Mental models and human reasoning

PubMed Central

Johnson-Laird, Philip N.

2010-01-01

To be rational is to be able to reason. Thirty years ago psychologists believed that human reasoning depended on formal rules of inference akin to those of a logical calculus. This hypothesis ran into difficulties, which led to an alternative view: reasoning depends on envisaging the possibilities consistent with the starting point—a perception of the world, a set of assertions, a memory, or some mixture of them. We construct mental models of each distinct possibility and derive a conclusion from them. The theory predicts systematic errors in our reasoning, and the evidence corroborates this prediction. Yet, our ability to use counterexamples to refute invalid inferences provides a foundation for rationality. On this account, reasoning is a simulation of the world fleshed out with our knowledge, not a formal rearrangement of the logical skeletons of sentences. PMID:20956326

Promoting the Self-Regulation of Clinical Reasoning Skills in Nursing Students

PubMed Central

Kuiper, R; Pesut, D; Kautz, D

2009-01-01

Aim: The purpose of this paper is to describe the research surrounding the theories and models the authors united to describe the essential components of clinical reasoning in nursing practice education. The research was conducted with nursing students in health care settings through the application of teaching and learning strategies with the Self-Regulated Learning Model (SRL) and the Outcome-Present-State-Test (OPT) Model of Reflective Clinical Reasoning. Standardized nursing languages provided the content and clinical vocabulary for the clinical reasoning task. Materials and Methods: This descriptive study described the application of the OPT model of clinical reasoning, use of nursing language content, and reflective journals based on the SRL model with 66 undergraduate nursing students over an 8 month period of time. The study tested the idea that self-regulation of clinical reasoning skills can be developed using self-regulation theory and the OPT model. Results: This research supports a framework for effective teaching and learning methods to promote and document learner progress in mastering clinical reasoning skills. Self-regulated Learning strategies coupled with the OPT model suggest benefits of self-observation and self-monitoring during clinical reasoning activities, and pinpoints where guidance is needed for the development of cognitive and metacognitive awareness. Recommendations and Conclusions: Thinking and reasoning about the complexities of patient care needs requires attention to the content, processes and outcomes that make a nursing care difference. These principles and concepts are valuable to clinical decision making for nurses globally as they deal with local, regional, national and international health care issues. PMID:19888432

Machine Learning-based Intelligent Formal Reasoning and Proving System

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Intelligent tutoring system for clinical reasoning skill acquisition in dental students.

PubMed

Suebnukarn, Siriwan

2009-10-01

Learning clinical reasoning is an important core activity of the modern dental curriculum. This article describes an intelligent tutoring system (ITS) for clinical reasoning skill acquisition. The system is designed to provide an experience that emulates that of live human-tutored problem-based learning (PBL) sessions as much as possible, while at the same time permitting the students to participate collaboratively from disparate locations. The system uses Bayesian networks to model individual student knowledge and activity, as well as that of the group. Tutoring algorithms use the models to generate tutoring hints. The system incorporates a multimodal interface that integrates text and graphics so as to provide a rich communication channel between the students and the system, as well as among students in the group. Comparison of learning outcomes shows that student clinical reasoning gains from the ITS are similar to those obtained from human-tutored sessions.

Examination of simplified travel demand model. [Internal volume forecasting model

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

Smith, R.L. Jr.; McFarlane, W.J.

1978-01-01

A simplified travel demand model, the Internal Volume Forecasting (IVF) model, proposed by Low in 1972 is evaluated as an alternative to the conventional urban travel demand modeling process. The calibration of the IVF model for a county-level study area in Central Wisconsin results in what appears to be a reasonable model; however, analysis of the structure of the model reveals two primary mis-specifications. Correction of the mis-specifications leads to a simplified gravity model version of the conventional urban travel demand models. Application of the original IVF model to ''forecast'' 1960 traffic volumes based on the model calibrated for 1970more » produces accurate estimates. Shortcut and ad hoc models may appear to provide reasonable results in both the base and horizon years; however, as shown by the IVF mode, such models will not always provide a reliable basis for transportation planning and investment decisions.« less

Model of critical diagnostic reasoning: achieving expert clinician performance.

PubMed

Harjai, Prashant Kumar; Tiwari, Ruby

2009-01-01

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

Follow the heart or the head? The interactive influence model of emotion and cognition

PubMed Central

Luo, Jiayi; Yu, Rongjun

2015-01-01

The experience of emotion has a powerful influence on daily-life decision making. Following Plato’s description of emotion and reason as two horses pulling us in opposite directions, modern dual-system models of decision making endorse the antagonism between reason and emotion. Decision making is perceived as the competition between an emotion system that is automatic but prone to error and a reason system that is slow but rational. The reason system (in “the head”) reins in our impulses (from “the heart”) and overrides our snap judgments. However, from Darwin’s evolutionary perspective, emotion is adaptive, guiding us to make sound decisions in uncertainty. Here, drawing findings from behavioral economics and neuroeconomics, we provide a new model, labeled “The interactive influence model of emotion and cognition,” to elaborate the relationship of emotion and reason in decision making. Specifically, in our model, we identify factors that determine when emotions override reason and delineate the type of contexts in which emotions help or hurt decision making. We then illustrate how cognition modulates emotion and how they cooperate to affect decision making. PMID:25999889

Modelling the Reasons for Training Choices: Technical Paper. Support Document

ERIC Educational Resources Information Center

Smith, Andrew; Oczkowski, Eddie; Hill, Mark

2009-01-01

This report provides the technical details on the modelling aspects of identifying significant drivers for the reasons for using certain types of training and for the choice of training types. The employed data is from the 2005 Survey of Employer Use and Views of the VET system (SEUV). The data has previously been analysed in NCVER (2006). This…

A Little Logic Goes a Long Way: Basing Experiment on Semantic Theory in the Cognitive Science of Conditional Reasoning

ERIC Educational Resources Information Center

Stenning, Keith; van Lambalgen, Michiel

2004-01-01

Modern logic provides accounts of both interpretation and derivation which work together to provide abstract frameworks for modelling the sensitivity of human reasoning to task, context and content. Cognitive theories have underplayed the importance of interpretative processes. We illustrate, using Wason's [Q. J. Exp. Psychol. 20 (1968) 273]…

Quantum Structure in Cognition and the Foundations of Human Reasoning

NASA Astrophysics Data System (ADS)

Aerts, Diederik; Sozzo, Sandro; Veloz, Tomas

2015-12-01

Traditional cognitive science rests on a foundation of classical logic and probability theory. This foundation has been seriously challenged by several findings in experimental psychology on human decision making. Meanwhile, the formalism of quantum theory has provided an efficient resource for modeling these classically problematical situations. In this paper, we start from our successful quantum-theoretic approach to the modeling of concept combinations to formulate a unifying explanatory hypothesis. In it, human reasoning is the superposition of two processes - a conceptual reasoning, whose nature is emergence of new conceptuality, and a logical reasoning, founded on an algebraic calculus of the logical type. In most cognitive processes however, the former reasoning prevails over the latter. In this perspective, the observed deviations from classical logical reasoning should not be interpreted as biases but, rather, as natural expressions of emergence in its deepest form.

A Tri-part Model for Genetics Literacy: Exploring Undergraduate Student Reasoning About Authentic Genetics Dilemmas

NASA Astrophysics Data System (ADS)

Shea, Nicole A.; Duncan, Ravit Golan; Stephenson, Celeste

2015-08-01

Genetics literacy is becoming increasingly important as advancements in our application of genetic technologies such as stem cell research, cloning, and genetic screening become more prevalent. Very few studies examine how genetics literacy is applied when reasoning about authentic genetic dilemmas. However, there is evidence that situational features of a reasoning task may influence how students apply content knowledge as they generate and support arguments. Understanding how students apply content knowledge to reason about authentic and complex issues is important for considering instructional practices that best support student thinking and reasoning. In this conceptual report, we present a tri-part model for genetics literacy that embodies the relationships between content knowledge use, argumentation quality, and the role of situational features in reasoning to support genetics literacy. Using illustrative examples from an interview study with early career undergraduate students majoring in the biological sciences and late career undergraduate students majoring in genetics, we provide insights into undergraduate student reasoning about complex genetics issues and discuss implications for teaching and learning. We further discuss the need for research about how the tri-part model of genetics literacy can be used to explore students' thinking and reasoning abilities in genetics.

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

PubMed Central

Quillin, Kim; Thomas, Stephen

2015-01-01

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

The microwave propagation and backscattering characteristics of vegetation. [wheat, sorghum, soybeans and corn fields in Kansas

NASA Technical Reports Server (NTRS)

Ulaby, F. T. (Principal Investigator); Wilson, E. A.

1984-01-01

A semi-empirical model for microwave backscatter from vegetation was developed and a complete set of canope attenuation measurements as a function of frequency, incidence angle and polarization was acquired. The semi-empirical model was tested on corn and sorghum data over the 8 to 35 GHz range. The model generally provided an excellent fit to the data as measured by the correlation and rms error between observed and predicted data. The model also predicted reasonable values of canopy attenuation. The attenuation data was acquired over the 1.6 to 10.2 GHz range for the linear polarizations at approximately 20 deg and 50 deg incidence angles for wheat and soybeans. An attenuation model is proposed which provides reasonable agreement with the measured data.

A Chemistry Concept Reasoning Test

ERIC Educational Resources Information Center

Cloonan, Carrie A.; Hutchinson, John S.

2011-01-01

A Chemistry Concept Reasoning Test was created and validated providing an easy-to-use tool for measuring conceptual understanding and critical scientific thinking of general chemistry models and theories. The test is designed to measure concept understanding comparable to that found in free-response questions requiring explanations over…

Using Data-Collection Sensors to Improve Reasoning About Experiment Design and Hypothesis Testing: An Undergraduate Course for Underrepresented Minorities Pursuing Careers Astrophysics Research

NASA Astrophysics Data System (ADS)

Robbins, Dennis M.; Ford, K. E. Saavik

2015-01-01

Strategies to improve the retention of underrepresented students in STEM fields include directly targeted programs and specialized courses. The NSF-supported 'AstroCom NYC' program, a collaboration of the City University of New York, American Museum of Natural History (AMNH), and Columbia University is one example of such a program with the explicit goal of increasing the participation of underrepresented minorities in astronomy and astrophysics through pedagogical mentoring and research experiences for undergraduate students. In addition, 'AstroCom NYC' provides students with a semester-long specialized course emphasizing scientific reasoning and mathematical modeling. The course curriculum uses computers and interfaced digital probeware (sensors) in a laboratory environment that encourages collaborative and active learning.We share course materials on preparing students to reason about control of variable experiment design and hypothesis testing and provide course data on student understanding of scientific reasoning, mathematical modeling and views about science.

A concise guide to clinical reasoning.

PubMed

Daly, Patrick

2018-04-30

What constitutes clinical reasoning is a disputed subject regarding the processes underlying accurate diagnosis, the importance of patient-specific versus population-based data, and the relation between virtue and expertise in clinical practice. In this paper, I present a model of clinical reasoning that identifies and integrates the processes of diagnosis, prognosis, and therapeutic decision making. The model is based on the generalized empirical method of Bernard Lonergan, which approaches inquiry with equal attention to the subject who investigates and the object under investigation. After identifying the structured operations of knowing and doing and relating these to a self-correcting cycle of learning, I correlate levels of inquiry regarding what-is-going-on and what-to-do to the practical and theoretical elements of clinical reasoning. I conclude that this model provides a methodical way to study questions regarding the operations of clinical reasoning as well as what constitute significant clinical data, clinical expertise, and virtuous health care practice. © 2018 John Wiley & Sons, Ltd.

Causal Reasoning in Medicine: Analysis of a Protocol.

ERIC Educational Resources Information Center

Kuipers, Benjamin; Kassirer, Jerome P.

1984-01-01

Describes the construction of a knowledge representation from the identification of the problem (nephrotic syndrome) to a running computer simulation of causal reasoning to provide a vertical slice of the construction of a cognitive model. Interactions between textbook knowledge, observations of human experts, and computational requirements are…

Applying Model Analysis to a Resource-Based Analysis of the Force and Motion Conceptual Evaluation

ERIC Educational Resources Information Center

Smith, Trevor I.; Wittmann, Michael C.; Carter, Tom

2014-01-01

Previously, we analyzed the Force and Motion Conceptual Evaluation in terms of a resources-based model that allows for clustering of questions so as to provide useful information on how students correctly or incorrectly reason about physics. In this paper, we apply model analysis to show that the associated model plots provide more information…

Inverse reasoning processes in obsessive-compulsive disorder.

PubMed

Wong, Shiu F; Grisham, Jessica R

2017-04-01

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

Measuring cancer patients' reasons for their information preference: construction of the Considerations Concerning Cancer Information (CCCI) questionnaire.

PubMed

ter Hoeven, Claartje L; Zandbelt, Linda C; Fransen, Sanne; de Haes, Hanneke; Oort, Frans; Geijsen, Debby; Koning, Caro; Smets, Ellen

2011-11-01

This paper describes the further development and psychometric properties of an instrument to measure cancer patients' reasons to want complete or limited information: the Considerations Concerning Cancer Information questionnaire (CCCI). Understanding cancer patients' reasons to want complete or limited information will provide the physician with information that enables him or her to tailor information giving. CCCI's content validity, internal structure, and convergent validity were investigated among 145 cancer patients, new to radiotherapy. Underlying reasons for information preference among cancer patients were derived from existing qualitative studies, narratives, and interviews. This resulted in the CCCI containing two parts: reasons to favor complete information disclosure and reasons to prefer only limited information about disease and treatment. The four identified dimensions to prefer information consist of: sense of control, expectations of others, anxiety, and autonomy. The four dimensions for reasons to give up on acquiring information consist of: avoidance, optimism, comprehension, and not wanting to be a burden. Confirmatory factor analysis indicated that the measurement model provided good fit to the data. Scales had good internal consistency, satisfactory item-total correlations corrected for overlap and satisfactory convergent validity. These findings confirm evidence of the reliability and validity of the CCCI for use in cancer care. Researchers and health-care providers can use the instrument to assess cancer patients' reasons to want complete or limited information and provide tailored care. Copyright © 2010 John Wiley & Sons, Ltd.

Spatial Reasoning Training Through Light Curves Of Model Asteroids

NASA Astrophysics Data System (ADS)

Ziffer, Julie; Nakroshis, Paul A.; Rudnick, Benjamin T.; Brautigam, Maxwell J.; Nelson, Tyler W.

2015-11-01

Recent research has demonstrated that spatial reasoning skills, long known to be crucial to math and science success, are teachable. Even short stints of training can improve spatial reasoning skills among students who lack them (Sorby et al., 2006). Teaching spatial reasoning is particularly valuable to women and minorities who, through societal pressure, often doubt their spatial reasoning skill (Hill et al., 2010). We have designed a hands on asteroid rotation lab that provides practice in spatial reasoning tasks while building the student’s understanding of photometry. For our tool, we mount a model asteroid, with any shape of our choosing, on a slowly rotating motor shaft, whose speed is controlled by the experimenter. To mimic an asteroid light curve, we place the model asteroid in a dark box, shine a movable light source upon our asteroid, and record the light reflected onto a moveable camera. Students may then observe changes in the light curve that result from varying a) the speed of rotation, b) the model asteroid’s orientation with respect to the motor axis, c) the model asteroid’s shape or albedo, and d) the phase angle. After practicing with our tool, students are asked to pair new objects to their corresponding light curves. To correctly pair objects to their light curves, students must imagine how light scattering off of a three dimensional rotating object is imaged on a ccd sensor plane, and then reduced to a series of points on a light curve plot. Through the use of our model asteroid, the student develops confidence in spatial reasoning skills.

MTK: An AI tool for model-based reasoning

NASA Technical Reports Server (NTRS)

Erickson, William K.; Rudokas, Mary R.

1988-01-01

A 1988 goal for the Systems Autonomy Demonstration Project Office of the NASA Ames Research Office is to apply model-based representation and reasoning techniques in a knowledge-based system that will provide monitoring, fault diagnosis, control, and trend analysis of the Space Station Thermal Control System (TCS). A number of issues raised during the development of the first prototype system inspired the design and construction of a model-based reasoning tool called MTK, which was used in the building of the second prototype. These issues are outlined here with examples from the thermal system to highlight the motivating factors behind them, followed by an overview of the capabilities of MTK, which was developed to address these issues in a generic fashion.

What every teacher needs to know about clinical reasoning.

PubMed

Eva, Kevin W

2005-01-01

One of the core tasks assigned to clinical teachers is to enable students to sort through a cluster of features presented by a patient and accurately assign a diagnostic label, with the development of an appropriate treatment strategy being the end goal. Over the last 30 years there has been considerable debate within the health sciences education literature regarding the model that best describes how expert clinicians generate diagnostic decisions. The purpose of this essay is to provide a review of the research literature on clinical reasoning for frontline clinical teachers. The strengths and weaknesses of different approaches to clinical reasoning will be examined using one of the core divides between various models (that of analytic (i.e. conscious/controlled) versus non-analytic (i.e. unconscious/automatic) reasoning strategies) as an orienting framework. Recent work suggests that clinical teachers should stress the importance of both forms of reasoning, thereby enabling students to marshal reasoning processes in a flexible and context-specific manner. Specific implications are drawn from this overview for clinical teachers.

Five-Year-Olds' Systematic Errors in Second-Order False Belief Tasks Are Due to First-Order Theory of Mind Strategy Selection: A Computational Modeling Study.

PubMed

Arslan, Burcu; Taatgen, Niels A; Verbrugge, Rineke

2017-01-01

The focus of studies on second-order false belief reasoning generally was on investigating the roles of executive functions and language with correlational studies. Different from those studies, we focus on the question how 5-year-olds select and revise reasoning strategies in second-order false belief tasks by constructing two computational cognitive models of this process: an instance-based learning model and a reinforcement learning model. Unlike the reinforcement learning model, the instance-based learning model predicted that children who fail second-order false belief tasks would give answers based on first-order theory of mind (ToM) reasoning as opposed to zero-order reasoning. This prediction was confirmed with an empirical study that we conducted with 72 5- to 6-year-old children. The results showed that 17% of the answers were correct and 83% of the answers were wrong. In line with our prediction, 65% of the wrong answers were based on a first-order ToM strategy, while only 29% of them were based on a zero-order strategy (the remaining 6% of subjects did not provide any answer). Based on our instance-based learning model, we propose that when children get feedback "Wrong," they explicitly revise their strategy to a higher level instead of implicitly selecting one of the available ToM strategies. Moreover, we predict that children's failures are due to lack of experience and that with exposure to second-order false belief reasoning, children can revise their wrong first-order reasoning strategy to a correct second-order reasoning strategy.

Five-Year-Olds’ Systematic Errors in Second-Order False Belief Tasks Are Due to First-Order Theory of Mind Strategy Selection: A Computational Modeling Study

PubMed Central

Arslan, Burcu; Taatgen, Niels A.; Verbrugge, Rineke

2017-01-01

The focus of studies on second-order false belief reasoning generally was on investigating the roles of executive functions and language with correlational studies. Different from those studies, we focus on the question how 5-year-olds select and revise reasoning strategies in second-order false belief tasks by constructing two computational cognitive models of this process: an instance-based learning model and a reinforcement learning model. Unlike the reinforcement learning model, the instance-based learning model predicted that children who fail second-order false belief tasks would give answers based on first-order theory of mind (ToM) reasoning as opposed to zero-order reasoning. This prediction was confirmed with an empirical study that we conducted with 72 5- to 6-year-old children. The results showed that 17% of the answers were correct and 83% of the answers were wrong. In line with our prediction, 65% of the wrong answers were based on a first-order ToM strategy, while only 29% of them were based on a zero-order strategy (the remaining 6% of subjects did not provide any answer). Based on our instance-based learning model, we propose that when children get feedback “Wrong,” they explicitly revise their strategy to a higher level instead of implicitly selecting one of the available ToM strategies. Moreover, we predict that children’s failures are due to lack of experience and that with exposure to second-order false belief reasoning, children can revise their wrong first-order reasoning strategy to a correct second-order reasoning strategy. PMID:28293206

Real-time value-driven diagnosis

NASA Technical Reports Server (NTRS)

Dambrosio, Bruce

1995-01-01

Diagnosis is often thought of as an isolated task in theoretical reasoning (reasoning with the goal of updating our beliefs about the world). We present a decision-theoretic interpretation of diagnosis as a task in practical reasoning (reasoning with the goal of acting in the world), and sketch components of our approach to this task. These components include an abstract problem description, a decision-theoretic model of the basic task, a set of inference methods suitable for evaluating the decision representation in real-time, and a control architecture to provide the needed continuing coordination between the agent and its environment. A principal contribution of this work is the representation and inference methods we have developed, which extend previously available probabilistic inference methods and narrow, somewhat, the gap between probabilistic and logical models of diagnosis.

How many kinds of reasoning? Inference, probability, and natural language semantics.

PubMed

Lassiter, Daniel; Goodman, Noah D

2015-03-01

The "new paradigm" unifying deductive and inductive reasoning in a Bayesian framework (Oaksford & Chater, 2007; Over, 2009) has been claimed to be falsified by results which show sharp differences between reasoning about necessity vs. plausibility (Heit & Rotello, 2010; Rips, 2001; Rotello & Heit, 2009). We provide a probabilistic model of reasoning with modal expressions such as "necessary" and "plausible" informed by recent work in formal semantics of natural language, and show that it predicts the possibility of non-linear response patterns which have been claimed to be problematic. Our model also makes a strong monotonicity prediction, while two-dimensional theories predict the possibility of reversals in argument strength depending on the modal word chosen. Predictions were tested using a novel experimental paradigm that replicates the previously-reported response patterns with a minimal manipulation, changing only one word of the stimulus between conditions. We found a spectrum of reasoning "modes" corresponding to different modal words, and strong support for our model's monotonicity prediction. This indicates that probabilistic approaches to reasoning can account in a clear and parsimonious way for data previously argued to falsify them, as well as new, more fine-grained, data. It also illustrates the importance of careful attention to the semantics of language employed in reasoning experiments. Copyright © 2014 Elsevier B.V. All rights reserved.

Cortisol, insulin and leptin during space flight and bed rest

NASA Technical Reports Server (NTRS)

Stein, T. P.; Schluter, M. D.; Leskiw, M. J.

1999-01-01

Most ground based models for studying muscle atrophy and bone loss show reasonable fidelity to the space flight situation. However there are some differences. Investigation of the reasons for these differences can provide useful information about humans during space flight and aid in the refinement of ground based models. This report discusses three such differences, the relationships between: (i) cortisol and the protein loss, (ii) cortisol and ACTH and (iii) leptin, insulin and food intake.

Quantization, Frobenius and Bi algebras from the Categorical Framework of Quantum Mechanics to Natural Language Semantics

NASA Astrophysics Data System (ADS)

Sadrzadeh, Mehrnoosh

2017-07-01

Compact Closed categories and Frobenius and Bi algebras have been applied to model and reason about Quantum protocols. The same constructions have also been applied to reason about natural language semantics under the name: ``categorical distributional compositional'' semantics, or in short, the ``DisCoCat'' model. This model combines the statistical vector models of word meaning with the compositional models of grammatical structure. It has been applied to natural language tasks such as disambiguation, paraphrasing and entailment of phrases and sentences. The passage from the grammatical structure to vectors is provided by a functor, similar to the Quantization functor of Quantum Field Theory. The original DisCoCat model only used compact closed categories. Later, Frobenius algebras were added to it to model long distance dependancies such as relative pronouns. Recently, bialgebras have been added to the pack to reason about quantifiers. This paper reviews these constructions and their application to natural language semantics. We go over the theory and present some of the core experimental results.

A qualitative study to identify reasons for discharges against medical advice in the cardiovascular setting

PubMed Central

Saunders, Elijah; Mullins, C Daniel; Pradel, Françoise G; Zuckerman, Marni; Loh, F Ellen; Weir, Matthew R

2012-01-01

Background Cardiovascular disease (CVD) is responsible for the largest number of discharges against medical advice (AMA). However, there is limited information regarding the reasons for discharges AMA in the CVD setting. Objective To identify reasons for discharges AMA among patients with CVD. Design Qualitative study using focus group interviews (FGIs). Participants A convenience sample of patients with a CVD-related discharge diagnosis who left AMA and providers (physicians, nurses and social workers) whose patients have left AMA. Primary and secondary outcomes To identify patients' reasons for discharges AMA as identified by patients and providers. To identify strategies to reduce discharges AMA. Approach FGIs were grouped according to patients, physicians and nurses/social workers. A content analysis was performed independently by three coauthors to identify the nature and range of the participants' viewpoints on the reasons for discharges AMA. The content analysis involved specific categories of reasons as motivated by the Health Belief Model as well as reasons (ie, themes) that emerged from the interview data. Results 9 patients, 10 physicians and 23 nurses/social workers were recruited for the FGIs. Patients and providers reported the same three reasons for discharges AMA: (1) patient's preference for their own doctor, (2) long wait time and (3) factors outside the hospital. Patients identified an unmet expectation to be involved in setting the treatment plan as a reason to leave AMA. Participants identified improved communication as a solution for reducing discharges AMA. Conclusions Patients wanted more involvement in their care, exhibited a strong preference for their own primary physician, felt that they spent a long time waiting in the hospital and were motivated to leave AMA by factors outside the hospital. Providers identified similar reasons except the patients' desire for involvement. Additional research is needed to determine the applicability of results in broader patient and provider populations. PMID:22850166

Information Uncertainty to Compare Qualitative Reasoning Security Risk Assessment Results

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

Chavez, Gregory M; Key, Brian P; Zerkle, David K

2009-01-01

The security risk associated with malevolent acts such as those of terrorism are often void of the historical data required for a traditional PRA. Most information available to conduct security risk assessments for these malevolent acts is obtained from subject matter experts as subjective judgements. Qualitative reasoning approaches such as approximate reasoning and evidential reasoning are useful for modeling the predicted risk from information provided by subject matter experts. Absent from these approaches is a consistent means to compare the security risk assessment results. Associated with each predicted risk reasoning result is a quantifiable amount of information uncertainty which canmore » be measured and used to compare the results. This paper explores using entropy measures to quantify the information uncertainty associated with conflict and non-specificity in the predicted reasoning results. The measured quantities of conflict and non-specificity can ultimately be used to compare qualitative reasoning results which are important in triage studies and ultimately resource allocation. Straight forward extensions of previous entropy measures are presented here to quantify the non-specificity and conflict associated with security risk assessment results obtained from qualitative reasoning models.« less

Self-calibrating models for dynamic monitoring and diagnosis

NASA Technical Reports Server (NTRS)

Kuipers, Benjamin

1994-01-01

The present goal in qualitative reasoning is to develop methods for automatically building qualitative and semiquantitative models of dynamic systems and to use them for monitoring and fault diagnosis. The qualitative approach to modeling provides a guarantee of coverage while our semiquantitative methods support convergence toward a numerical model as observations are accumulated. We have developed and applied methods for automatic creation of qualitative models, developed two methods for obtaining tractable results on problems that were previously intractable for qualitative simulation, and developed more powerful methods for learning semiquantitative models from observations and deriving semiquantitative predictions from them. With these advances, qualitative reasoning comes significantly closer to realizing its aims as a practical engineering method.

A dynamic model of reasoning and memory.

PubMed

Hawkins, Guy E; Hayes, Brett K; Heit, Evan

2016-02-01

Previous models of category-based induction have neglected how the process of induction unfolds over time. We conceive of induction as a dynamic process and provide the first fine-grained examination of the distribution of response times observed in inductive reasoning. We used these data to develop and empirically test the first major quantitative modeling scheme that simultaneously accounts for inductive decisions and their time course. The model assumes that knowledge of similarity relations among novel test probes and items stored in memory drive an accumulation-to-bound sequential sampling process: Test probes with high similarity to studied exemplars are more likely to trigger a generalization response, and more rapidly, than items with low exemplar similarity. We contrast data and model predictions for inductive decisions with a recognition memory task using a common stimulus set. Hierarchical Bayesian analyses across 2 experiments demonstrated that inductive reasoning and recognition memory primarily differ in the threshold to trigger a decision: Observers required less evidence to make a property generalization judgment (induction) than an identity statement about a previously studied item (recognition). Experiment 1 and a condition emphasizing decision speed in Experiment 2 also found evidence that inductive decisions use lower quality similarity-based information than recognition. The findings suggest that induction might represent a less cautious form of recognition. We conclude that sequential sampling models grounded in exemplar-based similarity, combined with hierarchical Bayesian analysis, provide a more fine-grained and informative analysis of the processes involved in inductive reasoning than is possible solely through examination of choice data. PsycINFO Database Record (c) 2016 APA, all rights reserved.

Applying a Multiple Group Causal Indicator Modeling Framework to the Reading Comprehension Skills of Third, Seventh, and Tenth Grade Students

PubMed Central

Tighe, Elizabeth L.; Wagner, Richard K.; Schatschneider, Christopher

2015-01-01

This study demonstrates the utility of applying a causal indicator modeling framework to investigate important predictors of reading comprehension in third, seventh, and tenth grade students. The results indicated that a 4-factor multiple indicator multiple indicator cause (MIMIC) model of reading comprehension provided adequate fit at each grade level. This model included latent predictor constructs of decoding, verbal reasoning, nonverbal reasoning, and working memory and accounted for a large portion of the reading comprehension variance (73% to 87%) across grade levels. Verbal reasoning contributed the most unique variance to reading comprehension at all grade levels. In addition, we fit a multiple group 4-factor MIMIC model to investigate the relative stability (or variability) of the predictor contributions to reading comprehension across development (i.e., grade levels). The results revealed that the contributions of verbal reasoning, nonverbal reasoning, and working memory to reading comprehension were stable across the three grade levels. Decoding was the only predictor that could not be constrained to be equal across grade levels. The contribution of decoding skills to reading comprehension was higher in third grade and then remained relatively stable between seventh and tenth grade. These findings illustrate the feasibility of using MIMIC models to explain individual differences in reading comprehension across the development of reading skills. PMID:25821346

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.

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.

Using lab notebooks to examine students' engagement in modeling in an upper-division electronics lab course

NASA Astrophysics Data System (ADS)

Stanley, Jacob T.; Su, Weifeng; Lewandowski, H. J.

2017-12-01

We demonstrate how students' use of modeling can be examined and assessed using student notebooks collected from an upper-division electronics lab course. The use of models is a ubiquitous practice in undergraduate physics education, but the process of constructing, testing, and refining these models is much less common. We focus our attention on a lab course that has been transformed to engage students in this modeling process during lab activities. The design of the lab activities was guided by a framework that captures the different components of model-based reasoning, called the Modeling Framework for Experimental Physics. We demonstrate how this framework can be used to assess students' written work and to identify how students' model-based reasoning differed from activity to activity. Broadly speaking, we were able to identify the different steps of students' model-based reasoning and assess the completeness of their reasoning. Varying degrees of scaffolding present across the activities had an impact on how thoroughly students would engage in the full modeling process, with more scaffolded activities resulting in more thorough engagement with the process. Finally, we identified that the step in the process with which students had the most difficulty was the comparison between their interpreted data and their model prediction. Students did not use sufficiently sophisticated criteria in evaluating such comparisons, which had the effect of halting the modeling process. This may indicate that in order to engage students further in using model-based reasoning during lab activities, the instructor needs to provide further scaffolding for how students make these types of experimental comparisons. This is an important design consideration for other such courses attempting to incorporate modeling as a learning goal.

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…

Automated extraction of knowledge for model-based diagnostics

NASA Technical Reports Server (NTRS)

Gonzalez, Avelino J.; Myler, Harley R.; Towhidnejad, Massood; Mckenzie, Frederic D.; Kladke, Robin R.

1990-01-01

The concept of accessing computer aided design (CAD) design databases and extracting a process model automatically is investigated as a possible source for the generation of knowledge bases for model-based reasoning systems. The resulting system, referred to as automated knowledge generation (AKG), uses an object-oriented programming structure and constraint techniques as well as internal database of component descriptions to generate a frame-based structure that describes the model. The procedure has been designed to be general enough to be easily coupled to CAD systems that feature a database capable of providing label and connectivity data from the drawn system. The AKG system is capable of defining knowledge bases in formats required by various model-based reasoning tools.

Assessing Understanding of Biological Processes: Elucidating Students' Models of Meiosis.

ERIC Educational Resources Information Center

Kindfield, Ann C.

1994-01-01

Presents a meiosis reasoning problem that provides direct access to students' current models of chromosomes and meiosis. Also included in the article are tips for classroom implementation and a summary of the solution evaluation. (ZWH)

What is the role of induction and deduction in reasoning and scientific inquiry?

NASA Astrophysics Data System (ADS)

Lawson, Anton E.

2005-08-01

A long-standing and continuing controversy exists regarding the role of induction and deduction in reasoning and in scientific inquiry. Given the inherent difficulty in reconstructing reasoning patterns based on personal and historical accounts, evidence about the nature of human reasoning in scientific inquiry has been sought from a controlled experiment designed to identify the role played by enumerative induction and deduction in cognition as well as from the relatively new field of neural modeling. Both experimental results and the neurological models imply that induction across a limited set of observations plays no role in task performance and in reasoning. Therefore, support has been obtained for Popper's hypothesis that enumerative induction does not exist as a psychological process. Instead, people appear to process information in terms of increasingly abstract cycles of hypothetico-deductive reasoning. Consequently, science instruction should provide students with opportunities to generate and test increasingly complex and abstract hypotheses and theories in a hypothetico-deductive manner. In this way students can be expected to become increasingly conscious of their underlying hypothetico-deductive thought processes, increasingly skilled in their application, and hence increasingly scientifically literate.

Why do we eat? Children's and adults' understanding of why we eat different meals.

PubMed

Raman, Lakshmi

2011-01-01

In this study the author examined why children and adults think they need to eat. Preschoolers through adults were provided with physiological, social, psychological, and routine causes for eating breakfast, lunch, snack, and dinner, and were asked to either agree or disagree with the causal responses provided. A 4 Reason x 4 Meal repeated measures analysis of variance revealed significant main effects for meals and reasons, as well as significant Meal x Reason and Meal x Reason x Grade interactions. The effect sizes ranged from 0.1 to 0.7. Across all age groups, participants acknowledged physiological needs and desires (fulfilling hunger and needs to stay healthy) and routine (e.g., it is dinner time) as the primary causes for eating breakfast, lunch, and dinner. However, for snack physiological needs were the primary reason. Second-grade students onward spontaneously produced biological justifications such as the need for energy and nutrition as important reasons for food consumption. These results lend support to the developmental model that children's and adults' understanding of eating changes in middle childhood.

Approximate reasoning using terminological models

NASA Technical Reports Server (NTRS)

Yen, John; Vaidya, Nitin

1992-01-01

Term Subsumption Systems (TSS) form a knowledge-representation scheme in AI that can express the defining characteristics of concepts through a formal language that has a well-defined semantics and incorporates a reasoning mechanism that can deduce whether one concept subsumes another. However, TSS's have very limited ability to deal with the issue of uncertainty in knowledge bases. The objective of this research is to address issues in combining approximate reasoning with term subsumption systems. To do this, we have extended an existing AI architecture (CLASP) that is built on the top of a term subsumption system (LOOM). First, the assertional component of LOOM has been extended for asserting and representing uncertain propositions. Second, we have extended the pattern matcher of CLASP for plausible rule-based inferences. Third, an approximate reasoning model has been added to facilitate various kinds of approximate reasoning. And finally, the issue of inconsistency in truth values due to inheritance is addressed using justification of those values. This architecture enhances the reasoning capabilities of expert systems by providing support for reasoning under uncertainty using knowledge captured in TSS. Also, as definitional knowledge is explicit and separate from heuristic knowledge for plausible inferences, the maintainability of expert systems could be improved.

An improved probabilistic account of counterfactual reasoning.

PubMed

Lucas, Christopher G; Kemp, Charles

2015-10-01

When people want to identify the causes of an event, assign credit or blame, or learn from their mistakes, they often reflect on how things could have gone differently. In this kind of reasoning, one considers a counterfactual world in which some events are different from their real-world counterparts and considers what else would have changed. Researchers have recently proposed several probabilistic models that aim to capture how people do (or should) reason about counterfactuals. We present a new model and show that it accounts better for human inferences than several alternative models. Our model builds on the work of Pearl (2000), and extends his approach in a way that accommodates backtracking inferences and that acknowledges the difference between counterfactual interventions and counterfactual observations. We present 6 new experiments and analyze data from 4 experiments carried out by Rips (2010), and the results suggest that the new model provides an accurate account of both mean human judgments and the judgments of individuals. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

Collective rationality: the integrative model explains it (as) well.

PubMed

Van Lange, Paul A M

2008-06-01

In this commentary, I argue that there is indeed considerable evidence in support of the notion that people tend to reason from a collective (or team) perspective by asking themselves questions such as "What do we want, and what should I do help achieve it?" [Colman, A. M., Pulford, B. D., & Rose, J. (2008). Collective rationality in interactive decisions: Evidence for team reasoning. Acta Psychologica]. As such, in my view, team reasoning -- and thinking, feeling, and acting in terms of collective rationality -- is consistent with a social utility model (or transformational model) which considers the weights that people attach not only to outcomes for self, but also to outcomes for other, and to equality in outcomes [Van Lange, P. A. M. (1999). The pursuit of joint outcomes and equality in outcomes: An integrative model of social value orientation. Journal of Personality and Social Psychology,77, 337-349]. This commentary provides an illustration demonstrating that the integrative model is well-suited to account for the findings observed by Colman et al. (2008).

Nonrational processes in ethical decision making.

PubMed

Rogerson, Mark D; Gottlieb, Michael C; Handelsman, Mitchell M; Knapp, Samuel; Younggren, Jeffrey

2011-10-01

Most current ethical decision-making models provide a logical and reasoned process for making ethical judgments, but these models are empirically unproven and rely upon assumptions of rational, conscious, and quasilegal reasoning. Such models predominate despite the fact that many nonrational factors influence ethical thought and behavior, including context, perceptions, relationships, emotions, and heuristics. For example, a large body of behavioral research has demonstrated the importance of automatic intuitive and affective processes in decision making and judgment. These processes profoundly affect human behavior and lead to systematic biases and departures from normative theories of rationality. Their influence represents an important but largely unrecognized component of ethical decision making. We selectively review this work; provide various illustrations; and make recommendations for scientists, trainers, and practitioners to aid them in integrating the understanding of nonrational processes with ethical decision making.

Incorporating Resilience into Dynamic Social Models

DTIC Science & Technology

2016-07-20

solved by simply using the information provided by the scenario. Instead, additional knowledge is required from relevant fields that study these...resilience function by leveraging Bayesian Knowledge Bases (BKBs), a probabilistic reasoning network framework[5],[6]. BKBs allow for inferencing...reasoning network framework based on Bayesian Knowledge Bases (BKBs). BKBs are central to our social resilience framework as they are used to

Semantically-Rigorous Systems Engineering Modeling Using Sysml and OWL

NASA Technical Reports Server (NTRS)

Jenkins, J. Steven; Rouquette, Nicolas F.

2012-01-01

The Systems Modeling Language (SysML) has found wide acceptance as a standard graphical notation for the domain of systems engineering. SysML subsets and extends the Unified Modeling Language (UML) to define conventions for expressing structural, behavioral, and analytical elements, and relationships among them. SysML-enabled modeling tools are available from multiple providers, and have been used for diverse projects in military aerospace, scientific exploration, and civil engineering. The Web Ontology Language (OWL) has found wide acceptance as a standard notation for knowledge representation. OWL-enabled modeling tools are available from multiple providers, as well as auxiliary assets such as reasoners and application programming interface libraries, etc. OWL has been applied to diverse projects in a wide array of fields. While the emphasis in SysML is on notation, SysML inherits (from UML) a semantic foundation that provides for limited reasoning and analysis. UML's partial formalization (FUML), however, does not cover the full semantics of SysML, which is a substantial impediment to developing high confidence in the soundness of any conclusions drawn therefrom. OWL, by contrast, was developed from the beginning on formal logical principles, and consequently provides strong support for verification of consistency and satisfiability, extraction of entailments, conjunctive query answering, etc. This emphasis on formal logic is counterbalanced by the absence of any graphical notation conventions in the OWL standards. Consequently, OWL has had only limited adoption in systems engineering. The complementary strengths and weaknesses of SysML and OWL motivate an interest in combining them in such a way that we can benefit from the attractive graphical notation of SysML and the formal reasoning of OWL. This paper describes an approach to achieving that combination.

Bridging the Gap between Human Judgment and Automated Reasoning in Predictive Analytics

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

Sanfilippo, Antonio P.; Riensche, Roderick M.; Unwin, Stephen D.

2010-06-07

Events occur daily that impact the health, security and sustainable growth of our society. If we are to address the challenges that emerge from these events, anticipatory reasoning has to become an everyday activity. Strong advances have been made in using integrated modeling for analysis and decision making. However, a wider impact of predictive analytics is currently hindered by the lack of systematic methods for integrating predictive inferences from computer models with human judgment. In this paper, we present a predictive analytics approach that supports anticipatory analysis and decision-making through a concerted reasoning effort that interleaves human judgment and automatedmore » inferences. We describe a systematic methodology for integrating modeling algorithms within a serious gaming environment in which role-playing by human agents provides updates to model nodes and the ensuing model outcomes in turn influence the behavior of the human players. The approach ensures a strong functional partnership between human players and computer models while maintaining a high degree of independence and greatly facilitating the connection between model and game structures.« less

An architecture for the development of real-time fault diagnosis systems using model-based reasoning

NASA Technical Reports Server (NTRS)

Hall, Gardiner A.; Schuetzle, James; Lavallee, David; Gupta, Uday

1992-01-01

Presented here is an architecture for implementing real-time telemetry based diagnostic systems using model-based reasoning. First, we describe Paragon, a knowledge acquisition tool for offline entry and validation of physical system models. Paragon provides domain experts with a structured editing capability to capture the physical component's structure, behavior, and causal relationships. We next describe the architecture of the run time diagnostic system. The diagnostic system, written entirely in Ada, uses the behavioral model developed offline by Paragon to simulate expected component states as reflected in the telemetry stream. The diagnostic algorithm traces causal relationships contained within the model to isolate system faults. Since the diagnostic process relies exclusively on the behavioral model and is implemented without the use of heuristic rules, it can be used to isolate unpredicted faults in a wide variety of systems. Finally, we discuss the implementation of a prototype system constructed using this technique for diagnosing faults in a science instrument. The prototype demonstrates the use of model-based reasoning to develop maintainable systems with greater diagnostic capabilities at a lower cost.

Models of clinical reasoning with a focus on general practice: A critical review.

PubMed

Yazdani, Shahram; Hosseinzadeh, Mohammad; Hosseini, Fakhrolsadat

2017-10-01

Diagnosis lies at the heart of general practice. Every day general practitioners (GPs) visit patients with a wide variety of complaints and concerns, with often minor but sometimes serious symptoms. General practice has many features which differentiate it from specialty care setting, but during the last four decades little attention was paid to clinical reasoning in general practice. Therefore, we aimed to critically review the clinical reasoning models with a focus on the clinical reasoning in general practice or clinical reasoning of general practitioners to find out to what extent the existing models explain the clinical reasoning specially in primary care and also identity the gaps of the model for use in primary care settings. A systematic search to find models of clinical reasoning were performed. To have more precision, we excluded the studies that focused on neurobiological aspects of reasoning, reasoning in disciplines other than medicine decision making or decision analysis on treatment or management plan. All the articles and documents were first scanned to see whether they include important relevant contents or any models. The selected studies which described a model of clinical reasoning in general practitioners or with a focus on general practice were then reviewed and appraisal or critics of other authors on these models were included. The reviewed documents on the model were synthesized. Six models of clinical reasoning were identified including hypothetic-deductive model, pattern recognition, a dual process diagnostic reasoning model, pathway for clinical reasoning, an integrative model of clinical reasoning, and model of diagnostic reasoning strategies in primary care. Only one model had specifically focused on general practitioners reasoning. A Model of clinical reasoning that included specific features of general practice to better help the general practitioners with the difficulties of clinical reasoning in this setting is needed.

Evidentiary Reasoning in Diagnostic Classification Models

ERIC Educational Resources Information Center

Levy, Roy

2009-01-01

In "Unique Characteristics of Diagnostic Classification Models: A Comprehensive Review of the Current State-of-the-Art," Rupp and Templin (2008) undertake the ambitious task of providing a thorough portrait of the current state of diagnostic classification models (DCM). In this commentary, the author applauds Rupp and Templin for their…

New normative standards of conditional reasoning and the dual-source model

PubMed Central

Singmann, Henrik; Klauer, Karl Christoph; Over, David

2014-01-01

There has been a major shift in research on human reasoning toward Bayesian and probabilistic approaches, which has been called a new paradigm. The new paradigm sees most everyday and scientific reasoning as taking place in a context of uncertainty, and inference is from uncertain beliefs and not from arbitrary assumptions. In this manuscript we present an empirical test of normative standards in the new paradigm using a novel probabilized conditional reasoning task. Our results indicated that for everyday conditional with at least a weak causal connection between antecedent and consequent only the conditional probability of the consequent given antecedent contributes unique variance to predicting the probability of conditional, but not the probability of the conjunction, nor the probability of the material conditional. Regarding normative accounts of reasoning, we found significant evidence that participants' responses were confidence preserving (i.e., p-valid in the sense of Adams, 1998) for MP inferences, but not for MT inferences. Additionally, only for MP inferences and to a lesser degree for DA inferences did the rate of responses inside the coherence intervals defined by mental probability logic (Pfeifer and Kleiter, 2005, 2010) exceed chance levels. In contrast to the normative accounts, the dual-source model (Klauer et al., 2010) is a descriptive model. It posits that participants integrate their background knowledge (i.e., the type of information primary to the normative approaches) and their subjective probability that a conclusion is seen as warranted based on its logical form. Model fits showed that the dual-source model, which employed participants' responses to a deductive task with abstract contents to estimate the form-based component, provided as good an account of the data as a model that solely used data from the probabilized conditional reasoning task. PMID:24860516

New normative standards of conditional reasoning and the dual-source model.

PubMed

Singmann, Henrik; Klauer, Karl Christoph; Over, David

2014-01-01

There has been a major shift in research on human reasoning toward Bayesian and probabilistic approaches, which has been called a new paradigm. The new paradigm sees most everyday and scientific reasoning as taking place in a context of uncertainty, and inference is from uncertain beliefs and not from arbitrary assumptions. In this manuscript we present an empirical test of normative standards in the new paradigm using a novel probabilized conditional reasoning task. Our results indicated that for everyday conditional with at least a weak causal connection between antecedent and consequent only the conditional probability of the consequent given antecedent contributes unique variance to predicting the probability of conditional, but not the probability of the conjunction, nor the probability of the material conditional. Regarding normative accounts of reasoning, we found significant evidence that participants' responses were confidence preserving (i.e., p-valid in the sense of Adams, 1998) for MP inferences, but not for MT inferences. Additionally, only for MP inferences and to a lesser degree for DA inferences did the rate of responses inside the coherence intervals defined by mental probability logic (Pfeifer and Kleiter, 2005, 2010) exceed chance levels. In contrast to the normative accounts, the dual-source model (Klauer et al., 2010) is a descriptive model. It posits that participants integrate their background knowledge (i.e., the type of information primary to the normative approaches) and their subjective probability that a conclusion is seen as warranted based on its logical form. Model fits showed that the dual-source model, which employed participants' responses to a deductive task with abstract contents to estimate the form-based component, provided as good an account of the data as a model that solely used data from the probabilized conditional reasoning task.

Continuation rates and reasons for discontinuation of intra-uterine device in three provinces of Pakistan: results of a 24-month prospective client follow-up.

PubMed

Hameed, Waqas; Azmat, Syed Khurram; Ishaque, Muhammad; Hussain, Wajahat; Munroe, Erik; Mustafa, Ghulam; Khan, Omar Farooq; Abbas, Ghazunfer; Ali, Safdar; Asghar, Qaiser Jamshaid; Ali, Sajid; Ahmed, Aftab; Hamza, Hasan Bin

2015-11-25

Long-acting reversible contraceptives, such as the intrauterine device (IUD), remain underutilised in Pakistan with high discontinuation rates. Based on a 24-month prospective client follow-up (nested within a larger quasi-experimental study), this paper presents the comparison of two intervention models, one using private mid-level providers branded as "Suraj" and the other using community midwives (CMWs) of Maternal Newborn and Child Health Programme, for method continuation among IUD users. Moreover, determinants of IUD continuation and the reasons for discontinuation, and switching behaviour were studied within each arm. A total of 1,163 IUD users, 824 from Suraj and 339 from the CMW model, were enrolled in this 24-month prospective client follow-up. Participants were followed-up by female community mobilisers physically every second month to ascertain continued IUD usage and to collect information on associated factors, switching behaviour, reasons for discontinuation, and pregnancy occurrence. The probabilities of IUD continuation and the risk factors for discontinuation were estimated by life table analysis and Cox proportional-hazard techniques, respectively. The cumulative probabilities of IUD continuation at 24 months in Suraj and CMW models were 82% and 80%, respectively. The difference between the two intervention areas was not significant. The probability distributions of IUD continuation were also similar in both interventions (Log rank test: χ(2) = 0.06, df = 1, P = 0.81; Breslow test: χ(2) = 0.6, df = 1, P = 0.44). Health concerns (Suraj = 57.1%, CMW = 38.7%) and pregnancy desire (Suraj = 29.3%, CMW = 40.3%) were reported as the most prominent reasons for IUD discontinuation in both intervention arms. IUD discontinuation was significantly associated with place of residence in Suraj and with age (15-25 years) in the CMW model. CMWs and private providers are equally capable of providing quality IUD services and ensuring higher method continuation. Pakistan's National Maternal Newborn and Child Health programme should consider training CMWs and providing IUDs through them. Moreover, private sector mid-level providers could be engaged in promoting the use of IUDs.

QR-STEM: Energy and Environment as a Context for Improving QR and STEM Understandings of 6-12 Grade Teachers II. The Quantitative Reasoning

NASA Astrophysics Data System (ADS)

Mayes, R.; Lyford, M. E.; Myers, J. D.

2009-12-01

The Quantitative Reasoning in STEM (QR STEM) project is a state level Mathematics and Science Partnership Project (MSP) with a focus on the mathematics and statistics that underlies the understanding of complex global scientific issues. This session is a companion session to the QR STEM: The Science presentation. The focus of this session is the quantitative reasoning aspects of the project. As students move from understandings that range from local to global in perspective on issues of energy and environment, there is a significant increase in the need for mathematical and statistical conceptual understanding. These understandings must be accessible to the students within the scientific context, requiring the special understandings that are endemic within quantitative reasoning. The QR STEM project brings together interdisciplinary teams of higher education faculty and middle/high school teachers to explore complex problems in energy and environment. The disciplines include life sciences, physics, chemistry, earth science, statistics, and mathematics. These interdisciplinary teams develop open ended performance tasks to implement in the classroom, based on scientific concepts that underpin energy and environment. Quantitative reasoning is broken down into three components: Quantitative Literacy, Quantitative Interpretation, and Quantitative Modeling. Quantitative Literacy is composed of arithmetic concepts such as proportional reasoning, numeracy, and descriptive statistics. Quantitative Interpretation includes algebraic and geometric concepts that underlie the ability to interpret a model of natural phenomena which is provided for the student. This model may be a table, graph, or equation from which the student is to make predictions or identify trends, or from which they would use statistics to explore correlations or patterns in data. Quantitative modeling is the ability to develop the model from data, including the ability to test hypothesis using statistical procedures. We use the term model very broadly, so it includes visual models such as box models, as well as best fit equation models and hypothesis testing. One of the powerful outcomes of the project is the conversation which takes place between science teachers and mathematics teachers. First they realize that though they are teaching concepts that cross their disciplines, the barrier of scientific language within their subjects restricts students from applying the concepts across subjects. Second the mathematics teachers discover the context of science as a means of providing real world situations that engage students in the utility of mathematics as a tool for solving problems. Third the science teachers discover the barrier to understanding science that is presented by poor quantitative reasoning ability. Finally the students are engaged in exploring energy and environment in a manner which exposes the importance of seeing a problem from multiple interdisciplinary perspectives. The outcome is a democratic citizen capable of making informed decisions, and perhaps a future scientist.

Parametric models of reflectance spectra for dyed fabrics

NASA Astrophysics Data System (ADS)

Aiken, Daniel C.; Ramsey, Scott; Mayo, Troy; Lambrakos, Samuel G.; Peak, Joseph

2016-05-01

This study examines parametric modeling of NIR reflectivity spectra for dyed fabrics, which provides for both their inverse and direct modeling. The dye considered for prototype analysis is triarylamine dye. The fabrics considered are camouflage textiles characterized by color variations. The results of this study provide validation of the constructed parametric models, within reasonable error tolerances for practical applications, including NIR spectral characteristics in camouflage textiles, for purposes of simulating NIR spectra corresponding to various dye concentrations in host fabrics, and potentially to mixtures of dyes.

On the Reliability and Validity of a Numerical Reasoning Speed Dimension Derived from Response Times Collected in Computerized Testing

ERIC Educational Resources Information Center

Davison, Mark L.; Semmes, Robert; Huang, Lan; Close, Catherine N.

2012-01-01

Data from 181 college students were used to assess whether math reasoning item response times in computerized testing can provide valid and reliable measures of a speed dimension. The alternate forms reliability of the speed dimension was .85. A two-dimensional structural equation model suggests that the speed dimension is related to the accuracy…

The Recursive Paradigm: Suppose We Already Knew.

ERIC Educational Resources Information Center

Maurer, Stephen B.

1995-01-01

Explains the recursive model in discrete mathematics through five examples and problems. Discusses the relationship between the recursive model, mathematical induction, and inductive reasoning and the relevance of these concepts in the school curriculum. Provides ideas for approaching this material with students. (Author/DDD)

Models of clinical reasoning with a focus on general practice: A critical review

PubMed Central

YAZDANI, SHAHRAM; HOSSEINZADEH, MOHAMMAD; HOSSEINI, FAKHROLSADAT

2017-01-01

Introduction: Diagnosis lies at the heart of general practice. Every day general practitioners (GPs) visit patients with a wide variety of complaints and concerns, with often minor but sometimes serious symptoms. General practice has many features which differentiate it from specialty care setting, but during the last four decades little attention was paid to clinical reasoning in general practice. Therefore, we aimed to critically review the clinical reasoning models with a focus on the clinical reasoning in general practice or clinical reasoning of general practitioners to find out to what extent the existing models explain the clinical reasoning specially in primary care and also identity the gaps of the model for use in primary care settings. Methods: A systematic search to find models of clinical reasoning were performed. To have more precision, we excluded the studies that focused on neurobiological aspects of reasoning, reasoning in disciplines other than medicine decision making or decision analysis on treatment or management plan. All the articles and documents were first scanned to see whether they include important relevant contents or any models. The selected studies which described a model of clinical reasoning in general practitioners or with a focus on general practice were then reviewed and appraisal or critics of other authors on these models were included. The reviewed documents on the model were synthesized. Results: Six models of clinical reasoning were identified including hypothetic-deductive model, pattern recognition, a dual process diagnostic reasoning model, pathway for clinical reasoning, an integrative model of clinical reasoning, and model of diagnostic reasoning strategies in primary care. Only one model had specifically focused on general practitioners reasoning. Conclusion: A Model of clinical reasoning that included specific features of general practice to better help the general practitioners with the difficulties of clinical reasoning in this setting is needed. PMID:28979912

JEDI Transmission Line Model | Jobs and Economic Development Impact Models

Science.gov Websites

, reasonable default values are provided. Individual projects may vary and when possible, project specific data Line Model rel. TL12.23.16. JEDI Transmission Line Model User Reference Guide Using MS Excel 2007 When ;High." Set the level to "Medium" or "Low" and then re-open the JEDI worksheet

Diagnostic causal reasoning with verbal information.

PubMed

Meder, Björn; Mayrhofer, Ralf

2017-08-01

In diagnostic causal reasoning, the goal is to infer the probability of causes from one or multiple observed effects. Typically, studies investigating such tasks provide subjects with precise quantitative information regarding the strength of the relations between causes and effects or sample data from which the relevant quantities can be learned. By contrast, we sought to examine people's inferences when causal information is communicated through qualitative, rather vague verbal expressions (e.g., "X occasionally causes A"). We conducted three experiments using a sequential diagnostic inference task, where multiple pieces of evidence were obtained one after the other. Quantitative predictions of different probabilistic models were derived using the numerical equivalents of the verbal terms, taken from an unrelated study with different subjects. We present a novel Bayesian model that allows for incorporating the temporal weighting of information in sequential diagnostic reasoning, which can be used to model both primacy and recency effects. On the basis of 19,848 judgments from 292 subjects, we found a remarkably close correspondence between the diagnostic inferences made by subjects who received only verbal information and those of a matched control group to whom information was presented numerically. Whether information was conveyed through verbal terms or numerical estimates, diagnostic judgments closely resembled the posterior probabilities entailed by the causes' prior probabilities and the effects' likelihoods. We observed interindividual differences regarding the temporal weighting of evidence in sequential diagnostic reasoning. Our work provides pathways for investigating judgment and decision making with verbal information within a computational modeling framework. Copyright © 2017 Elsevier Inc. All rights reserved.

Overcoming rule-based rigidity and connectionist limitations through massively-parallel case-based reasoning

NASA Technical Reports Server (NTRS)

Barnden, John; Srinivas, Kankanahalli

1990-01-01

Symbol manipulation as used in traditional Artificial Intelligence has been criticized by neural net researchers for being excessively inflexible and sequential. On the other hand, the application of neural net techniques to the types of high-level cognitive processing studied in traditional artificial intelligence presents major problems as well. A promising way out of this impasse is to build neural net models that accomplish massively parallel case-based reasoning. Case-based reasoning, which has received much attention recently, is essentially the same as analogy-based reasoning, and avoids many of the problems leveled at traditional artificial intelligence. Further problems are avoided by doing many strands of case-based reasoning in parallel, and by implementing the whole system as a neural net. In addition, such a system provides an approach to some aspects of the problems of noise, uncertainty and novelty in reasoning systems. The current neural net system (Conposit), which performs standard rule-based reasoning, is being modified into a massively parallel case-based reasoning version.

Training propositional reasoning.

PubMed

Klauer, K C; Meiser, T; Naumer, B

2000-08-01

Two experiments compared the effects of four training conditions on propositional reasoning. A syntactic training demonstrated formal derivations, in an abstract semantic training the standard truth-table definitions of logical connectives were explained, and a domain-specific semantic training provided thematic contexts for the premises of the reasoning task. In a control training, an inductive reasoning task was practised. In line with the account by mental models, both kinds of semantic training were significantly more effective than the control and the syntactic training, whereas there were no significant differences between the control and the syntactic training, nor between the two kinds of semantic training. Experiment 2 replicated this pattern of effects using a different set of syntactic and domain-specific training conditions.

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

PubMed

Quillin, Kim; Thomas, Stephen

2015-03-02

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

Bayes factors and multimodel inference

USGS Publications Warehouse

Link, W.A.; Barker, R.J.; Thomson, David L.; Cooch, Evan G.; Conroy, Michael J.

2009-01-01

Multimodel inference has two main themes: model selection, and model averaging. Model averaging is a means of making inference conditional on a model set, rather than on a selected model, allowing formal recognition of the uncertainty associated with model choice. The Bayesian paradigm provides a natural framework for model averaging, and provides a context for evaluation of the commonly used AIC weights. We review Bayesian multimodel inference, noting the importance of Bayes factors. Noting the sensitivity of Bayes factors to the choice of priors on parameters, we define and propose nonpreferential priors as offering a reasonable standard for objective multimodel inference.

77 FR 50390 - Equal Credit Opportunity Act (Regulation B)

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-21

... management companies, automated valuation models, and providing copies of appraisals and valuations.\\8\\ Many... the Bureau is considering proposing rules on reasonable information management, early intervention for...

New V and V Tools for Diagnostic Modeling Environment (DME)

NASA Technical Reports Server (NTRS)

Pecheur, Charles; Nelson, Stacy; Merriam, Marshall (Technical Monitor)

2002-01-01

The purpose of this report is to provide correctness and reliability criteria for verification and validation (V&V) of Second Generation Reusable Launch Vehicle (RLV) Diagnostic Modeling Environment, describe current NASA Ames Research Center tools for V&V of Model Based Reasoning systems, and discuss the applicability of Advanced V&V to DME. This report is divided into the following three sections: (1) correctness and reliability criteria; (2) tools for V&V of Model Based Reasoning; and (3) advanced V&V applicable to DME. The Executive Summary includes an overview of the main points from each section. Supporting details, diagrams, figures, and other information are included in subsequent sections. A glossary, acronym list, appendices, and references are included at the end of this report.

Intelligent Chatter Bot for Regulation Search

NASA Astrophysics Data System (ADS)

De Luise, María Daniela López; Pascal, Andrés; Saad, Ben; Álvarez, Claudia; Pescio, Pablo; Carrilero, Patricio; Malgor, Rafael; Díaz, Joaquín

2016-01-01

This communication presents a functional prototype, named PTAH, implementing a linguistic model focused on regulations in Spanish. Its global architecture, the reasoning model and short statistics are provided for the prototype. It is mainly a conversational robot linked to an Expert System by a module with many intelligent linguistic filters, implementing the reasoning model of an expert. It is focused on bylaws, regulations, jurisprudence and customized background representing entity mission, vision and profile. This Structure and model are generic enough to self-adapt to any regulatory environment, but as a first step, it was limited to an academic field. This way it is possible to limit the slang and data numbers. The foundations of the linguistic model are also outlined and the way the architecture implements the key features of the behavior.

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)

The effect of emotion on interpretation and logic in a conditional reasoning task.

PubMed

Blanchette, Isabelle

2006-07-01

The effect of emotional content on logical reasoning is explored in three experiments. Theparticipants completed a conditional reasoning task (If p, then q) with emotional and neutral contents. In Experiment 1, existing emotional and neutral words were used. The emotional value of initially neutral words was experimentally manipulated in Experiments 1B and 2, using classical conditioning. In all experiments, participants were less likely to provide normatively correct answers when reasoning about emotional stimuli, compared with neutral stimuli. This was true for both negative (Experiments 1B and 2) and positive contents (Experiment 2). The participants' interpretations of the conditional statements were also measured (perceived sufficiency, necessity, causality, and plausibility). The results showed the expected relationship between interpretation and reasoning. However, emotion did not affect interpretation. Emotional and neutral conditional statements were interpreted similarly. The results are discussed in light of current models of emotion and reasoning.

Integrated software health management for aerospace guidance, navigation, and control systems: A probabilistic reasoning approach

NASA Astrophysics Data System (ADS)

Mbaya, Timmy

Embedded Aerospace Systems have to perform safety and mission critical operations in a real-time environment where timing and functional correctness are extremely important. Guidance, Navigation, and Control (GN&C) systems substantially rely on complex software interfacing with hardware in real-time; any faults in software or hardware, or their interaction could result in fatal consequences. Integrated Software Health Management (ISWHM) provides an approach for detection and diagnosis of software failures while the software is in operation. The ISWHM approach is based on probabilistic modeling of software and hardware sensors using a Bayesian network. To meet memory and timing constraints of real-time embedded execution, the Bayesian network is compiled into an Arithmetic Circuit, which is used for on-line monitoring. This type of system monitoring, using an ISWHM, provides automated reasoning capabilities that compute diagnoses in a timely manner when failures occur. This reasoning capability enables time-critical mitigating decisions and relieves the human agent from the time-consuming and arduous task of foraging through a multitude of isolated---and often contradictory---diagnosis data. For the purpose of demonstrating the relevance of ISWHM, modeling and reasoning is performed on a simple simulated aerospace system running on a real-time operating system emulator, the OSEK/Trampoline platform. Models for a small satellite and an F-16 fighter jet GN&C (Guidance, Navigation, and Control) system have been implemented. Analysis of the ISWHM is then performed by injecting faults and analyzing the ISWHM's diagnoses.

Approximate Model for Turbulent Stagnation Point Flow.

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

Dechant, Lawrence

2016-01-01

Here we derive an approximate turbulent self-similar model for a class of favorable pressure gradient wedge-like flows, focusing on the stagnation point limit. While the self-similar model provides a useful gross flow field estimate this approach must be combined with a near wall model is to determine skin friction and by Reynolds analogy the heat transfer coefficient. The combined approach is developed in detail for the stagnation point flow problem where turbulent skin friction and Nusselt number results are obtained. Comparison to the classical Van Driest (1958) result suggests overall reasonable agreement. Though the model is only valid near themore » stagnation region of cylinders and spheres it nonetheless provides a reasonable model for overall cylinder and sphere heat transfer. The enhancement effect of free stream turbulence upon the laminar flow is used to derive a similar expression which is valid for turbulent flow. Examination of free stream enhanced laminar flow suggests that the rather than enhancement of a laminar flow behavior free stream disturbance results in early transition to turbulent stagnation point behavior. Excellent agreement is shown between enhanced laminar flow and turbulent flow behavior for high levels, e.g. 5% of free stream turbulence. Finally the blunt body turbulent stagnation results are shown to provide realistic heat transfer results for turbulent jet impingement problems.« less

Emerging issues with mentally ill offenders: causes and social consequences.

PubMed

Rock, M

2001-01-01

Persons with mental illness and co-occurring substance abuse disorders are incarcerated at disproportionately high rates in comparison to the general population. Reasons may include high standards for involuntary commitment, an overall increase in substance abuse and the policy of deinstitutionalization. However, one significant reason may be that psychiatric institutions serve a social control function, which has not been appreciated by policymakers and program developers since deinstitutionalization. This paper presents provider views of the population and issues of concern for clients, families, and the agencies. Discussion includes service-provider response to the population, new program models, and implications for policymakers.

Modeling Multiplicative Error Variance: An Example Predicting Tree Diameter from Stump Dimensions in Baldcypress

Treesearch

Bernard R. Parresol

1993-01-01

In the context of forest modeling, it is often reasonable to assume a multiplicative heteroscedastic error structure to the data. Under such circumstances ordinary least squares no longer provides minimum variance estimates of the model parameters. Through study of the error structure, a suitable error variance model can be specified and its parameters estimated. This...

Transforming Undergraduate Education Through the use of Analytical Reasoning (TUETAR)

NASA Astrophysics Data System (ADS)

Bishop, M. P.; Houser, C.; Lemmons, K.

2015-12-01

Traditional learning limits the potential for self-discovery, and the use of data and knowledge to understand Earth system relationships, processes, feedback mechanisms and system coupling. It is extremely difficult for undergraduate students to analyze, synthesize, and integrate quantitative information related to complex systems, as many concepts may not be mathematically tractable or yet to be formalized. Conceptual models have long served as a means for Earth scientists to organize their understanding of Earth's dynamics, and have served as a basis for human analytical reasoning and landscape interpretation. Consequently, we evaluated the use of conceptual modeling, knowledge representation and analytical reasoning to provide undergraduate students with an opportunity to develop and test geocomputational conceptual models based upon their understanding of Earth science concepts. This study describes the use of geospatial technologies and fuzzy cognitive maps to predict desertification across the South-Texas Sandsheet in an upper-level geomorphology course. Students developed conceptual models based on their understanding of aeolian processes from lectures, and then compared and evaluated their modeling results against an expert conceptual model and spatial predictions, and the observed distribution of dune activity in 2010. Students perceived that the analytical reasoning approach was significantly better for understanding desertification compared to traditional lecture, and promoted reflective learning, working with data, teamwork, student interaction, innovation, and creative thinking. Student evaluations support the notion that the adoption of knowledge representation and analytical reasoning in the classroom has the potential to transform undergraduate education by enabling students to formalize and test their conceptual understanding of Earth science. A model for developing and utilizing this geospatial technology approach in Earth science is presented.

Ultrasonic Motors (USM) - an emerging actuation technology for planetary applications

NASA Technical Reports Server (NTRS)

Bao, X.; Das, H.

2000-01-01

A hybrid model that addressed a complete ultrasonic motor as a system was developed. The model allows using powerful commercial FE package to express dynamic characteristics of the stator and the rotor in engineering practice. An analog model couples the finite element models for the stator and rotor for the stator-interface layer-rotor syste. The model provides reasonably accurate results for CAD.

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.

Qualitative Results from a Flight Investigation to Determine Aileron Effectiveness of Two Rocket-Propelled 1/20-Scale Models of the MX -76 Missile

NASA Technical Reports Server (NTRS)

Stevens, Joseph E.

1955-01-01

Free-flight tests of two rocket-propelled l/20-scale models of the Bell MX-776 missile have been conducted to obtain measurements of the aileron deflection required to counteract the induced rolling moments caused by combined angles of attack and sideslip and thus to determine whether the ailerons provided were capable of controlling the model at the attitudes produced by the test conditions. Inability to obtain reasonably steady-state conditions and superimposed high-frequency oscillations in the data precluded any detailed analysis of the results obtained from the tests. For these reasons, the data presented are limited largely to qualitative results.

Extended MAGTF Operations - Tactical Chat

DTIC Science & Technology

2017-03-01

vertical obstructions?  Over what ranges might such a system maintain connectivity? E . ORGANIZATION OF THESIS This thesis is organized in the...likely future models of UAVs will likely be capable of providing a relay platform for a long-range communication system that can solve the shadowing...problem presented in this study. However, for reasons outlined in the remainder of this section, current models of UAVs do not appear to provide a

Exploring the Effect of Embedded Scaffolding within Curricular Tasks on Third-Grade Students' Model-Based Explanations about Hydrologic Cycling

ERIC Educational Resources Information Center

Zangori, Laura; Forbes, Cory T.; Schwarz, Christina V.

2015-01-01

Opportunities to generate model-based explanations are crucial for elementary students, yet are rarely foregrounded in elementary science learning environments despite evidence that early learners can reason from models when provided with scaffolding. We used a quasi-experimental research design to investigate the comparative impact of a scaffold…

What variables can influence clinical reasoning?

PubMed

Ashoorion, Vahid; Liaghatdar, Mohammad Javad; Adibi, Peyman

2012-12-01

Clinical reasoning is one of the most important competencies that a physician should achieve. Many medical schools and licensing bodies try to predict it based on some general measures such as critical thinking, personality, and emotional intelligence. This study aimed at providing a model to design the relationship between the constructs. Sixty-nine medical students participated in this study. A battery test devised that consist four parts: Clinical reasoning measures, personality NEO inventory, Bar-On EQ inventory, and California critical thinking questionnaire. All participants completed the tests. Correlation and multiple regression analysis consumed for data analysis. There is low to moderate correlations between clinical reasoning and other variables. Emotional intelligence is the only variable that contributes clinical reasoning construct (r=0.17-0.34) (R(2) chnage = 0.46, P Value = 0.000). Although, clinical reasoning can be considered as a kind of thinking, no significant correlation detected between it and other constructs. Emotional intelligence (and its subscales) is the only variable that can be used for clinical reasoning prediction.

Dental care and treatments provided under general anaesthesia in the Helsinki Public Dental Service

PubMed Central

2012-01-01

Background Dental general anaesthesia (DGA) is a very efficient treatment modality, but is considered only in the last resort because of the risks posed by general anaesthesia to patients’ overall health. Health services and their treatment policies regarding DGA vary from country to country. The aims of this work were to determine the reasons for DGA in the Helsinki Public Dental Service (PDS) and to assess the role of patient characteristics in the variation in reasons and in the treatments given with special focus on preventive care. Methods The data covered all DGA patients treated in the PDS in Helsinki in 2010. The data were collected from patient documents and included personal background: age (<6, 6–12, 13–17, 18–68), gender, immigration, previous conscious sedation and previous DGA; medical background; reasons for DGA and treatments provided. Chi-square tests, Fisher’s exact test, and logistic regression modelling were employed in the statistical analyses. Results The DGA patients (n=349) were aged 2.3 to 67.2 years. Immigrants predominated in the youngest age group (p<0.001) and medically compromised patients among the adults (p<0.001) relative to the other age groups. The main reason for DGA was extreme non-cooperation (65%) followed by dental fear (37%) and an excessive need for treatment (26%). In total, 3435 treatments were performed under DGA, 57% of which were restorations, 24% tooth extractions, 5% preventive measures, 5% radiography, 4% endodontics and the remaining 5% periodontics, surgical procedures and miscellaneous. The reasons for DGA and the treatments provided varied according to age, immigration, previous sedation and DGA and medical background. The logistic regression model showed that previous sedation (OR 2.3; 95%CI 1.3-4.1; p=0.005) and extreme non-cooperation (OR 1.7; 95%CI 0.9-3.2; p=0.103) were most indicative of preventive measures given. Conclusions Extreme non-cooperation, dental fear and an excessive need for treatment were the main reasons for the use of comprehensive, conservative DGA in the Helsinki PDS. The reasons for the use of DGA and the treatments provided varied according to personal and medical background, and immigration status with no gender-differences. Preventive measures formed only a minor part of the dental care given under DGA. PMID:23102205

Dental care and treatments provided under general anaesthesia in the Helsinki Public Dental Service.

PubMed

Savanheimo, Nora; Sundberg, Sari A; Virtanen, Jorma I; Vehkalahti, Miira M

2012-10-27

Dental general anaesthesia (DGA) is a very efficient treatment modality, but is considered only in the last resort because of the risks posed by general anaesthesia to patients' overall health. Health services and their treatment policies regarding DGA vary from country to country. The aims of this work were to determine the reasons for DGA in the Helsinki Public Dental Service (PDS) and to assess the role of patient characteristics in the variation in reasons and in the treatments given with special focus on preventive care. The data covered all DGA patients treated in the PDS in Helsinki in 2010. The data were collected from patient documents and included personal background: age (<6, 6-12, 13-17, 18-68), gender, immigration, previous conscious sedation and previous DGA; medical background; reasons for DGA and treatments provided. Chi-square tests, Fisher's exact test, and logistic regression modelling were employed in the statistical analyses. The DGA patients (n=349) were aged 2.3 to 67.2 years. Immigrants predominated in the youngest age group (p<0.001) and medically compromised patients among the adults (p<0.001) relative to the other age groups. The main reason for DGA was extreme non-cooperation (65%) followed by dental fear (37%) and an excessive need for treatment (26%). In total, 3435 treatments were performed under DGA, 57% of which were restorations, 24% tooth extractions, 5% preventive measures, 5% radiography, 4% endodontics and the remaining 5% periodontics, surgical procedures and miscellaneous. The reasons for DGA and the treatments provided varied according to age, immigration, previous sedation and DGA and medical background. The logistic regression model showed that previous sedation (OR 2.3; 95%CI 1.3-4.1; p=0.005) and extreme non-cooperation (OR 1.7; 95%CI 0.9-3.2; p=0.103) were most indicative of preventive measures given. Extreme non-cooperation, dental fear and an excessive need for treatment were the main reasons for the use of comprehensive, conservative DGA in the Helsinki PDS. The reasons for the use of DGA and the treatments provided varied according to personal and medical background, and immigration status with no gender-differences. Preventive measures formed only a minor part of the dental care given under DGA.

Semiotic and Theoretic Control in Argumentation and Proof Activities

ERIC Educational Resources Information Center

Arzarello, Ferdinando; Sabena, Cristina

2011-01-01

We present a model to analyze the students' activities of argumentation and proof in the graphical context of Elementary Calculus. The theoretical background is provided by the integration of Toulmin's structural description of arguments, Peirce's notions of sign, diagrammatic reasoning and abduction, and Habermas' model for rational behavior.…

The E-R-A Model: A Heuristic Framework for Classification of Skill Training Programs for Couples and Families.

ERIC Educational Resources Information Center

Ulrici, Donna; And Others

1981-01-01

Provides a model for categorizing marital and family skill training programs according to their theoretical orientation. Describes emotional, reasoning, and action approaches to intervention which allow counselors to examine the relationship between client characteristics and intervention approaches. (JAC)

Product-market differentiation: a strategic planning model for community hospitals.

PubMed

Milch, R A

1980-01-01

Community hospitals would seem to have every reason to identify and capitalize on their product-market strengths. The strategic marketing/planning model provides a framework for rational analysis of the community hospital dilemma and for developing sensible solutions to the complex problems of accelerating hospital price-inflation.

Revisiting Your Outdoor Environment: Reasons to Reshape, Enrich, Redevelop the Outdoor Space.

ERIC Educational Resources Information Center

Mauffette, Anne Gillain

1998-01-01

Provides suggestions for designing effective outdoor space. Focuses on advocating for space, designing spaces based on children's characteristics and preferences, integrating the outdoors in educational planning, including children in decision making and work, knowing about injury prevention, providing adult models who love the outdoors, and…

Using Classic Mystery Stories in Teaching.

ERIC Educational Resources Information Center

Sheldon, Stephen H.; Noronha, Peter A.

1990-01-01

One third-year clinical clerkship in pediatrics has included Sherlock Holmes mysteries in its introductory curriculum, providing students with a model clinical problem-solving process and a list of issues on which they will need information. The nonclinical cases provide an effective and entertaining vehicle for learning clinical reasoning. (MSE)

A Bayesian Framework for False Belief Reasoning in Children: A Rational Integration of Theory-Theory and Simulation Theory

PubMed Central

Asakura, Nobuhiko; Inui, Toshio

2016-01-01

Two apparently contrasting theories have been proposed to account for the development of children's theory of mind (ToM): theory-theory and simulation theory. We present a Bayesian framework that rationally integrates both theories for false belief reasoning. This framework exploits two internal models for predicting the belief states of others: one of self and one of others. These internal models are responsible for simulation-based and theory-based reasoning, respectively. The framework further takes into account empirical studies of a developmental ToM scale (e.g., Wellman and Liu, 2004): developmental progressions of various mental state understandings leading up to false belief understanding. By representing the internal models and their interactions as a causal Bayesian network, we formalize the model of children's false belief reasoning as probabilistic computations on the Bayesian network. This model probabilistically weighs and combines the two internal models and predicts children's false belief ability as a multiplicative effect of their early-developed abilities to understand the mental concepts of diverse beliefs and knowledge access. Specifically, the model predicts that children's proportion of correct responses on a false belief task can be closely approximated as the product of their proportions correct on the diverse belief and knowledge access tasks. To validate this prediction, we illustrate that our model provides good fits to a variety of ToM scale data for preschool children. We discuss the implications and extensions of our model for a deeper understanding of developmental progressions of children's ToM abilities. PMID:28082941

A Bayesian Framework for False Belief Reasoning in Children: A Rational Integration of Theory-Theory and Simulation Theory.

PubMed

Asakura, Nobuhiko; Inui, Toshio

2016-01-01

Two apparently contrasting theories have been proposed to account for the development of children's theory of mind (ToM): theory-theory and simulation theory. We present a Bayesian framework that rationally integrates both theories for false belief reasoning. This framework exploits two internal models for predicting the belief states of others: one of self and one of others. These internal models are responsible for simulation-based and theory-based reasoning, respectively. The framework further takes into account empirical studies of a developmental ToM scale (e.g., Wellman and Liu, 2004): developmental progressions of various mental state understandings leading up to false belief understanding. By representing the internal models and their interactions as a causal Bayesian network, we formalize the model of children's false belief reasoning as probabilistic computations on the Bayesian network. This model probabilistically weighs and combines the two internal models and predicts children's false belief ability as a multiplicative effect of their early-developed abilities to understand the mental concepts of diverse beliefs and knowledge access. Specifically, the model predicts that children's proportion of correct responses on a false belief task can be closely approximated as the product of their proportions correct on the diverse belief and knowledge access tasks. To validate this prediction, we illustrate that our model provides good fits to a variety of ToM scale data for preschool children. We discuss the implications and extensions of our model for a deeper understanding of developmental progressions of children's ToM abilities.

Improved multi-objective ant colony optimization algorithm and its application in complex reasoning

NASA Astrophysics Data System (ADS)

Wang, Xinqing; Zhao, Yang; Wang, Dong; Zhu, Huijie; Zhang, Qing

2013-09-01

The problem of fault reasoning has aroused great concern in scientific and engineering fields. However, fault investigation and reasoning of complex system is not a simple reasoning decision-making problem. It has become a typical multi-constraint and multi-objective reticulate optimization decision-making problem under many influencing factors and constraints. So far, little research has been carried out in this field. This paper transforms the fault reasoning problem of complex system into a paths-searching problem starting from known symptoms to fault causes. Three optimization objectives are considered simultaneously: maximum probability of average fault, maximum average importance, and minimum average complexity of test. Under the constraints of both known symptoms and the causal relationship among different components, a multi-objective optimization mathematical model is set up, taking minimizing cost of fault reasoning as the target function. Since the problem is non-deterministic polynomial-hard(NP-hard), a modified multi-objective ant colony algorithm is proposed, in which a reachability matrix is set up to constrain the feasible search nodes of the ants and a new pseudo-random-proportional rule and a pheromone adjustment mechinism are constructed to balance conflicts between the optimization objectives. At last, a Pareto optimal set is acquired. Evaluation functions based on validity and tendency of reasoning paths are defined to optimize noninferior set, through which the final fault causes can be identified according to decision-making demands, thus realize fault reasoning of the multi-constraint and multi-objective complex system. Reasoning results demonstrate that the improved multi-objective ant colony optimization(IMACO) can realize reasoning and locating fault positions precisely by solving the multi-objective fault diagnosis model, which provides a new method to solve the problem of multi-constraint and multi-objective fault diagnosis and reasoning of complex system.

A Quantum Probability Model of Causal Reasoning

PubMed Central

Trueblood, Jennifer S.; Busemeyer, Jerome R.

2012-01-01

People can often outperform statistical methods and machine learning algorithms in situations that involve making inferences about the relationship between causes and effects. While people are remarkably good at causal reasoning in many situations, there are several instances where they deviate from expected responses. This paper examines three situations where judgments related to causal inference problems produce unexpected results and describes a quantum inference model based on the axiomatic principles of quantum probability theory that can explain these effects. Two of the three phenomena arise from the comparison of predictive judgments (i.e., the conditional probability of an effect given a cause) with diagnostic judgments (i.e., the conditional probability of a cause given an effect). The third phenomenon is a new finding examining order effects in predictive causal judgments. The quantum inference model uses the notion of incompatibility among different causes to account for all three phenomena. Psychologically, the model assumes that individuals adopt different points of view when thinking about different causes. The model provides good fits to the data and offers a coherent account for all three causal reasoning effects thus proving to be a viable new candidate for modeling human judgment. PMID:22593747

Use of and Reasons for Using Multiple Other Tobacco Products in Daily and Nondaily Smokers: Associations with Cigarette Consumption and Nicotine Dependence

PubMed Central

Dunbar, Michael S.; Shadel, William G.; Tucker, Joan S.; Edelen, Maria O.

2016-01-01

Background Use of other tobacco products (OTPs) among smokers is increasing. Little is known about types of OTP used and the reasons for use, and how OTP use and reasons for use correlate with smoking patterns and nicotine dependence in daily and nondaily smokers. This paper addresses these gaps in the literature. Methods 656 daily smokers and 203 nondaily smokers provided information on their use of different OTPs (hookah, e-cigarettes, chew/snuff, snus, cigars, dissolvables), and reasons for using OTPs (e.g., “to cut down on smoking”), as well as their cigarette consumption and nicotine dependence. Logistic regression models assessed the association of smoking status with OTP use (ever and current) and reasons for use. Within each smoking group, separate logistic regression models examined the associations of OTP use and reasons for use with cigarette consumption and nicotine dependence. Results Compared to daily smokers, nondaily smokers were more likely to use hookah and cigars, less likely to use dissolvables, and less likely to endorse using OTPs to reduce their smoking. Among non-daily smokers, nicotine dependence was associated with a higher likelihood of current OTP use (OR=1.04 [95% CI 1.01–1.07]; p < .05), whereas cigarette consumption was not. Conclusions Results suggest OTP use in nondaily smokers does not correlate with less frequent smoking, but may correlate with higher nicotine dependence. Use of combustible OTPs among nondaily smokers may offset any potential benefits achieved through less frequent cigarette consumption. Providers should explicitly address OTP use when discussing cigarette cessation and reduction. PMID:27664553

Use of and reasons for using multiple other tobacco products in daily and nondaily smokers: Associations with cigarette consumption and nicotine dependence.

PubMed

Dunbar, Michael S; Shadel, William G; Tucker, Joan S; Edelen, Maria O

2016-11-01

Use of other tobacco products (OTPs) among smokers is increasing. Little is known about types of OTP used and the reasons for use, and how OTP use and reasons for use correlate with smoking patterns and nicotine dependence in daily and nondaily smokers. This paper addresses these gaps in the literature. 656 daily smokers and 203 nondaily smokers provided information on their use of different OTPs (hookah, e-cigarettes, chew/snuff, snus, cigars, dissolvables), and reasons for using OTPs (e.g., "to cut down on smoking"), as well as their cigarette consumption and nicotine dependence. Logistic regression models assessed the association of smoking status with OTP use (ever and current) and reasons for use. Within each smoking group, separate logistic regression models examined the associations of OTP use and reasons for use with cigarette consumption and nicotine dependence. Compared to daily smokers, nondaily smokers were more likely to use hookah and cigars, less likely to use dissolvables, and less likely to endorse using OTPs to reduce their smoking. Among non-daily smokers, nicotine dependence was associated with a higher likelihood of current OTP use (OR=1.04 [95% CI 1.01-1.07]; p<0.05), whereas cigarette consumption was not. Results suggest OTP use in nondaily smokers does not correlate with less frequent smoking, but may correlate with higher nicotine dependence. Use of combustible OTPs among nondaily smokers may offset any potential benefits achieved through less frequent cigarette consumption. Providers should explicitly address OTP use when discussing cigarette cessation and reduction. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Clinical Reasoning in Massage Therapy

PubMed Central

LeMoon, Kim

2008-01-01

Background: Clinical reasoning has long been a valuable tool for health care practitioners, but it has been under-researched in the field of massage therapy. Case reports have been a useful method for exploring the clinical reasoning process in various fields of manual therapy and can provide a model for similar research in the field of massage therapy. A diagnostically challenging case concerning a client with low back pain serves as a guideline for examining the clinical reasoning process of a massage therapist. Methods: A two-part methodology was employed: Client profileReflective inquiry The inquiry included questions pertaining to beliefs about health problems; beliefs about the mechanisms of pain; medical conditions that could explain the client’s symptoms; knowledge of the client’s anatomy, assessment, and treatment choices; observations made during treatment; extent of experience in treating similar problems; and ability to recognize clinical patterns. Results: The clinical reasoning process of a massage therapist contributed to a differential diagnosis, which provided an explanation for the client’s symptoms and led to a satisfactory treatment resolution. Conclusion: The present report serves as an example of the value of clinical reasoning in the field of massage therapy, and the need for expanded research into its methods and applications. The results of such research could be beneficial in teaching the clinical reasoning process at both the introductory and the advanced levels of massage therapy education. PMID:21589814

Mechanical Characteristics Analysis of Surrounding Rock on Anchor Bar Reinforcement

NASA Astrophysics Data System (ADS)

Gu, Shuan-cheng; Zhou, Pan; Huang, Rong-bin

2018-03-01

Through the homogenization method, the composite of rock and anchor bar is considered as the equivalent material of continuous, homogeneous, isotropic and strength parameter enhancement, which is defined as reinforcement body. On the basis of elasticity, the composite and the reinforcement are analyzed, Based on strengthening theory of surrounding rock and displacement equivalent conditions, the expression of reinforcement body strength parameters and mechanical parameters is deduced. The example calculation shows that the theoretical results are close to the results of the Jia-mei Gao[9], however, closer to the results of FLAC3D numerical simulation, it is proved that the model and surrounding rock reinforcement body theory are reasonable. the model is easy to analyze and calculate, provides a new way for determining reasonable bolt support parameters, can also provides reference for the stability analysis of underground cavern bolting support.

Possibilities: A framework for modeling students' deductive reasoning in physics

NASA Astrophysics Data System (ADS)

Gaffney, Jonathan David Housley

Students often make errors when trying to solve qualitative or conceptual physics problems, and while many successful instructional interventions have been generated to prevent such errors, the process of deduction that students use when solving physics problems has not been thoroughly studied. In an effort to better understand that reasoning process, I have developed a new framework, which is based on the mental models framework in psychology championed by P. N. Johnson-Laird. My new framework models how students search possibility space when thinking about conceptual physics problems and suggests that errors arise from failing to flesh out all possibilities. It further suggests that instructional interventions should focus on making apparent those possibilities, as well as all physical consequences those possibilities would incur. The possibilities framework emerged from the analysis of data from a unique research project specifically invented for the purpose of understanding how students use deductive reasoning. In the selection task, participants were given a physics problem along with three written possible solutions with the goal of identifying which one of the three possible solutions was correct. Each participant was also asked to identify the errors in the incorrect solutions. For the study presented in this dissertation, participants not only performed the selection task individually on four problems, but they were also placed into groups of two or three and asked to discuss with each other the reasoning they used in making their choices and attempt to reach a consensus about which solution was correct. Finally, those groups were asked to work together to perform the selection task on three new problems. The possibilities framework appropriately models the reasoning that students use, and it makes useful predictions about potentially helpful instructional interventions. The study reported in this dissertation emphasizes the useful insight the possibilities framework provides. For example, this framework allows us to detect subtle differences in students' reasoning errors, even when those errors result in the same final answer. It also illuminates how simply mentioning overlooked quantities can instigate new lines of student reasoning. It allows us to better understand how well-known psychological biases, such as the belief bias, affect the reasoning process by preventing reasoners from fleshing out all of the possibilities. The possibilities framework also allows us to track student discussions about physics, revealing the need for all parties in communication to use the same set of possibilities in the conversations to facilitate successful understanding. The framework also suggests some of the influences that affect how reasoners choose between possible solutions to a given problem. This new framework for understanding how students reason when solving conceptual physics problems opens the door to a significant field of research. The framework itself needs to be further tested and developed, but it provides substantial suggestions for instructional interventions. If we hope to improve student reasoning in physics, the possibilities framework suggests that we are perhaps best served by teaching students how to fully flesh out the possibilities in every situation. This implies that we need to ensure students have a deep understanding of all of the implied possibilities afforded by the fundamental principles that are the cornerstones of the models we teach in physics classes.

Gambling and the Reasoned Action Model: Predicting Past Behavior, Intentions, and Future Behavior.

PubMed

Dahl, Ethan; Tagler, Michael J; Hohman, Zachary P

2018-03-01

Gambling is a serious concern for society because it is highly addictive and is associated with a myriad of negative outcomes. The current study applied the Reasoned Action Model (RAM) to understand and predict gambling intentions and behavior. Although prior studies have taken a reasoned action approach to understand gambling, no prior study has fully applied the RAM or used the RAM to predict future gambling. Across two studies the RAM was used to predict intentions to gamble, past gambling behavior, and future gambling behavior. In study 1 the model significantly predicted intentions and past behavior in both a college student and Amazon Mechanical Turk sample. In study 2 the model predicted future gambling behavior, measured 2 weeks after initial measurement of the RAM constructs. This study stands as the first to show the utility of the RAM in predicting future gambling behavior. Across both studies, attitudes and perceived normative pressure were the strongest predictors of intentions to gamble. These findings provide increased understanding of gambling and inform the development of gambling interventions based on the RAM.

(abstract) A Test of the Theoretical Models of Bipolar Outflows: The Bipolar Outflow in Mon R2

NASA Technical Reports Server (NTRS)

Xie, Taoling; Goldsmith, Paul; Patel, Nimesh

1993-01-01

We report some results of a study of the massive bipolar outflow in the central region of the relatively nearby giant molecular cloud Monoceros R2. We make a quantative comparison of our results with the Shu et al. outflow model which incorporates a radially directed wind sweeping up the ambient material into a shell. We find that this simple model naturally explains the shape of this thin shell. Although Shu's model in its simplest form predicts with reasonable parameters too much mass at very small polar angles, as previously pointed out by Masson and Chernin, it provides a reasonable good fit to the mass distribution at larger polar angles. It is possible that this discrepancy is due to inhomogeneities of the ambient molecular gas which is not considered by the model. We also discuss the constraints imposed by these results on recent jet-driven outflow models.

Coastal Surveillance Baseline Model Development

DTIC Science & Technology

2015-02-27

In the current STK model, a set of areas was defined for two reasons: To provide visual assistance during ship and aircraft route planning; and To...RF), electro-optic (EO), infrared (IR), and visual Partially Met The free version of STK can only generate simple generic sensors RQ-04 The model...25 APPENDIX A PLATFORM OBJECT ROUTE PLANNING PROCEDURE ............. A-1 APPENDIX B STK INSTALLATION

Causal role for inverse reasoning on obsessive-compulsive symptoms: Preliminary evidence from a cognitive bias modification for interpretation bias study.

PubMed

Wong, Shiu F; Grisham, Jessica R

2017-12-01

The inference-based approach (IBA) is a cognitive account of the genesis and maintenance of obsessive-compulsive disorder (OCD). According to the IBA, individuals with OCD are prone to using inverse reasoning, in which hypothetical causes form the basis of conclusions about reality. Several studies have provided preliminary support for an association between features of the IBA and OCD symptoms. However, there are currently no studies that have investigated the proposed causal relationship of inverse reasoning in OCD. In a non-clinical sample (N = 187), we used an interpretive cognitive bias procedure to train a bias towards using inverse reasoning (n = 64), healthy sensory-based reasoning (n = 65), or a control condition (n = 58). Participants were randomly allocated to these training conditions. This manipulation allowed us to assess whether, consistent with the IBA, inverse reasoning training increased compulsive-like behaviours and self-reported OCD symptoms. Results indicated that compared to a control condition, participants trained in inverse reasoning reported more OCD symptoms and were more avoidant of potentially contaminated objects. Moreover, change in inverse reasoning bias was a small but significant mediator of the relationship between training condition and behavioural avoidance. Conversely, training in a healthy (non-inverse) reasoning style did not have any effect on symptoms or behaviour relative to the control condition. As this study was conducted in a non-clinical sample, we were unable to generalise our findings to a clinical population. Findings generally support the IBA model by providing preliminary evidence of a causal role for inverse reasoning in OCD. Copyright © 2017 Elsevier Ltd. All rights reserved.

Low-order nonlinear dynamic model of IC engine-variable pitch propeller system for general aviation aircraft

NASA Technical Reports Server (NTRS)

Richard, Jacques C.

1995-01-01

This paper presents a dynamic model of an internal combustion engine coupled to a variable pitch propeller. The low-order, nonlinear time-dependent model is useful for simulating the propulsion system of general aviation single-engine light aircraft. This model is suitable for investigating engine diagnostics and monitoring and for control design and development. Furthermore, the model may be extended to provide a tool for the study of engine emissions, fuel economy, component effects, alternative fuels, alternative engine cycles, flight simulators, sensors, and actuators. Results show that the model provides a reasonable representation of the propulsion system dynamics from zero to 10 Hertz.

Students' Good Reasons.

ERIC Educational Resources Information Center

Alro, Helle; Skovsmose, Ole

1996-01-01

Provides examples and a discussion of the Inquiry Cooperation Model (ICM). The ICM is a way of describing a pattern of communicative cooperation between teacher and students. It tries to develop students' preconceptions into mathematical competence. Contains 15 references. (DDR)

Option Generation Techniques for Command and Control.

DTIC Science & Technology

1983-01-01

and discuss some reasons why decision making is often less than perfect. 3.2. The Process of Decision Making Figure 3.1 shows a model of the various...responses to changes in the problem context. Most of these potential reasons for poor decision making stem from the human decision maker’s cognitive...several advantages: (1) It provides a mechanism for quickly estimating the scope of the effort that should be involved in making the decison and a road map

Information Management for Unmanned Systems: Combining DL-Reasoning with Publish/Subscribe

NASA Astrophysics Data System (ADS)

Moser, Herwig; Reichelt, Toni; Oswald, Norbert; Förster, Stefan

Sharing capabilities and information between collaborating entities by using modem information- and communication-technology is a core principle in complex distributed civil or military mission scenarios. Previous work proved the suitability of Service-oriented Architectures for modelling and sharing the participating entities' capabilities. Albeit providing a satisfactory model for capabilities sharing, pure service-orientation curtails expressiveness for information exchange as opposed to dedicated data-centric communication principles. In this paper we introduce an Information Management System which combines OWL-Ontologies and automated reasoning with Publish/Subscribe-Systems, providing for a shared but decoupled data model. While confirming existing related research results, we emphasise the novel application and lack of practical experience of using Semantic Web technologies in areas other than originally intended. That is, aiding decision support and software design in the context of a mission scenario for an unmanned system. Experiments within a complex simulation environment show the immediate benefits of a semantic information-management and -dissemination platform: Clear separation of concerns in code and data model, increased service re-usability and extensibility as well as regulation of data flow and respective system behaviour through declarative rules.

The Balance-Scale Task Revisited: A Comparison of Statistical Models for Rule-Based and Information-Integration Theories of Proportional Reasoning

PubMed Central

Hofman, Abe D.; Visser, Ingmar; Jansen, Brenda R. J.; van der Maas, Han L. J.

2015-01-01

We propose and test three statistical models for the analysis of children’s responses to the balance scale task, a seminal task to study proportional reasoning. We use a latent class modelling approach to formulate a rule-based latent class model (RB LCM) following from a rule-based perspective on proportional reasoning and a new statistical model, the Weighted Sum Model, following from an information-integration approach. Moreover, a hybrid LCM using item covariates is proposed, combining aspects of both a rule-based and information-integration perspective. These models are applied to two different datasets, a standard paper-and-pencil test dataset (N = 779), and a dataset collected within an online learning environment that included direct feedback, time-pressure, and a reward system (N = 808). For the paper-and-pencil dataset the RB LCM resulted in the best fit, whereas for the online dataset the hybrid LCM provided the best fit. The standard paper-and-pencil dataset yielded more evidence for distinct solution rules than the online data set in which quantitative item characteristics are more prominent in determining responses. These results shed new light on the discussion on sequential rule-based and information-integration perspectives of cognitive development. PMID:26505905

OWL reasoning framework over big biological knowledge network.

PubMed

Chen, Huajun; Chen, Xi; Gu, Peiqin; Wu, Zhaohui; Yu, Tong

2014-01-01

Recently, huge amounts of data are generated in the domain of biology. Embedded with domain knowledge from different disciplines, the isolated biological resources are implicitly connected. Thus it has shaped a big network of versatile biological knowledge. Faced with such massive, disparate, and interlinked biological data, providing an efficient way to model, integrate, and analyze the big biological network becomes a challenge. In this paper, we present a general OWL (web ontology language) reasoning framework to study the implicit relationships among biological entities. A comprehensive biological ontology across traditional Chinese medicine (TCM) and western medicine (WM) is used to create a conceptual model for the biological network. Then corresponding biological data is integrated into a biological knowledge network as the data model. Based on the conceptual model and data model, a scalable OWL reasoning method is utilized to infer the potential associations between biological entities from the biological network. In our experiment, we focus on the association discovery between TCM and WM. The derived associations are quite useful for biologists to promote the development of novel drugs and TCM modernization. The experimental results show that the system achieves high efficiency, accuracy, scalability, and effectivity.

OWL Reasoning Framework over Big Biological Knowledge Network

PubMed Central

Chen, Huajun; Chen, Xi; Gu, Peiqin; Wu, Zhaohui; Yu, Tong

2014-01-01

Recently, huge amounts of data are generated in the domain of biology. Embedded with domain knowledge from different disciplines, the isolated biological resources are implicitly connected. Thus it has shaped a big network of versatile biological knowledge. Faced with such massive, disparate, and interlinked biological data, providing an efficient way to model, integrate, and analyze the big biological network becomes a challenge. In this paper, we present a general OWL (web ontology language) reasoning framework to study the implicit relationships among biological entities. A comprehensive biological ontology across traditional Chinese medicine (TCM) and western medicine (WM) is used to create a conceptual model for the biological network. Then corresponding biological data is integrated into a biological knowledge network as the data model. Based on the conceptual model and data model, a scalable OWL reasoning method is utilized to infer the potential associations between biological entities from the biological network. In our experiment, we focus on the association discovery between TCM and WM. The derived associations are quite useful for biologists to promote the development of novel drugs and TCM modernization. The experimental results show that the system achieves high efficiency, accuracy, scalability, and effectivity. PMID:24877076

Eight reasons payer interoperability and data sharing are essential in ACOs. Interoperability standards could be a prerequisite to measuring care.

PubMed

Mookencherry, Shefali

2012-01-01

It makes strategic and business sense for payers and providers to collaborate on how to take substantial cost out of the healthcare delivery system. Acting independently, neither medical groups, hospitals nor health plans have the optimal mix of resources and incentives to significantly reduce costs. Payers have core assets such as marketing, claims data, claims processing, reimbursement systems and capital. It would be cost prohibitive for all but the largest providers to develop these capabilities in order to compete directly with insurers. Likewise, medical groups and hospitals are positioned to foster financial interdependence among providers and coordinate the continuum of patient illnesses and care settings. Payers and providers should commit to reasonable clinical and cost goals, and share resources to minimize expenses and financial risks. It is in the interest of payers to work closely with providers on risk-management strategies because insurers need synergy with ACOs to remain cost competitive. It is in the interest of ACOs to work collaboratively with payers early on to develop reasonable and effective performance benchmarks. Hence, it is essential to have payer interoperability and data sharing integrated in an ACO model.

Adolescents' reasons for tanning and appearance motives: a preliminary study.

PubMed

Prior, Suzanne M; Fenwick, Kimberley D; Peterson, Jasmine C

2014-01-01

We examined adolescents' reasons for tanning and how these relate to appearance evaluation and orientation. Two hundred and sixty-four Canadian adolescents (age range 15-19 years) in grades 10, 11, and 12 completed a survey that included scales measuring their reasons for tanning, appearance evaluation, and appearance orientation. It was found that girls and boys differed on four of nine subscales measuring reasons for tanning. Girls believed more strongly than boys that tanning improved their general appearance and that friends influenced their decision to tan. Girls also expressed less concern than boys that tanning caused immediate skin damage or premature aging. The pattern of correlations between the reasons for tanning and appearance orientation was similar for girls and boys. For both, appearance reasons for tanning and sociocultural influences on tanning were positively associated with appearance orientation. Suggestions for future research with adolescents and a proposal for a guiding model are provided. Copyright © 2013 Elsevier Ltd. All rights reserved.

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.

Out-of-Hospital Decision-Making and Factors Influencing the Regional Distribution of Injured Patients in a Trauma System

PubMed Central

Newgard, Craig D.; Nelson, Maria J.; Kampp, Michael; Saha, Somnath; Zive, Dana; Schmidt, Terri; Daya, Mohamud; Jui, Jonathan; Wittwer, Lynn; Warden, Craig; Sahni, Ritu; Stevens, Mark; Gorman, Kyle; Koenig, Karl; Gubler, Dean; Rosteck, Pontine; Lee, Jan; Hedges, Jerris R.

2011-01-01

Background The decision-making processes used for out-of-hospital trauma triage and hospital selection in regionalized trauma systems remain poorly understood. The objective of this study was to understand the process of field triage decision-making in an established trauma system. Methods We used a mixed methods approach, including EMS records to quantify triage decisions and reasons for hospital selection in a population-based, injury cohort (2006 - 2008), plus a focused ethnography to understand EMS cognitive reasoning in making triage decisions. The study included 10 EMS agencies providing service to a 4-county regional trauma system with 3 trauma centers and 13 non-trauma hospitals. For qualitative analyses, we conducted field observation and interviews with 35 EMS field providers and a round-table discussion with 40 EMS management personnel to generate an empirical model of out-of-hospital decision making in trauma triage. Results 64,190 injured patients were evaluated by EMS, of whom 56,444 (88.0%) were transported to acute care hospitals and 9,637 (17.1% of transports) were field trauma activations. For non-trauma activations, patient/family preference and proximity accounted for 78% of destination decisions. EMS provider judgment was cited in 36% of field trauma activations and was the sole criterion in 23% of trauma patients. The empirical model demonstrated that trauma triage is driven primarily by EMS provider “gut feeling” (judgment) and relies heavily on provider experience, mechanism of injury, and early visual cues at the scene. Conclusions Provider cognitive reasoning for field trauma triage is more heuristic than algorithmic and driven primarily by provider judgment, rather than specific triage criteria. PMID:21817971

Common world model for unmanned systems

NASA Astrophysics Data System (ADS)

Dean, Robert Michael S.

2013-05-01

The Robotic Collaborative Technology Alliance (RCTA) seeks to provide adaptive robot capabilities which move beyond traditional metric algorithms to include cognitive capabilities. Key to this effort is the Common World Model, which moves beyond the state-of-the-art by representing the world using metric, semantic, and symbolic information. It joins these layers of information to define objects in the world. These objects may be reasoned upon jointly using traditional geometric, symbolic cognitive algorithms and new computational nodes formed by the combination of these disciplines. The Common World Model must understand how these objects relate to each other. Our world model includes the concept of Self-Information about the robot. By encoding current capability, component status, task execution state, and histories we track information which enables the robot to reason and adapt its performance using Meta-Cognition and Machine Learning principles. The world model includes models of how aspects of the environment behave, which enable prediction of future world states. To manage complexity, we adopted a phased implementation approach to the world model. We discuss the design of "Phase 1" of this world model, and interfaces by tracing perception data through the system from the source to the meta-cognitive layers provided by ACT-R and SS-RICS. We close with lessons learned from implementation and how the design relates to Open Architecture.

Predictive Behavior of a Computational Foot/Ankle Model through Artificial Neural Networks.

PubMed

Chande, Ruchi D; Hargraves, Rosalyn Hobson; Ortiz-Robinson, Norma; Wayne, Jennifer S

2017-01-01

Computational models are useful tools to study the biomechanics of human joints. Their predictive performance is heavily dependent on bony anatomy and soft tissue properties. Imaging data provides anatomical requirements while approximate tissue properties are implemented from literature data, when available. We sought to improve the predictive capability of a computational foot/ankle model by optimizing its ligament stiffness inputs using feedforward and radial basis function neural networks. While the former demonstrated better performance than the latter per mean square error, both networks provided reasonable stiffness predictions for implementation into the computational model.

An experimental study of several wind tunnel wall configurations using two V/STOL model configurations. [low speed wind tunnels

NASA Technical Reports Server (NTRS)

Binion, T. W., Jr.

1975-01-01

Experiments were conducted in the low speed wind tunnel using two V/STOL models, a jet-flap and a jet-in-fuselage configuration, to search for a wind tunnel wall configuration to minimize wall interference on V/STOL models. Data were also obtained on the jet-flap model with a uniform slotted wall configuration to provide comparisons between theoretical and experimental wall interference. A test section configuration was found which provided some data in reasonable agreement with interference-free results over a wide range of momentum coefficients.

Psychosocial factors associated with young elementary school children's intentions to consume legumes: a test of the theory of reasoned action.

PubMed

Folta, Sara C; Bell, Rick; Economos, Christina; Landers, Stewart; Goldberg, Jeanne P

2006-01-01

The purpose of this study was to test the utility of the Theory of Reasoned Action (TRA) in explaining young elementary school children's intention to consume legumes. A survey was conducted with children in an urban, multicultural community in Massachusetts. A total of 336 children participated. Logistic regression analysis was used to assess the strength of the relationship between attitude and subjective norm and intention. Although attitude was significantly associated with intention, the pseudo-R2 for the regression model that included only the TRA constructs was extremely low (.01). Adding demographic factors and preference improved the model's predictive ability, but attitude was no longer significant. The results of this study do not provide support for the predictive utility of the TRA with young elementary school children for this behavior, when demographic factors are accounted for. Hedonic factors, rather than reasoned judgments, may help drive children's intentions.

Linear estimation of coherent structures in wall-bounded turbulence at Re τ = 2000

NASA Astrophysics Data System (ADS)

Oehler, S.; Garcia–Gutiérrez, A.; Illingworth, S.

2018-04-01

The estimation problem for a fully-developed turbulent channel flow at Re τ = 2000 is considered. Specifically, a Kalman filter is designed using a Navier–Stokes-based linear model. The estimator uses time-resolved velocity measurements at a single wall-normal location (provided by DNS) to estimate the time-resolved velocity field at other wall-normal locations. The estimator is able to reproduce the largest scales with reasonable accuracy for a range of wavenumber pairs, measurement locations and estimation locations. Importantly, the linear model is also able to predict with reasonable accuracy the performance that will be achieved by the estimator when applied to the DNS. A more practical estimation scheme using the shear stress at the wall as measurement is also considered. The estimator is still able to estimate the largest scales with reasonable accuracy, although the estimator’s performance is reduced.

Deep-reasoning fault diagnosis - An aid and a model

NASA Technical Reports Server (NTRS)

Yoon, Wan Chul; Hammer, John M.

1988-01-01

The design and evaluation are presented for the knowledge-based assistance of a human operator who must diagnose a novel fault in a dynamic, physical system. A computer aid based on a qualitative model of the system was built to help the operators overcome some of their cognitive limitations. This aid differs from most expert systems in that it operates at several levels of interaction that are believed to be more suitable for deep reasoning. Four aiding approaches, each of which provided unique information to the operator, were evaluated. The aiding features were designed to help the human's casual reasoning about the system in predicting normal system behavior (N aiding), integrating observations into actual system behavior (O aiding), finding discrepancies between the two (O-N aiding), or finding discrepancies between observed behavior and hypothetical behavior (O-HN aiding). Human diagnostic performance was found to improve by almost a factor of two with O aiding and O-N aiding.

Detonation models of fast combustion waves in nanoscale Al-MoO3 bulk powder media

NASA Astrophysics Data System (ADS)

Shaw, Benjamin D.; Pantoya, Michelle L.; Dikici, Birce

2013-02-01

The combustion of nanometric aluminum (Al) powder with an oxidiser such as molybdenum trioxide (MoO3) is studied analytically. This study focuses on detonation wave models and a Chapman-Jouget detonation model provides reasonable agreement with experimentally-observed wave speeds provided that multiphase equilibrium sound speeds are applied at the downstream edge of the detonation wave. The results indicate that equilibrium sound speeds of multiphase mixtures can play a critical role in determining speeds of fast combustion waves in nanoscale Al-MoO3 powder mixtures.

DRS: Derivational Reasoning System

NASA Technical Reports Server (NTRS)

Bose, Bhaskar

1995-01-01

The high reliability requirements for airborne systems requires fault-tolerant architectures to address failures in the presence of physical faults, and the elimination of design flaws during the specification and validation phase of the design cycle. Although much progress has been made in developing methods to address physical faults, design flaws remain a serious problem. Formal methods provides a mathematical basis for removing design flaws from digital systems. DRS (Derivational Reasoning System) is a formal design tool based on advanced research in mathematical modeling and formal synthesis. The system implements a basic design algebra for synthesizing digital circuit descriptions from high level functional specifications. DRS incorporates an executable specification language, a set of correctness preserving transformations, verification interface, and a logic synthesis interface, making it a powerful tool for realizing hardware from abstract specifications. DRS integrates recent advances in transformational reasoning, automated theorem proving and high-level CAD synthesis systems in order to provide enhanced reliability in designs with reduced time and cost.

Mathematical interpretation of Brownian motor model: Limit cycles and directed transport phenomena

NASA Astrophysics Data System (ADS)

Yang, Jianqiang; Ma, Hong; Zhong, Suchuang

2018-03-01

In this article, we first suggest that the attractor of Brownian motor model is one of the reasons for the directed transport phenomenon of Brownian particle. We take the classical Smoluchowski-Feynman (SF) ratchet model as an example to investigate the relationship between limit cycles and directed transport phenomenon of the Brownian particle. We study the existence and variation rule of limit cycles of SF ratchet model at changing parameters through mathematical methods. The influences of these parameters on the directed transport phenomenon of a Brownian particle are then analyzed through numerical simulations. Reasonable mathematical explanations for the directed transport phenomenon of Brownian particle in SF ratchet model are also formulated on the basis of the existence and variation rule of the limit cycles and numerical simulations. These mathematical explanations provide a theoretical basis for applying these theories in physics, biology, chemistry, and engineering.

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

Diagnostic reasoning: where we've been, where we're going.

PubMed

Monteiro, Sandra M; Norman, Geoffrey

2013-01-01

Recently, clinical diagnostic reasoning has been characterized by "dual processing" models, which postulate a fast, unconscious (System 1) component and a slow, logical, analytical (System 2) component. However, there are a number of variants of this basic model, which may lead to conflicting claims. This paper critically reviews current theories and evidence about the nature of clinical diagnostic reasoning. We begin by briefly discussing the history of research in clinical reasoning. We then focus more specifically on the evidence to support dual-processing models. We conclude by identifying knowledge gaps about clinical reasoning and provide suggestions for future research. In contrast to work on analytical and nonanalytical knowledge as a basis for reasoning, these theories focus on the thinking process, not the nature of the knowledge retrieved. Ironically, this appears to be a revival of an outdated concept. Rather than defining diagnostic performance by problem-solving skills, it is now being defined by processing strategy. The version of dual processing that has received most attention in the literature in medical diagnosis might be labeled a "default/interventionist" model,(17) which suggests that a default system of cognitive processes (System 1) is responsible for cognitive biases that lead to diagnostic errors and that System 2 intervenes to correct these errors. Consequently, from this model, the best strategy for reducing errors is to make students aware of the biases and to encourage them to rely more on System 2. However, an accumulation of evidence suggests that (a) strategies directed at increasing analytical (System 2) processing, by slowing down, reducing distractions, paying conscious attention, and (b) strategies directed at making students aware of the effect of cognitive biases, have no impact on error rates. Conversely, strategies based on increasing application of relevant knowledge appear to have some success and are consistent with basic research on concept formation.

What variables can influence clinical reasoning?

PubMed Central

Ashoorion, Vahid; Liaghatdar, Mohammad Javad; Adibi, Peyman

2012-01-01

Background: Clinical reasoning is one of the most important competencies that a physician should achieve. Many medical schools and licensing bodies try to predict it based on some general measures such as critical thinking, personality, and emotional intelligence. This study aimed at providing a model to design the relationship between the constructs. Materials and Methods: Sixty-nine medical students participated in this study. A battery test devised that consist four parts: Clinical reasoning measures, personality NEO inventory, Bar-On EQ inventory, and California critical thinking questionnaire. All participants completed the tests. Correlation and multiple regression analysis consumed for data analysis. Results: There is low to moderate correlations between clinical reasoning and other variables. Emotional intelligence is the only variable that contributes clinical reasoning construct (r=0.17-0.34) (R2 chnage = 0.46, P Value = 0.000). Conclusion: Although, clinical reasoning can be considered as a kind of thinking, no significant correlation detected between it and other constructs. Emotional intelligence (and its subscales) is the only variable that can be used for clinical reasoning prediction. PMID:23853636

The neural basis of conditional reasoning with arbitrary content.

PubMed

Noveck, Ira A; Goel, Vinod; Smith, Kathleen W

2004-01-01

Behavioral predictions about reasoning have usually contrasted two accounts, Mental Logic and Mental Models. Neuroimaging techniques have been providing new measures that transcend this debate. We tested a hypothesis from Goel and Dolan (2003) that predicts neural activity predominantly in a left parietal-frontal system when participants reason with arbitrary (non-meaningful) materials. In an event-related fMRI investigation, we employed propositional syllogisms, the majority of which involved conditional reasoning. While investigating conditional reasoning generally, we ultimately focused on the neural activity linked to the two valid conditional forms--Modus Ponens (If p then q; p//q) and Modus Tollens (If p then q; not-q//not-p). Consistent with Goel and Dolan (2003), we found a left lateralized parietal frontal network for both inference forms with increasing activation when reasoning becomes more challenging by way of Modus Tollens. These findings show that the previous findings with more complex Aristotlean syllogisms are robust and cast doubt upon accounts of reasoning that accord primary inferential processes uniquely to either the right hemisphere or to language areas.

Evolution as represented through argumentation: A qualitative study on reasoning and argumentation in high school biology teaching practices

NASA Astrophysics Data System (ADS)

Yalcinoglu, Pelin

This study aimed to explore high school biology teachers' epistemological criteria and their attention to reasoning and argumentation within their instructional practices. This study investigated: (1) what epistemological criteria do high school biology teachers use when justifying the validity of conclusions, (2) what is the frequency of the explicit use of reasoning and argumentation, if any, in high school biology teachers' instructional practices, and to what extend are reasoning and argumentation skills reflected, if at all, in high school biology teachers' modes of assessment. Three different data collection methods were employed in this study; face-to-face interviews, classroom observations, and document collections. Teachers' epistemological criteria were investigated to provide insight about their reasoning structures. This investigation was made possible by having teachers provide an argument about the validity of hypothetical conclusions drawn by the students based on two different scenarios related to evolution. Toulmin's Argument Pattern used to create rubric to analyze high school biology teachers' levels of reasoning through argumentation. Results of the data analysis suggested following findings. First, high school biology teachers participated in this study presented variety of epistemological criteria which were presented as high, moderate and low levels of reasoning through the argumentations. Second, elements of Toulmin's Argument Pattern were visible in the participants teaching practices, however students were not explicitly introduced to a well structured argument in those classrooms. High level of reasoning was not evident in the instructional practices of the observed teachers. High school biology classrooms which were observed in this study do not provide opportunities for students to practice high level of reasoning or improve their argumentation skills. Third, Interview Protocols designed for this study were found useful to identify the epistemological criteria and level of reasoning individuals presented through argumentation. Toulmin's Argument Pattern provides a practical method to analyze the structure of arguments. Results of this study suggest the following implications for improving science education. These implications might be helpful in increasing teacher awareness of the importance of explicit teaching of reasoning and argumentation in science classrooms. Toulmin's Argument Model should be introduced to teachers through teacher education or professional development programs to increase the use of reasoning and argumentation skills in instructional practices. Toulmin's Argument Pattern may be used to design lessons or unit plans which present science as argumentation. Therefore, by engaging students in argumentation, teachers may help students to improve their content knowledge along with reasoning and argumentation skills in science classrooms. The results of this study suggest that use of Toulmin's Argument Pattern to evaluate high school biology teachers' presented levels of reasoning is a promising approach to understanding the structure of reasoning and argumentation that biology teachers use when providing judgments about the validity of hypothetical conclusions. The interview protocols and the rubrics used in this study should be tested in different subject areas in order to enhance and validate the use of Toulmin's Argument Pattern in measuring individuals' epistemological criteria and level of reasoning.

Toward an Aristotelian Model of Teacher Reasoning.

ERIC Educational Resources Information Center

Orton, Robert E.

1997-01-01

Utilizes Aristotle's three-way distinctions between theory, practice, and production to describe a balanced model of teacher reasoning. Reviews differing models of teacher reasoning that emphasize the role of contemplation and subject-matter representations. Uses the Aristotelian model to point toward a normative vision of teacher reasoning. (MJP)

Beyond the hype: a taxonomy of e-health business models.

PubMed

Parente, S T

2000-01-01

This paper describes a business model of e-commerce, its application to health care, and the reasons why the health policy community should monitor its development. The business model identifies the market barriers health e-commerce firms must overcome and provides perspective on opportunities for building a health care data infrastructure that is capable of delivering both a private and a public good.

Visualization of decision processes using a cognitive architecture

NASA Astrophysics Data System (ADS)

Livingston, Mark A.; Murugesan, Arthi; Brock, Derek; Frost, Wende K.; Perzanowski, Dennis

2013-01-01

Cognitive architectures are computational theories of reasoning the human mind engages in as it processes facts and experiences. A cognitive architecture uses declarative and procedural knowledge to represent mental constructs that are involved in decision making. Employing a model of behavioral and perceptual constraints derived from a set of one or more scenarios, the architecture reasons about the most likely consequence(s) of a sequence of events. Reasoning of any complexity and depth involving computational processes, however, is often opaque and challenging to comprehend. Arguably, for decision makers who may need to evaluate or question the results of autonomous reasoning, it would be useful to be able to inspect the steps involved in an interactive, graphical format. When a chain of evidence and constraint-based decision points can be visualized, it becomes easier to explore both how and why a scenario of interest will likely unfold in a particular way. In initial work on a scheme for visualizing cognitively-based decision processes, we focus on generating graphical representations of models run in the Polyscheme cognitive architecture. Our visualization algorithm operates on a modified version of Polyscheme's output, which is accomplished by augmenting models with a simple set of tags. We provide example visualizations and discuss properties of our technique that pose challenges for our representation goals. We conclude with a summary of feedback solicited from domain experts and practitioners in the field of cognitive modeling.

Using functional neuroimaging combined with a think-aloud protocol to explore clinical reasoning expertise in internal medicine.

PubMed

Durning, Steven J; Graner, John; Artino, Anthony R; Pangaro, Louis N; Beckman, Thomas; Holmboe, Eric; Oakes, Terrance; Roy, Michael; Riedy, Gerard; Capaldi, Vincent; Walter, Robert; van der Vleuten, Cees; Schuwirth, Lambert

2012-09-01

Clinical reasoning is essential to medical practice, but because it entails internal mental processes, it is difficult to assess. Functional magnetic resonance imaging (fMRI) and think-aloud protocols may improve understanding of clinical reasoning as these methods can more directly assess these processes. The objective of our study was to use a combination of fMRI and think-aloud procedures to examine fMRI correlates of a leading theoretical model in clinical reasoning based on experimental findings to date: analytic (i.e., actively comparing and contrasting diagnostic entities) and nonanalytic (i.e., pattern recognition) reasoning. We hypothesized that there would be functional neuroimaging differences between analytic and nonanalytic reasoning theory. 17 board-certified experts in internal medicine answered and reflected on validated U.S. Medical Licensing Exam and American Board of Internal Medicine multiple-choice questions (easy and difficult) during an fMRI scan. This procedure was followed by completion of a formal think-aloud procedure. fMRI findings provide some support for the presence of analytic and nonanalytic reasoning systems. Statistically significant activation of prefrontal cortex distinguished answering incorrectly versus correctly (p < 0.01), whereas activation of precuneus and midtemporal gyrus distinguished not guessing from guessing (p < 0.01). We found limited fMRI evidence to support analytic and nonanalytic reasoning theory, as our results indicate functional differences with correct vs. incorrect answers and guessing vs. not guessing. However, our findings did not suggest one consistent fMRI activation pattern of internal medicine expertise. This model of employing fMRI correlates offers opportunities to enhance our understanding of theory, as well as improve our teaching and assessment of clinical reasoning, a key outcome of medical education.

Computational models for the nonlinear analysis of reinforced concrete plates

NASA Technical Reports Server (NTRS)

Hinton, E.; Rahman, H. H. A.; Huq, M. M.

1980-01-01

A finite element computational model for the nonlinear analysis of reinforced concrete solid, stiffened and cellular plates is briefly outlined. Typically, Mindlin elements are used to model the plates whereas eccentric Timoshenko elements are adopted to represent the beams. The layering technique, common in the analysis of reinforced concrete flexural systems, is incorporated in the model. The proposed model provides an inexpensive and reasonably accurate approach which can be extended for use with voided plates.

A Coral Reef as an Analogical Model to Promote Collaborative Learning on Cultural & Ethnic Diversity in Science

ERIC Educational Resources Information Center

Yost, Robert W.; Gonzalez, Edward L. F.

2008-01-01

Analogical reasoning is integral to everyday living. The diversity associated with a coral reef provides a familiar model for initiating discussions focusing on cultural diversity and gender of past and present scientists with non-western science endeavors. These concepts are strengthened through the use of scientific biographical and historical…

Implications of Australian Distance Education Models for Rehabilitation Education [and] Comments on O'Brien et al.

ERIC Educational Resources Information Center

O'Brien, Gerald V.; And Others

1995-01-01

O'Brien and Schiro-Geist report on Australian university models for distance education, especially in rehabilitation. They note reasons that rehabilitation is not more involved in distance education and suggest that institutional bias prevents distance methods from being more widely used in the United States. Thomsen and Wong provide reactions to…

The Ranking of Global Environmental Issues and Problems by Polish Secondary Students and Teachers.

ERIC Educational Resources Information Center

Robinson, Michael; Trojok, Tomasz; Norwisz, Jan

1997-01-01

Identifies and discusses Polish student and teacher priorities of Bybee's 12 environmental problems in two cities in Katowice Province. Provides pertinent background on the Polish educational system. Presents reasons why the current science teaching model must be changed if the science curriculum is to provide more understanding of Bybee's 12…

Models of Technology Management at the Community College: The Role of the Chief Information Officer

ERIC Educational Resources Information Center

Armstrong, Scott; Simer, Lauren; Spaniol, Lee

2011-01-01

Community colleges provide a wide range of educational services to very diverse groups of students. For that reason, the variety and flexibility of services provided can be critical. In addition, quickly changing needs result in quickly changing system requirements. In this chapter, community college CIOs speak to their roles, focusing on the…

Trusted computation through biologically inspired processes

NASA Astrophysics Data System (ADS)

Anderson, Gustave W.

2013-05-01

Due to supply chain threats it is no longer a reasonable assumption that traditional protections alone will provide sufficient security for enterprise systems. The proposed cognitive trust model architecture extends the state-of-the-art in enterprise anti-exploitation technologies by providing collective immunity through backup and cross-checking, proactive health monitoring and adaptive/autonomic threat response, and network resource diversity.

Probabilistic Reasoning and Prediction with Young Children

ERIC Educational Resources Information Center

Kinnear, Virginia; Clark, Julie

2014-01-01

This paper reports findings from a classroom based study with 5 year old children in their first term of school. A data modelling activity contextualised by a picture story book was used to present a prediction problem. A data table with numerical data values provided for three consecutive days of rubbish collection was provided, with a fourth day…

Quantifying Uncertainty in Near Surface Electromagnetic Imaging Using Bayesian Methods

NASA Astrophysics Data System (ADS)

Blatter, D. B.; Ray, A.; Key, K.

2017-12-01

Geoscientists commonly use electromagnetic methods to image the Earth's near surface. Field measurements of EM fields are made (often with the aid an artificial EM source) and then used to infer near surface electrical conductivity via a process known as inversion. In geophysics, the standard inversion tool kit is robust and can provide an estimate of the Earth's near surface conductivity that is both geologically reasonable and compatible with the measured field data. However, standard inverse methods struggle to provide a sense of the uncertainty in the estimate they provide. This is because the task of finding an Earth model that explains the data to within measurement error is non-unique - that is, there are many, many such models; but the standard methods provide only one "answer." An alternative method, known as Bayesian inversion, seeks to explore the full range of Earth model parameters that can adequately explain the measured data, rather than attempting to find a single, "ideal" model. Bayesian inverse methods can therefore provide a quantitative assessment of the uncertainty inherent in trying to infer near surface conductivity from noisy, measured field data. This study applies a Bayesian inverse method (called trans-dimensional Markov chain Monte Carlo) to transient airborne EM data previously collected over Taylor Valley - one of the McMurdo Dry Valleys in Antarctica. Our results confirm the reasonableness of previous estimates (made using standard methods) of near surface conductivity beneath Taylor Valley. In addition, we demonstrate quantitatively the uncertainty associated with those estimates. We demonstrate that Bayesian inverse methods can provide quantitative uncertainty to estimates of near surface conductivity.

Leaky Landfills.

ERIC Educational Resources Information Center

Jones, Linda L. Cronin

1992-01-01

Provides background information on landfills and describes an activity where students learn how a modern landfill is constructed and develop an understanding of the reasons for several regulations regarding modern landfill construction. Students design and construct working models of three types of landfills. (PR)

Model parameters for representative wetland plant functional groups

USDA-ARS?s Scientific Manuscript database

Wetlands provide a wide variety of ecosystem services including water quality remediation, biodiversity refugia, groundwater recharge, and floodwater storage. Realistic estimation of ecosystem service benefits associated with wetlands requires reasonable simulation of the hydrology of each site and...

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.

A One-System Theory Which is Not Propositional.

PubMed

Witnauer, James E; Urcelay, Gonzalo P; Miller, Ralph R

2009-04-01

We argue that the propositional and link-based approaches to human contingency learning represent different levels of analysis because propositional reasoning requires a basis, which is plausibly provided by a link-based architecture. Moreover, in their attempt to compare two general classes of models (link-based and propositional), Mitchell et al. have referred to only two generic models and ignore the large variety of different models within each class.

Stochastic dynamics of cholera epidemics

NASA Astrophysics Data System (ADS)

Azaele, Sandro; Maritan, Amos; Bertuzzo, Enrico; Rodriguez-Iturbe, Ignacio; Rinaldo, Andrea

2010-05-01

We describe the predictions of an analytically tractable stochastic model for cholera epidemics following a single initial outbreak. The exact model relies on a set of assumptions that may restrict the generality of the approach and yet provides a realm of powerful tools and results. Without resorting to the depletion of susceptible individuals, as usually assumed in deterministic susceptible-infected-recovered models, we show that a simple stochastic equation for the number of ill individuals provides a mechanism for the decay of the epidemics occurring on the typical time scale of seasonality. The model is shown to provide a reasonably accurate description of the empirical data of the 2000/2001 cholera epidemic which took place in the Kwa Zulu-Natal Province, South Africa, with possibly notable epidemiological implications.

The Coastal Zone: Man and Nature. An Application of the Socio-Scientific Reasoning Model.

ERIC Educational Resources Information Center

Maul, June Paradise; And Others

The curriculum model described here has been designed by incorporating the socio-scientific reasoning model with a simulation design in an attempt to have students investigate the onshore impacts of Outer Continental Shelf (OCS) gas and oil development. The socio-scientific reasoning model incorporates a logical/physical reasoning component as…

Can Earth System Model Provide Reasonable Natural Runoff Estimates to Support Water Management Studies?

NASA Astrophysics Data System (ADS)

Kao, S. C.; Shi, X.; Kumar, J.; Ricciuto, D. M.; Mao, J.; Thornton, P. E.

2017-12-01

With the concern of changing hydrologic regime, there is a crucial need to better understand how water availability may change and influence water management decisions in the projected future climate conditions. Despite that surface hydrology has long been simulated by land model within the Earth System modeling (ESM) framework, given the coarser horizontal resolution and lack of engineering-level calibration, raw runoff from ESM is generally discarded by water resource managers when conducting hydro-climate impact assessments. To identify a likely path to improve the credibility of ESM-simulated natural runoff, we conducted regional model simulation using the land component (ALM) of the Accelerated Climate Modeling for Energy (ACME) version 1 focusing on the conterminous United States (CONUS). Two very different forcing data sets, including (1) the conventional 0.5° CRUNCEP (v5, 1901-2013) and (2) the 1-km Daymet (v3, 1980-2013) aggregated to 0.5°, were used to conduct 20th century transient simulation with satellite phenology. Additional meteorologic and hydrologic observations, including PRISM precipitation and U.S. Geological Survey WaterWatch runoff, were used for model evaluation. For various CONUS hydrologic regions (such as Pacific Northwest), we found that Daymet can significantly improve the reasonableness of simulated ALM runoff even without intensive calibration. The large dry bias of CRUNCEP precipitation (evaluated by PRISM) in multiple CONUS hydrologic regions is believed to be the main reason causing runoff underestimation. The results suggest that when driving with skillful precipitation estimates, ESM has the ability to produce reasonable natural runoff estimates to support further water management studies. Nevertheless, model calibration will be required for regions (such as Upper Colorado) where ill performance is showed for multiple different forcings.

Clinical cognition and diagnostic error: applications of a dual process model of reasoning.

PubMed

Croskerry, Pat

2009-09-01

Both systemic and individual factors contribute to missed or delayed diagnoses. Among the multiple factors that impact clinical performance of the individual, the caliber of cognition is perhaps the most relevant and deserves our attention and understanding. In the last few decades, cognitive psychologists have gained substantial insights into the processes that underlie cognition, and a new, universal model of reasoning and decision making has emerged, Dual Process Theory. The theory has immediate application to medical decision making and provides an overall schema for understanding the variety of theoretical approaches that have been taken in the past. The model has important practical applications for decision making across the multiple domains of healthcare, and may be used as a template for teaching decision theory, as well as a platform for future research. Importantly, specific operating characteristics of the model explain how diagnostic failure occurs.

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.

Validation of pavement performance curves for the mechanistic-empirical pavement design guide.

DOT National Transportation Integrated Search

2009-02-01

The objective of this research is to determine whether the nationally calibrated performance models used in the Mechanistic-Empirical : Pavement Design Guide (MEPDG) provide a reasonable prediction of actual field performance, and if the desired accu...

SPARC GENERATED CHEMICAL PROPERTIES DATABASE FOR USE IN NATIONAL RISK ASSESSMENTS

EPA Science Inventory

The SPARC (Sparc Performs Automated Reasoning in Chemistry) Model was used to provide temperature dependent algorithms used to estimate chemical properties for approximately 200 chemicals of interest to the promulgation of the Hazardous Waste Identification Rule (HWIR) . Proper...

Software Dependability Assessment Methods.

DTIC Science & Technology

1986-11-01

Maor.rldx TABLE ~~~~~~ ~ ~ .2.RVU OFWR ETBI1YMDL Goei Crot~Nor~ Nu wu.. Ps.~o, r1.~~j% 2-4 __ N App L,-caW L Nct A pp.cLL tc ReAAW -Ur e ’-cdtl L. Reaons I...bug is found and immediately removed. The model provides a good fit with data. The parameter estimates are reasonable for the data sets tested. 3.0...where n = the number of errors found to date. 6.3 Study Results The model provides a good fit with data. The model runs into slight trouble with its "no

Preliminary description of the area navigation software for a microcomputer-based Loran-C receiver

NASA Technical Reports Server (NTRS)

Oguri, F.

1983-01-01

The development of new software implementation of this software on a microcomputer (MOS 6502) to provide high quality navigation information is described. This software development provides Area/Route Navigation (RNAV) information from Time Differences (TDs) in raw form using an elliptical Earth model and a spherical model. The software is prepared for the microcomputer based Loran-C receiver. To compute navigation infomation, a (MOS 6502) microcomputer and a mathematical chip (AM 9511A) were combined with the Loran-C receiver. Final data reveals that this software does indeed provide accurate information with reasonable execution times.

Employing Model-Based Reasoning in Interdisciplinary Research Teams: Evidence-Based Practices for Integrating Knowledge Across Systems

NASA Astrophysics Data System (ADS)

Pennington, D. D.; Vincent, S.

2017-12-01

The NSF-funded project "Employing Model-Based Reasoning in Socio-Environmental Synthesis (EMBeRS)" has developed a generic model for exchanging knowledge across disciplines that is based on findings from the cognitive, learning, social, and organizational sciences addressing teamwork in complex problem solving situations. Two ten-day summer workshops for PhD students from large, NSF-funded interdisciplinary projects working on a variety of water issues were conducted in 2016 and 2017, testing the model by collecting a variety of data, including surveys, interviews, audio/video recordings, material artifacts and documents, and photographs. This presentation will introduce the EMBeRS model, the design of workshop activities based on the model, and results from surveys and interviews with the participating students. Findings suggest that this approach is very effective for developing a shared, integrated research vision across disciplines, compared with activities typically provided by most large research projects, and that students believe the skills developed in the EMBeRS workshops are unique and highly desireable.

The Dynamic Atmospheres of Carbon Rich Giants: Constraining Models Via Interferometry

NASA Astrophysics Data System (ADS)

Rau, Gioia; Hron, Josef; Paladini, Claudia; Aringer, Bernard; Eriksson, Kjell; Marigo, Paola

2016-07-01

Dynamic models for the atmospheres of C-rich Asymptotic Giant Branch stars are quite advanced and have been overall successful in reproducing spectroscopic and photometric observations. Interferometry provides independent information and is thus an important technique to study the atmospheric stratification and to further constrain the dynamic models. We observed a sample of six C-rich AGBs with the mid infrared interferometer VLTI/MIDI. These observations, combined with photometric and spectroscopic data from the literature, are compared with synthetic observables derived from dynamic model atmospheres (DMA, Eriksson et al. 2014). The SEDs can be reasonably well modelled and the interferometry supports the extended and multi-component structure of the atmospheres, but some differences remain. We discuss the possible reasons for these differences and we compare the stellar parameters derived from this comparison with stellar evolution models. Finally, we point out the high potential of MATISSE, the second generation VLTI instrument allowing interferometric imaging in the L, M, and N bands, for further progress in this field.

Resting state morphology predicts the effect of theta burst stimulation in false belief reasoning.

PubMed

Hartwright, Charlotte E; Hardwick, Robert M; Apperly, Ian A; Hansen, Peter C

2016-10-01

When required to represent a perspective that conflicts with one's own, functional magnetic resonance imaging (fMRI) suggests that the right ventrolateral prefrontal cortex (rvlPFC) supports the inhibition of that conflicting self-perspective. The present task dissociated inhibition of self-perspective from other executive control processes by contrasting belief reasoning-a cognitive state where the presence of conflicting perspectives was manipulated-with a conative desire state wherein no systematic conflict existed. Linear modeling was used to examine the effect of continuous theta burst stimulation (cTBS) to rvlPFC on participants' reaction times in belief and desire reasoning. It was anticipated that cTBS applied to rvlPFC would affect belief but not desire reasoning, by modulating activity in the Ventral Attention System (VAS). We further anticipated that this effect would be mediated by functional connectivity within this network, which was identified using resting state fMRI and an unbiased model-free approach. Simple reaction-time analysis failed to detect an effect of cTBS. However, by additionally modeling individual measures from within the stimulated network, the hypothesized effect of cTBS to belief (but, importantly, not desire) reasoning was demonstrated. Structural morphology within the stimulated region, rvlPFC, and right temporoparietal junction were demonstrated to underlie this effect. These data provide evidence that inconsistencies found with cTBS can be mediated by the composition of the functional network that is being stimulated. We suggest that the common claim that this network constitutes the VAS explains the effect of cTBS to this network on false belief reasoning. Hum Brain Mapp 37:3502-3514, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

A Computational Comparison of High Strain Rate Strength and Failure Models for Glass

DTIC Science & Technology

2012-11-05

many researchers, however accuracy across a broad range of impact conditions is still not always achievable. Glasses , including soda - lime - silica ...plug/cone failure appearance when testing soda - lime - silica glass (see Fig. 5 from Ref. [7]). He notes that at 60 µs, the plug begins to break up and...material model. Although the JH-2 model has been adapated to provide reasonably accurate predictions for soda - lime glass , the Holmquist-Johnson model

Village power options

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

Lilienthal, P.

1997-12-01

This paper describes three different computer codes which have been written to model village power applications. The reasons which have driven the development of these codes include: the existance of limited field data; diverse applications can be modeled; models allow cost and performance comparisons; simulations generate insights into cost structures. The models which are discussed are: Hybrid2, a public code which provides detailed engineering simulations to analyze the performance of a particular configuration; HOMER - the hybrid optimization model for electric renewables - which provides economic screening for sensitivity analyses; and VIPOR the village power model - which is amore » network optimization model for comparing mini-grids to individual systems. Examples of the output of these codes are presented for specific applications.« less

A case study of the abductive reasoning processes of pre-service elementary education students in a role playing setting concerning a mock senate hearing on global climate change

NASA Astrophysics Data System (ADS)

Petty, Michael Eugene

Science education has a rich history of studies into the impact of analogical reasoning upon researcher and student alike. These have focused on how induction and deduction are utilized in determining the appropriateness of the analogy being scrutinized. Research in artificial intelligence has demonstrated that human cognition cannot be modeled with only inductive and deductive forms of logic. Charles S. Peirce proposed abduction as a form of logic central to the process of inquiry and discovery. This involves reasoning from observation to best explanation or hypothesis. Peirce's Theory of Signs provided the theoretical foundation and a model of abduction developed by Shank and Cunningham from Peirce's theory offered the conceptual basis for the study. This study uses discourse analysis to attempt to understand the abductive reasoning processes of two groups of students as they interpret new information concerning the political and scientific perspective of the Greening Earth Society and the Center for Disease Control in an authentic, undergraduate-level classroom setting. The five students were members of a capstone course in science education for pre-service elementary education majors who had an interest in science education. The entire class was comprised of fourteen students partitioned into five groups for the culminating exercise for the course. Analysis was carried out using journal entries, audiotapes of planning sessions, a brief summary of their understanding, and videotapes of the mock Senate hearings. The results demonstrated that different members of the group arrived at their understanding using different pathways suggested by the model. While some proceeded linearly, others skipped some stages and later came back to find supportive evidence to strengthen their beliefs. The model is useful in understanding their abductive processes and may provide insight into how we might consider the process in the design of future curriculum for elementary science education.

Collective behavior in animal groups: theoretical models and empirical studies

PubMed Central

Giardina, Irene

2008-01-01

Collective phenomena in animal groups have attracted much attention in the last years, becoming one of the hottest topics in ethology. There are various reasons for this. On the one hand, animal grouping provides a paradigmatic example of self-organization, where collective behavior emerges in absence of centralized control. The mechanism of group formation, where local rules for the individuals lead to a coherent global state, is very general and transcends the detailed nature of its components. In this respect, collective animal behavior is a subject of great interdisciplinary interest. On the other hand, there are several important issues related to the biological function of grouping and its evolutionary success. Research in this field boasts a number of theoretical models, but much less empirical results to compare with. For this reason, even if the general mechanisms through which self-organization is achieved are qualitatively well understood, a quantitative test of the models assumptions is still lacking. New analysis on large groups, which require sophisticated technological procedures, can provide the necessary empirical data. PMID:19404431

What Does It Mean to Be Pragmatic? Pragmatic Methods, Measures, and Models to Facilitate Research Translation

ERIC Educational Resources Information Center

Glasgow, Russell E.

2013-01-01

Background: One of the reasons for the slow and uncertain translation of research into practice is likely due to the emphasis in science on explanatory models and efficacy designs rather than more pragmatic approaches. Methods: Following a brief definition of what constitutes a pragmatic approach, I provide examples of pragmatic methods, measures,…

How Does an Activity Theory Model Help to Know Better about Teaching with Electronic-Exercise-Bases?

ERIC Educational Resources Information Center

Abboud-Blanchard, Maha; Cazes, Claire

2012-01-01

The research presented in this paper relies on Activity Theory and particularly on Engestrom's model, to better understand the use of Electronic-Exercise-Bases (EEB) by mathematics teachers. This theory provides a holistic approach to illustrate the complexity of the EEB integration. The results highlight reasons and ways of using EEB and show…

Calculating landscape surface area from digital elevation models

Treesearch

Jeff S. Jenness

2004-01-01

There are many reasons to want to know the true surface area of the landscape, especially in landscape analysis and studies of wildlife habitat. Surface area provides a better estimate of the land area available to an animal than planimetric area, and the ratio of this surface area to planimetric area provides a useful measure of topographic roughness of the landscape...

True Numerical Cognition in the Wild.

PubMed

Piantadosi, Steven T; Cantlon, Jessica F

2017-04-01

Cognitive and neural research over the past few decades has produced sophisticated models of the representations and algorithms underlying numerical reasoning in humans and other animals. These models make precise predictions for how humans and other animals should behave when faced with quantitative decisions, yet primarily have been tested only in laboratory tasks. We used data from wild baboons' troop movements recently reported by Strandburg-Peshkin, Farine, Couzin, and Crofoot (2015) to compare a variety of models of quantitative decision making. We found that the decisions made by these naturally behaving wild animals rely specifically on numerical representations that have key homologies with the psychophysics of human number representations. These findings provide important new data on the types of problems human numerical cognition was designed to solve and constitute the first robust evidence of true numerical reasoning in wild animals.

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.

The Co-Emergence of Aggregate and Modelling Reasoning

ERIC Educational Resources Information Center

Aridor, Keren; Ben-Zvi, Dani

2017-01-01

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

Proportional Reasoning of Preservice Elementary Education Majors: An Epistemic Model of the Proportional Reasoning Construct.

ERIC Educational Resources Information Center

Fleener, M. Jayne

Current research and learning theory suggest that a hierarchy of proportional reasoning exists that can be tested. Using G. Vergnaud's four complexity variables (structure, content, numerical characteristics, and presentation) and T. E. Kieren's model of rational number knowledge building, an epistemic model of proportional reasoning was…

SAFETY: an integrated clinical reasoning and reflection framework for undergraduate nursing students.

PubMed

Hicks Russell, Bedelia; Geist, Melissa J; House Maffett, Jenny

2013-01-01

Nurse educators can no longer focus on imparting to students knowledge that is merely factual and content specific. Activities that provide students with opportunities to apply concepts in real-world scenarios can be powerful tools. Nurse educators should take advantage of student-patient interactions to model clinical reasoning and allow students to practice complex decision making throughout the entire curriculum. In response to this change in nursing education, faculty in a pediatric course designed a reflective clinical reasoning activity based on the SAFETY template, which is derived from the National Council of State Boards of Nursing RN practice analysis. Students were able to prioritize key components of nursing care, as well as integrate practice issues such as delegation, Health Insurance Portability and Accountability Act violations, and questioning the accuracy of orders. SAFETY is proposed as a framework for integration of content knowledge, clinical reasoning, and reflection on authentic professional nursing concerns. Copyright 2012, SLACK Incorporated.

Expertise and category-based induction.

PubMed

Proffitt, J B; Coley, J D; Medin, D L

2000-07-01

The authors examined inductive reasoning among experts in a domain. Three types of tree experts (landscapers, taxonomists, and parks maintenance personnel) completed 3 reasoning tasks. In Experiment 1, participants inferred which of 2 novel diseases would affect "more other kinds of trees" and provided justifications for their choices. In Experiment 2, the authors used modified instructions and asked which disease would be more likely to affect "all trees." In Experiment 3, the conclusion category was eliminated altogether, and participants were asked to generate a list of other affected trees. Among these populations, typicality and diversity effects were weak to nonexistent. Instead, experts' reasoning was influenced by "local" coverage (extension of the property to members of the same folk family) and causal-ecological factors. The authors concluded that domain knowledge leads to the use of a variety of reasoning strategies not captured by current models of category-based induction.

Modelling Mathematical Reasoning in Physics Education

NASA Astrophysics Data System (ADS)

Uhden, Olaf; Karam, Ricardo; Pietrocola, Maurício; Pospiech, Gesche

2012-04-01

Many findings from research as well as reports from teachers describe students' problem solving strategies as manipulation of formulas by rote. The resulting dissatisfaction with quantitative physical textbook problems seems to influence the attitude towards the role of mathematics in physics education in general. Mathematics is often seen as a tool for calculation which hinders a conceptual understanding of physical principles. However, the role of mathematics cannot be reduced to this technical aspect. Hence, instead of putting mathematics away we delve into the nature of physical science to reveal the strong conceptual relationship between mathematics and physics. Moreover, we suggest that, for both prospective teaching and further research, a focus on deeply exploring such interdependency can significantly improve the understanding of physics. To provide a suitable basis, we develop a new model which can be used for analysing different levels of mathematical reasoning within physics. It is also a guideline for shifting the attention from technical to structural mathematical skills while teaching physics. We demonstrate its applicability for analysing physical-mathematical reasoning processes with an example.

Intelligent diagnosis of jaundice with dynamic uncertain causality graph model.

PubMed

Hao, Shao-Rui; Geng, Shi-Chao; Fan, Lin-Xiao; Chen, Jia-Jia; Zhang, Qin; Li, Lan-Juan

2017-05-01

Jaundice is a common and complex clinical symptom potentially occurring in hepatology, general surgery, pediatrics, infectious diseases, gynecology, and obstetrics, and it is fairly difficult to distinguish the cause of jaundice in clinical practice, especially for general practitioners in less developed regions. With collaboration between physicians and artificial intelligence engineers, a comprehensive knowledge base relevant to jaundice was created based on demographic information, symptoms, physical signs, laboratory tests, imaging diagnosis, medical histories, and risk factors. Then a diagnostic modeling and reasoning system using the dynamic uncertain causality graph was proposed. A modularized modeling scheme was presented to reduce the complexity of model construction, providing multiple perspectives and arbitrary granularity for disease causality representations. A "chaining" inference algorithm and weighted logic operation mechanism were employed to guarantee the exactness and efficiency of diagnostic reasoning under situations of incomplete and uncertain information. Moreover, the causal interactions among diseases and symptoms intuitively demonstrated the reasoning process in a graphical manner. Verification was performed using 203 randomly pooled clinical cases, and the accuracy was 99.01% and 84.73%, respectively, with or without laboratory tests in the model. The solutions were more explicable and convincing than common methods such as Bayesian Networks, further increasing the objectivity of clinical decision-making. The promising results indicated that our model could be potentially used in intelligent diagnosis and help decrease public health expenditure.

Intelligent diagnosis of jaundice with dynamic uncertain causality graph model*

PubMed Central

Hao, Shao-rui; Geng, Shi-chao; Fan, Lin-xiao; Chen, Jia-jia; Zhang, Qin; Li, Lan-juan

2017-01-01

Jaundice is a common and complex clinical symptom potentially occurring in hepatology, general surgery, pediatrics, infectious diseases, gynecology, and obstetrics, and it is fairly difficult to distinguish the cause of jaundice in clinical practice, especially for general practitioners in less developed regions. With collaboration between physicians and artificial intelligence engineers, a comprehensive knowledge base relevant to jaundice was created based on demographic information, symptoms, physical signs, laboratory tests, imaging diagnosis, medical histories, and risk factors. Then a diagnostic modeling and reasoning system using the dynamic uncertain causality graph was proposed. A modularized modeling scheme was presented to reduce the complexity of model construction, providing multiple perspectives and arbitrary granularity for disease causality representations. A “chaining” inference algorithm and weighted logic operation mechanism were employed to guarantee the exactness and efficiency of diagnostic reasoning under situations of incomplete and uncertain information. Moreover, the causal interactions among diseases and symptoms intuitively demonstrated the reasoning process in a graphical manner. Verification was performed using 203 randomly pooled clinical cases, and the accuracy was 99.01% and 84.73%, respectively, with or without laboratory tests in the model. The solutions were more explicable and convincing than common methods such as Bayesian Networks, further increasing the objectivity of clinical decision-making. The promising results indicated that our model could be potentially used in intelligent diagnosis and help decrease public health expenditure. PMID:28471111

Mental models: an alternative evaluation of a sensemaking approach to ethics instruction.

PubMed

Brock, Meagan E; Vert, Andrew; Kligyte, Vykinta; Waples, Ethan P; Sevier, Sydney T; Mumford, Michael D

2008-09-01

In spite of the wide variety of approaches to ethics training it is still debatable which approach has the highest potential to enhance professionals' integrity. The current effort assesses a novel curriculum that focuses on metacognitive reasoning strategies researchers use when making sense of day-to-day professional practices that have ethical implications. The evaluated trainings effectiveness was assessed by examining five key sensemaking processes, such as framing, emotion regulation, forecasting, self-reflection, and information integration that experts and novices apply in ethical decision-making. Mental models of trained and untrained graduate students, as well as faculty, working in the field of physical sciences were compared using a think-aloud protocol 6 months following the ethics training. Evaluation and comparison of the mental models of participants provided further validation evidence for sensemaking training. Specifically, it was found that trained students applied metacognitive reasoning strategies learned during training in their ethical decision-making that resulted in complex mental models focused on the objective assessment of the situation. Mental models of faculty and untrained students were externally-driven with a heavy focus on autobiographical processes. The study shows that sensemaking training has a potential to induce shifts in researchers' mental models by making them more cognitively complex via the use of metacognitive reasoning strategies. Furthermore, field experts may benefit from sensemaking training to improve their ethical decision-making framework in highly complex, novel, and ambiguous situations.

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

PubMed

Edwards, Ian; Richardson, Barbara

2008-01-01

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

Qualitative models for space system engineering

NASA Technical Reports Server (NTRS)

Forbus, Kenneth D.

1990-01-01

The objectives of this project were: (1) to investigate the implications of qualitative modeling techniques for problems arising in the monitoring, diagnosis, and design of Space Station subsystems and procedures; (2) to identify the issues involved in using qualitative models to enhance and automate engineering functions. These issues include representing operational criteria, fault models, alternate ontologies, and modeling continuous signals at a functional level of description; and (3) to develop a prototype collection of qualitative models for fluid and thermal systems commonly found in Space Station subsystems. Potential applications of qualitative modeling to space-systems engineering, including the notion of intelligent computer-aided engineering are summarized. Emphasis is given to determining which systems of the proposed Space Station provide the most leverage for study, given the current state of the art. Progress on using qualitative models, including development of the molecular collection ontology for reasoning about fluids, the interaction of qualitative and quantitative knowledge in analyzing thermodynamic cycles, and an experiment on building a natural language interface to qualitative reasoning is reported. Finally, some recommendations are made for future research.

A semantic-web oriented representation of the clinical element model for secondary use of electronic health records data.

PubMed

Tao, Cui; Jiang, Guoqian; Oniki, Thomas A; Freimuth, Robert R; Zhu, Qian; Sharma, Deepak; Pathak, Jyotishman; Huff, Stanley M; Chute, Christopher G

2013-05-01

The clinical element model (CEM) is an information model designed for representing clinical information in electronic health records (EHR) systems across organizations. The current representation of CEMs does not support formal semantic definitions and therefore it is not possible to perform reasoning and consistency checking on derived models. This paper introduces our efforts to represent the CEM specification using the Web Ontology Language (OWL). The CEM-OWL representation connects the CEM content with the Semantic Web environment, which provides authoring, reasoning, and querying tools. This work may also facilitate the harmonization of the CEMs with domain knowledge represented in terminology models as well as other clinical information models such as the openEHR archetype model. We have created the CEM-OWL meta ontology based on the CEM specification. A convertor has been implemented in Java to automatically translate detailed CEMs from XML to OWL. A panel evaluation has been conducted, and the results show that the OWL modeling can faithfully represent the CEM specification and represent patient data.

A semantic-web oriented representation of the clinical element model for secondary use of electronic health records data

PubMed Central

Tao, Cui; Jiang, Guoqian; Oniki, Thomas A; Freimuth, Robert R; Zhu, Qian; Sharma, Deepak; Pathak, Jyotishman; Huff, Stanley M; Chute, Christopher G

2013-01-01

The clinical element model (CEM) is an information model designed for representing clinical information in electronic health records (EHR) systems across organizations. The current representation of CEMs does not support formal semantic definitions and therefore it is not possible to perform reasoning and consistency checking on derived models. This paper introduces our efforts to represent the CEM specification using the Web Ontology Language (OWL). The CEM-OWL representation connects the CEM content with the Semantic Web environment, which provides authoring, reasoning, and querying tools. This work may also facilitate the harmonization of the CEMs with domain knowledge represented in terminology models as well as other clinical information models such as the openEHR archetype model. We have created the CEM-OWL meta ontology based on the CEM specification. A convertor has been implemented in Java to automatically translate detailed CEMs from XML to OWL. A panel evaluation has been conducted, and the results show that the OWL modeling can faithfully represent the CEM specification and represent patient data. PMID:23268487

State medical licensure for telemedicine and teleradiology.

PubMed

Hunter, Tim B; Weinstein, Ronald S; Krupinski, Elizabeth A

2015-04-01

Physician medical licensure is state based for historical and constitutional reasons. It may also provide the best method for guaranteeing patient protection from unqualified, incompetent, impaired, or unprofessional practitioners of medicine. However, a significant cost for physicians practicing telemedicine is having to obtain multiple state medical licenses. There is reasonable likelihood that model legislation for the practice of telemedicine across state boundaries will be passed in the next few years, providing physicians with a simpler process for license reciprocity in multiple states via interstate licensing compacts. Physicians would have to be licensed in the state in which the patient resides. Patient complaints would still be adjudicated by the medical licensing board in the state where the patient resides according applicable state legislation.

A Case Study in the Use of Primary Literature in the Context of Authentic Learning Pedagogy in the Undergraduate Neuroscience Classroom.

PubMed

O'Keeffe, Gerard W; McCarthy, Marian M

2017-01-01

Providing opportunities for undergraduate science students to develop causal reasoning skills and the ability to think like research scientists is a crucial part of their preparation for professional practice as a scientist and/or a clinician. This has led many to question whether the traditional academic in-class lecture still has a functional role in today's undergraduate science education. Here, we performed a case study to attempt to maximize the use of in-class time to create a more authentic learning opportunity for undergraduate neuroscience students in our institution, the majority of whom go on to be research active scientists. We hypothesised that using seminal research papers as a teaching tool in a flipped classroom setting would model for neuroscience students what it means to think like a research scientist, would provide an opportunity for them to develop their causal reasoning skills and allow them to become more comfortable with the nature of professional practice (i.e., research) in the context of the discipline. We describe the design and implementation of this teaching approach to undergraduate final year neuroscience students, and evaluate their perception of it. We provide evidence that this approach models for the students what it means to reason like a research scientist, and discuss the implications of these findings for future practice. We propose that these findings will help add to the educational experience of all Neuroscience students whether they are on pre-med or on a research track.

Enhancements to the Engine Data Interpretation System (EDIS)

NASA Technical Reports Server (NTRS)

Hofmann, Martin O.

1993-01-01

The Engine Data Interpretation System (EDIS) expert system project assists the data review personnel at NASA/MSFC in performing post-test data analysis and engine diagnosis of the Space Shuttle Main Engine (SSME). EDIS uses knowledge of the engine, its components, and simple thermodynamic principles instead of, and in addition to, heuristic rules gathered from the engine experts. EDIS reasons in cooperation with human experts, following roughly the pattern of logic exhibited by human experts. EDIS concentrates on steady-state static faults, such as small leaks, and component degradations, such as pump efficiencies. The objective of this contract was to complete the set of engine component models, integrate heuristic rules into EDIS, integrate the Power Balance Model into EDIS, and investigate modification of the qualitative reasoning mechanisms to allow 'fuzzy' value classification. The results of this contract is an operational version of EDIS. EDIS will become a module of the Post-Test Diagnostic System (PTDS) and will, in this context, provide system-level diagnostic capabilities which integrate component-specific findings provided by other modules.

Enhancements to the Engine Data Interpretation System (EDIS)

NASA Technical Reports Server (NTRS)

Hofmann, Martin O.

1993-01-01

The Engine Data Interpretation System (EDIS) expert system project assists the data review personnel at NASA/MSFC in performing post-test data analysis and engine diagnosis of the Space Shuttle Main Engine (SSME). EDIS uses knowledge of the engine, its components, and simple thermodynamic principles instead of, and in addition to, heuristic rules gathered from the engine experts. EDIS reasons in cooperation with human experts, following roughly the pattern of logic exhibited by human experts. EDIS concentrates on steady-state static faults, such as small leaks, and component degradations, such as pump efficiencies. The objective of this contract was to complete the set of engine component models, integrate heuristic rules into EDIS, integrate the Power Balance Model into EDIS, and investigate modification of the qualitative reasoning mechanisms to allow 'fuzzy' value classification. The result of this contract is an operational version of EDIS. EDIS will become a module of the Post-Test Diagnostic System (PTDS) and will, in this context, provide system-level diagnostic capabilities which integrate component-specific findings provided by other modules.

Users Manual for the Dynamic Student Flow Model.

DTIC Science & Technology

1981-07-31

populations within each pipeline are reasonably homogeneous and the pipeline curriculum provides a structured path along which the student must progress...curriculum is structured, student populations are non-homogeneous. They are drawn from diverse sources such as the Naval Aca- demy, NROTC and the Aviation...Officer Candidate program in numbers subjectively determined to provide the best population for subsequent flight training. His- torically, different

Don't Think, Just Feel the Music: Individuals with Strong Pavlovian-to-Instrumental Transfer Effects Rely Less on Model-based Reinforcement Learning.

PubMed

Sebold, Miriam; Schad, Daniel J; Nebe, Stephan; Garbusow, Maria; Jünger, Elisabeth; Kroemer, Nils B; Kathmann, Norbert; Zimmermann, Ulrich S; Smolka, Michael N; Rapp, Michael A; Heinz, Andreas; Huys, Quentin J M

2016-07-01

Behavioral choice can be characterized along two axes. One axis distinguishes reflexive, model-free systems that slowly accumulate values through experience and a model-based system that uses knowledge to reason prospectively. The second axis distinguishes Pavlovian valuation of stimuli from instrumental valuation of actions or stimulus-action pairs. This results in four values and many possible interactions between them, with important consequences for accounts of individual variation. We here explored whether individual variation along one axis was related to individual variation along the other. Specifically, we asked whether individuals' balance between model-based and model-free learning was related to their tendency to show Pavlovian interferences with instrumental decisions. In two independent samples with a total of 243 participants, Pavlovian-instrumental transfer effects were negatively correlated with the strength of model-based reasoning in a two-step task. This suggests a potential common underlying substrate predisposing individuals to both have strong Pavlovian interference and be less model-based and provides a framework within which to interpret the observation of both effects in addiction.

A Protective Factors Model for Alcohol Abuse and Suicide Prevention among Alaska Native Youth

PubMed Central

Allen, James; Mohatt, Gerald V.; Fok, Carlotta Ching Ting; Henry, David; Burkett, Rebekah

2014-01-01

This study provides an empirical test of a culturally grounded theoretical model for prevention of alcohol abuse and suicide risk with Alaska Native youth, using a promising set of culturally appropriate measures for the study of the process of change and outcome. This model is derived from qualitative work that generated an heuristic model of protective factors from alcohol (Allen at al., 2006; Mohatt, Hazel et al., 2004; Mohatt, Rasmus et al., 2004). Participants included 413 rural Alaska Native youth ages 12-18 who assisted in testing a predictive model of Reasons for Life and Reflective Processes about alcohol abuse consequences as co-occurring outcomes. Specific individual, family, peer, and community level protective factor variables predicted these outcomes. Results suggest prominent roles for these predictor variables as intermediate prevention strategy target variables in a theoretical model for a multilevel intervention. The model guides understanding of underlying change processes in an intervention to increase the ultimate outcome variables of Reasons for Life and Reflective Processes regarding the consequences of alcohol abuse. PMID:24952249

Of Pigs and Men: Understanding Students' Reasoning About the Use of Pigs as Donors for Xenotransplantation

NASA Astrophysics Data System (ADS)

Lindahl, Mats Gunnar

2010-09-01

Two important roles of education are to provide students with knowledge for their democratic participation in society and to provide knowledge for a future profession. In science education, students encounter values that may be in conflict with their worldview. Such conflicts may, for example, lead to constructive reflections as well as rejection of scientific knowledge and technology. Students’ ways of reasoning are important starting points for discussing problematic issues and may be crucial for constructive dialogues in the classroom. This study investigates students’ reasoning about conflicting values concerning the human-animal relationship exemplified by the use of genetically modified pigs as organ donors for xenotransplantation. Students’ reasoning is analyzed using Giddens’ concepts of disembedded and embedded practices in parallel with moral philosophical theories in a framework based on human-animal relationships. Thirteen students were interviewed and their stances categorized. Kantian deontological and classical utilitarian ethics were found within the patronage and the partnership models. These students appreciated expert knowledge but those using the partnership model could not accept xenotransplantation if pigs were to be killed. Students using care ethics did not appreciate expert knowledge since it threatened naturalness. The results suggest that stances against the use of scientific knowledge are more problematic than knowledge per se, and that conflicting stances have similarities that present opportunities for understanding and development of students’ argumentation skills for future participation in societal discourse on utilizing expert knowledge. Furthermore it is argued that science education could benefit from a higher awareness of the presence of different morals.

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.

Syntactic error modeling and scoring normalization in speech recognition: Error modeling and scoring normalization in the speech recognition task for adult literacy training

NASA Technical Reports Server (NTRS)

Olorenshaw, Lex; Trawick, David

1991-01-01

The purpose was to develop a speech recognition system to be able to detect speech which is pronounced incorrectly, given that the text of the spoken speech is known to the recognizer. Better mechanisms are provided for using speech recognition in a literacy tutor application. Using a combination of scoring normalization techniques and cheater-mode decoding, a reasonable acceptance/rejection threshold was provided. In continuous speech, the system was tested to be able to provide above 80 pct. correct acceptance of words, while correctly rejecting over 80 pct. of incorrectly pronounced words.

Common world model for unmanned systems: Phase 2

NASA Astrophysics Data System (ADS)

Dean, Robert M. S.; Oh, Jean; Vinokurov, Jerry

2014-06-01

The Robotics Collaborative Technology Alliance (RCTA) seeks to provide adaptive robot capabilities which move beyond traditional metric algorithms to include cognitive capabilities. Key to this effort is the Common World Model, which moves beyond the state-of-the-art by representing the world using semantic and symbolic as well as metric information. It joins these layers of information to define objects in the world. These objects may be reasoned upon jointly using traditional geometric, symbolic cognitive algorithms and new computational nodes formed by the combination of these disciplines to address Symbol Grounding and Uncertainty. The Common World Model must understand how these objects relate to each other. It includes the concept of Self-Information about the robot. By encoding current capability, component status, task execution state, and their histories we track information which enables the robot to reason and adapt its performance using Meta-Cognition and Machine Learning principles. The world model also includes models of how entities in the environment behave which enable prediction of future world states. To manage complexity, we have adopted a phased implementation approach. Phase 1, published in these proceedings in 2013 [1], presented the approach for linking metric with symbolic information and interfaces for traditional planners and cognitive reasoning. Here we discuss the design of "Phase 2" of this world model, which extends the Phase 1 design API, data structures, and reviews the use of the Common World Model as part of a semantic navigation use case.

The emotional dog and its rational tail: a social intuitionist approach to moral judgment.

PubMed

Haidt, J

2001-10-01

Research on moral judgment has been dominated by rationalist models, in which moral judgment is thought to be caused by moral reasoning. The author gives 4 reasons for considering the hypothesis that moral reasoning does not cause moral judgment; rather, moral reasoning is usually a post hoc construction, generated after a judgment has been reached. The social intuitionist model is presented as an alternative to rationalist models. The model is a social model in that it deemphasizes the private reasoning done by individuals and emphasizes instead the importance of social and cultural influences. The model is an intuitionist model in that it states that moral judgment is generally the result of quick, automatic evaluations (intuitions). The model is more consistent that rationalist models with recent findings in social, cultural, evolutionary, and biological psychology, as well as in anthropology and primatology.

QuEST for malware type-classification

NASA Astrophysics Data System (ADS)

Vaughan, Sandra L.; Mills, Robert F.; Grimaila, Michael R.; Peterson, Gilbert L.; Oxley, Mark E.; Dube, Thomas E.; Rogers, Steven K.

2015-05-01

Current cyber-related security and safety risks are unprecedented, due in no small part to information overload and skilled cyber-analyst shortages. Advances in decision support and Situation Awareness (SA) tools are required to support analysts in risk mitigation. Inspired by human intelligence, research in Artificial Intelligence (AI) and Computational Intelligence (CI) have provided successful engineering solutions in complex domains including cyber. Current AI approaches aggregate large volumes of data to infer the general from the particular, i.e. inductive reasoning (pattern-matching) and generally cannot infer answers not previously programmed. Whereas humans, rarely able to reason over large volumes of data, have successfully reached the top of the food chain by inferring situations from partial or even partially incorrect information, i.e. abductive reasoning (pattern-completion); generating a hypothetical explanation of observations. In order to achieve an engineering advantage in computational decision support and SA we leverage recent research in human consciousness, the role consciousness plays in decision making, modeling the units of subjective experience which generate consciousness, qualia. This paper introduces a novel computational implementation of a Cognitive Modeling Architecture (CMA) which incorporates concepts of consciousness. We apply our model to the malware type-classification task. The underlying methodology and theories are generalizable to many domains.

The Mismeasure of Academic Labour

ERIC Educational Resources Information Center

Papadopoulos, Angelika

2017-01-01

In quantifying and qualifying the scope of academic labour, workload models serve multiple ends. They are intended to facilitate equitable and transparent divisions of academic work, to provide academics with a sense of whether their workload is reasonable relative to their colleagues, and universities with a mechanism for rationalising the…

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)

Integrating Mediators and Moderators in Research Design

ERIC Educational Resources Information Center

MacKinnon, David P.

2011-01-01

The purpose of this article is to describe mediating variables and moderating variables and provide reasons for integrating them in outcome studies. Separate sections describe examples of moderating and mediating variables and the simplest statistical model for investigating each variable. The strengths and limitations of incorporating mediating…

The influence of activation level on belief bias in relational reasoning.

PubMed

Banks, Adrian P

2013-04-01

A novel explanation of belief bias in relational reasoning is presented based on the role of working memory and retrieval in deductive reasoning, and the influence of prior knowledge on this process. It is proposed that belief bias is caused by the believability of a conclusion in working memory which influences its activation level, determining its likelihood of retrieval and therefore its effect on the reasoning process. This theory explores two main influences of belief on the activation levels of these conclusions. First, believable conclusions have higher activation levels and so are more likely to be recalled during the evaluation of reasoning problems than unbelievable conclusions, and therefore, they have a greater influence on the reasoning process. Secondly, prior beliefs about the conclusion have a base level of activation and may be retrieved when logically irrelevant, influencing the evaluation of the problem. The theory of activation and memory is derived from the Atomic Components of Thought-Rational (ACT-R) cognitive architecture and so this account is formalized in an ACT-R cognitive model. Two experiments were conducted to test predictions of this model. Experiment 1 tested strength of belief and Experiment 2 tested the impact of a concurrent working memory load. Both of these manipulations increased the main effect of belief overall and in particular raised belief-based responding in indeterminately invalid problems. These effects support the idea that the activation level of conclusions formed during reasoning influences belief bias. This theory adds to current explanations of belief bias by providing a detailed specification of the role of working memory and how it is influenced by prior knowledge. Copyright © 2012 Cognitive Science Society, Inc.

Health behavior models and oral health: a review.

PubMed

Hollister, M Catherine; Anema, Marion G

2004-01-01

Dental hygienists help their clients develop health promoting behaviors, by providing essential information about general health, and oral health in particular. Individual health practices such as oral self-care are based on personal choices. The guiding principles found in health behavior models provide useful methods to the oral health care providers in promoting effective individual client behaviors. Theories provide explanations about observable facts in a systematic manner. Research regarding health behavior has explored the effectiveness and applicability of various health models in oral health behavior modification. The Health Belief Model, Transtheoretical Model and Stages of Change, Theory of Reasoned Action, Self-Efficacy, Locus of Control, and Sense of Coherence are examples of models that focus on individuals assuming responsibility for their own health. Understanding the strengths of each and their applicability to health behaviors is critical for oral health care providers who work with patients to adopt methods and modify behaviors that contribute to good oral health. This paper describes health behavior models that have been applied to oral health education, presents a critical analysis of the effectiveness of each model in oral health education, and provides examples of application to oral health education.

Improving Hydrological Simulations by Incorporating GRACE Data for Parameter Calibration

NASA Astrophysics Data System (ADS)

Bai, P.

2017-12-01

Hydrological model parameters are commonly calibrated by observed streamflow data. This calibration strategy is questioned when the modeled hydrological variables of interest are not limited to streamflow. Well-performed streamflow simulations do not guarantee the reliable reproduction of other hydrological variables. One of the reasons is that hydrological model parameters are not reasonably identified. The Gravity Recovery and Climate Experiment (GRACE) satellite-derived total water storage change (TWSC) data provide an opportunity to constrain hydrological model parameterizations in combination with streamflow observations. We constructed a multi-objective calibration scheme based on GRACE-derived TWSC and streamflow observations, with the aim of improving the parameterizations of hydrological models. The multi-objective calibration scheme was compared with the traditional single-objective calibration scheme, which is based only on streamflow observations. Two monthly hydrological models were employed on 22 Chinese catchments with different hydroclimatic conditions. The model evaluation was performed using observed streamflows, GRACE-derived TWSC, and evapotranspiraiton (ET) estimates from flux towers and from the water balance approach. Results showed that the multi-objective calibration provided more reliable TWSC and ET simulations without significant deterioration in the accuracy of streamflow simulations than the single-objective calibration. In addition, the improvements of TWSC and ET simulations were more significant in relatively dry catchments than in relatively wet catchments. This study highlights the importance of including additional constraints besides streamflow observations in the parameter estimation to improve the performances of hydrological models.

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.

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.

Helping Students Develop Statistical Reasoning: Implementing a Statistical Reasoning Learning Environment

ERIC Educational Resources Information Center

Garfield, Joan; Ben-Zvi, Dani

2009-01-01

This article describes a model for an interactive, introductory secondary- or tertiary-level statistics course that is designed to develop students' statistical reasoning. This model is called a "Statistical Reasoning Learning Environment" and is built on the constructivist theory of learning.

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.

Methodological individualism in experimental games: not so easily dismissed.

PubMed

Krueger, Joachim I

2008-06-01

Orthodox game theory and social preference models cannot explain why people cooperate in many experimental games or how they manage to coordinate their choices. The theory of evidential decision making provides a solution, based on the idea that people tend to project their own choices onto others, whatever these choices might be. Evidential decision making preserves methodological individualism, and it works without recourse to social preferences. Rejecting methodological individualism, team reasoning is a thinly disguised resurgence of the group mind fallacy, and the experiments reported by Colman et al. [Colman, A. M., Pulford, B. D., & Rose, J. (this issue). Collective rationality in interactive decisions: Evidence for team reasoning. Acta Psychologica, doi:10.1016/j.actpsy.2007.08.003.] do not offer evidence that uniquely supports team reasoning.

Logical Reasoning versus Information Processing in the Dual-Strategy Model of Reasoning

ERIC Educational Resources Information Center

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

2017-01-01

One of the major debates concerning the nature of inferential reasoning is between counterexample-based strategies such as mental model theory and statistical strategies underlying probabilistic models. The dual-strategy model, proposed by Verschueren, Schaeken, & d'Ydewalle (2005a, 2005b), which suggests that people might have access to both…

Development of the Statistical Reasoning in Biology Concept Inventory (SRBCI)

PubMed Central

Deane, Thomas; Nomme, Kathy; Jeffery, Erica; Pollock, Carol; Birol, Gülnur

2016-01-01

We followed established best practices in concept inventory design and developed a 12-item inventory to assess student ability in statistical reasoning in biology (Statistical Reasoning in Biology Concept Inventory [SRBCI]). It is important to assess student thinking in this conceptual area, because it is a fundamental requirement of being statistically literate and associated skills are needed in almost all walks of life. Despite this, previous work shows that non–expert-like thinking in statistical reasoning is common, even after instruction. As science educators, our goal should be to move students along a novice-to-expert spectrum, which could be achieved with growing experience in statistical reasoning. We used item response theory analyses (the one-parameter Rasch model and associated analyses) to assess responses gathered from biology students in two populations at a large research university in Canada in order to test SRBCI’s robustness and sensitivity in capturing useful data relating to the students’ conceptual ability in statistical reasoning. Our analyses indicated that SRBCI is a unidimensional construct, with items that vary widely in difficulty and provide useful information about such student ability. SRBCI should be useful as a diagnostic tool in a variety of biology settings and as a means of measuring the success of teaching interventions designed to improve statistical reasoning skills. PMID:26903497

Predicting substance-abuse treatment providers' communication with clients about medication assisted treatment: a test of the theories of reasoned action and planned behavior.

PubMed

Roberto, Anthony J; Shafer, Michael S; Marmo, Jennifer

2014-01-01

The purpose of this investigation is to determine if the theory of reasoned action (TRA) and theory of planned behavior (TPB) can retrospectively predict whether substance-abuse treatment providers encourage their clients to use medicated-assisted treatment (MAT) as part of their treatment plan. Two-hundred and ten substance-abuse treatment providers completed a survey measuring attitudes, subjective norms, perceived behavioral control, intentions, and behavior. Results indicate that substance-abuse treatment providers have very positive attitudes, neutral subjective norms, somewhat positive perceived behavioral control, somewhat positive intentions toward recommending MAT as part of their clients' treatment plan, and were somewhat likely to engage in the actual behavior. Further, the data fit both the TRA and TPB, but with the TPB model having better fit and predictive power for this target audience and behavior. The theoretical and practical implications for the developing messages for substance-abuse treatment providers and other health-care professionals who provide treatment to patients with substance use disorders are discussed. Copyright © 2014 Elsevier Inc. All rights reserved.

Calculating and Understanding: Formal Models and Causal Explanations in Science, Common Reasoning and Physics Teaching

NASA Astrophysics Data System (ADS)

Besson, Ugo

2010-03-01

This paper presents an analysis of the different types of reasoning and physical explanation used in science, common thought, and physics teaching. It then reflects on the learning difficulties connected with these various approaches, and suggests some possible didactic strategies. Although causal reasoning occurs very frequently in common thought and daily life, it has long been the subject of debate and criticism among philosophers and scientists. In this paper, I begin by providing a description of some general tendencies of common reasoning that have been identified by didactic research. Thereafter, I briefly discuss the role of causality in science, as well as some different types of explanation employed in the field of physics. I then present some results of a study examining the causal reasoning used by students in solid and fluid mechanics. The differences found between the types of reasoning typical of common thought and those usually proposed during instruction can create learning difficulties and impede student motivation. Many students do not seem satisfied by the mere application of formal laws and functional relations. Instead, they express the need for a causal explanation, a mechanism that allows them to understand how a state of affairs has come about. I discuss few didactic strategies aimed at overcoming these problems, and describe, in general terms, two examples of mechanics teaching sequences which were developed and tested in different contexts. The paper ends with a reflection on the possible role to be played in physics learning by intuitive and imaginative thought, and the use of simple explanatory models based on physical analogies and causal mechanisms.

Technical Note: FreeCT_ICD: An Open Source Implementation of a Model-Based Iterative Reconstruction Method using Coordinate Descent Optimization for CT Imaging Investigations.

PubMed

Hoffman, John M; Noo, Frédéric; Young, Stefano; Hsieh, Scott S; McNitt-Gray, Michael

2018-06-01

To facilitate investigations into the impacts of acquisition and reconstruction parameters on quantitative imaging, radiomics and CAD using CT imaging, we previously released an open source implementation of a conventional weighted filtered backprojection reconstruction called FreeCT_wFBP. Our purpose was to extend that work by providing an open-source implementation of a model-based iterative reconstruction method using coordinate descent optimization, called FreeCT_ICD. Model-based iterative reconstruction offers the potential for substantial radiation dose reduction, but can impose substantial computational processing and storage requirements. FreeCT_ICD is an open source implementation of a model-based iterative reconstruction method that provides a reasonable tradeoff between these requirements. This was accomplished by adapting a previously proposed method that allows the system matrix to be stored with a reasonable memory requirement. The method amounts to describing the attenuation coefficient using rotating slices that follow the helical geometry. In the initially-proposed version, the rotating slices are themselves described using blobs. We have replaced this description by a unique model that relies on tri-linear interpolation together with the principles of Joseph's method. This model offers an improvement in memory requirement while still allowing highly accurate reconstruction for conventional CT geometries. The system matrix is stored column-wise and combined with an iterative coordinate descent (ICD) optimization. The result is FreeCT_ICD, which is a reconstruction program developed on the Linux platform using C++ libraries and the open source GNU GPL v2.0 license. The software is capable of reconstructing raw projection data of helical CT scans. In this work, the software has been described and evaluated by reconstructing datasets exported from a clinical scanner which consisted of an ACR accreditation phantom dataset and a clinical pediatric thoracic scan. For the ACR phantom, image quality was comparable to clinical reconstructions as well as reconstructions using open-source FreeCT_wFBP software. The pediatric thoracic scan also yielded acceptable results. In addition, we did not observe any deleterious impact in image quality associated with the utilization of rotating slices. These evaluations also demonstrated reasonable tradeoffs in storage requirements and computational demands. FreeCT_ICD is an open-source implementation of a model-based iterative reconstruction method that extends the capabilities of previously released open source reconstruction software and provides the ability to perform vendor-independent reconstructions of clinically acquired raw projection data. This implementation represents a reasonable tradeoff between storage and computational requirements and has demonstrated acceptable image quality in both simulated and clinical image datasets. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

The Effect of Functional Hearing and Hearing Aid Usage on Verbal Reasoning in a Large Community-Dwelling Population.

PubMed

Keidser, Gitte; Rudner, Mary; Seeto, Mark; Hygge, Staffan; Rönnberg, Jerker

2016-01-01

Verbal reasoning performance is an indicator of the ability to think constructively in everyday life and relies on both crystallized and fluid intelligence. This study aimed to determine the effect of functional hearing on verbal reasoning when controlling for age, gender, and education. In addition, the study investigated whether hearing aid usage mitigated the effect and examined different routes from hearing to verbal reasoning. Cross-sectional data on 40- to 70-year-old community-dwelling participants from the UK Biobank resource were accessed. Data consisted of behavioral and subjective measures of functional hearing, assessments of numerical and linguistic verbal reasoning, measures of executive function, and demographic and lifestyle information. Data on 119,093 participants who had completed hearing and verbal reasoning tests were submitted to multiple regression analyses, and data on 61,688 of these participants, who had completed additional cognitive tests and provided relevant lifestyle information, were submitted to structural equation modeling. Poorer performance on the behavioral measure of functional hearing was significantly associated with poorer verbal reasoning in both the numerical and linguistic domains (p < 0.001). There was no association between the subjective measure of functional hearing and verbal reasoning. Functional hearing significantly interacted with education (p < 0.002), showing a trend for functional hearing to have a greater impact on verbal reasoning among those with a higher level of formal education. Among those with poor hearing, hearing aid usage had a significant positive, but not necessarily causal, effect on both numerical and linguistic verbal reasoning (p < 0.005). The estimated effect of hearing aid usage was less than the effect of poor functional hearing. Structural equation modeling analyses confirmed that controlling for education reduced the effect of functional hearing on verbal reasoning and showed that controlling for executive function eliminated the effect. However, when computer usage was controlled for, the eliminating effect of executive function was weakened. Poor functional hearing was associated with poor verbal reasoning in a 40- to 70-year-old community-dwelling population after controlling for age, gender, and education. The effect of functional hearing on verbal reasoning was significantly reduced among hearing aid users and completely overcome by good executive function skills, which may be enhanced by playing computer games.

Common sense reasoning about petroleum flow

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

Rosenberg, S.

1981-02-01

This paper describes an expert system for understanding and Reasoning in a petroleum resources domain. A basic model is implemented in FRL (Frame Representation Language). Expertise is encoded as rule frames. The model consists of a set of episodic contexts which are sequentially generated over time. Reasoning occurs in separate reasoning contexts consisting of a buffer frame and packets of rules. These function similar to small production systems. reasoning is linked to the model through an interface of Sentinels (instance driven demons) which notice anomalous conditions. Heuristics and metaknowledge are used through the creation of further reasoning contexts which overlaymore » the simpler ones.« less

Preference of methadone maintenance patients for the integrative and decentralized service delivery models in Vietnam.

PubMed

Tran, Bach Xuan; Nguyen, Long Hoang; Phan, Huong Thu Thi; Nguyen, Linh Khanh; Latkin, Carl A

2015-09-17

Integrating and decentralizing services are essential to increase the accessibility and provide comprehensive care for methadone patients. Moreover, they assure the sustainability of a HIV/AIDS prevention program by reducing the implementation cost. This study aimed to measure the preference of patients enrolling in a MMT program for integrated and decentralized MMT clinics and then further examine related factors. A cross-sectional study was conducted among 510 patients receiving methadone at 3 clinics in Hanoi. Structured questionnaires were used to collect data about the preference for integrated and decentralized MMT services. Covariates including socio-economic status; health-related quality of life (using EQ-5D-5 L instrument) and HIV status; history of drug use along with MMT treatment; and exposure to the discrimination within family and community were also investigated. Multivariate logistic regression with polynomial fractions was used to identify the determinants of preference for integrative and decentralized models. Of 510 patients enrolled, 66.7 and 60.8 % preferred integrated and decentralized models, respectively. The main reason for preferring the integrative model was the convenience of use of various services (53.2 %), while more privacy (43.5 %) was the primary reason to select stand-alone model. People preferred the decentralized model primarily because of travel cost reduction (95.0 %), while the main reason for not selecting the model was increased privacy (7.7 %). After adjusting for covariates, factors influencing the preference for integrative model were poor socioeconomic status, anxiety/depression, history of drug rehabilitation, and ever disclosed health status; while exposure to community discrimination inversely associated with this preference. In addition, people who were self-employed, had a longer duration of MMT, and use current MMT with comprehensive HIV services were less likely to select decentralized model. In conclusion, the study confirmed the high preference of MMT patients for the integrative and decentralized MMT service delivery models. The convenience of healthcare services utilization and reduction of geographical barriers were the main reasons to use those models within drug use populations in Vietnam. Countering community stigma and encouraging communication between patients and their societies needed to be considered when implementing those models.

Integration of perception and reasoning in fast neural modules

NASA Technical Reports Server (NTRS)

Fritz, David G.

1989-01-01

Artificial neural systems promise to integrate symbolic and sub-symbolic processing to achieve real time control of physical systems. Two potential alternatives exist. In one, neural nets can be used to front-end expert systems. The expert systems, in turn, are developed with varying degrees of parallelism, including their implementation in neural nets. In the other, rule-based reasoning and sensor data can be integrated within a single hybrid neural system. The hybrid system reacts as a unit to provide decisions (problem solutions) based on the simultaneous evaluation of data and rules. Discussed here is a model hybrid system based on the fuzzy cognitive map (FCM). The operation of the model is illustrated with the control of a hypothetical satellite that intelligently alters its attitude in space in response to an intersecting micrometeorite shower.

Model-based reasoning in SSF ECLSS

NASA Technical Reports Server (NTRS)

Miller, J. K.; Williams, George P. W., Jr.

1992-01-01

The interacting processes and reconfigurable subsystems of the Space Station Freedom Environmental Control and Life Support System (ECLSS) present a tremendous technical challenge to Freedom's crew and ground support. ECLSS operation and problem analysis is time-consuming for crew members and difficult for current computerized control, monitoring, and diagnostic software. These challenges can be at least partially mitigated by the use of advanced techniques such as Model-Based Reasoning (MBR). This paper will provide an overview of MBR as it is being applied to Space Station Freedom ECLSS. It will report on work being done to produce intelligent systems to help design, control, monitor, and diagnose Freedom's ECLSS. Specifically, work on predictive monitoring, diagnosability, and diagnosis, with emphasis on the automated diagnosis of the regenerative water recovery and air revitalization processes will be discussed.

Protecting sensitive systems and data in an open agency

NASA Technical Reports Server (NTRS)

Hunt, Douglas B.; Tompkins, Frederick G.

1987-01-01

This paper focuses on the policy and definitional issues associated with providing adequate and reasonable levels of protection for sensitive systems and data in an agency whose basic charter mandates the open sharing of information and transfer of technology into the market economy. An information model based on current Federal regulatory issuances is presented. A scheme for determining sensitivity levels, based on a categorization taxonomy,is provided.

The Case for Reasonable Accommodation of Conscientious Objections to Declarations of Brain Death.

PubMed

Johnson, L Syd M

2016-03-01

Since its inception in 1968, the concept of whole-brain death has been contentious, and four decades on, controversy concerning the validity and coherence of whole-brain death continues unabated. Although whole-brain death is legally recognized and medically entrenched in the United States and elsewhere, there is reasonable disagreement among physicians, philosophers, and the public concerning whether brain death is really equivalent to death as it has been traditionally understood. A handful of states have acknowledged this plurality of viewpoints and enacted "conscience clauses" that require "reasonable accommodation" of religious and moral objections to the determination of death by neurological criteria. This paper argues for the universal adoption of "reasonable accommodation" policies using the New Jersey statute as a model, in light of both the ongoing controversy and the recent case of Jahi McMath, a child whose family raised religious objections to a declaration of brain death. Public policies that accommodate reasonable, divergent viewpoints concerning death provide a practical and compassionate way to resolve those conflicts that are the most urgent, painful, and difficult to reconcile.

Discontinuous categories affect information-integration but not rule-based category learning.

PubMed

Maddox, W Todd; Filoteo, J Vincent; Lauritzen, J Scott; Connally, Emily; Hejl, Kelli D

2005-07-01

Three experiments were conducted that provide a direct examination of within-category discontinuity manipulations on the implicit, procedural-based learning and the explicit, hypothesis-testing systems proposed in F. G. Ashby, L. A. Alfonso-Reese, A. U. Turken, and E. M. Waldron's (1998) competition between verbal and implicit systems model. Discontinuous categories adversely affected information-integration but not rule-based category learning. Increasing the magnitude of the discontinuity did not lead to a significant decline in performance. The distance to the bound provides a reasonable description of the generalization profile associated with the hypothesis-testing system, whereas the distance to the bound plus the distance to the trained response region provides a reasonable description of the generalization profile associated with the procedural-based learning system. These results suggest that within-category discontinuity differentially impacts information-integration but not rule-based category learning and provides information regarding the detailed processing characteristics of each category learning system. ((c) 2005 APA, all rights reserved).

Improvement of sand filter and constructed wetland design using an environmental decision support system.

PubMed

Turon, Clàudia; Comas, Joaquim; Torrens, Antonina; Molle, Pascal; Poch, Manel

2008-01-01

With the aim of improving effluent quality of waste stabilization ponds, different designs of vertical flow constructed wetlands and intermittent sand filters were tested on an experimental full-scale plant within the framework of a European project. The information extracted from this study was completed and updated with heuristic and bibliographic knowledge. The data and knowledge acquired were difficult to integrate into mathematical models because they involve qualitative information and expert reasoning. Therefore, it was decided to develop an environmental decision support system (EDSS-Filter-Design) as a tool to integrate mathematical models and knowledge-based techniques. This paper describes the development of this support tool, emphasizing the collection of data and knowledge and representation of this information by means of mathematical equations and a rule-based system. The developed support tool provides the main design characteristics of filters: (i) required surface, (ii) media type, and (iii) media depth. These design recommendations are based on wastewater characteristics, applied load, and required treatment level data provided by the user. The results of the EDSS-Filter-Design provide appropriate and useful information and guidelines on how to design filters, according to the expert criteria. The encapsulation of the information into a decision support system reduces the design period and provides a feasible, reasoned, and positively evaluated proposal.

The behavior of the Higgs field in the new inflationary universe

NASA Technical Reports Server (NTRS)

Guth, Alan H.; Pi, So-Young

1986-01-01

Answers are provided to questions about the standard model of the new inflationary universe (NIU) which have raised concerns about the model's validity. A baby toy problem which consists of the study of a single particle moving in one dimension under the influence of a potential with the form of an upside-down harmonic oscillator is studied, showing that the quantum mechanical wave function at large times is accurately described by classical physics. Then, an exactly soluble toy model for the behavior of the Higgs field in the NIU is described which should provide a reasonable approximation to the behavior of the Higgs field in the NIU. The dynamics of the toy model is described, and calculative results are reviewed which, the authors claim, provide strong evidence that the basic features of the standard picture are correct.

Constructivist Learning of Anatomy: Gaining Knowledge by Creating Anatomical Casts

ERIC Educational Resources Information Center

Hermiz, David J.; O'Sullivan, Daniel J.; Lujan, Heidi L.; DiCarlo, Stephen E.

2011-01-01

Educators are encouraged to provide inquiry-based, collaborative, and problem solving activities that enhance learning and promote curiosity, skepticism, objectivity, and the use of scientific reasoning. Making anatomical casts or models by injecting solidifying substances into organs is an example of a constructivist activity for achieving these…

The Modelling of Reasoning and Justification Methods in the Teaching of Fraction Division at Year 4 Level in Vietnam

ERIC Educational Resources Information Center

Norton, Stephen; Thao, Do Thi Phurong; Duy, Mai The

2014-01-01

Stephen Norton, Do Thi Phurong Thao and Mai The Duy provide an interesting insight into the teaching of fraction division in Vietnam. The article highlights one of the many teaching strategies available to teachers for building fraction concepts.

Processes Underlying Children's Adjustment in Families Characterized by Physical Aggression.

ERIC Educational Resources Information Center

Onyskiw, Judee; Hayduk, Leslie A.

2001-01-01

The hypothesis that physical aggression in the family affects children's adjustment through both observational learning/modeling and through its impact on parenting was tested, via LISREL, using data from a sample of Canadian children (N=11,221). Results showed observational learning and disrupted parenting provide reasonable explanations of…

Grief and Mourning Reactions Following Abortion and Miscarriage.

ERIC Educational Resources Information Center

Widener, Anmarie J.

1996-01-01

Explores current research on psychological reactions following induced and spontaneous abortions. Provides examples of studies wherein researchers have used a loss model to understand this experience. Explores possible reasons for the apparent inattention to grief reactions following this type of loss and offers an alternative approach to the loss…

High Tech Training at Arthur Andersen and Co.

ERIC Educational Resources Information Center

Dennis, Verl E.

1984-01-01

Discusses Arthur Andersen and Company's reasons for using high technology in job training, including its ability to improve productivity, provide training on demand, reduce training costs, and keep educational quality consistent. A Life Cycle Model which is used to integrate high technology into this accounting company's educational programs is…

Virtual Reality and Engineering Education.

ERIC Educational Resources Information Center

Pantelidis, Veronica S.

1997-01-01

Virtual Reality (VR) offers benefits to engineering education. This article defines VR and describes types; outlines reasons for using VR in engineering education; provides guidelines for using VR; presents a model for determining when to use VR; discusses VR applications; and describes hardware and software needed for a low-budget VR and…

Earthworms, Dirt, and Rotten Leaves: An Exploration in Ecology.

ERIC Educational Resources Information Center

McLaughlin, Molly

1994-01-01

This article provides a model for inviting children to "an exploration in ecology" by observing earthworms. It gives reasons to explore earthworms and guides the investigator through a detailed examination of the worms to answer 21 observation questions. Explores the ways in which earthworms interact with their environment. (LZ)

Meandering down to the Sea: The Wandering Ways of Rivers.

ERIC Educational Resources Information Center

Aslamazov, Lev

1992-01-01

Discusses the hydrodynamic reasons why a riverbed meanders through a plain. Describes how water movement at a bend in a river causes erosion and changes in the riverbed. Provides a mathematical model to explain the periodic shape of meanders of a river in a plain. (MDH)

Vegetarianism and food perception. Selective visual attention to meat pictures.

PubMed

Stockburger, Jessica; Renner, Britta; Weike, Almut I; Hamm, Alfons O; Schupp, Harald T

2009-04-01

Vegetarianism provides a model system to examine the impact of negative affect towards meat, based on ideational reasoning. It was hypothesized that meat stimuli are efficient attention catchers in vegetarians. Event-related brain potential recordings served to index selective attention processes at the level of initial stimulus perception. Consistent with the hypothesis, late positive potentials to meat pictures were enlarged in vegetarians compared to omnivores. This effect was specific for meat pictures and obtained during passive viewing and an explicit attention task condition. These findings demonstrate the attention capture of food stimuli, deriving affective salience from ideational reasoning and symbolic meaning.

Proof Rules for Automated Compositional Verification through Learning

NASA Technical Reports Server (NTRS)

Barringer, Howard; Giannakopoulou, Dimitra; Pasareanu, Corina S.

2003-01-01

Compositional proof systems not only enable the stepwise development of concurrent processes but also provide a basis to alleviate the state explosion problem associated with model checking. An assume-guarantee style of specification and reasoning has long been advocated to achieve compositionality. However, this style of reasoning is often non-trivial, typically requiring human input to determine appropriate assumptions. In this paper, we present novel assume- guarantee rules in the setting of finite labelled transition systems with blocking communication. We show how these rules can be applied in an iterative and fully automated fashion within a framework based on learning.

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.

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

PubMed

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

2017-01-01

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

Use of shape-preserving interpolation methods in surface modeling

NASA Technical Reports Server (NTRS)

Ftitsch, F. N.

1984-01-01

In many large-scale scientific computations, it is necessary to use surface models based on information provided at only a finite number of points (rather than determined everywhere via an analytic formula). As an example, an equation of state (EOS) table may provide values of pressure as a function of temperature and density for a particular material. These values, while known quite accurately, are typically known only on a rectangular (but generally quite nonuniform) mesh in (T,d)-space. Thus interpolation methods are necessary to completely determine the EOS surface. The most primitive EOS interpolation scheme is bilinear interpolation. This has the advantages of depending only on local information, so that changes in data remote from a mesh element have no effect on the surface over the element, and of preserving shape information, such as monotonicity. Most scientific calculations, however, require greater smoothness. Standard higher-order interpolation schemes, such as Coons patches or bicubic splines, while providing the requisite smoothness, tend to produce surfaces that are not physically reasonable. This means that the interpolant may have bumps or wiggles that are not supported by the data. The mathematical quantification of ideas such as physically reasonable and visually pleasing is examined.

Investigating College and Graduate Students' Multivariable Reasoning in Computational Modeling

ERIC Educational Resources Information Center

Wu, Hsin-Kai; Wu, Pai-Hsing; Zhang, Wen-Xin; Hsu, Ying-Shao

2013-01-01

Drawing upon the literature in computational modeling, multivariable reasoning, and causal attribution, this study aims at characterizing multivariable reasoning practices in computational modeling and revealing the nature of understanding about multivariable causality. We recruited two freshmen, two sophomores, two juniors, two seniors, four…

A flow resistance model for assessing the impact of vegetation on flood routing mechanics

NASA Astrophysics Data System (ADS)

Katul, Gabriel G.; Poggi, Davide; Ridolfi, Luca

2011-08-01

The specification of a flow resistance factor to account for vegetative effects in the Saint-Venant equation (SVE) remains uncertain and is a subject of active research in flood routing mechanics. Here, an analytical model for the flow resistance factor is proposed for submerged vegetation, where the water depth is commensurate with the canopy height and the roughness Reynolds number is sufficiently large so as to ignore viscous effects. The analytical model predicts that the resistance factor varies with three canonical length scales: the adjustment length scale that depends on the foliage drag and leaf area density, the canopy height, and the water level. These length scales can reasonably be inferred from a range of remote sensing products making the proposed flow resistance model eminently suitable for operational flood routing. Despite the numerous simplifications, agreement between measured and modeled resistance factors and bulk velocities is reasonable across a range of experimental and field studies. The proposed model asymptotically recovers the flow resistance formulation when the water depth greatly exceeds the canopy height. This analytical treatment provides a unifying framework that links the resistance factor to a number of concepts and length scales already in use to describe canopy turbulence. The implications of the coupling between the resistance factor and the water depth on solutions to the SVE are explored via a case study, which shows a reasonable match between empirical design standard and theoretical predictions.

A Survey of Long-Range Forecasting Models and Data Resources: A Method for Their Application at the Department of Defense.

DTIC Science & Technology

1979-08-08

confident analysis or prediction. Still, the behavioralist models do provide a basis for comparison and analysis of real world environments . In addition...p.236. 60 o Environmental - the lowest level and encompasses man’s physical environment (climate, land, water, air, and physical resources); also... analysis . The food model report is based on two postulates: a. It is reasonable to review agriculture in an ecosystems framework *Mesarovic, M., and Pestel

Learning In networks

NASA Technical Reports Server (NTRS)

Buntine, Wray L.

1995-01-01

Intelligent systems require software incorporating probabilistic reasoning, and often times learning. Networks provide a framework and methodology for creating this kind of software. This paper introduces network models based on chain graphs with deterministic nodes. Chain graphs are defined as a hierarchical combination of Bayesian and Markov networks. To model learning, plates on chain graphs are introduced to model independent samples. The paper concludes by discussing various operations that can be performed on chain graphs with plates as a simplification process or to generate learning algorithms.

The Emergence of Metaethical Reasoning.

ERIC Educational Resources Information Center

Langford, Peter E.

A multidimensional model of the growth of moral reasoning is described that is significantly different from those proposed by Kohlberg and Piaget. A study that tests several aspects of the model on university students is reported. The suggestion that well-developed chains of reasons are a prerequisite for the emergence of metaethical reasoning was…

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.

Picture this: The value of multiple visual representations for student learning of quantum concepts in general chemistry

NASA Astrophysics Data System (ADS)

Allen, Emily Christine

Mental models for scientific learning are often defined as, "cognitive tools situated between experiments and theories" (Duschl & Grandy, 2012). In learning, these cognitive tools are used to not only take in new information, but to help problem solve in new contexts. Nancy Nersessian (2008) describes a mental model as being "[loosely] characterized as a representation of a system with interactive parts with representations of those interactions. Models can be qualitative, quantitative, and/or simulative (mental, physical, computational)" (p. 63). If conceptual parts used by the students in science education are inaccurate, then the resulting model will not be useful. Students in college general chemistry courses are presented with multiple abstract topics and often struggle to fit these parts into complete models. This is especially true for topics that are founded on quantum concepts, such as atomic structure and molecular bonding taught in college general chemistry. The objectives of this study were focused on how students use visual tools introduced during instruction to reason with atomic and molecular structure, what misconceptions may be associated with these visual tools, and how visual modeling skills may be taught to support students' use of visual tools for reasoning. The research questions for this study follow from Gilbert's (2008) theory that experts use multiple representations when reasoning and modeling a system, and Kozma and Russell's (2005) theory of representational competence levels. This study finds that as students developed greater command of their understanding of abstract quantum concepts, they spontaneously provided additional representations to describe their more sophisticated models of atomic and molecular structure during interviews. This suggests that when visual modeling with multiple representations is taught, along with the limitations of the representations, it can assist students in the development of models for reasoning about abstract topics such as atomic and molecular structure. There is further gain if students' difficulties with these representations are targeted through the use additional instruction such as a workbook that requires the students to exercise their visual modeling skills.

Multistate Landau-Zener models with all levels crossing at one point

DOE PAGES

Li, Fuxiang; Sun, Chen; Chernyak, Vladimir Y.; ...

2017-08-04

Within this paper, we discuss common properties and reasons for integrability in the class of multistate Landau-Zener models with all diabatic levels crossing at one point. Exploring the Stokes phenomenon, we show that each previously solved model has a dual one, whose scattering matrix can be also obtained analytically. For applications, we demonstrate how our results can be used to study conversion of molecular into atomic Bose condensates during passage through the Feshbach resonance, and provide purely algebraic solutions of the bowtie and special cases of the driven Tavis-Cummings model.

Collaborative human-machine analysis using a controlled natural language

NASA Astrophysics Data System (ADS)

Mott, David H.; Shemanski, Donald R.; Giammanco, Cheryl; Braines, Dave

2015-05-01

A key aspect of an analyst's task in providing relevant information from data is the reasoning about the implications of that data, in order to build a picture of the real world situation. This requires human cognition, based upon domain knowledge about individuals, events and environmental conditions. For a computer system to collaborate with an analyst, it must be capable of following a similar reasoning process to that of the analyst. We describe ITA Controlled English (CE), a subset of English to represent analyst's domain knowledge and reasoning, in a form that it is understandable by both analyst and machine. CE can be used to express domain rules, background data, assumptions and inferred conclusions, thus supporting human-machine interaction. A CE reasoning and modeling system can perform inferences from the data and provide the user with conclusions together with their rationale. We present a logical problem called the "Analysis Game", used for training analysts, which presents "analytic pitfalls" inherent in many problems. We explore an iterative approach to its representation in CE, where a person can develop an understanding of the problem solution by incremental construction of relevant concepts and rules. We discuss how such interactions might occur, and propose that such techniques could lead to better collaborative tools to assist the analyst and avoid the "pitfalls".

A distributed reasoning engine ecosystem for semantic context-management in smart environments.

PubMed

Almeida, Aitor; López-de-Ipiña, Diego

2012-01-01

To be able to react adequately a smart environment must be aware of the context and its changes. Modeling the context allows applications to better understand it and to adapt to its changes. In order to do this an appropriate formal representation method is needed. Ontologies have proven themselves to be one of the best tools to do it. Semantic inference provides a powerful framework to reason over the context data. But there are some problems with this approach. The inference over semantic context information can be cumbersome when working with a large amount of data. This situation has become more common in modern smart environments where there are a lot sensors and devices available. In order to tackle this problem we have developed a mechanism to distribute the context reasoning problem into smaller parts in order to reduce the inference time. In this paper we describe a distributed peer-to-peer agent architecture of context consumers and context providers. We explain how this inference sharing process works, partitioning the context information according to the interests of the agents, location and a certainty factor. We also discuss the system architecture, analyzing the negotiation process between the agents. Finally we compare the distributed reasoning with the centralized one, analyzing in which situations is more suitable each approach.

A Case Study in the Use of Primary Literature in the Context of Authentic Learning Pedagogy in the Undergraduate Neuroscience Classroom

PubMed Central

O’Keeffe, Gerard W.; McCarthy, Marian M.

2017-01-01

Providing opportunities for undergraduate science students to develop causal reasoning skills and the ability to think like research scientists is a crucial part of their preparation for professional practice as a scientist and/or a clinician. This has led many to question whether the traditional academic in-class lecture still has a functional role in today’s undergraduate science education. Here, we performed a case study to attempt to maximize the use of in-class time to create a more authentic learning opportunity for undergraduate neuroscience students in our institution, the majority of whom go on to be research active scientists. We hypothesised that using seminal research papers as a teaching tool in a flipped classroom setting would model for neuroscience students what it means to think like a research scientist, would provide an opportunity for them to develop their causal reasoning skills and allow them to become more comfortable with the nature of professional practice (i.e., research) in the context of the discipline. We describe the design and implementation of this teaching approach to undergraduate final year neuroscience students, and evaluate their perception of it. We provide evidence that this approach models for the students what it means to reason like a research scientist, and discuss the implications of these findings for future practice. We propose that these findings will help add to the educational experience of all Neuroscience students whether they are on pre-med or on a research track. PMID:29371836

Representing Learning With Graphical Models

NASA Technical Reports Server (NTRS)

Buntine, Wray L.; Lum, Henry, Jr. (Technical Monitor)

1994-01-01

Probabilistic graphical models are being used widely in artificial intelligence, for instance, in diagnosis and expert systems, as a unified qualitative and quantitative framework for representing and reasoning with probabilities and independencies. Their development and use spans several fields including artificial intelligence, decision theory and statistics, and provides an important bridge between these communities. This paper shows by way of example that these models can be extended to machine learning, neural networks and knowledge discovery by representing the notion of a sample on the graphical model. Not only does this allow a flexible variety of learning problems to be represented, it also provides the means for representing the goal of learning and opens the way for the automatic development of learning algorithms from specifications.

Model-Based Reasoning in Humans Becomes Automatic with Training.

PubMed

Economides, Marcos; Kurth-Nelson, Zeb; Lübbert, Annika; Guitart-Masip, Marc; Dolan, Raymond J

2015-09-01

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

Combining Static Model Checking with Dynamic Enforcement Using the Statecall Policy Language

NASA Astrophysics Data System (ADS)

Madhavapeddy, Anil

Internet protocols encapsulate a significant amount of state, making implementing the host software complex. In this paper, we define the Statecall Policy Language (SPL) which provides a usable middle ground between ad-hoc coding and formal reasoning. It enables programmers to embed automata in their code which can be statically model-checked using SPIN and dynamically enforced. The performance overheads are minimal, and the automata also provide higher-level debugging capabilities. We also describe some practical uses of SPL by describing the automata used in an SSH server written entirely in OCaml/SPL.

Model-Based Reasoning

ERIC Educational Resources Information Center

Ifenthaler, Dirk; Seel, Norbert M.

2013-01-01

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

Economic models for prevention: making a system work for patients

PubMed Central

2015-01-01

The purpose of this article is to describe alternative means of providing patient centered, preventive based, services using an alternative non-profit, economic model. Hard to reach, vulnerable groups, including children, adults and elders, often have difficulties accessing traditional dental services for a number of reasons, including economic barriers. By partnering with community organizations that serve these groups, collaborative services and new opportunities for access are provided. The concept of a dental home is well accepted as a means of providing care, and, for these groups, provision of such services within community settings provides a sustainable means of delivery. Dental homes provided through community partnerships can deliver evidence based dental care, focused on a preventive model to achieve and maintain oral health. By using a non-profit model, the entire dental team is provided with incentives to deliver measurable quality improvements in care, rather than a more traditional focus on volume of activity alone. Examples are provided that demonstrate how integrated oral health services can deliver improved health outcomes with the potential to reduce total costs while improving quality. PMID:26391814

The coexistence of alternative and scientific conceptions in physics

NASA Astrophysics Data System (ADS)

Ozdemir, Omer F.

The purpose of this study was to inquire about the simultaneous coexistence of alternative and scientific conceptions in the domain of physics. This study was particularly motivated by several arguments put forward in opposition to the Conceptual Change Model. In the simplest form, these arguments state that people construct different domains of knowledge and different modes of perception in different situations. Therefore, holding different conceptualizations is unavoidable and expecting a replacement in an individual's conceptual structure is not plausible in terms of instructional practices. The following research questions were generated to inquire about this argument: (1) Do individuals keep their alternative conceptions after they have acquired scientific conceptions? (2) Assuming that individuals who acquired scientific conceptions also have alternative conceptions, how are these different conceptions nested in their conceptual structure? (3) What kind of knowledge, skills, and reasoning are necessary to transfer scientific principles instead of alternative ones in the construction of a valid model? Analysis of the data collected from the non-physics group indicated that the nature of alternative conceptions is framed by two types of reasoning: reasoning by mental simulation and semiformal reasoning. Analysis of the data collected from the physics group revealed that mental images or scenes feeding reasoning by mental simulation had not disappeared after the acquisition of scientific conceptions. The analysis of data also provided enough evidence to conclude that alternative principles feeding semiformal reasoning have not necessarily disappeared after the acquisition of scientific conceptions. However, in regard to semiformal reasoning, compartmentalization was not as clear as the case demonstrated in reasoning by mental simulation; instead semiformal and scientific reasoning are intertwined in a way that the components of semiformal reasoning can easily take their place among the components of scientific reasoning. In spite of the fact that the coexistence of multiple conceptions might obstruct the transfer of scientific conceptions in problem-solving situations, several factors stimulating the use of scientific conceptions were noticed explicitly. These factors were categorized as follows: (a) the level of individuals' domain specific knowledge in the corresponding field, (b) the level of individuals' knowledge about the process of science (how science generates its knowledge claims), (c) the level of individuals' awareness of different types of reasoning and conceptions, and (d) the context in which the problem is situated. (Abstract shortened by UMI.)

Vehicle Integrated Prognostic Reasoner (VIPR) 2010 Annual Final Report

NASA Technical Reports Server (NTRS)

Hadden, George D.; Mylaraswamy, Dinkar; Schimmel, Craig; Biswas, Gautam; Koutsoukos, Xenofon; Mack, Daniel

2011-01-01

Honeywell's Central Maintenance Computer Function (CMCF) and Aircraft Condition Monitoring Function (ACMF) represent the state-of-the art in integrated vehicle health management (IVHM). Underlying these technologies is a fault propagation modeling system that provides nose-to-tail coverage and root cause diagnostics. The Vehicle Integrated Prognostic Reasoner (VIPR) extends this technology to interpret evidence generated by advanced diagnostic and prognostic monitors provided by component suppliers to detect, isolate, and predict adverse events that affect flight safety. This report describes year one work that included defining the architecture and communication protocols and establishing the user requirements for such a system. Based on these and a set of ConOps scenarios, we designed and implemented a demonstration of communication pathways and associated three-tiered health management architecture. A series of scripted scenarios showed how VIPR would detect adverse events before they escalate as safety incidents through a combination of advanced reasoning and additional aircraft data collected from an aircraft condition monitoring system. Demonstrating VIPR capability for cases recorded in the ASIAS database and cross linking them with historical aircraft data is planned for year two.

White Matter Maturation Supports the Development of Reasoning Ability Through its Influence on Processing Speed

PubMed Central

Ferrer, E.; Whitaker, K.J.; Steele, J.; Green, C.T.; Wendelken, C.; Bunge, S.A.

2013-01-01

The structure of the human brain changes in several ways throughout childhood and adolescence. Perhaps the most salient of these changes is the strengthening of white matter tracts that enable distal brain regions to communicate with one another more quickly and efficiently. Here, we sought to understand whether and how white matter changes contribute to improved reasoning ability over development. In particular, we sought to understand whether previously reported relationships between white matter microstructure and reasoning are mediated by processing speed. To this end, we analyzed diffusion tensor imaging data as well as data from standard psychometric tests of cognitive abilities from 103 individuals between the ages of 6 and 18. We used structural equation modeling to investigate the network of relationships between brain and behavior variables. Our analyses provide support for the hypothesis that white matter maturation (as indexed either by microstructural organization or volume) supports improved processing speed, which, in turn, supports improved reasoning ability. PMID:24118718

Best friends' discussions of social dilemmas.

PubMed

McDonald, Kristina L; Malti, Tina; Killen, Melanie; Rubin, Kenneth H

2014-02-01

Peer relationships, particularly friendships, have been theorized to contribute to how children and adolescents think about social and moral issues. The current study examined how young adolescent best friends (191 dyads; 53.4% female) reason together about multifaceted social dilemmas and how their reasoning is related to friendship quality. Mutually-recognized friendship dyads were videotaped discussing dilemmas entailing moral, social-conventional and prudential/pragmatic issues. Both dyad members completed a self-report measure of friendship quality. Dyadic data analyses guided by the Actor-Partner Interdependence Model indicated that adolescent and friend reports of friendship qualities were related to the forms of reasoning used during discussion. Friends who both reported that they could resolve conflicts in a constructive way were more likely to use moral reasoning than friends who reported that their conflict resolution was poor or disagreed on the quality of their conflict resolution. The findings provide evidence for the important role that friendship interaction may play in adolescents' social and moral development.

Different neural systems contribute to semantic bias and conflict detection in the inclusion fallacy task.

PubMed

Liang, Peipeng; Goel, Vinod; Jia, Xiuqin; Li, Kuncheng

2014-01-01

The inclusion fallacy is a phenomenon in which generalization from a specific premise category to a more general conclusion category is considered stronger than a generalization to a specific conclusion category nested within the more general set. Such inferences violate rational norms and are part of the reasoning fallacy literature that provides interesting tasks to explore cognitive and neural basis of reasoning. To explore the functional neuroanatomy of the inclusion fallacy, we used a 2 × 2 factorial design, with factors for quantification (explicit and implicit) and response (fallacious and non-fallacious). It was found that a left fronto-temporal system, along with a superior medial frontal system, was specifically activated in response to fallacious responses consistent with a semantic biasing of judgment explanation. A right fronto-parietal system was specifically recruited in response to detecting conflict associated with the heightened fallacy condition. These results are largely consistent with previous studies of reasoning fallacy and support a multiple systems model of reasoning.

Best Friends’ Discussions of Social Dilemmas

PubMed Central

McDonald, Kristina L.; Malti, Tina; Killen, Melanie; Rubin, Kenneth H.

2013-01-01

Peer relationships, particularly friendships, have been theorized to contribute to how children and adolescents think about social and moral issues. The current study examined how young adolescent best friends (191 dyads; 53.4% female) reason together about multifaceted social dilemmas and how their reasoning is related to friendship quality. Mutually-recognized friendship dyads were videotaped discussing dilemmas entailing moral, social-conventional and prudential/pragmatic issues. Both dyad members completed a self-report measure of friendship quality. Dyadic data analyses guided by the Actor-Partner Interdependence Model indicated that adolescent and friend's reports of friendship qualities were related to the forms of reasoning used during discussion. Friends who both reported that they could resolve conflicts in a constructive way were more likely to use moral reasoning than friends who reported that their conflict resolution was poor or disagreed on the quality of their conflict resolution. The findings provide evidence for the important role that friendship interaction may play in adolescents’ social and moral development. PMID:23666555

Stimulating Scientific Reasoning with Drawing-Based Modeling

NASA Astrophysics Data System (ADS)

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

2018-02-01

We investigate the way students' reasoning about evolution can be supported by drawing-based modeling. We modified the drawing-based modeling tool SimSketch to allow for modeling evolutionary processes. In three iterations of development and testing, students in lower secondary education worked on creating an evolutionary model. After each iteration, the user interface and instructions were adjusted based on students' remarks and the teacher's observations. Students' conversations were analyzed on reasoning complexity as a measurement of efficacy of the modeling tool and the instructions. These findings were also used to compose a set of recommendations for teachers and curriculum designers for using and constructing models in the classroom. Our findings suggest that to stimulate scientific reasoning in students working with a drawing-based modeling, tool instruction about the tool and the domain should be integrated. In creating models, a sufficient level of scaffolding is necessary. Without appropriate scaffolds, students are not able to create the model. With scaffolding that is too high, students may show reasoning that incorrectly assigns external causes to behavior in the model.

The Attentional Drift Diffusion Model of Simple Perceptual Decision-Making.

PubMed

Tavares, Gabriela; Perona, Pietro; Rangel, Antonio

2017-01-01

Perceptual decisions requiring the comparison of spatially distributed stimuli that are fixated sequentially might be influenced by fluctuations in visual attention. We used two psychophysical tasks with human subjects to investigate the extent to which visual attention influences simple perceptual choices, and to test the extent to which the attentional Drift Diffusion Model (aDDM) provides a good computational description of how attention affects the underlying decision processes. We find evidence for sizable attentional choice biases and that the aDDM provides a reasonable quantitative description of the relationship between fluctuations in visual attention, choices and reaction times. We also find that exogenous manipulations of attention induce choice biases consistent with the predictions of the model.

Evaluation of Skin Temperatures Retrieved from GOES-8

NASA Technical Reports Server (NTRS)

Suggs, Ronnie, J.; Jedlovec, G. J.; Lapenta, W. M.; Haines, S. L.

2000-01-01

Skin temperatures derived from geostationary satellites have the potential of providing the temporal and spatial resolution needed for model assimilation. To adequately assess the potential improvements in numerical model forecasts that can be made by assimilating satellite data, an estimate of the accuracy of the skin temperature product is necessary. A particular skin temperature algorithm, the Physical Split Window Technique, that uses the longwave infrared channels of the GOES Imager has shown promise in recent model assimilation studies to provide land surface temperatures with reasonable accuracy. A comparison of retrieved GOES-8 skin temperatures from this algorithm with in situ measurements is presented. Various retrieval algorithm issues are addressed including surface emissivity

Verification and Validation of Autonomy Software at NASA

NASA Technical Reports Server (NTRS)

Pecheur, Charles

2000-01-01

Autonomous software holds the promise of new operation possibilities, easier design and development and lower operating costs. However, as those system close control loops and arbitrate resources on board with specialized reasoning, the range of possible situations becomes very large and uncontrollable from the outside, making conventional scenario-based testing very inefficient. Analytic verification and validation (V&V) techniques, and model checking in particular, can provide significant help for designing autonomous systems in a more efficient and reliable manner, by providing a better coverage and allowing early error detection. This article discusses the general issue of V&V of autonomy software, with an emphasis towards model-based autonomy, model-checking techniques and concrete experiments at NASA.

Verification and Validation of Autonomy Software at NASA

NASA Technical Reports Server (NTRS)

Pecheur, Charles

2000-01-01

Autonomous software holds the promise of new operation possibilities, easier design and development, and lower operating costs. However, as those system close control loops and arbitrate resources on-board with specialized reasoning, the range of possible situations becomes very large and uncontrollable from the outside, making conventional scenario-based testing very inefficient. Analytic verification and validation (V&V) techniques, and model checking in particular, can provide significant help for designing autonomous systems in a more efficient and reliable manner, by providing a better coverage and allowing early error detection. This article discusses the general issue of V&V of autonomy software, with an emphasis towards model-based autonomy, model-checking techniques, and concrete experiments at NASA.

Exploring family physicians' reasons to continue or discontinue providing intrapartum care: Qualitative descriptive study.

PubMed

Dove, Marion; Dogba, Maman Joyce; Rodríguez, Charo

2017-08-01

To examine the reasons why family physicians continue or discontinue providing intrapartum care in their clinical practice. Qualitative descriptive study. Two hospitals located in a multicultural area of Montreal, Que, in November 2011 to June 2012. Sixteen family physicians who were current or former providers of obstetric care. Data were collected using semistructured qualitative interviews. Thematic analysis was used to analyze the interview transcripts. Three overarching themes that help create understanding of why family doctors continue to provide obstetric care were identified: their attraction, often initiated by role models early in their careers, to practising complete continuity of care and accompanying patients in a special moment in their lives; the personal, family, and organizational pressures experienced while pursuing a family medicine career that includes obstetrics; and their ongoing reflection about continuing to practise obstetrics. The practice of obstetrics was very attractive to family physician participants whether they provided intrapartum care or decided to stop. More professional support and incentives might help keep family doctors practising obstetrics. Copyright© the College of Family Physicians of Canada.

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.

Model Package Report: Central Plateau Vadose Zone Geoframework Version 1.0

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

Springer, Sarah D.

The purpose of the Central Plateau Vadose Zone (CPVZ) Geoframework model (GFM) is to provide a reasonable, consistent, and defensible three-dimensional (3D) representation of the vadose zone beneath the Central Plateau at the Hanford Site to support the Composite Analysis (CA) vadose zone contaminant fate and transport models. The GFM is a 3D representation of the subsurface geologic structure. From this 3D geologic model, exported results in the form of point, surface, and/or volumes are used as inputs to populate and assemble the various numerical model architectures, providing a 3D-layered grid that is consistent with the GFM. The objective ofmore » this report is to define the process used to produce a hydrostratigraphic model for the vadose zone beneath the Hanford Site Central Plateau and the corresponding CA domain.« less

My Corporis Fabrica: an ontology-based tool for reasoning and querying on complex anatomical models

PubMed Central

2014-01-01

Background Multiple models of anatomy have been developed independently and for different purposes. In particular, 3D graphical models are specially useful for visualizing the different organs composing the human body, while ontologies such as FMA (Foundational Model of Anatomy) are symbolic models that provide a unified formal description of anatomy. Despite its comprehensive content concerning the anatomical structures, the lack of formal descriptions of anatomical functions in FMA limits its usage in many applications. In addition, the absence of connection between 3D models and anatomical ontologies makes it difficult and time-consuming to set up and access to the anatomical content of complex 3D objects. Results First, we provide a new ontology of anatomy called My Corporis Fabrica (MyCF), which conforms to FMA but extends it by making explicit how anatomical structures are composed, how they contribute to functions, and also how they can be related to 3D complex objects. Second, we have equipped MyCF with automatic reasoning capabilities that enable model checking and complex queries answering. We illustrate the added-value of such a declarative approach for interactive simulation and visualization as well as for teaching applications. Conclusions The novel vision of ontologies that we have developed in this paper enables a declarative assembly of different models to obtain composed models guaranteed to be anatomically valid while capturing the complexity of human anatomy. The main interest of this approach is its declarativity that makes possible for domain experts to enrich the knowledge base at any moment through simple editors without having to change the algorithmic machinery. This provides MyCF software environment a flexibility to process and add semantics on purpose for various applications that incorporate not only symbolic information but also 3D geometric models representing anatomical entities as well as other symbolic information like the anatomical functions. PMID:24936286

Interactive Visualization of Complex Seismic Data and Models Using Bokeh

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

Chai, Chengping; Ammon, Charles J.; Maceira, Monica

Visualizing multidimensional data and models becomes more challenging as the volume and resolution of seismic data and models increase. But thanks to the development of powerful and accessible computer systems, a model web browser can be used to visualize complex scientific data and models dynamically. In this paper, we present four examples of seismic model visualization using an open-source Python package Bokeh. One example is a visualization of a surface-wave dispersion data set, another presents a view of three-component seismograms, and two illustrate methods to explore a 3D seismic-velocity model. Unlike other 3D visualization packages, our visualization approach has amore » minimum requirement on users and is relatively easy to develop, provided you have reasonable programming skills. Finally, utilizing familiar web browsing interfaces, the dynamic tools provide us an effective and efficient approach to explore large data sets and models.« less

Interactive Visualization of Complex Seismic Data and Models Using Bokeh

DOE PAGES

Chai, Chengping; Ammon, Charles J.; Maceira, Monica; ...

2018-02-14

Visualizing multidimensional data and models becomes more challenging as the volume and resolution of seismic data and models increase. But thanks to the development of powerful and accessible computer systems, a model web browser can be used to visualize complex scientific data and models dynamically. In this paper, we present four examples of seismic model visualization using an open-source Python package Bokeh. One example is a visualization of a surface-wave dispersion data set, another presents a view of three-component seismograms, and two illustrate methods to explore a 3D seismic-velocity model. Unlike other 3D visualization packages, our visualization approach has amore » minimum requirement on users and is relatively easy to develop, provided you have reasonable programming skills. Finally, utilizing familiar web browsing interfaces, the dynamic tools provide us an effective and efficient approach to explore large data sets and models.« less

A protective factors model for alcohol abuse and suicide prevention among Alaska Native youth.

PubMed

Allen, James; Mohatt, Gerald V; Fok, Carlotta Ching Ting; Henry, David; Burkett, Rebekah

2014-09-01

This study provides an empirical test of a culturally grounded theoretical model for prevention of alcohol abuse and suicide risk with Alaska Native youth, using a promising set of culturally appropriate measures for the study of the process of change and outcome. This model is derived from qualitative work that generated an heuristic model of protective factors from alcohol (Allen et al. in J Prev Interv Commun 32:41-59, 2006; Mohatt et al. in Am J Commun Psychol 33:263-273, 2004a; Harm Reduct 1, 2004b). Participants included 413 rural Alaska Native youth ages 12-18 who assisted in testing a predictive model of Reasons for Life and Reflective Processes about alcohol abuse consequences as co-occurring outcomes. Specific individual, family, peer, and community level protective factor variables predicted these outcomes. Results suggest prominent roles for these predictor variables as intermediate prevention strategy target variables in a theoretical model for a multilevel intervention. The model guides understanding of underlying change processes in an intervention to increase the ultimate outcome variables of Reasons for Life and Reflective Processes regarding the consequences of alcohol abuse.

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Superlinear scaling for innovation in cities.

PubMed

Arbesman, Samuel; Kleinberg, Jon M; Strogatz, Steven H

2009-01-01

Superlinear scaling in cities, which appears in sociological quantities such as economic productivity and creative output relative to urban population size, has been observed, but not been given a satisfactory theoretical explanation. Here we provide a network model for the superlinear relationship between population size and innovation found in cities, with a reasonable range for the exponent.

One-Reason Decision Making Unveiled: A Measurement Model of the Recognition Heuristic

ERIC Educational Resources Information Center

Hilbig, Benjamin E.; Erdfelder, Edgar; Pohl, Rudiger F.

2010-01-01

The fast-and-frugal recognition heuristic (RH) theory provides a precise process description of comparative judgments. It claims that, in suitable domains, judgments between pairs of objects are based on recognition alone, whereas further knowledge is ignored. However, due to the confound between recognition and further knowledge, previous…

Elementary Students' Reasoning about Angle Constructions

ERIC Educational Resources Information Center

Cullen, Amanda L.; Cullen, Craig J.; O'Hanlon, Wendy A.

2017-01-01

In this report, we discuss the findings from 2 pilot studies investigating the effects of interventions designed to provide students in Grades 3-5 with opportunities to work with dynamic and static models of angles in a dynamic geometry environment. We discuss the effects of the interventions on the children's development of quantitative reasoning…

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,…

Superlinear scaling for innovation in cities

NASA Astrophysics Data System (ADS)

Arbesman, Samuel; Kleinberg, Jon M.; Strogatz, Steven H.

2009-01-01

Superlinear scaling in cities, which appears in sociological quantities such as economic productivity and creative output relative to urban population size, has been observed, but not been given a satisfactory theoretical explanation. Here we provide a network model for the superlinear relationship between population size and innovation found in cities, with a reasonable range for the exponent.

Spatial Processes in Linear Ordering

ERIC Educational Resources Information Center

von Hecker, Ulrich; Klauer, Karl Christoph; Wolf, Lukas; Fazilat-Pour, Masoud

2016-01-01

Memory performance in linear order reasoning tasks (A > B, B > C, C > D, etc.) shows quicker, and more accurate responses to queries on wider (AD) than narrower (AB) pairs on a hypothetical linear mental model (A -- B -- C -- D). While indicative of an analogue representation, research so far did not provide positive evidence for spatial…

Ohio Vocational Consumer/Homemaking Curriculum Guide. Practical Action.

ERIC Educational Resources Information Center

Ohio State Univ., Columbus. Instructional Materials Lab.

This curriculum guide helps students learn the technical skills of the occupation of homemaking. It also uses the process model of practical reasoning to assist men and women in taking action regarding the perennial problems that face individuals and families living in the world society. The first section provides the philosophy, aim, student…

Designing Genetics Instruction for a Socratic Approach

ERIC Educational Resources Information Center

Idros, Sharifah Norhaidah Syed

2004-01-01

Science is at heart a rational activity. Reasoning, being an important component of critical thinking has been successfully taught using Socratic methods. As an approach, the instructor or designer of instruction models an inquiring and probing mind focusing on providing questions and not answers. The main aim has been to allow learners to…

ProvenCare: Geisinger's Model for Care Transformation through Innovative Clinical Initiatives and Value Creation.

PubMed

2009-04-01

Geisinger's system of care can be seen as a microcosm of the national delivery of healthcare, with implications for decision makers in other health plans. In this interview, Dr Ronald A. Paulus focuses on Geisinger's unique approach to patient care. In its core, this approach represents a system of quality and value initiatives based on 3 major programs-Proven Health Navigation (medical home); the ProvenCare model; and transitions of care. The goal of such an approach is to optimize disease management by using a rational reimbursement paradigm for appropriate interventions, providing innovative incentives, and engaging patients in their own care as part of any intervention. Dr Paulus explains the reasons why, unlike Geisinger, other stakeholders, including payers, providers, patients, and employers, have no intrinsic reasons to be concerned with quality and value initiatives. In addition, he says, an electronic infrastructure that could be modified as management paradigms evolve is a necessary tool to ensure the healthcare delivery system's ability to adapt to new clinical realities quickly to ensure the continuation of delivering best value for all stakeholders.

Reducing cognitive skill decay and diagnostic error: theory-based practices for continuing education in health care.

PubMed

Weaver, Sallie J; Newman-Toker, David E; Rosen, Michael A

2012-01-01

Missed, delayed, or wrong diagnoses can have a severe impact on patients, providers, and the entire health care system. One mechanism implicated in such diagnostic errors is the deterioration of cognitive diagnostic skills that are used rarely or not at all over a prolonged period of time. Existing evidence regarding maintenance of effective cognitive reasoning skills in the clinical education, organizational training, and human factors literatures suggest that continuing education plays a critical role in mitigating and managing diagnostic skill decay. Recent models also underscore the role of system level factors (eg, cognitive decision support tools, just-in-time training opportunities) in supporting clinical reasoning process. The purpose of this manuscript is to offer a multidisciplinary review of cognitive models of clinical decision making skills in order to provide a list of best practices for supporting continuous improvement and maintenance of cognitive diagnostic processes through continuing education. Copyright © 2012 The Alliance for Continuing Education in the Health Professions, the Society for Academic Continuing Medical Education, and the Council on CME, Association for Hospital Medical Education.

Estimating a Reasonable Patient Panel Size for Primary Care Physicians With Team-Based Task Delegation

PubMed Central

Altschuler, Justin; Margolius, David; Bodenheimer, Thomas; Grumbach, Kevin

2012-01-01

PURPOSE Primary care faces the dilemma of excessive patient panel sizes in an environment of a primary care physician shortage. We aimed to estimate primary care panel sizes under different models of task delegation to nonphysician members of the primary care team. METHODS We used published estimates of the time it takes for a primary care physician to provide preventive, chronic, and acute care for a panel of 2,500 patients, and modeled how panel sizes would change if portions of preventive and chronic care services were delegated to nonphysician team members. RESULTS Using 3 assumptions about the degree of task delegation that could be achieved (77%, 60%, and 50% of preventive care, and 47%, 30%, and 25% of chronic care), we estimated that a primary care team could reasonably care for a panel of 1,947, 1,523, or 1,387 patients. CONCLUSIONS If portions of preventive and chronic care services are delegated to nonphysician team members, primary care practices can provide recommended preventive and chronic care with panel sizes that are achievable with the available primary care workforce. PMID:22966102

Estimating a reasonable patient panel size for primary care physicians with team-based task delegation.

PubMed

Altschuler, Justin; Margolius, David; Bodenheimer, Thomas; Grumbach, Kevin

2012-01-01

PURPOSE Primary care faces the dilemma of excessive patient panel sizes in an environment of a primary care physician shortage. We aimed to estimate primary care panel sizes under different models of task delegation to nonphysician members of the primary care team. METHODS We used published estimates of the time it takes for a primary care physician to provide preventive, chronic, and acute care for a panel of 2,500 patients, and modeled how panel sizes would change if portions of preventive and chronic care services were delegated to nonphysician team members. RESULTS Using 3 assumptions about the degree of task delegation that could be achieved (77%, 60%, and 50% of preventive care, and 47%, 30%, and 25% of chronic care), we estimated that a primary care team could reasonably care for a panel of 1,947, 1,523, or 1,387 patients. CONCLUSIONS If portions of preventive and chronic care services are delegated to nonphysician team members, primary care practices can provide recommended preventive and chronic care with panel sizes that are achievable with the available primary care workforce.

The effect of creative problem solving on students’ mathematical adaptive reasoning

NASA Astrophysics Data System (ADS)

Muin, A.; Hanifah, S. H.; Diwidian, F.

2018-01-01

This research was conducted to analyse the effect of creative problem solving (CPS) learning model on the students’ mathematical adaptive reasoning. The method used in this study was a quasi-experimental with randomized post-test only control group design. Samples were taken as many as two classes by cluster random sampling technique consisting of experimental class (CPS) as many as 40 students and control class (conventional) as many as 40 students. Based on the result of hypothesis testing with the t-test at the significance level of 5%, it was obtained that significance level of 0.0000 is less than α = 0.05. This shows that the students’ mathematical adaptive reasoning skills who were taught by CPS model were higher than the students’ mathematical adaptive reasoning skills of those who were taught by conventional model. The result of this research showed that the most prominent aspect of adaptive reasoning that could be developed through a CPS was inductive intuitive. Two aspects of adaptive reasoning, which were inductive intuitive and deductive intuitive, were mostly balanced. The different between inductive intuitive and deductive intuitive aspect was not too big. CPS model can develop student mathematical adaptive reasoning skills. CPS model can facilitate development of mathematical adaptive reasoning skills thoroughly.

Midwives׳ clinical reasoning during second stage labour: Report on an interpretive study.

PubMed

Jefford, Elaine; Fahy, Kathleen

2015-05-01

clinical reasoning was once thought to be the exclusive domain of medicine - setting it apart from 'non-scientific' occupations like midwifery. Poor assessment, clinical reasoning and decision-making skills are well known contributors to adverse outcomes in maternity care. Midwifery decision-making models share a common deficit: they are insufficiently detailed to guide reasoning processes for midwives in practice. For these reasons we wanted to explore if midwives actively engaged in clinical reasoning processes within their clinical practice and if so to what extent. The study was conducted using post structural, feminist methodology. to what extent do midwives engage in clinical reasoning processes when making decisions in the second stage labour? twenty-six practising midwives were interviewed. Feminist interpretive analysis was conducted by two researchers guided by the steps of a model of clinical reasoning process. Six narratives were excluded from analysis because they did not sufficiently address the research question. The midwives narratives were prepared via data reduction. A theoretically informed analysis and interpretation was conducted. using a feminist, interpretive approach we created a model of midwifery clinical reasoning grounded in the literature and consistent with the data. Thirteen of the 20 participant narratives demonstrate analytical clinical reasoning abilities but only nine completed the process and implemented the decision. Seven midwives used non-analytical decision-making without adequately checking against assessment data. over half of the participants demonstrated the ability to use clinical reasoning skills. Less than half of the midwives demonstrated clinical reasoning as their way of making decisions. The new model of Midwifery Clinical Reasoning includes 'intuition' as a valued way of knowing. Using intuition, however, should not replace clinical reasoning which promotes through decision-making can be made transparent and be consensually validated. Copyright © 2015 Elsevier Ltd. All rights reserved.

The use of multiple models in case-based diagnosis

NASA Technical Reports Server (NTRS)

Karamouzis, Stamos T.; Feyock, Stefan

1993-01-01

The work described in this paper has as its goal the integration of a number of reasoning techniques into a unified intelligent information system that will aid flight crews with malfunction diagnosis and prognostication. One of these approaches involves using the extensive archive of information contained in aircraft accident reports along with various models of the aircraft as the basis for case-based reasoning about malfunctions. Case-based reasoning draws conclusions on the basis of similarities between the present situation and prior experience. We maintain that the ability of a CBR program to reason about physical systems is significantly enhanced by the addition to the CBR program of various models. This paper describes the diagnostic concepts implemented in a prototypical case based reasoner that operates in the domain of in-flight fault diagnosis, the various models used in conjunction with the reasoner's CBR component, and results from a preliminary evaluation.

"Model-Based Reasoning is Not a Simple Thing": Investigating Enactment of Modeling in Five High School Biology Classrooms

NASA Astrophysics Data System (ADS)

Gaytan, Candice Renee

Modeling is an important scientific practice through which scientists generate, evaluate, and revise scientific knowledge, and it can be translated into science classrooms as a means for engaging students in authentic scientific practice. Much of the research investigating modeling in classrooms focuses on student learning, leaving a gap in understanding how teachers enact this important practice. This dissertation draws on data collected through a model-based curricular project to uncover instructional moves teachers made to enact modeling, to describe factors influencing enactment, and to discuss a framework for designing and enacting modeling lessons. I framed my analysis and interpretation of data within the varying perceptions of modeling found in the science studies and science education literature. Largely, modeling is described to varying degrees as a means to engage students in sense-making or as a means to deliver content to students. This frame revealed how the instructional moves teachers used to enact modeling may have influenced its portrayal as a reasoning practice. I found that teachers' responses to their students' ideas or questions may have important consequences for students' engagement in modeling, and thus, sense-making. To investigate factors influencing the portrayal of modeling, I analyzed teacher interviews and writings for what they perceived affected instruction. My findings illustrate alignments and misalignments between what teachers perceive modeling to be and what they do through instruction. In particular, teachers valued providing their students with time to collaborate and to share their ideas, but when time was perceived as a constraint, instruction shifted towards delivering content. Additionally, teachers' perceptions of students' capacity to engage in modeling is also related to if and how they provided opportunities for students to make sense of phenomena. The dissertation closes with a discussion of a framework for designing and enacting lessons for engaging students in modeling. I draw on examples from this study to provide context for how the framework can support teachers in engaging students in modeling. Altogether, this dissertation describes how teachers facilitate modeling and why varying enactments may be observed, filling a gap in researchers' understanding of how teachers enact modeling in science classrooms.

Development of the Computerized Model of Performance-Based Measurement System to Measure Nurses' Clinical Competence.

PubMed

Liou, Shwu-Ru; Liu, Hsiu-Chen; Tsai, Shu-Ling; Cheng, Ching-Yu; Yu, Wei-Chieh; Chu, Tsui-Ping

2016-04-01

Critical thinking skills and clinical competence are for providing quality patient care. The purpose of this study is to develop the Computerized Model of Performance-Based Measurement system based on the Clinical Reasoning Model. The system can evaluate and identify learning needs for clinical competency and be used as a learning tool to increase clinical competency by using computers. The system includes 10 high-risk, high-volume clinical case scenarios coupled with questions testing clinical reasoning, interpersonal, and technical skills. Questions were sequenced to reflect patients' changing condition and arranged by following the process of collecting and managing information, diagnosing and differentiating urgency of problems, and solving problems. The content validity and known-groups validity was established. The Kuder-Richardson Formula 20 was 0.90 and test-retest reliability was supported (r = 0.78). Nursing educators can use the system to understand students' needs for achieving clinical competence, and therefore, educational plans can be made to better prepare students and facilitate their smooth transition to a future clinical environment. Clinical nurses can use the system to evaluate their performance-based abilities and weakness in clinical reasoning. Appropriate training programs can be designed and implemented to practically promote nurses' clinical competence and quality of patient care.

Tableau Calculus for the Logic of Comparative Similarity over Arbitrary Distance Spaces

NASA Astrophysics Data System (ADS)

Alenda, Régis; Olivetti, Nicola

The logic CSL (first introduced by Sheremet, Tishkovsky, Wolter and Zakharyaschev in 2005) allows one to reason about distance comparison and similarity comparison within a modal language. The logic can express assertions of the kind "A is closer/more similar to B than to C" and has a natural application to spatial reasoning, as well as to reasoning about concept similarity in ontologies. The semantics of CSL is defined in terms of models based on different classes of distance spaces and it generalizes the logic S4 u of topological spaces. In this paper we consider CSL defined over arbitrary distance spaces. The logic comprises a binary modality to represent comparative similarity and a unary modality to express the existence of the minimum of a set of distances. We first show that the semantics of CSL can be equivalently defined in terms of preferential models. As a consequence we obtain the finite model property of the logic with respect to its preferential semantic, a property that does not hold with respect to the original distance-space semantics. Next we present an analytic tableau calculus based on its preferential semantics. The calculus provides a decision procedure for the logic, its termination is obtained by imposing suitable blocking restrictions.

Effects of alloy composition on cyclic flame hot-corrosion attack of cast nickel-base superalloys at 900 deg C

NASA Technical Reports Server (NTRS)

Deadmore, D. L.

1984-01-01

The effects of Cr, Al, Ti, Mo, Ta, Nb, and W content on the hot corrosion of nickel base alloys were investigated. The alloys were tested in a Mach 0.3 flame with 0.5 ppmw sodium at a temperature of 900 C. One nondestructive and three destructive tests were conducted. The best corrosion resistance was achieved when the Cr content was 12 wt %. However, some lower-Cr-content alloys ( 10 wt%) exhibited reasonable resistance provided that the Al content alloys ( 10 wt %) exhibited reasonable resistance provided that the Al content was 2.5 wt % and the Ti content was Aa wt %. The effect of W, Ta, Mo, and Nb contents on the hot-corrosion resistance varied depending on the Al and Ti contents. Several commercial alloy compositions were also tested and the corrosion attack was measured. Predicted attack was calculated for these alloys from derived regression equations and was in reasonable agreement with that experimentally measured. The regression equations were derived from measurements made on alloys in a one-quarter replicate of a 2(7) statistical design alloy composition experiment. These regression equations represent a simple linear model and are only a very preliminary analysis of the data needed to provide insights into the experimental method.

Playing spades: The rich resources of African American young men

NASA Astrophysics Data System (ADS)

Schademan, Alfred R.

Research has shown that African American young men as a demographic group occupy the lowest levels of academic performance in both science and mathematics. In spite of this educational problem, little research has been conducted on the knowledge related to these disciplines that these young men learn and develop through everyday cultural practices. Such knowledge is needed in order to: (1) combat the deficit views that many teachers currently hold of African American young men, and (2) inform teachers interested in implementing pedagogies in their classrooms that draw upon the knowledge of African American young men. To add to our knowledge in this field, this study examines the resources that African American young men learn, use, and develop through a card game called Spades. Specifically, the study identifies and analyzes the models and model-based reasoning that the players use in order to win games. The study focuses upon modeling as it is central to both science and mathematics. To imbed player models and reasoning in context, the study employs a syncretic theoretical framework that examines how Spades has changed over time and how it is currently played in a high school setting. The qualitative study uses ethnographic methods combined with play-by-play analyses to reconstruct games and examine player strategies and reasoning that guide their decisions. The study found that the players operate from a number of different models while playing the game. Specifically, the players consider multiple variables and factors, as well as their mathematical relationships, to predict future occurrences and then play cards accordingly. Further, the players use a number of resources to win games including changing the game to maintain a competitive edge, counting cards, selectively memorizing cards played, assessing risk, bluffing, reading partners as well as opponents, reneging, estimating probabilities, and predicting outcomes. The player models and resources bear striking resemblance to what scientists and mathematicians do when modeling. Lastly, the study identifies eight features of Spades that make it a rich context for the learning and development of significant forms of reasoning. Most importantly, Spades is an empowering context through which the players both learn and display their resources and abilities in order to deal with complex situations. Consequently, the study provides evidence that many African American young men routinely employ types of reasoning in everyday practices that are robust and relevant to science and mathematics.

An Analysis of Dust Halo and Extinction Toward X Persei

NASA Technical Reports Server (NTRS)

Valencic, Lynne A.; Smith, Randall K.

2007-01-01

Interstellar dust grain models are not sufficiently constrained by UV extinction curves to be able to distinguish between them. By testing grain models in the X-ray regime and applying elemental abundance constraints, we show to what extent the models can reproduce the observables in these regimes, and if they are capable of doing so while respecting the abundance limits. We tested the MRN and WD grain models. The fits to the X-ray data do not allow us to distinguish between MRN and WD; both models provide reasonable fits, but cannot do so while respecting the elemental abundance constraints. The situation in the UV regime is similar. Both MRN and WD underestimate the hydrogen column density NH. The model of ZDA provides promising results, as it finds NH much closer to the UV-measured value; further testing of this model is called for.

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.

Model Checking Degrees of Belief in a System of Agents

NASA Technical Reports Server (NTRS)

Raimondi, Franco; Primero, Giuseppe; Rungta, Neha

2014-01-01

Reasoning about degrees of belief has been investigated in the past by a number of authors and has a number of practical applications in real life. In this paper we present a unified framework to model and verify degrees of belief in a system of agents. In particular, we describe an extension of the temporal-epistemic logic CTLK and we introduce a semantics based on interpreted systems for this extension. In this way, degrees of beliefs do not need to be provided externally, but can be derived automatically from the possible executions of the system, thereby providing a computationally grounded formalism. We leverage the semantics to (a) construct a model checking algorithm, (b) investigate its complexity, (c) provide a Java implementation of the model checking algorithm, and (d) evaluate our approach using the standard benchmark of the dining cryptographers. Finally, we provide a detailed case study: using our framework and our implementation, we assess and verify the situational awareness of the pilot of Air France 447 flying in off-nominal conditions.

The reasoned/reactive model: A new approach to examining eating decisions among female college dieters and nondieters.

PubMed

Ruhl, Holly; Holub, Shayla C; Dolan, Elaine A

2016-12-01

Female college students are prone to unhealthy eating patterns that can impact long-term health. This study examined female students' healthy and unhealthy eating behaviors with three decision-making models. Specifically, the theory of reasoned action, prototype/willingness model, and new reasoned/reactive model were compared to determine how reasoned (logical) and reactive (impulsive) factors relate to dietary decisions. Females (N=583, M age =20.89years) completed measures on reasoned cognitions about foods (attitudes, subjective norms, nutrition knowledge, intentions to eat foods), reactive cognitions about foods (prototypes, affect, willingness to eat foods), dieting, and food consumption. Structural equation modeling (SEM) revealed the new reasoned/reactive model to be the preeminent model for examining eating behaviors. This model showed that attitudes were related to intentions and willingness to eat healthy and unhealthy foods. Affect was related to willingness to eat healthy and unhealthy foods, whereas nutrition knowledge was related to intentions and willingness to eat healthy foods only. Intentions and willingness were related to healthy and unhealthy food consumption. Dieting status played a moderating role in the model and revealed mean-level differences between dieters and nondieters. This study highlights the importance of specific factors in relation to female students' eating decisions and unveils a comprehensive model for examining health behaviors. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Stanford how things work project

NASA Technical Reports Server (NTRS)

Fikes, Richard; Gruber, Tom; Iwasaki, Yumi

1994-01-01

We provide an overview of the Stanford How Things Work (HTW) project, an ongoing integrated collection of research activities in the Knowledge Systems Laboratory at Stanford University. The project is developing technology for representing knowledge about engineered devices in a form that enables the knowledge to be used in multiple systems for multiple reasoning tasks and reasoning methods that enable the represented knowledge to be effectively applied to the performance of the core engineering task of simulating and analyzing device behavior. The central new capabilities currently being developed in the project are automated assistance with model formulation and with verification that a design for an electro-mechanical device satisfies its functional specification.

An evidential reasoning extension to quantitative model-based failure diagnosis

NASA Technical Reports Server (NTRS)

Gertler, Janos J.; Anderson, Kenneth C.

1992-01-01

The detection and diagnosis of failures in physical systems characterized by continuous-time operation are studied. A quantitative diagnostic methodology has been developed that utilizes the mathematical model of the physical system. On the basis of the latter, diagnostic models are derived each of which comprises a set of orthogonal parity equations. To improve the robustness of the algorithm, several models may be used in parallel, providing potentially incomplete and/or conflicting inferences. Dempster's rule of combination is used to integrate evidence from the different models. The basic probability measures are assigned utilizing quantitative information extracted from the mathematical model and from online computation performed therewith.

Using AberOWL for fast and scalable reasoning over BioPortal ontologies.

PubMed

Slater, Luke; Gkoutos, Georgios V; Schofield, Paul N; Hoehndorf, Robert

2016-08-08

Reasoning over biomedical ontologies using their OWL semantics has traditionally been a challenging task due to the high theoretical complexity of OWL-based automated reasoning. As a consequence, ontology repositories, as well as most other tools utilizing ontologies, either provide access to ontologies without use of automated reasoning, or limit the number of ontologies for which automated reasoning-based access is provided. We apply the AberOWL infrastructure to provide automated reasoning-based access to all accessible and consistent ontologies in BioPortal (368 ontologies). We perform an extensive performance evaluation to determine query times, both for queries of different complexity and for queries that are performed in parallel over the ontologies. We demonstrate that, with the exception of a few ontologies, even complex and parallel queries can now be answered in milliseconds, therefore allowing automated reasoning to be used on a large scale, to run in parallel, and with rapid response times.

The development and psychometric testing of a theory-based instrument to evaluate nurses' perception of clinical reasoning competence.

PubMed

Liou, Shwu-Ru; Liu, Hsiu-Chen; Tsai, Hsiu-Min; Tsai, Ying-Huang; Lin, Yu-Ching; Chang, Chia-Hao; Cheng, Ching-Yu

2016-03-01

The purpose of the study was to develop and psychometrically test the Nurses Clinical Reasoning Scale. Clinical reasoning is an essential skill for providing safe and quality patient care. Identifying pre-graduates' and nurses' needs and designing training courses to improve their clinical reasoning competence becomes a critical task. However, there is no instrument focusing on clinical reasoning in the nursing profession. Cross-sectional design was used. This study included the development of the scale, a pilot study that preliminary tested the readability and reliability of the developed scale and a main study that implemented and tested the psychometric properties of the developed scale. The Nurses Clinical Reasoning Scale was developed based on the Clinical Reasoning Model. The scale includes 15 items using a Likert five-point scale. Data were collected from 2013-2014. Two hundred and fifty-one participants comprising clinical nurses and nursing pre-graduates completed and returned the questionnaires in the main study. The instrument was tested for internal consistency and test-retest reliability. Its validity was tested with content, construct and known-groups validity. One factor emerged from the factor analysis. The known-groups validity was confirmed. The Cronbach's alpha for the entire instrument was 0·9. The reliability and validity of the Nurses Clinical Reasoning Scale were supported. The scale is a useful tool and can be easily administered for the self-assessment of clinical reasoning competence of clinical nurses and future baccalaureate nursing graduates. Study limitations and further recommendations are discussed. © 2015 John Wiley & Sons Ltd.

Development of a VOR/DME model for an advanced concepts simulator

NASA Technical Reports Server (NTRS)

Steinmetz, G. G.; Bowles, R. L.

1984-01-01

The report presents a definition of a VOR/DME, airborne and ground systems simulation model. This description was drafted in response to a need in the creation of an advanced concepts simulation in which flight station design for the 1980 era can be postulated and examined. The simulation model described herein provides a reasonable representation of VOR/DME station in the continental United States including area coverage by type and noise errors. The detail in which the model has been cast provides the interested researcher with a moderate fidelity level simulator tool for conducting research and evaluation of navigator algorithms. Assumptions made within the development are listed and place certain responsibilities (data bases, communication with other simulation modules, uniform round earth, etc.) upon the researcher.

Optimization of levitation and guidance forces in a superconducting Maglev system

NASA Astrophysics Data System (ADS)

Yildizer, Irfan; Cansiz, Ahmet; Ozturk, Kemal

2016-09-01

Optimization of the levitation for superconducting Maglev systems requires effective use of vertical and guidance forces during the operation. In this respect the levitation and guidance forces in terms of various permanent magnet array configurations are analyzed. The arrangements of permanent magnet arrays interacting with the superconductor are configured for the purpose of increasing the magnetic flux density. According to configurations, modeling the interaction forces between the permanent magnet and the superconductor are established in terms of the frozen image model. The model is complemented with the analytical calculations and provides a reasonable agreement with the experiments. The agreement of the analytical calculation associated with the frozen image model indicates a strong case to establish an optimization, in which provides preliminary analysis before constructing more complex Maglev system.

Perception of Risk and Terrorism-Related Behavior Change: Dual Influences of Probabilistic Reasoning and Reality Testing.

PubMed

Denovan, Andrew; Dagnall, Neil; Drinkwater, Kenneth; Parker, Andrew; Clough, Peter

2017-01-01

The present study assessed the degree to which probabilistic reasoning performance and thinking style influenced perception of risk and self-reported levels of terrorism-related behavior change. A sample of 263 respondents, recruited via convenience sampling, completed a series of measures comprising probabilistic reasoning tasks (perception of randomness, base rate, probability, and conjunction fallacy), the Reality Testing subscale of the Inventory of Personality Organization (IPO-RT), the Domain-Specific Risk-Taking Scale, and a terrorism-related behavior change scale. Structural equation modeling examined three progressive models. Firstly, the Independence Model assumed that probabilistic reasoning, perception of risk and reality testing independently predicted terrorism-related behavior change. Secondly, the Mediation Model supposed that probabilistic reasoning and reality testing correlated, and indirectly predicted terrorism-related behavior change through perception of risk. Lastly, the Dual-Influence Model proposed that probabilistic reasoning indirectly predicted terrorism-related behavior change via perception of risk, independent of reality testing. Results indicated that performance on probabilistic reasoning tasks most strongly predicted perception of risk, and preference for an intuitive thinking style (measured by the IPO-RT) best explained terrorism-related behavior change. The combination of perception of risk with probabilistic reasoning ability in the Dual-Influence Model enhanced the predictive power of the analytical-rational route, with conjunction fallacy having a significant indirect effect on terrorism-related behavior change via perception of risk. The Dual-Influence Model possessed superior fit and reported similar predictive relations between intuitive-experiential and analytical-rational routes and terrorism-related behavior change. The discussion critically examines these findings in relation to dual-processing frameworks. This includes considering the limitations of current operationalisations and recommendations for future research that align outcomes and subsequent work more closely to specific dual-process models.

Perception of Risk and Terrorism-Related Behavior Change: Dual Influences of Probabilistic Reasoning and Reality Testing

PubMed Central

Denovan, Andrew; Dagnall, Neil; Drinkwater, Kenneth; Parker, Andrew; Clough, Peter

2017-01-01

The present study assessed the degree to which probabilistic reasoning performance and thinking style influenced perception of risk and self-reported levels of terrorism-related behavior change. A sample of 263 respondents, recruited via convenience sampling, completed a series of measures comprising probabilistic reasoning tasks (perception of randomness, base rate, probability, and conjunction fallacy), the Reality Testing subscale of the Inventory of Personality Organization (IPO-RT), the Domain-Specific Risk-Taking Scale, and a terrorism-related behavior change scale. Structural equation modeling examined three progressive models. Firstly, the Independence Model assumed that probabilistic reasoning, perception of risk and reality testing independently predicted terrorism-related behavior change. Secondly, the Mediation Model supposed that probabilistic reasoning and reality testing correlated, and indirectly predicted terrorism-related behavior change through perception of risk. Lastly, the Dual-Influence Model proposed that probabilistic reasoning indirectly predicted terrorism-related behavior change via perception of risk, independent of reality testing. Results indicated that performance on probabilistic reasoning tasks most strongly predicted perception of risk, and preference for an intuitive thinking style (measured by the IPO-RT) best explained terrorism-related behavior change. The combination of perception of risk with probabilistic reasoning ability in the Dual-Influence Model enhanced the predictive power of the analytical-rational route, with conjunction fallacy having a significant indirect effect on terrorism-related behavior change via perception of risk. The Dual-Influence Model possessed superior fit and reported similar predictive relations between intuitive-experiential and analytical-rational routes and terrorism-related behavior change. The discussion critically examines these findings in relation to dual-processing frameworks. This includes considering the limitations of current operationalisations and recommendations for future research that align outcomes and subsequent work more closely to specific dual-process models. PMID:29062288

Extending pure luminosity evolution models into the mid-infrared, far-infrared and submillimetre

NASA Astrophysics Data System (ADS)

Hill, Michael D.; Shanks, Tom

2011-07-01

Simple pure luminosity evolution (PLE) models, in which galaxies brighten at high redshift due to increased star formation rates (SFRs), are known to provide a good fit to the colours and number counts of galaxies throughout the optical and near-infrared. We show that optically defined PLE models, where dust reradiates absorbed optical light into infrared spectra composed of local galaxy templates, fit galaxy counts and colours out to 8 μm and to at least z≈ 2.5. At 24-70 μm, the model is able to reproduce the observed source counts with reasonable success if 16 per cent of spiral galaxies show an excess in mid-IR flux due to a warmer dust component and a higher SFR, in line with observations of local starburst galaxies. There remains an underprediction of the number of faint-flux, high-z sources at 24 μm, so we explore how the evolution may be altered to correct this. At 160 μm and longer wavelengths, the model fails, with our model of normal galaxies accounting for only a few percent of sources in these bands. However, we show that a PLE model of obscured AGN, which we have previously shown to give a good fit to observations at 850 μm, also provides a reasonable fit to the Herschel/BLAST number counts and redshift distributions at 250-500 μm. In the context of a ΛCDM cosmology, an AGN contribution at 250-870 μm would remove the need to invoke a top-heavy IMF for high-redshift starburst galaxies.

Programmer/Analyst Guide for the Army Unit Resiliency Analysis (AURA) computer Simulation Model. Volume 1. AURA Methodology

DTIC Science & Technology

1990-10-01

involving a heavy artillery barrage, the impact point output alone could consume upwards of 10,000 pages of computer paper. For this reason, AURA provides...but pervasive factor: the asset allocation model must be compatible with the mathematical behavior of the input data. Thus, for example, if assets are...described as expendable during repair or decontamination activities, it must have HOMELINKS which appear in the consuming repair SUBCHAINs

Research and Development Project Priotization. An Annotated Bibliography.

DTIC Science & Technology

1980-04-01

matrix) theory provides the answer in any particular 17 problem. The matrix used is a table to express the number of votes cast for each motion...the majority-rule model and the game model. In 1964, Aumana’s chapter in Shelly and Bryan’s book [187] briefly described ordinal utility ranking...propositions to cast doubt on the existence of Bergson-Samuelson SWFs. They demonstrated that it was impossible to find a "reasonable" Bergson

Twilight reloaded: the peptide experience

PubMed Central

Weichenberger, Christian X.; Pozharski, Edwin; Rupp, Bernhard

2017-01-01

The de facto commoditization of biomolecular crystallography as a result of almost disruptive instrumentation automation and continuing improvement of software allows any sensibly trained structural biologist to conduct crystallo­graphic studies of biomolecules with reasonably valid outcomes: that is, models based on properly interpreted electron density. Robust validation has led to major mistakes in the protein part of structure models becoming rare, but some depositions of protein–peptide complex structure models, which generally carry significant interest to the scientific community, still contain erroneous models of the bound peptide ligand. Here, the protein small-molecule ligand validation tool Twilight is updated to include peptide ligands. (i) The primary technical reasons and potential human factors leading to problems in ligand structure models are presented; (ii) a new method used to score peptide-ligand models is presented; (iii) a few instructive and specific examples, including an electron-density-based analysis of peptide-ligand structures that do not contain any ligands, are discussed in detail; (iv) means to avoid such mistakes and the implications for database integrity are discussed and (v) some suggestions as to how journal editors could help to expunge errors from the Protein Data Bank are provided. PMID:28291756

Twilight reloaded: the peptide experience.

PubMed

Weichenberger, Christian X; Pozharski, Edwin; Rupp, Bernhard

2017-03-01

The de facto commoditization of biomolecular crystallography as a result of almost disruptive instrumentation automation and continuing improvement of software allows any sensibly trained structural biologist to conduct crystallographic studies of biomolecules with reasonably valid outcomes: that is, models based on properly interpreted electron density. Robust validation has led to major mistakes in the protein part of structure models becoming rare, but some depositions of protein-peptide complex structure models, which generally carry significant interest to the scientific community, still contain erroneous models of the bound peptide ligand. Here, the protein small-molecule ligand validation tool Twilight is updated to include peptide ligands. (i) The primary technical reasons and potential human factors leading to problems in ligand structure models are presented; (ii) a new method used to score peptide-ligand models is presented; (iii) a few instructive and specific examples, including an electron-density-based analysis of peptide-ligand structures that do not contain any ligands, are discussed in detail; (iv) means to avoid such mistakes and the implications for database integrity are discussed and (v) some suggestions as to how journal editors could help to expunge errors from the Protein Data Bank are provided.

At the biological modeling and simulation frontier.

PubMed

Hunt, C Anthony; Ropella, Glen E P; Lam, Tai Ning; Tang, Jonathan; Kim, Sean H J; Engelberg, Jesse A; Sheikh-Bahaei, Shahab

2009-11-01

We provide a rationale for and describe examples of synthetic modeling and simulation (M&S) of biological systems. We explain how synthetic methods are distinct from familiar inductive methods. Synthetic M&S is a means to better understand the mechanisms that generate normal and disease-related phenomena observed in research, and how compounds of interest interact with them to alter phenomena. An objective is to build better, working hypotheses of plausible mechanisms. A synthetic model is an extant hypothesis: execution produces an observable mechanism and phenomena. Mobile objects representing compounds carry information enabling components to distinguish between them and react accordingly when different compounds are studied simultaneously. We argue that the familiar inductive approaches contribute to the general inefficiencies being experienced by pharmaceutical R&D, and that use of synthetic approaches accelerates and improves R&D decision-making and thus the drug development process. A reason is that synthetic models encourage and facilitate abductive scientific reasoning, a primary means of knowledge creation and creative cognition. When synthetic models are executed, we observe different aspects of knowledge in action from different perspectives. These models can be tuned to reflect differences in experimental conditions and individuals, making translational research more concrete while moving us closer to personalized medicine.

Explore Care Pathways of Colorectal Cancer Patients with Social Network Analysis.

PubMed

Huo, Tianyao; George, Thomas J; Guo, Yi; He, Zhe; Prosperi, Mattia; Modave, François; Bian, Jiang

2017-01-01

Patients with colorectal cancer (CRC) often face treatment delays and the exact reasons have not been well studied. This study is to explore clinical workflow patterns for CRC patients using electronic health records (EHR). In particular, we modeled the clinical workflow (provider-provider interactions) of a CRC patient's workup period as a social network, and identified clusters of workflow patterns based on network characteristics. Understanding of these patterns will help guide healthcare policy-making and practice.

Dynamic Uncertain Causality Graph for Knowledge Representation and Reasoning: Utilization of Statistical Data and Domain Knowledge in Complex Cases.

PubMed

Zhang, Qin; Yao, Quanying

2018-05-01

The dynamic uncertain causality graph (DUCG) is a newly presented framework for uncertain causality representation and probabilistic reasoning. It has been successfully applied to online fault diagnoses of large, complex industrial systems, and decease diagnoses. This paper extends the DUCG to model more complex cases than what could be previously modeled, e.g., the case in which statistical data are in different groups with or without overlap, and some domain knowledge and actions (new variables with uncertain causalities) are introduced. In other words, this paper proposes to use -mode, -mode, and -mode of the DUCG to model such complex cases and then transform them into either the standard -mode or the standard -mode. In the former situation, if no directed cyclic graph is involved, the transformed result is simply a Bayesian network (BN), and existing inference methods for BNs can be applied. In the latter situation, an inference method based on the DUCG is proposed. Examples are provided to illustrate the methodology.

Using the theory of reasoned action to model retention in rural primary care physicians.

PubMed

Feeley, Thomas Hugh

2003-01-01

Much research attention has focused on medical students', residents', and physicians' decisions to join a rural practice, but far fewer studies have examined retention of rural primary care physicians. The current review uses Fishbein and Ajzen's Theory of Reasoned Action (TRA) to organize the literature on the predictors and correlates of retention of rural practicing physicians. TRA suggests turnover behavior is directly predicted by one's turnover intentions, which are, in turn, predicted by one's attitudes about rural practice and perceptions of salient others' (eg, spouse's) attitudes about rural practice and rural living. Narrative literature review of scholarship in predicting and understanding predictors and correlates of rural physician retention. The TRA model provides a useful conceptual model to organize the literature on rural physician retention. Physicians' subjective norms regarding rural practice are an important source of influence in the decision to remain or leave one's position, and this relation should be more fully examined in future research.

Optical and X-ray radiation from fast pulsars - Effects of duty cycle and spectral shape

NASA Technical Reports Server (NTRS)

Pacini, F.; Salvati, M.

1987-01-01

The optical luminosity of PSR 0540 is considerably stronger than what one would have predicted in a simple model developed earlier where the pulses are synchrotron radiation by secondary electrons near the light cylinder. This discrepancy can be eliminated if one incorporates into the model the effects of the large duty cycle and the spectral properties of PSR 0540. It is also shown that the same model can provide a reasonable fit to the observed X-ray fluxes from fast pulsars.

Effective Potentials for Folding Proteins

NASA Astrophysics Data System (ADS)

Chen, Nan-Yow; Su, Zheng-Yao; Mou, Chung-Yu

2006-02-01

A coarse-grained off-lattice model that is not biased in any way to the native state is proposed to fold proteins. To predict the native structure in a reasonable time, the model has included the essential effects of water in an effective potential. Two new ingredients, the dipole-dipole interaction and the local hydrophobic interaction, are introduced and are shown to be as crucial as the hydrogen bonding. The model allows successful folding of the wild-type sequence of protein G and may have provided important hints to the study of protein folding.

Life Support Baseline Values and Assumptions Document

NASA Technical Reports Server (NTRS)

Anderson, Molly S.; Ewert, Michael K.; Keener, John F.

2018-01-01

The Baseline Values and Assumptions Document (BVAD) provides analysts, modelers, and other life support researchers with a common set of values and assumptions which can be used as a baseline in their studies. This baseline, in turn, provides a common point of origin from which many studies in the community may depart, making research results easier to compare and providing researchers with reasonable values to assume for areas outside their experience. This document identifies many specific physical quantities that define life support systems, serving as a general reference for spacecraft life support system technology developers.

Life Support Baseline Values and Assumptions Document

NASA Technical Reports Server (NTRS)

Anderson, Molly S.; Ewert, Michael K.; Keener, John F.; Wagner, Sandra A.

2015-01-01

The Baseline Values and Assumptions Document (BVAD) provides analysts, modelers, and other life support researchers with a common set of values and assumptions which can be used as a baseline in their studies. This baseline, in turn, provides a common point of origin from which many studies in the community may depart, making research results easier to compare and providing researchers with reasonable values to assume for areas outside their experience. With the ability to accurately compare different technologies' performance for the same function, managers will be able to make better decisions regarding technology development.

Design and usability of heuristic-based deliberation tools for women facing amniocentesis.

PubMed

Durand, Marie-Anne; Wegwarth, Odette; Boivin, Jacky; Elwyn, Glyn

2012-03-01

Evidence suggests that in decision contexts characterized by uncertainty and time constraints (e.g. health-care decisions), fast and frugal decision-making strategies (heuristics) may perform better than complex rules of reasoning. To examine whether it is possible to design deliberation components in decision support interventions using simple models (fast and frugal heuristics). The 'Take The Best' heuristic (i.e. selection of a 'most important reason') and 'The Tallying' integration algorithm (i.e. unitary weighing of pros and cons) were used to develop two deliberation components embedded in a Web-based decision support intervention for women facing amniocentesis testing. Ten researchers (recruited from 15), nine health-care providers (recruited from 28) and ten pregnant women (recruited from 14) who had recently been offered amniocentesis testing appraised evolving versions of 'your most important reason' (Take The Best) and 'weighing it up' (Tallying). Most researchers found the tools useful in facilitating decision making although emphasized the need for simple instructions and clear layouts. Health-care providers however expressed concerns regarding the usability and clarity of the tools. By contrast, 7 out of 10 pregnant women found the tools useful in weighing up the pros and cons of each option, helpful in structuring and clarifying their thoughts and visualizing their decision efforts. Several pregnant women felt that 'weighing it up' and 'your most important reason' were not appropriate when facing such a difficult and emotional decision. Theoretical approaches based on fast and frugal heuristics can be used to develop deliberation tools that provide helpful support to patients facing real-world decisions about amniocentesis. © 2011 Blackwell Publishing Ltd.

Combining human and machine processes (CHAMP)

NASA Astrophysics Data System (ADS)

Sudit, Moises; Sudit, David; Hirsch, Michael

2015-05-01

Machine Reasoning and Intelligence is usually done in a vacuum, without consultation of the ultimate decision-maker. The late consideration of the human cognitive process causes some major problems in the use of automated systems to provide reliable and actionable information that users can trust and depend to make the best Course-of-Action (COA). On the other hand, if automated systems are created exclusively based on human cognition, then there is a danger of developing systems that don't push the barrier of technology and are mainly done for the comfort level of selected subject matter experts (SMEs). Our approach to combining human and machine processes (CHAMP) is based on the notion of developing optimal strategies for where, when, how, and which human intelligence should be injected within a machine reasoning and intelligence process. This combination is based on the criteria of improving the quality of the output of the automated process while maintaining the required computational efficiency for a COA to be actuated in timely fashion. This research addresses the following problem areas: • Providing consistency within a mission: Injection of human reasoning and intelligence within the reliability and temporal needs of a mission to attain situational awareness, impact assessment, and COA development. • Supporting the incorporation of data that is uncertain, incomplete, imprecise and contradictory (UIIC): Development of mathematical models to suggest the insertion of a cognitive process within a machine reasoning and intelligent system so as to minimize UIIC concerns. • Developing systems that include humans in the loop whose performance can be analyzed and understood to provide feedback to the sensors.

Reasoning strategies modulate gender differences in emotion processing.

PubMed

Markovits, Henry; Trémolière, Bastien; Blanchette, Isabelle

2018-01-01

The dual strategy model of reasoning has proposed that people's reasoning can be understood asa combination of two different ways of processing information related to problem premises: a counterexample strategy that examines information for explicit potential counterexamples and a statistical strategy that uses associative access to generate a likelihood estimate of putative conclusions. Previous studies have examined this model in the context of basic conditional reasoning tasks. However, the information processing distinction that underlies the dual strategy model can be seen asa basic description of differences in reasoning (similar to that described by many general dual process models of reasoning). In two studies, we examine how these differences in reasoning strategy may relate to processing very different information, specifically we focus on previously observed gender differences in processing negative emotions. Study 1 examined the intensity of emotional reactions to a film clip inducing primarily negative emotions. Study 2 examined the speed at which participants determine the emotional valence of sequences of negative images. In both studies, no gender differences were observed among participants using a counterexample strategy. Among participants using a statistical strategy, females produce significantly stronger emotional reactions than males (in Study 1) and were faster to recognize the valence of negative images than were males (in Study 2). Results show that the processing distinction underlying the dual strategy model of reasoning generalizes to the processing of emotions. Copyright © 2017 Elsevier B.V. All rights reserved.

Effective strategies for behavior change.

PubMed

Coleman, Mary Thoesen; Pasternak, Ryan H

2012-06-01

Strategies that are most effective in both prevention and management of chronic disease consider factors such as age, ethnicity, community, and technology. Most behavioral change strategies derive their components from application of the health belief model, the theory of reasoned action/theory of planned behavior, transtheoretical model, and social cognitive theory. Many tools such as the readiness ruler and personalized action plan form are available to assist health care teams to facilitate healthy behavior change. Primary care providers can support behavior changes by providing venues for peer interventions and family meetings and by making new partnerships with community organizations. Copyright © 2012 Elsevier Inc. All rights reserved.

Vaccine-associated sarcomas in cats: a unique cancer model.

PubMed

McNiel, E A

2001-01-01

Epidemiologic evidence supports a relationship between vaccination of cats for rabies and feline leukemia virus with the development of soft tissue sarcomas at the site of administration. These tumors are locally invasive and histologically aggressive. As with high-grade soft tissue sarcoma in humans, combination treatment with radiation therapy and surgery provides for optimum tumor control. Feline vaccine-associated sarcoma has become a difficult issue for the veterinary profession for legal, ethical, and clinical reasons. Although most research efforts have focused on therapeutic intervention, this tumor has great potential to provide an informative model for carcinogenesis and genetic susceptibility applicable to cancer in all species, including humans.

Rapid measurement and prediction of bacterial contamination in milk using an oxygen electrode.

PubMed

Numthuam, Sonthaya; Suzuki, Hiroaki; Fukuda, Junji; Phunsiri, Suthiluk; Rungchang, Saowaluk; Satake, Takaaki

2009-03-01

An oxygen electrode was used to measure oxygen consumption to determine bacterial contamination in milk. Dissolved oxygen (DO) measured at 10-35 degrees C for 2 hours provided a reasonable prediction efficiency (r > or = 0.90) of the amount of bacteria between 1.9 and 7.3 log (CFU/mL). A temperature-dependent predictive model was developed that has the same prediction accuracy like the normal predictive model. The analysis performed with and without stirring provided the same prediction efficiency, with correlation coefficient of 0.90. The measurement of DO is a simple and rapid method for the determination of bacteria in milk.

Complex groundwater flow systems as traveling agent models

PubMed Central

Padilla, Pablo; Escolero, Oscar; González, Tomas; Morales-Casique, Eric; Osorio-Olvera, Luis

2014-01-01

Analyzing field data from pumping tests, we show that as with many other natural phenomena, groundwater flow exhibits complex dynamics described by 1/f power spectrum. This result is theoretically studied within an agent perspective. Using a traveling agent model, we prove that this statistical behavior emerges when the medium is complex. Some heuristic reasoning is provided to justify both spatial and dynamic complexity, as the result of the superposition of an infinite number of stochastic processes. Even more, we show that this implies that non-Kolmogorovian probability is needed for its study, and provide a set of new partial differential equations for groundwater flow. PMID:25337455

The Cure for Ailing Self-Service Business Intelligence

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

Burke, Marsha; Simpson, Wayne; Staples, Shad

There are many reasons that self-service models fail. Furthermore, these reasons are directly applicable in the management of self-service business inteligence modeling. Our article expands upon the reasons for failure and suggests how self-service models can be made successful through implementation of a centralized approach to development, testing, implementation and support for the delivery of decision making information.

The Cure for Ailing Self-Service Business Intelligence

DOE PAGES

Burke, Marsha; Simpson, Wayne; Staples, Shad

2016-09-14

There are many reasons that self-service models fail. Furthermore, these reasons are directly applicable in the management of self-service business inteligence modeling. Our article expands upon the reasons for failure and suggests how self-service models can be made successful through implementation of a centralized approach to development, testing, implementation and support for the delivery of decision making information.

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

PubMed

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

2017-12-01

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

Solar EUV irradiance for space weather applications

NASA Astrophysics Data System (ADS)

Viereck, R. A.

2015-12-01

Solar EUV irradiance is an important driver of space weather models. Large changes in EUV and x-ray irradiances create large variability in the ionosphere and thermosphere. Proxies such as the F10.7 cm radio flux, have provided reasonable estimates of the EUV flux but as the space weather models become more accurate and the demands of the customers become more stringent, proxies are no longer adequate. Furthermore, proxies are often provided only on a daily basis and shorter time scales are becoming important. Also, there is a growing need for multi-day forecasts of solar EUV irradiance to drive space weather forecast models. In this presentation we will describe the needs and requirements for solar EUV irradiance information from the space weather modeler's perspective. We will then translate these requirements into solar observational requirements such as spectral resolution and irradiance accuracy. We will also describe the activities at NOAA to provide long-term solar EUV irradiance observations and derived products that are needed for real-time space weather modeling.

78 FR 53448 - Energy Conservation Program for Consumer Products: Decision and Order Granting a Waiver to BSH...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-29

... Secretary of Energy to prescribe test procedures that are reasonably designed to produce results which... conditions is met: (1) The petitioner's basic model contains one or more design characteristics that prevent... to provide materially inaccurate comparative data. (10 CFR 430.27(a)(1)) Petitioners must include in...

77 FR 68752 - Decision and Order Granting a Waiver Granted to Fujitsu General Limited From the Department of...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-16

... prescribe test procedures that are reasonably designed to produce results that measure energy efficiency... one of the following conditions is met: (1) The petitioner's basic model contains one or more design... provide materially inaccurate comparative data. 10 CFR 431.401(a)(1). Petitioners must include in their...

78 FR 57141 - Notice of Petition for Waiver of Samsung Electronics America, Inc. From the Department of Energy...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-17

... authorizes the Secretary of Energy to prescribe test procedures that are reasonably designed to produce... that the basic model for which the petition for waiver was submitted contains one or more design... consumption characteristics as to provide materially inaccurate comparative data. 10 CFR 430.27(l...

76 FR 79666 - Decision and Order Granting a Waiver to LG from the Department of Energy Residential Clothes...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-12-22

... that are reasonably designed to produce results which measure energy efficiency, energy use, or... petitioner's basic model for which the petition for waiver was submitted contains one or more design... characteristics as to provide materially inaccurate comparative data. 10 CFR 430.27(a)(1). Petitioners must...

E-Learning in Secondary Schools in Kenya: A Case of the NEPAD E-Schools

ERIC Educational Resources Information Center

Ayere, Mildred A.; Odera, F. Y.; Agak, J. O.

2010-01-01

The New Partnership for Africa's Development (NEPAD) schools were set up as centres of excellence in Information and Communication Technology (ICT) integration, so that other schools could copy their model in e-learning. It was for this reason that they were provided with computers, e-materials, internet appliances and trained personnel. But to…

Ethical Decision Making: A Teaching and Learning Model for Graduate Students and New Professionals

ERIC Educational Resources Information Center

McDonald, William M.; Ebelhar, Marcus Walker; Orehovec, Elizabeth R.; Sanderson, Robyn H.

2006-01-01

Student affairs practitioners are inundated with a variety of ethical considerations when making day-to-day decisions regarding the welfare of students and colleagues. There is every reason to believe that confronting ethical issues will be an increasingly difficult issue for student affairs professionals in the future. This article provides a…

Score Equating and Item Response Theory: Some Practical Considerations.

ERIC Educational Resources Information Center

Cook, Linda L.; Eignor, Daniel R.

The purposes of this paper are five-fold to discuss: (1) when item response theory (IRT) equating methods should provide better results than traditional methods; (2) which IRT model, the three-parameter logistic or the one-parameter logistic (Rasch), is the most reasonable to use; (3) what unique contributions IRT methods can offer the equating…

12 CFR Appendix A to Part 716 - Model Privacy Form

Code of Federal Regulations, 2012 CFR

2012-01-01

...) with black or other contrasting ink color. Spot color may be used to achieve visual interest, so long...'t share” if it answers “No” in the middle column. Only the sixth row (“For our affiliates to market... provide an opt-out. (6) For our affiliates to market to you. This reason incorporates sharing information...

12 CFR Appendix A to Part 40 - Model Privacy Form

Code of Federal Regulations, 2014 CFR

2014-01-01

...) with black or other contrasting ink color. Spot color may be used to achieve visual interest, so long...'t share” if it answers “No” in the middle column. Only the sixth row (“For our affiliates to market... provide an opt-out. (6) For our affiliates to market to you. This reason incorporates sharing information...

12 CFR Appendix A to Part 573 - Model Privacy Form

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2012-01-01

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Assessing Online Asynchronous Communication Strategies Designed to Enhance Large Student Cohort Engagement and Foster a Community of Learning

ERIC Educational Resources Information Center

Kebble, Paul G.

2017-01-01

With the increasing diversity of pedagogic models of delivery in higher education, universities are continually exploring practises of learning and teaching designed to enhance student experience and retention. The number of courses provided online continues to grow through, among other reasons, an escalation of higher education (HE) students…

Science Thought and Practices: A Professional Development Workshop on Teaching Scientific Reasoning, Mathematical Modeling and Data Analysis

NASA Astrophysics Data System (ADS)

Robbins, Dennis; Ford, K. E. Saavik

2018-01-01

The NSF-supported “AstroCom NYC” program, a collaboration of the City University of New York and the American Museum of Natural History (AMNH), has developed and offers hands-on workshops to undergraduate faculty on teaching science thought and practices. These professional development workshops emphasize a curriculum and pedagogical strategies that uses computers and other digital devices in a laboratory environment to teach students fundamental topics, including: proportional reasoning, control of variables thinking, experimental design, hypothesis testing, reasoning with data, and drawing conclusions from graphical displays. Topics addressed here are rarely taught in-depth during the formal undergraduate years and are frequently learned only after several apprenticeship research experiences. The goal of these workshops is to provide working and future faculty with an interactive experience in science learning and teaching using modern technological tools.

An exercise to teach quantitative analysis and modeling using Excel-based analysis of the carbon cycle in the anthropocene

NASA Astrophysics Data System (ADS)

Stoll, Heather

2013-04-01

A computer modeling exercise was created to allows students to investigate the consequences of fossil fuel burning and land use change on the amount of carbon dioxide in the atmosphere. Students work with a simple numerical model of the carbon cycle which is rendered in Excel, and conduct a set of different sensitivity tests with different amounts and rate of C additions, and then graph and discuss their results. In the recommended approach, the model is provided to students without the biosphere and in class the formulas to integrate this module are typed into Excel simultaneously by instructor and students, helping students understand how the larger model is set up. In terms of content, students learn to recognize the redistribution of fossil fuel carbon between the ocean and atmosphere, and distinguish the consequences of rapid vs slow rates of addition of fossil fuel CO2 and the reasons for this difference. Students become familiar with the use of formulas in Excel and working with a large (300 rows, 20 columns) worksheet and gain competence in graphical representation of multiple scenarios. Students learn to appreciate the power and limitations of numerical models of complex cycles, the concept of inverse and forward models, and sensitivity tests. Finally, students learn that a reasonable hypothesis, may be "reasonable" but still not quantitatively sufficient - in this case, that the "Industrial Revolution" was not the source of increasing atmospheric CO2 from 1750-1900. The described activity is available to educators on the Teach the Earth portal of the Science Education Research Center (SERC) http://serc.carleton.edu/quantskills/activities/68751.html.

The probability heuristics model of syllogistic reasoning.

PubMed

Chater, N; Oaksford, M

1999-03-01

A probability heuristic model (PHM) for syllogistic reasoning is proposed. An informational ordering over quantified statements suggests simple probability based heuristics for syllogistic reasoning. The most important is the "min-heuristic": choose the type of the least informative premise as the type of the conclusion. The rationality of this heuristic is confirmed by an analysis of the probabilistic validity of syllogistic reasoning which treats logical inference as a limiting case of probabilistic inference. A meta-analysis of past experiments reveals close fits with PHM. PHM also compares favorably with alternative accounts, including mental logics, mental models, and deduction as verbal reasoning. Crucially, PHM extends naturally to generalized quantifiers, such as Most and Few, which have not been characterized logically and are, consequently, beyond the scope of current mental logic and mental model theories. Two experiments confirm the novel predictions of PHM when generalized quantifiers are used in syllogistic arguments. PHM suggests that syllogistic reasoning performance may be determined by simple but rational informational strategies justified by probability theory rather than by logic. Copyright 1999 Academic Press.

Reasons why specialist doctors undertake rural outreach services: an Australian cross-sectional study.

PubMed

O'Sullivan, Belinda G; McGrail, Matthew R; Stoelwinder, Johannes U

2017-01-07

The purpose of the study is to explore the reasons why specialist doctors travel to provide regular rural outreach services, and whether reasons relate to (1) salaried or private fee-for-service practice and (2) providing rural outreach services in more remote locations. A national cross-sectional study of specialist doctors from the Medicine in Australia: Balancing Employment and Life (MABEL) survey in 2014 was implemented. Specialists providing rural outreach services self-reported on a 5-point scale their level of agreement with five reasons for participating. Chi-squared analysis tested association between agreement and variables of interest. Of 567 specialists undertaking rural outreach services, reasons for participating include to grow the practice (54%), maintain a regional connection (26%), provide complex healthcare (18%), healthcare for disadvantaged people (12%) and support rural staff (6%). Salaried specialists more commonly participated to grow the practice compared with specialists in fee-for-service practice (68 vs 49%). This reason was also related to travelling further and providing outreach services in outer regional/remote locations. Private fee-for-service specialists more commonly undertook outreach services to provide complex healthcare (22 vs 14%). Specialist doctors undertake rural outreach services for a range of reasons, mainly to complement the growth and diversity of their main practice or maintain a regional connection. Structuring rural outreach around the specialist's main practice is likely to support participation and improve service distribution.

Socio-economic exposure to natural disasters

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

Marin, Giovanni, E-mail: giovanni.marin@uniurb.it; IRCrES - CNR, Research Institute on Sustainable Economic Growth, Via Corti 12, 20133 - Milano; SEEDS, Ferrara

Even though the correct assessment of risks is a key aspect of the risk management analysis, we argue that limited effort has been devoted in the assessment of comprehensive measures of economic exposure at very low scale. For this reason, we aim at providing a series of suitable methodologies to provide a complete and detailed list of the exposure of economic activities to natural disasters. We use Input-Output models to provide information about several socio-economic variables, such as population density, employment density, firms' turnover and capital stock, that can be seen as direct and indirect socio-economic exposure to natural disasters.more » We then provide an application to the Italian context. These measures can be easily incorporated into risk assessment models to provide a clear picture of the disaster risk for local areas. - Highlights: • Ex ante assessment of economic exposure to disasters at very low geographical scale • Assessment of the cost of natural disasters in ex-post perspective • IO model and spatial autocorrelation to get information on socio-economic variables • Indicators supporting risk assessment and risk management models.« less

Effects of heat exchanger tubes on hydrodynamics and CO 2 capture of a sorbent-based fluidized bed reactor

DOE PAGES

Lai, Canhai; Xu, Zhijie; Li, Tingwen; ...

2017-08-05

In virtual design and scale up of pilot-scale carbon capture systems, the coupled reactive multiphase flow problem must be solved to predict the adsorber's performance and capture efficiency under various operation conditions. This paper focuses on the detailed computational fluid dynamics (CFD) modeling of a pilot-scale fluidized bed adsorber equipped with vertical cooling tubes. Multiphase Flow with Interphase eXchanges (MFiX), an open-source multiphase flow CFD solver, is used for the simulations with custom code to simulate the chemical reactions and filtered sub-grid models to capture the effect of the unresolved details in the coarser mesh for simulations with reasonable accuracymore » and manageable computational effort. Previously developed filtered models for horizontal cylinder drag, heat transfer, and reaction kinetics have been modified to derive the 2D filtered models representing vertical cylinders in the coarse-grid CFD simulations. The effects of the heat exchanger configurations (i.e., horizontal or vertical tubes) on the adsorber's hydrodynamics and CO 2 capture performance are then examined. A one-dimensional three-region process model is briefly introduced for comparison purpose. The CFD model matches reasonably well with the process model while provides additional information about the flow field that is not available with the process model.« less

Knowledge representation to support reasoning based on multiple models

NASA Technical Reports Server (NTRS)

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

1990-01-01

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

Recent Updates to the Arnold Mirror Modeler and Integration into the Evolving NASA Overall Design System for Large Space-Based Optical Systems

NASA Technical Reports Server (NTRS)

Arnold, William R.

2015-01-01

Since last year, a number of expanded capabilities have been added to the modeler. The support the integration with thermal modeling, the program can now produce simplified thermal models with the same geometric parameters as the more detailed dynamic and even more refined stress models. The local mesh refinement and mesh improvement tools have been expanded and more user friendly. The goal is to provide a means of evaluating both monolithic and segmented mirrors to the same level of fidelity and loading conditions at reasonable man-power efforts. The paper will demonstrate most of these new capabilities.

Recent Updates to the Arnold Mirror Modeler and Integration into the Evolving NASA Overall Design System for Large Space Based Optical Systems

NASA Technical Reports Server (NTRS)

Arnold, William R., Sr.

2015-01-01

Since last year, a number of expanded capabilities have been added to the modeler. The support the integration with thermal modeling, the program can now produce simplified thermal models with the same geometric parameters as the more detailed dynamic and even more refined stress models. The local mesh refinement and mesh improvement tools have been expanded and more user friendly. The goal is to provide a means of evaluating both monolithic and segmented mirrors to the same level of fidelity and loading conditions at reasonable man-power efforts. The paper will demonstrate most of these new capabilities.

Maximum likelihood estimation of finite mixture model for economic data

NASA Astrophysics Data System (ADS)

Phoong, Seuk-Yen; Ismail, Mohd Tahir

2014-06-01

Finite mixture model is a mixture model with finite-dimension. This models are provides a natural representation of heterogeneity in a finite number of latent classes. In addition, finite mixture models also known as latent class models or unsupervised learning models. Recently, maximum likelihood estimation fitted finite mixture models has greatly drawn statistician's attention. The main reason is because maximum likelihood estimation is a powerful statistical method which provides consistent findings as the sample sizes increases to infinity. Thus, the application of maximum likelihood estimation is used to fit finite mixture model in the present paper in order to explore the relationship between nonlinear economic data. In this paper, a two-component normal mixture model is fitted by maximum likelihood estimation in order to investigate the relationship among stock market price and rubber price for sampled countries. Results described that there is a negative effect among rubber price and stock market price for Malaysia, Thailand, Philippines and Indonesia.

Geometric Reasoning in an Active-Engagement Upper-Division E&M Classroom

NASA Astrophysics Data System (ADS)

Cerny, Leonard Thomas

A combination of theoretical perspectives is used to create a rich description of student reasoning when facing a highly-geometric electricity and magnetism problem in an upper-division active-engagement physics classroom at Oregon State University. Geometric reasoning as students encounter problem situations ranging from familiar to novel is described using van Zee and Manogue's (2010) ethnography of communication. Bing's (2008) epistemic framing model is used to illuminate how students are framing what they are doing and whether or not they see the problem as geometric. Kuo, Hull, Gupta, and Elby's (2010) blending model and Krutetskii's (1976) model of harmonic reasoning are used to illuminate ways students show problem-solving expertise. Sayer and Wittmann's (2008) model is used to show how resource plasticity impacts students' geometric reasoning and the degree to which students accept incorrect results.

Maximizing the nurses' preferences in nurse scheduling problem: mathematical modeling and a meta-heuristic algorithm

NASA Astrophysics Data System (ADS)

Jafari, Hamed; Salmasi, Nasser

2015-09-01

The nurse scheduling problem (NSP) has received a great amount of attention in recent years. In the NSP, the goal is to assign shifts to the nurses in order to satisfy the hospital's demand during the planning horizon by considering different objective functions. In this research, we focus on maximizing the nurses' preferences for working shifts and weekends off by considering several important factors such as hospital's policies, labor laws, governmental regulations, and the status of nurses at the end of the previous planning horizon in one of the largest hospitals in Iran i.e., Milad Hospital. Due to the shortage of available nurses, at first, the minimum total number of required nurses is determined. Then, a mathematical programming model is proposed to solve the problem optimally. Since the proposed research problem is NP-hard, a meta-heuristic algorithm based on simulated annealing (SA) is applied to heuristically solve the problem in a reasonable time. An initial feasible solution generator and several novel neighborhood structures are applied to enhance performance of the SA algorithm. Inspired from our observations in Milad hospital, random test problems are generated to evaluate the performance of the SA algorithm. The results of computational experiments indicate that the applied SA algorithm provides solutions with average percentage gap of 5.49 % compared to the upper bounds obtained from the mathematical model. Moreover, the applied SA algorithm provides significantly better solutions in a reasonable time than the schedules provided by the head nurses.

A Film Depositional Model of Permeability for Mineral Reactions in Unsaturated Media.

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

Freedman, Vicky L.; Saripalli, Prasad; Bacon, Diana H.

2004-11-15

A new modeling approach based on the biofilm models of Taylor et al. (1990, Water Resources Research, 26, 2153-2159) has been developed for modeling changes in porosity and permeability in saturated porous media and implemented in an inorganic reactive transport code. Application of the film depositional models to mineral precipitation and dissolution reactions requires that calculations of mineral films be dynamically changing as a function of time dependent reaction processes. Since calculations of film thicknesses do not consider mineral density, results show that the film porosity model does not adequately describe volumetric changes in the porous medium. These effects canmore » be included in permeability calculations by coupling the film permeability models (Mualem and Childs and Collis-George) to a volumetric model that incorporates both mineral density and reactive surface area. Model simulations demonstrate that an important difference between the biofilm and mineral film models is in the translation of changes in mineral radii to changes in pore space. Including the effect of tortuosity on pore radii changes improves the performance of the Mualem permeability model for both precipitation and dissolution. Results from simulation of simultaneous dissolution and secondary mineral precipitation provides reasonable estimates of porosity and permeability. Moreover, a comparison of experimental and simulated data show that the model yields qualitatively reasonable results for permeability changes due to solid-aqueous phase reactions.« less

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.

Intuitive Logic Revisited: New Data and a Bayesian Mixed Model Meta-Analysis

PubMed Central

Singmann, Henrik; Klauer, Karl Christoph; Kellen, David

2014-01-01

Recent research on syllogistic reasoning suggests that the logical status (valid vs. invalid) of even difficult syllogisms can be intuitively detected via differences in conceptual fluency between logically valid and invalid syllogisms when participants are asked to rate how much they like a conclusion following from a syllogism (Morsanyi & Handley, 2012). These claims of an intuitive logic are at odds with most theories on syllogistic reasoning which posit that detecting the logical status of difficult syllogisms requires effortful and deliberate cognitive processes. We present new data replicating the effects reported by Morsanyi and Handley, but show that this effect is eliminated when controlling for a possible confound in terms of conclusion content. Additionally, we reanalyze three studies () without this confound with a Bayesian mixed model meta-analysis (i.e., controlling for participant and item effects) which provides evidence for the null-hypothesis and against Morsanyi and Handley's claim. PMID:24755777

A dynamic access control method based on QoS requirement

NASA Astrophysics Data System (ADS)

Li, Chunquan; Wang, Yanwei; Yang, Baoye; Hu, Chunyang

2013-03-01

A dynamic access control method is put forward to ensure the security of the sharing service in Cloud Manufacturing, according to the application characteristics of cloud manufacturing collaborative task. The role-based access control (RBAC) model is extended according to the characteristics of cloud manufacturing in this method. The constraints are considered, which are from QoS requirement of the task context to access control, based on the traditional static authorization. The fuzzy policy rules are established about the weighted interval value of permissions. The access control authorities of executable service by users are dynamically adjusted through the fuzzy reasoning based on the QoS requirement of task. The main elements of the model are described. The fuzzy reasoning algorithm of weighted interval value based QoS requirement is studied. An effective method is provided to resolve the access control of cloud manufacturing.

Investigation of automated task learning, decomposition and scheduling

NASA Technical Reports Server (NTRS)

Livingston, David L.; Serpen, Gursel; Masti, Chandrashekar L.

1990-01-01

The details and results of research conducted in the application of neural networks to task planning and decomposition are presented. Task planning and decomposition are operations that humans perform in a reasonably efficient manner. Without the use of good heuristics and usually much human interaction, automatic planners and decomposers generally do not perform well due to the intractable nature of the problems under consideration. The human-like performance of neural networks has shown promise for generating acceptable solutions to intractable problems such as planning and decomposition. This was the primary reasoning behind attempting the study. The basis for the work is the use of state machines to model tasks. State machine models provide a useful means for examining the structure of tasks since many formal techniques have been developed for their analysis and synthesis. It is the approach to integrate the strong algebraic foundations of state machines with the heretofore trial-and-error approach to neural network synthesis.

Inverse magnetic catalysis from improved holographic QCD in the Veneziano limit

NASA Astrophysics Data System (ADS)

Gürsoy, Umut; Iatrakis, Ioannis; Järvinen, Matti; Nijs, Govert

2017-03-01

We study the dependence of the chiral condensate on external magnetic field in the context of holographic QCD at large number of flavors. We consider a holographic QCD model where the flavor degrees of freedom fully backreact on the color dynamics. Perturbative QCD calculations have shown that B acts constructively on the chiral condensate, a phenomenon called "magnetic catalysis". In contrast, recent lattice calculations show that, depending on the number of flavors and temperature, the magnetic field may also act destructively, which is called "inverse magnetic catalysis". Here we show that the holographic theory is capable of both behaviors depending on the choice of parameters. For reasonable choice of the potentials entering the model we find qualitative agreement with the lattice expectations. Our results provide insight for the physical reasons behind the inverse magnetic catalysis. In particular, we argue that the backreaction of the flavors to the background geometry decatalyzes the condensate.

The importance of an ethics curriculum in surgical education.

PubMed

Keune, Jason D; Kodner, Ira J

2014-07-01

The nature of surgical work provides fertile ground in which ethical problems can grow. The concept of what it means to be a "good surgeon" includes the ability to reason and deliberate about how the surgeon's unique technical capabilities integrate with larger society. Ethics education at the resident level is important for several reasons. It can ensure that care is delivered in a socially and ethically responsible manner through global and emergent effects on institutions and traditions. It will prepare residents for leadership positions. It can allow residents to confront issues, such as the scientific underdetermination of surgical practice, the application of new technologies to trusting patients that have been developed by for-profit companies, and a surgical environment that is becoming increasingly institutionalized. Resident ethics education provides the opportunity for a model of collective deliberation to be developed that can be used to make sense of ethical problems as they arise.

The Probability Heuristics Model of Syllogistic Reasoning.

ERIC Educational Resources Information Center

Chater, Nick; Oaksford, Mike

1999-01-01

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

Intentions of Chiropractic Interns Regarding use of Health Promotion in Practice: Applying Theory of Reasoned Action to Identify Attitudes, Beliefs, and Influencing Factors

PubMed Central

Evans, Marion W.; Ndetan, Harrison; Williams, Ronald D.

2009-01-01

Purpose: The theory of reasoned action is a health behavioral theory that has been used to predict personal health behaviors and intentions as well as those of providers delivering health care. The purpose of this study was to determine interns' future practices regarding the use of health promotion using this model to develop survey questions and to determine attitudes and perceived influences on their prospective behaviors in general, toward the use of health promotion once in practice. Methods: Across the course of one year, all graduating interns at a chiropractic college were queried with a 20 question survey designed using the theory of reasoned action. Frequencies and inferential statistics were performed including prediction modeling using logistic regression. Results: A majority (>85%) of interns indicated they would use health promotion in practice. Differences were noted based on perceived skill levels, perception of educational emphasis, various normative beliefs, and gender. Conclusion: Most interns will use some form of health promotion in practice. Normative influences including those seen as key influencers are as powerful a predictor as perceived education or skill levels on future practice of health promotion. PMID:19390679

Intentions of Chiropractic Interns Regarding use of Health Promotion in Practice: Applying Theory of Reasoned Action to Identify Attitudes, Beliefs, and Influencing Factors.

PubMed

Evans, Marion W; Ndetan, Harrison; Williams, Ronald D

2009-01-01

The theory of reasoned action is a health behavioral theory that has been used to predict personal health behaviors and intentions as well as those of providers delivering health care. The purpose of this study was to determine interns' future practices regarding the use of health promotion using this model to develop survey questions and to determine attitudes and perceived influences on their prospective behaviors in general, toward the use of health promotion once in practice. Across the course of one year, all graduating interns at a chiropractic college were queried with a 20 question survey designed using the theory of reasoned action. Frequencies and inferential statistics were performed including prediction modeling using logistic regression. A majority (>85%) of interns indicated they would use health promotion in practice. Differences were noted based on perceived skill levels, perception of educational emphasis, various normative beliefs, and gender. Most interns will use some form of health promotion in practice. Normative influences including those seen as key influencers are as powerful a predictor as perceived education or skill levels on future practice of health promotion.

Peer teaching in medical education: twelve reasons to move from theory to practice.

PubMed

Ten Cate, Olle; Durning, Steven

2007-09-01

To provide an estimation of how often peer teaching is applied in medical education, based on reports in the literature and to summarize reasons that support the use of this form of teaching. We surveyed the 2006 medical education literature and categorised reports of peer teaching according to educational distance between students teaching and students taught, group size, and level of formality of the teaching. Subsequently, we analysed the rationales for applying peer teaching. Most reports were published abstracts in either Medical Education's annual feature 'Really Good Stuff' or the AMEE's annual conference proceedings. We identified twelve distinct reasons to apply peer teaching, including 'alleviating faculty teaching burden', 'providing role models for junior students', 'enhancing intrinsic motivation' and 'preparing physicians for their future role as educators'. Peer teaching appears to be practiced often, but many peer teaching reports do not become full length journal articles. We conclude that specifically 'near-peer teaching' appears beneficial for student teachers and learners as well as for the organisation. The analogy of the 'journeyman', as intermediate between 'apprentice' and 'master', with both learning and teaching tasks, is a valuable but yet under-recognized source of education in the medical education continuum.

Reducing a Knowledge-Base Search Space When Data Are Missing

NASA Technical Reports Server (NTRS)

James, Mark

2007-01-01

This software addresses the problem of how to efficiently execute a knowledge base in the presence of missing data. Computationally, this is an exponentially expensive operation that without heuristics generates a search space of 1 + 2n possible scenarios, where n is the number of rules in the knowledge base. Even for a knowledge base of the most modest size, say 16 rules, it would produce 65,537 possible scenarios. The purpose of this software is to reduce the complexity of this operation to a more manageable size. The problem that this system solves is to develop an automated approach that can reason in the presence of missing data. This is a meta-reasoning capability that repeatedly calls a diagnostic engine/model to provide prognoses and prognosis tracking. In the big picture, the scenario generator takes as its input the current state of a system, including probabilistic information from Data Forecasting. Using model-based reasoning techniques, it returns an ordered list of fault scenarios that could be generated from the current state, i.e., the plausible future failure modes of the system as it presently stands. The scenario generator models a Potential Fault Scenario (PFS) as a black box, the input of which is a set of states tagged with priorities and the output of which is one or more potential fault scenarios tagged by a confidence factor. The results from the system are used by a model-based diagnostician to predict the future health of the monitored system.

Software Safety Analysis of a Flight Guidance System

NASA Technical Reports Server (NTRS)

Butler, Ricky W. (Technical Monitor); Tribble, Alan C.; Miller, Steven P.; Lempia, David L.

2004-01-01

This document summarizes the safety analysis performed on a Flight Guidance System (FGS) requirements model. In particular, the safety properties desired of the FGS model are identified and the presence of the safety properties in the model is formally verified. Chapter 1 provides an introduction to the entire project, while Chapter 2 gives a brief overview of the problem domain, the nature of accidents, model based development, and the four-variable model. Chapter 3 outlines the approach. Chapter 4 presents the results of the traditional safety analysis techniques and illustrates how the hazardous conditions associated with the system trace into specific safety properties. Chapter 5 presents the results of the formal methods analysis technique model checking that was used to verify the presence of the safety properties in the requirements model. Finally, Chapter 6 summarizes the main conclusions of the study, first and foremost that model checking is a very effective verification technique to use on discrete models with reasonable state spaces. Additional supporting details are provided in the appendices.

Modeling drug release from functionalized magnetic nanoparticles actuated by non-heating low frequency magnetic field

NASA Astrophysics Data System (ADS)

Golovin, Y.; Golovin, D.; Klyachko, N.; Majouga, A.; Kabanov, A.

2017-02-01

Various plausible acceleration mechanisms of drug release from nanocarriers composed of a single-domain magnetic nanoparticle core with attached long macromolecule chains activated by low frequency non-heating alternating magnetic field (AMF) are discussed. The most important system characteristics affecting the AMF exposure impact are determined. Impact of several reasonable mechanisms is estimated analytically or obtained using numerical modeling. Some conditions providing manifold release acceleration as a result from exposure in AMF are found.

Toward a Greater Understanding of the Reduction of Drift Coefficients in the Presence of Turbulence

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

Engelbrecht, N. E.; Strauss, R. D.; Burger, R. A.

2017-06-01

Drift effects play a significant role in the transport of charged particles in the heliosphere. A turbulent magnetic field is also known to reduce the effects of particle drifts. The exact nature of this reduction, however, is not clear. This study aims to provide some insight into this reduction and proposes a relatively simple, tractable means of modeling it that provides results in reasonable agreement with numerical simulations of the drift coefficient in a turbulent magnetic field.

Symbolic Processing Combined with Model-Based Reasoning

NASA Technical Reports Server (NTRS)

James, Mark

2009-01-01

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

Health, Supportive Environments, and the Reasonable Person Model

Treesearch

Stephen Kaplan; Rachel Kaplan

2003-01-01

The Reasonable Person Model is a conceptual framework that links environmental factors with human behavior. People are more reasonable, cooperative, helpful, and satisfied when the environment supports their basic informational needs. The same environmental supports are important factors in enhancing human health. We use this framework to identify the informational...

The justificatory power of moral experience.

PubMed

van Thiel, G J M W; van Delden, J J M

2009-04-01

A recurrent issue in the vast amount of literature on reasoning models in ethics is the role and nature of moral intuitions. In this paper, we start from the view that people who work and live in a certain moral practice usually possess specific moral wisdom. If we manage to incorporate their moral intuitions in ethical reasoning, we can arrive at judgements and (modest) theories that grasp a moral experience that generally cannot be found outside the practice. Reflective equilibrium (RE) provides a framework for balancing moral intuitions, ethical principles and general theories. Nevertheless, persisting problems associated with the use of intuitions need to be addressed. One is the objection that moral intuitions lack the credibility necessary to guide moral reasoning. Ethicists have tried to solve this problem by formulating criteria to separate the "bad" intuitions from the "good" ones at the beginning of the reasoning process. We call this the credible input-justified outcome strategy. An example is the appeal to the common morality by Beauchamp and Childress. We think this approach is unsuccessful. As an alternative, we outline the good reasoning-justified outcome strategy. It connects to a variant of RE in which intuitions from different sources are incorporated. We argue that the elements of RE have different levels of justificatory power at the start of reasoning. In our strategy, each element can gain or lose justificatory power when it is tested in a reasoning process that meets several criteria.

Reasons U.S. women have abortions: quantitative and qualitative perspectives.

PubMed

Finer, Lawrence B; Frohwirth, Lori F; Dauphinee, Lindsay A; Singh, Susheela; Moore, Ann M

2005-09-01

Understanding women's reasons for having abortions can inform public debate and policy regarding abortion and unwanted pregnancy. Demographic changes over the last two decades highlight the need for a reassessment of why women decide to have abortions. In 2004, a structured survey was completed by 1,209 abortion patients at 11 large providers, and in-depth interviews were conducted with 38 women at four sites. Bivariate analyses examined differences in the reasons for abortion across subgroups, and multivariate logistic regression models assessed associations between respondent characteristics and reported reasons. The reasons most frequently cited were that having a child would interfere with a woman's education, work or ability to care for dependents (74%); that she could not afford a baby now (73%); and that she did not want to be a single mother or was having relationship problems (48%). Nearly four in 10 women said they had completed their childbearing, and almost one-third were not ready to have a child. Fewer than 1% said their parents' or partners' desire for them to have an abortion was the most important reason. Younger women often reported that they were unprepared for the transition to motherhood, while older women regularly cited their responsibility to dependents. The decision to have an abortion is typically motivated by multiple, diverse and interrelated reasons. The themes of responsibility to others and resource limitations, such as financial constraints and lack of partner support, recurred throughout the study.

76 FR 21237 - Medical Devices; Obstetrical and Gynecological Devices; Classification of the Hemorrhoid...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-15

... reasonable assurance of safety and effectiveness of the device. A hemorrhoid prevention pressure wedge... provide reasonable assurance of safety and effectiveness, but there is sufficient information to establish special controls to provide reasonable assurance of the safety and effectiveness of the device for its...

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

PubMed

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

2018-03-01

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

The use of the bi-factor model to test the uni-dimensionality of a battery of reasoning tests.

PubMed

Primi, Ricardo; Rocha da Silva, Marjorie Cristina; Rodrigues, Priscila; Muniz, Monalisa; Almeida, Leandro S

2013-02-01

The Battery of Reasoning Tests 5 (BPR-5) aims to assess the reasoning ability of individuals, using sub-tests with different formats and contents that require basic processes of inductive and deductive reasoning for their resolution. The BPR has three sequential forms: BPR-5i (for children from first to fifth grade), BPR-5 - Form A (for children from sixth to eighth grade) and BPR-5 - form B (for high school and undergraduate students). The present study analysed 412 questionnaires concerning BPR-5i, 603 questionnaires concerning BPR-5 - Form A and 1748 questionnaires concerning BPR-5 - Form B. The main goal was to test the uni-dimensionality of the battery and its tests in relation to items using the bi-factor model. Results suggest that the g factor loadings (extracted by the uni-dimensional model) do not change when the data is adjusted for a more flexible multi-factor model (bi-factor model). A general reasoning factor underlying different contents items is supported.

Comparison of Data on Mutation Frequencies of Mice Caused by Radiation with Low Dose Model

NASA Astrophysics Data System (ADS)

Manabe, Yuichiro; Bando, Masako

2013-09-01

We propose low dose (LD) model, the extension of LDM model which was proposed in the previous paper [Y. Manabe et al.: J. Phys. Soc. Jpn. 81 (2012) 104004] to estimate biological damage caused by irradiation. LD model takes account of cell death effect in addition to the proliferation, apoptosis, repair which were included in LDM model. As a typical example of estimation, we apply LD model to the experiment of mutation frequency on the responses induced by the exposure to low levels of ionizing radiation. The most famous and extensive experiments are those summarized by Russell and Kelly [Proc. Natl. Acad. Sci. U.S.A. 79 (1982) 539], which are known as ``mega-mouse project''. This provides us with important information of the frequencies of transmitted specific-locus mutations induced in mouse spermatogonia stem-cells. It is found that the numerical results of the mutation frequency of mice are in reasonable agreement with the experimental data: the LD model reproduces the total dose and dose rate dependence of data reasonably. In order to see such dose-rate dependence more explicitly, we introduce the dose-rate effectiveness factor (DREF). This represents a sort of dose rate dependent effect, which are to be competitive with proliferation effect of broken cells induced by irradiation.

Immobile Robots: AI in the New Millennium

NASA Technical Reports Server (NTRS)

Williams, Brian C.; Nayak, P. Pandurang

1996-01-01

A new generation of sensor rich, massively distributed, autonomous systems are being developed that have the potential for profound social, environmental, and economic change. These include networked building energy systems, autonomous space probes, chemical plant control systems, satellite constellations for remote ecosystem monitoring, power grids, biosphere-like life support systems, and reconfigurable traffic systems, to highlight but a few. To achieve high performance, these immobile robots (or immobots) will need to develop sophisticated regulatory and immune systems that accurately and robustly control their complex internal functions. To accomplish this, immobots will exploit a vast nervous system of sensors to model themselves and their environment on a grand scale. They will use these models to dramatically reconfigure themselves in order to survive decades of autonomous operations. Achieving these large scale modeling and configuration tasks will require a tight coupling between the higher level coordination function provided by symbolic reasoning, and the lower level autonomic processes of adaptive estimation and control. To be economically viable they will need to be programmable purely through high level compositional models. Self modeling and self configuration, coordinating autonomic functions through symbolic reasoning, and compositional, model-based programming are the three key elements of a model-based autonomous systems architecture that is taking us into the New Millennium.

Verification of Orthogrid Finite Element Modeling Techniques

NASA Technical Reports Server (NTRS)

Steeve, B. E.

1996-01-01

The stress analysis of orthogrid structures, specifically with I-beam sections, is regularly performed using finite elements. Various modeling techniques are often used to simplify the modeling process but still adequately capture the actual hardware behavior. The accuracy of such 'Oshort cutso' is sometimes in question. This report compares three modeling techniques to actual test results from a loaded orthogrid panel. The finite element models include a beam, shell, and mixed beam and shell element model. Results show that the shell element model performs the best, but that the simpler beam and beam and shell element models provide reasonable to conservative results for a stress analysis. When deflection and stiffness is critical, it is important to capture the effect of the orthogrid nodes in the model.

Seasonal variability of atmospheric tides in the mesosphere and lower thermosphere: meteor radar data and simulations

NASA Astrophysics Data System (ADS)

Pokhotelov, Dimitry; Becker, Erich; Stober, Gunter; Chau, Jorge L.

2018-06-01

Thermal tides play an important role in the global atmospheric dynamics and provide a key mechanism for the forcing of thermosphere-ionosphere dynamics from below. A method for extracting tidal contributions, based on the adaptive filtering, is applied to analyse multi-year observations of mesospheric winds from ground-based meteor radars located in northern Germany and Norway. The observed seasonal variability of tides is compared to simulations with the Kühlungsborn Mechanistic Circulation Model (KMCM). It is demonstrated that the model provides reasonable representation of the tidal amplitudes, though substantial differences from observations are also noticed. The limitations of applying a conventionally coarse-resolution model in combination with parametrisation of gravity waves are discussed. The work is aimed towards the development of an ionospheric model driven by the dynamics of the KMCM.

Preface to FP-UML 2009

NASA Astrophysics Data System (ADS)

Trujillo, Juan; Kim, Dae-Kyoo

The Unified Modeling Language (UML) has been widely accepted as the standard object-oriented (OO) modeling language for modeling various aspects of software and information systems. The UML is an extensible language, in the sense that it provides mechanisms to introduce new elements for specific domains if necessary, such as web applications, database applications, business modeling, software development processes, data warehouses. Furthermore, the latest version of UML 2.0 got even bigger and more complicated with more diagrams for some good reasons. Although UML provides different diagrams for modeling different aspects of a software system, not all of them need to be applied in most cases. Therefore, heuristics, design guidelines, lessons learned from experiences are extremely important for the effective use of UML 2.0 and to avoid unnecessary complication. Also, approaches are needed to better manage UML 2.0 and its extensions so they do not become too complex too manage in the end.

[Construction of automatic elucidation platform for mechanism of traditional Chinese medicine].

PubMed

Zhang, Bai-xia; Luo, Si-jun; Yan, Jing; Gu, Hao; Luo, Ji; Zhang, Yan-ling; Tao, Ou; Wang, Yun

2015-10-01

Aim at the two problems in the field of traditional Chinese medicine (TCM) mechanism elucidation, one is the lack of detailed biological processes information, next is the low efficient in constructing network models, we constructed an auxiliary elucidation system for the TCM mechanism and realize the automatic establishment of biological network model. This study used the Entity Grammar Systems (EGS) as the theoretical framework, integrated the data of formulae, herbs, chemical components, targets of component, biological reactions, signaling pathways and disease related proteins, established the formal models, wrote the reasoning engine, constructed the auxiliary elucidation system for the TCM mechanism elucidation. The platform provides an automatic modeling method for biological network model of TCM mechanism. It would be benefit to perform the in-depth research on TCM theory of natures and combination and provides the scientific references for R&D of TCM.

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.

Neural correlates of depth of strategic reasoning in medial prefrontal cortex

PubMed Central

Coricelli, Giorgio; Nagel, Rosemarie

2009-01-01

We used functional MRI (fMRI) to investigate human mental processes in a competitive interactive setting—the “beauty contest” game. This game is well-suited for investigating whether and how a player's mental processing incorporates the thinking process of others in strategic reasoning. We apply a cognitive hierarchy model to classify subject's choices in the experimental game according to the degree of strategic reasoning so that we can identify the neural substrates of different levels of strategizing. According to this model, high-level reasoners expect the others to behave strategically, whereas low-level reasoners choose based on the expectation that others will choose randomly. The data show that high-level reasoning and a measure of strategic IQ (related to winning in the game) correlate with the neural activity in the medial prefrontal cortex, demonstrating its crucial role in successful mentalizing. This supports a cognitive hierarchy model of human brain and behavior. PMID:19470476

What are the Starting Points? Evaluating Base-Year Assumptions in the Asian Modeling Exercise

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

Chaturvedi, Vaibhav; Waldhoff, Stephanie; Clarke, Leon E.

2012-12-01

A common feature of model inter-comparison efforts is that the base year numbers for important parameters such as population and GDP can differ substantially across models. This paper explores the sources and implications of this variation in Asian countries across the models participating in the Asian Modeling Exercise (AME). Because the models do not all have a common base year, each team was required to provide data for 2005 for comparison purposes. This paper compares the year 2005 information for different models, noting the degree of variation in important parameters, including population, GDP, primary energy, electricity, and CO2 emissions. Itmore » then explores the difference in these key parameters across different sources of base-year information. The analysis confirms that the sources provide different values for many key parameters. This variation across data sources and additional reasons why models might provide different base-year numbers, including differences in regional definitions, differences in model base year, and differences in GDP transformation methodologies, are then discussed in the context of the AME scenarios. Finally, the paper explores the implications of base-year variation on long-term model results.« less

West Nile Virus: Using Adapted Primary Literature in Mathematical Biology to Teach Scientific and Mathematical Reasoning in High School

NASA Astrophysics Data System (ADS)

Norris, Stephen P.; Macnab, John S.; Wonham, Marjorie; de Vries, Gerda

2009-05-01

This paper promotes the use of adapted primary literature as a curriculum and instruction innovation for use in high school. Adapted primary literature is useful for promoting an understanding of scientific and mathematical reasoning and argument and for introducing modern science into the schools. We describe a prototype adapted from a published article on a mathematical model of the spread of the West Nile virus in North America. The prototype is available as a web-based resource that includes supplemental pedagogical units. Preliminary feedback from use of the prototype in two classrooms is described and a sketch of an ongoing formal evaluation is provided.

Functional neuroimaging correlates of thinking flexibility and knowledge structure in memory: Exploring the relationships between clinical reasoning and diagnostic thinking.

PubMed

Durning, Steven J; Costanzo, Michelle E; Beckman, Thomas J; Artino, Anthony R; Roy, Michael J; van der Vleuten, Cees; Holmboe, Eric S; Lipner, Rebecca S; Schuwirth, Lambert

2016-06-01

Diagnostic reasoning involves the thinking steps up to and including arrival at a diagnosis. Dual process theory posits that a physician's thinking is based on both non-analytic or fast, subconscious thinking and analytic thinking that is slower, more conscious, effortful and characterized by comparing and contrasting alternatives. Expertise in clinical reasoning may relate to the two dimensions measured by the diagnostic thinking inventory (DTI): memory structure and flexibility in thinking. Explored the functional magnetic resonance imaging (fMRI) correlates of these two aspects of the DTI: memory structure and flexibility of thinking. Participants answered and reflected upon multiple-choice questions (MCQs) during fMRI. A DTI was completed shortly after the scan. The brain processes associated with the two dimensions of the DTI were correlated with fMRI phases - assessing flexibility in thinking during analytical clinical reasoning, memory structure during non-analytical clinical reasoning and the total DTI during both non-analytical and analytical reasoning in experienced physicians. Each DTI component was associated with distinct functional neuroanatomic activation patterns, particularly in the prefrontal cortex. Our findings support diagnostic thinking conceptual models and indicate mechanisms through which cognitive demands may induce functional adaptation within the prefrontal cortex. This provides additional objective validity evidence for the use of the DTI in medical education and practice settings.

Reason for hospital admission: a pilot study comparing patient statements with chart reports.

PubMed

Berger, Zackary; Dembitzer, Anne; Beach, Mary Catherine

2013-01-01

Providers and patients bring different understandings of health and disease to their encounters in the hospital setting. The literature to date only infrequently addresses patient and provider concordance on the reported reason for hospitalization, that is, whether they express this reason in similar ways. An agreement or common ground between such understandings can serve as a basis for future communication regarding an illness and its treatment. We interviewed a convenience sample of patients on the medical wards of an urban academic medical center. We asked subjects to state the reason why their doctors admitted them to the hospital, and then compared their statement with the reason in the medical record. We defined concordance on reported reason for hospitalization as agreement between the patient's report and the reason abstracted from the chart. We interviewed and abstracted chart data from a total of 46 subjects. Concordance on reported reason for hospitalization was present in 24 (52%) and discordance in 17 (37%); 5 patients (11%) could not give any reason for their hospitalization. Among the 17 patients whose report was discordant with their chart, 12 (71%) reported a different organ system than was recorded in the chart. A significant proportion of medical inpatients could not state their physicians' reason for admission. In addition, patients who identify a different reason for hospitalization than the chart often give a different organ system altogether. Providers should explore patient understanding of the reason for their hospitalization to facilitate communication and shared decision making.

Evaluation of modeling as a tool to determine the potential impacts related to drilling wastes in the Brazilian offshore.

PubMed

Pivel, María Alejandra Gómez; Dal Sasso Freitas, Carla Maria

2010-08-01

Numerical models that predict the fate of drilling discharges at sea constitute a valuable tool for both the oil industry and regulatory agencies. In order to provide reliable estimates, models must be validated through the comparison of predictions with field or laboratory observations. In this paper, we used the Offshore Operators Committee Model to simulate the discharges from two wells drilled at Campos Basin, offshore SE Brazil, and compared the results with field observations obtained 3 months after drilling. The comparison showed that the model provided reasonable predictions, considering that data about currents were reconstructed and theoretical data were used to characterize the classes of solids. The model proved to be a valuable tool to determine the degree of potential impact associated to drilling activities. However, since the accuracy of the model is directly dependent on the quality of input data, different possible scenarios should be considered when used for forecast modeling.

Adventures in holistic ecosystem modelling: the cumberland basin ecosystem model

NASA Astrophysics Data System (ADS)

Gordon, D. C.; Keizer, P. D.; Daborn, G. R.; Schwinghamer, P.; Silvert, W. L.

A holistic ecosystem model has been developed for the Cumberland Basin, a turbid macrotidal estuary at the head of Canada's Bay of Fundy. The model was constructed as a group exercise involving several dozen scientists. Philosophy of approach and methods were patterned after the BOEDE Ems-Dollard modelling project. The model is one-dimensional, has 3 compartments and 3 boundaries, and is composed of 3 separate submodels (physical, pelagic and benthic). The 28 biological state variables cover the complete estuarine ecosystem and represent broad functional groups of organisms based on trophic relationships. Although still under development and not yet validated, the model has been verified and has reached the stage where most state variables provide reasonable output. The modelling process has stimulated interdisciplinary discussion, identified important data gaps and produced a quantitative tool which can be used to examine ecological hypotheses and determine critical environmental processes. As a result, Canadian scientists have a much better understanding of the Cumberland Basin ecosystem and are better able to provide competent advice on environmental management.

Using self-organizing maps to determine observation threshold limit predictions in highly variant data

USGS Publications Warehouse

Paganoni, C.A.; Chang, K.C.; Robblee, M.B.

2006-01-01

A significant data quality challenge for highly variant systems surrounds the limited ability to quantify operationally reasonable limits on the data elements being collected and provide reasonable threshold predictions. In many instances, the number of influences that drive a resulting value or operational range is too large to enable physical sampling for each influencer, or is too complicated to accurately model in an explicit simulation. An alternative method to determine reasonable observation thresholds is to employ an automation algorithm that would emulate a human analyst visually inspecting data for limits. Using the visualization technique of self-organizing maps (SOM) on data having poorly understood relationships, a methodology for determining threshold limits was developed. To illustrate this approach, analysis of environmental influences that drive the abundance of a target indicator species (the pink shrimp, Farfantepenaeus duorarum) provided a real example of applicability. The relationship between salinity and temperature and abundance of F. duorarum is well documented, but the effect of changes in water quality upstream on pink shrimp abundance is not well understood. The highly variant nature surrounding catch of a specific number of organisms in the wild, and the data available from up-stream hydrology measures for salinity and temperature, made this an ideal candidate for the approach to provide a determination about the influence of changes in hydrology on populations of organisms.

Using self-organizing maps to determine observation threshold limit predictions in highly variant data

NASA Astrophysics Data System (ADS)

Paganoni, Christopher A.; Chang, K. C.; Robblee, Michael B.

2006-05-01

A significant data quality challenge for highly variant systems surrounds the limited ability to quantify operationally reasonable limits on the data elements being collected and provide reasonable threshold predictions. In many instances, the number of influences that drive a resulting value or operational range is too large to enable physical sampling for each influencer, or is too complicated to accurately model in an explicit simulation. An alternative method to determine reasonable observation thresholds is to employ an automation algorithm that would emulate a human analyst visually inspecting data for limits. Using the visualization technique of self-organizing maps (SOM) on data having poorly understood relationships, a methodology for determining threshold limits was developed. To illustrate this approach, analysis of environmental influences that drive the abundance of a target indicator species (the pink shrimp, Farfantepenaeus duorarum) provided a real example of applicability. The relationship between salinity and temperature and abundance of F. duorarum is well documented, but the effect of changes in water quality upstream on pink shrimp abundance is not well understood. The highly variant nature surrounding catch of a specific number of organisms in the wild, and the data available from up-stream hydrology measures for salinity and temperature, made this an ideal candidate for the approach to provide a determination about the influence of changes in hydrology on populations of organisms.

Sexual Response Models: Toward a More Flexible Pattern of Women's Sexuality.

PubMed

Ferenidou, Fotini; Kirana, Paraskevi-Sofia; Fokas, Konstantinos; Hatzichristou, Dimitrios; Athanasiadis, Loukas

2016-09-01

Recent research suggests that none of the current theoretical models can sufficiently describe women's sexual response, because several factors and situations can influence this. To explore individual variations of a sexual model that describes women's sexual responses and to assess the association of endorsement of that model with sexual dysfunctions and reasons to engage in sexual activity. A sample of 157 randomly selected hospital employees completed self-administered questionnaires. Two models were developed: one merged the Master and Johnson model with the Kaplan model (linear) and the other was the Basson model (circular). Sexual function was evaluated by the Female Sexual Function Index and the Brief Sexual Symptom Checklist for Women. The Reasons for Having Sex Questionnaire was administered to investigate the reasons for which women have sex. Women reported that their current sexual experiences were at times consistent with the linear and circular models (66.9%), only the linear model (27%), only the circular model (5.4%), and neither model (0.7%). When the groups were reconfigured to the group that endorsed more than 5 of 10 sexual experiences, 64.3% of women endorsed the linear model, 20.4% chose the linear and circular models, 14.6% chose the circular model, and 0.7% selected neither. The Female Sexual Function Index, demographic factors, having sex for insecurity reasons, and sexual satisfaction correlated with the endorsement of a sexual response model. When these factors were entered in a stepwise logistic regression analysis, only the Female Sexual Function Index and having sex for insecurity reasons maintained a significant association with the sexual response model. The present study emphasizes the heterogeneity of female sexuality, with most of the sample reporting alternating between the linear and circular models. Sexual dysfunctions and having sex for insecurity reasons were associated with the Basson model. Copyright © 2016 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

Stimulating Scientific Reasoning with Drawing-Based Modeling

ERIC Educational Resources Information Center

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

2018-01-01

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

Nurses' intention to leave: critically analyse the theory of reasoned action and organizational commitment model.

PubMed

Liou, Shwu-Ru

2009-01-01

To systematically analyse the Organizational Commitment model and Theory of Reasoned Action and determine concepts that can better explain nurses' intention to leave their job. The Organizational Commitment model and Theory of Reasoned Action have been proposed and applied to understand intention to leave and turnover behaviour, which are major contributors to nursing shortage. However, the appropriateness of applying these two models in nursing was not analysed. Three main criteria of a useful model were used for the analysis: consistency in the use of concepts, testability and predictability. Both theories use concepts consistently. Concepts in the Theory of Reasoned Action are defined broadly whereas they are operationally defined in the Organizational Commitment model. Predictability of the Theory of Reasoned Action is questionable whereas the Organizational Commitment model can be applied to predict intention to leave. A model was proposed based on this analysis. Organizational commitment, intention to leave, work experiences, job characteristics and personal characteristics can be concepts for predicting nurses' intention to leave. Nursing managers may consider nurses' personal characteristics and experiences to increase their organizational commitment and enhance their intention to stay. Empirical studies are needed to test and cross-validate the re-synthesized model for nurses' intention to leave their job.

77 FR 9907 - Notice of Petition for Waiver of LG Electronics U.S.A., Inc. From the Department of Energy...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-21

... test procedures that are reasonably designed to produce results which measure energy efficiency, energy... that the basic model for which the petition for waiver was submitted contains one or more design... consumption characteristics as to provide materially inaccurate comparative data. 10 CFR 430.27(l)), 431.401(f...

Embedded Diagnostic/Prognostic Reasoning and Information Continuity for Improved Avionics Maintenance

DTIC Science & Technology

2006-01-01

enabling technologies such as built-in-test, advanced health monitoring algorithms, reliability and component aging models, prognostics methods, and...deployment and acceptance. This framework and vision is consistent with the onboard PHM ( Prognostic and Health Management) as well as advanced... monitored . In addition to the prognostic forecasting capabilities provided by monitoring system power, multiple confounding errors by electronic

Mapping pre-European settlement vegetation at fine resolutions using a hierarchical Bayesian model and GIS

Treesearch

Hong S. He; Daniel C. Dey; Xiuli Fan; Mevin B. Hooten; John M. Kabrick; Christopher K. Wikle; Zhaofei. Fan

2007-01-01

In the Midwestern United States, the GeneralLandOffice (GLO) survey records provide the only reasonably accurate data source of forest composition and tree species distribution at the time of pre-European settlement (circa late 1800 to early 1850). However, GLO data have two fundamental limitations: coarse spatial resolutions (the square mile section and half mile...

Sport, Moral Development, and the Role of the Teacher: Implications for Research and Moral Education.

ERIC Educational Resources Information Center

Arnold, Peter J.

2001-01-01

Examines the inadequacies of some purely justice or moral reasoning approaches to moral development in sport, especially when viewed from the perspective of virtue theory and Aristotelian concepts of phronesis and habituation, arguing that the latter approach provides more complete criteria for formulating a new model of the nature of the moral.…

77 FR 76356 - Privacy of Consumer Financial Information Under Title V of the Gramm-Leach-Bliley Act

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-28

... Under Title V of the Gramm-Leach-Bliley Act CFR Correction In Title 17 of the Code of Federal...). (2) Title. (3) Key frame (Why?, What?, How?). (4) Disclosure table (``Reasons we can share your... financial institution provides the model form and that institution is clearly identified in the title on...

75 FR 38397 - Airworthiness Directives; The Boeing Company Model 747-400, 747-400D, and 747-400F Series Airplanes

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-02

... 17,000-lb center wing tank (CWT) minimum fuel amount to select the CWT override/jettison pumps ON... the Boeing comment for the reasons provided and because the certification limitation for CWT minimum... prior FAA approvals. The note specified the following: ``The CWT and the HST may be emptied normally...

An exploratory study of proficient undergraduate Chemistry II students' application of Lewis's model

NASA Astrophysics Data System (ADS)

Lewis, Sumudu R.

This exploratory study was based on the assumption that proficiency in chemistry must not be determined exclusively on students' declarative and procedural knowledge, but it should be also described as the ability to use variety of reasoning strategies that enrich and diversify procedural methods. The study furthermore assumed that the ability to describe the structure of a molecule using Lewis's model and use it to predict its geometry as well as some of its properties is indicative of proficiency in the essential concepts of covalent bonding and molecule structure. The study therefore inquired into the reasoning methods and procedural techniques of proficient undergraduate Chemistry II students when solving problems, which require them to use Lewis's model. The research design included an original survey, designed by the researcher for this study, and two types of interviews, with students and course instructors. The purpose of the survey was two-fold. First and foremost, the survey provided a base for the student interview selection, and second it served as the foundation for the inquiry into the strategies the student use when solving survey problems. Twenty two students were interviewed over the course of the study. The interview with six instructors allowed to identify expected prior knowledge and skills, which the students should have acquired upon completion of the Chemistry I course. The data, including videos, audios, and photographs of the artifacts produced by students during the interviews, were organized and analyzed manually and using QSR NVivo 10. The research found and described the differences between proficient and non-proficient students' reasoning and procedural strategies when using Lewis's model to describe the structure of a molecule. One of the findings clearly showed that the proficient students used a variety of cues to reason, whereas other students used one memorized cue, or an algorithm, which often led to incorrect representations in cases where the algorithm cannot be applied. Additionally, the proficient students' understanding (i.e., representation, explanation and application) of the Valence Shell Electron-Pair Repulsion theory was accurate and precise, and they used the key terms in the correct context when explaining their reasoning. The results of this study can be of great importance to general chemistry and organic chemistry courses' instructors. This study identified students' baseline academic skills and abilities that lead to conceptual understanding of the essential concepts of covalent bonding and molecule structure, which instructors could use as a guide for developing instruction. Furthermore knowing the effective methods of reasoning the students use while applying Lewis's model, the instructors may be better informed and be able to better facilitate students' learning of Lewis' model and its application. Finally, the ideas and methods used in this study can be of value to chemistry education researchers to learn more about developing proficiency through reasoning methods in other chemistry concepts.

Benchmarked analyses of gamma skyshine using MORSE-CGA-PC and the DABL69 cross-section set

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

Reichert, P.T.; Golshani, M.

1991-01-01

Design for gamma-ray skyshine is a common consideration for a variety of nuclear and accelerator facilities. Many of these designs can benefit from a more accurate and complete treatment than can be provided by simple skyshine analysis tools. Those methods typically require a number of conservative, simplifying assumptions in modeling the radiation source and shielding geometry. This paper considers the benchmarking of one analytical option. The MORSE-CGA Monte Carlo radiation transport code system provides the capability for detailed treatment of virtually any source and shielding geometry. Unfortunately, the mainframe computer costs of MORSE-CGA analyses can prevent cost-effective application to smallmore » projects. For this reason, the MORSE-CGA system was converted to run on IBM personal computer (PC)-compatible computers using the Intel 80386 or 80486 microprocessors. The DLC-130/DABL69 cross-section set (46n,23g) was chosen as the most suitable, readily available, broad-group library. The most important reason is the relatively high (P{sub 5}) Legendre order of expansion for angular distribution. This is likely to be beneficial in the deep-penetration conditions modeled in some skyshine problems.« less

Development of a mathematical model of the human cardiovascular system: An educational perspective

NASA Astrophysics Data System (ADS)

Johnson, Bruce Allen

A mathematical model of the human cardiovascular system will be a useful educational tool in biological sciences and bioengineering classrooms. The goal of this project is to develop a mathematical model of the human cardiovascular system that responds appropriately to variations of significant physical variables. Model development is based on standard fluid statics and dynamics principles, pressure-volume characteristics of the cardiac cycle, and compliant behavior of blood vessels. Cardiac cycle phases provide the physical and logical model structure, and Boolean algebra links model sections. The model is implemented using VisSim, a highly intuitive and easily learned block diagram modeling software package. Comparisons of model predictions of key variables to published values suggest that the model reasonably approximates expected behavior of those variables. The model responds plausibly to variations of independent variables. Projected usefulness of the model as an educational tool is threefold: independent variables which determine heart function may be easily varied to observe cause and effect; the model is used in an interactive setting; and the relationship of governing equations to model behavior is readily viewable and intuitive. Future use of this model in classrooms may give a more reasonable indication of its value as an educational tool.* *This dissertation includes a CD that is multimedia (contains text and other applications that are not available in a printed format). The CD requires the following applications: CorelPhotoHouse, CorelWordPerfect, VisSinViewer (included on CD), Internet access.

Parallel implementation of approximate atomistic models of the AMOEBA polarizable model

NASA Astrophysics Data System (ADS)

Demerdash, Omar; Head-Gordon, Teresa

2016-11-01

In this work we present a replicated data hybrid OpenMP/MPI implementation of a hierarchical progression of approximate classical polarizable models that yields speedups of up to ∼10 compared to the standard OpenMP implementation of the exact parent AMOEBA polarizable model. In addition, our parallel implementation exhibits reasonable weak and strong scaling. The resulting parallel software will prove useful for those who are interested in how molecular properties converge in the condensed phase with respect to the MBE, it provides a fruitful test bed for exploring different electrostatic embedding schemes, and offers an interesting possibility for future exascale computing paradigms.

Applications of the hybrid coordinate method to the TOPS autopilot

NASA Technical Reports Server (NTRS)

Fleischer, G. E.

1978-01-01

Preliminary results are presented from the application of the hybrid coordinate method to modeling TOPS (thermoelectric outer planet spacecraft) structural dynamics. Computer simulated responses of the vehicle are included which illustrate the interaction of relatively flexible appendages with an autopilot control system. Comparisons were made between simplified single-axis models of the control loop, with spacecraft flexibility represented by hinged rigid bodies, and a very detailed three-axis spacecraft model whose flexible portions are described by modal coordinates. While single-axis system, root loci provided reasonable qualitative indications of stability margins in this case, they were quantitatively optimistic when matched against responses of the detailed model.

Nilpotent singularities and dynamics in an SIR type of compartmental model with hospital resources

NASA Astrophysics Data System (ADS)

Shan, Chunhua; Yi, Yingfei; Zhu, Huaiping

2016-03-01

An SIR type of compartmental model with a standard incidence rate and a nonlinear recovery rate was formulated to study the impact of available resources of public health system especially the number of hospital beds. Cusp, focus and elliptic type of nilpotent singularities of codimension 3 are discovered and analyzed in this three dimensional model. Complex dynamics of disease transmission including multi-steady states and multi-periodicity are revealed by bifurcation analysis. Large-amplitude oscillations found in our model provide a more reasonable explanation for disease recurrence. With clinical data, our studies have practical implications for the prevention and control of infectious diseases.

NOx formation in combustion of gaseous fuel in ejection burner

NASA Astrophysics Data System (ADS)

Rimár, Miroslav; Kulikov, Andrii

2016-06-01

The aim of this work is to prepare model for researching of the formation in combustion of gaseous fuels. NOx formation is one of the main ecological problems nowadays as nitrogen oxides is one of main reasons of acid rains. The ANSYS model was designed according to the calculation to provide full combustion and good mixing of the fuel and air. The current model is appropriate to research NOx formation and the influence of the different principles of NOx reduction method. Applying of designed model should spare both time of calculations and research and also money as you do not need to measure the burner characteristics.

Redesigning care for patients at increased hospitalization risk: the Comprehensive Care Physician model.

PubMed

Meltzer, David O; Ruhnke, Gregory W

2014-05-01

Patients who have been hospitalized often experience care coordination problems that worsen outcomes and increase costs. One reason is that hospital care and ambulatory care are often provided by different physicians. However, interventions to improve care coordination for hospitalized patients have not consistently improved outcomes and generally have not reduced costs. We describe the rationale for the Comprehensive Care Physician model, in which physicians focus their practice on patients at increased risk of hospitalization so that they can provide both inpatient and outpatient care to their patients. We also describe the design and implementation of a study supported by the Center for Medicare and Medicaid Innovation to assess the model's effects on costs and outcomes. Evidence concerning the effectiveness of the program is expected by 2016. If the program is found to be effective, the next steps will be to assess the durability of its benefits and the model's potential for dissemination; evidence to the contrary will provide insights into how to alter the program to address sources of failure.

A Formal Theory for Modular ERDF Ontologies

NASA Astrophysics Data System (ADS)

Analyti, Anastasia; Antoniou, Grigoris; Damásio, Carlos Viegas

The success of the Semantic Web is impossible without any form of modularity, encapsulation, and access control. In an earlier paper, we extended RDF graphs with weak and strong negation, as well as derivation rules. The ERDF #n-stable model semantics of the extended RDF framework (ERDF) is defined, extending RDF(S) semantics. In this paper, we propose a framework for modular ERDF ontologies, called modular ERDF framework, which enables collaborative reasoning over a set of ERDF ontologies, while support for hidden knowledge is also provided. In particular, the modular ERDF stable model semantics of modular ERDF ontologies is defined, extending the ERDF #n-stable model semantics. Our proposed framework supports local semantics and different points of view, local closed-world and open-world assumptions, and scoped negation-as-failure. Several complexity results are provided.

Reconstruction of mass balance variations for Franz Josef Glacier, New Zealand, 1913 to 1989

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

Woo, Mingko Woo; Fitzharris, B.B.

1992-11-01

A model of mass balance is constructed for the Franz Josef Glacier on the west coast of New Zealand. It uses daily data from a nearby, but short-record climate station. The model is extended back to 1913 by creating hybrid climate data from a long-record, but more distant, climate station. Its monthly data provide long-term temperature and precipitation trends, and daily fluctuations are simulated using a stochastic approach that is tuned to the characteristics of the short-record station. The glacier model provides estimates of equilibrium-line altitudes which are in reasonable agreement with those observed, and variations of cumulative mass balancemore » that correspond with patterns of advance and retreat of the glacier terminus.« less

Cold induced mortality of the Burmese Python: An explanation via stochastic analysis

NASA Astrophysics Data System (ADS)

Quansah, Emmanuel; Parshad, Rana D.; Mondal, Sumona

2017-02-01

The Burmese python (Python bivitatus) is an invasive species, wreaking havoc on indigenous species in the Florida everglades. Data suggests an exponential growth in their population from 1995 to 2009, with a sharp decline however in 2010-2012 (Dorcas et al., 2012). In Mazzotti et al. (2011) an explanation is provided, citing the unusually cold winter that year, as the primary reason for this decline. We provide a first mathematical model, in the form of a system of stochastic differential equations, that supports the explanation in Mazzotti et al. (2011), by accurately matching the field data presented in Dorcas et al. (2012). More generally, our model provides a tool to predict the population dynamics of rapidly growing alien species, in the advent of climate change.

COBE DMR-normalized open inflation cold dark matter cosmogony

NASA Technical Reports Server (NTRS)

Gorski, Krzysztof M.; Ratra, Bharat; Sugiyama, Naoshi; Banday, Anthony J.

1995-01-01

A cut-sky orthogonal mode analysis of the 2 year COBE DMR 53 and 90 GHz sky maps (in Galactic coordinates) is used to determine the normalization of an open inflation model based on the cold dark matter (CDM) scenario. The normalized model is compared to measures of large-scale structure in the universe. Although the DMR data alone does not provide sufficient discriminative power to prefer a particular value of the mass density parameter, the open model appears to be reasonably consistent with observations when Omega(sub 0) is approximately 0.3-0.4 and merits further study.

[Cybernetics and biology].

PubMed

Vasil'ev, G F

2013-01-01

Owing to methodical disadvantages, the theory of control still lacks the potential for the analysis of biological systems. To get the full benefit of the method in addition to the algorithmic model of control (as of today the only used model in the theory of control) a parametric model of control is offered to employ. The reasoning for it is explained. The approach suggested provides the possibility to use all potential of the modern theory of control for the analysis of biological systems. The cybernetic approach is shown taking a system of the rise of glucose concentration in blood as an example.

DEVS representation of dynamical systems - Event-based intelligent control. [Discrete Event System Specification

NASA Technical Reports Server (NTRS)

Zeigler, Bernard P.

1989-01-01

It is shown how systems can be advantageously represented as discrete-event models by using DEVS (discrete-event system specification), a set-theoretic formalism. Such DEVS models provide a basis for the design of event-based logic control. In this control paradigm, the controller expects to receive confirming sensor responses to its control commands within definite time windows determined by its DEVS model of the system under control. The event-based contral paradigm is applied in advanced robotic and intelligent automation, showing how classical process control can be readily interfaced with rule-based symbolic reasoning systems.

Toward Accessing Spatial Structure from Building Information Models

NASA Astrophysics Data System (ADS)

Schultz, C.; Bhatt, M.

2011-08-01

Data about building designs and layouts is becoming increasingly more readily available. In the near future, service personal (such as maintenance staff or emergency rescue workers) arriving at a building site will have immediate real-time access to enormous amounts of data relating to structural properties, utilities, materials, temperature, and so on. The critical problem for users is the taxing and error prone task of interpreting such a large body of facts in order to extract salient information. This is necessary for comprehending a situation and deciding on a plan of action, and is a particularly serious issue in time-critical and safety-critical activities such as firefighting. Current unifying building models such as the Industry Foundation Classes (IFC), while being comprehensive, do not directly provide data structures that focus on spatial reasoning and spatial modalities that are required for high-level analytical tasks. The aim of the research presented in this paper is to provide computational tools for higher level querying and reasoning that shift the cognitive burden of dealing with enormous amounts of data away from the user. The user can then spend more energy and time in planning and decision making in order to accomplish the tasks at hand. We present an overview of our framework that provides users with an enhanced model of "built-up space". In order to test our approach using realistic design data (in terms of both scale and the nature of the building models) we describe how our system interfaces with IFC, and we conduct timing experiments to determine the practicality of our approach. We discuss general computational approaches for deriving higher-level spatial modalities by focusing on the example of route graphs. Finally, we present a firefighting scenario with alternative route graphs to motivate the application of our framework.

Influences on the use of capital by public hospitals.

PubMed

Anderson, D

1994-01-01

This paper examines key influences on the volume of capital employed by public hospitals. Empirical models are constructed and analysed separately for total capital employed and for plant and equipment only, using data from 68 Victorian hospitals. Such data provide an empirical base to guide government decisions on funding capital expenditure in hospitals. The analysis finds that the proportion of hospital expenditure devoted to outpatients and teaching, and the proportion of funding derived from government all influence the level of capital utilised per inpatient. The model provided a reasonable fit for plant and equipment, but much improved data coverage and consistent valuation of land and buildings are required to adequately explain influences on total capital.

The SAMI2 Open Source Project

NASA Astrophysics Data System (ADS)

Huba, J. D.; Joyce, G.

2001-05-01

In the past decade, the Open Source Model for software development has gained popularity and has had numerous major achievements: emacs, Linux, the Gimp, and Python, to name a few. The basic idea is to provide the source code of the model or application, a tutorial on its use, and a feedback mechanism with the community so that the model can be tested, improved, and archived. Given the success of the Open Source Model, we believe it may prove valuable in the development of scientific research codes. With this in mind, we are `Open Sourcing' the low to mid-latitude ionospheric model that has recently been developed at the Naval Research Laboratory: SAMI2 (Sami2 is Another Model of the Ionosphere). The model is comprehensive and uses modern numerical techniques. The structure and design of SAMI2 make it relatively easy to understand and modify: the numerical algorithms are simple and direct, and the code is reasonably well-written. Furthermore, SAMI2 is designed to run on personal computers; prohibitive computational resources are not necessary, thereby making the model accessible and usable by virtually all researchers. For these reasons, SAMI2 is an excellent candidate to explore and test the open source modeling paradigm in space physics research. We will discuss various topics associated with this project. Research supported by the Office of Naval Research.

A three-dimensional semianalytical model of hydraulic fracture growth through weak barriers

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

Luiskutty, C.T.; Tomutes, L.; Palmer, I.D.

1989-08-01

The goal of this research was to develop a fracture model for length/height ratio {le}4 that includes 2D flow (and a line source corresponding to the perforated interval) but makes approximations that allow a semianalytical solution, with large computer-time savings over the fully numerical mode. The height, maximum width, and pressure at the wellbore in this semianalytical model are calculated and compared with the results of the fully three-dimensional (3D) model. There is reasonable agreement in all parameters, the maximum discrepancy being 24%. Comparisons of fracture volume and leakoff volume also show reasonable agreement in volume and fluid efficiencies. Themore » values of length/height ratio, in the four cases in which agreement is found, vary from 1.5 to 3.7. The model offers a useful first-order (or screening) calculation of fracture-height growth through weak barriers (e.g., low stress contrasts). When coupled with the model developed for highly elongated fractures of length/height ratio {ge}4, which are also found to be in basic agreement with the fully numerical model, this new model provides the capability for approximating fracture-height growth through barriers for vertical fracture shapes that vary from penny to highly elongated. The computer time required is estimated to be less than the time required for the fully numerical model by a factor of 10 or more.« less

Transfer after process-based object-location memory training in healthy older adults.

PubMed

Zimmermann, Kathrin; von Bastian, Claudia C; Röcke, Christina; Martin, Mike; Eschen, Anne

2016-11-01

A substantial part of age-related episodic memory decline has been attributed to the decreasing ability of older adults to encode and retrieve associations among simultaneously processed information units from long-term memory. In addition, this ability seems to share unique variance with reasoning. In this study, we therefore examined whether process-based training of the ability to learn and remember associations has the potential to induce transfer effects to untrained episodic memory and reasoning tasks in healthy older adults (60-75 years). For this purpose, the experimental group (n = 36) completed 30 sessions of process-based object-location memory training, while the active control group (n = 31) practiced visual perception on the same material. Near (spatial episodic memory), intermediate (verbal episodic memory), and far transfer effects (reasoning) were each assessed with multiple tasks at four measurements (before, midway through, immediately after, and 4 months after training). Linear mixed-effects models revealed transfer effects on spatial episodic memory and reasoning that were still observed 4 months after training. These results provide first empirical evidence that process-based training can enhance healthy older adults' associative memory performance and positively affect untrained episodic memory and reasoning abilities. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Affect and Moral Reasoning.

ERIC Educational Resources Information Center

Olejnik, Anthony B.; LaRue, Asenath A.

1980-01-01

Positive and negative mood conditions do affect principled moral reasoning. Results do not imply that affective states raise levels of moral reasoning, but a positive affective state provides a condition conducive to using more principled level moral reasoning. (Author/JAC)

Teaching Children Real-World Knowledge and Reasoning.

ERIC Educational Resources Information Center

Williams, Wendy M.

2002-01-01

Introduces this special issue topic by asserting that empirically powerful and theoretically guided educational research needs to be designed with the teacher in mind. Provides rationale for research focus on real-world knowledge and reasoning, and reasons for selecting research projects on inductive reasoning, mathematical reasoning, map skills,…

Models of Human Information Requirements: "When Reasonable Aiding Systems Disagree"

NASA Technical Reports Server (NTRS)

Corker, Kevin; Pisanich, Gregory; Shafto, Michael (Technical Monitor)

1994-01-01

Aircraft flight management and Air Traffic Control (ATC) automation are under development to maximize the economy of flight and to increase the capacity of the terminal area airspace while maintaining levels of flight safety equal to or better than current system performance. These goals are being realized by the introduction of flight management automation aiding and operations support systems on the flight deck and by new developments of ATC aiding systems that seek to optimize scheduling of aircraft while potentially reducing required separation and accounting for weather and wake vortex turbulence. Aiding systems on both the flight deck and the ground operate through algorithmic functions on models of the aircraft and of the airspace. These models may differ from each other as a result of variations in their models of the immediate environment. The resultant flight operations or ATC commands may differ in their response requirements (e.g. different preferred descent speeds or descent initiation points). The human operators in the system must then interact with the automation to reconcile differences and resolve conflicts. We have developed a model of human performance including cognitive functions (decision-making, rule-based reasoning, procedural interruption recovery and forgetting) that supports analysis of the information requirements for resolution of flight aiding and ATC conflicts. The model represents multiple individuals in the flight crew and in ATC. The model is supported in simulation on a Silicon Graphics' workstation using Allegro Lisp. Design guidelines for aviation automation aiding systems have been developed using the model's specification of information and team procedural requirements. Empirical data on flight deck operations from full-mission flight simulation are provided to support the model's predictions. The paper describes the model, its development and implementation, the simulation test of the model predictions, and the empirical validation process. The model and its supporting data provide a generalizable tool that is being expanded to include air/ground compatibility and ATC crew interactions in air traffic management.

How do frequent users of crisis helplines differ from other users regarding their reasons for calling? Results from a survey with callers to Lifeline, Australia's national crisis helpline service.

PubMed

Middleton, Aves; Woodward, Alan; Gunn, Jane; Bassilios, Bridget; Pirkis, Jane

2017-05-01

Crisis helplines are designed to provide short-term support to people in an immediate crisis. However, there is a group of users who call crisis helplines frequently over an extended period of time. The reasons for their ongoing use remain unclear. The aim of this study was to investigate the differences in the reasons for calling between frequent and other users of crisis helplines. This was achieved by examining the findings from a brief survey completed by callers to Lifeline Australia at the end of their call between February and July 2015. In the survey, callers reported on their socio-demographics, reasons for their current call and number of calls made in the past month. Survey respondents were categorised as frequent, episodic and one-off users, and analyses were conducted using ordered logistic regression. Three hundred and fifteen callers completed the survey, which represented 57% of eligible callers. Twenty-two per cent reported calling 20 times or more in the past month (frequent users), 51% reported calling between 2 and 19 times (episodic users) and 25% reported calling once (one-off users). Two per cent were unable to recall the number of calls they made in the past month. Frequent users reported similar reasons for calling as other users but they were more likely to call regularly to talk about their feelings [OR = 6.0; 95% CI: 3.7-9.8]. This pattern of service use is at odds with the current model of care offered by crisis helplines which is designed to provide one-off support. There is a need to investigate further the factors that drive frequent users to call crisis helplines regularly. © 2016 John Wiley & Sons Ltd.

Model-Based Reasoning in the Physics Laboratory: Framework and Initial Results

ERIC Educational Resources Information Center

Zwickl, Benjamin M.; Hu, Dehui; Finkelstein, Noah; Lewandowski, H. J.

2015-01-01

We review and extend existing frameworks on modeling to develop a new framework that describes model-based reasoning in introductory and upper-division physics laboratories. Constructing and using models are core scientific practices that have gained significant attention within K-12 and higher education. Although modeling is a broadly applicable…

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.

Fitting Item Response Theory Models to Two Personality Inventories: Issues and Insights.

PubMed

Chernyshenko, O S; Stark, S; Chan, K Y; Drasgow, F; Williams, B

2001-10-01

The present study compared the fit of several IRT models to two personality assessment instruments. Data from 13,059 individuals responding to the US-English version of the Fifth Edition of the Sixteen Personality Factor Questionnaire (16PF) and 1,770 individuals responding to Goldberg's 50 item Big Five Personality measure were analyzed. Various issues pertaining to the fit of the IRT models to personality data were considered. We examined two of the most popular parametric models designed for dichotomously scored items (i.e., the two- and three-parameter logistic models) and a parametric model for polytomous items (Samejima's graded response model). Also examined were Levine's nonparametric maximum likelihood formula scoring models for dichotomous and polytomous data, which were previously found to provide good fits to several cognitive ability tests (Drasgow, Levine, Tsien, Williams, & Mead, 1995). The two- and three-parameter logistic models fit some scales reasonably well but not others; the graded response model generally did not fit well. The nonparametric formula scoring models provided the best fit of the models considered. Several implications of these findings for personality measurement and personnel selection were described.

INDUCTIVE SYSTEM HEALTH MONITORING WITH STATISTICAL METRICS

NASA Technical Reports Server (NTRS)

Iverson, David L.

2005-01-01

Model-based reasoning is a powerful method for performing system monitoring and diagnosis. Building models for model-based reasoning is often a difficult and time consuming process. The Inductive Monitoring System (IMS) software was developed to provide a technique to automatically produce health monitoring knowledge bases for systems that are either difficult to model (simulate) with a computer or which require computer models that are too complex to use for real time monitoring. IMS processes nominal data sets collected either directly from the system or from simulations to build a knowledge base that can be used to detect anomalous behavior in the system. Machine learning and data mining techniques are used to characterize typical system behavior by extracting general classes of nominal data from archived data sets. In particular, a clustering algorithm forms groups of nominal values for sets of related parameters. This establishes constraints on those parameter values that should hold during nominal operation. During monitoring, IMS provides a statistically weighted measure of the deviation of current system behavior from the established normal baseline. If the deviation increases beyond the expected level, an anomaly is suspected, prompting further investigation by an operator or automated system. IMS has shown potential to be an effective, low cost technique to produce system monitoring capability for a variety of applications. We describe the training and system health monitoring techniques of IMS. We also present the application of IMS to a data set from the Space Shuttle Columbia STS-107 flight. IMS was able to detect an anomaly in the launch telemetry shortly after a foam impact damaged Columbia's thermal protection system.

Does it always feel good to get what you want? Young children differentiate between material and wicked desires.

PubMed

Smith, Craig E; Warneken, Felix

2014-03-01

One line of research on children's attributions of guilt suggests that 3-year-olds attribute negative emotion to self-serving victimizers, slightly older children attribute happiness, and with increasing age, attributions become negative again (i.e., a three-step model; Yuill et al., 1996, Br. J. Dev. Psychol., 14, 457). Another line of research provides reason to expect that 3-year-olds may be predisposed to view self-serving moral transgression as leading to positive emotion; this is a linear developmental model in which emotion attributions to transgressors become increasingly negative over the course of childhood (e.g., Nunner-Winkler & Sodian, 1988, Child Dev., 59, 1323). However, key differences in methodology make it difficult to compare across these findings. The present study was designed to address this problem. We asked how 3- to 9-year-old children (n = 111) reason about transgression scenarios that involve satisfying wicked desires (wanting to cause harm and doing so successfully) versus material desires (wanting an object and getting it successfully via harmful behaviour). Three-year-old children reasoned differently about desire and emotion across these two types of transgressions, attributing negative emotion in the case of wicked desires and positive emotion in the case of material desires. This pattern of emotion attribution by young children provides new information about how young children process information about desires and emotions in the moral domain, and it bridges a gap in the existing literature on this topic. © 2013 The British Psychological Society.

Structure induction in diagnostic causal reasoning.

PubMed

Meder, Björn; Mayrhofer, Ralf; Waldmann, Michael R

2014-07-01

Our research examines the normative and descriptive adequacy of alternative computational models of diagnostic reasoning from single effects to single causes. Many theories of diagnostic reasoning are based on the normative assumption that inferences from an effect to its cause should reflect solely the empirically observed conditional probability of cause given effect. We argue against this assumption, as it neglects alternative causal structures that may have generated the sample data. Our structure induction model of diagnostic reasoning takes into account the uncertainty regarding the underlying causal structure. A key prediction of the model is that diagnostic judgments should not only reflect the empirical probability of cause given effect but should also depend on the reasoner's beliefs about the existence and strength of the link between cause and effect. We confirmed this prediction in 2 studies and showed that our theory better accounts for human judgments than alternative theories of diagnostic reasoning. Overall, our findings support the view that in diagnostic reasoning people go "beyond the information given" and use the available data to make inferences on the (unobserved) causal rather than on the (observed) data level. (c) 2014 APA, all rights reserved.

From neural oscillations to reasoning ability: Simulating the effect of the theta-to-gamma cycle length ratio on individual scores in a figural analogy test.

PubMed

Chuderski, Adam; Andrelczyk, Krzysztof

2015-02-01

Several existing computational models of working memory (WM) have predicted a positive relationship (later confirmed empirically) between WM capacity and the individual ratio of theta to gamma oscillatory band lengths. These models assume that each gamma cycle represents one WM object (e.g., a binding of its features), whereas the theta cycle integrates such objects into the maintained list. As WM capacity strongly predicts reasoning, it might be expected that this ratio also predicts performance in reasoning tasks. However, no computational model has yet explained how the differences in the theta-to-gamma ratio found among adult individuals might contribute to their scores on a reasoning test. Here, we propose a novel model of how WM capacity constraints figural analogical reasoning, aimed at explaining inter-individual differences in reasoning scores in terms of the characteristics of oscillatory patterns in the brain. In the model, the gamma cycle encodes the bindings between objects/features and the roles they play in the relations processed. Asynchrony between consecutive gamma cycles results from lateral inhibition between oscillating bindings. Computer simulations showed that achieving the highest WM capacity required reaching the optimal level of inhibition. When too strong, this inhibition eliminated some bindings from WM, whereas, when inhibition was too weak, the bindings became unstable and fell apart or became improperly grouped. The model aptly replicated several empirical effects and the distribution of individual scores, as well as the patterns of correlations found in the 100-people sample attempting the same reasoning task. Most importantly, the model's reasoning performance strongly depended on its theta-to-gamma ratio in same way as the performance of human participants depended on their WM capacity. The data suggest that proper regulation of oscillations in the theta and gamma bands may be crucial for both high WM capacity and effective complex cognition. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Students' Initial Knowledge of Electric and Magnetic Fields--More Profound Explanations and Reasoning Models for Undesired Conceptions

ERIC Educational Resources Information Center

Saarelainen, M.; Laaksonen, A.; Hirvonen, P. E.

2007-01-01

This study explores undergraduate students' understanding and reasoning models of electric and magnetic fields. The results indicate that the tested students had various alternative concepts in applying their reasoning to certain CSEM test questions. The total number of physics students tested at the beginning of the first course on…

Condition trees as a mechanism for communicating the meaning of uncertainties

NASA Astrophysics Data System (ADS)

Beven, Keith

2015-04-01

Uncertainty communication for environmental problems is fraught with difficulty for good epistemic reasons. The fact that most sources of uncertainty are subject to, and often dominated by, epistemic uncertainties means that the unthinking use of probability theory might actually be misleading and lead to false inference (even in some cases where the assumptions of a probabilistic error model might seem to be reasonably valid). This therefore creates problems in communicating the meaning of probabilistic uncertainties of model predictions to potential users (there are many examples in hydrology, hydraulics, climate change and other domains). It is suggested that one way of being more explicit about the meaning of uncertainties is to associate each type of application with a condition tree of assumptions that need to be made in producing an estimate of uncertainty. The condition tree then provides a basis for discussion and communication of assumptions about uncertainties with users. Agreement of assumptions (albeit generally at some institutional level) will provide some buy-in on the part of users, and a basis for commissioning of future studies. Even in some relatively well-defined problems, such as mapping flood risk, such a condition tree can be rather extensive, but by making each step in the tree explicit then an audit trail is established for future reference. This can act to provide focus in the exercise of agreeing more realistic assumptions.

Remarks on Height-Diameter Modeling

Treesearch

Lei Yuancai; Bernard R. Parresol

2001-01-01

Height-diameter model forms in earlier published papers are examined. The selection criteria used in height-diameter model forms are not reasonable when considering tree biological growth pattern. During model selection, forms for height-diameter relationships should include consideration of both data-related and reasonable biological criteria, not just data-related...

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

ERIC Educational Resources Information Center

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

2012-01-01

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

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

A strategy to improve the identification reliability of the chemical constituents by high-resolution mass spectrometry-based isomer structure prediction combined with a quantitative structure retention relationship analysis: Phthalide compounds in Chuanxiong as a test case.

PubMed

Zhang, Qingqing; Huo, Mengqi; Zhang, Yanling; Qiao, Yanjiang; Gao, Xiaoyan

2018-06-01

High-resolution mass spectrometry (HRMS) provides a powerful tool for the rapid analysis and identification of compounds in herbs. However, the diversity and large differences in the content of the chemical constituents in herbal medicines, especially isomerisms, are a great challenge for mass spectrometry-based structural identification. In the current study, a new strategy for the structural characterization of potential new phthalide compounds was proposed by isomer structure predictions combined with a quantitative structure-retention relationship (QSRR) analysis using phthalide compounds in Chuanxiong as an example. This strategy consists of three steps. First, the structures of phthalide compounds were reasonably predicted on the basis of the structure features and MS/MS fragmentation patterns: (1) the collected raw HRMS data were preliminarily screened by an in-house database; (2) the MS/MS fragmentation patterns of the analogous compounds were summarized; (3) the reported phthalide compounds were identified, and the structures of the isomers were reasonably predicted. Second, the QSRR model was established and verified using representative phthalide compound standards. Finally, the retention times of the predicted isomers were calculated by the QSRR model, and the structures of these peaks were rationally characterized by matching retention times of the detected chromatographic peaks and the predicted isomers. A multiple linear regression QSRR model in which 6 physicochemical variables were screened was built using 23 phthalide standards. The retention times of the phthalide isomers in Chuanxiong were well predicted by the QSRR model combined with reasonable structure predictions (R 2 =0.955). A total of 81 peaks were detected from Chuanxiong and assigned to reasonable structures, and 26 potential new phthalide compounds were structurally characterized. This strategy can improve the identification efficiency and reliability of homologues in complex materials. Copyright © 2018 Elsevier B.V. All rights reserved.

Modelling default and likelihood reasoning as probabilistic reasoning

NASA Technical Reports Server (NTRS)

Buntine, Wray

1990-01-01

A probabilistic analysis of plausible reasoning about defaults and about likelihood is presented. Likely and by default are in fact treated as duals in the same sense as possibility and necessity. To model these four forms probabilistically, a qualitative default probabilistic (QDP) logic and its quantitative counterpart DP are derived that allow qualitative and corresponding quantitative reasoning. Consistency and consequent results for subsets of the logics are given that require at most a quadratic number of satisfiability tests in the underlying propositional logic. The quantitative logic shows how to track the propagation error inherent in these reasoning forms. The methodology and sound framework of the system highlights their approximate nature, the dualities, and the need for complementary reasoning about relevance.

12 CFR Appendix B to Part 363 - Illustrative Management Reports

Code of Federal Regulations, 2011 CFR

2011-01-01

... with governance, management, and other personnel, designed to provide reasonable assurance regarding..., designed to provide reasonable assurance regarding the reliability of financial reporting and the... designed and effected by those charged with governance, management, and other personnel, to provide...

12 CFR Appendix B to Part 363 - Illustrative Management Reports

Code of Federal Regulations, 2012 CFR

2012-01-01

... with governance, management, and other personnel, designed to provide reasonable assurance regarding..., designed to provide reasonable assurance regarding the reliability of financial reporting and the... designed and effected by those charged with governance, management, and other personnel, to provide...

12 CFR Appendix B to Part 363 - Illustrative Management Reports

Code of Federal Regulations, 2013 CFR

2013-01-01

... with governance, management, and other personnel, designed to provide reasonable assurance regarding..., designed to provide reasonable assurance regarding the reliability of financial reporting and the... designed and effected by those charged with governance, management, and other personnel, to provide...

12 CFR Appendix B to Part 363 - Illustrative Management Reports

Code of Federal Regulations, 2010 CFR

2010-01-01

... with governance, management, and other personnel, designed to provide reasonable assurance regarding..., designed to provide reasonable assurance regarding the reliability of financial reporting and the... designed and effected by those charged with governance, management, and other personnel, to provide...

12 CFR Appendix B to Part 363 - Illustrative Management Reports

Code of Federal Regulations, 2014 CFR

2014-01-01

... with governance, management, and other personnel, designed to provide reasonable assurance regarding..., designed to provide reasonable assurance regarding the reliability of financial reporting and the... designed and effected by those charged with governance, management, and other personnel, to provide...

Law and order: Assessing and enforcing compliance with ontological modeling principles in the Foundational Model of Anatomy

PubMed Central

Zhang, Songmao; Bodenreider, Olivier

2006-01-01

The objective of this study is to provide an operational definition of principles with which well-formed ontologies should comply. We define 15 such principles, related to classification (e.g., no hierarchical cycles are allowed; concepts have a reasonable number of children), incompatible relationships (e.g., two concepts cannot stand both in a taxonomic and partitive relation), dependence among concepts, and the co-dependence of equivalent sets of relations. Implicit relations—embedded in concept names or inferred from a combination of explicit relations—are used in this process in addition to the relations explicitly represented. As a case study, we investigate the degree to which the Foundational Model of Anatomy (FMA)—a large ontology of anatomy—complies with these 15 principles. The FMA succeeds in complying with all the principles: totally with one and mostly with the others. Reasons for non-compliance are analyzed and suggestions are made for implementing effective enforcement mechanisms in ontology development environments. The limitations of this study are also discussed. PMID:16144698

Reasons to temper enthusiasm about open access nursing journals.

PubMed

de Jong, Gideon

2017-04-01

Open access is a relatively new phenomenon within nursing science. Several papers from various nursing journals have been published recently on the disadvantages of the traditional model of purchasing proprietary fee-based databases to access scholarly information. Just few nursing scholars are less optimistic about the possible benefits of open access nursing journals. A critical reflection on the merits and pitfalls of open access journals along insights from the literature and personal opinion. Two arguments are discussed, providing justification for tempering enthusiasm about open access journals. First, only research groups with sufficient financial resources can publish in open access journals. Second, open access has conflicting incentives, where the aim is to expand production at the expense of publishing quality articles; a business model that fits well into a neoliberal discourse. There are valid reasons to criticise the traditional publishers for the excessive costs of a single article, therefore preventing the dissemination of scholarly nursing information. On the contrary, the business model of open access publishers is no less imbued with the neoliberal tendency of lining the pockets.

Using an ecological ethics framework to make decisions about the relocation of wildlife.

PubMed

McCoy, Earl D; Berry, Kristin

2008-12-01

Relocation is an increasingly prominent conservation tool for a variety of wildlife, but the technique also is controversial, even among conservation practitioners. An organized framework for addressing the moral dilemmas often accompanying conservation actions such as relocation has been lacking. Ecological ethics may provide such a framework and appears to be an important step forward in aiding ecological researchers and biodiversity managers to make difficult moral choices. A specific application of this framework can make the reasoning process more transparent and give more emphasis to the strong sentiments about non-human organisms held by many potential users. Providing an example of the application of the framework may also increase the appeal of the reasoning process to ecological researchers and biodiversity managers. Relocation as a conservation action can be accompanied by a variety of moral dilemmas that reflect the interconnection of values, ethical positions, and conservation decisions. A model that is designed to address moral dilemmas arising from relocation of humans provides/demonstrates/illustrates a possible way to apply the ecological ethics framework and to involve practicing conservationists in the overall decision-making process.

Context Aware Middleware Architectures: Survey and Challenges

PubMed Central

Li, Xin; Eckert, Martina; Martinez, José-Fernán; Rubio, Gregorio

2015-01-01

Context aware applications, which can adapt their behaviors to changing environments, are attracting more and more attention. To simplify the complexity of developing applications, context aware middleware, which introduces context awareness into the traditional middleware, is highlighted to provide a homogeneous interface involving generic context management solutions. This paper provides a survey of state-of-the-art context aware middleware architectures proposed during the period from 2009 through 2015. First, a preliminary background, such as the principles of context, context awareness, context modelling, and context reasoning, is provided for a comprehensive understanding of context aware middleware. On this basis, an overview of eleven carefully selected middleware architectures is presented and their main features explained. Then, thorough comparisons and analysis of the presented middleware architectures are performed based on technical parameters including architectural style, context abstraction, context reasoning, scalability, fault tolerance, interoperability, service discovery, storage, security & privacy, context awareness level, and cloud-based big data analytics. The analysis shows that there is actually no context aware middleware architecture that complies with all requirements. Finally, challenges are pointed out as open issues for future work. PMID:26307988

"Clinical Reasoning Theater": A New Approach to Clinical Reasoning Education.

ERIC Educational Resources Information Center

Borleffs, Jan C. C.; Custers, Eugene J. F. M.; van Gijn, Jan; ten Gate, Olle Th. J.

2003-01-01

Describes a new approach to clinical reasoning education called clinical reasoning theater (CRT). With students as the audience, the doctor's clinical reasoning skills are modeled in CRT when he or she thinks aloud during conversations with the patient. Preliminary results of students' evaluations of the relevance of CRT reveal that they…

Secondary Students' Dynamic Modeling Processes: Analyzing, Reasoning About, Synthesizing, and Testing Models of Stream Ecosystems.

ERIC Educational Resources Information Center

Stratford, Steven J.; Krajeik, Joseph; Soloway, Elliot

This paper presents the results of a study of the cognitive strategies in which ninth-grade science students engaged as they used a learner-centered dynamic modeling tool (called Model-It) to make original models based upon stream ecosystem scenarios. The research questions were: (1) In what Cognitive Strategies for Modeling (analyzing, reasoning,…

Effects of Inquiry-Based Agriscience Instruction on Student Scientific Reasoning

ERIC Educational Resources Information Center

Thoron, Andrew C.; Myers, Brian E.

2012-01-01

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

Progress Towards an LES Wall Model Including Unresolved Roughness

NASA Astrophysics Data System (ADS)

Craft, Kyle; Redman, Andrew; Aikens, Kurt

2015-11-01

Wall models used in large eddy simulations (LES) are often based on theories for hydraulically smooth walls. While this is reasonable for many applications, there are also many where the impact of surface roughness is important. A previously developed wall model has been used primarily for jet engine aeroacoustics. However, jet simulations have not accurately captured thick initial shear layers found in some experimental data. This may partly be due to nozzle wall roughness used in the experiments to promote turbulent boundary layers. As a result, the wall model is extended to include the effects of unresolved wall roughness through appropriate alterations to the log-law. The methodology is tested for incompressible flat plate boundary layers with different surface roughness. Correct trends are noted for the impact of surface roughness on the velocity profile. However, velocity deficit profiles and the Reynolds stresses do not collapse as well as expected. Possible reasons for the discrepancies as well as future work will be presented. This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number ACI-1053575. Computational resources on TACC Stampede were provided under XSEDE allocation ENG150001.

Can a minimalist model of wind forced baroclinic Rossby waves produce reasonable results?

NASA Astrophysics Data System (ADS)

Watanabe, Wandrey B.; Polito, Paulo S.; da Silveira, Ilson C. A.

2016-04-01

The linear theory predicts that Rossby waves are the large scale mechanism of adjustment to perturbations of the geophysical fluid. Satellite measurements of sea level anomaly (SLA) provided sturdy evidence of the existence of these waves. Recent studies suggest that the variability in the altimeter records is mostly due to mesoscale nonlinear eddies and challenges the original interpretation of westward propagating features as Rossby waves. The objective of this work is to test whether a classic linear dynamic model is a reasonable explanation for the observed SLA. A linear-reduced gravity non-dispersive Rossby wave model is used to estimate the SLA forced by direct and remote wind stress. Correlations between model results and observations are up to 0.88. The best agreement is in the tropical region of all ocean basins. These correlations decrease towards insignificance in mid-latitudes. The relative contributions of eastern boundary (remote) forcing and local wind forcing in the generation of Rossby waves are also estimated and suggest that the main wave forming mechanism is the remote forcing. Results suggest that linear long baroclinic Rossby wave dynamics explain a significant part of the SLA annual variability at least in the tropical oceans.

Ontology method for 3DGIS modeling

NASA Astrophysics Data System (ADS)

Sun, Min; Chen, Jun

2006-10-01

Data modeling is a baffling problem in 3DGIS, no satisfied solution has been provided until today, reason come from various sides. In this paper, a new solution named "Ontology method" is proposed. GIS traditional modeling method mainly focus on geometrical modeling, i.e., try to abstract geometry primitives for objects representation, this kind modeling method show it's awkward in 3DGIS modeling process. Ontology method begins modeling from establishing a set of ontology with different levels. The essential difference of this method is to swap the position of 'spatial data' and 'attribute data' in 2DGIS modeling process for 3DGIS modeling. Ontology method has great advantages in many sides, a system based on ontology is easy to realize interoperation for communication and data mining for knowledge deduction, in addition has many other advantages.

Weighting the Parameters, a Response to Bancel׳s "Searching for Global Consciousness: A Seventeen Year Exploration".

PubMed

Nelson, Roger

This brief report is a response to the article by Peter Bancel entitled "Searching for Global Consciousness: A Seventeen Year Exploration" in which he compares a goal orientation (GO) model with a field-like model he refers to as global consciousness (GC). He first attempts to exclude the latter, and then presents selected tests that compare the models. While the article appears to provide support for Bancel׳s conclusion that GC cannot explain the data and must be supplanted by GO, there are good reasons to believe this conclusion is premature at best. I address the vulnerable assumptions underlying Bancel׳s rejection of GC, and then provide multiple examples of parametric structure in the data, which cannot be attributed to GO, but are amenable to explanation by field-like models. Copyright © 2017 Elsevier Inc. All rights reserved.

What’s Driving Uncertainty? The Model or the Model Parameters (What’s Driving Uncertainty? The influences of model and model parameters in data analysis)

DOE PAGES

Anderson-Cook, Christine Michaela

2017-03-01

Here, one of the substantial improvements to the practice of data analysis in recent decades is the change from reporting just a point estimate for a parameter or characteristic, to now including a summary of uncertainty for that estimate. Understanding the precision of the estimate for the quantity of interest provides better understanding of what to expect and how well we are able to predict future behavior from the process. For example, when we report a sample average as an estimate of the population mean, it is good practice to also provide a confidence interval (or credible interval, if youmore » are doing a Bayesian analysis) to accompany that summary. This helps to calibrate what ranges of values are reasonable given the variability observed in the sample and the amount of data that were included in producing the summary.« less

Modeling Off-Nominal Behavior in SysML

NASA Technical Reports Server (NTRS)

Day, John; Donahue, Kenny; Ingham, Mitch; Kadesch, Alex; Kennedy, Kit; Post, Ethan

2012-01-01

Fault Management is an essential part of the system engineering process that is limited in its effectiveness by the ad hoc nature of the applied approaches and methods. Providing a rigorous way to develop and describe off-nominal behavior is a necessary step in the improvement of fault management, and as a result, will enable safe, reliable and available systems even as system complexity increases... The basic concepts described in this paper provide a foundation to build a larger set of necessary concepts and relationships for precise modeling of off-nominal behavior, and a basis for incorporating these ideas into the overall systems engineering process.. The simple FMEA example provided applies the modeling patterns we have developed and illustrates how the information in the model can be used to reason about the system and derive typical fault management artifacts.. A key insight from the FMEA work was the utility of defining failure modes as the "inverse of intent", and deriving this from the behavior models.. Additional work is planned to extend these ideas and capabilities to other types of relevant information and additional products.

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

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

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

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.

Nurses' clinical reasoning practices that support safe medication administration: An integrative review of the literature.

PubMed

Rohde, Emily; Domm, Elizabeth

2018-02-01

To review the current literature about nurses' clinical reasoning practices that support safe medication administration. The literature about medication administration frequently focuses on avoiding medication errors. Nurses' clinical reasoning used during medication administration to maintain medication safety receives less attention in the literature. As healthcare professionals, nurses work closely with patients, assessing and intervening to promote mediation safety prior to, during and after medication administration. They also provide discharge teaching about using medication safely. Nurses' clinical reasoning and practices that support medication safety are often invisible when the focus is medication errors avoidance. An integrative literature review was guided by Whittemore and Knafl's (Journal of Advanced Nursing, 5, 2005 and 546) five-stage review of the 11 articles that met review criteria. This review is modelled after Gaffney et al.'s (Journal of Clinical Nursing, 25, 2016 and 906) integrative review on medical error recovery. Health databases were accessed and systematically searched for research reporting nurses' clinical reasoning practices that supported safe medication administration. The level and quality of evidence of the included research articles were assessed using The Johns Hopkins Nursing Evidence-Based Practice Rating Scale©. Nurses have a central role in safe medication administration, including but not limited to risk awareness about the potential for medication errors. Nurses assess patients and their medication and use knowledge and clinical reasoning to administer medication safely. Results indicated nurses' use of clinical reasoning to maintain safe medication administration was inadequately articulated in 10 of 11 studies reviewed. Nurses are primarily responsible for safe medication administration. Nurses draw from their foundational knowledge of patient conditions and organisational processes and use clinical reasoning that supports safe medication practice. There was minimal evidence clearly articulating nurses' clinical reasoning used to support medication safety. This review focused on finding evidence of nurses' clinical reasoning that supported safe medication administration. © 2017 John Wiley & Sons Ltd.

Billing code algorithms to identify cases of peripheral artery disease from administrative data

PubMed Central

Fan, Jin; Arruda-Olson, Adelaide M; Leibson, Cynthia L; Smith, Carin; Liu, Guanghui; Bailey, Kent R; Kullo, Iftikhar J

2013-01-01

Objective To construct and validate billing code algorithms for identifying patients with peripheral arterial disease (PAD). Methods We extracted all encounters and line item details including PAD-related billing codes at Mayo Clinic Rochester, Minnesota, between July 1, 1997 and June 30, 2008; 22 712 patients evaluated in the vascular laboratory were divided into training and validation sets. Multiple logistic regression analysis was used to create an integer code score from the training dataset, and this was tested in the validation set. We applied a model-based code algorithm to patients evaluated in the vascular laboratory and compared this with a simpler algorithm (presence of at least one of the ICD-9 PAD codes 440.20–440.29). We also applied both algorithms to a community-based sample (n=4420), followed by a manual review. Results The logistic regression model performed well in both training and validation datasets (c statistic=0.91). In patients evaluated in the vascular laboratory, the model-based code algorithm provided better negative predictive value. The simpler algorithm was reasonably accurate for identification of PAD status, with lesser sensitivity and greater specificity. In the community-based sample, the sensitivity (38.7% vs 68.0%) of the simpler algorithm was much lower, whereas the specificity (92.0% vs 87.6%) was higher than the model-based algorithm. Conclusions A model-based billing code algorithm had reasonable accuracy in identifying PAD cases from the community, and in patients referred to the non-invasive vascular laboratory. The simpler algorithm had reasonable accuracy for identification of PAD in patients referred to the vascular laboratory but was significantly less sensitive in a community-based sample. PMID:24166724

Child Speech, Language and Communication Need Re-Examined in a Public Health Context: A New Direction for the Speech and Language Therapy Profession

ERIC Educational Resources Information Center

Law, James; Reilly, Sheena; Snow, Pamela C.

2013-01-01

Background: Historically speech and language therapy services for children have been framed within a rehabilitative framework with explicit assumptions made about providing therapy to individuals. While this is clearly important in many cases, we argue that this model needs revisiting for a number of reasons. First, our understanding of the nature…

Predicting and Understanding Korean High School Students' Science Track Choice: Testing the Theory of Reasoned Action by Structural Equation Modeling.

ERIC Educational Resources Information Center

Myeong, Jeon-ok; Crawley, Frank E.

The purpose of a study was to provide some practical and theoretical suggestions to science educators in the United States and Korea who are struggling to attract more students to study science and pursue science-related careers. Two research questions were addressed: (1) What are the determinants of Korean high-school students' track choice…

The DPAC Compensation Model: An Introductory Handbook.

DTIC Science & Technology

1987-04-01

introductory and advanced economics courses at the US Air Force Academy, he served for four years as an analyst and action officer in the ...introduces new users to the ACOL framework and provides some guidelines for choosing reasonable values for the four long-run parameters required to run the ...regression coefficients for ACOL and the civilian unemployment rate; for pilots, the number of " new " pilot

Life, Liberty, and the Pursuit of Happiness. Materials for Using American Issues Forum in the American History Classroom, Topic IX.

ERIC Educational Resources Information Center

New York State Education Dept., Albany. Bureau of Secondary Curriculum Development.

Four modules of classroom strategies provide suggestions for examining U.S. history in light of contemporary issues. "The Right to Life" uses the Karen Anne Quinlan case as a model for exploring moral, legal, and medical issues related to euthanasia. Students discuss the reasoning and viewpoints of various groups associated with the…

Personality and organizational influences on aerospace human performance

NASA Technical Reports Server (NTRS)

Helmreich, Robert L.

1989-01-01

Individual and organizational influences on performance in aerospace environments are discussed. A model of personality with demonstrated validity is described along with reasons why personality's effects on performance have been underestimated. Organizational forces including intergroup conflict and coercive pressures are also described. It is suggested that basic and applied research in analog situations is needed to provide necessary guidance for planning future space missions.

Update on matter radii of O-2417

NASA Astrophysics Data System (ADS)

Fortune, H. T.

2018-05-01

The appearance of new theoretical papers concerning matter radii of neutron-rich oxygen nuclei has prompted a return to this problem. New results provide no better agreement with experimental values than did previous calculations with a simple model. I maintain that there is no reason to adjust the 22O core in the 24O nucleus, and the case of 24O should be reexamined experimentally.

Reasoning in Reference Games: Individual- vs. Population-Level Probabilistic Modeling

PubMed Central

Franke, Michael; Degen, Judith

2016-01-01

Recent advances in probabilistic pragmatics have achieved considerable success in modeling speakers’ and listeners’ pragmatic reasoning as probabilistic inference. However, these models are usually applied to population-level data, and so implicitly suggest a homogeneous population without individual differences. Here we investigate potential individual differences in Theory-of-Mind related depth of pragmatic reasoning in so-called reference games that require drawing ad hoc Quantity implicatures of varying complexity. We show by Bayesian model comparison that a model that assumes a heterogenous population is a better predictor of our data, especially for comprehension. We discuss the implications for the treatment of individual differences in probabilistic models of language use. PMID:27149675

Langrangian model of nitrogen kinetics in the Chattahoochee river

USGS Publications Warehouse

Jobson, H.E.

1987-01-01

A Lagrangian reference frame is used to solve the convection-dispersion equation and interpret water-quality obtained from the Chattahoochee River. The model was calibrated using unsteady concentrations of organic nitrogen, ammonia, and nitrite plus nitrate obtained during June 1977 and verified using data obtained during August 1976. Reaction kinetics of the cascade type are shown to provide a reasonable description of the nitrogen-species processes in the Chattahoochee River. The conceptual model is easy to visualize in the physical sense and the output includes information that is not easily determined from an Eulerian approach, but which is very helpful in model calibration and data interpretation. For example, the model output allows one to determine which data are of most value in model calibration or verification.

Estimation of the contribution of private providers in tuberculosis case notification and treatment outcome in Pakistan.

PubMed

Chughtai, A A; Qadeer, E; Khan, W; Hadi, H; Memon, I A

2013-03-01

To improve involvement of the private sector in the national tuberculosis (TB) programme in Pakistan various public-private mix projects were set up between 2004 and 2009. A retrospective analysis of data was made to study 6 different public-private mix models for TB control in Pakistan and estimate the contribution of the various private providers to TB case notification and treatment outcome. The number of TB cases notified through the private sector increased significantly from 77 cases in 2004 to 37,656 in 2009. Among the models, the nongovernmental organization model made the greatest contribution to case notification (58.3%), followed by the hospital-based model (18.9%). Treatment success was highest for the district-led model (94.1%) and lowest for the hospital-based model (74.2%). The private sector made an important contribution to the national data through the various public-private mix projects. Issues of sustainability and the lack of treatment supporters are discussed as reasons for lack of success of some projects.

A clinical reasoning model focused on clients' behaviour change with reference to physiotherapists: its multiphase development and validation.

PubMed

Elvén, Maria; Hochwälder, Jacek; Dean, Elizabeth; Söderlund, Anne

2015-05-01

A biopsychosocial approach and behaviour change strategies have long been proposed to serve as a basis for addressing current multifaceted health problems. This emphasis has implications for clinical reasoning of health professionals. This study's aim was to develop and validate a conceptual model to guide physiotherapists' clinical reasoning focused on clients' behaviour change. Phase 1 consisted of the exploration of existing research and the research team's experiences and knowledge. Phases 2a and 2b consisted of validation and refinement of the model based on input from physiotherapy students in two focus groups (n = 5 per group) and from experts in behavioural medicine (n = 9). Phase 1 generated theoretical and evidence bases for the first version of a model. Phases 2a and 2b established the validity and value of the model. The final model described clinical reasoning focused on clients' behaviour change as a cognitive, reflective, collaborative and iterative process with multiple interrelated levels that included input from the client and physiotherapist, a functional behavioural analysis of the activity-related target behaviour and the selection of strategies for behaviour change. This unique model, theory- and evidence-informed, has been developed to help physiotherapists to apply clinical reasoning systematically in the process of behaviour change with their clients.

Modeling the Effects of Argument Length and Validity on Inductive and Deductive Reasoning

ERIC Educational Resources Information Center

Rotello, Caren M.; Heit, Evan

2009-01-01

In an effort to assess models of inductive reasoning and deductive reasoning, the authors, in 3 experiments, examined the effects of argument length and logical validity on evaluation of arguments. In Experiments 1a and 1b, participants were given either induction or deduction instructions for a common set of stimuli. Two distinct effects were…

Exploring students' patterns of reasoning

NASA Astrophysics Data System (ADS)

Matloob Haghanikar, Mojgan

As part of a collaborative study of the science preparation of elementary school teachers, we investigated the quality of students' reasoning and explored the relationship between sophistication of reasoning and the degree to which the courses were considered inquiry oriented. To probe students' reasoning, we developed open-ended written content questions with the distinguishing feature of applying recently learned concepts in a new context. We devised a protocol for developing written content questions that provided a common structure for probing and classifying students' sophistication level of reasoning. In designing our protocol, we considered several distinct criteria, and classified students' responses based on their performance for each criterion. First, we classified concepts into three types: Descriptive, Hypothetical, and Theoretical and categorized the abstraction levels of the responses in terms of the types of concepts and the inter-relationship between the concepts. Second, we devised a rubric based on Bloom's revised taxonomy with seven traits (both knowledge types and cognitive processes) and a defined set of criteria to evaluate each trait. Along with analyzing students' reasoning, we visited universities and observed the courses in which the students were enrolled. We used the Reformed Teaching Observation Protocol (RTOP) to rank the courses with respect to characteristics that are valued for the inquiry courses. We conducted logistic regression for a sample of 18courses with about 900 students and reported the results for performing logistic regression to estimate the relationship between traits of reasoning and RTOP score. In addition, we analyzed conceptual structure of students' responses, based on conceptual classification schemes, and clustered students' responses into six categories. We derived regression model, to estimate the relationship between the sophistication of the categories of conceptual structure and RTOP scores. However, the outcome variable with six categories required a more complicated regression model, known as multinomial logistic regression, generalized from binary logistic regression. With the large amount of collected data, we found that the likelihood of the higher cognitive processes were in favor of classes with higher measures on inquiry. However, the usage of more abstract concepts with higher order conceptual structures was less prevalent in higher RTOP courses.

Exact transition probabilities in a 6-state Landau–Zener system with path interference

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

Sinitsyn, Nikolai A.

2015-04-23

In this paper, we identify a nontrivial multistate Landau–Zener (LZ) model for which transition probabilities between any pair of diabatic states can be determined analytically and exactly. In the semiclassical picture, this model features the possibility of interference of different trajectories that connect the same initial and final states. Hence, transition probabilities are generally not described by the incoherent successive application of the LZ formula. Finally, we discuss reasons for integrability of this system and provide numerical tests of the suggested expression for the transition probability matrix.

Evaluation of a bulk calorimeter and heat balance for determination of supersonic combustor efficiency

NASA Technical Reports Server (NTRS)

Mcclinton, C. R.; Anderson, G. Y.

1980-01-01

Results are presented from the shakedown and evaluation test of a bulk calorimeter. The calorimeter is designed to quench the combustion at the exit of a direct-connect, hydrogen fueled, scramjet combustor model, and to provide the measurements necessary to perform an analysis of combustion efficiency. Results indicate that the calorimeter quenches reaction, that reasonable response times are obtained, and that the calculated combustion efficiency is repeatable within + or -3 percent and varies in a regular way with combustor model parameters such as injected fuel equivalence ratio.

Delaminations in composite plates under transverse impact loads - Experimental results

NASA Technical Reports Server (NTRS)

Finn, Scott R.; He, Ye-Fei; Springer, George S.

1993-01-01

Tests were performed measuring the locations and geometries of delaminations in Fiberite T300/976 graphite/epoxy, Fiberite IM7/977-2 graphite-toughened epoxy, and ICI APC-2 graphite/PEEK plates subjected to transverse impact loads. The data provide specific information on the effects of impactor velocity, impactor mass, material, thickness of back ply group, difference in fiber orientation between adjacent ply groups, plate thickness, and impactor nose radius. The data were compared to the results of the Finn-Springer model. The model was found to describe the data with reasonable accuracy.

An integrated water system model considering hydrological and biogeochemical processes at basin scale: model construction and application

NASA Astrophysics Data System (ADS)

Zhang, Y. Y.; Shao, Q. X.; Ye, A. Z.; Xing, H. T.

2014-08-01

Integrated water system modeling is a reasonable approach to provide scientific understanding and possible solutions to tackle the severe water crisis faced over the world and to promote the implementation of integrated river basin management. Such a modeling practice becomes more feasible nowadays due to better computing facilities and available data sources. In this study, the process-oriented water system model (HEXM) is developed by integrating multiple water related processes including hydrology, biogeochemistry, environment and ecology, as well as the interference of human activities. The model was tested in the Shaying River Catchment, the largest, highly regulated and heavily polluted tributary of Huai River Basin in China. The results show that: HEXM is well integrated with good performance on the key water related components in the complex catchments. The simulated daily runoff series at all the regulated and less-regulated stations matches observations, especially for the high and low flow events. The average values of correlation coefficient and coefficient of efficiency are 0.81 and 0.63, respectively. The dynamics of observed daily ammonia-nitrogen (NH4N) concentration, as an important index to assess water environmental quality in China, are well captured with average correlation coefficient of 0.66. Furthermore, the spatial patterns of nonpoint source pollutant load and grain yield are also simulated properly, and the outputs have good agreements with the statistics at city scale. Our model shows clear superior performance in both calibration and validation in comparison with the widely used SWAT model. This model is expected to give a strong reference for water system modeling in complex basins, and provide the scientific foundation for the implementation of integrated river basin management all over the world as well as the technical guide for the reasonable regulation of dams and sluices and environmental improvement in river basins.

Mental health assessment of rape offenders.

PubMed

Sarkar, Jaydip

2013-07-01

There is an urgent need for development of methods of assessment and management of sex offenders (rapists, child sex offenders, other sexual offenders, and murderers) to mount a society-wide battle against the scourge of sexual offences in India. This paper provides an overview of theories, models, and assessment methods of rapists. It draws upon literature from psychiatry, psychology, criminology, probation, and ethics to provide a framework for understanding reasons behind rape, how mental health issues are implicated, what mental health professionals can do to contribute to crime management, and why this is ethically right and proper.