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

ERIC Educational Resources Information Center

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

2012-01-01

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

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Current programs are developed under uncertain environments, as the underlying analyses are carried out on the basis of outdated and unreliable data.

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

ERIC Educational Resources Information Center

Cevik, Yasemin Demiraslan; Andre, Thomas

2013-01-01

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

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

ERIC Educational Resources Information Center

Khamparia, Aditya; Pandey, Babita

2017-01-01

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

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

PubMed

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

2015-06-01

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

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

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.

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

PubMed

Schmidt, Rainer; Gierl, Lothar

2002-01-01

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

Expert system for web based collaborative CAE

NASA Astrophysics Data System (ADS)

Hou, Liang; Lin, Zusheng

2006-11-01

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

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

NASA Technical Reports Server (NTRS)

King, James A.

1987-01-01

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

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.

A case-based assistant for clinical psychiatry expertise.

PubMed

Bichindaritz, I

1994-01-01

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

ROENTGEN: case-based reasoning and radiation therapy planning.

PubMed Central

Berger, J.

1992-01-01

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

Case-based Reasoning for Automotive Engine Performance Tune-up

NASA Astrophysics Data System (ADS)

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

2010-05-01

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

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

PubMed

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

2018-01-30

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

A new hybrid case-based reasoning approach for medical diagnosis systems.

PubMed

Sharaf-El-Deen, Dina A; Moawad, Ibrahim F; Khalifa, M E

2014-02-01

Case-Based Reasoning (CBR) has been applied in many different medical applications. Due to the complexities and the diversities of this domain, most medical CBR systems become hybrid. Besides, the case adaptation process in CBR is often a challenging issue as it is traditionally carried out manually by domain experts. In this paper, a new hybrid case-based reasoning approach for medical diagnosis systems is proposed to improve the accuracy of the retrieval-only CBR systems. The approach integrates case-based reasoning and rule-based reasoning, and also applies the adaptation process automatically by exploiting adaptation rules. Both adaptation rules and reasoning rules are generated from the case-base. After solving a new case, the case-base is expanded, and both adaptation and reasoning rules are updated. To evaluate the proposed approach, a prototype was implemented and experimented to diagnose breast cancer and thyroid diseases. The final results show that the proposed approach increases the diagnosing accuracy of the retrieval-only CBR systems, and provides a reliable accuracy comparing to the current breast cancer and thyroid diagnosis systems.

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.

Case-Based Reasoning in Mixed Paradigm Settings and with Learning

DTIC Science & Technology

1994-04-30

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

Secondary School Students' Understanding of Science and Their Socioscientific Reasoning

NASA Astrophysics Data System (ADS)

Karahan, Engin; Roehrig, Gillian

2017-08-01

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

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

PubMed

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

2011-08-01

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

A Qualitative Study about Performance Based Assesment Methods Used in Information Technologies Lesson

ERIC Educational Resources Information Center

Daghan, Gökhan; Akkoyunlu, Buket

2014-01-01

In this study, Information Technologies teachers' views and usage cases on performance based assesment methods (PBAMs) are examined. It is aimed to find out which of the PBAMs are used frequently or not used, preference reasons of these methods and opinions about the applicability of them. Study is designed with the phenomenological design which…

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

NASA Astrophysics Data System (ADS)

Stranieri, Andrew; Yearwood, John; Pham, Binh

1999-07-01

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

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

PubMed

Montaldo L, Gustavo; Herskovic L, Pedro

2013-07-01

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

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

PubMed Central

2014-01-01

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

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.

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Designing and Implementation of Fuzzy Case-based Reasoning System on Android Platform Using Electronic Discharge Summary of Patients with Chronic Kidney Diseases

PubMed Central

Tahmasebian, Shahram; Langarizadeh, Mostafa; Ghazisaeidi, Marjan; Mahdavi-Mazdeh, Mitra

2016-01-01

Introduction: Case-based reasoning (CBR) systems are one of the effective methods to find the nearest solution to the current problems. These systems are used in various spheres as well as industry, business, and economy. The medical field is not an exception in this regard, and these systems are nowadays used in the various aspects of diagnosis and treatment. Methodology: In this study, the effective parameters were first extracted from the structured discharge summary prepared for patients with chronic kidney diseases based on data mining method. Then, through holding a meeting with experts in nephrology and using data mining methods, the weights of the parameters were extracted. Finally, fuzzy system has been employed in order to compare the similarities of current case and previous cases, and the system was implemented on the Android platform. Discussion: The data on electronic discharge records of patients with chronic kidney diseases were entered into the system. The measure of similarity was assessed using the algorithm provided in the system, and then compared with other known methods in CBR systems. Conclusion: Developing Clinical fuzzy CBR system used in Knowledge management framework for registering specific therapeutic methods, Knowledge sharing environment for experts in a specific domain and Powerful tools at the point of care. PMID:27708490

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

PubMed

Schmidt, Rainer; Gierl, Lothar

2005-03-01

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

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

PubMed

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

2011-02-01

The paper studies the new learning technique called cost-sensitive case-based reasoning (CSCBR) incorporating unequal misclassification cost into CBR model. Conventional CBR is now considered as a suitable technique for diagnosis, prognosis and prescription in medicine. However it lacks the ability to reflect asymmetric misclassification and often assumes that the cost of a positive diagnosis (an illness) as a negative one (no illness) is the same with that of the opposite situation. Thus, the objective of this research is to overcome the limitation of conventional CBR and encourage applying CBR to many real world medical cases associated with costs of asymmetric misclassification errors. The main idea involves adjusting the optimal cut-off classification point for classifying the absence or presence of diseases and the cut-off distance point for selecting optimal neighbors within search spaces based on similarity distribution. These steps are dynamically adapted to new target cases using a genetic algorithm. We apply this proposed method to five real medical datasets and compare the results with two other cost-sensitive learning methods-C5.0 and CART. Our finding shows that the total misclassification cost of CSCBR is lower than other cost-sensitive methods in many cases. Even though the genetic algorithm has limitations in terms of unstable results and over-fitting training data, CSCBR results with GA are better overall than those of other methods. Also the paired t-test results indicate that the total misclassification cost of CSCBR is significantly less than C5.0 and CART for several datasets. We have proposed a new CBR method called cost-sensitive case-based reasoning (CSCBR) that can incorporate unequal misclassification costs into CBR and optimize the number of neighbors dynamically using a genetic algorithm. It is meaningful not only for introducing the concept of cost-sensitive learning to CBR, but also for encouraging the use of CBR in the medical area. The result shows that the total misclassification costs of CSCBR do not increase in arithmetic progression as the cost of false absence increases arithmetically, thus it is cost-sensitive. We also show that total misclassification costs of CSCBR are the lowest among all methods in four datasets out of five and the result is statistically significant in many cases. The limitation of our proposed CSCBR is confined to classify binary cases for minimizing misclassification cost because our proposed CSCBR is originally designed to classify binary case. Our future work extends this method for multi-classification which can classify more than two groups. Copyright © 2010 Elsevier B.V. All rights reserved.

Knowledge and intelligent computing system in medicine.

PubMed

Pandey, Babita; Mishra, R B

2009-03-01

Knowledge-based systems (KBS) and intelligent computing systems have been used in the medical planning, diagnosis and treatment. The KBS consists of rule-based reasoning (RBR), case-based reasoning (CBR) and model-based reasoning (MBR) whereas intelligent computing method (ICM) encompasses genetic algorithm (GA), artificial neural network (ANN), fuzzy logic (FL) and others. The combination of methods in KBS such as CBR-RBR, CBR-MBR and RBR-CBR-MBR and the combination of methods in ICM is ANN-GA, fuzzy-ANN, fuzzy-GA and fuzzy-ANN-GA. The combination of methods from KBS to ICM is RBR-ANN, CBR-ANN, RBR-CBR-ANN, fuzzy-RBR, fuzzy-CBR and fuzzy-CBR-ANN. In this paper, we have made a study of different singular and combined methods (185 in number) applicable to medical domain from mid 1970s to 2008. The study is presented in tabular form, showing the methods and its salient features, processes and application areas in medical domain (diagnosis, treatment and planning). It is observed that most of the methods are used in medical diagnosis very few are used for planning and moderate number in treatment. The study and its presentation in this context would be helpful for novice researchers in the area of medical expert system.

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

PubMed

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

2014-01-01

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

Index cost estimate based BIM method - Computational example for sports fields

NASA Astrophysics Data System (ADS)

Zima, Krzysztof

2017-07-01

The paper presents an example ofcost estimation in the early phase of the project. The fragment of relative database containing solution, descriptions, geometry of construction object and unit cost of sports facilities was shown. The Index Cost Estimate Based BIM method calculationswith use of Case Based Reasoning were presented, too. The article presentslocal and global similarity measurement and example of BIM based quantity takeoff process. The outcome of cost calculations based on CBR method was presented as a final result of calculations.

DERMA: A Melanoma Diagnosis Platform Based on Collaborative Multilabel Analog Reasoning

PubMed Central

Golobardes, Elisabet; Corral, Guiomar; Puig, Susana; Malvehy, Josep

2014-01-01

The number of melanoma cancer-related death has increased over the last few years due to the new solar habits. Early diagnosis has become the best prevention method. This work presents a melanoma diagnosis architecture based on the collaboration of several multilabel case-based reasoning subsystems called DERMA. The system has to face up several challenges that include data characterization, pattern matching, reliable diagnosis, and self-explanation capabilities. Experiments using subsystems specialized in confocal and dermoscopy images have provided promising results for helping experts to assess melanoma diagnosis. PMID:24578629

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

PubMed

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

2010-01-01

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

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

PubMed

Nagao, Noriko; Kadooka, Yasuhiro; Asai, Atsushi

2014-03-04

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

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

NASA Astrophysics Data System (ADS)

Demigha, Souâd.

2016-03-01

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

Teaching clinical reasoning: case-based and coached.

PubMed

Kassirer, Jerome P

2010-07-01

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

Collaborative Interactivity and Integrated Thinking in Brazilian Business Schools Using Cognitive Flexibility Hypertexts: The Panteon Project

ERIC Educational Resources Information Center

Lima, Marcos; Koehler, Matthew J.; Spiro, Rand J.

2004-01-01

In this article, we discuss how the Harvard Method of case study, Interactive Communication Technologies, and Cognitive Flexibility Theory may contribute to case-based learning about business decision-making. In particular, we are interested in designing learning environments that foster critical thinking, creativity, and reasoning that entertains…

Building Better Decision-Support by Using Knowledge Discovery.

ERIC Educational Resources Information Center

Jurisica, Igor

2000-01-01

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

Integration of Optimal Scheduling with Case-Based Planning.

DTIC Science & Technology

1995-08-01

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

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.

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

PubMed

Goodman, D

1997-01-01

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

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

Code of Federal Regulations, 2010 CFR

2010-04-01

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

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

Code of Federal Regulations, 2012 CFR

2012-04-01

... 26 Internal Revenue 5 2012-04-01 2011-04-01 true Reasonable funding methods. 1.412(c)(3)-1 Section...(c)(3)-1 Reasonable funding methods. (a) Introduction—(1) In general. This section prescribes rules for determining whether or not, in the case of an ongoing plan, a funding method is reasonable for...

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

Code of Federal Regulations, 2011 CFR

2011-04-01

... 26 Internal Revenue 5 2011-04-01 2011-04-01 false Reasonable funding methods. 1.412(c)(3)-1...(c)(3)-1 Reasonable funding methods. (a) Introduction—(1) In general. This section prescribes rules for determining whether or not, in the case of an ongoing plan, a funding method is reasonable for...

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

Code of Federal Regulations, 2013 CFR

2013-04-01

... 26 Internal Revenue 5 2013-04-01 2013-04-01 false Reasonable funding methods. 1.412(c)(3)-1...(c)(3)-1 Reasonable funding methods. (a) Introduction—(1) In general. This section prescribes rules for determining whether or not, in the case of an ongoing plan, a funding method is reasonable for...

[The reasons why 13 MK1 attachment were re-fabricated and some methods for improvement].

PubMed

Wu, Zhi-hong; Zhang, Xue-jun; Zhao, Jun

2013-12-01

To investigate the reasons why 13 MK1 attachment were re-fabricated and to suggest some improvement methods. Mechanics and denture production technology were reviewed in 13 cases with MK1 attachment denture to determine the causes of failure. In some cases, MK1 attachments were poorly designed, while in other cases problems were found during denture design and production process due to limited experiences at the initial stage. MK1 attachments were re-done based on the specific cause and the outcome was good after 1-1.5 years of follow-up. When using MK1 attachment, prosthodontists should be familiar with the characteristics and indications of MK1 attachment. Meanwhile, we should strengthen doctor-patient communication and follow up patients timely to improve the success rate of MK1 attached denture repair.

Case-Based Capture and Reuse of Aerospace Design Rationale

NASA Technical Reports Server (NTRS)

Leake, David B.

2001-01-01

The goal of this project was to apply artificial intelligence techniques to facilitate capture and reuse of aerospace design rationale. The project combined case-based reasoning (CBR) and concept maps (CMaps) to develop methods for capturing, organizing, and interactively accessing records of experiences encapsulating the methods and rationale underlying expert aerospace design, in order to bring the captured knowledge to bear to support future reasoning. The project's results contribute both principles and methods for effective design-aiding systems that aid capture and access of useful design knowledge. The project has been guided by the tenets that design-aiding systems must: (1) Leverage a designer's knowledge, rather than attempting to replace it; (2) Be able to reflect different designers' differing conceptualizations of the design task, and to clarify those conceptualizations to others; (3) Include capabilities to capture information both by interactive knowledge modeling and during normal use; and (4) Integrate into normal designer tasks as naturally and unobtrusive as possible.

Knowledge acquisition for case-based reasoning systems

NASA Technical Reports Server (NTRS)

Riesbeck, Christopher K.

1988-01-01

Case-based reasoning (CBR) is a simple idea: solve new problems by adapting old solutions to similar problems. The CBR approach offers several potential advantages over rule-based reasoning: rules are not combined blindly in a search for solutions, solutions can be explained in terms of concrete examples, and performance can improve automatically as new problems are solved and added to the case library. Moving CBR for the university research environment to the real world requires smooth interfaces for getting knowledge from experts. Described are the basic elements of an interface for acquiring three basic bodies of knowledge that any case-based reasoner requires: the case library of problems and their solutions, the analysis rules that flesh out input problem specifications so that relevant cases can be retrieved, and the adaptation rules that adjust old solutions to fit new problems.

Hybrid Filtering in Semantic Query Processing

ERIC Educational Resources Information Center

Jeong, Hanjo

2011-01-01

This dissertation presents a hybrid filtering method and a case-based reasoning framework for enhancing the effectiveness of Web search. Web search may not reflect user needs, intent, context, and preferences, because today's keyword-based search is lacking semantic information to capture the user's context and intent in posing the search query.…

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

NASA Technical Reports Server (NTRS)

Pulaski, Kirt; Casadaban, Cyprian

1988-01-01

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

Virtual TeleRehab: a case study.

PubMed

Pareto, Lena; Johansson, Britt; Zeller, Sally; Sunnerhagen, Katharina S; Rydmark, Martin; Broeren, Jurgen

2011-01-01

We examined the efficacy of a remotely based occupational therapy intervention. A 40-year-old woman who suffered a stroke participated in a telerehabilitation program. The intervention method is based on virtual reality gaming to enhance the training experience and to facilitate the relearning processes. The results indicate that Virtual TeleRehab is an effective method for motivational, economical, and practical reasons by combining game-based rehabilitation in the home with weekly distance meetings.

Cognitive problem solving patterns of medical students correlate with success in diagnostic case solutions.

PubMed

Kiesewetter, Jan; Ebersbach, René; Görlitz, Anja; Holzer, Matthias; Fischer, Martin R; Schmidmaier, Ralf

2013-01-01

Problem-solving in terms of clinical reasoning is regarded as a key competence of medical doctors. Little is known about the general cognitive actions underlying the strategies of problem-solving among medical students. In this study, a theory-based model was used and adapted in order to investigate the cognitive actions in which medical students are engaged when dealing with a case and how patterns of these actions are related to the correct solution. Twenty-three medical students worked on three cases on clinical nephrology using the think-aloud method. The transcribed recordings were coded using a theory-based model consisting of eight different cognitive actions. The coded data was analysed using time sequences in a graphical representation software. Furthermore the relationship between the coded data and accuracy of diagnosis was investigated with inferential statistical methods. The observation of all main actions in a case elaboration, including evaluation, representation and integration, was considered a complete model and was found in the majority of cases (56%). This pattern significantly related to the accuracy of the case solution (φ = 0.55; p<.001). Extent of prior knowledge was neither related to the complete model nor to the correct solution. The proposed model is suitable to empirically verify the cognitive actions of problem-solving of medical students. The cognitive actions evaluation, representation and integration are crucial for the complete model and therefore for the accuracy of the solution. The educational implication which may be drawn from this study is to foster students reasoning by focusing on higher level reasoning.

Candida endophthalmitis after heroin abuse.

PubMed

Malecaze, F; Arne, J L; Bec, P; Séguéla, J P; Linas, M D; Recco, P; Béssières, M H

1985-11-01

Three cases of ocular candidosis involving heroin abusers have been observed in 1983 in Toulouse department of ophthalmology. These three patients had used iranian brown heroin. Twenty similar cases have been published in these last years. This new pathology can be explained on two reasons. The first is that the drug abusers have some immunity pertubation; however, immunity exploration in these patients does not reveal any immunodeficiency. The second reason, certainly more important, is the method of using heroin. The diagnosis of Candida endophthalmitis of course based on clinical context must be proved by biological tests. Candida albicans is never identified in aqueous humor. For this reason, it seems very interesting to detect anti-candida antibodies in aqueous humor. It has been used as methods of dosage laser Nephelemetry for IgG and immunofluorescence for candidosis antibodies. The criterion used is similar to the toxoplasmosis coefficient established by Desmonts (3). In two cases, this test was the only way that permits us to have certitude of candidosis ocular diagnosis. Otherwise the observations show that anterior chamber punction is more significant when there is an anterior uveitis.

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

ERIC Educational Resources Information Center

Gauthier, Geneviève; Lajoie, Susanne P.

2014-01-01

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

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

NASA Astrophysics Data System (ADS)

Khussainova, Gulmira; Petrovic, Sanja; Jagannathan, Rupa

2015-05-01

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

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

PubMed Central

Liu, Yan; Xu, Zhen-Jun

2013-01-01

As a high-risk subindustry involved in construction projects, highway construction safety has experienced major developments in the past 20 years, mainly due to the lack of safe early warnings in Chinese construction projects. By combining the current state of early warning technology with the requirements of the State Administration of Work Safety and using case-based reasoning (CBR), this paper expounds on the concept and flow of highway construction safety early warnings based on CBR. The present study provides solutions to three key issues, index selection, accident cause association analysis, and warning degree forecasting implementation, through the use of association rule mining, support vector machine classifiers, and variable fuzzy qualitative and quantitative change criterion modes, which fully cover the needs of safe early warning systems. Using a detailed description of the principles and advantages of each method and by proving the methods' effectiveness and ability to act together in safe early warning applications, effective means and intelligent technology for a safe highway construction early warning system are established. PMID:24191134

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

PubMed

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

2013-01-01

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

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

PubMed

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

2012-08-01

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

Web-based unfolding cases: a strategy to enhance and evaluate clinical reasoning skills.

PubMed

Johnson, Gail; Flagler, Susan

2013-10-01

Clinical reasoning involves the use of both analytical and nonanalytical intuitive cognitive processes. Fostering student development of clinical reasoning skills and evaluating student performance in this cognitive arena can challenge educators. The use of Web-based unfolding cases is proposed as a strategy to address these challenges. Unfolding cases mimic real-life clinical situations by presenting only partial clinical information in sequential segments. Students receive immediate feedback after submitting a response to a given segment. The student's comparison of the desired and submitted responses provides information to enhance the development of clinical reasoning skills. Each student's set of case responses are saved for the instructor in an individual-student electronic file, providing a record of the student's knowledge and thinking processes for faculty evaluation. For the example case given, the approaches used to evaluate individual components of clinical reasoning are provided. Possible future uses of Web-based unfolding cases are described. Copyright 2013, SLACK Incorporated.

Identifying the drivers of liking by investigating the reasons for (dis)liking using CATA in cross-cultural context: a case study on barbecue sauce.

PubMed

Choi, Ji-Hye; Gwak, Mi-Jin; Chung, Seo-Jin; Kim, Kwang-Ok; O'Mahony, Michael; Ishii, Rie; Bae, Ye-Won

2015-06-01

The present study cross-culturally investigated the drivers of liking for traditional and ethnic chicken marinades using descriptive analysis and consumer taste tests incorporating the check-all-that-apply (CATA) method. Seventy-three Koreans and 86 US consumers participated. The tested sauces comprised three tomato-based sauces, a teriyaki-based sauce and a Korean spicy seasoning-based sauce. Chicken breasts were marinated with each of the five barbecue sauces, grilled and served for evaluation. Descriptive analysis and consumer taste tests were conducted. Consumers rated the acceptance on a hedonic scale and checked the reasons for (dis)liking by the CATA method for each sauce. A general linear model, multiple factor analysis and chi-square analysis were conducted using the data. The results showed that the preference orders of the samples between Koreans and US consumers were strikingly similar to each other. However, the reasons for (dis)liking the samples differed cross-culturally. The drivers of liking of two sauces sharing relatively similar sensory profiles but differing significantly in hedonic ratings were effectively delineated by reasons of (dis)liking CATA results. Reasons for (dis)liking CATA proved to be a powerful supporting method to understand the internal drivers of liking which can be overlooked by generic descriptive analysis. © 2014 Society of Chemical Industry.

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.

Casuistry as bioethical method: an empirical perspective.

PubMed

Braunack-Mayer, A

2001-07-01

This paper examines the role that casuistry, a model of bioethical reasoning revived by Jonsen and Toulmin, plays in ordinary moral reasoning. I address the question: 'What is the evidence for contemporary casuistry's claim that everyday moral reasoning is casuistic in nature?' The paper begins with a description of the casuistic method, and then reviews the empirical arguments Jonsen and Toulmin offer to show that every-day moral decision-making is casuistic. Finally, I present the results of qualitative research conducted with 15 general practitioners (GPs) in South Australia, focusing on the ways in which these GP participants used stories and anecdotes in their own moral reasoning. This research found that the GPs interviewed did use a form of casuistry when talking about ethical dilemmas. However, the GPs' homespun casuistry often lacked one central element of casuistic reasoning--clear paradigm cases on which to base comparisons. I conclude that casuistic reasoning does appear to play a role in every-day moral decision-making, but that it is a more subdued role than perhaps casuists would like.

Intelligent methods for the process parameter determination of plastic injection molding

NASA Astrophysics Data System (ADS)

Gao, Huang; Zhang, Yun; Zhou, Xundao; Li, Dequn

2018-03-01

Injection molding is one of the most widely used material processing methods in producing plastic products with complex geometries and high precision. The determination of process parameters is important in obtaining qualified products and maintaining product quality. This article reviews the recent studies and developments of the intelligent methods applied in the process parameter determination of injection molding. These intelligent methods are classified into three categories: Case-based reasoning methods, expert system- based methods, and data fitting and optimization methods. A framework of process parameter determination is proposed after comprehensive discussions. Finally, the conclusions and future research topics are discussed.

A case-based reasoning system based on weighted heterogeneous value distance metric for breast cancer diagnosis.

PubMed

Gu, Dongxiao; Liang, Changyong; Zhao, Huimin

2017-03-01

We present the implementation and application of a case-based reasoning (CBR) system for breast cancer related diagnoses. By retrieving similar cases in a breast cancer decision support system, oncologists can obtain powerful information or knowledge, complementing their own experiential knowledge, in their medical decision making. We observed two problems in applying standard CBR to this context: the abundance of different types of attributes and the difficulty in eliciting appropriate attribute weights from human experts. We therefore used a distance measure named weighted heterogeneous value distance metric, which can better deal with both continuous and discrete attributes simultaneously than the standard Euclidean distance, and a genetic algorithm for learning the attribute weights involved in this distance measure automatically. We evaluated our CBR system in two case studies, related to benign/malignant tumor prediction and secondary cancer prediction, respectively. Weighted heterogeneous value distance metric with genetic algorithm for weight learning outperformed several alternative attribute matching methods and several classification methods by at least 3.4%, reaching 0.938, 0.883, 0.933, and 0.984 in the first case study, and 0.927, 0.842, 0.939, and 0.989 in the second case study, in terms of accuracy, sensitivity×specificity, F measure, and area under the receiver operating characteristic curve, respectively. The evaluation result indicates the potential of CBR in the breast cancer diagnosis domain. Copyright © 2017 Elsevier B.V. All rights reserved.

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-05-25

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

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

ERIC Educational Resources Information Center

Cevik, Yasemin Demiraslan; Andre, Thomas

2013-01-01

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

THE USE OF ELECTRONIC DATA PROCESSING IN CORRECTIONS AND LAW ENFORCEMENT,

DTIC Science & Technology

Reviews the reasons, methods, accomplishments and goals of the use of electronic data processing in the fields of correction and law enforcement . Suggest...statistical and case history data in building a sounder theoretical base in the field of law enforcement . (Author)

Enabling the use of hereditary information from pedigree tools in medical knowledge-based systems.

PubMed

Gay, Pablo; López, Beatriz; Plà, Albert; Saperas, Jordi; Pous, Carles

2013-08-01

The use of family information is a key issue to deal with inheritance illnesses. This kind of information use to come in the form of pedigree files, which contain structured information as tree or graphs, which explains the family relationships. Knowledge-based systems should incorporate the information gathered by pedigree tools to assess medical decision making. In this paper, we propose a method to achieve such a goal, which consists on the definition of new indicators, and methods and rules to compute them from family trees. The method is illustrated with several case studies. We provide information about its implementation and integration on a case-based reasoning tool. The method has been experimentally tested with breast cancer diagnosis data. The results show the feasibility of our methodology. Copyright © 2013 Elsevier Inc. All rights reserved.

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

PubMed

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

2007-08-01

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

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

ERIC Educational Resources Information Center

Schmidt, Cecil

2007-01-01

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

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

PubMed

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

2016-03-01

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

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

NASA Astrophysics Data System (ADS)

Becker, Jörg; Bergener, Philipp; Räckers, Michael

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

Toward translational incremental similarity-based reasoning in breast cancer grading

NASA Astrophysics Data System (ADS)

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

2009-02-01

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

Clinical Case Studies in Psychoanalytic and Psychodynamic Treatment

PubMed Central

Willemsen, Jochem; Della Rosa, Elena; Kegerreis, Sue

2017-01-01

This manuscript provides a review of the clinical case study within the field of psychoanalytic and psychodynamic treatment. The method has been contested for methodological reasons and because it would contribute to theoretical pluralism in the field. We summarize how the case study method is being applied in different schools of psychoanalysis, and we clarify the unique strengths of this method and areas for improvement. Finally, based on the literature and on our own experience with case study research, we come to formulate nine guidelines for future case study authors: (1) basic information to include, (2) clarification of the motivation to select a particular patient, (3) information about informed consent and disguise, (4) patient background and context of referral or self-referral, (5) patient's narrative, therapist's observations and interpretations, (6) interpretative heuristics, (7) reflexivity and counter-transference, (8) leaving room for interpretation, and (9) answering the research question, and comparison with other cases. PMID:28210235

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

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.

Illness script development in pre-clinical education through case-based clinical reasoning training

PubMed Central

Keemink, Yvette; van Dijk, Savannah; ten Cate, Olle

2018-01-01

Objectives To assess illness script richness and maturity in preclinical students after they attended a specifically structured instructional format, i.e., a case based clinical reasoning (CBCR) course. Methods In a within-subject experimental design, medical students who had finished the CBCR course participated in an illness script experiment. In the first session, richness and maturity of students’ illness scripts for diseases discussed during the CBCR course were compared to illness script richness and maturity for similar diseases not included in the course. In the second session, diagnostic performance was tested, to test for differences between CBCR cases and non-CBCR cases. Scores on the CBCR course exam were related to both experimental outcomes. Results Thirty-two medical students participated. Illness script richness for CBCR diseases was almost 20% higher than for non-CBCR diseases, on average 14.47 (SD=3.25) versus 12.14 (SD=2.80), respectively (p<0.001). In addition, students provided more information on Enabling Conditions and less on Fault-related aspects of the disease. Diagnostic performance was better for the diseases discussed in the CBCR course, mean score 1.63 (SD=0.32) versus 1.15 (SD=0.29) for non-CBCR diseases (p<0.001). A significant correlation of exam results with recognition of CBCR cases was found (r=0.571, p<0.001), but not with illness script richness (r=–0.006, p=NS). Conclusions The CBCR-course fosters early development of clinical reasoning skills by increasing the illness script richness and diagnostic performance of pre-clinical students. However, these results are disease-specific and therefore we cannot conclude that students develop a more general clinical reasoning ability. PMID:29428911

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Applying Case-Based Reasoning in Knowledge Management to Support Organizational Performance

ERIC Educational Resources Information Center

Wang, Feng-Kwei

2006-01-01

Research and practice in human performance technology (HPT) has recently accelerated the search for innovative approaches to supplement or replace traditional training interventions for improving organizational performance. This article examines a knowledge management framework built upon the theories and techniques of case-based reasoning (CBR)…

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

Overview of psychiatric ethics IV: the method of casuistry.

PubMed

Robertson, Michael; Ryan, Christopher; Walter, Garry

2007-08-01

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

Ethical case deliberation and decision making.

PubMed

Gracia, Diego

2003-01-01

During the last thirty years different methods have been proposed in order to manage and resolve ethical quandaries, specially in the clinical setting. Some of these methodologies are based on the principles of Decision-making theory. Others looked to other philosophical traditions, like Principlism, Hermeneutics, Narrativism, Casuistry, Pragmatism, etc. This paper defends the view that deliberation is the cornerstone of any adequate methodology. This is due to the fact that moral decisions must take into account not only principles and ideas, but also emotions, values and beliefs. Deliberation is the process in which everyone concerned by the decision is considered a valid moral agent, obliged to give reasons for their own points of view, and to listen to the reasons of others. The goal of this process is not the reaching of a consensus but the enrichment of one's own point of view with that of the others, increasing in this way the maturity of one's own decision, in order to make it more wise or prudent. In many cases the members of a group of deliberation will differ in the final solution of the case, but the confrontation of their reasons will modify the perception of the problem of everyone. This is the profit of the process. Our moral decisions cannot be completely rational, due to the fact that they are influenced by feelings, values, beliefs, etc., but they must be reasonable, that is, wise and prudent. Deliberation is the main procedure to reach this goal. It obliges us to take others into account, respecting their different beliefs and values and prompting them to give reasons for their own points of view. This method has been traditional in Western clinical medicine all over its history, and it should be also the main procedure for clinical ethics.

In Search of a Pony: Sources, Methods, Outcomes, and Motivated Reasoning.

PubMed

Stone, Marc B

2018-05-01

It is highly desirable to be able to evaluate the effect of policy interventions. Such evaluations should have expected outcomes based upon sound theory and be carefully planned, objectively evaluated and prospectively executed. In many cases, however, assessments originate with investigators' poorly substantiated beliefs about the effects of a policy. Instead of designing studies that test falsifiable hypotheses, these investigators adopt methods and data sources that serve as little more than descriptions of these beliefs in the guise of analysis. Interrupted time series analysis is one of the most popular forms of analysis used to present these beliefs. It is intuitively appealing but, in most cases, it is based upon false analogies, fallacious assumptions and analytical errors.

The role of emotions in moral case deliberation: theory, practice, and methodology.

PubMed

Molewijk, Bert; Kleinlugtenbelt, Dick; Widdershoven, Guy

2011-09-01

In clinical moral decision making, emotions often play an important role. However, many clinical ethicists are ignorant, suspicious or even critical of the role of emotions in making moral decisions and in reflecting on them. This raises practical and theoretical questions about the understanding and use of emotions in clinical ethics support services. This paper presents an Aristotelian view on emotions and describes its application in the practice of moral case deliberation. According to Aristotle, emotions are an original and integral part of (virtue) ethics. Emotions are an inherent part of our moral reasoning and being, and therefore they should be an inherent part of any moral deliberation. Based on Aristotle's view, we examine five specific aspects of emotions: the description of emotions, the attitude towards emotions, the thoughts present in emotions, the reliability of emotions, and the reasonable principle that guides an emotion. We then discuss three ways of dealing with emotions in the process of moral case deliberation. Finally, we present an Aristotelian conversation method, and present practical experiences using this method. © 2011 Blackwell Publishing Ltd.

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

PubMed

Anderson, James G

2004-03-18

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

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

ERIC Educational Resources Information Center

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

2014-01-01

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

Detection of Natural Fractures from Observed Surface Seismic Data Based on a Linear-Slip Model

NASA Astrophysics Data System (ADS)

Chen, Huaizhen; Zhang, Guangzhi

2018-03-01

Natural fractures play an important role in migration of hydrocarbon fluids. Based on a rock physics effective model, the linear-slip model, which defines fracture parameters (fracture compliances) for quantitatively characterizing the effects of fractures on rock total compliance, we propose a method to detect natural fractures from observed seismic data via inversion for the fracture compliances. We first derive an approximate PP-wave reflection coefficient in terms of fracture compliances. Using the approximate reflection coefficient, we derive azimuthal elastic impedance as a function of fracture compliances. An inversion method to estimate fracture compliances from seismic data is presented based on a Bayesian framework and azimuthal elastic impedance, which is implemented in a two-step procedure: a least-squares inversion for azimuthal elastic impedance and an iterative inversion for fracture compliances. We apply the inversion method to synthetic and real data to verify its stability and reasonability. Synthetic tests confirm that the method can make a stable estimation of fracture compliances in the case of seismic data containing a moderate signal-to-noise ratio for Gaussian noise, and the test on real data reveals that reasonable fracture compliances are obtained using the proposed method.

42 CFR 405.502 - Criteria for determining reasonable charges.

Code of Federal Regulations, 2014 CFR

2014-10-01

...) of this section, in the case of services of assistants-at-surgery as defined in § 405.580 in teaching and non-teaching settings, charges that are not more than 16 percent of the prevailing charge in the... deficient payment amount. (v) The limit is either a specific dollar amount or is based on a special method...

Nurses' reasoning process during care planning taking pressure ulcer prevention as an example. A think-aloud study.

PubMed

Funkesson, Kajsa Helena; Anbäcken, Els-Marie; Ek, Anna-Christina

2007-09-01

Nurses' clinical reasoning is of great importance for the delivery of safe and efficient care. Pressure ulcer prevention allows a variety of aspects within nursing to be viewed. The aim of this study was to describe both the process and the content of nurses' reasoning during care planning at different nursing homes, using pressure ulcer prevention as an example. A qualitative research design was chosen. Seven different nursing homes within one community were included. Eleven registered nurses were interviewed. The methods used were think-aloud technique, protocol analysis and qualitative content analysis. Client simulation illustrating transition was used. The case used for care planning was in three parts covering the transition from hospital until 3 weeks in the nursing home. Most nurses in this study conducted direct and indirect reasoning in a wide range of areas in connection with pressure ulcer prevention. The reasoning focused different parts of the nursing process depending on part of the case. Complex assertations as well as strategies aiming to reduce cognitive strain were rare. Nurses involved in direct nursing care held a broader reasoning than consultant nurses. Both explanations and actions based on older ideas and traditions occurred. Reasoning concerning pressure ulcer prevention while care planning was dominated by routine thinking. Knowing the person over a period of time made a more complex reasoning possible. The nurses' experience, knowledge together with how close to the elderly the nurses work seem to be important factors that affect the content of reasoning.

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

PubMed

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

2011-04-01

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

The Effect of Teaching Medical Ethics on Medical Students' Moral Reasoning.

ERIC Educational Resources Information Center

Self, Donnie J; And Others

1989-01-01

A study of the effect of incorporating medical ethics into the medical curriculum and comparing two teaching methods (lecture and case studies) found higher moral reasoning after instruction, but neither method was significantly more effective. (Author/MSE)

Hybrid neural intelligent system to predict business failure in small-to-medium-size enterprises.

PubMed

Borrajo, M Lourdes; Baruque, Bruno; Corchado, Emilio; Bajo, Javier; Corchado, Juan M

2011-08-01

During the last years there has been a growing need of developing innovative tools that can help small to medium sized enterprises to predict business failure as well as financial crisis. In this study we present a novel hybrid intelligent system aimed at monitoring the modus operandi of the companies and predicting possible failures. This system is implemented by means of a neural-based multi-agent system that models the different actors of the companies as agents. The core of the multi-agent system is a type of agent that incorporates a case-based reasoning system and automates the business control process and failure prediction. The stages of the case-based reasoning system are implemented by means of web services: the retrieval stage uses an innovative weighted voting summarization of self-organizing maps ensembles-based method and the reuse stage is implemented by means of a radial basis function neural network. An initial prototype was developed and the results obtained related to small and medium enterprises in a real scenario are presented.

La mejora de la educacion infantil desde el analisis del pensamiento practico de sus educadores. [The Improvement of Early Childhood Education from an Analysis of the Practical Thinking of Early Childhood Educators.

ERIC Educational Resources Information Center

Argos, Javier

2000-01-01

Discusses proposals for the innovation and development of early childhood education practice, based on findings from case studies on the practical knowledge of four experienced female early childhood educators. Argues that improving early childhood education should be based on its reasons and purposes rather than content or method. (JPB)

Philosophy of science and the diagnostic process.

PubMed

Willis, Brian H; Beebee, Helen; Lasserson, Daniel S

2013-10-01

This is an overview of the principles that underpin philosophy of science and how they may provide a framework for the diagnostic process. Although philosophy dates back to antiquity, it is only more recently that philosophers have begun to enunciate the scientific method. Since Aristotle formulated deduction, other modes of reasoning including induction, inference to best explanation, falsificationism, theory-laden observations and Bayesian inference have emerged. Thus, rather than representing a single overriding dogma, the scientific method is a toolkit of ideas and principles of reasoning. Here we demonstrate that the diagnostic process is an example of science in action and is therefore subject to the principles encompassed by the scientific method. Although a number of the different forms of reasoning are used readily by clinicians in practice, without a clear understanding of their pitfalls and the assumptions on which they are based, it leaves doctors open to diagnostic error. We conclude by providing a case example from the medico-legal literature in which diagnostic errors were made, to illustrate how applying the scientific method may mitigate the chance for diagnostic error.

Trust-Guided Behavior Adaptation Using Case-Based Reasoning

DTIC Science & Technology

2015-08-01

the same behaviors were evaluated in each set. To account for this, the similarity function looks at the overlap between the two sets and ignores...interruptions would reduce the cost of case genera- tion. 6 Related Work Existing approaches for measuring inverse trust differ from our own in that...where a case- based reasoning system considers the reliability of a case’s source, also takes trust into account . Our work also has sim- ilarities

The Principle-Based Method of Practical Ethics.

PubMed

Spielthenner, Georg

2017-09-01

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

Bioethics education in clinical settings: theory and practice of the dilemma method of moral case deliberation.

PubMed

Stolper, Margreet; Molewijk, Bert; Widdershoven, Guy

2016-07-22

Moral Case Deliberation is a specific form of bioethics education fostering professionals' moral competence in order to deal with their moral questions. So far, few studies focus in detail on Moral Case Deliberation methodologies and their didactic principles. The dilemma method is a structured and frequently used method in Moral Case Deliberation that stimulates methodological reflection and reasoning through a systematic dialogue on an ethical issue experienced in practice. In this paper we present a case-study of a Moral Case Deliberation with the dilemma method in a health care institution for people with an intellectual disability, describing the theoretical background and the practical application of the dilemma method. The dilemma method focuses on moral experiences of participants concerning a concrete dilemma in practice. By an in-depth description of each of the steps of the deliberation process, we elucidate the educational value and didactics of this specific method. The didactics and methodical steps of the dilemma method both supported and structured the dialogical reflection process of the participants. The process shows that the participants learned to recognize the moral dimension of the issue at stake and were able to distinguish various perspectives and reasons in a systematic manner. The facilitator played an important role in the learning process of the participants, by assisting them in focusing on and exploring moral aspects of the case. The reflection and learning process, experienced by the participants, shows competency-based characteristics. The role of the facilitator is that of a Socratic teacher with specific knowledge and skills, fostering reflection, inquiry and dialogue. The specific didactics of the dilemma method is well suited for teaching bioethics in clinical settings. The dilemma method follows an inductive learning approach through a dialogical moral inquiry in which participants develop not only knowledge but also skills, attitude and character. The role of a trained facilitator and a specific view on teaching and practicing ethics are essential when using the dilemma method in teaching health care professionals how to reflect on their own moral issues in practice.

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.

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

PubMed

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

2016-08-22

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

Evidence Arguments for Using Formal Methods in Software Certification

NASA Technical Reports Server (NTRS)

Denney, Ewen W.; Pai, Ganesh

2013-01-01

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

Defense Small Business Innovation Research Program (SBIR). Volume 4. Defense Agency Projects, Abstracts of Phase 1 Awards from FY 1989 SBIR Solicitation

DTIC Science & Technology

1990-04-01

EXPLOSIVE ACTIVITY . FINDINGS AND MEASUREMENTS FROM EACH IMAGE WILL BE COMBINED IN A GEOGRAPHIC INFORMATION DATA BASE . VARIOUS IMAGE AND MAP PROJECTS WILL BE...PROPOSAL OF LAND MINES DETECTION BY A NUCLEAR ACTIVATION METHOD IS BASED ON A NEW EXTREMELY INTENSE, COMPACT PULSED SOURCE OF 14.1 MeV NEUTRONS (WITH A...CONVENTIONAL KNOWLEDGE- BASED SYSTEMS TOPIC# 38 OFFICE: PM/SBIR IDENT#: 33862 CASE- BASED REASONING (CBR) REPRESENTS A POWERFUL NEW PARADIGM FOR BUILDING EXPERT

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

PubMed

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

2014-01-01

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

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

PubMed Central

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

2014-01-01

Objective Clinical reasoning is usually taught using a problem-solving approach, which is widely adopted in medical education. However, learning through problem solving is difficult as a result of the contextualization and dynamic aspects of actual problems. Moreover, knowledge acquired from problem-solving practice tends to be inert and fragmented. This study proposed a computer-based cognitive representation approach that externalizes and facilitates the complex processes in learning clinical reasoning. The approach is operationalized in a computer-based cognitive representation tool that involves argument mapping to externalize the problem-solving process and concept mapping to reveal the knowledge constructed from the problems. Methods Twenty-nine Year 3 or higher students from a medical school in east China participated in the study. Participants used the proposed approach implemented in an e-learning system to complete four learning cases in 4 weeks on an individual basis. For each case, students interacted with the problem to capture critical data, generate and justify hypotheses, make a diagnosis, recall relevant knowledge, and update their conceptual understanding of the problem domain. Meanwhile, students used the computer-based cognitive representation tool to articulate and represent the key elements and their interactions in the learning process. Results A significant improvement was found in students’ learning products from the beginning to the end of the study, consistent with students’ report of close-to-moderate progress in developing problem-solving and knowledge-construction abilities. No significant differences were found between the pretest and posttest scores with the 4-week period. The cognitive representation approach was found to provide more formative assessment. Conclusions The computer-based cognitive representation approach improved the learning of clinical reasoning in both problem solving and knowledge construction. PMID:25518871

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

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

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

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

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

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

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

PubMed

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

2015-08-01

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

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

PubMed

May, Stephen A

2013-01-01

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

Fan broadband interaction noise modeling using a low-order method

NASA Astrophysics Data System (ADS)

Grace, S. M.

2015-06-01

A low-order method for simulating broadband interaction noise downstream of the fan stage in a turbofan engine is explored in this paper. The particular noise source of interest is due to the interaction of the fan rotor wake with the fan exit guide vanes (FEGVs). The vanes are modeled as flat plates and the method utilizes strip theory relying on unsteady aerodynamic cascade theory at each strip. This paper shows predictions for 6 of the 9 cases from NASA's Source Diagnostic Test (SDT) and all 4 cases from the 2014 Fan Broadband Workshop Fundamental Case 2 (FC2). The turbulence in the rotor wake is taken from hot-wire data for the low speed SDT cases and the FC2 cases. Additionally, four different computational simulations of the rotor wake flow for all of the SDT rotor speeds have been used to determine the rotor wake turbulence parameters. Comparisons between predictions based on the different inputs highlight the possibility of a potential effect present in the hot-wire data for the SDT as well as the importance of accurately describing the turbulence length scale when using this model. The method produces accurate predictions of the spectral shape for all of the cases. It also predicts reasonably well all of the trends that can be considered based on the included cases such as vane geometry, vane count, turbulence level, and rotor speed.

Application of Psychological Theories in Agent-Based Modeling: The Case of the Theory of Planned Behavior.

PubMed

Scalco, Andrea; Ceschi, Andrea; Sartori, Riccardo

2018-01-01

It is likely that computer simulations will assume a greater role in the next future to investigate and understand reality (Rand & Rust, 2011). Particularly, agent-based models (ABMs) represent a method of investigation of social phenomena that blend the knowledge of social sciences with the advantages of virtual simulations. Within this context, the development of algorithms able to recreate the reasoning engine of autonomous virtual agents represents one of the most fragile aspects and it is indeed crucial to establish such models on well-supported psychological theoretical frameworks. For this reason, the present work discusses the application case of the theory of planned behavior (TPB; Ajzen, 1991) in the context of agent-based modeling: It is argued that this framework might be helpful more than others to develop a valid representation of human behavior in computer simulations. Accordingly, the current contribution considers issues related with the application of the model proposed by the TPB inside computer simulations and suggests potential solutions with the hope to contribute to shorten the distance between the fields of psychology and computer science.

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

ERIC Educational Resources Information Center

He, Wu

2014-01-01

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

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

NASA Technical Reports Server (NTRS)

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

1997-01-01

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

A Hybrid Approach Using Case-Based Reasoning and Rule-Based Reasoning to Support Cancer Diagnosis: A Pilot Study.

PubMed

Saraiva, Renata M; Bezerra, João; Perkusich, Mirko; Almeida, Hyggo; Siebra, Clauirton

2015-01-01

Recently there has been an increasing interest in applying information technology to support the diagnosis of diseases such as cancer. In this paper, we present a hybrid approach using case-based reasoning (CBR) and rule-based reasoning (RBR) to support cancer diagnosis. We used symptoms, signs, and personal information from patients as inputs to our model. To form specialized diagnoses, we used rules to define the input factors' importance according to the patient's characteristics. The model's output presents the probability of the patient having a type of cancer. To carry out this research, we had the approval of the ethics committee at Napoleão Laureano Hospital, in João Pessoa, Brazil. To define our model's cases, we collected real patient data at Napoleão Laureano Hospital. To define our model's rules and weights, we researched specialized literature and interviewed health professional. To validate our model, we used K-fold cross validation with the data collected at Napoleão Laureano Hospital. The results showed that our approach is an effective CBR system to diagnose cancer.

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

NASA Astrophysics Data System (ADS)

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

2010-05-01

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

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

PubMed

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

2016-11-01

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

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

PubMed

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

2016-12-01

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

CDMBE: A Case Description Model Based on Evidence

PubMed Central

Zhu, Jianlin; Yang, Xiaoping; Zhou, Jing

2015-01-01

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

Estimating the capacity value of concentrating solar power plants: A case study of the southwestern United States

DOE PAGES

Madaeni, Seyed Hossein; Sioshansi, Ramteen; Denholm, Paul

2012-01-27

Here, we estimate the capacity value of concentrating solar power (CSP) plants without thermal energy storage in the southwestern U.S. Our results show that CSP plants have capacity values that are between 45% and 95% of maximum capacity, depending on their location and configuration. We also examine the sensitivity of the capacity value of CSP to a number of factors and show that capacity factor-based methods can provide reasonable approximations of reliability-based estimates.

A viewpoint-based case-based reasoning approach utilising an enterprise architecture ontology for experience management

NASA Astrophysics Data System (ADS)

Martin, Andreas; Emmenegger, Sandro; Hinkelmann, Knut; Thönssen, Barbara

2017-04-01

The accessibility of project knowledge obtained from experiences is an important and crucial issue in enterprises. This information need about project knowledge can be different from one person to another depending on the different roles he or she has. Therefore, a new ontology-based case-based reasoning (OBCBR) approach that utilises an enterprise ontology is introduced in this article to improve the accessibility of this project knowledge. Utilising an enterprise ontology improves the case-based reasoning (CBR) system through the systematic inclusion of enterprise-specific knowledge. This enterprise-specific knowledge is captured using the overall structure given by the enterprise ontology named ArchiMEO, which is a partial ontological realisation of the enterprise architecture framework (EAF) ArchiMate. This ontological representation, containing historical cases and specific enterprise domain knowledge, is applied in a new OBCBR approach. To support the different information needs of different stakeholders, this OBCBR approach has been built in such a way that different views, viewpoints, concerns and stakeholders can be considered. This is realised using a case viewpoint model derived from the ISO/IEC/IEEE 42010 standard. The introduced approach was implemented as a demonstrator and evaluated using an application case that has been elicited from a business partner in the Swiss research project.

Cognition of an expert tackling an unfamiliar conceptual physics problem

NASA Astrophysics Data System (ADS)

Schuster, David; Undreiu, Adriana

2009-11-01

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

Computer aided fixture design - A case based approach

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

[Behavioral phenotypes: cognitive and emotional explanation].

PubMed

Pérez-Alvarez, F; Timoneda-Gallart, C

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

Understanding and Evaluating Assurance Cases

NASA Technical Reports Server (NTRS)

Rushby, John; Xu, Xidong; Rangarajan, Murali; Weaver, Thomas L.

2015-01-01

Assurance cases are a method for providing assurance for a system by giving an argument to justify a claim about the system, based on evidence about its design, development, and tested behavior. In comparison with assurance based on guidelines or standards (which essentially specify only the evidence to be produced), the chief novelty in assurance cases is provision of an explicit argument. In principle, this can allow assurance cases to be more finely tuned to the specific circumstances of the system, and more agile than guidelines in adapting to new techniques and applications. The first part of this report (Sections 1-4) provides an introduction to assurance cases. Although this material should be accessible to all those with an interest in these topics, the examples focus on software for airborne systems, traditionally assured using the DO-178C guidelines and its predecessors. A brief survey of some existing assurance cases is provided in Section 5. The second part (Section 6) considers the criteria, methods, and tools that may be used to evaluate whether an assurance case provides sufficient confidence that a particular system or service is fit for its intended use. An assurance case cannot provide unequivocal "proof" for its claim, so much of the discussion focuses on the interpretation of such less-than-definitive arguments, and on methods to counteract confirmation bias and other fallibilities in human reasoning.

A method based on the Jacobi tau approximation for solving multi-term time-space fractional partial differential equations

NASA Astrophysics Data System (ADS)

Bhrawy, A. H.; Zaky, M. A.

2015-01-01

In this paper, we propose and analyze an efficient operational formulation of spectral tau method for multi-term time-space fractional differential equation with Dirichlet boundary conditions. The shifted Jacobi operational matrices of Riemann-Liouville fractional integral, left-sided and right-sided Caputo fractional derivatives are presented. By using these operational matrices, we propose a shifted Jacobi tau method for both temporal and spatial discretizations, which allows us to present an efficient spectral method for solving such problem. Furthermore, the error is estimated and the proposed method has reasonable convergence rates in spatial and temporal discretizations. In addition, some known spectral tau approximations can be derived as special cases from our algorithm if we suitably choose the corresponding special cases of Jacobi parameters θ and ϑ. Finally, in order to demonstrate its accuracy, we compare our method with those reported in the literature.

WE-AB-207A-02: John’s Equation Based Consistency Condition and Incomplete Projection Restoration Upon Circular Orbit CBCT

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

Ma, J; Qi, H; Wu, S

Purpose: In transmitted X-ray tomography imaging, projections are sometimes incomplete due to a variety of reasons, such as geometry inaccuracy, defective detector cells, etc. To address this issue, we have derived a direct consistency condition based on John’s Equation, and proposed a method to effectively restore incomplete projections based on this consistency condition. Methods: Through parameter substitutions, we have derived a direct consistency condition equation from John’s equation, in which the left side is only projection derivative of view and the right side is projection derivative of other geometrical parameters. Based on this consistency condition, a projection restoration method ismore » proposed, which includes five steps: 1) Forward projecting reconstructed image and using linear interpolation to estimate the incomplete projections as the initial result; 2) Performing Fourier transform on the projections; 3) Restoring the incomplete frequency data using the consistency condition equation; 4) Performing inverse Fourier transform; 5) Repeat step 2)∼4) until our criteria is met to terminate the iteration. Results: A beam-blocking-based scatter correction case and a bad-pixel correction case were used to demonstrate the efficacy and robustness of our restoration method. The mean absolute error (MAE), signal noise ratio (SNR) and mean square error (MSE) were employed as our evaluation metrics of the reconstructed images. For the scatter correction case, the MAE is reduced from 63.3% to 71.7% with 4 iterations. Compared with the existing Patch’s method, the MAE of our method is further reduced by 8.72%. For the bad-pixel case, the SNR of the reconstructed image by our method is increased from 13.49% to 21.48%, with the MSE being decreased by 45.95%, compared with linear interpolation method. Conclusion: Our studies have demonstrated that our restoration method based on the new consistency condition could effectively restore the incomplete projections, especially for their high frequency component.« less

Verifying Hybrid Systems Modeled as Timed Automata: A Case Study

DTIC Science & Technology

1997-03-01

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

16 CFR 306.5 - Automotive fuel rating.

Code of Federal Regulations, 2010 CFR

2010-01-01

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

A personalized health-monitoring system for elderly by combining rules and case-based reasoning.

PubMed

Ahmed, Mobyen Uddin

2015-01-01

Health-monitoring system for elderly in home environment is a promising solution to provide efficient medical services that increasingly interest by the researchers within this area. It is often more challenging when the system is self-served and functioning as personalized provision. This paper proposed a personalized self-served health-monitoring system for elderly in home environment by combining general rules with a case-based reasoning approach. Here, the system generates feedback, recommendation and alarm in a personalized manner based on elderly's medical information and health parameters such as blood pressure, blood glucose, weight, activity, pulse, etc. A set of general rules has used to classify individual health parameters. The case-based reasoning approach is used to combine all different health parameters, which generates an overall classification of health condition. According to the evaluation result considering 323 cases and k=2 i.e., top 2 most similar retrieved cases, the sensitivity, specificity and overall accuracy are achieved as 90%, 97% and 96% respectively. The preliminary result of the system is acceptable since the feedback; recommendation and alarm messages are personalized and differ from the general messages. Thus, this approach could be possibly adapted for other situations in personalized elderly monitoring.

Patients who make terrible therapeutic choices.

PubMed

Curzer, Howard J

2014-01-01

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

Case-based reasoning using electronic health records efficiently identifies eligible patients for clinical trials

PubMed Central

Miotto, Riccardo

2015-01-01

Objective To develop a cost-effective, case-based reasoning framework for clinical research eligibility screening by only reusing the electronic health records (EHRs) of minimal enrolled participants to represent the target patient for each trial under consideration. Materials and Methods The EHR data—specifically diagnosis, medications, laboratory results, and clinical notes—of known clinical trial participants were aggregated to profile the “target patient” for a trial, which was used to discover new eligible patients for that trial. The EHR data of unseen patients were matched to this “target patient” to determine their relevance to the trial; the higher the relevance, the more likely the patient was eligible. Relevance scores were a weighted linear combination of cosine similarities computed over individual EHR data types. For evaluation, we identified 262 participants of 13 diversified clinical trials conducted at Columbia University as our gold standard. We ran a 2-fold cross validation with half of the participants used for training and the other half used for testing along with other 30 000 patients selected at random from our clinical database. We performed binary classification and ranking experiments. Results The overall area under the ROC curve for classification was 0.95, enabling the highlight of eligible patients with good precision. Ranking showed satisfactory results especially at the top of the recommended list, with each trial having at least one eligible patient in the top five positions. Conclusions This relevance-based method can potentially be used to identify eligible patients for clinical trials by processing patient EHR data alone without parsing free-text eligibility criteria, and shows promise of efficient “case-based reasoning” modeled only on minimal trial participants. PMID:25769682

A Chaotic Ordered Hierarchies Consistency Analysis Performance Evaluation Model

NASA Astrophysics Data System (ADS)

Yeh, Wei-Chang

2013-02-01

The Hierarchies Consistency Analysis (HCA) is proposed by Guh in-cooperated along with some case study on a Resort to reinforce the weakness of Analytical Hierarchy Process (AHP). Although the results obtained enabled aid for the Decision Maker to make more reasonable and rational verdicts, the HCA itself is flawed. In this paper, our objective is to indicate the problems of HCA, and then propose a revised method called chaotic ordered HCA (COH in short) which can avoid problems. Since the COH is based upon Guh's method, the Decision Maker establishes decisions in a way similar to that of the original method.

CABINS: Case-based interactive scheduler

NASA Technical Reports Server (NTRS)

Miyashita, Kazuo; Sycara, Katia

1992-01-01

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

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

PubMed

Bazrafcan, Leila; Takmil, Farnaz; Shokrpour, Nasrin

2018-06-18

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

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

PubMed

Postma, T C; White, J G

2016-08-01

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

Memory Reconsolidation and Computational Learning

DTIC Science & Technology

2010-03-01

Cooper and H.T. Siegelmann, "Memory Reconsolidation for Natural Language Processing," Cognitive Neurodynamics , 3, 2009: 365-372. M.M. Olsen, N...computerized memories and other state of the art cognitive architectures, our memory system has the ability to process on-line and in real-time as...on both continuous and binary inputs, unlike state of the art methods in case based reasoning and in cognitive architectures, which are bound to

Uncertainty management by relaxation of conflicting constraints in production process scheduling

NASA Technical Reports Server (NTRS)

Dorn, Juergen; Slany, Wolfgang; Stary, Christian

1992-01-01

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

Analysis of caries status development in relation to socio-economic variables using a case-based system.

PubMed

Swedberg, Y; Norén, J G

2001-01-01

The aim of this study was to detect, using case-based reasoning (CBR) induction methods in time series analysis, how measurable socio-economical adjustments were related to the caries status development. The study concerned the year classes leaving the organised dental care for the time period 1987-95, and had received dental care at the Public Dental Service of Göteborg. The results, as presented by a caries incidence index, indicated that at least one socioeconomical factor, individuals seeking employment, was of importance for the caries status development, a factor with an increase of considerable proportions since 1990. The findings indicated that the other socio-economic variables used did not have the same importance for the caries status development. One feasible explanation is that these factors reflect more upon the social family situation than the economical. If the caries status reflects the social situation of the individual more than the economical, this argument will elucidate the reasoning. Using CBR for the analysis of relationships between oral disease and parameters possibly influencing health development has proven to be a valuable tool and complement to more traditional statistical methods. The analysis can make relationships explicit through the hierarchic knowledge trees and also show redundant information, attributes not appearing in the trees.

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

Pre-Service Physics Teachers' Difficulties in Understanding Special Relativity Topics

ERIC Educational Resources Information Center

Ünlü Yavas, Pervin; Kizilcik, Hasan Sahin

2016-01-01

The aim of this study is to identify the reasons why pre-service physics teachers have difficulties related to special relativity topics. In this study conducted with 25 pre-service physics teachers, the case study method, which is a qualitative research method, was used. Interviews were held with the participants about their reasons for…

Patterns of Clinical Reasoning in Physical Therapist Students.

PubMed

Gilliland, Sarah; Wainwright, Susan Flannery

2017-05-01

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

Reasons For Not Performing Keratorefractive Surgery in Patients Seeking Refractive Surgery in a Hospital-Based Cohort in “Yemen”

PubMed Central

Bamashmus, Mahfouth A.; Saleh, Mahmoud F.; Awadalla, Mohamed A.

2010-01-01

Background: To determine and analyze the reasons why keratorefractive surgery, laser in situ keratomileusis (LASIK) and photorefractive keratectomy (PRK) were not performed in patients who presented for refractive surgery consultation. Materials and Methods: A retrospective observational study was performed between January 2006 and December 2007 in the Yemen Magrabi Hospital. The case records of 2,091 consecutive new patients who presented for refractive surgery were reviewed. Information from the pre-operative ophthalmic examination, such as refractive error, corneal topography and visual acuity, were analyzed. The reasons for not performing LASIK and PRK in the cases that were rejected were recorded and analyzed. Results: In this cohort, 1,660 (79.4%) patients were advised to have LASIK or PRK from the 2,091 patients examined. LASIK and PRK were not advised in 431 (21%) patients. The most common reasons for not performing the surgery were high myopia >-11.00 Diopters (19%), keratoconus (18%), suboptimal central corneal thickness (15%), cataract (12%) and keratoconus suspect (forme fruste keratoconus) (10%). Conclusion: Patients who requested keratorefractive surgery have a variety of problems and warrant comprehensive attention to selection criteria on the part of the surgeon. Corneal topographies and pachymetry of refractive surgery candidates need to be read cautiously. High-refractive error, keratoconus and insufficient corneal thickness were found to be the leading reasons for not performing keratorefractive surgery in this study. PMID:21180437

Prediction model for the return to work of workers with injuries in Hong Kong.

PubMed

Xu, Yanwen; Chan, Chetwyn C H; Lo, Karen Hui Yu-Ling; Tang, Dan

2008-01-01

This study attempts to formulate a prediction model of return to work for a group of workers who have been suffering from chronic pain and physical injury while also being out of work in Hong Kong. The study used Case-based Reasoning (CBR) method, and compared the result with the statistical method of logistic regression model. The database of the algorithm of CBR was composed of 67 cases who were also used in the logistic regression model. The testing cases were 32 participants who had a similar background and characteristics to those in the database. The methods of setting constraints and Euclidean distance metric were used in CBR to search the closest cases to the trial case based on the matrix. The usefulness of the algorithm was tested on 32 new participants, and the accuracy of predicting return to work outcomes was 62.5%, which was no better than the 71.2% accuracy derived from the logistic regression model. The results of the study would enable us to have a better understanding of the CBR applied in the field of occupational rehabilitation by comparing with the conventional regression analysis. The findings would also shed light on the development of relevant interventions for the return-to-work process of these workers.

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

PubMed

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

2014-04-01

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

Case-Based Policy and Goal Recognition

DTIC Science & Technology

2015-09-30

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

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

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

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

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

2010-05-21

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

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

PubMed Central

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

2017-01-01

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

The effect of teaching medical ethics on medical students' moral reasoning.

PubMed

Self, D J; Wolinsky, F D; Baldwin, D C

1989-12-01

A study assessed the effect of incorporating medical ethics into the medical curriculum and the relative effects of two methods of implementing that curriculum, namely, lecture and case-study discussions. Results indicate a statistically significant increase (p less than or equal to .0001) in the level of moral reasoning of students exposed to the medical ethics course, regardless of format. Moreover, the unadjusted posttest scores indicated that the case-study method was significantly (p less than or equal to .03) more effective than the lecture method in increasing students' level of moral reasoning. When adjustment were made for the pretest scores, however, this difference was not statistically significant (p less than or equal to .18). Regression analysis by linear panel techniques revealed that age, gender, undergraduate grade-point average, and scores on the Medical College Admission Test were not related to the changes in moral-reasoning scores. All of the variance that could be explained was due to the students' being in one of the two experimental groups. In comparison with the control group, the change associated with each experimental format was statistically significant (lecture, p less than or equal to .004; case study, p less than or equal to .0001). Various explanations for these findings and their implications are given.

Radiotherapy supporting system based on the image database using IS&C magneto-optical disk

NASA Astrophysics Data System (ADS)

Ando, Yutaka; Tsukamoto, Nobuhiro; Kunieda, Etsuo; Kubo, Atsushi

1994-05-01

Since radiation oncologists make the treatment plan by prior experience, information about previous cases is helpful in planning the radiation treatment. We have developed an supporting system for the radiation therapy. The case-based reasoning method was implemented in order to search old treatments and images of past cases. This system evaluates similarities between the current case and all stored cases (case base). The portal images of the similar cases can be retrieved for reference images, as well as treatment records which show examples of the radiation treatment. By this system radiotherapists can easily make suitable plans of the radiation therapy. This system is useful to prevent inaccurate plannings due to preconceptions and/or lack of knowledge. Images were stored into magneto-optical disks and the demographic data is recorded to the hard disk which is equipped in the personal computer. Images can be displayed quickly on the radiotherapist's demands. The radiation oncologist can refer past cases which are recorded in the case base and decide the radiation treatment of the current case. The file and data format of magneto-optical disk is the IS&C format. This format provides the interchangeability and reproducibility of the medical information which includes images and other demographic data.

Combination of DNA-based and conventional methods to detect human leukocyte antigen polymorphism and its use for paternity testing.

PubMed

Kereszturya, László; Rajczya, Katalin; Lászikb, András; Gyódia, Eva; Pénzes, Mária; Falus, András; Petrányia, Gyõzõ G

2002-03-01

In cases of disputed paternity, the scientific goal is to promote either the exclusion of a falsely accused man or the affiliation of the alleged father. Until now, in addition to anthropologic characteristics, the determination of genetic markers included human leukocyte antigen gene variants; erythrocyte antigens and serum proteins were used for that reason. Recombinant DNA techniques provided a new set of highly variable genetic markers based on DNA nucleotide sequence polymorphism. From the practical standpoint, the application of these techniques to paternity testing provides greater versatility than do conventional genetic marker systems. The use of methods to detect the polymorphism of human leukocyte antigen loci significantly increases the chance of validation of ambiguous results in paternity testing. The outcome of 2384 paternity cases investigated by serologic and/or DNA-based human leukocyte antigen typing was statistically analyzed. Different cases solved by DNA typing are presented involving cases with one or two accused men, exclusions and nonexclusions, and tests of the paternity of a deceased man. The results provide evidence for the advantage of the combined application of various techniques in forensic diagnostics and emphasizes the outstanding possibilities of DNA-based assays. Representative examples demonstrate the strength of combined techniques in paternity testing.

Liquefaction assessment based on combined use of CPT and shear wave velocity measurements

NASA Astrophysics Data System (ADS)

Bán, Zoltán; Mahler, András; Győri, Erzsébet

2017-04-01

Soil liquefaction is one of the most devastating secondary effects of earthquakes and can cause significant damage in built infrastructure. For this reason liquefaction hazard shall be considered in all regions where moderate-to-high seismic activity encounters with saturated, loose, granular soil deposits. Several approaches exist to take into account this hazard, from which the in-situ test based empirical methods are the most commonly used in practice. These methods are generally based on the results of CPT, SPT or shear wave velocity measurements. In more complex or high risk projects CPT and VS measurement are often performed at the same location commonly in the form of seismic CPT. Furthermore, VS profile determined by surface wave methods can also supplement the standard CPT measurement. However, combined use of both in-situ indices in one single empirical method is limited. For this reason, the goal of this research was to develop such an empirical method within the framework of simplified empirical procedures where the results of CPT and VS measurements are used in parallel and can supplement each other. The combination of two in-situ indices, a small strain property measurement with a large strain measurement, can reduce uncertainty of empirical methods. In the first step by careful reviewing of the already existing liquefaction case history databases, sites were selected where the records of both CPT and VS measurement are available. After implementing the necessary corrections on the gathered 98 case histories with respect to fines content, overburden pressure and magnitude, a logistic regression was performed to obtain the probability contours of liquefaction occurrence. Logistic regression is often used to explore the relationship between a binary response and a set of explanatory variables. The occurrence or absence of liquefaction can be considered as binary outcome and the equivalent clean sand value of normalized overburden corrected cone tip resistance (qc1Ncs), the overburden corrected shear wave velocity (V S1), and the magnitude and effective stress corrected cyclic stress ratio (CSRM=7.5,σv'=1atm) were considered as input variables. In this case the graphical representation of the cyclic resistance ratio curve for a given probability has been replaced by a surface that separates the liquefaction and non-liquefaction cases.

Interactive Learning: The Casewriting Method as an Entire Semester Course for Higher Education.

ERIC Educational Resources Information Center

Bowen, Brent D.

This guide explains the reasons for employing the case method as a tool in the academic discipline of aviation. It promotes the use of case writing as a unique opportunity to derive even further benefits from case analysis. The benefits to students of using case writing as a learning strategy include a focus on the strategy of a real situation;…

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…

A seasonal forecast scheme for the Inner Mongolia spring drought part-II: a logical reasoning evidence-based method for spring predictions

NASA Astrophysics Data System (ADS)

Gao, Tao; Wulan, Wulan; Yu, Xiao; Yang, Zelong; Gao, Jing; Hua, Weiqi; Yang, Peng; Si, Yaobing

2018-05-01

Spring precipitation is the predominant factor that controls meteorological drought in Inner Mongolia (IM), China. This study used the anomaly percentage of spring precipitation (PAP) as a drought index to measure spring drought. A scheme for forecasting seasonal drought was designed based on evidence of spring drought occurrence and speculative reasoning methods introduced in computer artificial intelligence theory. Forecast signals with sufficient lead-time for predictions of spring drought were extracted from eight crucial areas of oceans and 500-hPa geopotential height. Using standardized values, these signals were synthesized into three examples of spring drought evidence (SDE) depending on their primary effects on three major atmospheric circulation components of spring precipitation in IM: the western Pacific subtropical high, North Polar vortex, and East Asian trough. Thresholds for the SDE were determined following numerical analyses of the influential factors. Furthermore, five logical reasoning rules for distinguishing the occurrence of SDE were designed after examining all possible combined cases. The degree of confidence in the rules was determined based on estimations of their prior probabilities. Then, an optimized logical reasoning scheme was identified for judging the possibility of spring drought. The scheme was successful in hindcast predictions of 11 of the 16 (accuracy: 68.8%) spring droughts that have occurred during 1960-2009. Moreover, the accuracy ratio for the same period was 82.0% for drought (PAP ≤ -20%) or not (PAP > -20%). Predictions for the recent 6-year period (2010-2015) demonstrated successful outcomes.

Bayesian processing of context-dependent text: reasons for appointments can improve detection of influenza.

PubMed

Alemi, Farrokh; Torii, Manabu; Atherton, Martin J; Pattie, David C; Cox, Kenneth L

2012-01-01

This article aims to examine whether words listed in reasons for appointments could effectively predict laboratory-verified influenza cases in syndromic surveillance systems. Data were collected from the Armed Forces Health Longitudinal Technological Application medical record system. We used 2 algorithms to combine the impact of words within reasons for appointments: Dependent (DBSt) and Independent (IBSt) Bayesian System. We used receiver operating characteristic curves to compare the accuracy of these 2 methods of processing reasons for appointments against current and previous lists of diagnoses used in the Department of Defense's syndromic surveillance system. We examined 13,096 cases, where the results of influenza tests were available. Each reason for an appointment had an average of 3.5 words (standard deviation = 2.2 words). There was no difference in performance of the 2 algorithms. The area under the curve for IBSt was 0.58 and for DBSt was 0.56. The difference was not statistically significant (McNemar statistic = 0.0054; P = 0.07). These data suggest that reasons for appointments can improve the accuracy of lists of diagnoses in predicting laboratory-verified influenza cases. This study recommends further exploration of the DBSt algorithm and reasons for appointments in predicting likely influenza cases.

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

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

Evaluating Secondary Students' Scientific Reasoning in Genetics Using a Two-Tier Diagnostic Instrument

NASA Astrophysics Data System (ADS)

Tsui, Chi-Yan; Treagust, David

2010-05-01

While genetics has remained as one key topic in school science, it continues to be conceptually and linguistically difficult for students with the concomitant debates as to what should be taught in the age of biotechnology. This article documents the development and implementation of a two-tier multiple-choice instrument for diagnosing grades 10 and 12 students' understanding of genetics in terms of reasoning. The pretest and posttest forms of the diagnostic instrument were used alongside other methods in evaluating students' understanding of genetics in a case-based qualitative study on teaching and learning with multiple representations in three Western Australian secondary schools. Previous studies have shown that a two-tier diagnostic instrument is useful in probing students' understanding or misunderstanding of scientific concepts and ideas. The diagnostic instrument in this study was designed and then progressively refined, improved, and implemented to evaluate student understanding of genetics in three case schools. The final version of the instrument had Cronbach's alpha reliability of 0.75 and 0.64, respectively, for its pretest and the posttest forms when it was administered to a group of grade 12 students (n = 17). This two-tier diagnostic instrument complemented other qualitative data collection methods in this research in generating a more holistic picture of student conceptual learning of genetics in terms of scientific reasoning. Implications of the findings of this study using the diagnostic instrument are discussed.

Ecosystem Services Insights into Water Resources Management in China: A Case of Xi'an City.

PubMed

Liu, Jingya; Li, Jing; Gao, Ziyi; Yang, Min; Qin, Keyu; Yang, Xiaonan

2016-11-24

Global climate and environmental changes are endangering global water resources; and several approaches have been tested to manage and reduce the pressure on these decreasing resources. This study uses the case study of Xi'an City in China to test reasonable and effective methods to address water resource shortages. The study generated a framework combining ecosystem services and water resource management. Seven ecosystem indicators were classified as supply services, regulating services, or cultural services. Index values for each indicator were calculated, and based on questionnaire results, each index's weight was calculated. Using the Likert method, we calculated ecosystem service supplies in every region of the city. We found that the ecosystem's service capability is closely related to water resources, providing a method for managing water resources. Using Xi'an City as an example, we apply the ecosystem services concept to water resources management, providing a method for decision makers.

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

PubMed

Kantin, Holly; Wendler, David

2015-10-01

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

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

ERIC Educational Resources Information Center

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

2015-01-01

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

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

PubMed

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

1990-01-01

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

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

PubMed

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

2017-08-01

Script concordance testing (SCT) is a method of assessment of clinical reasoning. We developed a new type of SCT case design, the evolving SCT (E-SCT), whereby the patient's clinical story is "evolving" and with thoughtful integration of new information at each stage, decisions related to clinical decision-making become increasingly clear. We aimed to: (1) determine whether an E-SCT could differentiate clinical reasoning ability among junior residents (JR), senior residents (SR), and pediatricians, (2) evaluate the reliability of an E-SCT, and (3) obtain qualitative feedback from participants to help inform the potential acceptability of the E-SCT. A 12-case E-SCT, embedded within a 24-case pediatric SCT (PaedSCT), was administered to 91 pediatric residents (JR: n = 50; SR: n = 41). A total of 21 pediatricians served on the panel of experts (POE). A one-way analysis of variance (ANOVA) was conducted across the levels of experience. Participants' feedback on the E-SCT was obtained with a post-test survey and analyzed using two methods: percentage preference and thematic analysis. Statistical differences existed across levels of training: F = 19.31 (df = 2); p < 0.001. The POE scored higher than SR (mean difference = 10.34; p < 0.001) and JR (mean difference = 16.00; p < 0.001). SR scored higher than JR (mean difference = 5.66; p < 0.001). Reliability (Cronbach's α) was 0.83. Participants found the E-SCT engaging, easy to follow and true to the daily clinical decision-making process. The E-SCT demonstrated very good reliability and was effective in distinguishing clinical reasoning ability across three levels of experience. Participants found the E-SCT engaging and representative of real-life clinical reasoning and decision-making processes. We suggest that further refinement and utilization of the evolving style case will enhance SCT as a robust, engaging, and relevant method for the assessment of clinical reasoning.

Investigating Students' Reasoning about Acid-Base Reactions

ERIC Educational Resources Information Center

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

2016-01-01

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

Beyond Corroboration: Strengthening Model Validation by Looking for Unexpected Patterns

PubMed Central

Chérel, Guillaume; Cottineau, Clémentine; Reuillon, Romain

2015-01-01

Models of emergent phenomena are designed to provide an explanation to global-scale phenomena from local-scale processes. Model validation is commonly done by verifying that the model is able to reproduce the patterns to be explained. We argue that robust validation must not only be based on corroboration, but also on attempting to falsify the model, i.e. making sure that the model behaves soundly for any reasonable input and parameter values. We propose an open-ended evolutionary method based on Novelty Search to look for the diverse patterns a model can produce. The Pattern Space Exploration method was tested on a model of collective motion and compared to three common a priori sampling experiment designs. The method successfully discovered all known qualitatively different kinds of collective motion, and performed much better than the a priori sampling methods. The method was then applied to a case study of city system dynamics to explore the model’s predicted values of city hierarchisation and population growth. This case study showed that the method can provide insights on potential predictive scenarios as well as falsifiers of the model when the simulated dynamics are highly unrealistic. PMID:26368917

Medical History as an Introduction to Clinical Reasoning.

ERIC Educational Resources Information Center

Maulitz, Russell C.; And Others

1983-01-01

An elective course in the history of medicine focuses on clinical thinking using the case study method. Course goals include: student recognition of clinical reasoning as a historical process; understanding of distinctions between disease categories and etiological frameworks; and different conceptualizations (etiological and syndromic) of…

Multiobjective Optimization of Rocket Engine Pumps Using Evolutionary Algorithm

NASA Technical Reports Server (NTRS)

Oyama, Akira; Liou, Meng-Sing

2001-01-01

A design optimization method for turbopumps of cryogenic rocket engines has been developed. Multiobjective Evolutionary Algorithm (MOEA) is used for multiobjective pump design optimizations. Performances of design candidates are evaluated by using the meanline pump flow modeling method based on the Euler turbine equation coupled with empirical correlations for rotor efficiency. To demonstrate the feasibility of the present approach, a single stage centrifugal pump design and multistage pump design optimizations are presented. In both cases, the present method obtains very reasonable Pareto-optimal solutions that include some designs outperforming the original design in total head while reducing input power by one percent. Detailed observation of the design results also reveals some important design criteria for turbopumps in cryogenic rocket engines. These results demonstrate the feasibility of the EA-based design optimization method in this field.

A computing method for spatial accessibility based on grid partition

NASA Astrophysics Data System (ADS)

Ma, Linbing; Zhang, Xinchang

2007-06-01

An accessibility computing method and process based on grid partition was put forward in the paper. As two important factors impacting on traffic, density of road network and relative spatial resistance for difference land use was integrated into computing traffic cost in each grid. A* algorithms was inducted to searching optimum traffic cost of grids path, a detailed searching process and definition of heuristic evaluation function was described in the paper. Therefore, the method can be implemented more simply and its data source is obtained more easily. Moreover, by changing heuristic searching information, more reasonable computing result can be obtained. For confirming our research, a software package was developed with C# language under ArcEngine9 environment. Applying the computing method, a case study on accessibility of business districts in Guangzhou city was carried out.

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

ERIC Educational Resources Information Center

Tawfik, Andrew; Jonassen, David

2013-01-01

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

38 CFR 36.4279 - Extensions and reamortizations.

Code of Federal Regulations, 2010 CFR

2010-07-01

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

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

PubMed

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

2017-02-01

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

Tag SNP selection via a genetic algorithm.

PubMed

Mahdevar, Ghasem; Zahiri, Javad; Sadeghi, Mehdi; Nowzari-Dalini, Abbas; Ahrabian, Hayedeh

2010-10-01

Single Nucleotide Polymorphisms (SNPs) provide valuable information on human evolutionary history and may lead us to identify genetic variants responsible for human complex diseases. Unfortunately, molecular haplotyping methods are costly, laborious, and time consuming; therefore, algorithms for constructing full haplotype patterns from small available data through computational methods, Tag SNP selection problem, are convenient and attractive. This problem is proved to be an NP-hard problem, so heuristic methods may be useful. In this paper we present a heuristic method based on genetic algorithm to find reasonable solution within acceptable time. The algorithm was tested on a variety of simulated and experimental data. In comparison with the exact algorithm, based on brute force approach, results show that our method can obtain optimal solutions in almost all cases and runs much faster than exact algorithm when the number of SNP sites is large. Our software is available upon request to the corresponding author.

Socio-demographic and academic correlates of clinical reasoning in a dental school in South Africa.

PubMed

Postma, T C; White, J G

2017-02-01

There are no empirical studies that describe factors that may influence the development of integrated clinical reasoning skills in dental education. Hence, this study examines the association between outcomes of clinical reasoning in relation with differences in instructional design and student factors. Progress test scores, including diagnostic and treatment planning scores, of fourth and fifth year dental students (2009-2011) at the University of Pretoria, South Africa served as the outcome measures in stepwise linear regression analyses. These scores were correlated with the instructional design (lecture-based teaching and learning (LBTL = 0) or case-based teaching and learning (CBTL = 1), students' grades in Oral Biology, indicators of socio-economic status (SES) and gender. CBTL showed an independent association with progress test scores. Oral Biology scores correlated with diagnostic component scores. Diagnostic component scores correlated with treatment planning scores in the fourth year of study but not in the fifth year of study. 'SES' correlated with progress test scores in year five only, while gender showed no correlation. The empirical evidence gathered in this study provides support for scaffolded inductive teaching and learning methods to develop clinical reasoning skills. Knowledge in Oral Biology and reading skills may be important attributes to develop to ensure that students are able to reason accurately in a clinical setting. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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

PubMed

Shellenbarger, Teresa; Robb, Meigan

2015-01-01

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

Emotional reasoning and parent-based reasoning in normal children.

PubMed

Morren, Mattijn; Muris, Peter; Kindt, Merel

2004-01-01

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

Estimating individual influences of behavioral intentions: an application of random-effects modeling to the theory of reasoned action.

PubMed

Hedeker, D; Flay, B R; Petraitis, J

1996-02-01

Methods are proposed and described for estimating the degree to which relations among variables vary at the individual level. As an example of the methods, M. Fishbein and I. Ajzen's (1975; I. Ajzen & M. Fishbein, 1980) theory of reasoned action is examined, which posits first that an individual's behavioral intentions are a function of 2 components: the individual's attitudes toward the behavior and the subjective norms as perceived by the individual. A second component of their theory is that individuals may weight these 2 components differently in assessing their behavioral intentions. This article illustrates the use of empirical Bayes methods based on a random-effects regression model to estimate these individual influences, estimating an individual's weighting of both of these components (attitudes toward the behavior and subjective norms) in relation to their behavioral intentions. This method can be used when an individual's behavioral intentions, subjective norms, and attitudes toward the behavior are all repeatedly measured. In this case, the empirical Bayes estimates are derived as a function of the data from the individual, strengthened by the overall sample data.

A Comparative Approach for Ranking Contaminated Sites Based on the Risk Assessment Paradigm Using Fuzzy PROMETHEE

NASA Astrophysics Data System (ADS)

Zhang, Kejiang; Kluck, Cheryl; Achari, Gopal

2009-11-01

A ranking system for contaminated sites based on comparative risk methodology using fuzzy Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE) was developed in this article. It combines the concepts of fuzzy sets to represent uncertain site information with the PROMETHEE, a subgroup of Multi-Criteria Decision Making (MCDM) methods. Criteria are identified based on a combination of the attributes (toxicity, exposure, and receptors) associated with the potential human health and ecological risks posed by contaminated sites, chemical properties, site geology and hydrogeology and contaminant transport phenomena. Original site data are directly used avoiding the subjective assignment of scores to site attributes. When the input data are numeric and crisp the PROMETHEE method can be used. The Fuzzy PROMETHEE method is preferred when substantial uncertainties and subjectivities exist in site information. The PROMETHEE and fuzzy PROMETHEE methods are both used in this research to compare the sites. The case study shows that this methodology provides reasonable results.

A comparative approach for ranking contaminated sites based on the risk assessment paradigm using fuzzy PROMETHEE.

PubMed

Zhang, Kejiang; Kluck, Cheryl; Achari, Gopal

2009-11-01

A ranking system for contaminated sites based on comparative risk methodology using fuzzy Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE) was developed in this article. It combines the concepts of fuzzy sets to represent uncertain site information with the PROMETHEE, a subgroup of Multi-Criteria Decision Making (MCDM) methods. Criteria are identified based on a combination of the attributes (toxicity, exposure, and receptors) associated with the potential human health and ecological risks posed by contaminated sites, chemical properties, site geology and hydrogeology and contaminant transport phenomena. Original site data are directly used avoiding the subjective assignment of scores to site attributes. When the input data are numeric and crisp the PROMETHEE method can be used. The Fuzzy PROMETHEE method is preferred when substantial uncertainties and subjectivities exist in site information. The PROMETHEE and fuzzy PROMETHEE methods are both used in this research to compare the sites. The case study shows that this methodology provides reasonable results.

Comparison of case note review methods for evaluating quality and safety in health care.

PubMed

Hutchinson, A; Coster, J E; Cooper, K L; McIntosh, A; Walters, S J; Bath, P A; Pearson, M; Young, T A; Rantell, K; Campbell, M J; Ratcliffe, J

2010-02-01

To determine which of two methods of case note review--holistic (implicit) and criterion-based (explicit)--provides the most useful and reliable information for quality and safety of care, and the level of agreement within and between groups of health-care professionals when they use the two methods to review the same record. To explore the process-outcome relationship between holistic and criterion-based quality-of-care measures and hospital-level outcome indicators. Case notes of patients at randomly selected hospitals in England. In the first part of the study, retrospective multiple reviews of 684 case notes were undertaken at nine acute hospitals using both holistic and criterion-based review methods. Quality-of-care measures included evidence-based review criteria and a quality-of-care rating scale. Textual commentary on the quality of care was provided as a component of holistic review. Review teams comprised combinations of: doctors (n = 16), specialist nurses (n = 10) and clinically trained audit staff (n = 3) and non-clinical audit staff (n = 9). In the second part of the study, process (quality and safety) of care data were collected from the case notes of 1565 people with either chronic obstructive pulmonary disease (COPD) or heart failure in 20 hospitals. Doctors collected criterion-based data from case notes and used implicit review methods to derive textual comments on the quality of care provided and score the care overall. Data were analysed for intrarater consistency, inter-rater reliability between pairs of staff using intraclass correlation coefficients (ICCs) and completeness of criterion data capture, and comparisons were made within and between staff groups and between review methods. To explore the process-outcome relationship, a range of publicly available health-care indicator data were used as proxy outcomes in a multilevel analysis. Overall, 1473 holistic and 1389 criterion-based reviews were undertaken in the first part of the study. When same staff-type reviewer pairs/groups reviewed the same record, holistic scale score inter-rater reliability was moderate within each of the three staff groups [intraclass correlation coefficient (ICC) 0.46-0.52], and inter-rater reliability for criterion-based scores was moderate to good (ICC 0.61-0.88). When different staff-type pairs/groups reviewed the same record, agreement between the reviewer pairs/groups was weak to moderate for overall care (ICC 0.24-0.43). Comparison of holistic review score and criterion-based score of case notes reviewed by doctors and by non-clinical audit staff showed a reasonable level of agreement (p-values for difference 0.406 and 0.223, respectively), although results from all three staff types showed no overall level of agreement (p-value for difference 0.057). Detailed qualitative analysis of the textual data indicated that the three staff types tended to provide different forms of commentary on quality of care, although there was some overlap between some groups. In the process-outcome study there generally were high criterion-based scores for all hospitals, whereas there was more interhospital variation between the holistic review overall scale scores. Textual commentary on the quality of care verified the holistic scale scores. Differences among hospitals with regard to the relationship between mortality and quality of care were not statistically significant. Using the holistic approach, the three groups of staff appeared to interpret the recorded care differently when they each reviewed the same record. When the same clinical record was reviewed by doctors and non-clinical audit staff, there was no significant difference between the assessments of quality of care generated by the two groups. All three staff groups performed reasonably well when using criterion-based review, although the quality and type of information provided by doctors was of greater value. Therefore, when measuring quality of care from case notes, consideration needs to be given to the method of review, the type of staff undertaking the review, and the methods of analysis available to the review team. Review can be enhanced using a combination of both criterion-based and structured holistic methods with textual commentary, and variation in quality of care can best be identified from a combination of holistic scale scores and textual data review.

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.

[Contraception with levonorgestrel (Norplant) subcutaneous implants. African experience in Burkina Faso].

PubMed

Koné, B; Lankoandé, J; Ouédraogo, C M; Ouédraogo, A; Bonané, B; Dao, B; Sanou, J

1999-02-01

The subcutaneous implants from the levonorgestrel (Norplant) has been introduced in Burkina Faso in September 1992 within the context of a project assisted by a non-governmental organization (the Population Council). The aim was to reinforce the family planning programme in Burkina Faso by increasing the number of family planning methods available for the clients. 4 years after its introduction, we propose to make a report of our experience in terms of the contraception through subcutaneous implants in order to better set up an IEC campaign on this method. Within 4 years, 1,660 users benefitted from that contraceptive method. They were housewives in 65% of the cases. The age-group of 30-34 years old most used this method with 28.6%. Multipares most benefitted from this method with 64.3%. In 72% of the cases, the insertion was made during the premenstrual period. On the whole, 247 withdrawals have been made before the fourth years for various reasons. Among those reasons are cycle disorders (60 withdrawals), medical reasons (53 withdrawals), personal conveniences (47 withdrawals), weight gaining (14 withdrawals), failures (2 withdrawals). Regarding the side effects, they were mainly represented by the menstrual cycle disorders such as amenorrhoea, spotting, hypermenorrhoea in 51% of the cases. A good information and sensitization campaign should reduce the number of implants withdrawals before the fourth year of use. Moreover, a perfect knowledge of contraindications is indispensable before any prescription.

Development of Extended Ray-tracing method including diffraction, polarization and wave decay effects

NASA Astrophysics Data System (ADS)

Yanagihara, Kota; Kubo, Shin; Dodin, Ilya; Nakamura, Hiroaki; Tsujimura, Toru

2017-10-01

Geometrical Optics Ray-tracing is a reasonable numerical analytic approach for describing the Electron Cyclotron resonance Wave (ECW) in slowly varying spatially inhomogeneous plasma. It is well known that the result with this conventional method is adequate in most cases. However, in the case of Helical fusion plasma which has complicated magnetic structure, strong magnetic shear with a large scale length of density can cause a mode coupling of waves outside the last closed flux surface, and complicated absorption structure requires a strong focused wave for ECH. Since conventional Ray Equations to describe ECW do not have any terms to describe the diffraction, polarization and wave decay effects, we can not describe accurately a mode coupling of waves, strong focus waves, behavior of waves in inhomogeneous absorption region and so on. For fundamental solution of these problems, we consider the extension of the Ray-tracing method. Specific process is planned as follows. First, calculate the reference ray by conventional method, and define the local ray-base coordinate system along the reference ray. Then, calculate the evolution of the distributions of amplitude and phase on ray-base coordinate step by step. The progress of our extended method will be presented.

Case-Based Plan Recognition Using Action Sequence Graphs

DTIC Science & Technology

2014-10-01

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

Reasons for Vocabulary Attrition: Revisiting the State of the Art

ERIC Educational Resources Information Center

Alharthi, Thamer

2015-01-01

This paper reports on a one year, mixed-methods longitudinal case study investigating the neglected area of the perceived reasons why participants forget vocabulary knowledge. The participants were 43 fourth year male Saudi EFL majors at King Abdulaziz University KAU, Saudi Arabia. Quantitative and qualitative data including self-reported…

Research on Standard and Automatic Judgment of Press-fit Curve of Locomotive Wheel-set Based on AAR Standard

NASA Astrophysics Data System (ADS)

Lu, Jun; Xiao, Jun; Gao, Dong Jun; Zong, Shu Yu; Li, Zhu

2018-03-01

In the production of the Association of American Railroads (AAR) locomotive wheel-set, the press-fit curve is the most important basis for the reliability of wheel-set assembly. In the past, Most of production enterprises mainly use artificial detection methods to determine the quality of assembly. There are cases of miscarriage of justice appear. For this reason, the research on the standard is carried out. And the automatic judgment of press-fit curve is analysed and designed, so as to provide guidance for the locomotive wheel-set production based on AAR standard.

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

PubMed

Ozer, Bugra; Sağıroğlu, Mahmut; Demirci, Hüseyin

2015-11-15

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

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

PubMed

Asad, Munazza; Iqbal, Khadija; Sabir, Mohammad

2015-01-01

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

An ontological case base engineering methodology for diabetes management.

PubMed

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

2014-08-01

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

Online Sensor Fault Detection Based on an Improved Strong Tracking Filter

PubMed Central

Wang, Lijuan; Wu, Lifeng; Guan, Yong; Wang, Guohui

2015-01-01

We propose a method for online sensor fault detection that is based on the evolving Strong Tracking Filter (STCKF). The cubature rule is used to estimate states to improve the accuracy of making estimates in a nonlinear case. A residual is the difference in value between an estimated value and the true value. A residual will be regarded as a signal that includes fault information. The threshold is set at a reasonable level, and will be compared with residuals to determine whether or not the sensor is faulty. The proposed method requires only a nominal plant model and uses STCKF to estimate the original state vector. The effectiveness of the algorithm is verified by simulation on a drum-boiler model. PMID:25690553

Dental extrusion with orthodontic miniscrew anchorage: a case report describing a modified method.

PubMed

Horliana, Ricardo Fidos; Horliana, Anna Carolina Ratto Tempestini; Wuo, Alexandre do Vale; Perez, Flávio Eduardo Guillin; Abrão, Jorge

2015-01-01

In recent years, the skeletal anchorage through miniscrews has expanded the treatment options in orthodontics (Yamaguchi et al., 2012). We hereby present a modified method for tooth extrusion for cases where crown-lengthening surgery is contraindicated for aesthetic reasons. This modified method uses three orthodontic appliances: a mini-implant, an orthodontic wire, and a bracket. The aim of this case report was to increase the length of the clinical crown of a fractured tooth (tooth 23) by means of an orthodontic extrusion with the modified method of Roth and Diedrich.

The effect of short-term workshop on improving clinical reasoning skill of medical students

PubMed Central

Yousefichaijan, Parsa; Jafari, Farshad; Kahbazi, Manijeh; Rafiei, Mohammad; Pakniyat, AbdolGhader

2016-01-01

Background: Clinical reasoning process leads clinician to get purposeful steps from signs and symptoms toward diagnosis and treatment. This research intends to investigate the effect of teaching clinical reasoning on problem-solving skills of medical students. Methods: This research is a semi-experimental study. Nineteen Medical student of the pediatric ward as case group participated in a two-day workshop for training clinical reasoning. Before the workshop, they filled out Diagnostic Thinking Inventory (DTI) questionnaires. Fifteen days after the workshop the DTI questionnaire completed and "key feature" (KF) test and "clinical reasoning problem" (CRP) test was held. 23 Medical student as the control group, without passing the clinical reasoning workshop DTI questionnaire completed, and KF test and CRP test was held. Results: The average score of the DTI questionnaire in the control group was 162.04 and in the case group before the workshop was 153.26 and after the workshop was 181.68. Compare the average score of the DTI questionnaire before and after the workshop there is a significant difference. The difference between average KF test scores in the control and the case group was not significant but between average CRP test scores was significant. Conclusion: Clinical reasoning workshop is effectiveness in promoting problem-solving skills of students. PMID:27579286

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

PubMed Central

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

2016-01-01

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

Preparing perservice teachers to teach elementary school science

NASA Astrophysics Data System (ADS)

Lewis, Amy D.

The development of scientifically literate citizens begins in the elementary school. Yet elementary school teachers are ill prepared to teach science (Trygstad, Smith, Banilower, Nelson, & Horizon Research, Inc., 2013). The research base on teacher preparation finds that programs designed to prepare elementary teachers are inadequate in providing both the content knowledge and pedagogical content knowledge necessary to teach science effectively (Baumgartner, 2010; Bodzin & Beerer, 2003; Bulunuz & Jarrett 2009). This mixed methods study examined what happened when a science methods course was interactively co-taught by an expert in elementary teaching methods and a physics expert. This study also aimed to discover what aspects of the curriculum pre-service teachers (PSTs) said helped them in developing their understanding of science content and scientific reasoning, and how to implement inquiry practices to teach science. A nested case study of three PSTs provided descriptive portraits of student experiences in the class. A whole class case analysis was used to examine what PSTs learned in terms of science, scientific reasoning skills, and pedagogical content knowledge (PCK) from their experiences in the course. It was found that students often conflated science content with the experiences they had in learning the content. Although PSTs felt the interactive co-teaching model effectively created a balance between theory and practice, it was their experiences doing science--conducting physical experiments, developing and discussing scientific models, and the use of inquiry-based instruction--that they credited for their learning. Even with careful curriculum planning, and a course purposely designed to bridge the theory to practice gap, this study found one semester-long methods course to be insufficient in providing the vast content knowledge and PCK elementary school science teachers need.

The use of rapid review methods in health technology assessments: 3 case studies.

PubMed

Kaltenthaler, Eva; Cooper, Katy; Pandor, Abdullah; Martyn-St James, Marrissa; Chatters, Robin; Wong, Ruth

2016-08-26

Rapid reviews are of increasing importance within health technology assessment due to time and resource constraints. There are many rapid review methods available although there is little guidance as to the most suitable methods. We present three case studies employing differing methods to suit the evidence base for each review and outline some issues to consider when selecting an appropriate method. Three recently completed systematic review short reports produced for the UK National Institute for Health Research were examined. Different approaches to rapid review methods were used in the three reports which were undertaken to inform the commissioning of services within the NHS and to inform future trial design. We describe the methods used, the reasoning behind the choice of methods and explore the strengths and weaknesses of each method. Rapid review methods were chosen to meet the needs of the review and each review had distinctly different challenges such as heterogeneity in terms of populations, interventions, comparators and outcome measures (PICO) and/or large numbers of relevant trials. All reviews included at least 10 randomised controlled trials (RCTs), each with numerous included outcomes. For the first case study (sexual health interventions), very diverse studies in terms of PICO were included. P-values and summary information only were presented due to substantial heterogeneity between studies and outcomes measured. For the second case study (premature ejaculation treatments), there were over 100 RCTs but also several existing systematic reviews. Data for meta-analyses were extracted directly from existing systematic reviews with new RCT data added where available. For the final case study (cannabis cessation therapies), studies included a wide range of interventions and considerable variation in study populations and outcomes. A brief summary of the key findings for each study was presented and narrative synthesis used to summarise results for each pair of interventions compared. Rapid review methods need to be chosen to meet both the nature of the evidence base of a review and the challenges presented by the included studies. Appropriate methods should be chosen after an assessment of the evidence base.

Case based learning: a method for better understanding of biochemistry in medical students.

PubMed

Nair, Sandhya Pillai; Shah, Trushna; Seth, Shruti; Pandit, Niraj; Shah, G V

2013-08-01

Health professionals need to develop analytic and diagnostic thinking skills and not just a mere accumulation of large amount of facts. Hence, Case Based Learning (CBL) has been used in the medical curriculum for this reason, so that the students are exposed to the real medical problems, which helps them in develop analysing abilities. This also helps them in interpreting and solving the problems and in the course of doing this, they develop interest. In addition to didactic lectures, CBL was used as a learning method. This study was conducted in the Department of Biochemistry, S.B.K.S.M.I and R.C, Sumandeep Vidyapeeth ,Piparia, Gujarat, India. A group of 100 students were selected and they were divided into two groups as the control group and the study group. A total of 50 students were introduced to case based learning, which formed the study group and 50 students who attended didactic lectures formed the control group. A very significant improvement (p<0.0001) was observed among the students after the CBL sessions and they were also motivated by these sessions. A 4 point Likert scale questionnaire which contained 8 questions was administered to the students, to know their perception on the usefulness of the CBL. 98% of the students reported that they found the CBL sessions to be an interesting method of gaining knowledge. 84% of them felt that they exposed them to an experience of logical application of the knowledge which was gained in cracking cases, which would be of great help in the future also. Case Based Learning (CBL) was used and it is effective in the medical curriculum for a better understanding of Biochemistry among the medical students.

Tinea Capitis in Infants

PubMed Central

Michaels, Brent D.

2012-01-01

Tinea capitis is a reasonably common infection among the pediatric population; however, it is still a relatively rare entity among infants less than one year of age. As such, a high index of suspicion is necessary for diagnosis among infants and an appropriate diagnostic work up should be employed in any case where a dermatophyte infection is suspected. Several methods are available for diagnosis. In addition, proper identification of the specific dermatophyte genera involved should be considered as treatment options may be altered based on the causative pathogen identified. PMID:22468173

Performance of a Method to Standardize Breast Ultrasound Interpretation Using Image Processing and Case-Based Reasoning

NASA Astrophysics Data System (ADS)

André, M. P.; Galperin, M.; Berry, A.; Ojeda-Fournier, H.; O'Boyle, M.; Olson, L.; Comstock, C.; Taylor, A.; Ledgerwood, M.

Our computer-aided diagnostic (CADx) tool uses advanced image processing and artificial intelligence to analyze findings on breast sonography images. The goal is to standardize reporting of such findings using well-defined descriptors and to improve accuracy and reproducibility of interpretation of breast ultrasound by radiologists. This study examined several factors that may impact accuracy and reproducibility of the CADx software, which proved to be highly accurate and stabile over several operating conditions.

On Measuring Quantitative Interpretations of Reasonable Doubt

ERIC Educational Resources Information Center

Dhami, Mandeep K.

2008-01-01

Beyond reasonable doubt represents a probability value that acts as the criterion for conviction in criminal trials. I introduce the membership function (MF) method as a new tool for measuring quantitative interpretations of reasonable doubt. Experiment 1 demonstrated that three different methods (i.e., direct rating, decision theory based, and…

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

NASA Astrophysics Data System (ADS)

Mansouri, Masoumeh; Pecora, Federico

2016-09-01

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

Reasonable Accommodation Information Tracking System

EPA Pesticide Factsheets

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

Deghosting based on the transmission matrix method

NASA Astrophysics Data System (ADS)

Wang, Benfeng; Wu, Ru-Shan; Chen, Xiaohong

2017-12-01

As the developments of seismic exploration and subsequent seismic exploitation advance, marine acquisition systems with towed streamers become an important seismic data acquisition method. But the existing air-water reflective interface can generate surface related multiples, including ghosts, which can affect the accuracy and performance of the following seismic data processing algorithms. Thus, we derive a deghosting method from a new perspective, i.e. using the transmission matrix (T-matrix) method instead of inverse scattering series. The T-matrix-based deghosting algorithm includes all scattering effects and is convergent absolutely. Initially, the effectiveness of the proposed method is demonstrated using synthetic data obtained from a designed layered model, and its noise-resistant property is also illustrated using noisy synthetic data contaminated by random noise. Numerical examples on complicated data from the open SMAART Pluto model and field marine data further demonstrate the validity and flexibility of the proposed method. After deghosting, low frequency components are recovered reasonably and the fake high frequency components are attenuated, and the recovered low frequency components will be useful for the subsequent full waveform inversion. The proposed deghosting method is currently suitable for two-dimensional towed streamer cases with accurate constant depth information and its extension into variable-depth streamers in three-dimensional cases will be studied in the future.

Efficiency of the spectral-spatial classification of hyperspectral imaging data

NASA Astrophysics Data System (ADS)

Borzov, S. M.; Potaturkin, O. I.

2017-01-01

The efficiency of methods of the spectral-spatial classification of similarly looking types of vegetation on the basis of hyperspectral data of remote sensing of the Earth, which take into account local neighborhoods of analyzed image pixels, is experimentally studied. Algorithms that involve spatial pre-processing of the raw data and post-processing of pixel-based spectral classification maps are considered. Results obtained both for a large-size hyperspectral image and for its test fragment with different methods of training set construction are reported. The classification accuracy in all cases is estimated through comparisons of ground-truth data and classification maps formed by using the compared methods. The reasons for the differences in these estimates are discussed.

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

PubMed

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

2013-01-01

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

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

PubMed Central

Almeida, Fernando; Moreira, Diana

2017-01-01

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

Socio-scientific reasoning influenced by identities

NASA Astrophysics Data System (ADS)

Simonneaux, Laurence; Simonneaux, Jean

2009-09-01

Based on the comments by Lopez-Facal and Jiménez-Aleixandre, we consider that the cultural identities within Europe interfere with the question of the re-introduction of the Slovenian bear, generating a kind of "discrimination." When the SAQs under debate run against the students' systems of value, it seems that the closer the connection between the SAQs (socially acute questions) and the territorial and cultural identity, the more deeply the associated systems of values are affected; and the more the evidence is denied, the weaker the socio-scientific reasoning becomes. This result shows the importance of attempting to get the students to clarify the values underlying their socio-scientific reasoning. As Sadler observed, there was no transfer of socio-scientific reasoning on the three questions considered; each SAQ, as they are deeply related to social representations and identity, generated a specific line of reasoning balancing more or less each operation. Among various methods of teaching SAQs—problematizing, genetic, doctrinal and praxeological methods--socio-scientific reasoning may be a complex activity of problematization fostering the development of critical thinking. Confronted with the refusal to analyse the evidence in the case of the bear, and because of the nature of SAQs, we explore the notion of tangible proof. We think it relevant to study, together with the students, the processes of investigation used by the actors to establish or disestablish tangible proof on SAQs by analysing the intermediary states of the systems of proof, and possibly the "weak signals" which result in calling for the implementation of the precautionary principle.

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

PubMed

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

2017-01-01

Background: Clinical reasoning, comprising the processes of clinical thinking, which form the basis of medical decisions, constitutes a central competence in the clinical routine on which diagnostic and therapeutic steps are based. In medical curricula in Germany, clinical reasoning is currently taught explicitly only to a small extend. Therefore, the aim of this project was to develop and implement a clinical reasoning course in the final year of undergraduate medical training. Project description: A clinical reasoning course with six learning units and 18 learning objectives was developed, which was taught by two to four instructors on the basis of 32 paper cases from the clinical practice of the instructors. In the years 2011 to 2013, the course of eight weeks with two hours per week was taught seven times. Before the first and after the last seminar, the participating students filled out a self-assessment questionnaire with a 6-point Likert scale regarding eight different clinical reasoning skills. At the same times, they received a patient case with the assignment to prepare a case presentation and differential diagnoses. Results: From 128 participating students altogether, 42 complete data sets were available. After the course, participants assessed themselves significantly better than before the course in all eight clinical reasoning skills, for example in "Summarizing and presentation of a paper case" or in the "Skill to enumerate differential diagnoses" (p<0.05). The greatest increase occurred in the skill to recognize typical cognitive errors in medicine and to identify risk situations for their occurrence (pre: 2.98±0.92 and retro-pre: 2.64±1.01, respectively, versus post: 4.38±0.88). Based on the ratio of number of words used per keywords used the problem presentation of the paper case was significantly more focused after the course (p=0.011). A significant increase in the number of gathered differential diagnoses was not detected after the course. Conclusion: The newly developed and established Clinical Reasoning Course leads to a gain in the desired skills from the students' self-assessment perspective and to a more structured case presentation. To establish better options to exercise clinical reasoning, a longitudinal implementation in the medical curriculum seems to be desirable. Faculty training would be useful to implement the concept as standardized as possible.

Women's reasons for choosing abortion method: A systematic literature review.

PubMed

Kanstrup, Charlotte; Mäkelä, Marjukka; Hauskov Graungaard, Anette

2017-07-01

We aim to describe and classify reasons behind women's choice between medical and surgical abortion. A systematic literature review was conducted in PubMed and PsycINFO in October 2015. The subjects were women in early pregnancy opting for abortion at clinics or hospitals in high-income countries. We extracted women's reasons for choice of abortion method and analysed these qualitatively, looking at main reasons for choosing either medical or surgical abortion. Reasons for choice of method were classified to five main groups: technical nature of the intervention, fear of complications, fear of surgery or anaesthesia, timing and sedation. Reasons for selecting medical abortion were often based on the perception of the method being 'more natural' and the wish to have abortion in one's home in addition to fear of complications. Women who opted for surgical abortion appreciated the quicker process, viewed it as the safer option, and wished to avoid pain and excess bleeding. Reasons were often based on emotional reactions, previous experiences and a lack of knowledge about the procedures. Some topics such as pain or excess bleeding received little attention. Overall the quality of the studies was low, most studies were published more than 10 years ago, and the generalisability of the findings was poor. Women did not base their choice of abortion method only on rational information from professionals but also on emotions and especially fears. Support techniques for a more informed choice are needed. Recent high-quality studies in this area are lacking.

Analysis of concrete beams using applied element method

NASA Astrophysics Data System (ADS)

Lincy Christy, D.; Madhavan Pillai, T. M.; Nagarajan, Praveen

2018-03-01

The Applied Element Method (AEM) is a displacement based method of structural analysis. Some of its features are similar to that of Finite Element Method (FEM). In AEM, the structure is analysed by dividing it into several elements similar to FEM. But, in AEM, elements are connected by springs instead of nodes as in the case of FEM. In this paper, background to AEM is discussed and necessary equations are derived. For illustrating the application of AEM, it has been used to analyse plain concrete beam of fixed support condition. The analysis is limited to the analysis of 2-dimensional structures. It was found that the number of springs has no much influence on the results. AEM could predict deflection and reactions with reasonable degree of accuracy.

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

PubMed

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

2016-01-01

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

Validation of the Quantitative Diagnostic Thinking Inventory for Athletic Training: A Pilot Study

ERIC Educational Resources Information Center

Kicklighter, Taz; Barnum, Mary; Geisler, Paul R.; Martin, Malissa

2016-01-01

Context: The cognitive process of making a clinical decision lies somewhere on a continuum between novices using hypothetico-deductive reasoning and experts relying more on case pattern recognition. Although several methods exist for measuring facets of clinical reasoning in specific situations, none have been experimentally applied, as of yet, to…

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

PubMed Central

2017-01-01

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

Linear Elastic and Cohesive Fracture Analysis to Model Hydraulic Fracture in Brittle and Ductile Rocks

NASA Astrophysics Data System (ADS)

Yao, Yao

2012-05-01

Hydraulic fracturing technology is being widely used within the oil and gas industry for both waste injection and unconventional gas production wells. It is essential to predict the behavior of hydraulic fractures accurately based on understanding the fundamental mechanism(s). The prevailing approach for hydraulic fracture modeling continues to rely on computational methods based on Linear Elastic Fracture Mechanics (LEFM). Generally, these methods give reasonable predictions for hard rock hydraulic fracture processes, but still have inherent limitations, especially when fluid injection is performed in soft rock/sand or other non-conventional formations. These methods typically give very conservative predictions on fracture geometry and inaccurate estimation of required fracture pressure. One of the reasons the LEFM-based methods fail to give accurate predictions for these materials is that the fracture process zone ahead of the crack tip and softening effect should not be neglected in ductile rock fracture analysis. A 3D pore pressure cohesive zone model has been developed and applied to predict hydraulic fracturing under fluid injection. The cohesive zone method is a numerical tool developed to model crack initiation and growth in quasi-brittle materials considering the material softening effect. The pore pressure cohesive zone model has been applied to investigate the hydraulic fracture with different rock properties. The hydraulic fracture predictions of a three-layer water injection case have been compared using the pore pressure cohesive zone model with revised parameters, LEFM-based pseudo 3D model, a Perkins-Kern-Nordgren (PKN) model, and an analytical solution. Based on the size of the fracture process zone and its effect on crack extension in ductile rock, the fundamental mechanical difference of LEFM and cohesive fracture mechanics-based methods is discussed. An effective fracture toughness method has been proposed to consider the fracture process zone effect on the ductile rock fracture.

Ecosystem Services Insights into Water Resources Management in China: A Case of Xi’an City

PubMed Central

Liu, Jingya; Li, Jing; Gao, Ziyi; Yang, Min; Qin, Keyu; Yang, Xiaonan

2016-01-01

Global climate and environmental changes are endangering global water resources; and several approaches have been tested to manage and reduce the pressure on these decreasing resources. This study uses the case study of Xi’an City in China to test reasonable and effective methods to address water resource shortages. The study generated a framework combining ecosystem services and water resource management. Seven ecosystem indicators were classified as supply services, regulating services, or cultural services. Index values for each indicator were calculated, and based on questionnaire results, each index’s weight was calculated. Using the Likert method, we calculated ecosystem service supplies in every region of the city. We found that the ecosystem’s service capability is closely related to water resources, providing a method for managing water resources. Using Xi’an City as an example, we apply the ecosystem services concept to water resources management, providing a method for decision makers. PMID:27886137

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

ERIC Educational Resources Information Center

Cuban, Sondra

2007-01-01

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

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

PubMed

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

2011-01-01

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

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

PubMed

Svantesson, Mia; Silén, Marit; James, Inger

2018-03-01

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

A method for diagnosing time dependent faults using model-based reasoning systems

NASA Technical Reports Server (NTRS)

Goodrich, Charles H.

1995-01-01

This paper explores techniques to apply model-based reasoning to equipment and systems which exhibit dynamic behavior (that which changes as a function of time). The model-based system of interest is KATE-C (Knowledge based Autonomous Test Engineer) which is a C++ based system designed to perform monitoring and diagnosis of Space Shuttle electro-mechanical systems. Methods of model-based monitoring and diagnosis are well known and have been thoroughly explored by others. A short example is given which illustrates the principle of model-based reasoning and reveals some limitations of static, non-time-dependent simulation. This example is then extended to demonstrate representation of time-dependent behavior and testing of fault hypotheses in that environment.

Lecture-based versus problem-based learning in ethics education among nursing students.

PubMed

Khatiban, Mahnaz; Falahan, Seyede Nayereh; Amini, Roya; Farahanchi, Afshin; Soltanian, Alireza

2018-01-01

Moral reasoning is a vital skill in the nursing profession. Teaching moral reasoning to students is necessary toward promoting nursing ethics. The aim of this study was to compare the effectiveness of problem-based learning and lecture-based methods in ethics education in improving (1) moral decision-making, (2) moral reasoning, (3) moral development, and (4) practical reasoning among nursing students. This is a repeated measurement quasi-experimental study. Participants and research context: The participants were nursing students in a University of Medical Sciences in west of Iran who were randomly assigned to the lecture-based (n = 33) or the problem-based learning (n = 33) groups. The subjects were provided nursing ethics education in four 2-h sessions. The educational content was similar, but the training methods were different. The subjects completed the Nursing Dilemma Test before, immediately after, and 1 month after the training. The data were analyzed and compared using the SPSS-16 software. Ethical considerations: The program was explained to the students, all of whom signed an informed consent form at the baseline. The two groups were similar in personal characteristics (p > 0.05). A significant improvement was observed in the mean scores on moral development in the problem-based learning compared with the lecture-based group (p < 0.05). Although the mean scores on moral reasoning improved in both the problem-based learning and the lecture-based groups immediately after the training and 1 month later, the change was significant only in the problem-based learning group (p < 0.05). The mean scores on moral decision-making, practical considerations, and familiarity with dilemmas were relatively similar for the two groups. The use of the problem-based learning method in ethics education enhances moral development among nursing students. However, further studies are needed to determine whether such method improves moral decision-making, moral reasoning, practical considerations, and familiarity with the ethical issues among nursing students.

Suicide attempts and suicides in Bolivia from 2007 to 2012: pesticides are the preferred method - females try but males commit suicide!

PubMed

Jørs, Erik; Christoffersen, Mette; Veirum, Nikoline Høgsgaard; Aquilar, Guido Condarco; Morant, Rafael Cervantes; Konradsen, Flemming

2014-01-01

Suicide attempts and suicides constitute a significant burden on communities and health systems, especially in low income countries. However, many low income countries lack epidemiological information on which to base future preventive strategies. This study reports on gender and age profiles as well as the likely background and means used for suicide attempts and suicides in Bolivia. This study presents 1124 cases from four different sources of information: (i) emergency ward data with suicide attempts by poisoning from the year 2007, (ii) psychiatric ward data including suicide attempts from July 2011 to July 2012, (iii) newspaper articles reporting attempted suicides and suicides from 2009 to 2011, and (iv) the National Statistics on Crime reporting suicides from the years 2010-2011. Data on age was stratified into three age groups: adolescents aged 10-19 years, young adults aged 20-29 years, and older adults aged above 29 years. Data from the hospital wards and Crime Statistics were pooled to compare characteristics of suicide attempts with suicides concerning age and gender. Data on age, gender, methods used, and reasons were analyzed using IBM SPSS version 21. Hospital data showed that more females (403/657, 61%) than males (254/657, 39%) attempted suicide, and females attempted suicide at a younger age than males (p<0.05). In contrast to this, more males (208/293, 70.5%) than females (85/293, 29.5%) committed suicide, and furthermore it was most prevalent among young adults aged 20-29 years of both genders, as observed from the Crime Statistics. The dominant method was pesticide poisoning varying from 400 out of 657 (70.5%) of the hospital poisoning cases to 65 out of 172 (37.8%) of the newspaper cases. Newspaper data showed a higher mortality rate (65/77, 85.1%) among those using violent methods such as hanging and jumping compared to non-violent methods (43/84, 50.9%) such as ingesting chemicals and drugs (p<0.05). The reasons were related to interpersonal problems, economic problems, depression, and unwanted pregnancies. Many cases of suicide seemed to be hidden due to cultural and religious reasons. More females attempted suicide, whereas more males realized suicide. Suicide attempts were most numerous among adolescents in contrast to suicides being most prevalent in the older age groups. Self-poisoning with pesticides was the most popular method used. Access to potential suicide materials should be restricted and psychosocial interventions initiated to prevent suicides.

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.

Casuistry and its communitarian critics.

PubMed

Kuczewski, Mark G

1994-06-01

Communitarian critics have derided case-based reasoning for ignoring the need to arrive at a shared hierarchy of goods prior to case resolution. They claim that such a failure means that casuistry depends on either a naive metaphysical realism or an ethical conventionalism. Casuistry does embrace a certain unobjectionable moral realism and can require appeals to narrative histories, but despite this dependence on the surrounding culture, casuists possess a way to remain critical of society through the concept of practical wisdom and the use of a moral taxonomy. Therefore, casuistry's viability depends upon the existence and employment of this Aristotelian virtue. Furthermore, the casuistry that emerges is a sophisticated type of communitarianism rather than a free-standing method.

How Do Clinicians Prefer Cultural Competence Training? Findings from the DSM-5 Cultural Formulation Interview Field Trial

PubMed Central

Aggarwal, Neil Krishan; Lam, Peter; Castillo, Enrico; Weiss, Mitchell G.; Diaz, Esperanza; Alarcón, Renato D.; van Dijk, Rob; Rohlof, Hans; Ndetei, David M.; Scalco, Monica; Aguilar-Gaxiola, Sergio; Bassiri, Kavoos; Deshpande, Smita; Groen, Simon; Jadhav, Sushrut; Kirmayer, Laurence J.; Paralikar, Vasudeo; Westermeyer, Joseph; Santos, Filipa; Vega-Dienstmaier, Johann; Anez, Luis; Boiler, Marit; Nicasio, Andel V.; Lewis-Fernández, Roberto

2015-01-01

Objective This study’s objective is to analyze training methods clinicians reported as most and least helpful during the DSM-5 Cultural Formulation Interview field trial, reasons why, and associations between demographic characteristics and method preferences. Method The authors used mixed methods to analyze interviews from 75 clinicians in five continents on their training preferences after a standardized training session and clinicians’ first administration of the Cultural Formulation Interview. Content analysis identified most and least helpful educational methods by reason. Bivariate and logistic regression analysis compared clinician characteristics to method preferences. Results Most frequently, clinicians named case-based behavioral simulations as “most helpful” and video as “least helpful” training methods. Bivariate and logistic regression models, first unadjusted and then clustered by country, found that each additional year of a clinician’s age was associated with a preference for behavioral simulations: OR=1.05 (95% CI: 1.01–1.10; p=0.025). Conclusions Most clinicians preferred active behavioral simulations in cultural competence training, and this effect was most pronounced among older clinicians. Effective training may be best accomplished through a combination of reviewing written guidelines, video demonstration, and behavioral simulations. Future work can examine the impact of clinician training satisfaction on patient symptoms and quality of life. PMID:26449983

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

NASA Technical Reports Server (NTRS)

Mitchell, Christine M.; Thurman, David A.

1998-01-01

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

Use of emergency department electronic medical records for automated epidemiological surveillance of suicide attempts: a French pilot study.

PubMed

Metzger, Marie-Hélène; Tvardik, Nastassia; Gicquel, Quentin; Bouvry, Côme; Poulet, Emmanuel; Potinet-Pagliaroli, Véronique

2017-06-01

The aim of this study was to determine whether an expert system based on automated processing of electronic health records (EHRs) could provide a more accurate estimate of the annual rate of emergency department (ED) visits for suicide attempts in France, as compared to the current national surveillance system based on manual coding by emergency practitioners. A feasibility study was conducted at Lyon University Hospital, using data for all ED patient visits in 2012. After automatic data extraction and pre-processing, including automatic coding of medical free-text through use of the Unified Medical Language System, seven different machine-learning methods were used to classify the reasons for ED visits into "suicide attempts" versus "other reasons". The performance of these different methods was compared by using the F-measure. In a test sample of 444 patients admitted to the ED in 2012 (98 suicide attempts, 48 cases of suicidal ideation, and 292 controls with no recorded non-fatal suicidal behaviour), the F-measure for automatic detection of suicide attempts ranged from 70.4% to 95.3%. The random forest and naïve Bayes methods performed best. This study demonstrates that machine-learning methods can improve the quality of epidemiological indicators as compared to current national surveillance of suicide attempts. Copyright © 2016 John Wiley & Sons, Ltd.

Middle School Students' Reasoning about 3-Dimensional Objects: A Case Study

ERIC Educational Resources Information Center

Okumus, Samet

2016-01-01

According to the National Council of Teacher of Mathematics (NCTM) (2000), K-12 students should be given an opportunity to develop their spatial reasoning abilities. One of the topics that may allow students to develop their spatial skills is forming 3-dimensional objects using spinning and extrusion methods. Also, extrusion and spinning methods…

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

PubMed Central

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

2017-01-01

Background: Clinical reasoning, comprising the processes of clinical thinking, which form the basis of medical decisions, constitutes a central competence in the clinical routine on which diagnostic and therapeutic steps are based. In medical curricula in Germany, clinical reasoning is currently taught explicitly only to a small extend. Therefore, the aim of this project was to develop and implement a clinical reasoning course in the final year of undergraduate medical training. Project description: A clinical reasoning course with six learning units and 18 learning objectives was developed, which was taught by two to four instructors on the basis of 32 paper cases from the clinical practice of the instructors. In the years 2011 to 2013, the course of eight weeks with two hours per week was taught seven times. Before the first and after the last seminar, the participating students filled out a self-assessment questionnaire with a 6-point Likert scale regarding eight different clinical reasoning skills. At the same times, they received a patient case with the assignment to prepare a case presentation and differential diagnoses. Results: From 128 participating students altogether, 42 complete data sets were available. After the course, participants assessed themselves significantly better than before the course in all eight clinical reasoning skills, for example in “Summarizing and presentation of a paper case” or in the “Skill to enumerate differential diagnoses” (p<0.05). The greatest increase occurred in the skill to recognize typical cognitive errors in medicine and to identify risk situations for their occurrence (pre: 2.98±0.92 and retro-pre: 2.64±1.01, respectively, versus post: 4.38±0.88). Based on the ratio of number of words used per keywords used the problem presentation of the paper case was significantly more focused after the course (p=0.011). A significant increase in the number of gathered differential diagnoses was not detected after the course. Conclusion: The newly developed and established Clinical Reasoning Course leads to a gain in the desired skills from the students’ self-assessment perspective and to a more structured case presentation. To establish better options to exercise clinical reasoning, a longitudinal implementation in the medical curriculum seems to be desirable. Faculty training would be useful to implement the concept as standardized as possible. PMID:29226234

Optimal allocation model of construction land based on two-level system optimization theory

NASA Astrophysics Data System (ADS)

Liu, Min; Liu, Yanfang; Xia, Yuping; Lei, Qihong

2007-06-01

The allocation of construction land is an important task in land-use planning. Whether implementation of planning decisions is a success or not, usually depends on a reasonable and scientific distribution method. Considering the constitution of land-use planning system and planning process in China, multiple levels and multiple objective decision problems is its essence. Also, planning quantity decomposition is a two-level system optimization problem and an optimal resource allocation decision problem between a decision-maker in the topper and a number of parallel decision-makers in the lower. According the characteristics of the decision-making process of two-level decision-making system, this paper develops an optimal allocation model of construction land based on two-level linear planning. In order to verify the rationality and the validity of our model, Baoan district of Shenzhen City has been taken as a test case. Under the assistance of the allocation model, construction land is allocated to ten townships of Baoan district. The result obtained from our model is compared to that of traditional method, and results show that our model is reasonable and usable. In the end, the paper points out the shortcomings of the model and further research directions.

Uncertainty reasoning in expert systems

NASA Technical Reports Server (NTRS)

Kreinovich, Vladik

1993-01-01

Intelligent control is a very successful way to transform the expert's knowledge of the type 'if the velocity is big and the distance from the object is small, hit the brakes and decelerate as fast as possible' into an actual control. To apply this transformation, one must choose appropriate methods for reasoning with uncertainty, i.e., one must: (1) choose the representation for words like 'small', 'big'; (2) choose operations corresponding to 'and' and 'or'; (3) choose a method that transforms the resulting uncertain control recommendations into a precise control strategy. The wrong choice can drastically affect the quality of the resulting control, so the problem of choosing the right procedure is very important. From a mathematical viewpoint these choice problems correspond to non-linear optimization and are therefore extremely difficult. In this project, a new mathematical formalism (based on group theory) is developed that allows us to solve the problem of optimal choice and thus: (1) explain why the existing choices are really the best (in some situations); (2) explain a rather mysterious fact that fuzzy control (i.e., control based on the experts' knowledge) is often better than the control by these same experts; and (3) give choice recommendations for the cases when traditional choices do not work.

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

PubMed

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

2015-03-21

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

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

PubMed

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

2003-10-01

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

Virtual patients in the acquisition of clinical reasoning skills: does presentation mode matter? A quasi-randomized controlled trial.

PubMed

Schubach, Fabian; Goos, Matthias; Fabry, Götz; Vach, Werner; Boeker, Martin

2017-09-15

The objective of this study is to compare two different instructional methods in the curricular use of computerized virtual patients in undergraduate medical education. We aim to investigate whether using many short and focused cases - the key feature principle - is more effective for the learning of clinical reasoning skills than using few long and systematic cases. We conducted a quasi-randomized, non-blinded, controlled parallel-group intervention trial in a large medical school in Southwestern Germany. During two seminar sessions, fourth- and fifth-year medical students (n = 56) worked on the differential diagnosis of the acute abdomen. The educational tool - virtual patients - was the same, but the instructional method differed: In one trial arm, students worked on multiple short cases, with the instruction being focused only on important elements ("key feature arm", n = 30). In the other trial arm, students worked on few long cases, with the instruction being comprehensive and systematic ("systematic arm", n = 26). The overall training time was the same in both arms. The students' clinical reasoning capacity was measured by a specifically developed instrument, a script concordance test. Their motivation and the perceived effectiveness of the instruction were assessed using a structured evaluation questionnaire. Upon completion of the script concordance test with a reference score of 80 points and a standard deviation of 5 for experts, students in the key feature arm attained a mean of 57.4 points (95% confidence interval: 50.9-63.9), and in the systematic arm, 62.7 points (57.2-68.2), with Cohen's d at 0.337. The difference is statistically non-significant (p = 0.214). In the evaluation survey, students in the key feature arm indicated that they experienced more time pressure and perceived the material as more difficult. In this study powered for a medium effect, we could not provide empirical evidence for the hypothesis that a key feature-based instruction on multiple short cases is superior to a systematic instruction on few long cases in the curricular implementation of virtual patients. The results of the evaluation survey suggest that learners should be given enough time to work through case examples, and that caution should be taken to prevent cognitive overload.

Hard-Rock Stability Analysis for Span Design in Entry-Type Excavations with Learning Classifiers

PubMed Central

García-Gonzalo, Esperanza; Fernández-Muñiz, Zulima; García Nieto, Paulino José; Bernardo Sánchez, Antonio; Menéndez Fernández, Marta

2016-01-01

The mining industry relies heavily on empirical analysis for design and prediction. An empirical design method, called the critical span graph, was developed specifically for rock stability analysis in entry-type excavations, based on an extensive case-history database of cut and fill mining in Canada. This empirical span design chart plots the critical span against rock mass rating for the observed case histories and has been accepted by many mining operations for the initial span design of cut and fill stopes. Different types of analysis have been used to classify the observed cases into stable, potentially unstable and unstable groups. The main purpose of this paper is to present a new method for defining rock stability areas of the critical span graph, which applies machine learning classifiers (support vector machine and extreme learning machine). The results show a reasonable correlation with previous guidelines. These machine learning methods are good tools for developing empirical methods, since they make no assumptions about the regression function. With this software, it is easy to add new field observations to a previous database, improving prediction output with the addition of data that consider the local conditions for each mine. PMID:28773653

Hard-Rock Stability Analysis for Span Design in Entry-Type Excavations with Learning Classifiers.

PubMed

García-Gonzalo, Esperanza; Fernández-Muñiz, Zulima; García Nieto, Paulino José; Bernardo Sánchez, Antonio; Menéndez Fernández, Marta

2016-06-29

The mining industry relies heavily on empirical analysis for design and prediction. An empirical design method, called the critical span graph, was developed specifically for rock stability analysis in entry-type excavations, based on an extensive case-history database of cut and fill mining in Canada. This empirical span design chart plots the critical span against rock mass rating for the observed case histories and has been accepted by many mining operations for the initial span design of cut and fill stopes. Different types of analysis have been used to classify the observed cases into stable, potentially unstable and unstable groups. The main purpose of this paper is to present a new method for defining rock stability areas of the critical span graph, which applies machine learning classifiers (support vector machine and extreme learning machine). The results show a reasonable correlation with previous guidelines. These machine learning methods are good tools for developing empirical methods, since they make no assumptions about the regression function. With this software, it is easy to add new field observations to a previous database, improving prediction output with the addition of data that consider the local conditions for each mine.

The Case Method in Teaching Critical Thinking.

ERIC Educational Resources Information Center

Gantt, Vernon W.

When one instructor teaches a course called "Communication and Critical Thinking," he uses Josina Makau's book "Reasoning and Communication: Thinking Critically about Arguments" (1990), which maintains that critical thinking requires training. Case methodology can be used for training, not exclusively but as an alternative to…

The harms of enhancement and the conclusive reasons view.

PubMed

Douglas, Thomas

2015-01-01

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

Reasoning with case histories of process knowledge for efficient process development

NASA Technical Reports Server (NTRS)

Bharwani, Seraj S.; Walls, Joe T.; Jackson, Michael E.

1988-01-01

The significance of compiling case histories of empirical process knowledge and the role of such histories in improving the efficiency of manufacturing process development is discussed in this paper. Methods of representing important investigations as cases and using the information from such cases to eliminate redundancy of empirical investigations in analogous process development situations are also discussed. A system is proposed that uses such methods to capture the problem-solving framework of the application domain. A conceptual design of the system is presented and discussed.

A duality theorem-based algorithm for inexact quadratic programming problems: Application to waste management under uncertainty

NASA Astrophysics Data System (ADS)

Kong, X. M.; Huang, G. H.; Fan, Y. R.; Li, Y. P.

2016-04-01

In this study, a duality theorem-based algorithm (DTA) for inexact quadratic programming (IQP) is developed for municipal solid waste (MSW) management under uncertainty. It improves upon the existing numerical solution method for IQP problems. The comparison between DTA and derivative algorithm (DAM) shows that the DTA method provides better solutions than DAM with lower computational complexity. It is not necessary to identify the uncertain relationship between the objective function and decision variables, which is required for the solution process of DAM. The developed method is applied to a case study of MSW management and planning. The results indicate that reasonable solutions have been generated for supporting long-term MSW management and planning. They could provide more information as well as enable managers to make better decisions to identify desired MSW management policies in association with minimized cost under uncertainty.

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

PubMed Central

Gustafsson, Marie; Jontell, Mats; Torgersson, Olof

2008-01-01

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

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

PubMed

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

2016-11-01

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

An improved silhouette for human pose estimation

NASA Astrophysics Data System (ADS)

Hawes, Anthony H.; Iftekharuddin, Khan M.

2017-08-01

We propose a novel method for analyzing images that exploits the natural lines of a human poses to find areas where self-occlusion could be present. Errors caused by self-occlusion cause several modern human pose estimation methods to mis-identify body parts, which reduces the performance of most action recognition algorithms. Our method is motivated by the observation that, in several cases, occlusion can be reasoned using only boundary lines of limbs. An intelligent edge detection algorithm based on the above principle could be used to augment the silhouette with information useful for pose estimation algorithms and push forward progress on occlusion handling for human action recognition. The algorithm described is applicable to computer vision scenarios involving 2D images and (appropriated flattened) 3D images.

Linguistic and pragmatic constraints on utterance interpretation

NASA Astrophysics Data System (ADS)

Hinkelman, Elizabeth A.

1990-05-01

In order to model how people understand language, it is necessary to understand not only grammar and logic but also how people use language to affect their environment. This area of study is known as natural language pragmatics. Speech acts, for instance, are the offers, promises, announcements, etc., that people make by talking. The same expression may be different acts in different contexts, and yet not every expression performs every act. We want to understand how people are able to recognize other's intentions and implications in saying something. Previous plan-based theories of speech act interpretation do not account for the conventional aspect of speech acts. They can, however, be made sensitive to both linguistic and propositional information. This dissertation presents a method of speech act interpretation which uses patterns of linguistic features (e.g., mood, verb form, sentence adverbials, thematic roles) to identify a range of speech act interpretations for the utterance. These are then filtered and elaborated by inferences about agents' goals and plans. In many cases the plan reasoning consists of short, local inference chains (that are in fact conversational implicatures) and, extended reasoning is necessary only for the most difficult cases. The method is able to accommodate a wide range of cases, from those which seem very idiomatic to those which must be analyzed using knowledge about the world and human behavior. It explains how, Can you pass the salt, can be a request while, Are you able to pass the salt, is not.

Severe forms of concealed penis without hypospadias: Surgical strategies

PubMed Central

de Jesus, Lisieux Eyer; Dekermacher, Samuel; Anderson, Kleber M.

2015-01-01

Introduction: Concealed penis (CP) may vary in severity and includes megaprepuce (MP) as a variant. Many different surgical strategies have been described in order to maximize penile exposure and to deal with skin deficiency. We describe the strategies that we use to overcome technical problems in severe cases of CP. Materials and Methods: Six consecutive cases of severe CP (including 3 with MP) were treated in a 2-year period between January 2011 and April 2013. These patients were treated using extensive degloving, removal of dysplastic dartos, Alexander's preputial flap, scrotal flaps and skin grafts. Three patients had been previously circumcised. Cases associated with hypospadias, obesity, disorders of sexual differentiation and micropenises were excluded. Results: All six patients attained good results, with good exposure of the penis, ability to void standing with a well-directed flow and reasonable esthetic results. A technical algorithm for the treatment of primary or recurring cases of CP is proposed. Conclusion: Alexander’ s distally based ventral preputial flap is a useful technical resource to treat MP cases. Free skin grafts and/or laterally based scrotal flaps may be used to cover the penis after release in severe cases of CP. PMID:26604447

Philosophical methodology and strikes.

PubMed

Thomasma, David C

1991-01-01

...how do we train residents to employ ethical reasoning? This is a good question, not only for the problem of strikes, but also for all medical training. The best method is inductive, since that most closely parallels the clinical reasoning processes that define the reality of medical practice. The strengths of inductive reasoning are that it most closely matches the realities of practice, it arises from the particular circumstances of the case, and it leads to a casuistic conclusion that applies more directly than abstract reasoning models to the problem at hand. The weaknesses, though, require that inductive models include a check and balance.

A cloud-based multimodality case file for mobile devices.

PubMed

Balkman, Jason D; Loehfelm, Thomas W

2014-01-01

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

Learning material recommendation based on case-based reasoning similarity scores

NASA Astrophysics Data System (ADS)

Masood, Mona; Mokmin, Nur Azlina Mohamed

2017-10-01

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

Smoking cessation and the Internet: a qualitative method examining online consumer behavior.

PubMed

Frisby, Genevieve; Bessell, Tracey L; Borland, Ron; Anderson, Jeremy N

2002-01-01

Smoking is a major preventable cause of disease and disability around the world. Smoking cessation support-including information, discussion groups, cognitive behavioral treatment, and self-help materials-can be delivered via the Internet. There is limited information about the reasons and methods consumers access smoking cessation information on the Internet. This study aims to determine the feasibility of a method to examine the online behavior of consumers seeking smoking cessation resources. In particular, we sought to identify the reasons and methods consumers use to access and assess the quality of these resources. Thirteen participants were recruited via the state-based Quit smoking cessation campaign, operated by the Victorian Cancer Council, in December 2001. Online behavior was evaluated using semi-structured interviews and Internet simulations where participants sought smoking cessation information and addressed set-case scenarios. Online interaction was tracked through pervasive logging with specialist software. Thirteen semi-structured interviews and 4 Internet simulations were conducted in January 2002. Participants sought online smoking cessation resources for reasons of convenience, timeliness, and anonymity-and because their current information needs were unmet. They employed simple search strategies and could not always find information in an efficient manner. Participants employed several different strategies to assess the quality of online health resources. Consumer online behavior can be studied using a combination of survey, observation, and online surveillance. However, further qualitative and observational research is required to harness the full potential of the Internet to deliver public health resources.

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

PubMed

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

2014-07-03

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

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

PubMed

Dakin, Emily

2014-01-01

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

To BECCS or Not To BECCS: A Question of Method

NASA Astrophysics Data System (ADS)

DeCicco, J. M.

2017-12-01

Bioenergy with carbon capture and storage (BECCS) is seen as an important option in many climate stabilization scenarios. Limited demonstrations are underway, including a system that captures and sequesters the fermentation CO2 from ethanol production. However, its net CO2 emissions are uncertain for reasons related to both system characteristics and methodological issues. As for bioenergy in general, evaluations draw on both ecological and engineering methods. It is informative to apply different methods using available data for demonstration systems in comparison to related bioenergy systems. To do so, this paper examines a case study BECCS system and addresses questions regarding the utilization of terrestrial carbon, biomass sustainability and the implications for scalability. The analysis examines four systems, all utilizing the same land area, using two methods. The cases are: A) a crop system without either biofuel production or CCS; B) a biofuel production system without CCS; C) biofuel system with CCS, i.e., the BECCS case, and D) a crop system without biofuel production or CCS but with crop residue removal and conversion to a stable char. In cases A and D, the delivered fuel is fossil-based; in cases B and C the fuel is biomass-based. The first method is LCA, involving steady-flow modeling of systems over a defined lifecycle, following current practice as seen in the attributional LCA component of California's Low-Carbon Fuel Standard (LCFS). The second method involves spatially and temporally explicit analysis, reflecting the dynamics of carbon exchanges with the atmosphere. Although parameters are calibrated to the California LCFS LCA model, simplified spreadsheet modeling is used to maximize transparency while highlighting assumptions that most influence the results. The analysis reveals distinctly different pictures of net CO2 emissions for the cases examined, with the dynamic method painting a less optimistic picture of the BECCS system than the LCA method. Differences in results are traced to differing representations of terrestrial carbon exchanges and associated modeling assumptions. We conclude with suggestions for future work on project- and program-scale carbon accounting methods and the need for caution in advancing BECCS before such methods are better validated.

16 CFR 306.5 - Automotive fuel rating.

Code of Federal Regulations, 2011 CFR

2011-01-01

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

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

ERIC Educational Resources Information Center

Thacker, Rebecca A.; Gohmann, Stephen F.

1993-01-01

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

Probabilistic Reasoning for Plan Robustness

NASA Technical Reports Server (NTRS)

Schaffer, Steve R.; Clement, Bradley J.; Chien, Steve A.

2005-01-01

A planning system must reason about the uncertainty of continuous variables in order to accurately project the possible system state over time. A method is devised for directly reasoning about the uncertainty in continuous activity duration and resource usage for planning problems. By representing random variables as parametric distributions, computing projected system state can be simplified in some cases. Common approximation and novel methods are compared for over-constrained and lightly constrained domains. The system compares a few common approximation methods for an iterative repair planner. Results show improvements in robustness over the conventional non-probabilistic representation by reducing the number of constraint violations witnessed by execution. The improvement is more significant for larger problems and problems with higher resource subscription levels but diminishes as the system is allowed to accept higher risk levels.

Spectral signature variations, atmospheric scintillations and sensor parameters

NASA Astrophysics Data System (ADS)

Berger, Henry; Neander, John

2002-11-01

The spectral signature of a material is the curve of power density vs. wavelength (λ) obtained from measurements of reflected light. It is used, among other things, for the identification of targets in remotely acquired images. Sometimes, however, unpredictable distortions may prevent this. In only a few cases have such distortions been explained. We propose some reasonable arguments that in a significant number of circumstances, atmospheric turbulence may contribute to such spectral signature distortion. We propose, based on this model, what appears to be one method that could combat such distortion.

Structure-based CoMFA as a predictive model - CYP2C9 inhibitors as a test case.

PubMed

Yasuo, Kazuya; Yamaotsu, Noriyuki; Gouda, Hiroaki; Tsujishita, Hideki; Hirono, Shuichi

2009-04-01

In this study, we tried to establish a general scheme to create a model that could predict the affinity of small compounds to their target proteins. This scheme consists of a search for ligand-binding sites on a protein, a generation of bound conformations (poses) of ligands in each of the sites by docking, identifications of the correct poses of each ligand by consensus scoring and MM-PBSA analysis, and a construction of a CoMFA model with the obtained poses to predict the affinity of the ligands. By using a crystal structure of CYP 2C9 and the twenty known CYP inhibitors as a test case, we obtained a CoMFA model with a good statistics, which suggested that the classification of the binding sites as well as the predicted bound poses of the ligands should be reasonable enough. The scheme described here would give a method to predict the affinity of small compounds with a reasonable accuracy, which is expected to heighten the value of computational chemistry in the drug design process.

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

NASA Astrophysics Data System (ADS)

Park, J.; Yoo, K.

2013-12-01

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

Preferences of Teaching Methods and Techniques in Mathematics with Reasons

ERIC Educational Resources Information Center

Ünal, Menderes

2017-01-01

In this descriptive study, the goal was to determine teachers' preferred pedagogical methods and techniques in mathematics. Qualitative research methods were employed, primarily case studies. 40 teachers were randomly chosen from various secondary schools in Kirsehir during the 2015-2016 educational terms, and data were gathered via…

A method of classification for multisource data in remote sensing based on interval-valued probabilities

NASA Technical Reports Server (NTRS)

Kim, Hakil; Swain, Philip H.

1990-01-01

An axiomatic approach to intervalued (IV) probabilities is presented, where the IV probability is defined by a pair of set-theoretic functions which satisfy some pre-specified axioms. On the basis of this approach representation of statistical evidence and combination of multiple bodies of evidence are emphasized. Although IV probabilities provide an innovative means for the representation and combination of evidential information, they make the decision process rather complicated. It entails more intelligent strategies for making decisions. The development of decision rules over IV probabilities is discussed from the viewpoint of statistical pattern recognition. The proposed method, so called evidential reasoning method, is applied to the ground-cover classification of a multisource data set consisting of Multispectral Scanner (MSS) data, Synthetic Aperture Radar (SAR) data, and digital terrain data such as elevation, slope, and aspect. By treating the data sources separately, the method is able to capture both parametric and nonparametric information and to combine them. Then the method is applied to two separate cases of classifying multiband data obtained by a single sensor. In each case a set of multiple sources is obtained by dividing the dimensionally huge data into smaller and more manageable pieces based on the global statistical correlation information. By a divide-and-combine process, the method is able to utilize more features than the conventional maximum likelihood method.

GhostWriter-2.0: Product Reviews with Case-Based Support

NASA Astrophysics Data System (ADS)

Bridge, Derek; Healy, Paul

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

A way forward for teaching and learning of Physiology: Students’ perception of the effectiveness of teaching methodologies

PubMed Central

Rehan, Rabiya; Ahmed, Khalid; Khan, Hira; Rehman, Rehana

2016-01-01

Objective: To compare the perception of medical students on the usefulness of the interactive lectures, case-based lectures, and structured interactive sessions (SIS) in teaching and learning of Physiology. Methods: A cross-sectional study was carried out from January to December 2012 at Bahria University Medical & Dental College, Karachi, which had qualitative and quantitative aspects, assessed by self- reported questionnaire and focused group discussion (FGD). The questionnaire was distributed to 100 medical students after completion of first year of teaching of MBBS Physiology. The data was analyzed using SPSS version 15. Differences were considered significant at p-values <0.05 after application of Friedman test. Responses of FGD were analyzed. Results: All the teaching methodologies helped in understanding of precise learning objectives. The comprehension of structure and functions with understanding of difficult concepts was made best possible by SIS (p=0.04, p<0.01). SIS enabled adult learning, self-directed learning, peer learning and critical reasoning more than the other teaching strategies (p< 0.01). Conclusion: SIS involved students who used reasoning skills and power of discussion in a group to comprehend difficult concepts for better understanding of Physiology as compared to interactive and case-based lectures. PMID:28083047

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

NASA Astrophysics Data System (ADS)

Develaki, Maria

2017-11-01

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

The Effects of Integrating LEGO Robotics into a Mathematics Curriculum to Promote the Development of Proportional Reasoning

ERIC Educational Resources Information Center

Casler-Failing, Shelli L.

2017-01-01

This mixed methods, action research case study sought to investigate the effects of incorporating LEGO robotics into a seventh grade mathematics curriculum focused on the development of proportional reasoning through the lens of Social Constructivist Theory. Quantitative data was collected via pre- and post-tests from the mathematics class of six…

On the Reasons We Want Teachers of Good Disposition and Moral Character

ERIC Educational Resources Information Center

Osguthorpe, Richard D.

2008-01-01

The point of this article is to make a case for teachers of moral disposition without regard for the moral development of students. The article concludes that there are multiple reasons for wanting teachers of good disposition and moral character; that teachers' dispositions are best conceived as modifiers to the methods that they employ; and that…

Brain Imaging, Forward Inference, and Theories of Reasoning

PubMed Central

Heit, Evan

2015-01-01

This review focuses on the issue of how neuroimaging studies address theoretical accounts of reasoning, through the lens of the method of forward inference (Henson, 2005, 2006). After theories of deductive and inductive reasoning are briefly presented, the method of forward inference for distinguishing between psychological theories based on brain imaging evidence is critically reviewed. Brain imaging studies of reasoning, comparing deductive and inductive arguments, comparing meaningful versus non-meaningful material, investigating hemispheric localization, and comparing conditional and relational arguments, are assessed in light of the method of forward inference. Finally, conclusions are drawn with regard to future research opportunities. PMID:25620926

Brain imaging, forward inference, and theories of reasoning.

PubMed

Heit, Evan

2014-01-01

This review focuses on the issue of how neuroimaging studies address theoretical accounts of reasoning, through the lens of the method of forward inference (Henson, 2005, 2006). After theories of deductive and inductive reasoning are briefly presented, the method of forward inference for distinguishing between psychological theories based on brain imaging evidence is critically reviewed. Brain imaging studies of reasoning, comparing deductive and inductive arguments, comparing meaningful versus non-meaningful material, investigating hemispheric localization, and comparing conditional and relational arguments, are assessed in light of the method of forward inference. Finally, conclusions are drawn with regard to future research opportunities.

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

PubMed

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

2016-05-01

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

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

PubMed

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

2016-03-01

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

Smoking Cessation and the Internet: A Qualitative Method Examining Online Consumer Behavior

PubMed Central

Frisby, Genevieve; Borland, Ron; Anderson, Jeremy N

2002-01-01

Background Smoking is a major preventable cause of disease and disability around the world. Smoking cessation support — including information, discussion groups, cognitive behavioral treatment, and self-help materials — can be delivered via the Internet. There is limited information about the reasons and methods consumers access smoking cessation information on the Internet. Objectives This study aims to determine the feasibility of a method to examine the online behavior of consumers seeking smoking cessation resources. In particular, we sought to identify the reasons and methods consumers use to access and assess the quality of these resources. Methods Thirteen participants were recruited via the state-based Quit® smoking cessation campaign, operated by the Victorian Cancer Council, in December 2001. Online behavior was evaluated using semi-structured interviews and Internet simulations where participants sought smoking cessation information and addressed set-case scenarios. Online interaction was tracked through pervasive logging with specialist software. Results Thirteen semi-structured interviews and 4 Internet simulations were conducted in January 2002. Participants sought online smoking cessation resources for reasons of convenience, timeliness, and anonymity — and because their current information needs were unmet. They employed simple search strategies and could not always find information in an efficient manner. Participants employed several different strategies to assess the quality of online health resources. Conclusions Consumer online behavior can be studied using a combination of survey, observation, and online surveillance. However, further qualitative and observational research is required to harness the full potential of the Internet to deliver public health resources. PMID:12554555

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

PubMed

Merisier, Sophia; Larue, Caroline; Boyer, Louise

2018-06-01

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

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

PubMed

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

2017-01-01

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

Major Anthropogenic Causes for and Outcomes of Wild Animal Presentation to a Wildlife Clinic in East Tennessee, USA, 2000–2011

PubMed Central

Schenk, Ashley N.; Souza, Marcy J.

2014-01-01

To determine the reasons for presentation and outcome of wildlife cases in East Tennessee, a retrospective analysis was performed using 14,303 records from cases presented to the wildlife clinic of the University of Tennessee Veterinary Teaching Hospital between 2000 and 2011. The cases were first categorized into amphibian/non-avian reptile, mammal, or avian and then classified into groups based on the primary admitting/presenting sign. There are a variety of reasons animals were presented to the clinic, and some were directly or indirectly anthropogenic in origin, including cat related, dog related, hit by automobile, and other human encounters leading to trauma; of the cases reviewed, 4,443 (31.1%) presented for one of these 4 reasons. Overall case fatality risk in regard to these 4 admitting/presenting signs was 0.519 for the amphibian/non-avian reptile cases, 0.675 for mammal cases, and 0.687 for avian cases. This study confirms the importance of monitoring wildlife morbidity and mortality and of focusing efforts to reduce the anthropogenic threat on native habitats and resident wildlife populations. PMID:24686490

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

PubMed

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

2008-12-01

Emotional and parent-based reasoning refer to the tendency to rely on personal or parental anxiety response information rather than on objective danger information when estimating the dangerousness of a situation. This study investigated the prospective relationships of emotional and parent-based reasoning with anxiety symptoms in a sample of non-clinical children aged 8-14 years (n = 122). Children completed the anxiety subscales of the Revised Children's Anxiety and Depression Scale (Muris et al. Clin Psychol Psychother 9:430-442, 2002) and provided danger ratings of scenarios that systematically combined objective danger and objective safety information with anxiety-response and positive-response information. These measurements were repeated 10 months later (range 8-11 months). Emotional and parent-based reasoning effects emerged on both occasions. In addition, both effects were modestly stable, but only in case of objective safety. Evidence was found that initial anxiety levels were positively related to emotional reasoning 10 months later. In addition, initial levels of emotional reasoning were positively related to anxiety at a later time, but only when age was taken into account. That is, this relationship changed with increasing age from positive to negative. No significant prospective relationships emerged between anxiety and parent-based reasoning. As yet the clinical implications of these findings are limited, although preliminary evidence indicates that interpretation bias can be modified to decrease anxiety.

A Study of the Reasoning Abilities of Ninth Standard Students with Respect to Their Gender and Type of the Institution

ERIC Educational Resources Information Center

Sarsani, Mahender Reddy

2008-01-01

Reasoning and learning are closely related, both being the methods of solving problems, learning usually results from the process of reasoning. All inventions, discoveries, art, literature and advances in culture and civilization are based on thinking, reasoning and problem solving capacity of human being. A sound reasoning leads to better…

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

PubMed

Drescher, Uta; Warren, Fiona; Norton, Kingsley

2004-12-01

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

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

NASA Astrophysics Data System (ADS)

Tripathy, Debi Prasad; Ala, Charan Kumar

2018-04-01

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

Summative assessment of 5th year medical students’ clinical reasoning by script concordance test: requirements and challenges

PubMed Central

2012-01-01

Background The Script Concordance Test (SCT) has not been reported in summative assessment of students across the multiple domains of a medical curriculum. We report the steps used to build a test for summative assessment in a medical curriculum. Methods A 51 case, 158-question, multidisciplinary paper was constructed to assess clinical reasoning in 5th-year. 10–16 experts in each of 7 discipline-based reference panels answered questions on-line. A multidisciplinary group considered reference panel data and data from a volunteer group of 6th Years, who sat the same test, to determine the passing score for the 5th Years. Results The mean (SD) scores were 63.6 (7.6) and 68.6 (4.8) for the 6th Year (n = 23, alpha = 0.78) and and 5th Year (n = 132, alpha =0.62) groups (p < 0.05), respectively. The passing score was set at 4 SD from the expert mean. Four students failed. Conclusions The SCT may be a useful method to assess clinical reasoning in medical students in multidisciplinary summative assessments. Substantial investment in training of faculty and students and in the development of questions is required. PMID:22571351

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

PubMed

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

2016-05-01

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

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

ERIC Educational Resources Information Center

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

2018-01-01

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

A systematic composite service design modeling method using graph-based theory.

PubMed

Elhag, Arafat Abdulgader Mohammed; Mohamad, Radziah; Aziz, Muhammad Waqar; Zeshan, Furkh

2015-01-01

The composite service design modeling is an essential process of the service-oriented software development life cycle, where the candidate services, composite services, operations and their dependencies are required to be identified and specified before their design. However, a systematic service-oriented design modeling method for composite services is still in its infancy as most of the existing approaches provide the modeling of atomic services only. For these reasons, a new method (ComSDM) is proposed in this work for modeling the concept of service-oriented design to increase the reusability and decrease the complexity of system while keeping the service composition considerations in mind. Furthermore, the ComSDM method provides the mathematical representation of the components of service-oriented design using the graph-based theoryto facilitate the design quality measurement. To demonstrate that the ComSDM method is also suitable for composite service design modeling of distributed embedded real-time systems along with enterprise software development, it is implemented in the case study of a smart home. The results of the case study not only check the applicability of ComSDM, but can also be used to validate the complexity and reusability of ComSDM. This also guides the future research towards the design quality measurement such as using the ComSDM method to measure the quality of composite service design in service-oriented software system.

A Systematic Composite Service Design Modeling Method Using Graph-Based Theory

PubMed Central

Elhag, Arafat Abdulgader Mohammed; Mohamad, Radziah; Aziz, Muhammad Waqar; Zeshan, Furkh

2015-01-01

The composite service design modeling is an essential process of the service-oriented software development life cycle, where the candidate services, composite services, operations and their dependencies are required to be identified and specified before their design. However, a systematic service-oriented design modeling method for composite services is still in its infancy as most of the existing approaches provide the modeling of atomic services only. For these reasons, a new method (ComSDM) is proposed in this work for modeling the concept of service-oriented design to increase the reusability and decrease the complexity of system while keeping the service composition considerations in mind. Furthermore, the ComSDM method provides the mathematical representation of the components of service-oriented design using the graph-based theoryto facilitate the design quality measurement. To demonstrate that the ComSDM method is also suitable for composite service design modeling of distributed embedded real-time systems along with enterprise software development, it is implemented in the case study of a smart home. The results of the case study not only check the applicability of ComSDM, but can also be used to validate the complexity and reusability of ComSDM. This also guides the future research towards the design quality measurement such as using the ComSDM method to measure the quality of composite service design in service-oriented software system. PMID:25928358

Method for Calculating the Optical Diffuse Reflection Coefficient for the Ocular Fundus

NASA Astrophysics Data System (ADS)

Lisenko, S. A.; Kugeiko, M. M.

2016-07-01

We have developed a method for calculating the optical diffuse reflection coefficient for the ocular fundus, taking into account multiple scattering of light in its layers (retina, epithelium, choroid) and multiple refl ection of light between layers. The method is based on the formulas for optical "combination" of the layers of the medium, in which the optical parameters of the layers (absorption and scattering coefficients) are replaced by some effective values, different for cases of directional and diffuse illumination of the layer. Coefficients relating the effective optical parameters of the layers and the actual values were established based on the results of a Monte Carlo numerical simulation of radiation transport in the medium. We estimate the uncertainties in retrieval of the structural and morphological parameters for the fundus from its diffuse reflectance spectrum using our method. We show that the simulated spectra correspond to the experimental data and that the estimates of the fundus parameters obtained as a result of solving the inverse problem are reasonable.

MapReduce Based Parallel Bayesian Network for Manufacturing Quality Control

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

geneCBR: a translational tool for multiple-microarray analysis and integrative information retrieval for aiding diagnosis in cancer research.

PubMed

Glez-Peña, Daniel; Díaz, Fernando; Hernández, Jesús M; Corchado, Juan M; Fdez-Riverola, Florentino

2009-06-18

Bioinformatics and medical informatics are two research fields that serve the needs of different but related communities. Both domains share the common goal of providing new algorithms, methods and technological solutions to biomedical research, and contributing to the treatment and cure of diseases. Although different microarray techniques have been successfully used to investigate useful information for cancer diagnosis at the gene expression level, the true integration of existing methods into day-to-day clinical practice is still a long way off. Within this context, case-based reasoning emerges as a suitable paradigm specially intended for the development of biomedical informatics applications and decision support systems, given the support and collaboration involved in such a translational development. With the goals of removing barriers against multi-disciplinary collaboration and facilitating the dissemination and transfer of knowledge to real practice, case-based reasoning systems have the potential to be applied to translational research mainly because their computational reasoning paradigm is similar to the way clinicians gather, analyze and process information in their own practice of clinical medicine. In addressing the issue of bridging the existing gap between biomedical researchers and clinicians who work in the domain of cancer diagnosis, prognosis and treatment, we have developed and made accessible a common interactive framework. Our geneCBR system implements a freely available software tool that allows the use of combined techniques that can be applied to gene selection, clustering, knowledge extraction and prediction for aiding diagnosis in cancer research. For biomedical researches, geneCBR expert mode offers a core workbench for designing and testing new techniques and experiments. For pathologists or oncologists, geneCBR diagnostic mode implements an effective and reliable system that can diagnose cancer subtypes based on the analysis of microarray data using a CBR architecture. For programmers, geneCBR programming mode includes an advanced edition module for run-time modification of previous coded techniques. geneCBR is a new translational tool that can effectively support the integrative work of programmers, biomedical researches and clinicians working together in a common framework. The code is freely available under the GPL license and can be obtained at http://www.genecbr.org.

Price elasticity matrix of demand in power system considering demand response programs

NASA Astrophysics Data System (ADS)

Qu, Xinyao; Hui, Hongxun; Yang, Shengchun; Li, Yaping; Ding, Yi

2018-02-01

The increasing renewable energy power generations have brought more intermittency and volatility to the electric power system. Demand-side resources can improve the consumption of renewable energy by demand response (DR), which becomes one of the important means to improve the reliability of power system. In price-based DR, the sensitivity analysis of customer’s power demand to the changing electricity prices is pivotal for setting reasonable prices and forecasting loads of power system. This paper studies the price elasticity matrix of demand (PEMD). An improved PEMD model is proposed based on elasticity effect weight, which can unify the rigid loads and flexible loads. Moreover, the structure of PEMD, which is decided by price policies and load types, and the calculation method of PEMD are also proposed. Several cases are studied to prove the effectiveness of this method.

Dendritic cells (DCs) can be successfully generated from leukemic blasts in individual patients with AML or MDS: an evaluation of different methods.

PubMed

Kremser, Andreas; Dressig, Julia; Grabrucker, Christine; Liepert, Anja; Kroell, Tanja; Scholl, Nina; Schmid, Christoph; Tischer, Johanna; Kufner, Stefanie; Salih, Helmut; Kolb, Hans Jochem; Schmetzer, Helga

2010-01-01

Myeloid-leukemic cells (AML, MDS, CML) can be differentiated to leukemia-derived dendritic cell [DC (DCleu)] potentially presenting the whole leukemic antigen repertoire without knowledge of distinct leukemia antigens and are regarded as promising candidates for a vaccination strategy. We studied the capability of 6 serum-free DC culture methods, chosen according to different mechanisms, to induce DC differentiation in 137 cases of AML and 52 cases of MDS. DC-stimulating substances were cytokines ("standard-medium", "MCM-Mimic", "cytokine-method"), bacterial lysates ("Picibanil"), double-stranded RNA ["Poly (I:C)"] or a cytokine bypass method ("Ca-ionophore"). The quality/quantity of DC generated was estimated by flow cytometry studying (co) expressions of "DC"antigens, costimulatory, maturation, and blast-antigens. Comparing these methods on average 15% to 32% DC, depending on methods used, could be obtained from blast-containing mononuclear cells (MNC) in AML/MDS cases with a DC viability of more than 60%. In all, 39% to 64% of these DC were mature; 31% to 52% of leukemic blasts could be converted to DCleu and DCleu-proportions in the suspension were 2% to 70% (13%). Average results of all culture methods tested were comparable, however not every given case of AML could be differentiated to DC with 1 selected method. However performing a pre-analysis with 3 DC-generating methods (MCM-Mimic, Picibanil, Ca-ionophore) we could generate DC in any given case. Functional analyses provided proof, that DC primed T cells to antileukemia-directed cytotoxic cells, although an anti-leukemic reaction was not achieved in every case. In summary our data show that a successful, quantitative DC/DCleu generation is possible with the best of 3 previously tested methods in any given case. Reasons for different functional behaviors of DC-primed T cells must be evaluated to design a practicable DC-based vaccination strategy.

Increasing Reasoning Awareness: Video Analysis of Students’ Two-Party Virtual Patient Interactions

PubMed Central

Parodis, Ioannis; Lundberg, Ingrid E

2018-01-01

Background Collaborative reasoning occurs in clinical practice but is rarely developed during education. The computerized virtual patient (VP) cases allow for a stepwise exploration of cases and thus stimulate active learning. Peer settings during VP sessions are believed to have benefits in terms of reasoning but have received scant attention in the literature. Objective The objective of this study was to thoroughly investigate interactions during medical students’ clinical reasoning in two-party VP settings. Methods An in-depth exploration of students’ interactions in dyad settings of VP sessions was performed. For this purpose, two prerecorded VP sessions lasting 1 hour each were observed, transcribed in full, and analyzed. The transcriptions were analyzed using thematic analysis, and short clips from the videos were selected for subsequent analysis in relation to clinical reasoning and clinical aspects. Results Four categories of interactions were identified: (1) task-related dialogue, in which students negotiated a shared understanding of the task and strategies for information gathering; (2) case-related insights and perspectives were gained, and the students consolidated and applied preexisting biomedical knowledge into a clinical setting; (3) clinical reasoning interactions were made explicit. In these, hypotheses were followed up and clinical examples were used. The researchers observed interactions not only between students and the VP but also (4) interactions with other resources, such as textbooks. The interactions are discussed in relation to theories of clinical reasoning and peer learning. Conclusions The dyad VP setting is conducive to activities that promote analytic clinical reasoning. In this setting, components such as peer interaction, access to different resources, and reduced time constraints provided a productive situation in which the students pursued different lines of reasoning. PMID:29487043

Case-Based Planning: An Integrated Theory of Planning, Learning and Memory

DTIC Science & Technology

1986-10-01

rtvoeoo oldo II nocomtmry and Idonltly by block numbor) planning Case-based reasoning learning Artificial Intelligence 20. ABSTRACT (Conllnum...Computational Model of Analogical Prob- lem Solving, Proceedings of the Seventh International Joint Conference on Artificial Intelligence ...Understanding and Generalizing Plans., Proceedings of the Eight Interna- tional Joint Conference on Artificial Intelligence , IJCAI, Karlsrhue, Germany

Weather-based prediction of Plasmodium falciparum malaria in epidemic-prone regions of Ethiopia II. Weather-based prediction systems perform comparably to early detection systems in identifying times for interventions.

PubMed

Teklehaimanot, Hailay D; Schwartz, Joel; Teklehaimanot, Awash; Lipsitch, Marc

2004-11-19

Timely and accurate information about the onset of malaria epidemics is essential for effective control activities in epidemic-prone regions. Early warning methods that provide earlier alerts (usually by the use of weather variables) may permit control measures to interrupt transmission earlier in the epidemic, perhaps at the expense of some level of accuracy. Expected case numbers were modeled using a Poisson regression with lagged weather factors in a 4th-degree polynomial distributed lag model. For each week, the numbers of malaria cases were predicted using coefficients obtained using all years except that for which the prediction was being made. The effectiveness of alerts generated by the prediction system was compared against that of alerts based on observed cases. The usefulness of the prediction system was evaluated in cold and hot districts. The system predicts the overall pattern of cases well, yet underestimates the height of the largest peaks. Relative to alerts triggered by observed cases, the alerts triggered by the predicted number of cases performed slightly worse, within 5% of the detection system. The prediction-based alerts were able to prevent 10-25% more cases at a given sensitivity in cold districts than in hot ones. The prediction of malaria cases using lagged weather performed well in identifying periods of increased malaria cases. Weather-derived predictions identified epidemics with reasonable accuracy and better timeliness than early detection systems; therefore, the prediction of malarial epidemics using weather is a plausible alternative to early detection systems.

Deriving Safety Cases from Automatically Constructed Proofs

NASA Technical Reports Server (NTRS)

Basir, Nurlida; Denney, Ewen; Fischer, Bernd

2009-01-01

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

Forecasting malaria incidence based on monthly case reports and environmental factors in Karuzi, Burundi, 1997–2003

PubMed Central

Gomez-Elipe, Alberto; Otero, Angel; van Herp, Michel; Aguirre-Jaime, Armando

2007-01-01

Background The objective of this work was to develop a model to predict malaria incidence in an area of unstable transmission by studying the association between environmental variables and disease dynamics. Methods The study was carried out in Karuzi, a province in the Burundi highlands, using time series of monthly notifications of malaria cases from local health facilities, data from rain and temperature records, and the normalized difference vegetation index (NDVI). Using autoregressive integrated moving average (ARIMA) methodology, a model showing the relation between monthly notifications of malaria cases and the environmental variables was developed. Results The best forecasting model (R2adj = 82%, p < 0.0001 and 93% forecasting accuracy in the range ± 4 cases per 100 inhabitants) included the NDVI, mean maximum temperature, rainfall and number of malaria cases in the preceding month. Conclusion This model is a simple and useful tool for producing reasonably reliable forecasts of the malaria incidence rate in the study area. PMID:17892540

Mistakes Made by Freshman Students of Science Teaching and Their Reasons during the Proving Process

ERIC Educational Resources Information Center

Gökkurt, Burçin; Erdem, Emrullah; Basibüyük, Kani; Sahin, Ömer; Soylu, Yasin

2017-01-01

The aim of this study was to examine the mistakes made by freshman students of science teaching during the process of proving and the reasons for these mistakes. To this aim, the study, which was conducted via the case study method, was performed with 52 freshman students who were studying at the department of science teaching in a state…

[Reasons for consulting related to skin-bleaching products used by 104 women in Brazzaville].

PubMed

Gathse, A; Obengui; Ibara, J R

2005-12-01

A prospective survey has been carried out in the Brazzaville (Congo) dermatology service in order to specify dermatosis linked to the use of bleaching agents in 104 Congolese women consulting for this problem. The used bleaching agents were topical corticoids based products for 40 cases, hydroquinone for 32 cases, and hydroquinone associated with topical dermocorticoids for 32 cases. Acne was the most frequent motive for consulting (24%), followed by the paradoxical peri-orbital hyperpigmentation (21.1%), profuse mycosis (16.3%) and vibices(8.6%). The results of this survey were not superimposable to those of Dakar where infectious dermatosis were the first reason for consulting.

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

PubMed Central

Tsatsoulis, C; Amthauer, H

2003-01-01

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

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

PubMed Central

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

2016-01-01

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

Expert nurses' clinical reasoning under uncertainty: representation, structure, and process.

PubMed Central

Fonteyn, M. E.; Grobe, S. J.

1992-01-01

How do expert nurses reason when planning care and making clinical decisions for a patient who is at risk, and whose outcome is uncertain? In this study, a case study involving a critically ill elderly woman whose condition deteriorated over time, was presented in segments to ten expert critical care nurses. Think aloud method was used to elicit knowledge from these experts to provide conceptual information about their knowledge and to reveal their reasoning processes and problem-solving strategies. The verbatim transcripts were then analyzed using a systematic three-step method that makes analysis easier and adds creditability to study findings by providing a means of retracing and explaining analysis results. Findings revealed information about how patient problems were represented during reasoning, the manner in which experts subjects structured their plan of care, and the reasoning processes and heuristics they used to formulate solutions for resolving the patient's problems and preventing deterioration in the patient's condition. PMID:1482907

A Video-Based Measure of Preservice Teachers' Abilities to Predict Elementary Students' Scientific Reasoning

ERIC Educational Resources Information Center

Akerson, Valarie L.; Carter, Ingrid S.; Park Rogers, Meredith A.; Pongsanon, Khemmawadee

2018-01-01

In this mixed methods study, the researchers developed a video-based measure called a "Prediction Assessment" to determine preservice elementary teachers' abilities to predict students' scientific reasoning. The instrument is based on teachers' need to develop pedagogical content knowledge for teaching science. Developing a knowledge…

Advantages of video trigger in problem-based learning.

PubMed

Chan, Lap Ki; Patil, Nivritti G; Chen, Julie Y; Lam, Jamie C M; Lau, Chak S; Ip, Mary S M

2010-01-01

Traditionally, paper cases are used as 'triggers' to stimulate learning in problem-based learning (PBL). However, video may be a better medium because it preserves the original language, encourages the active extraction of information, avoids depersonalization of patients and allows direct observation of clinical consultations. In short, it exposes the students to the complexity of actual clinical problems. The study aims to find out whether students and facilitators who are accustomed to paper cases would prefer video triggers or paper cases and the reasons for their preference. After students and facilitators had completed a video PBL tutorial, their responses were measured by a structured questionnaire using a modified Likert scale. A total of 257 students (92%) and 26 facilitators (100%) responded. The majority of students and facilitators considered that using video triggers could enhance the students' observational powers and clinical reasoning, help them to integrate different information and better understand the cases and motivate them to learn. They found PBL using video triggers more interesting and preferred it to PBL using paper cases. Video triggers are preferred by both students and facilitators over paper cases in PBL.

The cost of cancer registry operations: Impact of volume on cost per case for core and enhanced registry activities

PubMed Central

Subramanian, Sujha; Tangka, Florence K.L.; Beebe, Maggie Cole; Trebino, Diana; Weir, Hannah K.; Babcock, Frances

2016-01-01

Background Cancer registration data is vital for creating evidence-based policies and interventions. Quantifying the resources needed for cancer registration activities and identifying potential efficiencies are critically important to ensure sustainability of cancer registry operations. Methods Using a previously validated web-based cost assessment tool, we collected activity-based cost data and report findings using 3 years of data from 40 National Program of Cancer Registry grantees. We stratified registries by volume: low-volume included fewer than 10,000 cases, medium-volume included 10,000–50,000 cases, and high-volume included >50,000 cases. Results Low-volume cancer registries incurred an average of $93.11 to report a case (without in-kind contributions) compared with $27.70 incurred by high-volume registries. Across all registries, the highest cost per case was incurred for data collection and abstraction ($8.33), management ($6.86), and administration ($4.99). Low- and medium-volume registries have higher costs than high-volume registries for all key activities. Conclusions Some cost differences by volume can be explained by the large fixed costs required for administering and performing registration activities, but other reasons may include the quality of the data initially submitted to the registries from reporting sources such as hospitals and pathology laboratories. Automation or efficiency improvements in data collection can potentially reduce overall costs. PMID:26702880

A Biomechanical Model for Lung Fibrosis in Proton Beam Therapy

NASA Astrophysics Data System (ADS)

King, David J. S.

The physics of protons makes them well-suited to conformal radiotherapy due to the well-known Bragg peak effect. From a proton's inherent stopping power, uncertainty effects can cause a small amount of dose to overflow to an organ at risk (OAR). Previous models for calculating normal tissue complication probabilities (NTCPs) relied on the equivalent uniform dose model (EUD), in which the organ was split into 1/3, 2/3 or whole organ irradiation. However, the problem of dealing with volumes <1/3 of the total volume renders this EUD based approach no longer applicable. In this work the case for an experimental data-based replacement at low volumes is investigated. Lung fibrosis is investigated as an NTCP effect typically arising from dose overflow from tumour irradiation at the spinal base. Considering a 3D geometrical model of the lungs, irradiations are modelled with variable parameters of dose overflow. To calculate NTCPs without the EUD model, experimental data is used from the quantitative analysis of normal tissue effects in the clinic (QUANTEC) data. Additional side projects are also investigated, introduced and explained at various points. A typical radiotherapy course for the patient of 30x2Gy per fraction is simulated. A range of geometry of the target volume and irradiation types is investigated. Investigations with X-rays found the majority of the data point ratios (ratio of EUD values found from calculation based and data based methods) at 20% within unity showing a relatively close agreement. The ratios have not systematically preferred one particular type of predictive method. No Vx metric was found to consistently outperform another. In certain cases there is a good agreement and not in other cases which can be found predicted in the literature. The overall results leads to conclusion that there is no reason to discount the use of the data based predictive method particularly, as a low volume replacement predictive method.

"Things I did not know": Retrospectives on a Canadian rural male youth suicide using an instrumental photovoice case study.

PubMed

Creighton, Genevieve M; Oliffe, John L; Lohan, Maria; Ogrodniczuk, John S; Palm, Emma

2017-11-01

In Canada, it is young, rural-based men who are at the greatest risk of suicide. While there is no consensus on the reasons for this, evidence points to contextual social factors including isolation, lack of confidential services, and pressure to uphold restrictive norms of rural masculinity. In this article, we share findings drawn from an instrumental photovoice case study to distil factors contributing to the suicide of a young, Canadian, rural-based man. Integrating photovoice methods and in-depth qualitative, we conducted interviews with seven family members and close friends of the deceased. The interviews and image data were analyzed using constant comparative methods to discern themes related to participants' reflections on and perceptions about rural male suicide. Three inductively derived themes, "Missing the signs," "Living up to his public image," and "Down in Rural Canada," reflect the challenges that survivors and young rural men can experience in attempting to be comply with restrictive dominant ideals of masculinity. We conclude that community-based suicide prevention efforts would benefit from gender-sensitive and place-specific approaches to advancing men's mental health by making tangibly available and affirming an array of masculinities to foster the well-being of young, rural-based men.

“Things I did not know”: Retrospectives on a Canadian rural male youth suicide using an instrumental photovoice case study

PubMed Central

Creighton, Genevieve M; Oliffe, John L; Lohan, Maria; Ogrodniczuk, John S; Palm, Emma

2016-01-01

In Canada, it is young, rural-based men who are at the greatest risk of suicide. While there is no consensus on the reasons for this, evidence points to contextual social factors including isolation, lack of confidential services, and pressure to uphold restrictive norms of rural masculinity. In this article, we share findings drawn from an instrumental photovoice case study to distil factors contributing to the suicide of a young, Canadian, rural-based man. Integrating photovoice methods and in-depth qualitative, we conducted interviews with seven family members and close friends of the deceased. The interviews and image data were analyzed using constant comparative methods to discern themes related to participants’ reflections on and perceptions about rural male suicide. Three inductively derived themes, “Missing the signs,” “Living up to his public image,” and “Down in Rural Canada,” reflect the challenges that survivors and young rural men can experience in attempting to be comply with restrictive dominant ideals of masculinity. We conclude that community-based suicide prevention efforts would benefit from gender-sensitive and place-specific approaches to advancing men’s mental health by making tangibly available and affirming an array of masculinities to foster the well-being of young, rural-based men. PMID:26979983

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.

Interpretive analysis of 85 systematic reviews suggests that narrative syntheses and meta-analyses are incommensurate in argumentation.

PubMed

Melendez-Torres, G J; O'Mara-Eves, A; Thomas, J; Brunton, G; Caird, J; Petticrew, M

2017-03-01

Using Toulmin's argumentation theory, we analysed the texts of systematic reviews in the area of workplace health promotion to explore differences in the modes of reasoning embedded in reports of narrative synthesis as compared with reports of meta-analysis. We used framework synthesis, grounded theory and cross-case analysis methods to analyse 85 systematic reviews addressing intervention effectiveness in workplace health promotion. Two core categories, or 'modes of reasoning', emerged to frame the contrast between narrative synthesis and meta-analysis: practical-configurational reasoning in narrative synthesis ('what is going on here? What picture emerges?') and inferential-predictive reasoning in meta-analysis ('does it work, and how well? Will it work again?'). Modes of reasoning examined quality and consistency of the included evidence differently. Meta-analyses clearly distinguished between warrant and claim, whereas narrative syntheses often presented joint warrant-claims. Narrative syntheses and meta-analyses represent different modes of reasoning. Systematic reviewers are likely to be addressing research questions in different ways with each method. It is important to consider narrative synthesis in its own right as a method and to develop specific quality criteria and understandings of how it is carried out, not merely as a complement to, or second-best option for, meta-analysis. © 2016 The Authors. Research Synthesis Methods published by John Wiley & Sons Ltd. © 2016 The Authors. Research Synthesis Methods published by John Wiley & Sons Ltd.

University Teachers' Job Dissatisfaction: Application of Two-Factor Theory--A Case of Pakistani Education System

ERIC Educational Resources Information Center

Mir, Imran Anwar

2012-01-01

This qualitative case study presents the reasons of teachers' job dissatisfaction in the government educational institutes in Pakistan. This case study is based on the two factor theory of Herzberg. The results of this case study reveal four core factors that cause job dissatisfaction among teachers in the public sector universities in developing…

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

PubMed

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

2018-01-01

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

Using diagnostic experiences in experience-based innovative design

NASA Astrophysics Data System (ADS)

Prabhakar, Sattiraju; Goel, Ashok K.

1992-03-01

Designing a novel class of devices requires innovation. Often, the design knowledge of these devices does not identify and address the constraints that are required for their performance in the real world operating environment. So any new design adapted from these devices tend to be similarly sketchy. In order to address this problem, we propose a case-based reasoning method called performance driven innovation (PDI). We model the design as a dynamic process, arrive at a design by adaptation from the known designs, generate failures for this design for some new constraints, and then use this failure knowledge to generate the required design knowledge for the new constraints. In this paper, we discuss two aspects of PDI: the representation of PDI cases and the translation of the failure knowledge into design knowledge for a constraint. Each case in PDI has two components: design and failure knowledge. Both of them are represented using a substance-behavior-function model. Failure knowledge has internal device failure behaviors and external environmental behaviors. The environmental behavior, for a constraint, interacting with the design behaviors, results in the failure internal behavior. The failure adaptation strategy generates functions, from the failure knowledge, which can be addressed using the routine design methods. These ideas are illustrated using a coffee-maker example.

Estimating Model Probabilities using Thermodynamic Markov Chain Monte Carlo Methods

NASA Astrophysics Data System (ADS)

Ye, M.; Liu, P.; Beerli, P.; Lu, D.; Hill, M. C.

2014-12-01

Markov chain Monte Carlo (MCMC) methods are widely used to evaluate model probability for quantifying model uncertainty. In a general procedure, MCMC simulations are first conducted for each individual model, and MCMC parameter samples are then used to approximate marginal likelihood of the model by calculating the geometric mean of the joint likelihood of the model and its parameters. It has been found the method of evaluating geometric mean suffers from the numerical problem of low convergence rate. A simple test case shows that even millions of MCMC samples are insufficient to yield accurate estimation of the marginal likelihood. To resolve this problem, a thermodynamic method is used to have multiple MCMC runs with different values of a heating coefficient between zero and one. When the heating coefficient is zero, the MCMC run is equivalent to a random walk MC in the prior parameter space; when the heating coefficient is one, the MCMC run is the conventional one. For a simple case with analytical form of the marginal likelihood, the thermodynamic method yields more accurate estimate than the method of using geometric mean. This is also demonstrated for a case of groundwater modeling with consideration of four alternative models postulated based on different conceptualization of a confining layer. This groundwater example shows that model probabilities estimated using the thermodynamic method are more reasonable than those obtained using the geometric method. The thermodynamic method is general, and can be used for a wide range of environmental problem for model uncertainty quantification.

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

PubMed

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

2016-04-01

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

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

PubMed

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

2018-04-01

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

Illness script development in pre-clinical education through case-based clinical reasoning training.

PubMed

Keemink, Yvette; Custers, Eugene J F M; van Dijk, Savannah; Ten Cate, Olle

2018-02-09

To assess illness script richness and maturity in preclinical students after they attended a specifically structured instructional format, i.e., a case based clinical reasoning (CBCR) course. In a within-subject experimental design, medical students who had finished the CBCR course participated in an illness script experiment. In the first session, richness and maturity of students' illness scripts for diseases discussed during the CBCR course were compared to illness script richness and maturity for similar diseases not included in the course. In the second session, diagnostic performance was tested, to test for differences between CBCR cases and non-CBCR cases. Scores on the CBCR course exam were related to both experimental outcomes. Thirty-two medical students participated. Illness script richness for CBCR diseases was almost 20% higher than for non-CBCR diseases, on average 14.47 (SD=3.25) versus 12.14 (SD=2.80), respectively (p<0.001). In addition, students provided more information on Enabling Conditions and less on Fault-related aspects of the disease. Diagnostic performance was better for the diseases discussed in the CBCR course, mean score 1.63 (SD=0.32) versus 1.15 (SD=0.29) for non-CBCR diseases (p<0.001). A significant correlation of exam results with recognition of CBCR cases was found (r=0.571, p<0.001), but not with illness script richness (r=-0.006, p=NS). The CBCR-course fosters early development of clinical reasoning skills by increasing the illness script richness and diagnostic performance of pre-clinical students. However, these results are disease-specific and therefore we cannot conclude that students develop a more general clinical reasoning ability.

Why does Japan use the probability method to set design flood?

NASA Astrophysics Data System (ADS)

Nakamura, S.; Oki, T.

2015-12-01

Design flood is hypothetical flood to make flood prevention plan. In Japan, a probability method based on precipitation data is used to define the scale of design flood: Tone River, the biggest river in Japan, is 1 in 200 years, Shinano River is 1 in 150 years, and so on. It is one of important socio-hydrological issue how to set reasonable and acceptable design flood in a changing world. The method to set design flood vary among countries. Although the probability method is also used in Netherland, but the base data is water level or discharge data and the probability is 1 in 1250 years (in fresh water section). On the other side, USA and China apply the maximum flood method which set the design flood based on the historical or probable maximum flood. This cases can leads a question: "what is the reason why the method vary among countries?" or "why does Japan use the probability method?" The purpose of this study is to clarify the historical process which the probability method was developed in Japan based on the literature. In the late 19the century, the concept of "discharge" and modern river engineering were imported by Dutch engineers, and modern flood prevention plans were developed in Japan. In these plans, the design floods were set based on the historical maximum method. Although the historical maximum method had been used until World War 2, however, the method was changed to the probability method after the war because of limitations of historical maximum method under the specific socio-economic situations: (1) the budget limitation due to the war and the GHQ occupation, (2) the historical floods: Makurazaki typhoon in 1945, Kathleen typhoon in 1947, Ione typhoon in 1948, and so on, attacked Japan and broke the record of historical maximum discharge in main rivers and the flood disasters made the flood prevention projects difficult to complete. Then, Japanese hydrologists imported the hydrological probability statistics from the West to take account of socio-economic situation in design flood, and they applied to Japanese rivers in 1958. The probability method was applied Japan to adapt the specific socio-economic and natural situation during the confusion after the war.

Grappling with the Future Use of Big Data for Translational Medicine and Clinical Care.

PubMed

Murphy, S; Castro, V; Mandl, K

2017-08-01

Objectives: Although patients may have a wealth of imaging, genomic, monitoring, and personal device data, it has yet to be fully integrated into clinical care. Methods: We identify three reasons for the lack of integration. The first is that "Big Data" is poorly managed by most Electronic Medical Record Systems (EMRS). The data is mostly available on "cloud-native" platforms that are outside the scope of most EMRs, and even checking if such data is available on a patient often must be done outside the EMRS. The second reason is that extracting features from the Big Data that are relevant to healthcare often requires complex machine learning algorithms, such as determining if a genomic variant is protein-altering. The third reason is that applications that present Big Data need to be modified constantly to reflect the current state of knowledge, such as instructing when to order a new set of genomic tests. In some cases, applications need to be updated nightly. Results: A new architecture for EMRS is evolving which could unite Big Data, machine learning, and clinical care through a microservice-based architecture which can host applications focused on quite specific aspects of clinical care, such as managing cancer immunotherapy. Conclusion: Informatics innovation, medical research, and clinical care go hand in hand as we look to infuse science-based practice into healthcare. Innovative methods will lead to a new ecosystem of applications (Apps) interacting with healthcare providers to fulfill a promise that is still to be determined. Georg Thieme Verlag KG Stuttgart.

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

ERIC Educational Resources Information Center

Sinutko, Jaime M.

2014-01-01

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

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.

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

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

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

PubMed

Petrovic, Sanja; Khussainova, Gulmira; Jagannathan, Rupa

2016-03-01

Radiotherapy treatment planning aims at delivering a sufficient radiation dose to cancerous tumour cells while sparing healthy organs in the tumour-surrounding area. It is a time-consuming trial-and-error process that requires the expertise of a group of medical experts including oncologists and medical physicists and can take from 2 to 3h to a few days. Our objective is to improve the performance of our previously built case-based reasoning (CBR) system for brain tumour radiotherapy treatment planning. In this system, a treatment plan for a new patient is retrieved from a case base containing patient cases treated in the past and their treatment plans. However, this system does not perform any adaptation, which is needed to account for any difference between the new and retrieved cases. Generally, the adaptation phase is considered to be intrinsically knowledge-intensive and domain-dependent. Therefore, an adaptation often requires a large amount of domain-specific knowledge, which can be difficult to acquire and often is not readily available. In this study, we investigate approaches to adaptation that do not require much domain knowledge, referred to as knowledge-light adaptation. We developed two adaptation approaches: adaptation based on machine-learning tools and adaptation-guided retrieval. They were used to adapt the beam number and beam angles suggested in the retrieved case. Two machine-learning tools, neural networks and naive Bayes classifier, were used in the adaptation to learn how the difference in attribute values between the retrieved and new cases affects the output of these two cases. The adaptation-guided retrieval takes into consideration not only the similarity between the new and retrieved cases, but also how to adapt the retrieved case. The research was carried out in collaboration with medical physicists at the Nottingham University Hospitals NHS Trust, City Hospital Campus, UK. All experiments were performed using real-world brain cancer patient cases treated with three-dimensional (3D)-conformal radiotherapy. Neural networks-based adaptation improved the success rate of the CBR system with no adaptation by 12%. However, naive Bayes classifier did not improve the current retrieval results as it did not consider the interplay among attributes. The adaptation-guided retrieval of the case for beam number improved the success rate of the CBR system by 29%. However, it did not demonstrate good performance for the beam angle adaptation. Its success rate was 29% versus 39% when no adaptation was performed. The obtained empirical results demonstrate that the proposed adaptation methods improve the performance of the existing CBR system in recommending the number of beams to use. However, we also conclude that to be effective, the proposed adaptation of beam angles requires a large number of relevant cases in the case base. Copyright © 2016 Elsevier B.V. All rights reserved.

Antipsychotic drug poisoning monitoring of clozapine in urine by using coffee ring effect based surface-enhanced Raman spectroscopy.

PubMed

Zhu, Qingxia; Yu, Xiaoyan; Wu, Zebing; Lu, Feng; Yuan, Yongfang

2018-07-19

Antipsychotics are the drugs most often involved in drug poisoning cases, and therefore, therapeutic drug monitoring (TDM) is necessary for safe and effective medication administration of these drugs. In this study, a coffee ring effect-based surface-enhanced Raman spectroscopy (CRE-SERS) method was developed and successfully used to monitor antipsychotic poisoning by using urine samples for the first time. The established method exhibited excellent SERS performance since more hot spots were obtained in the "coffee ring". Using the optimized CRE-SERS method, the sensitivity was improved one order more than that of the conventional method with reasonable reproducibility. The antipsychotic drug clozapine (CLO) spiked into urine samples at 0.5-50 μg mL -1 was quantitatively detected, at concentrations above the thresholds for toxicity. The CRE-SERS method allowed CLO and its metabolites to be ultimately distinguished from real poisoning urine samples. The coffee-ring effect would provide more opportunities for practical applications of the SERS-based method. The frequent occurrence of drug poisoning may have created a new area for the application of the CRE-SERS method. It is anticipated that the developed method will also have great potential for other drug poisoning monitoring. Copyright © 2018 Elsevier B.V. All rights reserved.

Faith and reason and physician-assisted suicide.

PubMed

Kaczor, Christopher

1998-08-01

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

Case-Based Capture and Reuse of Aerospace Design Rationale

NASA Technical Reports Server (NTRS)

Leake, David B.

1998-01-01

The goal of this project is to apply artificial intelligence techniques to facilitate capture and reuse of aerospace design rationale. The project applies case-based reasoning (CBR) and concept mapping (CMAP) tools to the task of capturing, organizing, and interactively accessing experiences or "cases" encapsulating the methods and rationale underlying expert aerospace design. As stipulated in the award, Indiana University and Ames personnel are collaborating on performance of research and determining the direction of research, to assure that the project focuses on high-value tasks. In the first five months of the project, we have made two visits to Ames Research Center to consult with our NASA collaborators, to learn about the advanced aerospace design tools being developed there, and to identify specific needs for intelligent design support. These meetings identified a number of task areas for applying CBR and concept mapping technology. We jointly selected a first task area to focus on: Acquiring the convergence criteria that experts use to guide the selection of useful data from a set of numerical simulations of high-lift systems. During the first funding period, we developed two software systems. First, we have adapted a CBR system developed at Indiana University into a prototype case-based reasoning shell to capture and retrieve information about design experiences, with the sample task of capturing and reusing experts' intuitive criteria for determining convergence (work conducted at Indiana University). Second, we have also adapted and refined existing concept mapping tools that will be used to clarify and capture the rationale underlying those experiences, to facilitate understanding of the expert's reasoning and guide future reuse of captured information (work conducted at the University of West Florida). The tools we have developed are designed to be the basis for a general framework for facilitating tasks within systems developed by the Advanced Design Technologies Testbed (ADTT) project at ARC. The tenets of our framework are (1) that the systems developed should leverage a designer's knowledge, rather than attempting to replace it; (2) that learning and user feedback must play a central role, so that the system can adapt to how it is used, and (3) that the learning and feedback processes must be as natural and as unobtrusive as possible. In the second funding period we will extend our current work, applying the tools to capturing higher-level design rationale.

The GIS map coloring support decision-making system based on case-based reasoning and simulated annealing algorithm

NASA Astrophysics Data System (ADS)

Deng, Shuang; Xiang, Wenting; Tian, Yangge

2009-10-01

Map coloring is a hard task even to the experienced map experts. In the GIS project, usually need to color map according to the customer, which make the work more complex. With the development of GIS, more and more programmers join the project team, which lack the training of cartology, their coloring map are harder to meet the requirements of customer. From the experience, customers with similar background usually have similar tastes for coloring map. So, we developed a GIS color scheme decision-making system which can select color schemes of similar customers from case base for customers to select and adjust. The system is a BS/CS mixed system, the client side use JSP and make it possible for the system developers to go on remote calling of the colors scheme cases in the database server and communicate with customers. Different with general case-based reasoning, even the customers are very similar, their selection may have difference, it is hard to provide a "best" option. So, we select the Simulated Annealing Algorithm (SAA) to arrange the emergence order of different color schemes. Customers can also dynamically adjust certain features colors based on existing case. The result shows that the system can facilitate the communication between the designers and the customers and improve the quality and efficiency of coloring map.

The development of scientific reasoning in medical education: a psychological perspective.

PubMed

Barz, Daniela Luminita; Achimaş-Cadariu, Andrei

2016-01-01

Scientific reasoning has been studied from a variety of theoretical perspectives, which have tried to identify the underlying mechanisms responsible for the development of this particular cognitive process. Scientific reasoning has been defined as a problem-solving process that involves critical thinking in relation to content, procedural, and epistemic knowledge. The development of scientific reasoning in medical education was influenced by current paradigmatic trends, it could be traced along educational curriculum and followed cognitive processes. The purpose of the present review is to discuss the role of scientific reasoning in medical education and outline educational methods for its development. Current evidence suggests that medical education should foster a new ways of development of scientific reasoning, which include exploration of the complexity of scientific inquiry, and also take into consideration the heterogeneity of clinical cases found in practice.

Defaults, context, and knowledge: alternatives for OWL-indexed knowledge bases.

PubMed

Rector, A

2004-01-01

The new Web Ontology Language (OWL) and its Description Logic compatible sublanguage (OWL-DL) explicitly exclude defaults and exceptions, as do all logic based formalisms for ontologies. However, many biomedical applications appear to require default reasoning, at least if they are to be engineered in a maintainable way. Default reasoning has always been one of the great strengths of Frame systems such as Protégé. Resolving this conflict requires analysis of the different uses for defaults and exceptions. In some cases, alternatives can be provided within the OWL framework; in others, it appears that hybrid reasoning about a knowledge base of contingent facts built around the core ontology is necessary. Trade-offs include both human factors and the scaling of computational performance. The analysis presented here is based on the OpenGALEN experience with large scale ontologies using a formalism, GRAIL, which explicitly incorporates constructs for hybrid reasoning, numerous experiments with OWL, and initial work on combining OWL and Protégé.

The synergistic use of computation, chemistry and biology to discover novel peptide-based drugs: the time is right.

PubMed

Audie, J; Boyd, C

2010-01-01

The case for peptide-based drugs is compelling. Due to their chemical, physical and conformational diversity, and relatively unproblematic toxicity and immunogenicity, peptides represent excellent starting material for drug discovery. Nature has solved many physiological and pharmacological problems through the use of peptides, polypeptides and proteins. If nature could solve such a diversity of challenging biological problems through the use of peptides, it seems reasonable to infer that human ingenuity will prove even more successful. And this, indeed, appears to be the case, as a number of scientific and methodological advances are making peptides and peptide-based compounds ever more promising pharmacological agents. Chief among these advances are powerful chemical and biological screening technologies for lead identification and optimization, methods for enhancing peptide in vivo stability, bioavailability and cell-permeability, and new delivery technologies. Other advances include the development and experimental validation of robust computational methods for peptide lead identification and optimization. Finally, scientific analysis, biology and chemistry indicate the prospect of designing relatively small peptides to therapeutically modulate so-called 'undruggable' protein-protein interactions. Taken together a clear picture is emerging: through the synergistic use of the scientific imagination and the computational, chemical and biological methods that are currently available, effective peptide therapeutics for novel targets can be designed that surpass even the proven peptidic designs of nature.

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

NASA Astrophysics Data System (ADS)

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

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

An analysis of whether a working-age ward-based liaison psychiatry service requires the input of a liaison psychiatrist.

PubMed

Guthrie, Elspeth A; McMeekin, Aaron T; Khan, Sylvia; Makin, Sally; Shaw, Ben; Longson, Damien

2017-06-01

Aims and method This article presents a 12-month case series to determine the fraction of ward referrals of adults of working age who needed a liaison psychiatrist in a busy tertiary referral teaching hospital. Results The service received 344 referrals resulting in 1259 face-to-face contacts. Depression accounted for the most face-to-face contacts. We deemed the involvement of a liaison psychiatrist necessary in 241 (70.1%) referrals, with medication management as the most common reason. Clinical implications A substantial amount of liaison ward work involves the treatment and management of severe and complex mental health problems. Our analysis suggests that in the majority of cases the input of a liaison psychiatrist is required.

Clinical reasoning and its application to nursing: concepts and research studies.

PubMed

Banning, Maggi

2008-05-01

Clinical reasoning may be defined as "the process of applying knowledge and expertise to a clinical situation to develop a solution" [Carr, S., 2004. A framework for understanding clinical reasoning in community nursing. J. Clin. Nursing 13 (7), 850-857]. Several forms of reasoning exist each has its own merits and uses. Reasoning involves the processes of cognition or thinking and metacognition. In nursing, clinical reasoning skills are an expected component of expert and competent practise. Nurse research studies have identified concepts, processes and thinking strategies that might underpin the clinical reasoning used by pre-registration nurses and experienced nurses. Much of the available research on reasoning is based on the use of the think aloud approach. Although this is a useful method, it is dependent on ability to describe and verbalise the reasoning process. More nursing research is needed to explore the clinical reasoning process. Investment in teaching and learning methods is needed to enhance clinical reasoning skills in nurses.

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

NASA Technical Reports Server (NTRS)

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

1988-01-01

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

A decision method based on uncertainty reasoning of linguistic truth-valued concept lattice

NASA Astrophysics Data System (ADS)

Yang, Li; Xu, Yang

2010-04-01

Decision making with linguistic information is a research hotspot now. This paper begins by establishing the theory basis for linguistic information processing and constructs the linguistic truth-valued concept lattice for a decision information system, and further utilises uncertainty reasoning to make the decision. That is, we first utilise the linguistic truth-valued lattice implication algebra to unify the different kinds of linguistic expressions; second, we construct the linguistic truth-valued concept lattice and decision concept lattice according to the concrete decision information system and third, we establish the internal and external uncertainty reasoning methods and talk about the rationality of them. We apply these uncertainty reasoning methods into decision making and present some generation methods of decision rules. In the end, we give an application of this decision method by an example.

Clinical physiology grand rounds.

PubMed

Richards, Jeremy; Schwartzstein, Richard; Irish, Julie; Almeida, Jacqueline; Roberts, David

2013-04-01

Clinical Physiology Grand Rounds (CPGR) is an interactive, case-based conference for medical students designed to: (1) integrate preclinical and clinical learning; (2) promote inductive clinical reasoning; and (3) emphasise students as peer teachers. CPGR specifically encourages mixed learning level student interactions and emphasises the use of concept mapping. We describe the theoretical basis and logistical considerations for an interactive, integrative, mixed-learner environment such as CPGR. In addition, we report qualitative data regarding students' attitudes towards and perceptions of CPGR. Medical students from first to fourth year participate in a monthly, interactive conference. The CPGR was designed to bridge gaps and reinforce linkages between basic science and clinical concepts, and to incorporate interactive vertical integration between preclinical and clinical students. Medical education and content experts use Socratic, interactive teaching methods to develop real-time concept maps to emphasise the presence and importance of linkages across curricula. Student focus groups were held to assess attitudes towards and perceptions of the mixed-learner environment and concept maps in CPGR. Qualitative analyses of focus group transcripts were performed to develop themes and codes describing the students' impressions of CPGR. CPGR is a case-based, interactive conference designed to help students gain an increased appreciation of linkages between basic science and clinical medicine concepts, and an increased awareness of clinical reasoning thought processes. Success is dependent upon explicit attention being given to goals for students' integrated learning. © Blackwell Publishing Ltd 2013.

Rocket Based Combined Cycle Exchange Inlet Performance Estimation at Supersonic Speeds

NASA Astrophysics Data System (ADS)

Murzionak, Aliaksandr

A method to estimate the performance of an exchange inlet for a Rocket Based Combined Cycle engine is developed. This method is to be used for exchange inlet geometry optimization and as such should be able to predict properties that can be used in the design process within a reasonable amount of time to allow multiple configurations to be evaluated. The method is based on a curve fit of the shocks developed around the major components of the inlet using solutions for shocks around sharp cones and 2D estimations of the shocks around wedges with blunt leading edges. The total pressure drop across the estimated shocks as well as the mass flow rate through the exchange inlet are calculated. The estimations for a selected range of free-stream Mach numbers between 1.1 and 7 are compared against numerical finite volume method simulations which were performed using available commercial software (Ansys-CFX). The total pressure difference between the two methods is within 10% for the tested Mach numbers of 5 and below, while for the Mach 7 test case the difference is 30%. The mass flow rate on average differs by less than 5% for all tested cases with the maximum difference not exceeding 10%. The estimation method takes less than 3 seconds on 3.0 GHz single core processor to complete the calculations for a single flight condition as oppose to over 5 days on 8 cores at 2.4 GHz system while using 3D finite volume method simulation with 1.5 million elements mesh. This makes the estimation method suitable for the use with exchange inlet geometry optimization algorithm.

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

PubMed

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

2016-02-01

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

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

PubMed

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

2015-11-01

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

Application of plausible reasoning to AI-based control systems

NASA Technical Reports Server (NTRS)

Berenji, Hamid; Lum, Henry, Jr.

1987-01-01

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

Research of Uncertainty Reasoning in Pineapple Disease Identification System

NASA Astrophysics Data System (ADS)

Liu, Liqun; Fan, Haifeng

In order to deal with the uncertainty of evidences mostly existing in pineapple disease identification system, a reasoning model based on evidence credibility factor was established. The uncertainty reasoning method is discussed,including: uncertain representation of knowledge, uncertain representation of rules, uncertain representation of multi-evidences and update of reasoning rules. The reasoning can fully reflect the uncertainty in disease identification and reduce the influence of subjective factors on the accuracy of the system.

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

NASA Astrophysics Data System (ADS)

Gallup, G. A.; Gerratt, J.

1985-09-01

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

A review of the handling of missing longitudinal outcome data in clinical trials

PubMed Central

2014-01-01

The aim of this review was to establish the frequency with which trials take into account missingness, and to discover what methods trialists use for adjustment in randomised controlled trials with longitudinal measurements. Failing to address the problems that can arise from missing outcome data can result in misleading conclusions. Missing data should be addressed as a means of a sensitivity analysis of the complete case analysis results. One hundred publications of randomised controlled trials with longitudinal measurements were selected randomly from trial publications from the years 2005 to 2012. Information was extracted from these trials, including whether reasons for dropout were reported, what methods were used for handing the missing data, whether there was any explanation of the methods for missing data handling, and whether a statistician was involved in the analysis. The main focus of the review was on missing data post dropout rather than missing interim data. Of all the papers in the study, 9 (9%) had no missing data. More than half of the papers included in the study failed to make any attempt to explain the reasons for their choice of missing data handling method. Of the papers with clear missing data handling methods, 44 papers (50%) used adequate methods of missing data handling, whereas 30 (34%) of the papers used missing data methods which may not have been appropriate. In the remaining 17 papers (19%), it was difficult to assess the validity of the methods used. An imputation method was used in 18 papers (20%). Multiple imputation methods were introduced in 1987 and are an efficient way of accounting for missing data in general, and yet only 4 papers used these methods. Out of the 18 papers which used imputation, only 7 displayed the results as a sensitivity analysis of the complete case analysis results. 61% of the papers that used an imputation explained the reasons for their chosen method. Just under a third of the papers made no reference to reasons for missing outcome data. There was little consistency in reporting of missing data within longitudinal trials. PMID:24947664

Using Interactive Data Visualizations for Exploratory Analysis in Undergraduate Genomics Coursework: Field Study Findings and Guidelines

NASA Astrophysics Data System (ADS)

Mirel, Barbara; Kumar, Anuj; Nong, Paige; Su, Gang; Meng, Fan

2016-02-01

Life scientists increasingly use visual analytics to explore large data sets and generate hypotheses. Undergraduate biology majors should be learning these same methods. Yet visual analytics is one of the most underdeveloped areas of undergraduate biology education. This study sought to determine the feasibility of undergraduate biology majors conducting exploratory analysis using the same interactive data visualizations as practicing scientists. We examined 22 upper level undergraduates in a genomics course as they engaged in a case-based inquiry with an interactive heat map. We qualitatively and quantitatively analyzed students' visual analytic behaviors, reasoning and outcomes to identify student performance patterns, commonly shared efficiencies and task completion. We analyzed students' successes and difficulties in applying knowledge and skills relevant to the visual analytics case and related gaps in knowledge and skill to associated tool designs. Findings show that undergraduate engagement in visual analytics is feasible and could be further strengthened through tool usability improvements. We identify these improvements. We speculate, as well, on instructional considerations that our findings suggested may also enhance visual analytics in case-based modules.

Using Interactive Data Visualizations for Exploratory Analysis in Undergraduate Genomics Coursework: Field Study Findings and Guidelines

PubMed Central

Kumar, Anuj; Nong, Paige; Su, Gang; Meng, Fan

2016-01-01

Life scientists increasingly use visual analytics to explore large data sets and generate hypotheses. Undergraduate biology majors should be learning these same methods. Yet visual analytics is one of the most underdeveloped areas of undergraduate biology education. This study sought to determine the feasibility of undergraduate biology majors conducting exploratory analysis using the same interactive data visualizations as practicing scientists. We examined 22 upper level undergraduates in a genomics course as they engaged in a case-based inquiry with an interactive heat map. We qualitatively and quantitatively analyzed students’ visual analytic behaviors, reasoning and outcomes to identify student performance patterns, commonly shared efficiencies and task completion. We analyzed students’ successes and difficulties in applying knowledge and skills relevant to the visual analytics case and related gaps in knowledge and skill to associated tool designs. Findings show that undergraduate engagement in visual analytics is feasible and could be further strengthened through tool usability improvements. We identify these improvements. We speculate, as well, on instructional considerations that our findings suggested may also enhance visual analytics in case-based modules. PMID:26877625

[A radiological case collection with interactive character as a new element in the education of medical students].

PubMed

Heye, T; Kurz, P; Eiers, M; Kauffmann, G W; Schipp, A

2008-04-01

Evaluation of an interactive, multimedia case-based learning platform for the radiological education of medical students. An interactive electronic learning platform for the education of medical students was built in HTML format independent of the operating system in the context of the Heidelberg Curriculum Medicinale (HeiCuMed). A case collection of 30 common and authentic clinical cases is used as the central theme and clinical background. The user has to work on each case by making decisions regarding a selection of diagnostic modalities and by analyzing the chosen studies. After a reasonable selection and sequence of diagnostic radiological modalities and their interpretation, a diagnosis has to be made. An extensive collection of normal findings for any modality is available for the user as a reference in correlation with the pathology at anytime within each case. The case collection consists of 2053 files with 1109 Internet pages (HTML) and 869 image files (.jpeg) with approximately 10 000 crosslinks (links). The case collection was evaluated by a questionnaire (scale 1 - 5) at the end of the radiological student course. The development of the results of the radiological course exam was analyzed to investigate any effect on the learning performance after the case collection was introduced. 97.6 % of the course participants would use the case collection beyond the radiological student course to learn radiology in their medical studies. The handling of the case collection was rated excellent in 36.9 %, good in 54.6 %, satisfactory in 8 % and unsatisfactory in 0.4 %. 41 % felt that the case collection was overall excellent, 49.2 % good, 7.8 % satisfactory, 1.6 % unsatisfactory and 0.4 % poor. A positive trend in the development of the results in the radiological course exam with less variance after the introduction of the case collection was found but failed statistical significance. A platform-independent, interactive, multimedia learning platform with authentic clinical cases and multiple choice elements for the user is the ideal method for supporting and expanding medical education in radiology. The usefulness and the reasonable exertion of diagnostic modalities are conveyed in a practical context as teaching goals. The high acceptance among students is based on the interactivity and use of multimedia.

Using Bronfenbrenner's Ecological Theory to Understand Community Partnerships: A Historical Case Study of One Urban High School

ERIC Educational Resources Information Center

Leonard, Jack

2011-01-01

Although the value of school-community partnerships is unquestioned, the reasons for success and failure are not sufficiently understood. This mixed-methods case study examines 60 years of partnering at one urban high school, using Bronfenbrenner's ecological systems theory to better understand the effect on student development as measured by…

INCORPORATING NONCHEMICAL STRESSORS INTO CUMMULATIVE RISK ASSESSMENTS

EPA Science Inventory

The risk assessment paradigm has begun to shift from assessing single chemicals using "reasonable worst case" assumptions for individuals to considering multiple chemicals and community-based models. Inherent in community-based risk assessment is examination of all stressors a...

Evolution of Students' Reasoning Skills on a Two Year Basis in a PBL Curriculum in Medicine.

ERIC Educational Resources Information Center

Bedard, Denis; And Others

A 2-year study at the University of Sherbrooke (Quebec) investigated the changes in six medical students' clinical reasoning processes as they participated in a problem-based learning (PBL) curriculum. In each year, students performed a think-aloud protocol with two medical case problems to solve, one in cardiology and one in urology. In the…

In College and in Recovery: Reasons for Joining a Collegiate Recovery Program

ERIC Educational Resources Information Center

Laudet, Alexandre B.; Harris, Kitty; Kimball, Thomas; Winters, Ken C.; Moberg, D. Paul

2016-01-01

Objective: Collegiate Recovery Programs (CRPs), a campus-based peer support model for students recovering from substance abuse problems, grew exponentially in the past decade, yet remain unexplored. Methods: This mixed-methods study examines students' reasons for CRP enrollment to guide academic institutions and referral sources. Students (N =…

Reasoning Maps: A Generally Applicable Method for Characterizing Hypothesis-Testing Behaviour. Research Report

ERIC Educational Resources Information Center

White, Brian

2004-01-01

This paper presents a generally applicable method for characterizing subjects' hypothesis-testing behaviour based on a synthesis that extends on previous work. Beginning with a transcript of subjects' speech and videotape of their actions, a Reasoning Map is created that depicts the flow of their hypotheses, tests, predictions, results, and…

Temporal and Resource Reasoning for Planning, Scheduling and Execution in Autonomous Agents

NASA Technical Reports Server (NTRS)

Muscettola, Nicola; Hunsberger, Luke; Tsamardinos, Ioannis

2005-01-01

This viewgraph slide tutorial reviews methods for planning and scheduling events. The presentation reviews several methods and uses several examples of scheduling events for the successful and timely completion of the overall plan. Using constraint based models the presentation reviews planning with time, time representations in problem solving and resource reasoning.

A Review of Diagnostic Techniques for ISHM Applications

NASA Technical Reports Server (NTRS)

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

2005-01-01

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

Extrasystoles: side effect of kangaroo care?

PubMed

Kluthe, Christof; Wauer, Roland R; Rüdiger, Mario

2004-09-01

To present an unpublished reason for an arrhythmic electrocardiogram (ECG) recording during kangaroo care in a preterm infant. Case report. Preterm infant. A preterm infant exhibited cardiac arrhythmia on the ECG monitor during kangaroo care, leading to interruption of kangarooing. Arrhythmia disappeared after placing the baby back into the incubator. The most likely reasons for arrhythmia were excluded. However, arrhythmia reappeared upon continuation of kangaroo care. ECG monitoring revealed the reason for the monitoring error. ECG monitoring during kangaroo care should cause error because of superimposed electric activity from the parent. Oxygen saturation represents a more reliable method of monitoring during kangaroo care.

Methods and principles in biomedical ethics.

PubMed

Beauchamp, T L

2003-10-01

The four principles approach to medical ethics plus specification is used in this paper. Specification is defined as a process of reducing the indeterminateness of general norms to give them increased action guiding capacity, while retaining the moral commitments in the original norm. Since questions of method are central to the symposium, the paper begins with four observations about method in moral reasoning and case analysis. Three of the four scenarios are dealt with. It is concluded in the "standard" Jehovah's Witness case that having autonomously chosen the authority of his religious institution, a Jehovah's Witness has a reasonable basis on which to refuse a recommended blood transfusion. The author's view of the child of a Jehovah's Witness scenario is that it is morally required-not merely permitted-to overrule this parental refusal of treatment. It is argued in the selling kidneys for transplantation scenario that a fair system of regulating and monitoring would be better than the present system which the author believes to be a shameful failure.

Methods and principles in biomedical ethics

PubMed Central

Beauchamp, T

2003-01-01

The four principles approach to medical ethics plus specification is used in this paper. Specification is defined as a process of reducing the indeterminateness of general norms to give them increased action guiding capacity, while retaining the moral commitments in the original norm. Since questions of method are central to the symposium, the paper begins with four observations about method in moral reasoning and case analysis. Three of the four scenarios are dealt with. It is concluded in the "standard" Jehovah's Witness case that having autonomously chosen the authority of his religious institution, a Jehovah's Witness has a reasonable basis on which to refuse a recommended blood transfusion. The author's view of the child of a Jehovah's Witness scenario is that it is morally required—not merely permitted—to overrule this parental refusal of treatment. It is argued in the selling kidneys for transplantation scenario that a fair system of regulating and monitoring would be better than the present system which the author believes to be a shameful failure. PMID:14519835

Improvement of Automated POST Case Success Rate Using Support Vector Machines

NASA Technical Reports Server (NTRS)

Zwack, Matthew R.; Dees, Patrick D.

2017-01-01

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

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

PubMed

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

2014-12-11

Abstract Morning reports offer opportunities for intensive work-based learning. In this controlled study, we measured learning processes and outcomes with the report of paediatric emergency room patients. Twelve specialists and 12 residents were randomised into four groups and discussed the same two paediatric cases. The groups differed in their presentation modality (verbal only vs. verbal + text) and the use of buzz groups (with vs. without). The verbal interactions were analysed for clinical reasoning processes. Perceptions of learning and judgment of learning were reported in a questionnaire. Diagnostic accuracy was assessed by a 20-item multiple-choice test. Combined bimodal presentation and buzz groups increased the odds ratio of clinical reasoning to occur in the discussion of cases by a factor of 1.90 (p = 0.013), indicating superior reasoning for buzz groups working with bimodal materials. For specialists, a positive effect of bimodal presentation was found on perceptions of learning (p < 0.05), and for residents, a positive effect of buzz groups was found on judgment of learning (p < 0.005). A positive effect of bimodal presentation on diagnostic accuracy was noted in the specialists (p < 0.05). Combined bimodal presentation and buzz group discussion of emergency cases improves clinicians' clinical reasoning and learning.

An efficient numerical method for solving the Boltzmann equation in multidimensions

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

A framework for the social valuation of ecosystem services.

PubMed

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

2015-05-01

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

Determination Instructions Efficiency of Teaching Methods in Teaching Physics in the Case of Teaching Unit "Viscosity. Newtonian and Stokes Law"

ERIC Educational Resources Information Center

Radulovic, Branka; Stojanovic, Maja

2015-01-01

The use of different teaching methods has resulted in different quality and quantity of students' knowledge. For this reason, it is important to constantly review the teaching methods and applied most effectively. One way of determining instruction efficiency is by using cognitive load and student achievement. Cognitive load can be generally…

Cellular automatons applied to gas dynamic problems

NASA Technical Reports Server (NTRS)

Long, Lyle N.; Coopersmith, Robert M.; Mclachlan, B. G.

1987-01-01

This paper compares the results of a relatively new computational fluid dynamics method, cellular automatons, with experimental data and analytical results. This technique has been shown to qualitatively predict fluidlike behavior; however, there have been few published comparisons with experiment or other theories. Comparisons are made for a one-dimensional supersonic piston problem, Stokes first problem, and the flow past a normal flat plate. These comparisons are used to assess the ability of the method to accurately model fluid dynamic behavior and to point out its limitations. Reasonable results were obtained for all three test cases, but the fundamental limitations of cellular automatons are numerous. It may be misleading, at this time, to say that cellular automatons are a computationally efficient technique. Other methods, based on continuum or kinetic theory, would also be very efficient if as little of the physics were included.

Modeling crime events by d-separation method

NASA Astrophysics Data System (ADS)

Aarthee, R.; Ezhilmaran, D.

2017-11-01

Problematic legal cases have recently called for a scientifically founded method of dealing with the qualitative and quantitative roles of evidence in a case [1].To deal with quantitative, we proposed a d-separation method for modeling the crime events. A d-separation is a graphical criterion for identifying independence in a directed acyclic graph. By developing a d-separation method, we aim to lay the foundations for the development of a software support tool that can deal with the evidential reasoning in legal cases. Such a tool is meant to be used by a judge or juror, in alliance with various experts who can provide information about the details. This will hopefully improve the communication between judges or jurors and experts. The proposed method used to uncover more valid independencies than any other graphical criterion.

[Analysis of gene mutation of early onset epileptic spasm with unknown reason].

PubMed

Yang, X; Pan, G; Li, W H; Zhang, L M; Wu, B B; Wang, H J; Zhang, P; Zhou, S Z

2017-11-02

Objective: To summarize the gene mutation of early onset epileptic spasm with unknown reason. Method: In this prospective study, data of patients with early onset epileptic spasm with unknown reason were collected from neurological department of Children's Hospital of Fudan University between March 2016 and December 2016. Patients with known disorders such as infection, metabolic, structural, immunological problems and known genetic mutations were excluded. Patients with genetic disease that can be diagnosed by clinical manifestations and phenotypic characteristics were also excluded. Genetic research methods included nervous system panel containing 1 427 epilepsy genes, whole exome sequencing (WES), analysis of copy number variation (CNV) and karyotype analysis of chromosome. The basic information, phenotypes, genetic results and the antiepileptic treatment of patients were analyzed. Result: Nine of the 17 cases with early onset epileptic spasm were boys and eight were girls. Patients' age at first seizure onset ranged from 1 day after birth to 8 months (median age of 3 months). The first hospital visit age ranged from 1 month to 2 years (median age of 4.5 months). The time of following-up ranged from 8 months to 3 years and 10 months. All the 17 patients had early onset epileptic spasm. Video electroencephalogram was used to monitor the spasm seizure. Five patients had Ohtahara syndrome, 10 had West syndrome, two had unclear classification. In 17 cases, 10 of them had detected pathogenic genes. Nine cases had point mutations, involving SCN2A, ARX, UNC80, KCNQ2, and GABRB3. Except one case of mutations in GABRB3 gene have been reported, all the other cases had new mutations. One patient had deletion mutation in CDKL5 gene. One CNV case had 6q 22.31 5.5MB repeats. Ten cases out of 17 were using 2-3 antiepileptic drugs (AEDs) and the drugs had no effect. Seven cases used adrenocorticotropic hormone (ACTH) and prednisone besides AEDs (a total course for 8 weeks). Among them, five cases had no effect and two cases were seizure free recently. A case with GABRB3 (C.905A>G) had seizure controlled for 3 mouths. A case with ARX (C.700G>A) had seizure controlled for 6 mouths. Conclusion: The early onset epileptic spasm with unknown reason is highly related to genetic disorders. A variety of genetic mutations, especially new mutations were found. Genetic heterogeneity of epileptic spasm is obvious.

Emergy-based comparative analysis on industrial clusters: economic and technological development zone of Shenyang area, China.

PubMed

Liu, Zhe; Geng, Yong; Zhang, Pan; Dong, Huijuan; Liu, Zuoxi

2014-09-01

In China, local governments of many areas prefer to give priority to the development of heavy industrial clusters in pursuit of high value of gross domestic production (GDP) growth to get political achievements, which usually results in higher costs from ecological degradation and environmental pollution. Therefore, effective methods and reasonable evaluation system are urgently needed to evaluate the overall efficiency of industrial clusters. Emergy methods links economic and ecological systems together, which can evaluate the contribution of ecological products and services as well as the load placed on environmental systems. This method has been successfully applied in many case studies of ecosystem but seldom in industrial clusters. This study applied the methodology of emergy analysis to perform the efficiency of industrial clusters through a series of emergy-based indices as well as the proposed indicators. A case study of Shenyang Economic Technological Development Area (SETDA) was investigated to show the emergy method's practical potential to evaluate industrial clusters to inform environmental policy making. The results of our study showed that the industrial cluster of electric equipment and electronic manufacturing produced the most economic value and had the highest efficiency of energy utilization among the four industrial clusters. However, the sustainability index of the industrial cluster of food and beverage processing was better than the other industrial clusters.

Formal reasoning about systems biology using theorem proving

PubMed Central

Hasan, Osman; Siddique, Umair; Tahar, Sofiène

2017-01-01

System biology provides the basis to understand the behavioral properties of complex biological organisms at different levels of abstraction. Traditionally, analysing systems biology based models of various diseases have been carried out by paper-and-pencil based proofs and simulations. However, these methods cannot provide an accurate analysis, which is a serious drawback for the safety-critical domain of human medicine. In order to overcome these limitations, we propose a framework to formally analyze biological networks and pathways. In particular, we formalize the notion of reaction kinetics in higher-order logic and formally verify some of the commonly used reaction based models of biological networks using the HOL Light theorem prover. Furthermore, we have ported our earlier formalization of Zsyntax, i.e., a deductive language for reasoning about biological networks and pathways, from HOL4 to the HOL Light theorem prover to make it compatible with the above-mentioned formalization of reaction kinetics. To illustrate the usefulness of the proposed framework, we present the formal analysis of three case studies, i.e., the pathway leading to TP53 Phosphorylation, the pathway leading to the death of cancer stem cells and the tumor growth based on cancer stem cells, which is used for the prognosis and future drug designs to treat cancer patients. PMID:28671950

Teaching Scientific Reasoning to Liberal Arts Students

NASA Astrophysics Data System (ADS)

Rubbo, Louis

2014-03-01

University courses in conceptual physics and astronomy typically serve as the terminal science experience for the liberal arts student. Within this population significant content knowledge gains can be achieved by utilizing research verified pedagogical methods. However, from the standpoint of the Univeristy, students are expected to complete these courses not necessarily for the content knowledge but instead for the development of scientific reasoning skills. Results from physics education studies indicate that unless scientific reasoning instruction is made explicit students do not progress in their reasoning abilities. How do we complement the successful content based pedagogical methods with instruction that explicitly focuses on the development of scientific reasoning skills? This talk will explore methodologies that actively engages the non-science students with the explicit intent of fostering their scientific reasoning abilities.

On the integration of reinforcement learning and approximate reasoning for control

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1991-01-01

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

Using Computer Simulations for Promoting Model-Based Reasoning: Epistemological and Educational Dimensions

ERIC Educational Resources Information Center

Develaki, Maria

2017-01-01

Scientific reasoning is particularly pertinent to science education since it is closely related to the content and methodologies of science and contributes to scientific literacy. Much of the research in science education investigates the appropriate framework and teaching methods and tools needed to promote students' ability to reason and…

26 CFR 1.924(a)-1T - Temporary regulations; definition of foreign trading gross receipts.

Code of Federal Regulations, 2010 CFR

2010-04-01

... related services furnished by the FSC (as described in this paragraph (d)(2)). In the case of a sale... the sale. In the case of a lease, reasonable expectations at the time of the lease are based on the... determined under the facts and circumstances of each case without regard to whether— (A) The services are...

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

ERIC Educational Resources Information Center

Huang, Wenyeh; Ho, Jonathan C.

2018-01-01

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

Normative Command and Control Influences: A Study of Cohesion in Terrorist Organizations and Their Effect on Society

DTIC Science & Technology

2007-06-01

general conclusions from specific examples. For this reason, single case studies will not be used in this thesis. Instead, short examples drawn from...potential members perceive others as wanting to relieve their internal conflicts using the same methods, in this case , violence.35...against the nation-state group. In this case , the smaller group, especially with leadership advocating opposing values, may develop norms that do

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.

Interpretive analysis of 85 systematic reviews suggests that narrative syntheses and meta‐analyses are incommensurate in argumentation

PubMed Central

O'Mara‐Eves, A.; Thomas, J.; Brunton, G.; Caird, J.; Petticrew, M.

2016-01-01

Using Toulmin's argumentation theory, we analysed the texts of systematic reviews in the area of workplace health promotion to explore differences in the modes of reasoning embedded in reports of narrative synthesis as compared with reports of meta‐analysis. We used framework synthesis, grounded theory and cross‐case analysis methods to analyse 85 systematic reviews addressing intervention effectiveness in workplace health promotion. Two core categories, or ‘modes of reasoning’, emerged to frame the contrast between narrative synthesis and meta‐analysis: practical–configurational reasoning in narrative synthesis (‘what is going on here? What picture emerges?’) and inferential–predictive reasoning in meta‐analysis (‘does it work, and how well? Will it work again?’). Modes of reasoning examined quality and consistency of the included evidence differently. Meta‐analyses clearly distinguished between warrant and claim, whereas narrative syntheses often presented joint warrant–claims. Narrative syntheses and meta‐analyses represent different modes of reasoning. Systematic reviewers are likely to be addressing research questions in different ways with each method. It is important to consider narrative synthesis in its own right as a method and to develop specific quality criteria and understandings of how it is carried out, not merely as a complement to, or second‐best option for, meta‐analysis. © 2016 The Authors. Research Synthesis Methods published by John Wiley & Sons Ltd. PMID:27860329

Analysis of public responses to preparedness policies: the cases of H1N1 influenza vaccination and gas mask distribution

PubMed Central

2013-01-01

Background During several months in 2009–2010, the Israeli population was asked to take part in two preparedness programs: Acquisition of gas masks against a potential chemical-warfare attack, and vaccination against the A/H1N1 influenza pandemics. Compliance with the first request was moderate and did not attract much attention, whereas compliance with the second request was very low and was accompanied by significant controversy. The aims of this study are to compare the public’s attitudes towards these two preparedness campaigns, and to explore the roles of trust, reasoned assessment, and reflexive reactions in the public’s response to governmental preparedness policies. Methods The comparative analysis was based on a telephone survey of 2,018 respondents representing a cross-section of the adult Israeli population. Univariate analysis to describe associations of public response and attitude was performed by Chi-square tests. Findings A set of queries related to actual compliance, trust in credibility of authorities, personal opinions, reasons for non-compliance, and attitudes towards uncertainties was used to characterize the response to mask-acquisition and vaccination. In the case of mask-acquisition, the dominant response profile was of trusting compliance based on non-conditional belief in the need to adhere to the recommendation (35.6% of respondents). In the case of vaccination, the dominant response profile was of trusting non-compliance based on a reflective belief in the need for adherence (34.8% of respondents). Among the variables examined in the study, passivity was found to be the major reason for non-compliance with mask-acquisition, whereas reasoned assessment of risk played a major role in non-compliance with vaccination. Realization of the complexity in dealing with uncertainty related to developing epidemics and to newly-developed vaccines was identified in the public’s response to the H1N1 vaccination campaign. Conclusions The newly identified profile of “trusting-reflective-non-complier” individuals should be of concern to policy makers. The public is not accepting governmental recommendations in an unconditional manner. This is not driven by lack of trust in authorities, but rather by the perception of the responsibility of individuals in confronting forthcoming risks. Nevertheless, under certain conditions the public may respond in a non-reflective way and delegate this responsibly to authorities in an uncontested manner. This leaves the policy makers with the complex challenge of interacting with a passive non-involved public or alternatively with an opinionated, reflexive public. PMID:23537171

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

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.

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

ERIC Educational Resources Information Center

Alshamali, Mahmoud A.; Daher, Wajeeh M.

2016-01-01

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

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

PubMed Central

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

2014-01-01

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

From spoken narratives to domain knowledge: mining linguistic data for medical image understanding.

PubMed

Guo, Xuan; Yu, Qi; Alm, Cecilia Ovesdotter; Calvelli, Cara; Pelz, Jeff B; Shi, Pengcheng; Haake, Anne R

2014-10-01

Extracting useful visual clues from medical images allowing accurate diagnoses requires physicians' domain knowledge acquired through years of systematic study and clinical training. This is especially true in the dermatology domain, a medical specialty that requires physicians to have image inspection experience. Automating or at least aiding such efforts requires understanding physicians' reasoning processes and their use of domain knowledge. Mining physicians' references to medical concepts in narratives during image-based diagnosis of a disease is an interesting research topic that can help reveal experts' reasoning processes. It can also be a useful resource to assist with design of information technologies for image use and for image case-based medical education systems. We collected data for analyzing physicians' diagnostic reasoning processes by conducting an experiment that recorded their spoken descriptions during inspection of dermatology images. In this paper we focus on the benefit of physicians' spoken descriptions and provide a general workflow for mining medical domain knowledge based on linguistic data from these narratives. The challenge of a medical image case can influence the accuracy of the diagnosis as well as how physicians pursue the diagnostic process. Accordingly, we define two lexical metrics for physicians' narratives--lexical consensus score and top N relatedness score--and evaluate their usefulness by assessing the diagnostic challenge levels of corresponding medical images. We also report on clustering medical images based on anchor concepts obtained from physicians' medical term usage. These analyses are based on physicians' spoken narratives that have been preprocessed by incorporating the Unified Medical Language System for detecting medical concepts. The image rankings based on lexical consensus score and on top 1 relatedness score are well correlated with those based on challenge levels (Spearman correlation>0.5 and Kendall correlation>0.4). Clustering results are largely improved based on our anchor concept method (accuracy>70% and mutual information>80%). Physicians' spoken narratives are valuable for the purpose of mining the domain knowledge that physicians use in medical image inspections. We also show that the semantic metrics introduced in the paper can be successfully applied to medical image understanding and allow discussion of additional uses of these metrics. Copyright © 2014 Elsevier B.V. All rights reserved.

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

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.

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

PubMed

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

2018-03-01

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

Correcting Classifiers for Sample Selection Bias in Two-Phase Case-Control Studies

PubMed Central

Theis, Fabian J.

2017-01-01

Epidemiological studies often utilize stratified data in which rare outcomes or exposures are artificially enriched. This design can increase precision in association tests but distorts predictions when applying classifiers on nonstratified data. Several methods correct for this so-called sample selection bias, but their performance remains unclear especially for machine learning classifiers. With an emphasis on two-phase case-control studies, we aim to assess which corrections to perform in which setting and to obtain methods suitable for machine learning techniques, especially the random forest. We propose two new resampling-based methods to resemble the original data and covariance structure: stochastic inverse-probability oversampling and parametric inverse-probability bagging. We compare all techniques for the random forest and other classifiers, both theoretically and on simulated and real data. Empirical results show that the random forest profits from only the parametric inverse-probability bagging proposed by us. For other classifiers, correction is mostly advantageous, and methods perform uniformly. We discuss consequences of inappropriate distribution assumptions and reason for different behaviors between the random forest and other classifiers. In conclusion, we provide guidance for choosing correction methods when training classifiers on biased samples. For random forests, our method outperforms state-of-the-art procedures if distribution assumptions are roughly fulfilled. We provide our implementation in the R package sambia. PMID:29312464

A power comparison of generalized additive models and the spatial scan statistic in a case-control setting.

PubMed

Young, Robin L; Weinberg, Janice; Vieira, Verónica; Ozonoff, Al; Webster, Thomas F

2010-07-19

A common, important problem in spatial epidemiology is measuring and identifying variation in disease risk across a study region. In application of statistical methods, the problem has two parts. First, spatial variation in risk must be detected across the study region and, second, areas of increased or decreased risk must be correctly identified. The location of such areas may give clues to environmental sources of exposure and disease etiology. One statistical method applicable in spatial epidemiologic settings is a generalized additive model (GAM) which can be applied with a bivariate LOESS smoother to account for geographic location as a possible predictor of disease status. A natural hypothesis when applying this method is whether residential location of subjects is associated with the outcome, i.e. is the smoothing term necessary? Permutation tests are a reasonable hypothesis testing method and provide adequate power under a simple alternative hypothesis. These tests have yet to be compared to other spatial statistics. This research uses simulated point data generated under three alternative hypotheses to evaluate the properties of the permutation methods and compare them to the popular spatial scan statistic in a case-control setting. Case 1 was a single circular cluster centered in a circular study region. The spatial scan statistic had the highest power though the GAM method estimates did not fall far behind. Case 2 was a single point source located at the center of a circular cluster and Case 3 was a line source at the center of the horizontal axis of a square study region. Each had linearly decreasing logodds with distance from the point. The GAM methods outperformed the scan statistic in Cases 2 and 3. Comparing sensitivity, measured as the proportion of the exposure source correctly identified as high or low risk, the GAM methods outperformed the scan statistic in all three Cases. The GAM permutation testing methods provide a regression-based alternative to the spatial scan statistic. Across all hypotheses examined in this research, the GAM methods had competing or greater power estimates and sensitivities exceeding that of the spatial scan statistic.

A power comparison of generalized additive models and the spatial scan statistic in a case-control setting

PubMed Central

2010-01-01

Background A common, important problem in spatial epidemiology is measuring and identifying variation in disease risk across a study region. In application of statistical methods, the problem has two parts. First, spatial variation in risk must be detected across the study region and, second, areas of increased or decreased risk must be correctly identified. The location of such areas may give clues to environmental sources of exposure and disease etiology. One statistical method applicable in spatial epidemiologic settings is a generalized additive model (GAM) which can be applied with a bivariate LOESS smoother to account for geographic location as a possible predictor of disease status. A natural hypothesis when applying this method is whether residential location of subjects is associated with the outcome, i.e. is the smoothing term necessary? Permutation tests are a reasonable hypothesis testing method and provide adequate power under a simple alternative hypothesis. These tests have yet to be compared to other spatial statistics. Results This research uses simulated point data generated under three alternative hypotheses to evaluate the properties of the permutation methods and compare them to the popular spatial scan statistic in a case-control setting. Case 1 was a single circular cluster centered in a circular study region. The spatial scan statistic had the highest power though the GAM method estimates did not fall far behind. Case 2 was a single point source located at the center of a circular cluster and Case 3 was a line source at the center of the horizontal axis of a square study region. Each had linearly decreasing logodds with distance from the point. The GAM methods outperformed the scan statistic in Cases 2 and 3. Comparing sensitivity, measured as the proportion of the exposure source correctly identified as high or low risk, the GAM methods outperformed the scan statistic in all three Cases. Conclusions The GAM permutation testing methods provide a regression-based alternative to the spatial scan statistic. Across all hypotheses examined in this research, the GAM methods had competing or greater power estimates and sensitivities exceeding that of the spatial scan statistic. PMID:20642827

A subagging regression method for estimating the qualitative and quantitative state of groundwater

NASA Astrophysics Data System (ADS)

Jeong, J.; Park, E.; Choi, J.; Han, W. S.; Yun, S. T.

2016-12-01

A subagging regression (SBR) method for the analysis of groundwater data pertaining to the estimation of trend and the associated uncertainty is proposed. The SBR method is validated against synthetic data competitively with other conventional robust and non-robust methods. From the results, it is verified that the estimation accuracies of the SBR method are consistent and superior to those of the other methods and the uncertainties are reasonably estimated where the others have no uncertainty analysis option. To validate further, real quantitative and qualitative data are employed and analyzed comparatively with Gaussian process regression (GPR). For all cases, the trend and the associated uncertainties are reasonably estimated by SBR, whereas the GPR has limitations in representing the variability of non-Gaussian skewed data. From the implementations, it is determined that the SBR method has potential to be further developed as an effective tool of anomaly detection or outlier identification in groundwater state data.

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

PubMed

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

2012-01-01

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

Practical dose point-based methods to characterize dose distribution in a stationary elliptical body phantom for a cone-beam C-arm CT system

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

Choi, Jang-Hwan, E-mail: jhchoi21@stanford.edu; Constantin, Dragos; Ganguly, Arundhuti

2015-08-15

Purpose: To propose new dose point measurement-based metrics to characterize the dose distributions and the mean dose from a single partial rotation of an automatic exposure control-enabled, C-arm-based, wide cone angle computed tomography system over a stationary, large, body-shaped phantom. Methods: A small 0.6 cm{sup 3} ion chamber (IC) was used to measure the radiation dose in an elliptical body-shaped phantom made of tissue-equivalent material. The IC was placed at 23 well-distributed holes in the central and peripheral regions of the phantom and dose was recorded for six acquisition protocols with different combinations of minimum kVp (109 and 125 kVp)more » and z-collimator aperture (full: 22.2 cm; medium: 14.0 cm; small: 8.4 cm). Monte Carlo (MC) simulations were carried out to generate complete 2D dose distributions in the central plane (z = 0). The MC model was validated at the 23 dose points against IC experimental data. The planar dose distributions were then estimated using subsets of the point dose measurements using two proposed methods: (1) the proximity-based weighting method (method 1) and (2) the dose point surface fitting method (method 2). Twenty-eight different dose point distributions with six different point number cases (4, 5, 6, 7, 14, and 23 dose points) were evaluated to determine the optimal number of dose points and their placement in the phantom. The performances of the methods were determined by comparing their results with those of the validated MC simulations. The performances of the methods in the presence of measurement uncertainties were evaluated. Results: The 5-, 6-, and 7-point cases had differences below 2%, ranging from 1.0% to 1.7% for both methods, which is a performance comparable to that of the methods with a relatively large number of points, i.e., the 14- and 23-point cases. However, with the 4-point case, the performances of the two methods decreased sharply. Among the 4-, 5-, 6-, and 7-point cases, the 7-point case (1.0% [±0.6%] difference) and the 6-point case (0.7% [±0.6%] difference) performed best for method 1 and method 2, respectively. Moreover, method 2 demonstrated high-fidelity surface reconstruction with as few as 5 points, showing pixelwise absolute differences of 3.80 mGy (±0.32 mGy). Although the performance was shown to be sensitive to the phantom displacement from the isocenter, the performance changed by less than 2% for shifts up to 2 cm in the x- and y-axes in the central phantom plane. Conclusions: With as few as five points, method 1 and method 2 were able to compute the mean dose with reasonable accuracy, demonstrating differences of 1.7% (±1.2%) and 1.3% (±1.0%), respectively. A larger number of points do not necessarily guarantee better performance of the methods; optimal choice of point placement is necessary. The performance of the methods is sensitive to the alignment of the center of the body phantom relative to the isocenter. In body applications where dose distributions are important, method 2 is a better choice than method 1, as it reconstructs the dose surface with high fidelity, using as few as five points.« less

Generalizability of Evidence-Based Assessment Recommendations for Pediatric Bipolar Disorder

PubMed Central

Jenkins, Melissa M.; Youngstrom, Eric A.; Youngstrom, Jennifer Kogos; Feeny, Norah C.; Findling, Robert L.

2013-01-01

Bipolar disorder is frequently clinically diagnosed in youths who do not actually satisfy DSM-IV criteria, yet cases that would satisfy full DSM-IV criteria are often undetected clinically. Evidence-based assessment methods that incorporate Bayesian reasoning have demonstrated improved diagnostic accuracy, and consistency; however, their clinical utility is largely unexplored. The present study examines the effectiveness of promising evidence-based decision-making compared to the clinical gold standard. Participants were 562 youth, ages 5-17 and predominantly African American, drawn from a community mental health clinic. Research diagnoses combined semi-structured interview with youths’ psychiatric, developmental, and family mental health histories. Independent Bayesian estimates relied on published risk estimates from other samples discriminated bipolar diagnoses, Area Under Curve=.75, p<.00005. The Bayes and confidence ratings correlated rs =.30. Agreement about an evidence-based assessment intervention “threshold model” (wait/assess/treat) had K=.24, p<.05. No potential moderators of agreement between the Bayesian estimates and confidence ratings, including type of bipolar illness, were significant. Bayesian risk estimates were highly correlated with logistic regression estimates using optimal sample weights, r=.81, p<.0005. Clinical and Bayesian approaches agree in terms of overall concordance and deciding next clinical action, even when Bayesian predictions are based on published estimates from clinically and demographically different samples. Evidence-based assessment methods may be useful in settings that cannot routinely employ gold standard assessments, and they may help decrease rates of overdiagnosis while promoting earlier identification of true cases. PMID:22004538

Scottish court dismisses a historic smoker's suit

PubMed Central

Friedman, L; Daynard, R

2007-01-01

The decision in a Scottish smoker's case, McTear v. Imperial Tobacco Limited, that there was no scientific proof of causation between the plaintiff's smoking and his death from lung cancer, accepted all of the traditional arguments that the tobacco industry has made throughout the history of tobacco litigation, including that epidemiology is not an adequate branch of science to draw a conclusion of causation, that the tobacco industry has no knowledge that its products are dangerous to consumers, and that, despite this lack of knowledge, the plaintiff had sufficient information to make an informed decision about the dangers of smoking. This case relied on outmoded methods of reasoning and placed too great a faith in the tobacco industry's timeworn argument that “everybody knew, nobody knows”. Further, the judge found it prejudicial that the plaintiff's expert witnesses were not paid for their services because she was indigent, believing that the lack of payment placed in doubt their credibility and claiming that the paid tobacco expert witnesses had more motive to testify independently because they had been paid, a perverse and novel line of reasoning. The McTear case contrasts unfavourably with the recent decision in United States v. Philip Morris, a United States decision that found the tobacco industry defendants to be racketeers, based both on the weight of a huge amount of internal tobacco industry documents showing that the tobacco industry knew their products were addictive and were made that way purposely to increase sales, and on the testimony of expert witnesses who, like those who testified in McTear, have made the advancement of the public health their life's work and are not “hired guns”. The McTear case's reasoning seems outdated and reminiscent of early litigation in the United States. Hopefully, it will not take courts outside of the United States 40 more years to acknowledge the current scientific knowledge about smoking and health. PMID:17897973

Extracorporeal Treatment in Phenytoin Poisoning: Systematic Review and Recommendations from the EXTRIP (Extracorporeal Treatments in Poisoning) Workgroup.

PubMed

Anseeuw, Kurt; Mowry, James B; Burdmann, Emmanuel A; Ghannoum, Marc; Hoffman, Robert S; Gosselin, Sophie; Lavergne, Valery; Nolin, Thomas D

2016-02-01

The Extracorporeal Treatments in Poisoning (EXTRIP) Workgroup conducted a systematic literature review using a standardized process to develop evidence-based recommendations on the use of extracorporeal treatment (ECTR) in patients with phenytoin poisoning. The authors reviewed all articles, extracted data, summarized findings, and proposed structured voting statements following a predetermined format. A 2-round modified Delphi method was used to reach a consensus on voting statements, and the RAND/UCLA Appropriateness Method was used to quantify disagreement. 51 articles met the inclusion criteria. Only case reports, case series, and pharmacokinetic studies were identified, yielding a very low quality of evidence. Clinical data from 31 patients and toxicokinetic grading from 46 patients were abstracted. The workgroup concluded that phenytoin is moderately dialyzable (level of evidence = C) despite its high protein binding and made the following recommendations. ECTR would be reasonable in select cases of severe phenytoin poisoning (neutral recommendation, 3D). ECTR is suggested if prolonged coma is present or expected (graded 2D) and it would be reasonable if prolonged incapacitating ataxia is present or expected (graded 3D). If ECTR is used, it should be discontinued when clinical improvement is apparent (graded 1D). The preferred ECTR modality in phenytoin poisoning is intermittent hemodialysis (graded 1D), but hemoperfusion is an acceptable alternative if hemodialysis is not available (graded 1D). In summary, phenytoin appears to be amenable to extracorporeal removal. However, because of the low incidence of irreversible tissue injury or death related to phenytoin poisoning and the relatively limited effect of ECTR on phenytoin removal, the workgroup proposed the use of ECTR only in very select patients with severe phenytoin poisoning. Copyright © 2016 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.

Revision of Viable Environmental Monitoring in a Development Pilot Plant Based on Quality Risk Assessment: A Case Study.

PubMed

Ziegler, Ildikó; Borbély-Jakab, Judit; Sugó, Lilla; Kovács, Réka J

2017-01-01

In this case study, the principles of quality risk management were applied to review sampling points and monitoring frequencies in the hormonal tableting unit of a formulation development pilot plant. In the cleanroom area, premises of different functions are located. Therefore a general method was established for risk evaluation based on the Hazard Analysis and Critical Control Points (HACCP) method to evaluate these premises (i.e., production area itself and ancillary clean areas) from the point of view of microbial load and state in order to observe whether the existing monitoring program met the emerged advanced monitoring practice. LAY ABSTRACT: In pharmaceutical production, cleanrooms are needed for the manufacturing of final dosage forms of drugs-intended for human or veterinary use-in order to protect the patient's weakened body from further infections. Cleanrooms are premises with a controlled level of contamination that is specified by the number of particles per cubic meter at a specified particle size or number of microorganisms (i.e. microbial count) per surface area. To ensure a low microbial count over time, microorganisms are detected and counted by environmental monitoring methods regularly. It is reasonable to find the easily infected places by risk analysis to make sure the obtained results really represent the state of the whole room. This paper presents a risk analysis method for the optimization of environmental monitoring and verification of the suitability of the method. © PDA, Inc. 2017.

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

The Validity of the Comparative Interrupted Time Series Design for Evaluating the Effect of School-Level Interventions.

PubMed

Jacob, Robin; Somers, Marie-Andree; Zhu, Pei; Bloom, Howard

2016-06-01

In this article, we examine whether a well-executed comparative interrupted time series (CITS) design can produce valid inferences about the effectiveness of a school-level intervention. This article also explores the trade-off between bias reduction and precision loss across different methods of selecting comparison groups for the CITS design and assesses whether choosing matched comparison schools based only on preintervention test scores is sufficient to produce internally valid impact estimates. We conduct a validation study of the CITS design based on the federal Reading First program as implemented in one state using results from a regression discontinuity design as a causal benchmark. Our results contribute to the growing base of evidence regarding the validity of nonexperimental designs. We demonstrate that the CITS design can, in our example, produce internally valid estimates of program impacts when multiple years of preintervention outcome data (test scores in the present case) are available and when a set of reasonable criteria are used to select comparison organizations (schools in the present case). © The Author(s) 2016.

True or false: do 5-year-olds understand belief?

PubMed

Fabricius, William V; Boyer, Ty W; Weimer, Amy A; Carroll, Kathleen

2010-11-01

In 3 studies (N = 188) we tested the hypothesis that children use a perceptual access approach to reason about mental states before they understand beliefs. The perceptual access hypothesis predicts a U-shaped developmental pattern of performance in true belief tasks, in which 3-year-olds who reason about reality should succeed, 4- to 5-year-olds who use perceptual access reasoning should fail, and older children who use belief reasoning should succeed. The results of Study 1 revealed the predicted pattern in 2 different true belief tasks. The results of Study 2 disconfirmed several alternate explanations based on possible pragmatic and inhibitory demands of the true belief tasks. In Study 3, we compared 2 methods of classifying individuals according to which 1 of the 3 reasoning strategies (reality reasoning, perceptual access reasoning, belief reasoning) they used. The 2 methods gave converging results. Both methods indicated that the majority of children used the same approach across tasks and that it was not until after 6 years of age that most children reasoned about beliefs. We conclude that because most prior studies have failed to detect young children's use of perceptual access reasoning, they have overestimated their understanding of false beliefs. We outline several theoretical implications that follow from the perceptual access hypothesis.

Modeling Multibody Stage Separation Dynamics Using Constraint Force Equation Methodology

NASA Technical Reports Server (NTRS)

Tartabini, Paul V.; Roithmayr, Carlos M.; Toniolo, Matthew D.; Karlgaard, Christopher D.; Pamadi, Bandu N.

2011-01-01

This paper discusses the application of the constraint force equation methodology and its implementation for multibody separation problems using three specially designed test cases. The first test case involves two rigid bodies connected by a fixed joint, the second case involves two rigid bodies connected with a universal joint, and the third test case is that of Mach 7 separation of the X-43A vehicle. For the first two cases, the solutions obtained using the constraint force equation method compare well with those obtained using industry- standard benchmark codes. For the X-43A case, the constraint force equation solutions show reasonable agreement with the flight-test data. Use of the constraint force equation method facilitates the analysis of stage separation in end-to-end simulations of launch vehicle trajectories

Experience with Using Multiple Types of Visual Educational Tools during Problem-Based Learning.

PubMed

Kang, Bong Jin

2012-06-01

This study describes the experience of using multiple types of visual educational tools in the setting of problem-based learning (PBL). The author intends to demonstrate their roles in diverse and efficient ways of clinical reasoning and problem solving. Visual educational tools were introduced in a lecture that included their various types, possible benefits, and some examples. Each group made one mechanistic case diagram per week, and each student designed one diagnostic schema or therapeutic algorithm per week, based on their learning issues. The students were also told to provide commentary, which was intended to give insights into their truthfulness. Subsequently, the author administered a questionnaire about the usefulness and weakness of visual educational tools and the difficulties with performing the work. Also, the qualities of the products were assessed by the author. There were many complaints about the adequacy of the introduction of visual educational tools, also revealed by the many initial inappropriate types of products. However, the exercise presentation in the first week improved the level of understanding regarding their purposes and the method of design. In general, students agreed on the benefits of their help in providing a deep understanding of the cases and the possibility of solving clinical problems efficiently. The commentary was helpful in evaluating the truthfulness of their efforts. Students gave suggestions for increasing the percentage of their scores, considering the efforts. Using multiple types of visual educational tools during PBL can be useful in understanding the diverse routes of clinical reasoning and clinical features.

Fault Diagnosis Method for a Mine Hoist in the Internet of Things Environment.

PubMed

Li, Juanli; Xie, Jiacheng; Yang, Zhaojian; Li, Junjie

2018-06-13

To reduce the difficulty of acquiring and transmitting data in mining hoist fault diagnosis systems and to mitigate the low efficiency and unreasonable reasoning process problems, a fault diagnosis method for mine hoisting equipment based on the Internet of Things (IoT) is proposed in this study. The IoT requires three basic architectural layers: a perception layer, network layer, and application layer. In the perception layer, we designed a collaborative acquisition system based on the ZigBee short distance wireless communication technology for key components of the mine hoisting equipment. Real-time data acquisition was achieved, and a network layer was created by using long-distance wireless General Packet Radio Service (GPRS) transmission. The transmission and reception platforms for remote data transmission were able to transmit data in real time. A fault diagnosis reasoning method is proposed based on the improved Dezert-Smarandache Theory (DSmT) evidence theory, and fault diagnosis reasoning is performed. Based on interactive technology, a humanized and visualized fault diagnosis platform is created in the application layer. The method is then verified. A fault diagnosis test of the mine hoisting mechanism shows that the proposed diagnosis method obtains complete diagnostic data, and the diagnosis results have high accuracy and reliability.

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.

Understanding case mix across three paediatric services: could integration of primary and secondary general paediatrics alter walk-in emergency attendances?

PubMed

Steele, Lloyd; Coote, Nicky; Klaber, Robert; Watson, Mando; Coren, Michael

2018-05-04

To understand the case mix of three different paediatric services, reasons for using an acute paediatric service in a region of developing integrated care and where acute attendances could alternatively have been managed. Mixed methods service evaluation, including retrospective review of referrals to general paediatric outpatients (n=534) and a virtual integrated service (email advice line) (n=474), as well as a prospective survey of paediatric ambulatory unit (PAU) attendees (n=95) and review by a paediatric consultant/registrar to decide where these cases could alternatively have been managed. The case mix of outpatient referrals and the email advice line was similar, but the case mix for PAU was more acute.The most common parental reasons for attending PAU were referral by a community health professional (27.2%), not being able to get a general practitioner (GP) appointment when desired (21.7%), wanting to avoid accident and emergency (17.4%) and wanting specialist paediatric input (14.1%). More than half of PAU presentations were deemed most appropriate for community management by a GP or midwife. The proportion of cases suitable for community management varied by the reason for attendance, with it highestl for parents reporting not being able to get a GP appointment (85%), and lowest for those referred by community health professionals (29%). One in two attendances to acute paediatric services could have been managed in the community. Integration of paediatric services could help address parental reasons for attending acute services, as well as facilitating the community management of chronic conditions. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Towards a formal genealogical classification of the Lezgian languages (North Caucasus): testing various phylogenetic methods on lexical data.

PubMed

Kassian, Alexei

2015-01-01

A lexicostatistical classification is proposed for 20 languages and dialects of the Lezgian group of the North Caucasian family, based on meticulously compiled 110-item wordlists, published as part of the Global Lexicostatistical Database project. The lexical data have been subsequently analyzed with the aid of the principal phylogenetic methods, both distance-based and character-based: Starling neighbor joining (StarlingNJ), Neighbor joining (NJ), Unweighted pair group method with arithmetic mean (UPGMA), Bayesian Markov chain Monte Carlo (MCMC), Unweighted maximum parsimony (UMP). Cognation indexes within the input matrix were marked by two different algorithms: traditional etymological approach and phonetic similarity, i.e., the automatic method of consonant classes (Levenshtein distances). Due to certain reasons (first of all, high lexicographic quality of the wordlists and a consensus about the Lezgian phylogeny among Caucasologists), the Lezgian database is a perfect testing area for appraisal of phylogenetic methods. For the etymology-based input matrix, all the phylogenetic methods, with the possible exception of UMP, have yielded trees that are sufficiently compatible with each other to generate a consensus phylogenetic tree of the Lezgian lects. The obtained consensus tree agrees with the traditional expert classification as well as some of the previously proposed formal classifications of this linguistic group. Contrary to theoretical expectations, the UMP method has suggested the least plausible tree of all. In the case of the phonetic similarity-based input matrix, the distance-based methods (StarlingNJ, NJ, UPGMA) have produced the trees that are rather close to the consensus etymology-based tree and the traditional expert classification, whereas the character-based methods (Bayesian MCMC, UMP) have yielded less likely topologies.

Towards a Formal Genealogical Classification of the Lezgian Languages (North Caucasus): Testing Various Phylogenetic Methods on Lexical Data

PubMed Central

Kassian, Alexei

2015-01-01

A lexicostatistical classification is proposed for 20 languages and dialects of the Lezgian group of the North Caucasian family, based on meticulously compiled 110-item wordlists, published as part of the Global Lexicostatistical Database project. The lexical data have been subsequently analyzed with the aid of the principal phylogenetic methods, both distance-based and character-based: Starling neighbor joining (StarlingNJ), Neighbor joining (NJ), Unweighted pair group method with arithmetic mean (UPGMA), Bayesian Markov chain Monte Carlo (MCMC), Unweighted maximum parsimony (UMP). Cognation indexes within the input matrix were marked by two different algorithms: traditional etymological approach and phonetic similarity, i.e., the automatic method of consonant classes (Levenshtein distances). Due to certain reasons (first of all, high lexicographic quality of the wordlists and a consensus about the Lezgian phylogeny among Caucasologists), the Lezgian database is a perfect testing area for appraisal of phylogenetic methods. For the etymology-based input matrix, all the phylogenetic methods, with the possible exception of UMP, have yielded trees that are sufficiently compatible with each other to generate a consensus phylogenetic tree of the Lezgian lects. The obtained consensus tree agrees with the traditional expert classification as well as some of the previously proposed formal classifications of this linguistic group. Contrary to theoretical expectations, the UMP method has suggested the least plausible tree of all. In the case of the phonetic similarity-based input matrix, the distance-based methods (StarlingNJ, NJ, UPGMA) have produced the trees that are rather close to the consensus etymology-based tree and the traditional expert classification, whereas the character-based methods (Bayesian MCMC, UMP) have yielded less likely topologies. PMID:25719456

System Matrix Analysis for Computed Tomography Imaging

PubMed Central

Flores, Liubov; Vidal, Vicent; Verdú, Gumersindo

2015-01-01

In practical applications of computed tomography imaging (CT), it is often the case that the set of projection data is incomplete owing to the physical conditions of the data acquisition process. On the other hand, the high radiation dose imposed on patients is also undesired. These issues demand that high quality CT images can be reconstructed from limited projection data. For this reason, iterative methods of image reconstruction have become a topic of increased research interest. Several algorithms have been proposed for few-view CT. We consider that the accurate solution of the reconstruction problem also depends on the system matrix that simulates the scanning process. In this work, we analyze the application of the Siddon method to generate elements of the matrix and we present results based on real projection data. PMID:26575482

Rock cliffs hazard analysis based on remote geostructural surveys: The Campione del Garda case study (Lake Garda, Northern Italy)

NASA Astrophysics Data System (ADS)

Ferrero, A. M.; Migliazza, M.; Roncella, R.; Segalini, A.

2011-02-01

The town of Campione del Garda (located on the west coast of Lake Garda) and its access road have been historically subject to rockfall phenomena with risk for public security in several areas of the coast. This paper presents a study devoted to the determination of risk for coastal cliffs and the design of mitigation measures. Our study was based on statistical rockfall analysis performed with a commercial code and on stability analysis of rock slopes based on the key block method. Hazard from block kinematics and rock-slope failure are coupled by applying the Rockfall Hazard Assessment Procedure (RHAP). Because of the huge dimensions of the slope, its morphology and the geostructural survey were particularly complicated and demanding. For these reasons, noncontact measurement methods, based on aerial photogrammetry by helicopter, were adopted. A special software program, developed by the authors, was applied for discontinuity identification and for their orientation measurements. The potentially of aerial photogrammetic survey in rock mechanic application and its improvement in the rock mass knowledge is analysed in the article.

Ab initio phasing based on topological restraints: automated determination of the space group and the number of molecules in the unit cell.

PubMed

Urzhumtseva, Ludmila; Lunina, Natalia; Fokine, Andrei; Samama, Jean Pierre; Lunin, Vladimir Y; Urzhumtsev, Alexandre

2004-09-01

The connectivity-based phasing method has been demonstrated to be capable of finding molecular packing and envelopes even for difficult cases of structure determination, as well as of identifying, in favorable cases, secondary-structure elements of protein molecules in the crystal. This method uses a single set of structure factor magnitudes and general topological features of a crystallographic image of the macromolecule under study. This information is expressed through a number of parameters. Most of these parameters are easy to estimate, and the results of phasing are practically independent of these parameters when they are chosen within reasonable limits. By contrast, the correct choice for such parameters as the expected number of connected regions in the unit cell is sometimes ambiguous. To study these dependencies, numerous tests were performed with simulated data, experimental data and mixed data sets, where several reflections missed in the experiment were completed by computed data. This paper demonstrates that the procedure is able to control this choice automatically and helps in difficult cases to identify the correct number of molecules in the asymmetric unit. In addition, the procedure behaves abnormally if the space group is defined incorrectly and therefore may distinguish between the rotation and screw axes even when high-resolution data are not available.

Chart Audit and Chart Stimulated Recall as Methods of Needs Assessment in Continuing Professional Health Education.

ERIC Educational Resources Information Center

Affleck, Louise; Jennett, Penny

1998-01-01

Chart audit (assessment of patient medical records) is a cost-effective continuing-education needs-assessment method. Chart stimulated recall, in which physicians' memory of particular cases is stimulated by records, potentially increases content validity and exploration of clinical reasoning as well as the context of clinical decisions. (SK)

Image matching algorithms for breech face marks and firing pins in a database of spent cartridge cases of firearms.

PubMed

Geradts, Z J; Bijhold, J; Hermsen, R; Murtagh, F

2001-06-01

On the market several systems exist for collecting spent ammunition data for forensic investigation. These databases store images of cartridge cases and the marks on them. Image matching is used to create hit lists that show which marks on a cartridge case are most similar to another cartridge case. The research in this paper is focused on the different methods of feature selection and pattern recognition that can be used for optimizing the results of image matching. The images are acquired by side light images for the breech face marks and by ring light for the firing pin impression. For these images a standard way of digitizing the images used. For the side light images and ring light images this means that the user has to position the cartridge case in the same position according to a protocol. The positioning is important for the sidelight, since the image that is obtained of a striation mark depends heavily on the angle of incidence of the light. In practice, it appears that the user positions the cartridge case with +/-10 degrees accuracy. We tested our algorithms using 49 cartridge cases of 19 different firearms, where the examiner determined that they were shot with the same firearm. For testing, these images were mixed with a database consisting of approximately 4900 images that were available from the Drugfire database of different calibers.In cases where the registration and the light conditions among those matching pairs was good, a simple computation of the standard deviation of the subtracted gray levels, delivered the best-matched images. For images that were rotated and shifted, we have implemented a "brute force" way of registration. The images are translated and rotated until the minimum of the standard deviation of the difference is found. This method did not result in all relevant matches in the top position. This is caused by the effect that shadows and highlights are compared in intensity. Since the angle of incidence of the light will give a different intensity profile, this method is not optimal. For this reason a preprocessing of the images was required. It appeared that the third scale of the "à trous" wavelet transform gives the best results in combination with brute force. Matching the contents of the images is less sensitive to the variation of the lighting. The problem with the brute force method is however that the time for calculation for 49 cartridge cases to compare between them, takes over 1 month of computing time on a Pentium II-computer with 333MHz. For this reason a faster approach is implemented: correlation in log polar coordinates. This gave similar results as the brute force calculation, however it was computed in 24h for a complete database with 4900 images.A fast pre-selection method based on signatures is carried out that is based on the Kanade Lucas Tomasi (KLT) equation. The positions of the points computed with this method are compared. In this way, 11 of the 49 images were in the top position in combination with the third scale of the à trous equation. It depends however on the light conditions and the prominence of the marks if correct matches are found in the top ranked position. All images were retrieved in the top 5% of the database. This method takes only a few minutes for the complete database if, and can be optimized for comparison in seconds if the location of points are stored in files. For further improvement, it is useful to have the refinement in which the user selects the areas that are relevant on the cartridge case for their marks. This is necessary if this cartridge case is damaged and other marks that are not from the firearm appear on it.

Conflict monitoring in dual process theories of thinking.

PubMed

De Neys, Wim; Glumicic, Tamara

2008-03-01

Popular dual process theories have characterized human thinking as an interplay between an intuitive-heuristic and demanding-analytic reasoning process. Although monitoring the output of the two systems for conflict is crucial to avoid decision making errors there are some widely different views on the efficiency of the process. Kahneman [Kahneman, D. (2002). Maps of bounded rationality: A perspective on intuitive judgement and choice. Nobel Prize Lecture. Retrieved January 11, 2006, from: http://nobelprize.org/nobel_prizes/economics/laureates/2002/kahnemann-lecture.pdf] and Evans [Evans, J. St. B. T. (1984). Heuristic and analytic processing in reasoning. British Journal of Psychology, 75, 451-468], for example, claim that the monitoring of the heuristic system is typically quite lax whereas others such as Sloman [Sloman, S. A. (1996). The empirical case for two systems of reasoning. Psychological Bulletin, 119, 3-22] and Epstein [Epstein, S. (1994). Integration of the cognitive and psychodynamic unconscious. American Psychologists, 49, 709-724] claim it is flawless and people typically experience a struggle between what they "know" and "feel" in case of a conflict. The present study contrasted these views. Participants solved classic base rate neglect problems while thinking aloud. In these problems a stereotypical description cues a response that conflicts with the response based on the analytic base rate information. Verbal protocols showed no direct evidence for an explicitly experienced conflict. As Kahneman and Evans predicted, participants hardly ever mentioned the base rates and seemed to base their judgment exclusively on heuristic reasoning. However, more implicit measures of conflict detection such as participants' retrieval of the base rate information in an unannounced recall test, decision making latencies, and the tendency to review the base rates indicated that the base rates had been thoroughly processed. On control problems where base rates and description did not conflict this was not the case. Results suggest that whereas the popular characterization of conflict detection as an actively experienced struggle can be questioned there is nevertheless evidence for Sloman's and Epstein's basic claim about the flawless operation of the monitoring. Whenever the base rates and description disagree people will detect this conflict and consequently redirect attention towards a deeper processing of the base rates. Implications for the dual process framework and the rationality debate are discussed.

Estimating Individual Influences of Behavioral Intentions: An Application of Random-Effects Modeling to the Theory of Reasoned Action.

ERIC Educational Resources Information Center

Hedeker, Donald; And Others

1996-01-01

Methods are proposed and described for estimating the degree to which relations among variables vary at the individual level. As an example, M. Fishbein and I. Ajzen's theory of reasoned action is examined. This article illustrates the use of empirical Bayes methods based on a random-effects regression model to estimate individual influences…

Proportional reasoning as a heuristic-based process: time constraint and dual task considerations.

PubMed

Gillard, Ellen; Van Dooren, Wim; Schaeken, Walter; Verschaffel, Lieven

2009-01-01

The present study interprets the overuse of proportional solution methods from a dual process framework. Dual process theories claim that analytic operations involve time-consuming executive processing, whereas heuristic operations are fast and automatic. In two experiments to test whether proportional reasoning is heuristic-based, the participants solved "proportional" problems, for which proportional solution methods provide correct answers, and "nonproportional" problems known to elicit incorrect answers based on the assumption of proportionality. In Experiment 1, the available solution time was restricted. In Experiment 2, the executive resources were burdened with a secondary task. Both manipulations induced an increase in proportional answers and a decrease in correct answers to nonproportional problems. These results support the hypothesis that the choice for proportional methods is heuristic-based.

Approximation methods for stochastic petri nets

NASA Technical Reports Server (NTRS)

Jungnitz, Hauke Joerg

1992-01-01

Stochastic Marked Graphs are a concurrent decision free formalism provided with a powerful synchronization mechanism generalizing conventional Fork Join Queueing Networks. In some particular cases the analysis of the throughput can be done analytically. Otherwise the analysis suffers from the classical state explosion problem. Embedded in the divide and conquer paradigm, approximation techniques are introduced for the analysis of stochastic marked graphs and Macroplace/Macrotransition-nets (MPMT-nets), a new subclass introduced herein. MPMT-nets are a subclass of Petri nets that allow limited choice, concurrency and sharing of resources. The modeling power of MPMT is much larger than that of marked graphs, e.g., MPMT-nets can model manufacturing flow lines with unreliable machines and dataflow graphs where choice and synchronization occur. The basic idea leads to the notion of a cut to split the original net system into two subnets. The cuts lead to two aggregated net systems where one of the subnets is reduced to a single transition. A further reduction leads to a basic skeleton. The generalization of the idea leads to multiple cuts, where single cuts can be applied recursively leading to a hierarchical decomposition. Based on the decomposition, a response time approximation technique for the performance analysis is introduced. Also, delay equivalence, which has previously been introduced in the context of marked graphs by Woodside et al., Marie's method and flow equivalent aggregation are applied to the aggregated net systems. The experimental results show that response time approximation converges quickly and shows reasonable accuracy in most cases. The convergence of Marie's method and flow equivalent aggregation are applied to the aggregated net systems. The experimental results show that response time approximation converges quickly and shows reasonable accuracy in most cases. The convergence of Marie's is slower, but the accuracy is generally better. Delay equivalence often fails to converge, while flow equivalent aggregation can lead to potentially bad results if a strong dependence of the mean completion time on the interarrival process exists.

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

NASA Astrophysics Data System (ADS)

Karahan, Engin

Addressing socioscientific issues (SSI) has been one of the main focuses in science education since the Science, Technology, and Society (STS) movement in the 1970s (Levinson, 2006); however, teaching controversial socioscientific issues has always been challenging for teachers (Dillon, 1994; Osborne, Duschl, & Fairbrother, 2002). Although teachers exhibit positive attitudes for using controversial socioscientific issues in their science classrooms, only a small percentage of them actually incorporate SSI content into their science curricula on a regular basis (Sadler, Amirshokoohi, Kazempour, & Allspaw, 2006; Lee & Witz, 2009). The literature in science education has highlighted the signi?cant relationships among teacher beliefs, teaching practices, and student learning (Bryan & Atwater, 2002; King, Shumow, & Lietz, 2001; Lederman, 1992). Despite the fact that the case studies present a relatively detailed picture of teachers' values and motivations for teaching SSI (e.g. Lee, 2006; Lee & Witz, 2009; Reis & Galvao, 2004), these studies still miss the practices of these teachers and potential outcomes for their students. Therefore, there is a great need for in-depth case studies that would focus on teachers' practices of designing and teaching SSI-based learning environments, their deeper beliefs and motivations for teaching SSI, and their students' response to these practices (Lee, 2006). This dissertation is structured as three separate, but related, studies about secondary school teachers' experiences of designing and teaching SSI-based classes and their students' understanding of science and SSI reasoning. The case studies in this dissertation seek answers for (1) teachers' practices of designing and teaching SSI-based instruction, as well as its relation to their deeper personal beliefs and motivations to teach SSI, and (2) how their students respond to their approaches of teaching SSI in terms of their science understanding and SSI reasoning. The first paper presents case studies of three secondary science teachers within three high schools located along the Minnesota River Basin. The findings of this study documented the experiences of the participant teachers, as well as the contextual influences on those experiences. The second paper presents a case study of a science teacher and a social studies teacher which describes how these two teachers collaboratively designed and taught an environmental ethics class. The results of this study documented teachers' ways of sharing responsibilities, bringing their content and pedagogical expertise, and promoting the agency of their students in the environmental ethics class. The final paper in this dissertation presents case studies of secondary school students who were the participants in the SSI-based science classes described in the first two studies. The results of this study provided evidence for participant students' understanding of science and their socioscientific reasoning, as well as how they were influenced by the instructional decisions their teachers made.

The effect of first chromosome long arm duplication on survival of endometrial carcinoma

PubMed Central

Sever, Erman; Doğer, Emek; Çakıroğlu, Yiğit; Sünnetçi, Deniz; Çine, Naci; Savlı, Hakan; Yücesoy, İzzet

2014-01-01

Objective: The aim of this study is to investigate the effect of first chromosome long arm duplication (dup(1q)) in cases with endometrial carcinoma detected with array based comperative genomic hybridization (aCGH) on survival from the cancer. Materials and Methods: A total of 53 patients with the diagnosis of endometrial carcinom due to endometrial biopsy and who have been operated for this reason have been allocated in the study. Frozen section biopsy and staging surgery have been performed for all the cases. Samples obtained from the tumoral mass have been investigated for chromosomal aberrations with aCGH method. Kaplan-Meier and Cox-regression analysis have been performed for survival analysis. Results: Among 53 cases with endometrial carcinomas, dup(1q) was diagnosed in 14 (26.4%) of the cases. For the patient group that has been followed-up for 24 months (3-33 months), dup(1q) (p=.01), optimal cytoreduction (p<.001), lymph node positivity (p=.006), tumor stage >1 (p=.006) and presence of high risk tumor were the factors that were associated with survival. Cox-regression analysis has revealed that optimal cytoreduction was the most important prognostic factor (p=.02). Conclusion: Presence of 1q duplication can be used as a prognostic factor in the preoperative period. PMID:28913021

Teaching and Assessing Clinical Reasoning Skills.

PubMed

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

2015-09-01

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

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,…

Organising the Chemistry of Question-Based Learning: A Case Study

ERIC Educational Resources Information Center

de Jesus, Helena Pedrosa; de Souza, Francisle Neri; Teixeira-Dias, Jose J. C.; Watts, Mike

2005-01-01

Designing inquiry-based-learning with and for university students develops problem-solving skills and logical reasoning, as well as reflective thinking. It involves working as a member of a team, questioning, being creative, shaping the skills for continued intellectual development. It is argued that inquiry-based group work is one of the most…

Assessing Complex Emergency Management with Clinical Case-Vignettes: A Validation Study

PubMed Central

2015-01-01

Objective To evaluate whether responses to dynamic case-vignettes accurately reflect actual practices in complex emergency situations. We hypothesized that when obstetricians were faced with vignette of emergency situation identical to one they previously managed, they would report the management strategy they actually used. On the other hand, there is no reason to suppose that their response to a vignette based on a source case managed by another obstetrician would be the same as the actual management. Methods A multicenter vignette-based study was used in 7 French maternity units. We chose the example of severe postpartum hemorrhage (PPH) to study the use of case-vignettes for assessing the management of complex situations. We developed dynamic case-vignettes describing incidents of PPH in several steps, using documentation in patient files. Vignettes described the postpartum course and included multiple-choice questions detailing proposed clinical care. Each participating obstetrician was asked to evaluate 4 case-vignettes: 2 directly derived from cases they previously managed and 2 derived from other obstetricians’ cases. We compared the final treatment decision in vignette responses to those documented in the source-case by the overall agreement and the Kappa coefficient, both for the cases the obstetricians previously managed and the cases of others. Results Thirty obstetricians participated. Overall agreement between final treatment decisions in case-vignettes and documented care for cases obstetricians previously managed was 82% (Kappa coefficient: 0.75, 95% CI [0.62–0.88]). Overall agreement between final treatment decisions in case-vignettes and documented care in vignettes derived from other obstetricians’ cases was only 48% (Kappa coefficient: 0.30, 95% CI [0.12–0.48]). Final agreement with documented care was significantly better for cases based on their own previous cases than for others (p<0.001). Conclusions Dynamic case-vignettes accurately reflect actual practices in complex emergency situations. Therefore, they can be used to assess the quality of management in these situations. PMID:26383261

Influx: A Tool and Framework for Reasoning under Uncertainty

DTIC Science & Technology

2015-09-01

Interfaces to external programs Not all types of problems are naturally suited to being entirely modelled and implemented within Influx1. In general... development pertaining to the implementation of the reasoning tool and specific applications are not included in this document. RELEASE LIMITATION...which case a probability is supposed to reflect the subjective belief of an agent for the problem at hand ( based on its experience and/or current state

First Attempt of Orbit Determination of SLR Satellites and Space Debris Using Genetic Algorithms

NASA Astrophysics Data System (ADS)

Deleflie, F.; Coulot, D.; Descosta, R.; Fernier, A.; Richard, P.

2013-08-01

We present an orbit determination method based on genetic algorithms. Contrary to usual estimation methods mainly based on least-squares methods, these algorithms do not require any a priori knowledge of the initial state vector to be estimated. These algorithms can be applied when a new satellite is launched or for uncatalogued objects that appear in images obtained from robotic telescopes such as the TAROT ones. We show in this paper preliminary results obtained from an SLR satellite, for which tracking data acquired by the ILRS network enable to build accurate orbital arcs at a few centimeter level, which can be used as a reference orbit ; in this case, the basic observations are made up of time series of ranges, obtained from various tracking stations. We show as well the results obtained from the observations acquired by the two TAROT telescopes on the Telecom-2D satellite operated by CNES ; in that case, the observations are made up of time series of azimuths and elevations, seen from the two TAROT telescopes. The method is carried out in several steps: (i) an analytical propagation of the equations of motion, (ii) an estimation kernel based on genetic algorithms, which follows the usual steps of such approaches: initialization and evolution of a selected population, so as to determine the best parameters. Each parameter to be estimated, namely each initial keplerian element, has to be searched among an interval that is preliminary chosen. The algorithm is supposed to converge towards an optimum over a reasonable computational time.

Model Updating of Complex Structures Using the Combination of Component Mode Synthesis and Kriging Predictor

PubMed Central

Li, Yan; Wang, Dejun; Zhang, Shaoyi

2014-01-01

Updating the structural model of complex structures is time-consuming due to the large size of the finite element model (FEM). Using conventional methods for these cases is computationally expensive or even impossible. A two-level method, which combined the Kriging predictor and the component mode synthesis (CMS) technique, was proposed to ensure the successful implementing of FEM updating of large-scale structures. In the first level, the CMS was applied to build a reasonable condensed FEM of complex structures. In the second level, the Kriging predictor that was deemed as a surrogate FEM in structural dynamics was generated based on the condensed FEM. Some key issues of the application of the metamodel (surrogate FEM) to FEM updating were also discussed. Finally, the effectiveness of the proposed method was demonstrated by updating the FEM of a real arch bridge with the measured modal parameters. PMID:24634612

Formal Consistency Verification of Deliberative Agents with Respect to Communication Protocols

NASA Technical Reports Server (NTRS)

Ramirez, Jaime; deAntonio, Angelica

2004-01-01

The aim of this paper is to show a method that is able to detect inconsistencies in the reasoning carried out by a deliberative agent. The agent is supposed to be provided with a hybrid Knowledge Base expressed in a language called CCR-2, based on production rules and hierarchies of frames, which permits the representation of non-monotonic reasoning, uncertain reasoning and arithmetic constraints in the rules. The method can give a specification of the scenarios in which the agent would deduce an inconsistency. We define a scenario to be a description of the initial agent s state (in the agent life cycle), a deductive tree of rule firings, and a partially ordered set of messages and/or stimuli that the agent must receive from other agents and/or the environment. Moreover, the method will make sure that the scenarios will be valid w.r.t. the communication protocols in which the agent is involved.

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

ERIC Educational Resources Information Center

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

2013-01-01

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

An unsupervised method for summarizing egocentric sport videos

NASA Astrophysics Data System (ADS)

Habibi Aghdam, Hamed; Jahani Heravi, Elnaz; Puig, Domenec

2015-12-01

People are getting more interested to record their sport activities using head-worn or hand-held cameras. This type of videos which is called egocentric sport videos has different motion and appearance patterns compared with life-logging videos. While a life-logging video can be defined in terms of well-defined human-object interactions, notwithstanding, it is not trivial to describe egocentric sport videos using well-defined activities. For this reason, summarizing egocentric sport videos based on human-object interaction might fail to produce meaningful results. In this paper, we propose an unsupervised method for summarizing egocentric videos by identifying the key-frames of the video. Our method utilizes both appearance and motion information and it automatically finds the number of the key-frames. Our blind user study on the new dataset collected from YouTube shows that in 93:5% cases, the users choose the proposed method as their first video summary choice. In addition, our method is within the top 2 choices of the users in 99% of studies.

Pneumococcal vaccination and risk of myocardial infarction

PubMed Central

Lamontagne, François; Garant, Marie-Pierre; Carvalho, Jean-Christophe; Lanthier, Luc; Smieja, Marek; Pilon, Danielle

2008-01-01

Background Based on promising results from laboratory studies, we hypothesized that pneumococcal vaccination would protect patients from myocardial infarction. Methods We conducted a hospital-based case–control study that included patients considered to be at risk of myocardial infarction. We used health databases to obtain hospital diagnoses and vaccination status. We compared patients who had been admitted for treatment of myocardial infarction with patients admitted to a surgical department in the same hospital for a reason other than myocardial infarction between 1997 and 2003. Results We found a total of 43 209 patients who were at risk; of these, we matched 999 cases and 3996 controls according to age, sex and year of hospital admission. Cases were less likely than controls to have been vaccinated (adjusted odds ratio [OR] 0.53, 95% confidence interval [CI] 0.40–0.70). This putative protective role of the vaccine was not observed for patients who had received the vaccine up to 1 year before myocardial infarction (adjusted OR 0.85, 95% CI 0.54–1.33). In contrast, if vaccination had occurred 2 years or more before the hospital admission, the association was stronger (adjusted OR 0.33, 95% CI 0.20–0.46). Interpretation Pneumococcal vaccination was associated with a decrease of more than 50% in the rate myocardial infarction 2 years after exposure. If confirmed, this association should generate interest in exploring the putative mechanisms and may offer another reason to promote pneumococcal vaccination. PMID:18838452

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.

Multimodal navigated skull base tumor resection using image-based vascular and cranial nerve segmentation: A prospective pilot study

PubMed Central

Dolati, Parviz; Gokoglu, Abdulkerim; Eichberg, Daniel; Zamani, Amir; Golby, Alexandra; Al-Mefty, Ossama

2015-01-01

Background: Skull base tumors frequently encase or invade adjacent normal neurovascular structures. For this reason, optimal tumor resection with incomplete knowledge of patient anatomy remains a challenge. Methods: To determine the accuracy and utility of image-based preoperative segmentation in skull base tumor resections, we performed a prospective study. Ten patients with skull base tumors underwent preoperative 3T magnetic resonance imaging, which included thin section three-dimensional (3D) space T2, 3D time of flight, and magnetization-prepared rapid acquisition gradient echo sequences. Imaging sequences were loaded in the neuronavigation system for segmentation and preoperative planning. Five different neurovascular landmarks were identified in each case and measured for accuracy using the neuronavigation system. Each segmented neurovascular element was validated by manual placement of the navigation probe, and errors of localization were measured. Results: Strong correspondence between image-based segmentation and microscopic view was found at the surface of the tumor and tumor-normal brain interfaces in all cases. The accuracy of the measurements was 0.45 ± 0.21 mm (mean ± standard deviation). This information reassured the surgeon and prevented vascular injury intraoperatively. Preoperative segmentation of the related cranial nerves was possible in 80% of cases and helped the surgeon localize involved cranial nerves in all cases. Conclusion: Image-based preoperative vascular and neural element segmentation with 3D reconstruction is highly informative preoperatively and could increase the vigilance of neurosurgeons for preventing neurovascular injury during skull base surgeries. Additionally, the accuracy found in this study is superior to previously reported measurements. This novel preliminary study is encouraging for future validation with larger numbers of patients. PMID:26674155

Current distribution on a cylindrical antenna with parallel orientation in a lossy magnetoplasma

NASA Technical Reports Server (NTRS)

Klein, C. A.; Klock, P. W.; Deschamps, G. A.

1972-01-01

The current distribution and impedance of a thin cylindrical antenna with parallel orientation to the static magnetic field of a lossy magnetoplasma is calculated with the method of moments. The electric field produced by an infinitesimal current source is first derived. Results are presented for a wide range of plasma parameters. Reasonable answers are obtained for all cases except for the overdense hyperbolic case. A discussion of the numerical stability is included which not only applies to this problem but other applications of the method of moments.

Intelligent Gearbox Diagnosis Methods Based on SVM, Wavelet Lifting and RBR

PubMed Central

Gao, Lixin; Ren, Zhiqiang; Tang, Wenliang; Wang, Huaqing; Chen, Peng

2010-01-01

Given the problems in intelligent gearbox diagnosis methods, it is difficult to obtain the desired information and a large enough sample size to study; therefore, we propose the application of various methods for gearbox fault diagnosis, including wavelet lifting, a support vector machine (SVM) and rule-based reasoning (RBR). In a complex field environment, it is less likely for machines to have the same fault; moreover, the fault features can also vary. Therefore, a SVM could be used for the initial diagnosis. First, gearbox vibration signals were processed with wavelet packet decomposition, and the signal energy coefficients of each frequency band were extracted and used as input feature vectors in SVM for normal and faulty pattern recognition. Second, precision analysis using wavelet lifting could successfully filter out the noisy signals while maintaining the impulse characteristics of the fault; thus effectively extracting the fault frequency of the machine. Lastly, the knowledge base was built based on the field rules summarized by experts to identify the detailed fault type. Results have shown that SVM is a powerful tool to accomplish gearbox fault pattern recognition when the sample size is small, whereas the wavelet lifting scheme can effectively extract fault features, and rule-based reasoning can be used to identify the detailed fault type. Therefore, a method that combines SVM, wavelet lifting and rule-based reasoning ensures effective gearbox fault diagnosis. PMID:22399894

Intelligent gearbox diagnosis methods based on SVM, wavelet lifting and RBR.

PubMed

Gao, Lixin; Ren, Zhiqiang; Tang, Wenliang; Wang, Huaqing; Chen, Peng

2010-01-01

Given the problems in intelligent gearbox diagnosis methods, it is difficult to obtain the desired information and a large enough sample size to study; therefore, we propose the application of various methods for gearbox fault diagnosis, including wavelet lifting, a support vector machine (SVM) and rule-based reasoning (RBR). In a complex field environment, it is less likely for machines to have the same fault; moreover, the fault features can also vary. Therefore, a SVM could be used for the initial diagnosis. First, gearbox vibration signals were processed with wavelet packet decomposition, and the signal energy coefficients of each frequency band were extracted and used as input feature vectors in SVM for normal and faulty pattern recognition. Second, precision analysis using wavelet lifting could successfully filter out the noisy signals while maintaining the impulse characteristics of the fault; thus effectively extracting the fault frequency of the machine. Lastly, the knowledge base was built based on the field rules summarized by experts to identify the detailed fault type. Results have shown that SVM is a powerful tool to accomplish gearbox fault pattern recognition when the sample size is small, whereas the wavelet lifting scheme can effectively extract fault features, and rule-based reasoning can be used to identify the detailed fault type. Therefore, a method that combines SVM, wavelet lifting and rule-based reasoning ensures effective gearbox fault diagnosis.

Identifying developmental features in students' clinical reasoning to inform teaching.

PubMed

Pinnock, Ralph; Anakin, Megan; Lawrence, Julie; Chignell, Helen; Wilkinson, Tim

2018-04-27

There is increasing evidence that students at different levels of training may benefit from different methods of learning clinical reasoning. Two of the common methods of teaching are the "whole - case" format and the "serial cue" approach. There is little empirical evidence to guide teachers as to which method to use and when to introduce them. We observed 23 students from different stages of training to examine how they were taking a history and how they were thinking whilst doing this. Each student interviewed a simulated patient who presented with a straightforward and a complex presentation. We inferred how students were reasoning from how they took a history and how they described their thinking while doing this. Early in their training students can only take a generic history. Only later in training are they able to take a focused history, remember the information they have gathered, use it to seek further specific information, compare and contrast possibilities and analyze their data as they are collecting it. Early in their training students are unable to analyze data during history taking. When they have started developing illness scripts, they are able to benefit from the "serial cue" approach of teaching clinical reasoning.

Second trimester abortions in India.

PubMed

Dalvie, Suchitra S

2008-05-01

This article gives an overview of what is known about second trimester abortions in India, including the reasons why women seek abortions in the second trimester, the influence of abortion law and policy, surgical and medical methods used, both safe and unsafe, availability of services, requirements for second trimester service delivery, and barriers women experience in accessing second trimester services. Based on personal experiences and personal communications from other doctors since 1993, when I began working as an abortion provider, the practical realities of second trimester abortion and case histories of women seeking second trimester abortion are also described. Recommendations include expanding the cadre of service providers to non-allopathic clinicians and trained nurses, introducing second trimester medical abortion into the public health system, replacing ethacridine lactate with mifepristone-misoprostol, values clarification among providers to challenge stigma and poor treatment of women seeking second trimester abortion, and raising awareness that abortion is legal in the second trimester and is mostly not requested for reasons of sex selection.

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

PubMed Central

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

1998-01-01

One goal of artificial intelligence research into case-based reasoning (CBR) systems is to develop approaches for designing useful and practical interactive case-based environments. Explaining each step of the design of the case-base and of the retrieval process is critical for the application of case-based systems to the real world. We describe herein our approach to the design of IDEM--Images and Diagnosis from Examples in Medicine--a medical image case-based retrieval system for pathologists. Our approach is based on the expressiveness of an object-oriented modeling language standard: the Unified Modeling Language (UML). We created a set of diagrams in UML notation illustrating the steps of the CBR methodology we used. The key aspect of this approach was selecting the relevant objects of the system according to user requirements and making visualization of cases and of the components of the case retrieval process. Further evaluation of the expressiveness of the design document is required but UML seems to be a promising formalism, improving the communication between the developers and users. Images Figure 6 Figure 7 PMID:9929346

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

PubMed

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

1998-01-01

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

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

PubMed

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

2015-01-01

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

16 CFR 306.5 - Automotive fuel rating.

Code of Federal Regulations, 2014 CFR

2014-01-01

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

16 CFR 306.5 - Automotive fuel rating.

Code of Federal Regulations, 2013 CFR

2013-01-01

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

16 CFR 306.5 - Automotive fuel rating.

Code of Federal Regulations, 2012 CFR

2012-01-01

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

Correlates of Incident Cognitive Impairment in the REasons for Geographic and Racial Differences in Stroke (REGARDS) Study

PubMed Central

Gillett, Sarah R.; Thacker, Evan L.; Letter, Abraham J.; McClure, Leslie A.; Wadley, Virginia G.; Unverzagt, Frederick W.; Kissela, Brett M.; Kennedy, Richard E.; Glasser, Stephen P.; Levine, Deborah A.; Cushman, Mary

2015-01-01

Objective To identify approximately 500 cases of incident cognitive impairment (ICI) in a large, national sample adapting an existing cognitive test-based case definition and to examine relationships of vascular risk factors with ICI. Method Participants were from the REGARDS study, a national sample of 30,239 African-American and white Americans. Participants included in this analysis had normal cognitive screening and no history of stroke at baseline, and at least one follow-up cognitive assessment with a three test battery (TTB). Regression-based norms were applied to TTB scores to identify cases of ICI. Logistic regression was used to model associations with baseline vascular risk factors. Results We identified 495 participants with ICI out of 17,630 eligible participants. In multivariable modeling, income (OR 1.83 CI 1.27,2.62), stroke belt residence (OR 1.45 CI 1.18,1.78), history of transient ischemic attack (OR 1.90 CI 1.29,2.81), coronary artery disease(OR 1.32 CI 1.02,1.70), diabetes (OR 1.48 CI 1.17,1.87), obesity (OR 1.40 CI 1.05,1.86), and incident stroke (OR 2.73 CI 1.52,4.90) were associated with ICI. Conclusions We adapted a previously validated cognitive test-based case definition to identify cases of ICI. Many previously identified risk factors were associated with ICI, supporting the criterion-related validity of our definition. PMID:25978342

Socratic Method for the Right Reasons and in the Right Way: Lessons from Teaching Legal Analysis beyond the American Law School

ERIC Educational Resources Information Center

Szypszak, Charles

2015-01-01

Socratic method is associated with law school teaching by which students are asked questions in class that require them to analyze cases and derive legal principles. Despite the method's potential benefits, students usually do not view it as supportive and enriching but rather as a kind of survival ritual. As a pedagogical approach for use in any…

Research on optimal DEM cell size for 3D visualization of loess terraces

NASA Astrophysics Data System (ADS)

Zhao, Weidong; Tang, Guo'an; Ji, Bin; Ma, Lei

2009-10-01

In order to represent the complex artificial terrains like loess terraces in Shanxi Province in northwest China, a new 3D visual method namely Terraces Elevation Incremental Visual Method (TEIVM) is put forth by the authors. 406 elevation points and 14 enclosed constrained lines are sampled according to the TIN-based Sampling Method (TSM) and DEM Elevation Points and Lines Classification (DEPLC). The elevation points and constrained lines are used to construct Constrained Delaunay Triangulated Irregular Networks (CD-TINs) of the loess terraces. In order to visualize the loess terraces well by use of optimal combination of cell size and Elevation Increment Value (EIV), the CD-TINs is converted to Grid-based DEM (G-DEM) by use of different combination of cell size and EIV with linear interpolating method called Bilinear Interpolation Method (BIM). Our case study shows that the new visual method can visualize the loess terraces steps very well when the combination of cell size and EIV is reasonable. The optimal combination is that the cell size is 1 m and the EIV is 6 m. Results of case study also show that the cell size should be at least smaller than half of both the terraces average width and the average vertical offset of terraces steps for representing the planar shapes of the terraces surfaces and steps well, while the EIV also should be larger than 4.6 times of the terraces average height. The TEIVM and results above is of great significance to the highly refined visualization of artificial terrains like loess terraces.

A generalised multiple-mass based method for the determination of the live mass of a force transducer

NASA Astrophysics Data System (ADS)

Montalvão, Diogo; Baker, Thomas; Ihracska, Balazs; Aulaqi, Muhammad

2017-01-01

Many applications in Experimental Modal Analysis (EMA) require that the sensors' masses are known. This is because the added mass from sensors will affect the structural mode shapes, and in particular its natural frequencies. EMA requires the measurement of the exciting forces at given coordinates, which is often made using piezoelectric force transducers. In such a case, the live mass of the force transducer, i.e. the mass as 'seen' by the structure in perpendicular directions must be measured somehow, so that compensation methods like mass cancelation can be performed. This however presents a problem on how to obtain an accurate measurement for the live mass. If the system is perfectly calibrated, then a reasonably accurate estimate can be made using a straightforward method available in most classical textbooks based on Newton's second law. However, this is often not the case (for example when the transducer's sensitivity changed over time, when it is unknown or when the connection influences the transmission of the force). In a self-calibrating iterative method, both the live mass and calibration factor are determined, but this paper shows that the problem may be ill-conditioned, producing misleading results if certain conditions are not met. Therefore, a more robust method is presented and discussed in this paper, reducing the ill-conditioning problems and the need to know the calibration factors beforehand. The three methods will be compared and discussed through numerical and experimental examples, showing that classical EMA still is a field of research that deserves the attention from scientists and engineers.

Validation of equations for pleural effusion volume estimation by ultrasonography.

PubMed

Hassan, Maged; Rizk, Rana; Essam, Hatem; Abouelnour, Ahmed

2017-12-01

To validate the accuracy of previously published equations that estimate pleural effusion volume using ultrasonography. Only equations using simple measurements were tested. Three measurements were taken at the posterior axillary line for each case with effusion: lateral height of effusion ( H ), distance between collapsed lung and chest wall ( C ) and distance between lung and diaphragm ( D ). Cases whose effusion was aspirated to dryness were included and drained volume was recorded. Intra-class correlation coefficient (ICC) was used to determine the predictive accuracy of five equations against the actual volume of aspirated effusion. 46 cases with effusion were included. The most accurate equation in predicting effusion volume was ( H  +  D ) × 70 (ICC 0.83). The simplest and yet accurate equation was H  × 100 (ICC 0.79). Pleural effusion height measured by ultrasonography gives a reasonable estimate of effusion volume. Incorporating distance between lung base and diaphragm into estimation improves accuracy from 79% with the first method to 83% with the latter.

Inclusion of particle-vibration coupling in the Fayans functional: Odd-even mass differences of semimagic nuclei

NASA Astrophysics Data System (ADS)

Saperstein, E. E.; Baldo, M.; Pankratov, S. S.; Tolokonnikov, S. V.

2018-05-01

A method is presented to evaluate the particle-phonon coupling (PC) corrections to the single-particle energies in semimagic nuclei, based on the direct solution of the Dyson equation with PC-corrected mass operator. It is used for finding the odd-even mass difference between even Pb and Sn isotopes and their odd-proton neighbors. The Fayans energy density functional DF3-a is used, which gives rather highly accurate predictions for these mass differences already at the mean-field level. In the case of the lead chain, account for the PC corrections induced by the low-lying phonons 21+ and 31- makes agreement of the theory with the experimental data significantly better. For the tin chain, the situation is not so definite. In this case, the PC corrections make agreement better in the case of the addition mode but they spoil the agreement for the removal mode. We discuss the reason for such a discrepancy.

Agnotology: learning from mistakes

NASA Astrophysics Data System (ADS)

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

2013-05-01

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

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

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

Zhou, Z; Folkert, M; Wang, J

2016-06-15

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

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

ERIC Educational Resources Information Center

Jaeger, Martin; Adair, Desmond

2015-01-01

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

An Analysis of Categorical and Quantitative Methods for Planning Under Uncertainty

PubMed Central

Langlotz, Curtis P.; Shortliffe, Edward H.

1988-01-01

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

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

PubMed

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

2014-01-01

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

Distributed Deliberative Recommender Systems

NASA Astrophysics Data System (ADS)

Recio-García, Juan A.; Díaz-Agudo, Belén; González-Sanz, Sergio; Sanchez, Lara Quijano

Case-Based Reasoning (CBR) is one of most successful applied AI technologies of recent years. Although many CBR systems reason locally on a previous experience base to solve new problems, in this paper we focus on distributed retrieval processes working on a network of collaborating CBR systems. In such systems, each node in a network of CBR agents collaborates, arguments and counterarguments its local results with other nodes to improve the performance of the system's global response. We describe D2ISCO: a framework to design and implement deliberative and collaborative CBR systems that is integrated as a part of jcolibritwo an established framework in the CBR community. We apply D2ISCO to one particular simplified type of CBR systems: recommender systems. We perform a first case study for a collaborative music recommender system and present the results of an experiment of the accuracy of the system results using a fuzzy version of the argumentation system AMAL and a network topology based on a social network. Besides individual recommendation we also discuss how D2ISCO can be used to improve recommendations to groups and we present a second case of study based on the movie recommendation domain with heterogeneous groups according to the group personality composition and a group topology based on a social network.

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

PubMed Central

2011-01-01

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

Application of 3D Zernike descriptors to shape-based ligand similarity searching.

PubMed

Venkatraman, Vishwesh; Chakravarthy, Padmasini Ramji; Kihara, Daisuke

2009-12-17

The identification of promising drug leads from a large database of compounds is an important step in the preliminary stages of drug design. Although shape is known to play a key role in the molecular recognition process, its application to virtual screening poses significant hurdles both in terms of the encoding scheme and speed. In this study, we have examined the efficacy of the alignment independent three-dimensional Zernike descriptor (3DZD) for fast shape based similarity searching. Performance of this approach was compared with several other methods including the statistical moments based ultrafast shape recognition scheme (USR) and SIMCOMP, a graph matching algorithm that compares atom environments. Three benchmark datasets are used to thoroughly test the methods in terms of their ability for molecular classification, retrieval rate, and performance under the situation that simulates actual virtual screening tasks over a large pharmaceutical database. The 3DZD performed better than or comparable to the other methods examined, depending on the datasets and evaluation metrics used. Reasons for the success and the failure of the shape based methods for specific cases are investigated. Based on the results for the three datasets, general conclusions are drawn with regard to their efficiency and applicability. The 3DZD has unique ability for fast comparison of three-dimensional shape of compounds. Examples analyzed illustrate the advantages and the room for improvements for the 3DZD.

Application of 3D Zernike descriptors to shape-based ligand similarity searching

PubMed Central

2009-01-01

Background The identification of promising drug leads from a large database of compounds is an important step in the preliminary stages of drug design. Although shape is known to play a key role in the molecular recognition process, its application to virtual screening poses significant hurdles both in terms of the encoding scheme and speed. Results In this study, we have examined the efficacy of the alignment independent three-dimensional Zernike descriptor (3DZD) for fast shape based similarity searching. Performance of this approach was compared with several other methods including the statistical moments based ultrafast shape recognition scheme (USR) and SIMCOMP, a graph matching algorithm that compares atom environments. Three benchmark datasets are used to thoroughly test the methods in terms of their ability for molecular classification, retrieval rate, and performance under the situation that simulates actual virtual screening tasks over a large pharmaceutical database. The 3DZD performed better than or comparable to the other methods examined, depending on the datasets and evaluation metrics used. Reasons for the success and the failure of the shape based methods for specific cases are investigated. Based on the results for the three datasets, general conclusions are drawn with regard to their efficiency and applicability. Conclusion The 3DZD has unique ability for fast comparison of three-dimensional shape of compounds. Examples analyzed illustrate the advantages and the room for improvements for the 3DZD. PMID:20150998

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

PubMed

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

2008-08-26

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

[Therapeutic strategy for different types of epicanthus].

PubMed

Gaofeng, Li; Jun, Tan; Zihan, Wu; Wei, Ding; Huawei, Ouyang; Fan, Zhang; Mingcan, Luo

2015-11-01

To explore the reasonable therapeutic strategy for different types of epicanthus. Patients with epicanthus were classificated according to the shape, extent and inner canthal distance and treated with different methods appropriately. Modified asymmetric Z plasty with two curve method was used in lower eyelid type epicanthus, inner canthus type epicanthus and severe upper eyelid type epicanthus. Moderate upper epicanthus underwent '-' shape method. Mild Upper epicanthus in two conditions which underwent nasal augumentation and double eyelid formation with normal inner canthal distance need no correction surgery. The other mild epicanthus underwent '-' shape method. A total of 66 cases underwent the classification and the appropriate treatment. All wounds healed well. During 3 to 12 months follow-up period, all epicanthus were corrected completely with natural contour and unconspicuous scars. All patients were satisfied with the results. Classification of epicanthus hosed on the shape, extent and inner canthal distance and correction with appropriate methods is a reasonable therapeutic strategy.

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

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

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

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

Single-Case Analysis to Determine Reasons for Failure of Behavioral Treatment via Telehealth

ERIC Educational Resources Information Center

Schieltz, Kelly M.; Romani, Patrick W.; Wacker, David P.; Suess, Alyssa N.; Huang, Pei; Berg, Wendy K.; Lindgren, Scott D.; Kopelman, Todd G.

2018-01-01

Functional communication training (FCT) is a widely used and effective function-based treatment for problem behavior. The purpose of this article is to present two cases in which FCT was unsuccessful in reducing the occurrence of problem behavior displayed by two young children with an autism spectrum disorder. Both children received the same…

Learning to Think Spatially in an Undergraduate Interdisciplinary Computational Design Context: A Case Study

ERIC Educational Resources Information Center

Ben Youssef, Belgacem; Berry, Barbara

2012-01-01

Spatial thinking skills are vital for success in everyday living and work, not to mention the centrality of spatial reasoning in scientific discoveries, design-based disciplines, medicine, geosciences and mathematics to name a few. This case study describes a course in spatial thinking and communicating designed and delivered by an…

Adult Gesture in Collaborative Mathematics Reasoning in Different Ages

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

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

PubMed

Andersson, Nina; Klang, Birgitta; Petersson, Gunilla

2012-03-01

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

A Time-Space Domain Information Fusion Method for Specific Emitter Identification Based on Dempster-Shafer Evidence Theory.

PubMed

Jiang, Wen; Cao, Ying; Yang, Lin; He, Zichang

2017-08-28

Specific emitter identification plays an important role in contemporary military affairs. However, most of the existing specific emitter identification methods haven't taken into account the processing of uncertain information. Therefore, this paper proposes a time-space domain information fusion method based on Dempster-Shafer evidence theory, which has the ability to deal with uncertain information in the process of specific emitter identification. In this paper, radars will generate a group of evidence respectively based on the information they obtained, and our main task is to fuse the multiple groups of evidence to get a reasonable result. Within the framework of recursive centralized fusion model, the proposed method incorporates a correlation coefficient, which measures the relevance between evidence and a quantum mechanical approach, which is based on the parameters of radar itself. The simulation results of an illustrative example demonstrate that the proposed method can effectively deal with uncertain information and get a reasonable recognition result.

Increasing the Runtime Speed of Case-Based Plan Recognition

DTIC Science & Technology

2015-05-01

number of situations that the robot might reasonably be expected to encounter. This requires ef- ficient indexing schemes to ensure that plan retrieval...collection of information if it does not display a currently valid OMB control number . 1. REPORT DATE MAY 2015 2. REPORT TYPE 3. DATES COVERED 00...00-2015 to 00-00-2015 4. TITLE AND SUBTITLE Increasing the Runtime Speed of Case-Based Plan Recognition 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c

Retrieval of Understory NDVI in Sparse Boreal Forests By MODIS Brdf Data

NASA Astrophysics Data System (ADS)

Yang, W.; Kobayashi, H.; Suzuki, R.; Nasahara, K. N.

2014-12-01

Global products of leaf area index (LAI) usually show large uncertainties in sparsely vegetated areas. The reason is that the understory contribution is not negligible in reflectance modeling for the case of low to intermediate canopy cover. Therefore many efforts have been carried out on inclusion of understory properties in the LAI estimation algorithms. Compared with conventional data bank method, estimation of forest understory property from satellite data is superior in the studies at global or continental scale during a long periods. However, the existing remote sensing method based on multi-angular observations is very complicated to implement. Alternatively, a simple method to retrieve understory NDVI (NDVIu) for sparse boreal forests was proposed in this study. The method is based on the property that the bi-directional variation of NDVIu is much smaller than that of the canopy-level NDVI. To retrieve NDVIu for a certain pixel, linear extrapolation was applied using the pixels within a 5×5 target-pixel-centered window. The NDVI values were reconstructed from the MODIS BRDF data corresponding to eight different solar-view angles. NDVIu was estimated as the average of the NDVI values corresponding to the position where the stand NDVI has the smallest angular variation. Validation by noise-free simulation dataset yielded high agreement between estimated and true NDVIu with R2 and RMSE of 0.99 and 0.03, respectively. By the MODIS BRDF data, we got the estimate of NDVIu close to the in situ measured value (0.61 vs. 0.66 for estimate and measurement, respectively), and also reasonable seasonal patterns of NDVIu in 2010-2013. The results imply a potential application of the retrieved NDVIu to improve the estimation of overstory LAI for sparse boreal forests.

Ontology-Based Learner Categorization through Case Based Reasoning and Fuzzy Logic

ERIC Educational Resources Information Center

Sarwar, Sohail; García-Castro, Raul; Qayyum, Zia Ul; Safyan, Muhammad; Munir, Rana Faisal

2017-01-01

Learner categorization has a pivotal role in making e-learning systems a success. However, learner characteristics exploited at abstract level of granularity by contemporary techniques cannot categorize the learners effectively. In this paper, an architecture of e-learning framework has been presented that exploits the machine learning based…

Developing Metacognition: A Basis for Active Learning

ERIC Educational Resources Information Center

Vos, Henk; de Graaff, E.

2004-01-01

The reasons to introduce formats of active learning in engineering (ALE) such as project work, problem-based learning, use of cases, etc. are mostly based on practical experience, and sometimes from applied research on teaching and learning. Such research shows that students learn more and different abilities than in traditional formats of…

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

PubMed

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

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

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

PubMed

Tsopra, R; Venot, A; Duclos, C

2014-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Identification of Matra Region and Overlapping Characters for OCR of Printed Bengali Scripts

NASA Astrophysics Data System (ADS)

Goswami, Subhra Sundar

One of the important reasons for poor recognition rate in optical character recognition (OCR) system is the error in character segmentation. In case of Bangla scripts, the errors occur due to several reasons, which include incorrect detection of matra (headline), over-segmentation and under-segmentation. We have proposed a robust method for detecting the headline region. Existence of overlapping characters (in under-segmented parts) in scanned printed documents is a major problem in designing an effective character segmentation procedure for OCR systems. In this paper, a predictive algorithm is developed for effectively identifying overlapping characters and then selecting the cut-borders for segmentation. Our method can be successfully used in achieving high recognition result.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Incremental Query Rewriting with Resolution

NASA Astrophysics Data System (ADS)

Riazanov, Alexandre; Aragão, Marcelo A. T.

We address the problem of semantic querying of relational databases (RDB) modulo knowledge bases using very expressive knowledge representation formalisms, such as full first-order logic or its various fragments. We propose to use a resolution-based first-order logic (FOL) reasoner for computing schematic answers to deductive queries, with the subsequent translation of these schematic answers to SQL queries which are evaluated using a conventional relational DBMS. We call our method incremental query rewriting, because an original semantic query is rewritten into a (potentially infinite) series of SQL queries. In this chapter, we outline the main idea of our technique - using abstractions of databases and constrained clauses for deriving schematic answers, and provide completeness and soundness proofs to justify the applicability of this technique to the case of resolution for FOL without equality. The proposed method can be directly used with regular RDBs, including legacy databases. Moreover, we propose it as a potential basis for an efficient Web-scale semantic search technology.

Testing the domain-specificity of a theory of mind deficit in brain-injured patients: evidence for consistent performance on non-verbal, "reality-unknown" false belief and false photograph tasks.

PubMed

Apperly, Ian A; Samson, Dana; Chiavarino, Claudia; Bickerton, Wai-Ling; Humphreys, Glyn W

2007-05-01

To test the domain-specificity of "theory of mind" abilities we compared the performance of a case-series of 11 brain-lesioned patients on a recently developed test of false belief reasoning () and on a matched false photograph task, which did not require belief reasoning and which addressed problems with existing false photograph methods. A strikingly similar pattern of performance was shown across the false belief and false photograph tests. Patients who were selectively impaired on false belief tasks were also impaired on false photograph tasks; patients spared on false belief tasks also showed preserved performance with false photographs. In some cases the impairment on false belief and false photograph tasks coincided with good performance on control tasks matched for executive demands. We discuss whether the patients have a domain-specific deficit in reasoning about representations common to both false belief and false photograph tasks.

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

PubMed

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

2017-01-01

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

Reasons for discontinuation of reversible contraceptive methods by women with epilepsy.

PubMed

Mandle, Hannah B; Cahill, Kaitlyn E; Fowler, Kristen M; Hauser, W Allen; Davis, Anne R; Herzog, Andrew G

2017-05-01

To report the reasons for discontinuation of contraceptive methods by women with epilepsy (WWE). These retrospective data come from a web-based survey regarding the contraceptive practices of 1,144 WWE in the community, ages 18-47 years. We determined the frequencies of contraceptive discontinuations and the reasons for discontinuation. We compared risk ratios for rates of discontinuation among contraceptive methods and categories. We used chi-square analysis to test the independence of discontinuation reasons among the various contraceptive methods and categories and when stratified by antiepileptic drug (AED) categories. Nine hundred fifty-nine of 2,393 (40.6%) individual, reversible contraceptive methods were discontinued. One-half (51.8%) of the WWE who discontinued a method discontinued at least two methods. Hormonal contraception was discontinued most often (553/1,091, 50.7%) with a risk ratio of 1.94 (1.54-2.45, p < 0.0001) compared to intrauterine devices (IUDs), the category that was discontinued the least (57/227, 25.1%). Among all individual methods, the contraceptive patch was stopped most often (79.7%) and the progestin-IUD was stopped the least (20.1%). The top three reasons for discontinuation among all methods were reliability concerns (13.9%), menstrual problems (13.5%), and increased seizures (8.6%). There were significant differences among discontinuation rates and reasons when stratified by AED category for hormonal contraception but not for any other contraceptive category. Contraception counseling for WWE should consider the special experience profiles that are unique to this special population on systemic hormonal contraception. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

Argumentation and Equity in Inquiry-Based Science Instruction: Reasoning Patterns of Teachers and Students

NASA Astrophysics Data System (ADS)

Irish, Tobias E. L.

This multiple case study explores issues of equity in science education through an examination of how teachers' reasoning patterns compare with students' reasoning patterns during inquiry-based lessons. It also examines the ways in which teachers utilize students' cultural and linguistic resources, or funds of knowledge, during inquiry-based lessons and the ways in which students utilize their funds of knowledge, during inquiry-based lessons. Three middle school teachers and a total of 57 middle school students participated in this study. The data collection involved classroom observations and multiple interviews with each of the teachers individually and with small groups of students. The findings indicate that the students are capable of far more complex reasoning than what was elicited by the lessons observed or what was modeled and expected by the teachers, but that during the inquiry-based lessons they conformed to the more simplistic reasoning patterns they perceived as the expected norm of classroom dialogue. The findings also indicate that the students possess funds of knowledge that are relevant to science topics, but very seldom use these funds in the context of their inquiry-based lessons. In addition, the teachers in this study very seldom worked to elicit students' use of their funds in these contexts. The few attempts they did make involved the use of analogies, examples, or questions. The findings from this study have implications for both teachers and teacher educators in that they highlight similarities and differences in reasoning that can help teachers establish instructional congruence and facilitate more equitable science instruction. They also provide insight into how students' cultural and linguistic resources are utilized during inquiry-based science lessons.

Method for detecting moment connection fracture using high-frequency transients in recorded accelerations

USGS Publications Warehouse

Rodgers, J.E.; Elebi, M.

2011-01-01

The 1994 Northridge earthquake caused brittle fractures in steel moment frame building connections, despite causing little visible building damage in most cases. Future strong earthquakes are likely to cause similar damage to the many un-retrofitted pre-Northridge buildings in the western US and elsewhere. Without obvious permanent building deformation, costly intrusive inspections are currently the only way to determine if major fracture damage that compromises building safety has occurred. Building instrumentation has the potential to provide engineers and owners with timely information on fracture occurrence. Structural dynamics theory predicts and scale model experiments have demonstrated that sudden, large changes in structure properties caused by moment connection fractures will cause transient dynamic response. A method is proposed for detecting the building-wide level of connection fracture damage, based on observing high-frequency, fracture-induced transient dynamic responses in strong motion accelerograms. High-frequency transients are short (<1 s), sudden-onset waveforms with frequency content above 25 Hz that are visually apparent in recorded accelerations. Strong motion data and damage information from intrusive inspections collected from 24 sparsely instrumented buildings following the 1994 Northridge earthquake are used to evaluate the proposed method. The method's overall success rate for this data set is 67%, but this rate varies significantly with damage level. The method performs reasonably well in detecting significant fracture damage and in identifying cases with no damage, but fails in cases with few fractures. Combining the method with other damage indicators and removing records with excessive noise improves the ability to detect the level of damage. ?? 2010 Elsevier B.V. All rights reserved.

Determination of confidence limits for experiments with low numbers of counts. [Poisson-distributed photon counts from astrophysical sources

NASA Technical Reports Server (NTRS)

Kraft, Ralph P.; Burrows, David N.; Nousek, John A.

1991-01-01

Two different methods, classical and Bayesian, for determining confidence intervals involving Poisson-distributed data are compared. Particular consideration is given to cases where the number of counts observed is small and is comparable to the mean number of background counts. Reasons for preferring the Bayesian over the classical method are given. Tables of confidence limits calculated by the Bayesian method are provided for quick reference.

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

PubMed

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

2017-09-13

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

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

PubMed Central

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

2017-01-01

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

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.

Identification of magnetic anomalies based on ground magnetic data analysis using multifractal modeling: a case study in Qoja-Kandi, East Azerbaijan Province, Iran

NASA Astrophysics Data System (ADS)

Mansouri, E.; Feizi, F.; Karbalaei Ramezanali, A. A.

2015-07-01

Ground magnetic anomaly separation using reduction-to-the-pole (RTP) technique and the fractal concentration-area (C-A) method has been applied to the Qoja-Kandi prosepecting area in NW Iran. The geophysical survey that resulted in the ground magnetic data was conducted for magnetic elements exploration. Firstly, RTP technique was applied for recognizing underground magnetic anomalies. RTP anomalies was classified to different populations based on this method. For this reason, drilling points determination with RTP technique was complicated. Next, C-A method was applied on the RTP-Magnetic-Anomalies (RTP-MA) for demonstrating magnetic susceptibility concentration. This identification was appropriate for increasing the resolution of the drilling points determination and decreasing the drilling risk, due to the economic costs of underground prospecting. In this study, the results of C-A Modeling on the RTP-MA are compared with 8 borehole data. The results show there is good correlation between anomalies derived via C-A method and log report of boreholes. Two boreholes were drilled in magnetic susceptibility concentration, based on multifractal modeling data analyses, between 63 533.1 and 66 296 nT. Drilling results show appropriate magnetite thickness with the grades greater than 20 % Fe total. Also, anomalies associated with andesite units host iron mineralization.

Towards a Semantic Web of Things: A Hybrid Semantic Annotation, Extraction, and Reasoning Framework for Cyber-Physical System.

PubMed

Wu, Zhenyu; Xu, Yuan; Yang, Yunong; Zhang, Chunhong; Zhu, Xinning; Ji, Yang

2017-02-20

Web of Things (WoT) facilitates the discovery and interoperability of Internet of Things (IoT) devices in a cyber-physical system (CPS). Moreover, a uniform knowledge representation of physical resources is quite necessary for further composition, collaboration, and decision-making process in CPS. Though several efforts have integrated semantics with WoT, such as knowledge engineering methods based on semantic sensor networks (SSN), it still could not represent the complex relationships between devices when dynamic composition and collaboration occur, and it totally depends on manual construction of a knowledge base with low scalability. In this paper, to addresses these limitations, we propose the semantic Web of Things (SWoT) framework for CPS (SWoT4CPS). SWoT4CPS provides a hybrid solution with both ontological engineering methods by extending SSN and machine learning methods based on an entity linking (EL) model. To testify to the feasibility and performance, we demonstrate the framework by implementing a temperature anomaly diagnosis and automatic control use case in a building automation system. Evaluation results on the EL method show that linking domain knowledge to DBpedia has a relative high accuracy and the time complexity is at a tolerant level. Advantages and disadvantages of SWoT4CPS with future work are also discussed.

Ethical case deliberation on the ward. A comparison of four methods.

PubMed

Steinkamp, Norbert; Gordijn, Bert

2003-01-01

The objective of this article is to analyse and compare four methods of ethical case deliberation. These include Clinical Pragmatism, The Nijmegen Method of ethical case deliberation, Hermeneutic dialogue, and Socratic dialogue. The origin of each method will be briefly sketched. Furthermore, the methods as well as the related protocols will be presented. Each method will then be evaluated against the background of those situations in which it is being used. The article aims to show that there is not one ideal method of ethical case deliberation, which fits to all possible kinds of moral problems. Rather, as each of the methods highlights a limited number of morally relevant aspects, each method has its strengths and weaknesses as well. These strengths and weaknesses should be evaluated in relation to different types of situations, for instance moral problems in treatment decisions, moral uneasiness and residue, and the like. The suggestion arrived at on the basis of the findings of this paper is a reasonable methodological plurality. This means that a method can be chosen depending on the type of moral problem to be deliberated upon. At the same time it means, that by means of a method, deliberation should be facilitated.

Structural modal parameter identification using local mean decomposition

NASA Astrophysics Data System (ADS)

Keyhani, Ali; Mohammadi, Saeed

2018-02-01

Modal parameter identification is the first step in structural health monitoring of existing structures. Already, many powerful methods have been proposed for this concept and each method has some benefits and shortcomings. In this study, a new method based on local mean decomposition is proposed for modal identification of civil structures from free or ambient vibration measurements. The ability of the proposed method was investigated using some numerical studies and the results compared with those obtained from the Hilbert-Huang transform (HHT). As a major advantage, the proposed method can extract natural frequencies and damping ratios of all active modes from only one measurement. The accuracy of the identified modes depends on their participation in the measured responses. Nevertheless, the identified natural frequencies have reasonable accuracy in both cases of free and ambient vibration measurements, even in the presence of noise. The instantaneous phase angle and the natural logarithm of instantaneous amplitude curves obtained from the proposed method have more linearity rather than those from the HHT algorithm. Also, the end effect is more restricted for the proposed method.

Analysis Balance Parameter of Optimal Ramp metering

NASA Astrophysics Data System (ADS)

Li, Y.; Duan, N.; Yang, X.

2018-05-01

Ramp metering is a motorway control method to avoid onset congestion through limiting the access of ramp inflows into the main road of the motorway. The optimization model of ramp metering is developed based upon cell transmission model (CTM). With the piecewise linear structure of CTM, the corresponding motorway traffic optimization problem can be formulated as a linear programming (LP) problem. It is known that LP problem can be solved by established solution algorithms such as SIMPLEX or interior-point methods for the global optimal solution. The commercial software (CPLEX) is adopted in this study to solve the LP problem within reasonable computational time. The concept is illustrated through a case study of the United Kingdom M25 Motorway. The optimal solution provides useful insights and guidances on how to manage motorway traffic in order to maximize the corresponding efficiency.

Research on driver fatigue detection

NASA Astrophysics Data System (ADS)

Zhang, Ting; Chen, Zhong; Ouyang, Chao

2018-03-01

Driver fatigue is one of the main causes of frequent traffic accidents. In this case, driver fatigue detection system has very important significance in avoiding traffic accidents. This paper presents a real-time method based on fusion of multiple facial features, including eye closure, yawn and head movement. The eye state is classified as being open or closed by a linear SVM classifier trained using HOG features of the detected eye. The mouth state is determined according to the width-height ratio of the mouth. The head movement is detected by head pitch angle calculated by facial landmark. The driver's fatigue state can be reasoned by the model trained by above features. According to experimental results, drive fatigue detection obtains an excellent performance. It indicates that the developed method is valuable for the application of avoiding traffic accidents caused by driver's fatigue.

Reengineering through natural structures: the fractal factory

NASA Astrophysics Data System (ADS)

Sihn, Wilfried

1995-08-01

Many branches of European industry have had to recognize that their lead in the world market has been caught up with, particularly through Asian competition. In many cases a deficit of up to 30% in costs and productivity already exists. The reasons are rigid, Tayloristic company structures. The companies are not in a position to react flexibly to constantly changing environmental conditions. This article illustrates the methods of the `fractal company' which are necessary to solve the structure crisis. The fractal company distinguishes itself through its dynamics and its vitality, as well as its independent reaction to the changing circumstances. The developed methods, procedures, and framework conditions such as company structuring, human networking, hierarchy formation, and models for renumeration and working time are explained. They are based on practical examples from IPA's work with the automobile industry, their suppliers, and the engineering industry.