, we rank all genes based on frequency, conservation, pedigree and detailed variation information to find out the causative reason of the disease state. We demonstrate the usage of GeneCOST with public and real life Mendelian disease cases including recessive, dominant, compound heterozygous and sporadic models. As a result, we were able to identify causative reason behind the disease state in top rankings of our list, proving that this novel prioritization framework provides a powerful environment for the analysis in genetic disease studies alternative to filtering-based approaches. GeneCOST software is freely available at www.igbam.bilgem.tubitak.gov.tr/en/softwares/genecost-en/index.html. buozer@gmail.com Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Teaching clinical reasoning by making thinking visible: an action research project with allied health clinical educators

PubMed Central

2014-01-01

Background Clinical reasoning is fundamental to all forms of professional health practice, however it is also difficult to teach and learn because it is complex, tacit, and effectively invisible for students. In this paper we present an approach for teaching clinical reasoning based on making expert thinking visible and accessible to students. Methods Twenty-one experienced allied health clinical educators from three tertiary Australian hospitals attended up to seven action research discussion sessions, where they developed a tentative heuristic of their own clinical reasoning, trialled it with students, evaluated if it helped their students to reason clinically, and then refined it so the heuristic was targeted to developing each student’s reasoning skills. Data included participants’ written descriptions of the thinking routines they developed and trialed with their students and the transcribed action research discussion sessions. Content analysis was used to summarise this data and categorise themes about teaching and learning clinical reasoning. Results Two overriding themes emerged from participants’ reports about using the ‘making thinking visible approach’. The first was a specific focus by participating educators on students’ understanding of the reasoning process and the second was heightened awareness of personal teaching styles and approaches to teaching clinical reasoning. Conclusions We suggest that the making thinking visible approach has potential to assist educators to become more reflective about their clinical reasoning teaching and acts as a scaffold to assist them to articulate their own expert reasoning and for students to access and use. PMID:24479414

Heuristic for Critical Machine Based a Lot Streaming for Two-Stage Hybrid Production Environment

NASA Astrophysics Data System (ADS)

Vivek, P.; Saravanan, R.; Chandrasekaran, M.; Pugazhenthi, R.

2017-03-01

Lot streaming in Hybrid flowshop [HFS] is encountered in many real world problems. This paper deals with a heuristic approach for Lot streaming based on critical machine consideration for a two stage Hybrid Flowshop. The first stage has two identical parallel machines and the second stage has only one machine. In the second stage machine is considered as a critical by valid reasons these kind of problems is known as NP hard. A mathematical model developed for the selected problem. The simulation modelling and analysis were carried out in Extend V6 software. The heuristic developed for obtaining optimal lot streaming schedule. The eleven cases of lot streaming were considered. The proposed heuristic was verified and validated by real time simulation experiments. All possible lot streaming strategies and possible sequence under each lot streaming strategy were simulated and examined. The heuristic consistently yielded optimal schedule consistently in all eleven cases. The identification procedure for select best lot streaming strategy was suggested.

A Rawlsian Approach to Distribute Responsibilities in Networks

PubMed Central

2009-01-01

Due to their non-hierarchical structure, socio-technical networks are prone to the occurrence of the problem of many hands. In the present paper an approach is introduced in which people’s opinions on responsibility are empirically traced. The approach is based on the Rawlsian concept of Wide Reflective Equilibrium (WRE) in which people’s considered judgments on a case are reflectively weighed against moral principles and background theories, ideally leading to a state of equilibrium. Application of the method to a hypothetical case with an artificially constructed network showed that it is possible to uncover the relevant data to assess a consensus amongst people in terms of their individual WRE. It appeared that the moral background theories people endorse are not predictive for their actual distribution of responsibilities but that they indicate ways of reasoning and justifying outcomes. Two ways of ascribing responsibilities were discerned, corresponding to two requirements of a desirable responsibility distribution: fairness and completeness. Applying the method triggered learning effects, both with regard to conceptual clarification and moral considerations, and in the sense that it led to some convergence of opinions. It is recommended to apply the method to a real engineering case in order to see whether this approach leads to an overlapping consensus on a responsibility distribution which is justifiable to all and in which no responsibilities are left unfulfilled, therewith trying to contribute to the solution of the problem of many hands. PMID:19626463

Can Tauc plot extrapolation be used for direct-band-gap semiconductor nanocrystals?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feng, Y., E-mail: yu.feng@unsw.edu.au; Lin, S.; Huang, S.

Despite that Tauc plot extrapolation has been widely adopted for extracting bandgap energies of semiconductors, there is a lack of theoretical support for applying it to nanocrystals. In this paper, direct-allowed optical transitions in semiconductor nanocrystals have been formulated based on a purely theoretical approach. This result reveals a size-dependant transition of the power factor used in Tauc plot, increasing from one half used in the 3D bulk case to one in the 0D case. This size-dependant intermediate value of power factor allows a better extrapolation of measured absorption data. Being a material characterization technique, the generalized Tauc extrapolation givesmore » a more reasonable and accurate acquisition of the intrinsic bandgap, while the unjustified purpose of extrapolating any elevated bandgap caused by quantum confinement is shown to be incorrect.« less

Demonstration of a tool for automatic learning and re-use of knowledge in the activated sludge process.

PubMed

Comas, J; Rodríguez-Roda, I; Poch, M; Gernaey, K V; Rosen, C; Jeppsson, U

2006-01-01

Wastewater treatment plant operators encounter complex operational problems related to the activated sludge process and usually respond to these by applying their own intuition and by taking advantage of what they have learnt from past experiences of similar problems. However, previous process experiences are not easy to integrate in numerical control, and new tools must be developed to enable re-use of plant operating experience. The aim of this paper is to investigate the usefulness of a case-based reasoning (CBR) approach to apply learning and re-use of knowledge gained during past incidents to confront actual complex problems through the IWA/COST Benchmark protocol. A case study shows that the proposed CBR system achieves a significant improvement of the benchmark plant performance when facing a high-flow event disturbance.

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

NASA Astrophysics Data System (ADS)

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.

Using National Health Care Databases and Problem-Based Practice Analysis to Inform Integrated Curriculum Development.

PubMed

Baker, Amy J; Raymond, Mark R; Haist, Steven A; Boulet, John R

2017-04-01

One challenge when implementing case-based learning, and other approaches to contextualized learning, is determining which clinical problems to include. This article illustrates how health care utilization data, readily available from the National Center for Health Statistics (NCHS), can be incorporated into an educational needs assessment to identify medical problems physicians are likely to encounter in clinical practice. The NCHS survey data summarize patient demographics, diagnoses, and interventions for tens of thousands of patients seen in various settings, including emergency departments (EDs), clinics, and hospitals.Selected data from the National Hospital Ambulatory Medical Care Survey: Emergency Department illustrate how instructional materials can be derived from the results of such public-use health care data. Using fever as the reason for visit to the ED, the patient management path is depicted in the form of a case drill-down by exploring the most common diagnoses, blood tests, diagnostic studies, procedures, and medications associated with fever.Although these types of data are quite useful, they should not serve as the sole basis for determining which instructional cases to include. Additional sources of information should be considered to ensure the inclusion of cases that represent infrequent but high-impact problems and those that illustrate fundamental principles that generalize to other cases.

Load Balancing in Structured P2P Networks

NASA Astrophysics Data System (ADS)

Zhu, Yingwu

In this chapter we start by addressing the importance and necessity of load balancing in structured P2P networks, due to three main reasons. First, structured P2P networks assume uniform peer capacities while peer capacities are heterogeneous in deployed P2P networks. Second, resorting to pseudo-uniformity of the hash function used to generate node IDs and data item keys leads to imbalanced overlay address space and item distribution. Lastly, placement of data items cannot be randomized in some applications (e.g., range searching). We then present an overview of load aggregation and dissemination techniques that are required by many load balancing algorithms. Two techniques are discussed including tree structure-based approach and gossip-based approach. They make different tradeoffs between estimate/aggregate accuracy and failure resilience. To address the issue of load imbalance, three main solutions are described: virtual server-based approach, power of two choices, and address-space and item balancing. While different in their designs, they all aim to improve balance on the address space and data item distribution. As a case study, the chapter discusses a virtual server-based load balancing algorithm that strives to ensure fair load distribution among nodes and minimize load balancing cost in bandwidth. Finally, the chapter concludes with future research and a summary.

Adaptive scenarios: a training model for today's public health workforce.

PubMed

Uden-Holman, Tanya; Bedet, Jennifer; Walkner, Laurie; Abd-Hamid, Nor Hashidah

2014-01-01

With the current economic climate, money for training is scarce. In addition, time is a major barrier to participation in trainings. To meet the public health workforce's rising demand for training, while struggling with less time and fewer resources, the Upper Midwest Preparedness and Emergency Response Learning Center has developed a model of online training that provides the public health workforce with individually customized, needs-based training experiences. Adaptive scenarios are rooted in case-based reasoning, a learning approach that focuses on the specific knowledge needed to solve a problem. Proponents of case-based reasoning argue that learners benefit from being able to remember previous similar situations and reusing information and knowledge from that situation. Adaptive scenarios based on true-to-life job performance provide an opportunity to assess skills by presenting the user with choices to make in a problem-solving context. A team approach was used to develop the adaptive scenarios. Storylines were developed that incorporated situations aligning with the knowledge, skills, and attitudes outlined in the Public Health Preparedness and Response Core Competency Model. This article examines 2 adaptive scenarios: "Ready or Not? A Family Preparedness Scenario" and "Responding to a Crisis: Managing Emotions and Stress Scenario." The scenarios are available on Upper Midwest Preparedness and Emergency Response Learning Center's Learning Management System, the Training Source (http://training-source.org). Evaluation data indicate that users' experiences have been positive. Integrating the assessment and training elements of the scenarios so that the training experience is uniquely adaptive to each user is one of the most efficient ways to provide training. The opportunity to provide individualized, needs-based training without having to administer separate assessments has the potential to save time and resources. These adaptive scenarios continue to be marketed to target audiences through partner organizations, various Web sites, electronic newsletters, and social media. Next steps include the implementation of a 6-month follow-up evaluation, using Kirkpatrick level III. Kirkpatrick level III evaluation measures whether there was actual transfer of learning to the work setting.

Numerical Prediction of CCV in a PFI Engine using a Parallel LES Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ameen, Muhsin M; Mirzaeian, Mohsen; Millo, Federico

Cycle-to-cycle variability (CCV) is detrimental to IC engine operation and can lead to partial burn, misfire, and knock. Predicting CCV numerically is extremely challenging due to two key reasons. Firstly, high-fidelity methods such as large eddy simulation (LES) are required to accurately resolve the incylinder turbulent flowfield both spatially and temporally. Secondly, CCV is experienced over long timescales and hence the simulations need to be performed for hundreds of consecutive cycles. Ameen et al. (Int. J. Eng. Res., 2017) developed a parallel perturbation model (PPM) approach to dissociate this long time-scale problem into several shorter timescale problems. The strategy ismore » to perform multiple single-cycle simulations in parallel by effectively perturbing the initial velocity field based on the intensity of the in-cylinder turbulence. This strategy was demonstrated for motored engine and it was shown that the mean and variance of the in-cylinder flowfield was captured reasonably well by this approach. In the present study, this PPM approach is extended to simulate the CCV in a fired port-fuel injected (PFI) SI engine. Two operating conditions are considered – a medium CCV operating case corresponding to 2500 rpm and 16 bar BMEP and a low CCV case corresponding to 4000 rpm and 12 bar BMEP. The predictions from this approach are also shown to be similar to the consecutive LES cycles. Both the consecutive and PPM LES cycles are observed to under-predict the variability in the early stage of combustion. The parallel approach slightly underpredicts the cyclic variability at all stages of combustion as compared to the consecutive LES cycles. However, it is shown that the parallel approach is able to predict the coefficient of variation (COV) of the in-cylinder pressure and burn rate related parameters with sufficient accuracy, and is also able to predict the qualitative trends in CCV with changing operating conditions. The convergence of the statistics predicted by the PPM approach with respect to the number of consecutive cycles required for each parallel simulation is also investigated. It is shown that this new approach is able to give accurate predictions of the CCV in fired engines in less than one-tenth of the time required for the conventional approach of simulating consecutive engine cycles.« less

Stakeholder Analysis for the CF Counter-IED Training Courses

DTIC Science & Technology

2010-05-01

for more than purely research purposes when the experimenter is present. 3.1.3 Learning Style- based Adaptation The Index of Learning Styles (Felder...student. It is recommended that the Adaption Module uses the same ontology based reasoning approach as the Evaluation Module. RacerPro is the recommended...reasoner. RacerPro is used as a system for managing semantic web ontologies based on Web Ontology Language (OWL). The design phase will confirm

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

PubMed Central

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” (p<0.05). The greatest increase occurred in the skill to recognize typical cognitive errors in medicine and to identify risk situations for their occurrence (pre: 2.98±0.92 and retro-pre: 2.64±1.01, respectively, versus post: 4.38±0.88). Based on the ratio of number of words used per keywords used the problem presentation 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 curriculum seems to be desirable. Faculty training would be useful to implement the concept as standardized as possible. PMID:29226234

Elucidating the role of surface chemistry on cationic phosphorus dendrimer-siRNA complexation.

PubMed

Deriu, Marco A; Tsapis, Nicolas; Noiray, Magali; Grasso, Gianvito; El Brahmi, Nabil; Mignani, Serge; Majoral, Jean-Pierre; Fattal, Elias; Danani, Andrea

2018-06-14

In the field of dendrimers targeting small interfering RNA (siRNA) delivery, dendrimer structural properties, such as the flexibility/rigidity ratio, play a crucial role in the efficiency of complexation. However, advances in organic chemistry have enabled the development of dendrimers that differ only by a single atom on their surface terminals. This is the case for cationic phosphorus dendrimers functionalized with either pyrrolidinium (DP) or morpholinium (DM) terminal groups. This small change was shown to strongly affect the dendrimer-siRNA complexation, leading to more efficient anti-inflammatory effects in the case of DP. Reasons for this different behavior can hardly be inferred only by biological in vitro and in vivo experiments due to the high number of variables and complexity of the investigated biological system. However, an understanding of how small chemical surface changes may completely modify the overall dendrimer-siRNA complexation is a significant breakthrough towards the design of efficient dendrimers for nucleic acid delivery. Herein, we present experimental and computational approaches based on isothermal titration calorimetry and molecular dynamics simulations to elucidate the molecular reasons behind different efficiencies and activities of DP and DM. Results of the present research highlight how chemical surface modifications may drive the overall dendrimer-siRNA affinity by influencing enthalpic and entropic contributions of binding free energy. Moreover, this study elucidates molecular reasons related to complexation stoichiometry that may be crucial in determining the dendrimer complexation efficiency.

Value of Construction Company and its Dependence on Significant Variables

NASA Astrophysics Data System (ADS)

Vítková, E.; Hromádka, V.; Ondrušková, E.

2017-10-01

The paper deals with the value of the construction company assessment respecting usable approaches and determinable variables. The reasons of the value of the construction company assessment are different, but the most important reasons are the sale or the purchase of the company, the liquidation of the company, the fusion of the company with another subject or the others. According the reason of the value assessment it is possible to determine theoretically different approaches for valuation, mainly it concerns about the yield method of valuation and the proprietary method of valuation. Both approaches are dependant of detailed input variables, which quality will influence the final assessment of the company´s value. The main objective of the paper is to suggest, according to the analysis, possible ways of input variables, mainly in the form of expected cash-flows or the profit, determination. The paper is focused mainly on methods of time series analysis, regression analysis and mathematical simulation utilization. As the output, the results of the analysis on the case study will be demonstrated.

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

PubMed

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 research on clinical reasoning, by suggesting that intuition involves a complex constellation of concepts important to how the construct of evidence is understood. The list of concepts the study generated offers a basis for reflection on the nature of evidence in diagnostic reasoning and the importance of intuition to that reasoning.

Priority-setting and hospital strategic planning: a qualitative case study.

PubMed

Martin, Douglas; Shulman, Ken; Santiago-Sorrell, Patricia; Singer, Peter

2003-10-01

To describe and evaluate the priority-setting element of a hospital's strategic planning process. Qualitative case study and evaluation against the conditions of 'accountability for reasonableness' of a strategic planning process at a large urban university-affiliated hospital. The hospital's strategic planning process met the conditions of 'accountability for reasonableness' in large part. Specifically: the hospital based its decisions on reasons (both information and criteria) that the participants felt were relevant to the hospital; the number and type of participants were very extensive; the process, decisions and reasons were well communicated throughout the organization, using multiple communication vehicles; and the process included an ethical framework linked to an effort to evaluate and improve the process. However, there were opportunities to improve the process, particularly by giving participants more time to absorb the information relevant to priority-setting decisions, more time to take difficult decisions and some means to appeal or revise decisions. A case study linked to an evaluation using 'accountability for reasonableness' can serve to improve priority-setting in the context of hospital strategic planning.

Probing student reasoning approaches through the lens of dual-process theories: A case study in buoyancy

NASA Astrophysics Data System (ADS)

Gette, Cody R.; Kryjevskaia, Mila; Stetzer, MacKenzie R.; Heron, Paula R. L.

2018-06-01

A growing body of scholarly work indicates that student performance on physics problems stems from many factors, including relevant conceptual understanding. However, in contexts in which significant conceptual difficulties have been documented via research, it can be difficult to pinpoint and isolate such factors because students' written and interview responses rarely reveal the full richness of their conscious and, perhaps more importantly, subconscious reasoning paths. In this investigation, informed by dual-process theories of reasoning and decision making as well as the theoretical construct of accessibility, we conducted a series of experiments in order to gain greater insight into the factors impacting student performance on the "five-block problem," which has been used in the literature to probe student thinking about buoyancy. In particular, we examined both the impact of problem design (including salient features and cueing) and the impact of targeted instruction focused on density-based arguments for sinking and floating and on neutral buoyancy. The investigation found that instructional modifications designed to remove the strong intuitive appeal of the first-available response led to significantly improved performance, without improving student conceptual understanding of the requisite buoyancy concepts. As such, our findings represent an important first step in identifying systematic strategies for using theories from cognitive science to guide the development and refinement of research-based instructional materials.

Percutaneous endoscopic lumbar discectomy via contralateral approach: a technical case report.

PubMed

Kim, Jin-Sung; Choi, Gun; Lee, Sang-Ho

2011-08-01

Technical case report. The authors report a new percutaneous endoscopic lumbar discectomy (PELD) technique for the treatment of lumbar disc herniation via a contralateral approach. When there are highly down-migrated lumbar disc herniation along just medial to pedicle and narrow ipsilateral intervertebral foramen, the conventional PELD is not easily accessible via ipsilateral transforaminal route. Five patients manifested gluteal and leg pain because of a soft disc herniation at the L4-L5 level. Transforaminal PELD via a contralateral approach was performed to remove the herniated fragment, achieving complete decompression of the nerve root. The symptom was relieved and the patient was discharged the next day. When a conventional transforaminal PELD is difficult because of some anatomical reasons, PELD via a contralateral route could be a good alternative option in selected cases.

DOE Zero Energy Ready Home Case Study: Amaris Custom Homes, St.Paul, Minnesota; DOE Zero Energy Ready Home Case Study, Energy Efficiency & Renewable Energy (EERE)

DOE Office of Scientific and Technical Information (OSTI.GOV)

2015-06-01

For this project Amaris worked with U.S. Department of Energy (DOE) team, NorthernSTAR Building America Partnership, to approach zero energy in Minnesota's cold climate using reasonable, cost-effective, and replicable construction materials and practices. The result is a passive solar, super-efficient 3542-ft2 walkout rambler with all the creature comforts.

The harms of enhancement and the conclusive reasons view.

PubMed

Douglas, Thomas

2015-01-01

Many critics of bioenhancement go to considerable lengths to establish the existence of reasons against pursuing bioenhancements but do little to establish the absence of reasons in favor. This suggests that they accept what Allen Buchanan has called the conclusive reasons view (CRV). According to this view, our reasons against bioenhancement are obviously decisive, so there is no need to balance them against countervailing reasons. Buchanan criticizes the CRV by showing that the reasons most commonly adduced against bioenhancement are not decisive, or, at least, not obviously so. In this article, I suggest that both Buchanan and the authors to whom he is responding underestimate the strength of the case for the CRV. There are, I argue, harm-based reasons against bioenhancement that provide stronger support to the CRV than the reasons that have most often been adduced by critics of enhancement. However, I then argue that even these harm-based reasons are not obviously decisive. Thus, I ultimately agree with Buchanan about the falsity of the CRV, though I disagree with him about the reasons for its falsity.

An efficient numerical method for solving the Boltzmann equation in multidimensions

NASA Astrophysics Data System (ADS)

Dimarco, Giacomo; Loubère, Raphaël; Narski, Jacek; Rey, Thomas

2018-01-01

In this paper we deal with the extension of the Fast Kinetic Scheme (FKS) (Dimarco and Loubère, 2013 [26]) originally constructed for solving the BGK equation, to the more challenging case of the Boltzmann equation. The scheme combines a robust and fast method for treating the transport part based on an innovative Lagrangian technique supplemented with conservative fast spectral schemes to treat the collisional operator by means of an operator splitting approach. This approach along with several implementation features related to the parallelization of the algorithm permits to construct an efficient simulation tool which is numerically tested against exact and reference solutions on classical problems arising in rarefied gas dynamic. We present results up to the 3 D × 3 D case for unsteady flows for the Variable Hard Sphere model which may serve as benchmark for future comparisons between different numerical methods for solving the multidimensional Boltzmann equation. For this reason, we also provide for each problem studied details on the computational cost and memory consumption as well as comparisons with the BGK model or the limit model of compressible Euler equations.

Surgical approach in treatment of translation/rotation injuries of the lower cervical spine in 21 patients.

PubMed

Llácer-Ortega, Jose L; Riesgo-Suárez, Pedro; Piquer-Belloch, Jose; Rovira-Lillo, Vicente

2012-05-01

The management of lower cervical spine injuries with a dislocation of one or both facet joints and a displacement of a vertebra over the adjacent stills generates considerable controversy. We describe our experience in surgical approach of these injuries. We present 21 cases treated between 2003-2010. Neurological status was evaluated with Frankel scale. Diagnosis was done by radiograph (XR), computed tomography (CT) and/or magnetic resonance image (MRI). Cervical traction was placed in 10 cases before surgery. Posterior and/or anterior approach was used for reduction and stabilization. The 21 cases presented were treated by surgery. Posterior approach was initially used in 17 cases and complete reduction was achieved in 13 of them. The 4 cases where we only got a partial reduction, surgery had to be delayed for different reasons. Anterior approach was initially used in 4 of the 21 cases. In 3 of them, reduction was previously obtained by traction and the fourth case anterior approach was used initially due to an important spinal cord compression. Permanent stabilization was achieved in 19 of the 21 cases. In 1 of the other 2 cases an important deformity was detected after the anterior approach. The other case had a minimal progression after a posterior approach with no increase in successive check-ups. In the first 10 cases, we used traction before surgery but reduction was achieved only in 3 of them. As the number of cases increased we rather used posterior approach in the first place, without even trying a preoperative traction. There was no case of neurological deterioration after surgery. Translation/rotation injuries of the lower cervical spine are unstable and surgical treatment must be indicated. It is our impression that posterior approach allows a better reduction and stabilization of this injuries and should be used initially without even trying a preoperative traction. Copyright © 2011 Sociedad Española de Neurocirugía. Published by Elsevier España. All rights reserved.

Context Impact of Clinical Scenario on Knowledge Transfer and Reasoning Capacity in a Medical Problem-Based Learning Curriculum

ERIC Educational Resources Information Center

Collard, A.; Brédart, S.; Bourguignon, J.-P.

2016-01-01

Since 2000, the faculty of Medicine at the University of Liège has integrated problem-based learning (PBL) seminars from year two to seven in its seven-year curriculum. The PBL approach has been developed to facilitate students' acquisition of reasoning capacity. This contextualized learning raises the question of the de- and re-contextualization…

Advancing clinical reasoning in virtual patients - development and application of a conceptual framework.

PubMed

Hege, Inga; Kononowicz, Andrzej A; Berman, Norman B; Lenzer, Benedikt; Kiesewetter, Jan

2018-01-01

Background: Clinical reasoning is a complex skill students have to acquire during their education. For educators it is difficult to explain their reasoning to students, because it is partly an automatic and unconscious process. Virtual Patients (VPs) are used to support the acquisition of clinical reasoning skills in healthcare education. However, until now it remains unclear which features or settings of VPs optimally foster clinical reasoning. Therefore, our aims were to identify key concepts of the clinical reasoning process in a qualitative approach and draw conclusions on how each concept can be enhanced to advance the learning of clinical reasoning with virtual patients. Methods: We chose a grounded theory approach to identify key categories and concepts of learning clinical reasoning and develop a framework. Throughout this process, the emerging codes were discussed with a panel of interdisciplinary experts. In a second step we applied the framework to virtual patients. Results: Based on the data we identified the core category as the "multifactorial nature of learning clinical reasoning". This category is reflected in the following five main categories: Psychological Theories, Patient-centeredness, Context, Learner-centeredness, and Teaching/Assessment. Each category encompasses between four and six related concepts. Conclusions: With our approach we were able to elaborate how key categories and concepts of clinical reasoning can be applied to virtual patients. This includes aspects such as allowing learners to access a large number of VPs with adaptable levels of complexity and feedback or emphasizing dual processing, errors, and uncertainty.

Advancing clinical reasoning in virtual patients – development and application of a conceptual framework

PubMed Central

Hege, Inga; Kononowicz, Andrzej A.; Berman, Norman B.; Lenzer, Benedikt; Kiesewetter, Jan

2018-01-01

Background: Clinical reasoning is a complex skill students have to acquire during their education. For educators it is difficult to explain their reasoning to students, because it is partly an automatic and unconscious process. Virtual Patients (VPs) are used to support the acquisition of clinical reasoning skills in healthcare education. However, until now it remains unclear which features or settings of VPs optimally foster clinical reasoning. Therefore, our aims were to identify key concepts of the clinical reasoning process in a qualitative approach and draw conclusions on how each concept can be enhanced to advance the learning of clinical reasoning with virtual patients. Methods: We chose a grounded theory approach to identify key categories and concepts of learning clinical reasoning and develop a framework. Throughout this process, the emerging codes were discussed with a panel of interdisciplinary experts. In a second step we applied the framework to virtual patients. Results: Based on the data we identified the core category as the "multifactorial nature of learning clinical reasoning". This category is reflected in the following five main categories: Psychological Theories, Patient-centeredness, Context, Learner-centeredness, and Teaching/Assessment. Each category encompasses between four and six related concepts. Conclusions: With our approach we were able to elaborate how key categories and concepts of clinical reasoning can be applied to virtual patients. This includes aspects such as allowing learners to access a large number of VPs with adaptable levels of complexity and feedback or emphasizing dual processing, errors, and uncertainty. PMID:29497697

Analysis of students’ mathematical reasoning

NASA Astrophysics Data System (ADS)

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.

Case-based Reasoning for Automotive Engine Performance Tune-up

NASA Astrophysics Data System (ADS)

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

2010-05-01

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.

A Pilot Study on Modeling of Diagnostic Criteria Using OWL and SWRL.

PubMed

Hong, Na; Jiang, Guoqian; Pathak, Jyotishiman; Chute, Christopher G

2015-01-01

The objective of this study is to describe our efforts in a pilot study on modeling diagnostic criteria using a Semantic Web-based approach. We reused the basic framework of the ICD-11 content model and refined it into an operational model in the Web Ontology Language (OWL). The refinement is based on a bottom-up analysis method, in which we analyzed data elements (including value sets) in a collection (n=20) of randomly selected diagnostic criteria. We also performed a case study to formalize rule logic in the diagnostic criteria of metabolic syndrome using the Semantic Web Rule Language (SWRL). The results demonstrated that it is feasible to use OWL and SWRL to formalize the diagnostic criteria knowledge, and to execute the rules through reasoning.

An Algorithm Using Twelve Properties of Antibiotics to Find the Recommended Antibiotics, as in CPGs

PubMed Central

Tsopra, R.; Venot, A.; Duclos, C.

2014-01-01

Background Clinical Decision Support Systems (CDSS) incorporating justifications, updating and adjustable recommendations can considerably improve the quality of healthcare. We propose a new approach to the design of CDSS for empiric antibiotic prescription, based on implementation of the deeper medical reasoning used by experts in the development of clinical practice guidelines (CPGs), to deduce the recommended antibiotics. Methods We investigated two methods (“exclusion” versus “scoring”) for reproducing this reasoning based on antibiotic properties. Results The “exclusion” method reproduced expert reasoning the more accurately, retrieving the full list of recommended antibiotics for almost all clinical situations. Discussion This approach has several advantages: (i) it provides convincing explanations for physicians; (ii) updating could easily be incorporated into the CDSS; (iii) it can provide recommendations for clinical situations missing from CPGs. PMID:25954422

Learning material recommendation based on case-based reasoning similarity scores

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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.

40 CFR 1502.22 - Incomplete or unavailable information.

Code of Federal Regulations, 2013 CFR

2013-07-01

... approaches or research methods generally accepted in the scientific community. For the purposes of this... credible scientific evidence which is relevant to evaluating the reasonably foreseeable significant adverse... scientific evidence, is not based on pure conjecture, and is within the rule of reason. (c) The amended...

40 CFR 1502.22 - Incomplete or unavailable information.

Code of Federal Regulations, 2014 CFR

2014-07-01

... approaches or research methods generally accepted in the scientific community. For the purposes of this... credible scientific evidence which is relevant to evaluating the reasonably foreseeable significant adverse... scientific evidence, is not based on pure conjecture, and is within the rule of reason. (c) The amended...

40 CFR 1502.22 - Incomplete or unavailable information.

Code of Federal Regulations, 2012 CFR

2012-07-01

... approaches or research methods generally accepted in the scientific community. For the purposes of this... credible scientific evidence which is relevant to evaluating the reasonably foreseeable significant adverse... scientific evidence, is not based on pure conjecture, and is within the rule of reason. (c) The amended...

40 CFR 1502.22 - Incomplete or unavailable information.

Code of Federal Regulations, 2010 CFR

2010-07-01

... approaches or research methods generally accepted in the scientific community. For the purposes of this... credible scientific evidence which is relevant to evaluating the reasonably foreseeable significant adverse... scientific evidence, is not based on pure conjecture, and is within the rule of reason. (c) The amended...

40 CFR 1502.22 - Incomplete or unavailable information.

Code of Federal Regulations, 2011 CFR

2011-07-01

... approaches or research methods generally accepted in the scientific community. For the purposes of this... credible scientific evidence which is relevant to evaluating the reasonably foreseeable significant adverse... scientific evidence, is not based on pure conjecture, and is within the rule of reason. (c) The amended...

16 CFR 306.5 - Automotive fuel rating.

Code of Federal Regulations, 2011 CFR

2011-01-01

... fuels other than biodiesel blends and biomass-based diesel blends, you must possess a reasonable basis... alternative liquid automotive fuel that you must disclose. In the case of biodiesel blends, you must possess a reasonable basis, consisting of competent and reliable evidence, for the percentage of biodiesel contained in...

Male/Female Differences in Perceptions and Effects of Hostile Environment Sexual Harassment: "Reasonable" Assumptions?

ERIC Educational Resources Information Center

Thacker, Rebecca A.; Gohmann, Stephen F.

1993-01-01

Discusses the "reasonable woman" standard in sexual harassment cases and gender-based differences in defining harassment. Investigates the issue of these differences in the emotional and psychological effects of hostile environments, using data from a survey of 8,523 public employees. (SK)

Development and Validation of a Tool to Evaluate the Evolution of Clinical Reasoning in Trauma Using Virtual Patients.

PubMed

Fleiszer, David; Hoover, Michael L; Posel, Nancy; Razek, Tarek; Bergman, Simon

Undergraduate medical students at a large academic trauma center are required to manage a series of online virtual trauma patients as a mandatory exercise during their surgical rotation. Clinical reasoning during undergraduate medical education can be difficult to assess. The purpose of the study was to determine whether we could use components of the students' virtual patient management to measure changes in their clinical reasoning over the course of the clerkship year. In order to accomplish this, we decided to determine if the use of scoring rubrics could change the traditional subjective assessment to a more objective evaluation. Two groups of students, one at the beginning of clerkship (Juniors) and one at the end of clerkship (Seniors), were chosen. Each group was given the same virtual patient case, a clinical scenario based on the Advanced Trauma Life Support (ATLS) Primary Trauma Survey, which had to be completed during their trauma rotation. The learner was required to make several key patient management choices based on their clinical reasoning, which would take them along different routes through the case. At the end of the case they had to create a summary report akin to sign-off. These summaries were graded independently by two domain "Experts" using a traditional subjective surgical approach to assessment and by two "Non-Experts" using two internally validated scoring rubrics. One rubric assessed procedural or domain knowledge (Procedural Rubric), while the other rubric highlighted semantic qualifiers (Semantic Rubric). Each of the rubrics was designed to reflect established components of clinical reasoning. Student's t-tests were used to compare the rubric scores for the two groups and Cohen's d was used to determine effect size. Kendall's τ was used to compare the difference between the two groups based on the "Expert's" subjective assessment. Inter-rater reliability (IRR) was determined using Cronbach's alpha. The Seniors did better than the Juniors with respect to "Procedural" issues but not for "Semantic" issues using the rubrics as assessed by the "Non-Experts". The average Procedural rubric score for the Senior group was 59% ± 13% while for the junior group, it was 51% ± 12% (t (80) = 2.715; p = 0.008; Cohen's d = 1.53). The average Semantic rubric score for the Senior group was 31% ± 15% while for the Junior group, it was 28% ± 14% (t (80) = 1.010; p = .316, ns). There was no statistical difference in the marks given to the Senior versus Junior groups by the "Experts" (Kendall's τ = 0.182, p = 0.07). The IRR between the "Non-Experts" using the rubrics was higher than the IRR of the "Experts" using the traditional surgical approach to assessment. The Cronbach's alpha for the Procedural and Semantic rubrics was 0.94 and 0.97, respectively, indicating very high IRR. The correlation between the Procedural rubric scores and "Experts" assessment was approximately r = 0.78, and that between the Semantic rubric and the "Experts" assessment was roughly r = 0.66, indicating high concurrent validity for the Procedural rubric and moderately high validity for the Semantic rubric. Clinical reasoning, as measured by some of its "procedural" features, improves over the course of the clerkship year. Rubrics can be created to objectively assess the summary statement of an online interactive trauma VP for "procedural" issues but not for "semantic" issues. Using IRR as a measure, the quality of assessment is improved using the rubrics. The "Procedural" rubric appears to measure changes in clinical reasoning over the course of 3rd-year undergraduate clinical studies. Copyright © 2017 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Assessing clinical reasoning (ASCLIRE): Instrument development and validation.

PubMed

Kunina-Habenicht, Olga; Hautz, Wolf E; Knigge, Michel; Spies, Claudia; Ahlers, Olaf

2015-12-01

Clinical reasoning is an essential competency in medical education. This study aimed at developing and validating a test to assess diagnostic accuracy, collected information, and diagnostic decision time in clinical reasoning. A norm-referenced computer-based test for the assessment of clinical reasoning (ASCLIRE) was developed, integrating the entire clinical decision process. In a cross-sectional study participants were asked to choose as many diagnostic measures as they deemed necessary to diagnose the underlying disease of six different cases with acute or sub-acute dyspnea and provide a diagnosis. 283 students and 20 content experts participated. In addition to diagnostic accuracy, respective decision time and number of used relevant diagnostic measures were documented as distinct performance indicators. The empirical structure of the test was investigated using a structural equation modeling approach. Experts showed higher accuracy rates and lower decision times than students. In a cross-sectional comparison, the diagnostic accuracy of students improved with the year of study. Wrong diagnoses provided by our sample were comparable to wrong diagnoses in practice. We found an excellent fit for a model with three latent factors-diagnostic accuracy, decision time, and choice of relevant diagnostic information-with diagnostic accuracy showing no significant correlation with decision time. ASCLIRE considers decision time as an important performance indicator beneath diagnostic accuracy and provides evidence that clinical reasoning is a complex ability comprising diagnostic accuracy, decision time, and choice of relevant diagnostic information as three partly correlated but still distinct aspects.

GhostWriter-2.0: Product Reviews with Case-Based Support

NASA Astrophysics Data System (ADS)

Bridge, Derek; Healy, Paul

A lot of user-generated content on the Web takes the form of records of personal experiences. Case-Based Reasoning offers a way of helping one user to reuse another's experiences from the Web. In this paper, we present GhostWriter-2.0, a Case-Based Reasoning system that supports a user who is writing a product review. GhostWriter-2.0 makes suggestions to the user, in the form of short phrases that are mined from other reviews. The purpose of the suggestions is to prompt the user to write a more comprehensive and helpful review than she might otherwise have done. We explain how GhostWriter-2.0's case base is populated with relevant and helpful reviews from Amazon. We show how it extracts and scores phrases in these reviews to decide which to suggest to the user.We report a trial with real users, in which users made greater use of GhostWriter-2.0's suggested phrases than they did of phrases suggested by a system that used a more random form of selection.

Case-Based Reasoning in Mixed Paradigm Settings and with Learning

DTIC Science & Technology

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

Timing of Surgery for Spinal Fractures Associated with Systemic Trauma: A Need for a Strategic and Systemic Approach.

PubMed

Koksal, Ismet; Alagoz, Fatih; Celik, Haydar; Yildirim, Ali Erdem; Akin, Tezcan; Guvenc, Yahya; Karatay, Mete; Erdem, Yavuz

An underestimated evaluation of systemic organs in cases with spinal fractures might jeopardize the intervention for treatment and future complications with an increased morbidity and mortality are almost warranted. In the present study, a retrospective analysis of spinal fracture cases associated with systemic trauma was performed to assess surgical success. A retrospective analysis of patients with thoracolumbar fractures who were admitted to the emergency unit between September 2012 and September 2014 was used for the study. The cases were categorized according to age, sex, reason of trauma, associated trauma, neurological condition and treatment details and results were analysed using SPSS 14.0 for Windows. The most common reason of trauma is detected as falls in 101 cases (64.3%). Radiological evaluation of spinal fractures revealed a compression fracture in 106 cases (67.5%) and other fractures in 51 cases (32.5%). Surgical treatment for spinal fracture was performed in 60.5% of the cases and conservative approach was preferred in 39.5% cases. In non-compressive spinal fractures, an associated pathology like head trauma, lower extremity fracture or neurological deficit was found to be higher in incidence (p < 0.05). Necessity for surgical intervention was found to be more prominent in this group (p < 0.05). However, the fracture type was not found to be associated with morbidity and mortality (p < 0.05). A surgical intervention for a spinal fracture necessitating surgery should rather be performed right after stabilization of the systemic condition which might be associated with decreased morbidity and mortality.

The Insignificance of Thresholds in Environmental Impact Assessment: An Illustrative Case Study in Canada

NASA Astrophysics Data System (ADS)

Murray, Cathryn Clarke; Wong, Janson; Singh, Gerald G.; Mach, Megan; Lerner, Jackie; Ranieri, Bernardo; Peterson St-Laurent, Guillaume; Guimaraes, Alice; Chan, Kai M. A.

2018-06-01

Environmental assessment is the process that decision-makers rely on to predict, evaluate, and prevent biophysical, social, and economic impacts of potential project developments. The determination of significance in environmental assessment is central to environmental management in many nations. We reviewed ten recent environmental impact assessments from British Columbia, Canada and systematically reviewed and scored significance determination and the approaches used by assessors, the use of thresholds in significance determination, threshold exceedances, and the outcomes. Findings of significant impacts were exceedingly rare and practitioners used a combination of significance determination approaches, most commonly relying upon reasoned argumentation. Quantitative thresholds were rarely employed, with less than 10% of the valued components evaluated using thresholds. Even where quantitative thresholds for significance were exceeded, in every case practitioners used a variety of rationales to demote negative impacts to non-significance. These reasons include combinations of scale (temporal and spatial) of impacts, an already exceeded baseline, model uncertainty and/or substituting less stringent thresholds. Governments and agencies can better protect resources by requiring clear and defensible significance determinations, by making government-defined thresholds legally enforceable and accountable, and by requiring or encouraging significance determination through inclusive and collaborative approaches.

Constraint reasoning in deep biomedical models.

PubMed

Cruz, Jorge; Barahona, Pedro

2005-05-01

Deep biomedical models are often expressed by means of differential equations. Despite their expressive power, they are difficult to reason about and make decisions, given their non-linearity and the important effects that the uncertainty on data may cause. The objective of this work is to propose a constraint reasoning framework to support safe decisions based on deep biomedical models. The methods used in our approach include the generic constraint propagation techniques for reducing the bounds of uncertainty of the numerical variables complemented with new constraint reasoning techniques that we developed to handle differential equations. The results of our approach are illustrated in biomedical models for the diagnosis of diabetes, tuning of drug design and epidemiology where it was a valuable decision-supporting tool notwithstanding the uncertainty on data. The main conclusion that follows from the results is that, in biomedical decision support, constraint reasoning may be a worthwhile alternative to traditional simulation methods, especially when safe decisions are required.

Towards case-based medical learning in radiological decision making using content-based image retrieval

PubMed Central

2011-01-01

Background Radiologists' training is based on intensive practice and can be improved with the use of diagnostic training systems. However, existing systems typically require laboriously prepared training cases and lack integration into the clinical environment with a proper learning scenario. Consequently, diagnostic training systems advancing decision-making skills are not well established in radiological education. Methods We investigated didactic concepts and appraised methods appropriate to the radiology domain, as follows: (i) Adult learning theories stress the importance of work-related practice gained in a team of problem-solvers; (ii) Case-based reasoning (CBR) parallels the human problem-solving process; (iii) Content-based image retrieval (CBIR) can be useful for computer-aided diagnosis (CAD). To overcome the known drawbacks of existing learning systems, we developed the concept of image-based case retrieval for radiological education (IBCR-RE). The IBCR-RE diagnostic training is embedded into a didactic framework based on the Seven Jump approach, which is well established in problem-based learning (PBL). In order to provide a learning environment that is as similar as possible to radiological practice, we have analysed the radiological workflow and environment. Results We mapped the IBCR-RE diagnostic training approach into the Image Retrieval in Medical Applications (IRMA) framework, resulting in the proposed concept of the IRMAdiag training application. IRMAdiag makes use of the modular structure of IRMA and comprises (i) the IRMA core, i.e., the IRMA CBIR engine; and (ii) the IRMAcon viewer. We propose embedding IRMAdiag into hospital information technology (IT) infrastructure using the standard protocols Digital Imaging and Communications in Medicine (DICOM) and Health Level Seven (HL7). Furthermore, we present a case description and a scheme of planned evaluations to comprehensively assess the system. Conclusions The IBCR-RE paradigm incorporates a novel combination of essential aspects of diagnostic learning in radiology: (i) Provision of work-relevant experiences in a training environment integrated into the radiologist's working context; (ii) Up-to-date training cases that do not require cumbersome preparation because they are provided by routinely generated electronic medical records; (iii) Support of the way adults learn while remaining suitable for the patient- and problem-oriented nature of medicine. Future work will address unanswered questions to complete the implementation of the IRMAdiag trainer. PMID:22032775

Towards case-based medical learning in radiological decision making using content-based image retrieval.

PubMed

Welter, Petra; Deserno, Thomas M; Fischer, Benedikt; Günther, Rolf W; Spreckelsen, Cord

2011-10-27

Radiologists' training is based on intensive practice and can be improved with the use of diagnostic training systems. However, existing systems typically require laboriously prepared training cases and lack integration into the clinical environment with a proper learning scenario. Consequently, diagnostic training systems advancing decision-making skills are not well established in radiological education. We investigated didactic concepts and appraised methods appropriate to the radiology domain, as follows: (i) Adult learning theories stress the importance of work-related practice gained in a team of problem-solvers; (ii) Case-based reasoning (CBR) parallels the human problem-solving process; (iii) Content-based image retrieval (CBIR) can be useful for computer-aided diagnosis (CAD). To overcome the known drawbacks of existing learning systems, we developed the concept of image-based case retrieval for radiological education (IBCR-RE). The IBCR-RE diagnostic training is embedded into a didactic framework based on the Seven Jump approach, which is well established in problem-based learning (PBL). In order to provide a learning environment that is as similar as possible to radiological practice, we have analysed the radiological workflow and environment. We mapped the IBCR-RE diagnostic training approach into the Image Retrieval in Medical Applications (IRMA) framework, resulting in the proposed concept of the IRMAdiag training application. IRMAdiag makes use of the modular structure of IRMA and comprises (i) the IRMA core, i.e., the IRMA CBIR engine; and (ii) the IRMAcon viewer. We propose embedding IRMAdiag into hospital information technology (IT) infrastructure using the standard protocols Digital Imaging and Communications in Medicine (DICOM) and Health Level Seven (HL7). Furthermore, we present a case description and a scheme of planned evaluations to comprehensively assess the system. The IBCR-RE paradigm incorporates a novel combination of essential aspects of diagnostic learning in radiology: (i) Provision of work-relevant experiences in a training environment integrated into the radiologist's working context; (ii) Up-to-date training cases that do not require cumbersome preparation because they are provided by routinely generated electronic medical records; (iii) Support of the way adults learn while remaining suitable for the patient- and problem-oriented nature of medicine. Future work will address unanswered questions to complete the implementation of the IRMAdiag trainer.

Spinal meningioma, aortic aneurysms and the missing link of observation: the anchoring heuristic approach.

PubMed

Floros, Nikolaos; Papadakis, Marios; Schelzig, Hubert; Oberhuber, Alexander

2018-03-10

Over the last three decades, the development of systematic and protocol-based algorithms, and advances in available diagnostic tests have become the indispensable parts of practising medicine. Naturally, despite the implementation of meticulous protocols involving diagnostic tests or even trials of empirical therapies, the cause of one's symptoms may still not be obvious. We herein report a case of chronic back pain, which took about 5 years to get accurately diagnosed. The case challenges the diagnostic assumptions and sets ground of discussion for the diagnostic reasoning pitfalls and heuristic biases that mislead the caring physicians and cost years of low quality of life to our patient. This case serves as an example of how anchoring heuristics can interfere in the diagnostic process of a complex and rare entity when combined with a concurrent potentially life-threatening condition. © BMJ Publishing Group Ltd (unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Solving a supply chain scheduling problem with non-identical job sizes and release times by applying a novel effective heuristic algorithm

NASA Astrophysics Data System (ADS)

Pei, Jun; Liu, Xinbao; Pardalos, Panos M.; Fan, Wenjuan; Wang, Ling; Yang, Shanlin

2016-03-01

Motivated by applications in manufacturing industry, we consider a supply chain scheduling problem, where each job is characterised by non-identical sizes, different release times and unequal processing times. The objective is to minimise the makespan by making batching and sequencing decisions. The problem is formalised as a mixed integer programming model and proved to be strongly NP-hard. Some structural properties are presented for both the general case and a special case. Based on these properties, a lower bound is derived, and a novel two-phase heuristic (TP-H) is developed to solve the problem, which guarantees to obtain a worst case performance ratio of ?. Computational experiments with a set of different sizes of random instances are conducted to evaluate the proposed approach TP-H, which is superior to another two heuristics proposed in the literature. Furthermore, the experimental results indicate that TP-H can effectively and efficiently solve large-size problems in a reasonable time.

Agnotology: learning from mistakes

NASA Astrophysics Data System (ADS)

Benestad, R. E.; Hygen, H. O.; van Dorland, R.; Cook, J.; Nuccitelli, D.

2013-05-01

Replication is an important part of science, and by repeating past analyses, we show that a number of papers in the scientific literature contain severe methodological flaws which can easily be identified through simple tests and demonstrations. In many cases, shortcomings are related to a lack of robustness, leading to results that are not universally valid but rather an artifact of a particular experimental set-up. Some examples presented here have ignored data that do not fit the conclusions, and in several other cases, inappropriate statistical methods have been adopted or conclusions have been based on misconceived physics. These papers may serve as educational case studies for why certain analytical approaches sometimes are unsuitable in providing reliable answers. They also highlight the merit of replication. A lack of common replication has repercussions for the quality of the scientific literature, and may be a reason why some controversial questions remain unanswered even when ignorance could be reduced. Agnotology is the study of such ignorance. A free and open-source software is provided for demonstration purposes.

Exploring the Use of Enterprise Content Management Systems in Unification Types of Organizations

NASA Astrophysics Data System (ADS)

Izza Arshad, Noreen; Mehat, Mazlina; Ariff, Mohamed Imran Mohamed

2014-03-01

The aim of this paper is to better understand how highly standardized and integrated businesses known as unification types of organizations use Enterprise Content Management Systems (ECMS) to support their business processes. Multiple case study approach was used to study the ways two unification organizations use their ECMS in their daily work practices. Arising from these case studies are insights into the differing ways in which ECMS is used to support businesses. Based on the comparisons of the two cases, this study proposed that unification organizations may use ECMS in four ways, for: (1) collaboration, (2) information sharing that supports a standardized process structure, (3) building custom workflows that support integrated and standardized processes, and (4) providing links and access to information systems. These findings may guide organizations that are highly standardized and integrated in fashion, to achieve their intended ECMS-use, to understand reasons for ECMS failures and underutilization and to exploit technologies investments.

Variation of student numerical and figural reasoning approaches by pattern generalization type, strategy use and grade level

NASA Astrophysics Data System (ADS)

El Mouhayar, Rabih; Jurdak, Murad

2016-02-01

This paper explored variation of student numerical and figural reasoning approaches across different pattern generalization types and across grade level. An instrument was designed for this purpose. The instrument was given to a sample of 1232 students from grades 4 to 11 from five schools in Lebanon. Analysis of data showed that the numerical reasoning approach seems to be more dominant than the figural reasoning approach for the near and far pattern generalization types but not for the immediate generalization type. The findings showed that for the recursive strategy, the numerical reasoning approach seems to be more dominant than the figural reasoning approach for each of the three pattern generalization types. However, the figural reasoning approach seems to be more dominant than the numerical reasoning approach for the functional strategy, for each generalization type. The findings also showed that the numerical reasoning was more dominant than the figural reasoning in lower grade levels (grades 4 and 5) for each generalization type. In contrast, the figural reasoning became more dominant than the numerical reasoning in the upper grade levels (grades 10 and 11).

A model-based reasoning approach to sensor placement for monitorability

NASA Technical Reports Server (NTRS)

Chien, Steve; Doyle, Richard; Homemdemello, Luiz

1992-01-01

An approach is presented to evaluating sensor placements to maximize monitorability of the target system while minimizing the number of sensors. The approach uses a model of the monitored system to score potential sensor placements on the basis of four monitorability criteria. The scores can then be analyzed to produce a recommended sensor set. An example from our NASA application domain is used to illustrate our model-based approach to sensor placement.

Automatic and controlled components of judgment and decision making.

PubMed

Ferreira, Mario B; Garcia-Marques, Leonel; Sherman, Steven J; Sherman, Jeffrey W

2006-11-01

The categorization of inductive reasoning into largely automatic processes (heuristic reasoning) and controlled analytical processes (rule-based reasoning) put forward by dual-process approaches of judgment under uncertainty (e.g., K. E. Stanovich & R. F. West, 2000) has been primarily a matter of assumption with a scarcity of direct empirical findings supporting it. The present authors use the process dissociation procedure (L. L. Jacoby, 1991) to provide convergent evidence validating a dual-process perspective to judgment under uncertainty based on the independent contributions of heuristic and rule-based reasoning. Process dissociations based on experimental manipulation of variables were derived from the most relevant theoretical properties typically used to contrast the two forms of reasoning. These include processing goals (Experiment 1), cognitive resources (Experiment 2), priming (Experiment 3), and formal training (Experiment 4); the results consistently support the author's perspective. They conclude that judgment under uncertainty is neither an automatic nor a controlled process but that it reflects both processes, with each making independent contributions.

Modular Knowledge Representation and Reasoning in the Semantic Web

NASA Astrophysics Data System (ADS)

Serafini, Luciano; Homola, Martin

Construction of modular ontologies by combining different modules is becoming a necessity in ontology engineering in order to cope with the increasing complexity of the ontologies and the domains they represent. The modular ontology approach takes inspiration from software engineering, where modularization is a widely acknowledged feature. Distributed reasoning is the other side of the coin of modular ontologies: given an ontology comprising of a set of modules, it is desired to perform reasoning by combination of multiple reasoning processes performed locally on each of the modules. In the last ten years, a number of approaches for combining logics has been developed in order to formalize modular ontologies. In this chapter, we survey and compare the main formalisms for modular ontologies and distributed reasoning in the Semantic Web. We select four formalisms build on formal logical grounds of Description Logics: Distributed Description Logics, ℰ-connections, Package-based Description Logics and Integrated Distributed Description Logics. We concentrate on expressivity and distinctive modeling features of each framework. We also discuss reasoning capabilities of each framework.

Deconstructing climate misinformation to identify reasoning errors

NASA Astrophysics Data System (ADS)

Cook, John; Ellerton, Peter; Kinkead, David

2018-02-01

Misinformation can have significant societal consequences. For example, misinformation about climate change has confused the public and stalled support for mitigation policies. When people lack the expertise and skill to evaluate the science behind a claim, they typically rely on heuristics such as substituting judgment about something complex (i.e. climate science) with judgment about something simple (i.e. the character of people who speak about climate science) and are therefore vulnerable to misleading information. Inoculation theory offers one approach to effectively neutralize the influence of misinformation. Typically, inoculations convey resistance by providing people with information that counters misinformation. In contrast, we propose inoculating against misinformation by explaining the fallacious reasoning within misleading denialist claims. We offer a strategy based on critical thinking methods to analyse and detect poor reasoning within denialist claims. This strategy includes detailing argument structure, determining the truth of the premises, and checking for validity, hidden premises, or ambiguous language. Focusing on argument structure also facilitates the identification of reasoning fallacies by locating them in the reasoning process. Because this reason-based form of inoculation is based on general critical thinking methods, it offers the distinct advantage of being accessible to those who lack expertise in climate science. We applied this approach to 42 common denialist claims and find that they all demonstrate fallacious reasoning and fail to refute the scientific consensus regarding anthropogenic global warming. This comprehensive deconstruction and refutation of the most common denialist claims about climate change is designed to act as a resource for communicators and educators who teach climate science and/or critical thinking.

An Evaluation of Curriculum Materials Based Upon the Socio-Scientific Reasoning Model.

ERIC Educational Resources Information Center

Henkin, Gayle; And Others

To address the need to develop a scientifically literate citizenry, the socio-scientific reasoning model was created to guide curriculum development. Goals of this developmental approach include increasing: (1) students' skills in dealing with problems containing multiple interacting variables; (2) students' decision-making skills incorporating a…

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

PubMed

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.

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

PubMed

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.

Automatic Concept-Based Query Expansion Using Term Relational Pathways Built from a Collection-Specific Association Thesaurus

ERIC Educational Resources Information Center

Lyall-Wilson, Jennifer Rae

2013-01-01

The dissertation research explores an approach to automatic concept-based query expansion to improve search engine performance. It uses a network-based approach for identifying the concept represented by the user's query and is founded on the idea that a collection-specific association thesaurus can be used to create a reasonable representation of…

Semantic Web Ontology and Data Integration: a Case Study in Aiding Psychiatric Drug Repurposing.

PubMed

Liang, Chen; Sun, Jingchun; Tao, Cui

2015-01-01

There remain significant difficulties selecting probable candidate drugs from existing databases. We describe an ontology-oriented approach to represent the nexus between genes, drugs, phenotypes, symptoms, and diseases from multiple information sources. We also report a case study in which we attempted to explore candidate drugs effective for bipolar disorder and epilepsy. We constructed an ontology incorporating knowledge between the two diseases and performed semantic reasoning tasks with the ontology. The results suggested 48 candidate drugs that hold promise for further breakthrough. The evaluation demonstrated the validity our approach. Our approach prioritizes the candidate drugs that have potential associations among genes, phenotypes and symptoms, and thus facilitates the data integration and drug repurposing in psychiatric disorders.

The clinician in the driver's seat: part 2 - intelligent uses of space in a drag/drop user-composable electronic health record.

PubMed

Senathirajah, Yalini; Kaufman, David; Bakken, Suzanne

2014-12-01

User-composable approaches provide clinicians with the control to design and assemble information elements on screen via drag/drop. They hold considerable promise for enhancing the electronic-health-records (EHRs) user experience. We previously described this novel approach to EHR design and our illustrative system, MedWISE. The purpose of this paper is to describe clinician users' intelligent uses of space during completion of real patient case studies in a laboratory setting using MedWISE. Thirteen clinicians at a quaternary academic medical center used the system to review four real patient cases. We analyzed clinician utterances, behaviors, screen layouts (i.e., interface designs), and their perceptions associated with completing patient case studies. Clinicians effectively used the system to review all cases. Two coding schemata pertaining to human-computer interaction and diagnostic reasoning were used to analyze the data. Users adopted three main interaction strategies: rapidly gathering items on screen and reviewing ('opportunistic selection' approach); creating highly structured screens ('structured' approach); and interacting with small groups of items in sequence as their case review progressed ('dynamic stage' approach). They also used spatial arrangement in ways predicted by theory and research on workplace spatial arrangement. This includes assignment of screen regions for particular purposes (24% of spatial codes), juxtaposition to facilitate calculation or other cognitive tasks ('epistemic action'), and grouping elements with common meanings or relevance to the diagnostic facets of the case (20.3%). A left-to-right progression of orienting materials, data, and action items or reflection space was a commonly observed pattern. Widget selection was based on user assessment of what information was useful or relevant. We developed and tested an illustrative system that gives clinicians greater control of the EHR, and demonstrated its feasibility for case review by typical clinicians. Producing the simplifying inventions, such as user-composable platforms that shift control to the user, may serve to promote productive EHR use and enhance its value as an instrument of patient care. Copyright © 2014 Elsevier Inc. All rights reserved.

The Clinician in the Driver’s Seat: Part 2 – Intelligent Uses of Space in a Drag/Drop User-Composable Electronic Health Record

PubMed Central

Senathirajah, Yalini; Kaufman, David; Bakken, Suzanne

2018-01-01

User-composable approaches provide clinicians with the control to design and assemble information elements on screen via drag/drop. They hold considerable promise for enhancing the electronic-health-records (EHRs) user experience. We previously described this novel approach to EHR design and our illustrative system, MedWISE. The purpose of this paper is to describe clinician users’ intelligent uses of space during completion of real patient case studies in a laboratory setting using MedWISE. Thirteen clinicians at a quaternary academic medical center used the system to review four real patient cases. We analyzed clinician utterances, behaviors, screen layouts (i.e., interface designs), and their perceptions associated with completing patient case studies. Clinicians effectively used the system to review all cases. Two coding schemata pertaining to human-computer interaction and diagnostic reasoning were used to analyze the data. Users adopted three main interaction strategies: rapidly gathering items on screen and reviewing (‘opportunistic selection’ approach); creating highly structured screens (‘structured’ approach); and interacting with small groups of items in sequence as their case review progressed (‘dynamic stage’ approach). They also used spatial arrangement in ways predicted by theory and research on workplace spatial arrangement. This includes assignment of screen regions for particular purposes (24% of spatial codes), juxtaposition to facilitate calculation or other cognitive tasks (‘epistemic action’), and grouping elements with common meanings or relevance to the diagnostic facets of the case (20.3%). A left-to-right progression of orienting materials, data, and action items or reflection space was a commonly observed pattern. Widget selection was based on user assessment of what information was useful or relevant. We developed and tested an illustrative system that gives clinicians greater control of the EHR, and demonstrated its feasibility for case review by typical clinicians. Producing the simplifying inventions, such as user-composable platforms that shift control to the user, may serve to promote productive EHR use and enhance its value as an instrument of patient care. PMID:25445921

The Developmental Approach to School Readiness.

ERIC Educational Resources Information Center

Ogletree, Earl J.

In the United States, a psychometric psychology dominates the thinking of educators. For traditional, political, and social reasons, developmental psychology rarely informs educational practices. This is the case even though studies show that the inducing of cognitive learning before a child is ready will reduce the child's learning potential and…

10 CFR 455.20 - Contents of State Plan.

Code of Federal Regulations, 2013 CFR

2013-01-01

... one approach may be used for all technical assistance programs in the State. If the State elects to... apportioning the funds that are available for schools and hospitals in a case of severe hardship. Such policies...'s policy regarding reasonable selection of energy conservation measures for study in a technical...

10 CFR 455.20 - Contents of State Plan.

Code of Federal Regulations, 2010 CFR

2010-01-01

... one approach may be used for all technical assistance programs in the State. If the State elects to... apportioning the funds that are available for schools and hospitals in a case of severe hardship. Such policies...'s policy regarding reasonable selection of energy conservation measures for study in a technical...

10 CFR 455.20 - Contents of State Plan.

Code of Federal Regulations, 2014 CFR

2014-01-01

... one approach may be used for all technical assistance programs in the State. If the State elects to... apportioning the funds that are available for schools and hospitals in a case of severe hardship. Such policies...'s policy regarding reasonable selection of energy conservation measures for study in a technical...

10 CFR 455.20 - Contents of State Plan.

Code of Federal Regulations, 2011 CFR

2011-01-01

... one approach may be used for all technical assistance programs in the State. If the State elects to... apportioning the funds that are available for schools and hospitals in a case of severe hardship. Such policies...'s policy regarding reasonable selection of energy conservation measures for study in a technical...

10 CFR 455.20 - Contents of State Plan.

Code of Federal Regulations, 2012 CFR

2012-01-01

... one approach may be used for all technical assistance programs in the State. If the State elects to... apportioning the funds that are available for schools and hospitals in a case of severe hardship. Such policies...'s policy regarding reasonable selection of energy conservation measures for study in a technical...

Nursing Admission Practices to Discern "Fit": A Case Study Exemplar

ERIC Educational Resources Information Center

Sinutko, Jaime M.

2014-01-01

Admission to a baccalaureate nursing school in the United States is currently a challenging proposition for a variety of reasons. This research explored a holistic nursing school admission process at a small, private, baccalaureate college using a retrospective, mixed-method, approach. The holistic method included multiple admission criteria, both…

Facing History and Ourselves: An Instructional Tool for Constructivist Theory.

ERIC Educational Resources Information Center

Presseisen, Barbara Z.; Beyer, Francine S.

This paper presents a study using "Facing History and Ourselves," an interdisciplinary approach to knowledge development that focuses on the period of Nazi totalitarianism as a powerful case study through which teachers can stimulate moral reasoning and develop critical thinking skills in their students. The program encourages teenage…

Major Anthropogenic Causes for and Outcomes of Wild Animal Presentation to a Wildlife Clinic in East Tennessee, USA, 2000–2011

PubMed Central

Schenk, Ashley N.; Souza, Marcy J.

2014-01-01

To determine the reasons for presentation and outcome of wildlife cases in East Tennessee, a retrospective analysis was performed using 14,303 records from cases presented to the wildlife clinic of the University of Tennessee Veterinary Teaching Hospital between 2000 and 2011. The cases were first categorized into amphibian/non-avian reptile, mammal, or avian and then classified into groups based on the primary admitting/presenting sign. There are a variety of reasons animals were presented to the clinic, and some were directly or indirectly anthropogenic in origin, including cat related, dog related, hit by automobile, and other human encounters leading to trauma; of the cases reviewed, 4,443 (31.1%) presented for one of these 4 reasons. Overall case fatality risk in regard to these 4 admitting/presenting signs was 0.519 for the amphibian/non-avian reptile cases, 0.675 for mammal cases, and 0.687 for avian cases. This study confirms the importance of monitoring wildlife morbidity and mortality and of focusing efforts to reduce the anthropogenic threat on native habitats and resident wildlife populations. PMID:24686490

[Surgical approach of internal fixation of maxillofacial fracture].

PubMed

Liu, Dashun; Zhang, Ruizhen; Dong, Xiao

2013-11-01

By summary and analysis of rigid internal fixation for the treatment of maxillofacial fractures incision and exposure, investigate the plate reasonable surgical approach of fracture reduction and fixation titanium. Summary of the 76 surgical cases, Counting the statistics of the number that the surgery ways choose by facial incision and fractures location, analysis of the indications for surgery and the advantages and disadvantages of various surgical approaches. Followed up for more than six months, in order to observe the recovery of occlusal function and the facial cosmetic results. The upper jaw or cheek bone has the more possibility in facial fracture, which used of a small incision hidden under the lip gingival sulcus and lower eyelid. After six months, the facial wound healing recover in good occlusal with no obvious scarring. Reasonable choice of surgical incision can make the fracture site exposure and the facial aesthetic effect into account.

The portfolio approach to competency-based assessment at the Cleveland Clinic Lerner College of Medicine.

PubMed

Dannefer, Elaine F; Henson, Lindsey C

2007-05-01

Despite the rapid expansion of interest in competency-based assessment, few descriptions of assessment systems specifically designed for a competency-based curriculum have been reported. The purpose of this article is to describe the design of a portfolio approach to a comprehensive, competency-based assessment system that is fully integrated with the curriculum to foster an educational environment focused on learning. The educational design goal of the Cleveland Clinic Lerner College of Medicine of Case Western Reserve University was to create an integrated educational program-curriculum and instructional methods, student assessment processes, and learning environment-to prepare medical students for success in careers as physician investigators. The first class in the five-year program matriculated in 2004. To graduate, a student must demonstrate mastery of nine competencies: research, medical knowledge, communication, professionalism, clinical skills, clinical reasoning, health care systems, personal development, and reflective practice. The portfolio provides a tool for collecting and managing multiple types of assessment evidence from multiple contexts and sources within the curriculum to document competence and promote reflective practice skills. This article describes how the portfolio was developed to provide both formative and summative assessment of student achievement in relation to the program's nine competencies.

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

PubMed

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

2008-12-01

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 non-clinical children aged 8-14 years (n = 122). Children completed the anxiety subscales of the Revised Children's Anxiety and Depression Scale (Muris et al. Clin Psychol Psychother 9:430-442, 2002) and provided danger ratings of scenarios that systematically combined objective danger and objective safety information with anxiety-response and positive-response information. These measurements were repeated 10 months later (range 8-11 months). Emotional and parent-based reasoning effects emerged on both occasions. In addition, both effects were modestly stable, but only in case of objective safety. Evidence was found that initial anxiety levels were positively related to emotional reasoning 10 months later. In addition, initial levels of emotional reasoning were positively related to anxiety at a later time, but only when age was taken into account. That is, this relationship changed with increasing age from positive to negative. No significant prospective relationships emerged between anxiety and parent-based reasoning. As yet the clinical implications of these findings are limited, although preliminary evidence indicates that interpretation bias can be modified to decrease anxiety.

Technology and task parameters relating to the effectiveness of the bracing strategy

NASA Technical Reports Server (NTRS)

Book, Wayne J.; Wang, J. J.

1989-01-01

The bracing strategy has been proposed in various forms as a way to improve robot performance. One version of the strategy employs independent stages of motion. The first stage, referred to as the large or bracing arm, carries the second stage of motion. After the first stage has completed its motion it is braced to provide a more rigid base of motion with a more accurate relationship to the parts to be manipulated. The hypothesis is that more rapid completion of certain tasks is possible with lighter arms using the bracing strategy. While it is easy to make conceptual arguments why this should be so, it is less easy to specify even approximately when this will be true for some reasonably generic situation. There is no relevant experience base with bracing arms to be compared to non-bracing arms. Furthermore, if one were interested in obtaining such practical experience, there would be no methodical guidance on the selection of an interesting case, one in which the unproven approach, bracing, can show its superiority. If one such case exists, only the extent of applicability of the new approach is in question. One set of interesting cases is likely to be applications in which a large workspace must be covered, but where a series of small accurate moves will remain within a smaller region of the total workspace. A prototype application with these characteristics is set up and a skeleton design of arms using the competing strategies are compared.

Differential diagnosis and management of an older runner with an atypical neurodynamic presentation: a case for clinical reasoning.

PubMed

Sylvain, Jonathan; Reiman, Michael P

2015-04-01

Case Report. The purpose of this case report is to describe the clinical reasoning process involved with the differential diagnosis and management of a 69 year-old male runner reporting a six month history of insidious onset of left sided low back and buttock pain of low to medium degree of irritability. The case presented describes the utilization of clinical reasoning by a clinician in fellowship training when a patient with atypical adverse neurodynamic dysfunction related to running was encountered. The patient's physical examination was relatively unremarkable. Assessment of the patient's subjective history, self-report measures [Oswestry Disability Index (ODI), global rating of change scale (GROC)], objective findings, and tests and measures led to a working diagnosis of atypical adverse peripheral neurodynamic dysfunction. The lumbar spine, sacroiliac joint, hip joint and lower extremity were ruled out by a comprehensive subjective and objective examination. The diagnosis of adverse neurodynamic dysfunction became a diagnosis of exclusion. Returning two and a half weeks after initial evaluation the patient reported no pain with running. Twelve weeks after the initiation of physical therapy, the patient was contacted via email. He was sent, and asked to fill out an ODI. The patient demonstrated an improvement in ODI from 10% to 2%. He also reported that he continued to run after treatment without pain. Determining the source of a patient complaint can occasionally be an arduous undertaking. Pathological sources of a patient's symptoms may not be easily determined. Development of differential diagnosis and clinical reasoning skills is imperative. Improving clinical reasoning skills requires deliberate practice through reflective thinking before, during, and after patient interactions. Refinement of these skills leads to the primary goal of identifying the patient's clinical presentation, thus matching it with the most effective treatment approach. Level 4.

Evaluation of the approach based on the concept of hyperbolicity breaking for prediction of flooding velocity of both room temperature and cryogenic fluids

NASA Astrophysics Data System (ADS)

Zhou, Rui; Yu, Liu; Xie, Huangjun; Qiu, Limin; Zhi, Xiaoqin; Zhang, Xiaobin

2018-07-01

The theoretical approach for the prediction of flooding velocity based on the concept of hyperbolicity breaking was evaluated in the counter-current two-phase flow. Detailed mathematical derivations of neutral stability condition together with the correlation of the void fraction are presented. The flooding velocity is obtained by assuming that the wavelength at flooding is proportional to the wavelength of the fastest-growing wave at Helmholtz instability. Some available experimental data for different fluid pair flow in inclined tubes is adopted for comparison with the theoretical calculations, which includes the data of water/air, aqueous oleic acid natrium solution/air, Aq. butanol 2%/air and kerosene/air in the published papers, as well as the liquid nitrogen/vapor nitrogen by the present authors. The comparison of flooding velocity proves that the approach can predict the flooding velocity with accepted accuracy for the water/air and liquid nitrogen/vapor nitrogen flow if the tube diameter is greater than 9 mm. While the diameter is smaller than 9 mm, regardless of the inclinations and the fluid pairs, the error becomes larger relative to the cases of diameter larger than 9 mm. The calculations for small diameter cases also fail to predict the critical liquid velocity at which the flooding velocity of gas reaches the maximum value, as revealed by the experiments. The reasons for the increased errors were qualitatively explained.

Modeling the Residual Stresses in Reactive Resins-Based Materials: a Case Study of Photo-Sensitive Composites for Dental Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grassia, Luigi; D'Amore, Alberto

Residual stresses in reactive resins-based composites are associated to the net volumetric contraction (shrinkage) arising during the cross-linking reactions. Depending on the restoration geometry (the ratio of the free surface area to the volume of the cavity) the frozen-in stresses can be as high as the strength of the dental composites. This is the main reason why the effectiveness and then the durability of restorations with composites remains quite lower than those realized with metal alloys based materials. In this paper we first explore the possibility to circumvent the mathematical complexity arising from the determination of residual stresses in reactivemore » systems three-dimensionally constrained. Then, the results of our modeling approach are applied to a series of commercially available composites showing that almost all samples develop residual stresses such that the restoration undergoes failure as soon as it is realized.« less

Classifying Drivers' Cognitive Load Using EEG Signals.

PubMed

Barua, Shaibal; Ahmed, Mobyen Uddin; Begum, Shahina

2017-01-01

A growing traffic safety issue is the effect of cognitive loading activities on traffic safety and driving performance. To monitor drivers' mental state, understanding cognitive load is important since while driving, performing cognitively loading secondary tasks, for example talking on the phone, can affect the performance in the primary task, i.e. driving. Electroencephalography (EEG) is one of the reliable measures of cognitive load that can detect the changes in instantaneous load and effect of cognitively loading secondary task. In this driving simulator study, 1-back task is carried out while the driver performs three different simulated driving scenarios. This paper presents an EEG based approach to classify a drivers' level of cognitive load using Case-Based Reasoning (CBR). The results show that for each individual scenario as well as using data combined from the different scenarios, CBR based system achieved approximately over 70% of classification accuracy.

Ecosystem Services Insights into Water Resources Management in China: A Case of Xi'an City.

PubMed

Liu, Jingya; Li, Jing; Gao, Ziyi; Yang, Min; Qin, Keyu; Yang, Xiaonan

2016-11-24

Global climate and environmental changes are endangering global water resources; and several approaches have been tested to manage and reduce the pressure on these decreasing resources. This study uses the case study of Xi'an City in China to test reasonable and effective methods to address water resource shortages. The study generated a framework combining ecosystem services and water resource management. Seven ecosystem indicators were classified as supply services, regulating services, or cultural services. Index values for each indicator were calculated, and based on questionnaire results, each index's weight was calculated. Using the Likert method, we calculated ecosystem service supplies in every region of the city. We found that the ecosystem's service capability is closely related to water resources, providing a method for managing water resources. Using Xi'an City as an example, we apply the ecosystem services concept to water resources management, providing a method for decision makers.

Self-harming behavior of a parent with borderline personality disorder assessed using revealed preference and attributional approaches: a case study.

PubMed

Tustin, R Don

2002-08-01

This article discusses a case study involving a parent with Borderline Personality Disorder who exhibited self-harming behaviors. Assessment and intervention were based both on a review of the client's attributions about causes of her own behavior as being either internalizing or externalizing, and on a review of motivation of the behaviors using functional analysis. Antecedent situations for self-harming behaviors were identified to provide a basis for reviewing the client's attributions of reasons for disordered behavior. A new technique of functional analysis was applied using the principle of revealed preference arising from behavioral economics. Revealed preference identified outcomes that were valued by the client, enabling new responses to be identified to attain these reinforcers. Attribution re-training was provided. Significant reductions in self-harming behaviors were achieved during brief therapy and were maintained during follow-up.

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

ERIC Educational Resources Information Center

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…

Optimization of wastewater treatment alternative selection by hierarchy grey relational analysis.

PubMed

Zeng, Guangming; Jiang, Ru; Huang, Guohe; Xu, Min; Li, Jianbing

2007-01-01

This paper describes an innovative systematic approach, namely hierarchy grey relational analysis for optimal selection of wastewater treatment alternatives, based on the application of analytic hierarchy process (AHP) and grey relational analysis (GRA). It can be applied for complicated multicriteria decision-making to obtain scientific and reasonable results. The effectiveness of this approach was verified through a real case study. Four wastewater treatment alternatives (A(2)/O, triple oxidation ditch, anaerobic single oxidation ditch and SBR) were evaluated and compared against multiple economic, technical and administrative performance criteria, including capital cost, operation and maintenance (O and M) cost, land area, removal of nitrogenous and phosphorous pollutants, sludge disposal effect, stability of plant operation, maturity of technology and professional skills required for O and M. The result illustrated that the anaerobic single oxidation ditch was the optimal scheme and would obtain the maximum general benefits for the wastewater treatment plant to be constructed.

Dynamic analysis for solid waste management systems: an inexact multistage integer programming approach.

PubMed

Li, Yongping; Huang, Guohe

2009-03-01

In this study, a dynamic analysis approach based on an inexact multistage integer programming (IMIP) model is developed for supporting municipal solid waste (MSW) management under uncertainty. Techniques of interval-parameter programming and multistage stochastic programming are incorporated within an integer-programming framework. The developed IMIP can deal with uncertainties expressed as probability distributions and interval numbers, and can reflect the dynamics in terms of decisions for waste-flow allocation and facility-capacity expansion over a multistage context. Moreover, the IMIP can be used for analyzing various policy scenarios that are associated with different levels of economic consequences. The developed method is applied to a case study of long-term waste-management planning. The results indicate that reasonable solutions have been generated for binary and continuous variables. They can help generate desired decisions of system-capacity expansion and waste-flow allocation with a minimized system cost and maximized system reliability.

Imagination, distributed responsibility and vulnerable technological systems: the case of Snorre A.

PubMed

Coeckelbergh, Mark; Wackers, Ger

2007-06-01

An influential approach to engineering ethics is based on codes of ethics and the application of moral principles by individual practitioners. However, to better understand the ethical problems of complex technological systems and the moral reasoning involved in such contexts, we need other tools as well. In this article, we consider the role of imagination and develop a concept of distributed responsibility in order to capture a broader range of human abilities and dimensions of moral responsibility. We show that in the case of Snorre A, a near-disaster with an oil and gas production installation, imagination played a crucial and morally relevant role in how the crew coped with the crisis. For example, we discuss the role of scenarios and images in the moral reasoning and discussion of the platform crew in coping with the crisis. Moreover, we argue that responsibility for increased system vulnerability, turning an undesired event into a near-disaster, should not be ascribed exclusively, for example to individual engineers alone, but should be understood as distributed between various actors, levels and times. We conclude that both managers and engineers need imagination to transcend their disciplinary perspectives in order to improve the robustness of their organisations and to be better prepared for crisis situations. We recommend that education and training programmes should be transformed accordingly.

Social Case-work in General Practice: An Alternative Approach

PubMed Central

Ratoff, L.; Pearson, Barbara

1970-01-01

During a two-year period a senior case-worker was seconded by a voluntary family case-work agency, the Liverpool Personal Service Society, to work with three general practitioners. The commonest reasons for referral of the 157 new patients to the social worker over this study period were extreme poverty; housing, matrimonial, and psychiatric problems; and problems of fatherless families. The successful and valuable co-operation between the general practitioners, case-worker, and various specialist professional and financial services of the Society have proved that a professional social worker has an important role in the general-practice team. PMID:5420213

Phronesis: practical wisdom the role of professional practice knowledge in the clinical reasoning of Bobath instructors.

PubMed

Vaughan-Graham, Julie; Cott, Cheryl

2017-10-01

Clinical reasoning is an essential aspect of clinical practice, however is largely ignored in the current rehabilitation sciences evidence base. Literature related to clinical reasoning and clinical expertise has evolved concurrently although rehabilitation reasoning frameworks remain relatively generic. The purpose of this study was to explicate the clinical reasoning process of Bobath instructors of a widely used neuro-rehabilitation approach, the Bobath concept. A qualitative interpretive description approach consisting of stimulated recall using video-recorded treatment sessions and in-depth interviews. Purposive sampling was used to recruit members of the International Bobath Instructors Training Association (IBITA). Interview transcripts were transcribed verbatim providing the raw data. Data analysis was progressive, iterative, and inductive. Twenty-two IBITA instructors from 7 different countries participated. Ranging in clinical experience from 12 to 40 years, and instructor experience from 1 to 35 years. Three themes were developed, (a) a Bobath clinical framework, (b) person-centered, and (c) a Bobath reasoning approach, highlighting the role of practical wisdom, phronesis in the clinical reasoning process. In particular the role of visuospatial-kinesthetic perception, an element of technical expertise, was illuminated as an integral aspect of clinical reasoning in this expert group. This study provides an interpretive understanding of the clinical reasoning process used by IBITA instructors illustrating an inactive embodied view of clinical reasoning, specifically the role of phronesis, requiring further investigation in nonexpert Bobath therapists, as well as in novice and experienced therapists in other specialty areas. © 2016 John Wiley & Sons, Ltd.

Case-Based Planning: An Integrated Theory of Planning, Learning and Memory

DTIC Science & Technology

1986-10-01

rtvoeoo oldo II nocomtmry and Idonltly by block numbor) planning Case-based reasoning learning Artificial Intelligence 20. ABSTRACT (Conllnum...Computational Model of Analogical Prob- lem Solving, Proceedings of the Seventh International Joint Conference on Artificial Intelligence ...Understanding and Generalizing Plans., Proceedings of the Eight Interna- tional Joint Conference on Artificial Intelligence , IJCAI, Karlsrhue, Germany

A Semi-Supervised Learning Approach to Enhance Health Care Community–Based Question Answering: A Case Study in Alcoholism

PubMed Central

Klabjan, Diego; Jonnalagadda, Siddhartha Reddy

2016-01-01

Background Community-based question answering (CQA) sites play an important role in addressing health information needs. However, a significant number of posted questions remain unanswered. Automatically answering the posted questions can provide a useful source of information for Web-based health communities. Objective In this study, we developed an algorithm to automatically answer health-related questions based on past questions and answers (QA). We also aimed to understand information embedded within Web-based health content that are good features in identifying valid answers. Methods Our proposed algorithm uses information retrieval techniques to identify candidate answers from resolved QA. To rank these candidates, we implemented a semi-supervised leaning algorithm that extracts the best answer to a question. We assessed this approach on a curated corpus from Yahoo! Answers and compared against a rule-based string similarity baseline. Results On our dataset, the semi-supervised learning algorithm has an accuracy of 86.2%. Unified medical language system–based (health related) features used in the model enhance the algorithm’s performance by proximately 8%. A reasonably high rate of accuracy is obtained given that the data are considerably noisy. Important features distinguishing a valid answer from an invalid answer include text length, number of stop words contained in a test question, a distance between the test question and other questions in the corpus, and a number of overlapping health-related terms between questions. Conclusions Overall, our automated QA system based on historical QA pairs is shown to be effective according to the dataset in this case study. It is developed for general use in the health care domain, which can also be applied to other CQA sites. PMID:27485666

Medical education and cognitive continuum theory: an alternative perspective on medical problem solving and clinical reasoning.

PubMed

Custers, Eugène J F M

2013-08-01

Recently, human reasoning, problem solving, and decision making have been viewed as products of two separate systems: "System 1," the unconscious, intuitive, or nonanalytic system, and "System 2," the conscious, analytic, or reflective system. This view has penetrated the medical education literature, yet the idea of two independent dichotomous cognitive systems is not entirely without problems.This article outlines the difficulties of this "two-system view" and presents an alternative, developed by K.R. Hammond and colleagues, called cognitive continuum theory (CCT). CCT is featured by three key assumptions. First, human reasoning, problem solving, and decision making can be arranged on a cognitive continuum, with pure intuition at one end, pure analysis at the other, and a large middle ground called "quasirationality." Second, the nature and requirements of the cognitive task, as perceived by the person performing the task, determine to a large extent whether a task will be approached more intuitively or more analytically. Third, for optimal task performance, this approach needs to match the cognitive properties and requirements of the task. Finally, the author makes a case that CCT is better able than a two-system view to describe medical problem solving and clinical reasoning and that it provides clear clues for how to organize training in clinical reasoning.

Outline-based morphometrics, an overlooked method in arthropod studies?

PubMed

Dujardin, Jean-Pierre; Kaba, D; Solano, P; Dupraz, M; McCoy, K D; Jaramillo-O, N

2014-12-01

Modern methods allow a geometric representation of forms, separating size and shape. In entomology, as well as in many other fields involving arthropod studies, shape variation has proved useful for species identification and population characterization. In medical entomology, it has been applied to very specific questions such as population structure, reinfestation of insecticide-treated areas and cryptic species recognition. For shape comparisons, great importance is given to the quality of landmarks in terms of comparability. Two conceptually and statistically separate approaches are: (i) landmark-based morphometrics, based on the relative position of a few anatomical "true" or "traditional" landmarks, and (ii) outline-based morphometrics, which captures the contour of forms through a sequence of close "pseudo-landmarks". Most of the studies on insects of medical, veterinary or economic importance make use of the landmark approach. The present survey makes a case for the outline method, here based on elliptic Fourier analysis. The collection of pseudo-landmarks may require the manual digitization of many points and, for this reason, might appear less attractive. It, however, has the ability to compare homologous organs or structures having no landmarks at all. This strength offers the possibility to study a wider range of anatomical structures and thus, a larger range of arthropods. We present a few examples highlighting its interest for separating close or cryptic species, or characterizing conspecific geographic populations, in a series of different vector organisms. In this simple application, i.e. the recognition of close or cryptic forms, the outline approach provided similar scores as those obtained by the landmark-based approach. Copyright © 2014 Elsevier B.V. All rights reserved.

Nurses' decision-making process in cases of physical restraint in acute elderly care: a qualitative study.

PubMed

Goethals, S; Dierckx de Casterlé, B; Gastmans, C

2013-05-01

The increasing vulnerability of patients in acute elderly care requires constant critical reflection in ethically charged situations such as when employing physical restraint. Qualitative evidence concerning nurses' decision making in cases of physical restraint is limited and fragmented. A thorough understanding of nurses' decision-making process could be useful to understand how nurses reason and make decisions in ethically laden situations. The aims of this study were to explore and describe nurses' decision-making process in cases of physical restraint. We used a qualitative interview design inspired by the Grounded Theory approach. Data analysis was guided by the Qualitative Analysis Guide of Leuven. Twelve hospitals geographically spread throughout the five provinces of Flanders, Belgium. Twenty-one acute geriatric nurses interviewed between October 2009 and April 2011 were purposively and theoretically selected, with the aim of including nurses having a variety of characteristics and experiences concerning decisions on using physical restraint. In cases of physical restraint in acute elderly care, nurses' decision making was never experienced as a fixed decision but rather as a series of decisions. Decision making was mostly reasoned upon and based on rational arguments; however, decisions were also made routinely and intuitively. Some nurses felt very certain about their decisions, while others experienced feelings of uncertainty regarding their decisions. Nurses' decision making is an independent process that requires nurses to obtain a good picture of the patient, to be constantly observant, and to assess and reassess the patient's situation. Coming to thoughtful and individualized decisions requires major commitment and constant critical reflection. Copyright © 2012 Elsevier Ltd. All rights reserved.

Spatial information semantic query based on SPARQL

NASA Astrophysics Data System (ADS)

Xiao, Zhifeng; Huang, Lei; Zhai, Xiaofang

2009-10-01

How can the efficiency of spatial information inquiries be enhanced in today's fast-growing information age? We are rich in geospatial data but poor in up-to-date geospatial information and knowledge that are ready to be accessed by public users. This paper adopts an approach for querying spatial semantic by building an Web Ontology language(OWL) format ontology and introducing SPARQL Protocol and RDF Query Language(SPARQL) to search spatial semantic relations. It is important to establish spatial semantics that support for effective spatial reasoning for performing semantic query. Compared to earlier keyword-based and information retrieval techniques that rely on syntax, we use semantic approaches in our spatial queries system. Semantic approaches need to be developed by ontology, so we use OWL to describe spatial information extracted by the large-scale map of Wuhan. Spatial information expressed by ontology with formal semantics is available to machines for processing and to people for understanding. The approach is illustrated by introducing a case study for using SPARQL to query geo-spatial ontology instances of Wuhan. The paper shows that making use of SPARQL to search OWL ontology instances can ensure the result's accuracy and applicability. The result also indicates constructing a geo-spatial semantic query system has positive efforts on forming spatial query and retrieval.

A flowgraph model for bladder carcinoma

PubMed Central

2014-01-01

Background Superficial bladder cancer has been the subject of numerous studies for many years, but the evolution of the disease still remains not well understood. After the tumor has been surgically removed, it may reappear at a similar level of malignancy or progress to a higher level. The process may be reasonably modeled by means of a Markov process. However, in order to more completely model the evolution of the disease, this approach is insufficient. The semi-Markov framework allows a more realistic approach, but calculations become frequently intractable. In this context, flowgraph models provide an efficient approach to successfully manage the evolution of superficial bladder carcinoma. Our aim is to test this methodology in this particular case. Results We have built a successful model for a simple but representative case. Conclusion The flowgraph approach is suitable for modeling of superficial bladder cancer. PMID:25080066

True or false: do 5-year-olds understand belief?

PubMed

Fabricius, William V; Boyer, Ty W; Weimer, Amy A; Carroll, Kathleen

2010-11-01

In 3 studies (N = 188) we tested the hypothesis that children use a perceptual access approach to reason about mental states before they understand beliefs. The perceptual access hypothesis predicts a U-shaped developmental pattern of performance in true belief tasks, in which 3-year-olds who reason about reality should succeed, 4- to 5-year-olds who use perceptual access reasoning should fail, and older children who use belief reasoning should succeed. The results of Study 1 revealed the predicted pattern in 2 different true belief tasks. The results of Study 2 disconfirmed several alternate explanations based on possible pragmatic and inhibitory demands of the true belief tasks. In Study 3, we compared 2 methods of classifying individuals according to which 1 of the 3 reasoning strategies (reality reasoning, perceptual access reasoning, belief reasoning) they used. The 2 methods gave converging results. Both methods indicated that the majority of children used the same approach across tasks and that it was not until after 6 years of age that most children reasoned about beliefs. We conclude that because most prior studies have failed to detect young children's use of perceptual access reasoning, they have overestimated their understanding of false beliefs. We outline several theoretical implications that follow from the perceptual access hypothesis.

Power and Responsibility in Therapy: Integrating Feminism and Multiculturalism

ERIC Educational Resources Information Center

Williams, Elizabeth Nutt; Barber, Jill S.

2004-01-01

The integration of feminist and multicultural approaches to psychotherapy, called for many times, has not yet materialized. This article reviews possible reasons this integration has not taken place and offers an approach to integration based on the guiding principles of power and responsibility, which builds on previous theories and approaches.

Perspective: moving students beyond an organ-based approach when teaching medical interviewing and physical examination skills.

PubMed

Alexander, Erik K

2008-10-01

Medical interviewing and physical examination skills are core pillars of clinical medicine. Though nearly all U.S. medical students participate in preclinical courses designed to teach these skills, medical school faculty often comment that students' abilities remain limited on entering their clinical clerkships. The reason for this contention is not clear.The author briefly describes the current preclinical curricula at most medical schools that are designed to teach patient interviewing and examination. An organ-based curriculum is commonly employed, although the limitations of such an approach readily become apparent. For example, many hospitalized patients do not suffer from single-organ illnesses, but rather from infections or metabolic derangements, which cause numerous abnormalities to several body systems. Furthermore, clinical reasoning skills are rarely taught in such preclinical courses, though these abilities form the foundation for effective doctoring. These findings suggest an opportunity for content development surrounding patient interviewing and examination. The author proposes an educational approach that depicts how the confluence of both content knowledge skills and clinical reasoning skills can work synergistically to enhance preclinical teaching of the medical interview and physical examination.

[Reasons for consulting related to skin-bleaching products used by 104 women in Brazzaville].

PubMed

Gathse, A; Obengui; Ibara, J R

2005-12-01

A prospective survey has been carried out in the Brazzaville (Congo) dermatology service in order to specify dermatosis linked to the use of bleaching agents in 104 Congolese women consulting for this problem. The used bleaching agents were topical corticoids based products for 40 cases, hydroquinone for 32 cases, and hydroquinone associated with topical dermocorticoids for 32 cases. Acne was the most frequent motive for consulting (24%), followed by the paradoxical peri-orbital hyperpigmentation (21.1%), profuse mycosis (16.3%) and vibices(8.6%). The results of this survey were not superimposable to those of Dakar where infectious dermatosis were the first reason for consulting.

What do District Health Planners in Tanzania think about improving priority setting using 'Accountability for Reasonableness'?

PubMed Central

Mshana, Simon; Shemilu, Haji; Ndawi, Benedict; Momburi, Roman; Olsen, Oystein Evjen; Byskov, Jens; Martin, Douglas K

2007-01-01

Background Priority setting in every health system is complex and difficult. In less wealthy countries the dominant approach to priority setting has been Burden of Disease (BOD) and cost-effectiveness analysis (CEA), which is helpful, but insufficient because it focuses on a narrow range of values – need and efficiency – and not the full range of relevant values, including legitimacy and fairness. 'Accountability for reasonableness' is a conceptual framework for legitimate and fair priority setting and is empirically based and ethically justified. It connects priority setting to broader, more fundamental, democratic deliberative processes that have an impact on social justice and equity. Can 'accountability for reasonableness' be helpful for improving priority setting in less wealthy countries? Methods In 2005, Tanzanian scholars from the Primary Health Care Institute (PHCI) conducted 6 capacity building workshops with senior health staff, district planners and managers, and representatives of the Tanzanian Ministry of Health to discussion improving priority setting in Tanzania using 'accountability for reasonableness'. The purpose of this paper is to describe this initiative and the participants' views about the approach. Results The approach to improving priority setting using 'accountability for reasonableness' was viewed by district decision makers with enthusiastic favour because it was the first framework that directly addressed their priority setting concerns. High level Ministry of Health participants were also very supportive of the approach. Conclusion Both Tanzanian district and governmental health planners viewed the 'accountability for reasonableness' approach with enthusiastic favour because it was the first framework that directly addressed their concerns. PMID:17997824

Using rhetorical theory in medical ethics cases.

PubMed

Heifferon, B

2000-01-01

In this paper I argue that rhetorical theory is a valuable tool in medical ethics cases. The case I use as an example is one in which traditional, philosophy-based medical ethics are applied. In this case the traditional ethical approach is not adequate to the task. Key issues and problems are not addressed, resulting in a problem that seems to be solved on the surface, but, when rhetorically analyzed, it's obvious that none of the issues have been resolved in any satisfactory way. By using rhetorical theory, such as that Michel Foucault uses in Power/Knowledge, we discover that the reason this case has not been solved is that the power issues have not been addressed. Using Foucault's concepts of "subjugated knowledge", "local knowledge", "situated knowledge", and "docile bodies", we can tease out the real issues that surface in this ethics case and solve them. Foucault also recommends we use theory as a "toolkit". I propose a model that is a further iteration of this idea. My model uses numerous rhetorical and literary theories, depending on the issues that need to be addressed in each individual medical ethics case. I briefly describe the various theories and include a handout of what the new model of using rhetorical theory in such cases would look like.

Scientific Reasoning for Pre-service Elementary Teachers

NASA Astrophysics Data System (ADS)

Sadaghiani, Homeyra R.

2010-10-01

The objectives of K-12 teacher education science courses often focus on conceptual learning and improving students overall attitude towards science. It is often assumed that with the use of research-based curriculum material and more hands on inquiry approaches, without any explicit instruction, student scientific and critical thinking skills would also be enhanced. In the last three years, we have been investigating student scientific and evidence-based reasoning abilities in a K-8 pre-service science course at Cal Poly Pomona. After recognizing student difficulties understanding the elements of scientific reasoning, we have provided explicit feedback using a rubric to assist students to become more rigorous and reflective thinkers; to use appropriate and accurate vocabulary; exercise evidence-base reasoning; and develop skepticism with respect to their own views. We will share the rubric and report on the preliminary results.

Human rights reasoning and medical law: a sceptical essay.

PubMed

Wall, Jesse

2015-03-01

I am sceptical as to the contribution that human rights can make to our evaluation of medical law. I will argue here that viewing medical law through a human rights framework provides no greater clarity, insight or focus. If anything, human rights reasoning clouds any bioethical or evaluative analysis. In Section 1 of this article, I outline the general structure of human rights reasoning. I will describe human rights reasoning as (a) reasoning from rights that each person has 'by virtue of their humanity', (b) reasoning from rights that provide 'hard to defeat' reasons for action and (c) reasoning from abstract norms to specified duties. I will then argue in Section 2 that, unless we (a) re-conceive of human rights as narrow categories of liberties, it becomes (b) necessary for our human rights reasoning to gauge the normative force of each claim or liberty. When we apply this approach to disputes in medical law, we (in the best case scenario) end up (c) 'looking straight through' the human right to the (disagreement about) values and features that each person has by virtue of their humanity. © 2014 John Wiley & Sons Ltd.

Understanding Preprocedure Patient Flow in IR.

PubMed

Zafar, Abdul Mueed; Suri, Rajeev; Nguyen, Tran Khanh; Petrash, Carson Cope; Fazal, Zanira

2016-08-01

To quantify preprocedural patient flow in interventional radiology (IR) and to identify potential contributors to preprocedural delays. An administrative dataset was used to compute time intervals required for various preprocedural patient-flow processes. These time intervals were compared across on-time/delayed cases and inpatient/outpatient cases by Mann-Whitney U test. Spearman ρ was used to assess any correlation of the rank of a procedure on a given day and the procedure duration to the preprocedure time. A linear-regression model of preprocedure time was used to further explore potential contributing factors. Any identified reason(s) for delay were collated. P < .05 was considered statistically significant. Of the total 1,091 cases, 65.8% (n = 718) were delayed. Significantly more outpatient cases started late compared with inpatient cases (81.4% vs 45.0%; P < .001, χ(2) test). The multivariate linear regression model showed outpatient status, length of delay in arrival, and longer procedure times to be significantly associated with longer preprocedure times. Late arrival of patients (65.9%), unavailability of physicians (18.4%), and unavailability of procedure room (13.0%) were the three most frequently identified reasons for delay. The delay was multifactorial in 29.6% of cases (n = 213). Objective measurement of preprocedural IR patient flow demonstrated considerable waste and highlighted high-yield areas of possible improvement. A data-driven approach may aid efficient delivery of IR care. Copyright © 2016 SIR. Published by Elsevier Inc. All rights reserved.

Theorising and Practitioners in HRD: The Role of Abductive Reasoning

ERIC Educational Resources Information Center

Gold, Jeff; Walton, John; Cureton, Peter; Anderson, Lisa

2011-01-01

Purpose: The purpose of this paper is to argue that abductive reasoning is a typical but usually unrecognised process used by HRD scholars and practitioners alike. Design/methodology/approach: This is a conceptual paper that explores recent criticism of traditional views of theory-building, based on the privileging of scientific theorising, which…

Teachers' Pedagogical Reasoning and Reframing of Practice in Digital Contexts

ERIC Educational Resources Information Center

Holmberg, Jörgen; Fransson, Göran; Fors, Uno

2018-01-01

Purpose: The purpose of this paper is to advance the understanding of teachers' reframing of practice in digital contexts by analysing teachers' pedagogical reasoning processes as they explore ways of using information and communication technologies (ICT) to create added pedagogical value. Design/methodology/approach: A design-based research (DBR)…

A Modeling Approach to the Development of Students' Informal Inferential Reasoning

ERIC Educational Resources Information Center

Doerr, Helen M.; Delmas, Robert; Makar, Katie

2017-01-01

Teaching from an informal statistical inference perspective can address the challenge of teaching statistics in a coherent way. We argue that activities that promote model-based reasoning address two additional challenges: providing a coherent sequence of topics and promoting the application of knowledge to novel situations. We take a models and…

The dawn of science-based moral reasoning.

PubMed

Baschetti, Riccardo

2007-01-01

In 1998, Edward O. Wilson discussed the biological basis of morality, pointed out that the analysis of its material origins should enable us to fashion a wise ethical consensus, and predicted the dawn of science-based moral reasoning. This article testifies that his prediction was right. Morality, being based on altruism and collaboration, evolved as a socially advantageous biological phenomenon aimed at ensuring the survival of our species, which was structured in small groups at high risk of extinction for the 99.5% of its existence. In the last 0.5%, the advent of agriculture resulted in a demographic explosion that impaired human beings' moral discernment, because the socially detrimental consequences of immoral actions, which had been recognised and condemned promptly in small groups consisting of a few tens of members, were diluted among millions of untouched individuals, thereby becoming less easily recognisable. Nowadays, to test the supposed morality of individual actions and government policies, we should use reason or, in doubtful cases, mathematical modelling to determine their predictable effects on the survival of small theoretical communities. Unless we untenably claim that the unlikelihood of extinction of today's immense societies entitles us to overturn the meaning of morality, all actions and policies that would cause the extinction of small communities should be regarded as indisputably immoral. This article also presents some examples of science-based moral arguments showing the immorality of restrictions and bans on research with human embryonic stem cells and demonstrates that the old concept of the "naturalistic fallacy", which philosophers frequently invoke to dismiss any scientific approach to morality, is no longer tenable, because it increasingly emerges to be a proof of what may well be defined the "philosophical fallacy".

A Comparison of Reasoning Processes in a Collaborative Modelling Environment: Learning about genetics problems using virtual chat

NASA Astrophysics Data System (ADS)

Pata, Kai; Sarapuu, Tago

2006-09-01

This study investigated the possible activation of different types of model-based reasoning processes in two learning settings, and the influence of various terms of reasoning on the learners’ problem representation development. Changes in 53 students’ problem representations about genetic issue were analysed while they worked with different modelling tools in a synchronous network-based environment. The discussion log-files were used for the “microgenetic” analysis of reasoning types. For studying the stages of students’ problem representation development, individual pre-essays and post-essays and their utterances during two reasoning phases were used. An approach for mapping problem representations was developed. Characterizing the elements of mental models and their reasoning level enabled the description of five hierarchical categories of problem representations. Learning in exploratory and experimental settings was registered as the shift towards more complex stages of problem representations in genetics. The effect of different types of reasoning could be observed as the divergent development of problem representations within hierarchical categories.

Making a Case for a Blended Approach: The Need for The Design-Based Case Study

ERIC Educational Resources Information Center

Deaton, Cynthia C. M.; Malloy, Jacquelynn A.

2017-01-01

Design-based case studies address research questions that involve instructional innovations within a bounded system. This blend of case study and design-based research provides a systematic approach to examining instructional innovations that are bounded by perspective, context, and time. Design-based case studies provide a framework for engaging…

Trends and Determinants of Familial Consent for Corneal Donation in Chinese.

PubMed

Lee, Allie; Ni, Michael Y; Luk, Amanda C K; Lau, Jessie K P; Lam, Karen S Y; Li, Tom K; Wong, Catherine S M; Wong, Victoria W Y

2017-03-01

Corneal transplantation is the treatment of choice for many corneal diseases. At present, there is a global shortage of corneal transplant tissues, and failure to obtain consent from families of potential donors is a major limiting factor in tissue procurement. All family members of potential donors after cardiac death approached by the local eye bank staff members from January 2008 to December 2014 in Hong Kong were included. Reasons for consent or refusal and sociodemographic details of the deceased and the family members approached were reviewed. Trends in consent rates from 2008 to 2014 were examined. Multivariable logistic regression was performed to examine determinants of donation among cases from 2013 to 2014. A total of 1740 cases were identified. The overall consent rate was 36.8%, and the consent rate did not change significantly over the 7-year study period (P = 0.24). The most common reason for consent by family members was "the wish to help others" (86.0%), and the most common reason for refusal was "traditional Chinese culture to keep the body intact after death" (42.7%). From the multivariable analysis in the subset of cases from 2013 to 2014 (n = 628), family members were more likely to consent when the deceased was female (adjusted odds ratio 1.45, P = 0.03), with a do-not-resuscitate order (adjusted odds ratio 2.27, P < 0.001). The consent rate for eye donation did not change significantly from 2008 to 2014. Our findings suggest that health education and promotion campaigns need to address cultural barriers to organ donation.

Advantages of video trigger in problem-based learning.

PubMed

Chan, Lap Ki; Patil, Nivritti G; Chen, Julie Y; Lam, Jamie C M; Lau, Chak S; Ip, Mary S M

2010-01-01

Traditionally, paper cases are used as 'triggers' to stimulate learning in problem-based learning (PBL). However, video may be a better medium because it preserves the original language, encourages the active extraction of information, avoids depersonalization of patients and allows direct observation of clinical consultations. In short, it exposes the students to the complexity of actual clinical problems. The study aims to find out whether students and facilitators who are accustomed to paper cases would prefer video triggers or paper cases and the reasons for their preference. After students and facilitators had completed a video PBL tutorial, their responses were measured by a structured questionnaire using a modified Likert scale. A total of 257 students (92%) and 26 facilitators (100%) responded. The majority of students and facilitators considered that using video triggers could enhance the students' observational powers and clinical reasoning, help them to integrate different information and better understand the cases and motivate them to learn. They found PBL using video triggers more interesting and preferred it to PBL using paper cases. Video triggers are preferred by both students and facilitators over paper cases in PBL.

Risk assessment and optimization (ALARA) analysis for the environmental remediation of Brookhaven National Laboratory`s hazardous waste management facility

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dionne, B.J.; Morris, S.C. III; Baum, J.W.

1998-01-01

The Department of Energy`s (DOE) Office of Environment, Safety, and Health (EH) sought examples of risk-based approaches to environmental restoration to include in their guidance for DOE nuclear facilities. Extensive measurements of radiological contamination in soil and ground water have been made at Brookhaven National Laboratory`s Hazardous Waste Management Facility (HWMF) as part of a Comprehensive Environmental Response, Compensation and Liability Act (CERCLA) remediation process. This provided an ideal opportunity for a case study. This report provides a risk assessment and an {open_quotes}As Low as Reasonably Achievable{close_quotes} (ALARA) analysis for use at other DOE nuclear facilities as an example ofmore » a risk-based decision technique. This document contains the Appendices for the report.« less

For your first born child: an ethical defense of the exploitation argument against commercial surrogacy.

PubMed

Osberg, Brendan

2006-01-01

In this essay I explore two arguments against commercial surrogacy, based on commodification and exploitation respectively. I adopt a consequentialist framework and argue that commodification arguments must be grounded in a resultant harm to either child or surrogate, and that a priori arguments which condemn the practice for puritanical reasons cannot form a basis for public law. Furthermore there is no overwhelming evidence of harm caused to either party involved in commercial surrogacy, and hence Canadian law (which forbids the practice) must (and can) be justified on exploitative grounds. Objections raised by Wilkinson based on an 'isolated case' approach are addressed when one takes into account the political implications of public policy. I argue that is precisely these implications that justify laws forbidding commercial surrogacy on the grounds of preventing systematic exploitation.

Multiobjective Optimization of Rocket Engine Pumps Using Evolutionary Algorithm

NASA Technical Reports Server (NTRS)

Oyama, Akira; Liou, Meng-Sing

2001-01-01

A design optimization method for turbopumps of cryogenic rocket engines has been developed. Multiobjective Evolutionary Algorithm (MOEA) is used for multiobjective pump design optimizations. Performances of design candidates are evaluated by using the meanline pump flow modeling method based on the Euler turbine equation coupled with empirical correlations for rotor efficiency. To demonstrate the feasibility of the present approach, a single stage centrifugal pump design and multistage pump design optimizations are presented. In both cases, the present method obtains very reasonable Pareto-optimal solutions that include some designs outperforming the original design in total head while reducing input power by one percent. Detailed observation of the design results also reveals some important design criteria for turbopumps in cryogenic rocket engines. These results demonstrate the feasibility of the EA-based design optimization method in this field.

An unsupervised two-stage clustering approach for forest structure classification based on X-band InSAR data - A case study in complex temperate forest stands

NASA Astrophysics Data System (ADS)

Abdullahi, Sahra; Schardt, Mathias; Pretzsch, Hans

2017-05-01

Forest structure at stand level plays a key role for sustainable forest management, since the biodiversity, productivity, growth and stability of the forest can be positively influenced by managing its structural diversity. In contrast to field-based measurements, remote sensing techniques offer a cost-efficient opportunity to collect area-wide information about forest stand structure with high spatial and temporal resolution. Especially Interferometric Synthetic Aperture Radar (InSAR), which facilitates worldwide acquisition of 3d information independent from weather conditions and illumination, is convenient to capture forest stand structure. This study purposes an unsupervised two-stage clustering approach for forest structure classification based on height information derived from interferometric X-band SAR data which was performed in complex temperate forest stands of Traunstein forest (South Germany). In particular, a four dimensional input data set composed of first-order height statistics was non-linearly projected on a two-dimensional Self-Organizing Map, spatially ordered according to similarity (based on the Euclidean distance) in the first stage and classified using the k-means algorithm in the second stage. The study demonstrated that X-band InSAR data exhibits considerable capabilities for forest structure classification. Moreover, the unsupervised classification approach achieved meaningful and reasonable results by means of comparison to aerial imagery and LiDAR data.

Linking biomedical engineering ethics case study approach and policy.

PubMed

Dibrell, William; Dobie, Elizabeth Ann

2007-01-01

In this paper we link bioengineering case study methods to the development of policy. The case study approach to ethics is an excellent way to show the complex nature of practical/moral reasoning. This approach can, however, lead to a kind of overwhelming complexity. The individual nature of each case makes it difficult to identify the most important information and difficult to see what moral considerations are most relevant. In order to make the overwhelming complexity less debilitating, we present a framework for moral decision making derived from suggestions made by W.D. Ross and Virginia Held. Ross articulates the multiple sources of morality and Held deepens the discussion by reminding us of the foundational importance of care and sympathy to our moral natures. We show how to use the notion of prima facie duty and discuss moral conflict. In doing this, we show how the framework, applied to cases, can be of assistance in helping us develop policies and codes of ethics with sufficient plasticity to be useful in the complex world of the bioengineer.

Use of Complementary Health Approaches for Musculoskeletal Pain Disorders Among Adults: United States, 2012.

PubMed

Clarke, Tainya C; Nahin, Richard L; Barnes, Patricia M; Stussman, Barbara J

2016-10-01

This report examines the use of complementary health approaches among U.S. adults aged 18 and over who had a musculoskeletal pain disorder. Prevalence of use among this population subgroup is compared with use by persons without a musculoskeletal disorder. Use for any reason, as well as specifically to treat musculoskeletal pain disorders, is examined. Using the 2012 National Health Interview Survey, estimates of the use of complementary health approaches for any reason, as well as use to treat musculoskeletal pain disorders, are presented. Statistical tests were performed to assess the significance of differences between groups of complementary health approaches used among persons with specific musculoskeletal pain disorders. Musculoskeletal pain disorders included lower back pain, sciatica, neck pain, joint pain or related conditions, arthritic conditions, and other musculoskeletal pain disorders not included in any of the previous categories. Respondents could report having more than one disorder. In 2012, 54.5% of U.S. adults had a musculoskeletal pain disorder. The use of any complementary health approach for any reason among persons with a musculoskeletal pain disorder (41.6%) was significantly higher than use among persons without a musculoskeletal pain disorder (24.1%). Among adults with any musculoskeletal pain disorder, the use of natural products for any reason (24.7%) was significantly higher than the use of mind and body approaches (15.3%), practitioner-based approaches (18.2%), or whole medical system approaches (5.3%). The pattern of use of the above-mentioned groups of complementary health approaches was similar for persons without a musculoskeletal disorder. However, prevalence of use among these persons was significantly lower compared with persons with a musculoskeletal disorder. For treatment, the use of practitioner-based approaches among persons with any musculoskeletal pain disorder (9.7%) was more than three times as high as the use of any other group of approaches (0.7%-3.1%). The patterns of use of specific groups of complementary health approaches also differed among specific musculoskeletal pain disorders. All material appearing in this report is in the public domain and may be reproduced or copied without permission; citation as to source, however, is appreciated.

University Teachers' Job Dissatisfaction: Application of Two-Factor Theory--A Case of Pakistani Education System

ERIC Educational Resources Information Center

Mir, Imran Anwar

2012-01-01

This qualitative case study presents the reasons of teachers' job dissatisfaction in the government educational institutes in Pakistan. This case study is based on the two factor theory of Herzberg. The results of this case study reveal four core factors that cause job dissatisfaction among teachers in the public sector universities in developing…

Identifying developmental features in students' clinical reasoning to inform teaching.

PubMed

Pinnock, Ralph; Anakin, Megan; Lawrence, Julie; Chignell, Helen; Wilkinson, Tim

2018-04-27

There is increasing evidence that students at different levels of training may benefit from different methods of learning clinical reasoning. Two of the common methods of teaching are the "whole - case" format and the "serial cue" approach. There is little empirical evidence to guide teachers as to which method to use and when to introduce them. We observed 23 students from different stages of training to examine how they were taking a history and how they were thinking whilst doing this. Each student interviewed a simulated patient who presented with a straightforward and a complex presentation. We inferred how students were reasoning from how they took a history and how they described their thinking while doing this. Early in their training students can only take a generic history. Only later in training are they able to take a focused history, remember the information they have gathered, use it to seek further specific information, compare and contrast possibilities and analyze their data as they are collecting it. Early in their training students are unable to analyze data during history taking. When they have started developing illness scripts, they are able to benefit from the "serial cue" approach of teaching clinical reasoning.

A Declarative Design Approach to Modeling Traditional and Non-Traditional Space Systems

NASA Astrophysics Data System (ADS)

Hoag, Lucy M.

The space system design process is known to be laborious, complex, and computationally demanding. It is highly multi-disciplinary, involving several interdependent subsystems that must be both highly optimized and reliable due to the high cost of launch. Satellites must also be capable of operating in harsh and unpredictable environments, so integrating high-fidelity analysis is important. To address each of these concerns, a holistic design approach is necessary. However, while the sophistication of space systems has evolved significantly in the last 60 years, improvements in the design process have been comparatively stagnant. Space systems continue to be designed using a procedural, subsystem-by-subsystem approach. This method is inadequate since it generally requires extensive iteration and limited or heuristic-based search, which can be slow, labor-intensive, and inaccurate. The use of a declarative design approach can potentially address these inadequacies. In the declarative programming style, the focus of a problem is placed on what the objective is, and not necessarily how it should be achieved. In the context of design, this entails knowledge expressed as a declaration of statements that are true about the desired artifact instead of explicit instructions on how to implement it. A well-known technique is through constraint-based reasoning, where a design problem is represented as a network of rules and constraints that are reasoned across by a solver to dynamically discover the optimal candidate(s). This enables implicit instantiation of the tradespace and allows for automatic generation of all feasible design candidates. As such, this approach also appears to be well-suited to modeling adaptable space systems, which generally have large tradespaces and possess configurations that are not well-known a priori. This research applied a declarative design approach to holistic satellite design and to tradespace exploration for adaptable space systems. The approach was tested during the design of USC's Aeneas nanosatellite project, and a case study was performed to assess the advantages of the new approach over past procedural approaches. It was found that use of the declarative approach improved design accuracy through exhaustive tradespace search and provable optimality; decreased design time through improved model generation, faster run time, and reduction in time and number of iteration cycles; and enabled modular and extensible code. Observed weaknesses included non-intuitive model abstraction; increased debugging time; and difficulty of data extrapolation and analysis.

Application of the 2016 diagnostic approach for autoimmune encephalitis from Lancet Neurology to Chinese patients.

PubMed

Li, Lin; Sun, Lin; Du, Rong; Zheng, Yuanchu; Dai, Feifei; Ma, Qiuying; Wang, Jiawei

2017-11-06

A unified clinical approach to diagnose autoimmune encephalitis was published in Lancet Neurology in 2016. Purpose of our study is to examine the feasibility and reasonability of the 2016 "A clinical approach to diagnosis of autoimmune encephalitis" in China with a retrospective study. We retrospectively collected 95 cases of autoimmune encephalitis and non autoimmune encephalitis cases with detailed clinical data from Beijing Tongren Hospital and the China National Knowledge Infrastructure (CNKI). All cases were analysed stepwise according to the approach in Lancet Neurology to compare the new diagnosis with the final clinical diagnosis. The disease course of these 95 cases ranged from 2 to 540 days. Initial symptoms include fever, headache, seizure, mental and behavioral disorders, memory deterioration and illusion. Based on symptoms and signs when the patient came to the hospital, the sensitivity and specificity of criteria were as follows: possible autoimmune encephalitis (pAE) 84% and 94%, definite autoimmune limbic encephalitis (dALE) 38% and 96%, probable anti-N-methyl-D-aspartate receptor encephalitis (prNMDARE) 49% and 98%. The sensitivities of the above three criteria and the specificity of pAE were low during early disease stage, while the specificities of dALE and prNMDAER remained relatively high in different time periods. This new autoimmune encephalitis diagnostic approach can recognize possible autoimmune encephalitis. The chances of a case being autoimmune-mediated following classification as autoimmune encephalitis with the new criteria are high. The flowchart is recommended to use as a whole. At the early disease stage, criteria with low sensitivity and high specificity, such as dALE and prNMDARE, lead most cases to enter subsequent diagnosis steps, namely autoantibody detection in the flowchart. Final diagnoses can only be made by autoantibody tests. These factors may make it challenging for clinicians to make diagnosis promptly and to begin immune-modulating therapy immediately. Moreover, the criteria for patients with paraneoplastic syndromes (PNSs) should be considered to avoid diagnosis omission. For Chinese patients, a multi-centre, prospective study on the clinical manifestations, laboratory diagnostic technology, therapy, and prognosis is greatly needed.

Scaffolding Student Learning in the Discipline-Specific Knowledge through Contemporary Science Practices: Developing High-School Students' Epidemiologic Reasoning through Data Analysis

NASA Astrophysics Data System (ADS)

Oura, Hiroki

Science is a disciplined practice about knowing puzzling observations and unknown phenomena. Scientific knowledge of the product is applied to develop technological artifacts and solve complex problems in society. Scientific practices are undeniably relevant to our economy, civic activity, and personal lives, and thus public education should help children acquire scientific knowledge and recognize the values in relation to their own lives and civil society. Likewise, developing scientific thinking skills is valuable not only for becoming a scientist, but also for becoming a citizen who is able to critically evaluate everyday information, select and apply only the trustworthy, and make wise judgments in their personal and cultural goals as well as for obtaining jobs that require complex problem solving and creative working in the current knowledge-based economy and rapid-changing world. To develop students' scientific thinking, science instruction should focus not only on scientific knowledge and inquiry processes, but also on its epistemological aspects including the forms of causal explanations and methodological choices along with epistemic aims and values under the social circumstances in focal practices. In this perspective, disciplinary knowledge involves heterogeneous elements including material, cognitive, social, and cultural ones and the formation differs across practices. Without developing such discipline-specific knowledge, students cannot enough deeply engage in scientific "practices" and understand the true values of scientific enterprises. In this interest, this dissertation explores instructional approaches to make student engagement in scientific investigations more authentic or disciplinary. The present dissertation work is comprised of three research questions as stand-alone studies written for separate publication. All of the studies discuss different theoretical aspects related to disciplinary engagement in epidemiologic inquiry and student development in epidemiologic reasoning. The first chapter reviews literature on epistemological instruction and explores theoretical frameworks for epistemically-guided instruction. The second chapter explores methodological strategies to elicit students' disciplinary understanding and demonstrates an approach with a case study in which students engaged in a curriculum unit for an epidemiologic investigation. The last chapter directs the focus into scientific reasoning and demonstrates how the curriculum unit and its scaffolds helped students develop epidemiologic reasoning with a focus on population-based reasoning.

Mirroring, Gestaltswitching and Transformative Social Learning: Stepping Stones for Developing Sustainability Competence

ERIC Educational Resources Information Center

Wals, Arjen E. J.

2010-01-01

Purpose: The purpose of this paper is to identify components and educational design principles for strengthening sustainability competence in and through higher education. Design/methodology/approach: This is a conceptual paper that uses an exemplary autobiographical empirical case study in order to illustrate and support a line of reasoning.…

Teacher Dismissal for Immoral and Illegal Conduct.

ERIC Educational Resources Information Center

Delon, Floyd G.

The traditional approach of the courts was to accept as "reasonable cause" for teacher dismissal any conduct that set a bad example for students. This chapter examines a cross-section of cases illustrating recent court decisions in this area and attempts to identify any consistent patterns of adjudication and their implications for school…

Improving Training in Enterprise Resource Planning Systems Implementation through Communities of Practice

ERIC Educational Resources Information Center

Kerr, Don; Burgess, Kevin J.; Houghton, Luke; Murray, Peter A.

2012-01-01

The Enterprise Resource Planning (ERP) literature suggests that effective training is one of the key reasons for success in ERP implementations. However, limited research has been conducted on what constitutes effective training in an ERP environment. A case study approach was used to explore the effectiveness of traditional training and to…