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.

Intelligent design of permanent magnet synchronous motor based on CBR

NASA Astrophysics Data System (ADS)

Li, Cong; Fan, Beibei

2018-05-01

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

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.

The application of hybrid artificial intelligence systems for forecasting

NASA Astrophysics Data System (ADS)

Lees, Brian; Corchado, Juan

1999-03-01

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

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.

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.

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.

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

Rough case-based reasoning system for continues casting

NASA Astrophysics Data System (ADS)

Su, Wenbin; Lei, Zhufeng

2018-04-01

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

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.

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.

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.

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.

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

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.

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…

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.

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.

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.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

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

PubMed

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

2016-06-01

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

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.

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…

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.

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.

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.

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.

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.

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.

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

Case-based reasoning in design: An apologia

NASA Technical Reports Server (NTRS)

Pulaski, Kirt

1990-01-01

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

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.

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.

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.

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

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.

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.

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.

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.

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…

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.

Improving real-time efficiency of case-based reasoning for medical diagnosis.

PubMed

Park, Yoon-Joo

2014-01-01

Conventional case-based reasoning (CBR) does not perform efficiently for high volume dataset because of case-retrieval time. Some previous researches overcome this problem by clustering a case-base into several small groups, and retrieve neighbors within a corresponding group to a target case. However, this approach generally produces less accurate predictive performances than the conventional CBR. This paper suggests a new case-based reasoning method called the Clustering-Merging CBR (CM-CBR) which produces similar level of predictive performances than the conventional CBR with spending significantly less computational cost.

Decision Support System for Medical Care Quality Assessment Based on Health Records Analysis in Russia.

PubMed

Taranik, Maksim; Kopanitsa, Georgy

2017-01-01

The paper presents developed decision system, oriented for healthcare providers. The system allows healthcare providers to detect and decrease nonconformities in health records and forecast the sum of insurance payments taking into account nonconformities. The components are ISO13606, fuzzy logic and case-based reasoning concept. The result of system implementation allowed to 10% increase insurance payments for healthcare provider.

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

PubMed

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

2015-01-01

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

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…

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.

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

NASA Technical Reports Server (NTRS)

Sary, Charisse

1994-01-01

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

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.

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.

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.

Explanation-aware computing of the prognosis for breast cancer supported by IK-DCBRC: Technical innovation.

PubMed

Khelassi, Abdeldjalil

2014-01-01

Active research is being conducted to determine the prognosis for breast cancer. However, the uncertainty is a major obstacle in this domain of medical research. In that context, explanation-aware computing has the potential for providing meaningful interactions between complex medical applications and users, which would ensure a significant reduction of uncertainty and risks. This paper presents an explanation-aware agent, supported by Intensive Knowledge-Distributed Case-Based Reasoning Classifier (IK-DCBRC), to reduce the uncertainty and risks associated with the diagnosis of breast cancer. A meaningful explanation is generated by inferring from a rule-based system according to the level of abstraction and the reasoning traces. The computer-aided detection is conducted by IK-DCBRC, which is a multi-agent system that applies the case-based reasoning paradigm and a fuzzy similarity function for the automatic prognosis by the class of breast tumors, i.e. malignant or benign, from a pattern of cytological images. A meaningful interaction between the physician and the computer-aided diagnosis system, IK-DCBRC, is achieved via an intelligent agent. The physician can observe the trace of reasoning, terms, justifications, and the strategy to be used to decrease the risks and doubts associated with the automatic diagnosis. The capability of the system we have developed was proven by an example in which conflicts were clarified and transparency was ensured. The explanation agent ensures the transparency of the automatic diagnosis of breast cancer supported by IK-DCBRC, which decreases uncertainty and risks and detects some conflicts.

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

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…

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.

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.

Massively parallel support for a case-based planning system

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

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.

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…

Hybrid Architectures and Their Impact on Intelligent Design

NASA Technical Reports Server (NTRS)

Kandel, Abe

1996-01-01

In this presentation we investigate a novel framework for the design of autonomous fuzzy intelligent systems. The system integrates the following modules into a single autonomous entity: (1) a fuzzy expert system; (2) artificial neural network; (3) genetic algorithm; and (4) case-base reasoning. We describe the integration of these units into one intelligent structure and discuss potential applications.

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.

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.

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

PubMed

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

2016-04-01

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

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.

Using Case-Based Reasoning to Improve the Quality of Feedback Provided by Automated Grading Systems

ERIC Educational Resources Information Center

Kyrilov, Angelo; Noelle, David C.

2014-01-01

Information technology is now ubiquitous in higher education institutions worldwide. More than 85% of American universities use e-learning systems to supplement traditional classroom activities while some have started offering Massive Online Open Courses (MOOCs), which are completely online. An obvious benefit of these online tools is their…

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.

A hybrid intelligence approach to artifact recognition in digital publishing

NASA Astrophysics Data System (ADS)

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

2006-02-01

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

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…

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.

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

DOT National Transportation Integrated Search

1998-01-01

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

Hybrid approach for robust diagnostics of cutting tools

NASA Astrophysics Data System (ADS)

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

1994-03-01

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

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

PubMed

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

2013-05-07

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

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.

A Case-Based Reasoning Method with Rank Aggregation

NASA Astrophysics Data System (ADS)

Sun, Jinhua; Du, Jiao; Hu, Jian

2018-03-01

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

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.

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.

Case Study: Lackland Air Force Base Commissary

EPA Pesticide Factsheets

DeCA chose to adopt a NH3/CO2 cascade system for two main reasons: (1) to control future capital and operating costs, and (2) to meet the energy and sustainability goals the U.S. Government has established for all public buildings.

Using Case-Based Reasoning to Improve the Quality of Feedback Provided by Automated Assessment Systems for Programming Exercises

ERIC Educational Resources Information Center

Kyrilov, Angelo

2017-01-01

Information technology is now ubiquitous in higher education institutions worldwide. More than 85% of American universities use e-learning systems to supplement traditional classroom activities. An obvious benefit of these online tools is their ability to automatically grade exercises submitted by students and provide immediate feedback. Most of…

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.

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

PubMed

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

2017-09-11

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

Case-based medical informatics

PubMed Central

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

2004-01-01

Background The "applied" nature distinguishes applied sciences from theoretical sciences. To emphasize this distinction, we begin with a general, meta-level overview of the scientific endeavor. We introduce the knowledge spectrum and four interconnected modalities of knowledge. In addition to the traditional differentiation between implicit and explicit knowledge we outline the concepts of general and individual knowledge. We connect general knowledge with the "frame problem," a fundamental issue of artificial intelligence, and individual knowledge with another important paradigm of artificial intelligence, case-based reasoning, a method of individual knowledge processing that aims at solving new problems based on the solutions to similar past problems. We outline the fundamental differences between Medical Informatics and theoretical sciences and propose that Medical Informatics research should advance individual knowledge processing (case-based reasoning) and that natural language processing research is an important step towards this goal that may have ethical implications for patient-centered health medicine. Discussion We focus on fundamental aspects of decision-making, which connect human expertise with individual knowledge processing. We continue with a knowledge spectrum perspective on biomedical knowledge and conclude that case-based reasoning is the paradigm that can advance towards personalized healthcare and that can enable the education of patients and providers. We center the discussion on formal methods of knowledge representation around the frame problem. We propose a context-dependent view on the notion of "meaning" and advocate the need for case-based reasoning research and natural language processing. In the context of memory based knowledge processing, pattern recognition, comparison and analogy-making, we conclude that while humans seem to naturally support the case-based reasoning paradigm (memory of past experiences of problem-solving and powerful case matching mechanisms), technical solutions are challenging. Finally, we discuss the major challenges for a technical solution: case record comprehensiveness, organization of information on similarity principles, development of pattern recognition and solving ethical issues. Summary Medical Informatics is an applied science that should be committed to advancing patient-centered medicine through individual knowledge processing. Case-based reasoning is the technical solution that enables a continuous individual knowledge processing and could be applied providing that challenges and ethical issues arising are addressed appropriately. PMID:15533257

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

PubMed

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

2015-06-01

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

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.

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.

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

ERIC Educational Resources Information Center

Cevik, Yasemin Demiraslan; Andre, Thomas

2012-01-01

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

Neighborhood graph and learning discriminative distance functions for clinical decision support.

PubMed

Tsymbal, Alexey; Zhou, Shaohua Kevin; Huber, Martin

2009-01-01

There are two essential reasons for the slow progress in the acceptance of clinical case retrieval and similarity search-based decision support systems; the especial complexity of clinical data making it difficult to define a meaningful and effective distance function on them and the lack of transparency and explanation ability in many existing clinical case retrieval decision support systems. In this paper, we try to address these two problems by introducing a novel technique for visualizing inter-patient similarity based on a node-link representation with neighborhood graphs and by considering two techniques for learning discriminative distance function that help to combine the power of strong "black box" learners with the transparency of case retrieval and nearest neighbor classification.

A Computational Model of Reasoning from the Clinical Literature

PubMed Central

Rennels, Glenn D.

1986-01-01

This paper explores the premise that a formalized representation of empirical studies can play a central role in computer-based decision support. The specific motivations underlying this research include the following propositions: 1. Reasoning from experimental evidence contained in the clinical literature is central to the decisions physicians make in patient care. 2. A computational model, based upon a declarative representation for published reports of clinical studies, can drive a computer program that selectively tailors knowledge of the clinical literature as it is applied to a particular case. 3. The development of such a computational model is an important first step toward filling a void in computer-based decision support systems. Furthermore, the model may help us better understand the general principles of reasoning from experimental evidence both in medicine and other domains. Roundsman is a developmental computer system which draws upon structured representations of the clinical literature in order to critique plans for the management of primary breast cancer. Roundsman is able to produce patient-specific analyses of breast cancer management options based on the 24 clinical studies currently encoded in its knowledge base. The Roundsman system is a first step in exploring how the computer can help to bring a critical analysis of the relevant literature to the physician, structured around a particular patient and treatment decision.

Short-term solar flare prediction using image-case-based reasoning

NASA Astrophysics Data System (ADS)

Liu, Jin-Fu; Li, Fei; Zhang, Huai-Peng; Yu, Da-Ren

2017-10-01

Solar flares strongly influence space weather and human activities, and their prediction is highly complex. The existing solutions such as data based approaches and model based approaches have a common shortcoming which is the lack of human engagement in the forecasting process. An image-case-based reasoning method is introduced to achieve this goal. The image case library is composed of SOHO/MDI longitudinal magnetograms, the images from which exhibit the maximum horizontal gradient, the length of the neutral line and the number of singular points that are extracted for retrieving similar image cases. Genetic optimization algorithms are employed for optimizing the weight assignment for image features and the number of similar image cases retrieved. Similar image cases and prediction results derived by majority voting for these similar image cases are output and shown to the forecaster in order to integrate his/her experience with the final prediction results. Experimental results demonstrate that the case-based reasoning approach has slightly better performance than other methods, and is more efficient with forecasts improved by humans.

Reasoning with Incomplete and Uncertain Information

DTIC Science & Technology

1991-08-01

are rationally compatible (just as is the case in the fundamental computational mechanisms of truth maintenance systems ). The logics we construct will...complete, pre- cise, and unvarying. This fundamental assumption is a principal source of the limitation of many diagnostic systems to single fault diagnoses...Air Force Systems Command Griffiss Air Force Base, NY 13441-5700 This report has been reviewed by the Rome Laboratory Public Affairs Dffice (PA) and

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.

Application of artifical intelligence principles to the analysis of "crazy" speech.

PubMed

Garfield, D A; Rapp, C

1994-04-01

Artificial intelligence computer simulation methods can be used to investigate psychotic or "crazy" speech. Here, symbolic reasoning algorithms establish semantic networks that schematize speech. These semantic networks consist of two main structures: case frames and object taxonomies. Node-based reasoning rules apply to object taxonomies and pathway-based reasoning rules apply to case frames. Normal listeners may recognize speech as "crazy talk" based on violations of node- and pathway-based reasoning rules. In this article, three separate segments of schizophrenic speech illustrate violations of these rules. This artificial intelligence approach is compared and contrasted with other neurolinguistic approaches and is discussed as a conceptual link between neurobiological and psychodynamic understandings of psychopathology.

Multimodal hybrid reasoning methodology for personalized wellbeing services.

PubMed

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

2016-02-01

A wellness system provides wellbeing recommendations to support experts in promoting a healthier lifestyle and inducing individuals to adopt healthy habits. Adopting physical activity effectively promotes a healthier lifestyle. A physical activity recommendation system assists users to adopt daily routines to form a best practice of life by involving themselves in healthy physical activities. Traditional physical activity recommendation systems focus on general recommendations applicable to a community of users rather than specific individuals. These recommendations are general in nature and are fit for the community at a certain level, but they are not relevant to every individual based on specific requirements and personal interests. To cover this aspect, we propose a multimodal hybrid reasoning methodology (HRM) that generates personalized physical activity recommendations according to the user׳s specific needs and personal interests. The methodology integrates the rule-based reasoning (RBR), case-based reasoning (CBR), and preference-based reasoning (PBR) approaches in a linear combination that enables personalization of recommendations. RBR uses explicit knowledge rules from physical activity guidelines, CBR uses implicit knowledge from experts׳ past experiences, and PBR uses users׳ personal interests and preferences. To validate the methodology, a weight management scenario is considered and experimented with. The RBR part of the methodology generates goal, weight status, and plan recommendations, the CBR part suggests the top three relevant physical activities for executing the recommended plan, and the PBR part filters out irrelevant recommendations from the suggested ones using the user׳s personal preferences and interests. To evaluate the methodology, a baseline-RBR system is developed, which is improved first using ranged rules and ultimately using a hybrid-CBR. A comparison of the results of these systems shows that hybrid-CBR outperforms the modified-RBR and baseline-RBR systems. Hybrid-CBR yields a 0.94% recall, a 0.97% precision, a 0.95% f-score, and low Type I and Type II errors. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

PubMed

Khan, Abdus Salam; Hoffmann, Achim

2003-02-01

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

Optimized model tuning in medical systems.

PubMed

Kléma, Jirí; Kubalík, Jirí; Lhotská, Lenka

2005-12-01

In medical systems it is often advantageous to utilize specific problem situations (cases) in addition to or instead of a general model. Decisions are then based on relevant past cases retrieved from a case memory. The reliability of such decisions depends directly on the ability to identify cases of practical relevance to the current situation. This paper discusses issues of automated tuning in order to obtain a proper definition of mutual case similarity in a specific medical domain. The main focus is on a reasonably time-consuming optimization of the parameters that determine case retrieval and further utilization in decision making/ prediction. The two case studies - mortality prediction after cardiological intervention, and resource allocation at a spa - document that the optimization process is influenced by various characteristics of the problem domain.

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)…

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.

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

NASA Technical Reports Server (NTRS)

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

1988-01-01

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

Elective surgical case cancellation in the Veterans Health Administration system: identifying areas for improvement.

PubMed

Argo, Joshua L; Vick, Catherine C; Graham, Laura A; Itani, Kamal M F; Bishop, Michael J; Hawn, Mary T

2009-11-01

This study evaluated elective surgical case cancellation (CC) rates, reasons for these cancellations, and identified areas for improvement within the Veterans Health Administration (VA) system. CC data for 2006 were collected from the scheduling software for 123 VA facilities. Surveys were distributed to 40 facilities (10 highest and 10 lowest CC rates for high- and low-volume facilities). CC reasons were standardized and piloted at 5 facilities. Of 329,784 cases scheduled by 9 surgical specialties, 40,988 (12.4%) were cancelled. CC reasons (9,528) were placed into 6 broad categories: patient (35%), work-up/medical condition change (28%), facility (20%), surgeon (8%), anesthesia (1%), and miscellaneous (8%). Survey results show areas for improvement at the facility level and a standardized list of 28 CC reasons was comprehensive. Interventions that decrease cancellations caused by patient factors, inadequate work-up, and facility factors are needed to reduce overall elective surgical case cancellations.

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.

Machine Learning-based Intelligent Formal Reasoning and Proving System

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

The use of computer-assisted orthopedic surgery for total knee replacement in daily practice: a survey among ESSKA/SGO-SSO members.

PubMed

Friederich, N; Verdonk, R

2008-06-01

Computer-assisted orthopedic surgery (CAOS) for total knee arthroplasty is an emerging surgical tool, yet little is known about how it is being used in everyday orthopedic centers. We sought to better understand physicians' current practices and beliefs on this topic through performing a Web-based survey. Between December 2006 and January 2007, a 24-question survey was emailed to 3,330 members of the European Society of Sports Traumatology Knee Surgery and Arthroscopy (ESSKA) and the Swiss Orthopedic Society (SGO-SSO), with 389 (11.7%) agreeing to participate. Of this group, 202 (51.9%) reported that their center was equipped with a navigation system, which was an image-free based system for most (83.2%) and was primarily used for total knee arthroplasty (61.4%). In terms of the proportion of use, 50.5% of respondents used their navigation system in less than 25% of cases, 16.3% in 25-50% of cases, 7.4% in 51-75% of cases, and 25.7% in more than 75% of cases. The potential for improving the alignment of prosthesis was the most strongly cited reason for using a navigation system, while the potential for increasing operation times and the risk of infections were the most strongly cited reasons for not using a navigation system. Approximately half of respondents surveyed believed navigation systems were a real innovation contributing to the improvement of total knee implantation. However, heavy usage of computer-assisted navigation (> or =51% of cases) was observed in only 33.1% of respondents, with only a quarter using it at rates that could be considered frequent (>75% of cases). Forty-eight percent of respondents said they will use a navigation system in more cases and 39.1% that their usage will stay the same. These findings indicate that CAOS is being used only moderately in current practices, though respondents generally had a positive opinion of its potential benefits. Physicians may be awaiting more data before adopting the use of these systems, though survey responses also suggest a projected increase in their use in the coming years.

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.

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

ERIC Educational Resources Information Center

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

2014-01-01

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

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

NASA Astrophysics Data System (ADS)

Sandhu, Rajinder; Kaur, Jaspreet; Thapar, Vivek

2018-02-01

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

An architecture for object-oriented intelligent control of power systems in space

NASA Technical Reports Server (NTRS)

Holmquist, Sven G.; Jayaram, Prakash; Jansen, Ben H.

1993-01-01

A control system for autonomous distribution and control of electrical power during space missions is being developed. This system should free the astronauts from localizing faults and reconfiguring loads if problems with the power distribution and generation components occur. The control system uses an object-oriented simulation model of the power system and first principle knowledge to detect, identify, and isolate faults. Each power system component is represented as a separate object with knowledge of its normal behavior. The reasoning process takes place at three different levels of abstraction: the Physical Component Model (PCM) level, the Electrical Equivalent Model (EEM) level, and the Functional System Model (FSM) level, with the PCM the lowest level of abstraction and the FSM the highest. At the EEM level the power system components are reasoned about as their electrical equivalents, e.g, a resistive load is thought of as a resistor. However, at the PCM level detailed knowledge about the component's specific characteristics is taken into account. The FSM level models the system at the subsystem level, a level appropriate for reconfiguration and scheduling. The control system operates in two modes, a reactive and a proactive mode, simultaneously. In the reactive mode the control system receives measurement data from the power system and compares these values with values determined through simulation to detect the existence of a fault. The nature of the fault is then identified through a model-based reasoning process using mainly the EEM. Compound component models are constructed at the EEM level and used in the fault identification process. In the proactive mode the reasoning takes place at the PCM level. Individual components determine their future health status using a physical model and measured historical data. In case changes in the health status seem imminent the component warns the control system about its impending failure. The fault isolation process uses the FSM level for its reasoning base.

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.

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

Bird, Lori; Cochran, Jaquelin; Wang, Xi

This report examines U.S. curtailment practices, with a particular emphasis on utilities in the Western states. The information presented here is based on a series of interviews conducted with utilities, system operators, wind energy developers, and non-governmental organizations. The report provides case studies of curtailment experience and examines the reasons for curtailment, curtailment procedures, compensation, and practices that can minimize curtailment.

An Automated Approach to Reasoning Under Multiple Perspectives

NASA Technical Reports Server (NTRS)

deBessonet, Cary

2004-01-01

This is the final report with emphasis on research during the last term. The context for the research has been the development of an automated reasoning technology for use in SMS (symbolic Manipulation System), a system used to build and query knowledge bases (KBs) using a special knowledge representation language SL (Symbolic Language). SMS interpreters assertive SL input and enters the results as components of its universe. The system operates in two basic models: 1) constructive mode (for building KBs); and 2) query/search mode (for querying KBs). Query satisfaction consists of matching query components with KB components. The system allows "penumbral matches," that is, matches that do not exactly meet the specifications of the query, but which are deemed relevant for the conversational context. If the user wants to know whether SMS has information that holds, say, for "any chow," the scope of relevancy might be set so that the system would respond based on a finding that it has information that holds for "most dogs," although this is not exactly what was called for by the query. The response would be qualified accordingly, as would normally be the case in ordinary human conversation. The general goal of the research was to develop an approach by which assertive content could be interpreted from multiple perspectives so that reasoning operations could be successfully conducted over the results. The interpretation of an SL statement such as, "{person believes [captain (asserted (perhaps)) (astronaut saw (comet (bright)))]}," which in English would amount to asserting something to the effect that, "Some person believes that a captain perhaps asserted that an astronaut saw a bright comet," would require the recognition of multiple perspectives, including some that are: a) epistemically-based (focusing on "believes"); b) assertion-based (focusing on "asserted"); c) perception-based (focusing on "saw"); d) adjectivally-based (focusing on "bight"); and e) modally-based (focusing on "perhaps"). Any conclusion reached under a line of reasoning that employs such an assertion or its associated implications should somehow reflect the employed perspectives. The investigators made significant progress in developing an approach that would enable a system to conduct reasoning operations over assertions of this kind while maintaining consistency in its knowledge bases. Significant accomplishments were made in the areas of: 1) integration and inferencing; 2) generation of perspectives, including wholistic ad composite views; and 3) consistency maintenance.

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

PubMed

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

2018-01-01

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

Framework for the mapping of the monthly average daily solar radiation using an advanced case-based reasoning and a geostatistical technique.

PubMed

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

2014-04-15

For the effective photovoltaic (PV) system, it is necessary to accurately determine the monthly average daily solar radiation (MADSR) and to develop an accurate MADSR map, which can simplify the decision-making process for selecting the suitable location of the PV system installation. Therefore, this study aimed to develop a framework for the mapping of the MADSR using an advanced case-based reasoning (CBR) and a geostatistical technique. The proposed framework consists of the following procedures: (i) the geographic scope for the mapping of the MADSR is set, and the measured MADSR and meteorological data in the geographic scope are collected; (ii) using the collected data, the advanced CBR model is developed; (iii) using the advanced CBR model, the MADSR at unmeasured locations is estimated; and (iv) by applying the measured and estimated MADSR data to the geographic information system, the MADSR map is developed. A practical validation was conducted by applying the proposed framework to South Korea. It was determined that the MADSR map developed through the proposed framework has been improved in terms of accuracy. The developed MADSR map can be used for estimating the MADSR at unmeasured locations and for determining the optimal location for the PV system installation.

Dynamic reasoning in a knowledge-based system

NASA Technical Reports Server (NTRS)

Rao, Anand S.; Foo, Norman Y.

1988-01-01

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

Expert system shell to reason on large amounts of data

NASA Technical Reports Server (NTRS)

Giuffrida, Gionanni

1994-01-01

The current data base management systems (DBMS's) do not provide a sophisticated environment to develop rule based expert systems applications. Some of the new DBMS's come with some sort of rule mechanism; these are active and deductive database systems. However, both of these are not featured enough to support full implementation based on rules. On the other hand, current expert system shells do not provide any link with external databases. That is, all the data are kept in the system working memory. Such working memory is maintained in main memory. For some applications the reduced size of the available working memory could represent a constraint for the development. Typically these are applications which require reasoning on huge amounts of data. All these data do not fit into the computer main memory. Moreover, in some cases these data can be already available in some database systems and continuously updated while the expert system is running. This paper proposes an architecture which employs knowledge discovering techniques to reduce the amount of data to be stored in the main memory; in this architecture a standard DBMS is coupled with a rule-based language. The data are stored into the DBMS. An interface between the two systems is responsible for inducing knowledge from the set of relations. Such induced knowledge is then transferred to the rule-based language working memory.

[Digoxin as a cause of chromatopsia and depression in a patient with heart failure and hyperthyroidism].

PubMed

Chyrek, R; Jabłecka, A; Pupek-Musialik, D; Lowicki, Z

2000-08-01

67 year old patient with chronic heart failure and persistent atrial fibrillation had overdosed glycosides for several months. The symptoms of gastrointestinal system and nervous system appeared after long term therapy with toxic doses of glycosides. Originally depression was diagnosed based on the central nervous system disturbances. Even though overdose of glycosides was diagnosed the blood serum glycoside level was within the therapeutic limits. Based on the precise analysis of the data, it was concluded that the reason for normal blood serum glycoside level in this case was coexisting hyperthyreosis.

Model of critical diagnostic reasoning: achieving expert clinician performance.

PubMed

Harjai, Prashant Kumar; Tiwari, Ruby

2009-01-01

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

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

ERIC Educational Resources Information Center

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

2012-01-01

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

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.

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.

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.

Economic costs of recorded reasons for cow mortality and culling in a pasture-based dairy industry.

PubMed

Kerslake, J I; Amer, P R; O'Neill, P L; Wong, S L; Roche, J R; Phyn, C V C

2018-02-01

The objective of this study was to determine the economic costs associated with different reasons for cow culling or on-farm mortality in a pasture-based seasonal system. A bioeconomic model was developed to quantify costs associated with the different farmer-recorded reasons and timing of cow wastage. The model accounted for the parity and stage of lactation at which the cows were removed as well as the consequent effect on the replacement rate and average age structure of the herd. The costs and benefits associated with the change were quantified, including animal replacement cost, cull salvage value, milk production loss, and the profitability of altered genetic merit based on industry genetic trends for each parity. The total cost of cow wastage was estimated to be NZ$23,628/100 cows per year (NZ$1 = US$0.69) in a pasture-based system. Of this total cost, NZ$14,300/100 cows worth of removals were for nonpregnancy and unknown reasons, and another NZ$3,631/100 cows was attributed to low milk production, mastitis, and udder problems. The total cost for cow removals due to farmer-recorded biological reasons (excluding unknown, production, and management-related causes) was estimated to be NZ$13,632/100 cows per year. Of this cost, an estimated NZ$10,286/100 cows was attributed to nonpregnancy, mastitis, udder problems, calving trouble, and injury or accident. There is a strong economic case for the pasture-based dairy industries to invest in genetic, herd health, and production management research focused on reducing animal wastage due to reproductive failure, mastitis, udder problems, injuries or accidents, and calving difficulties. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Categorization and reasoning among tree experts: do all roads lead to Rome?

PubMed

Medin, D L; Lynch, E B; Coley, J D; Atran, S

1997-02-01

To what degree do conceptual systems reflect universal patterns of featural covariation in the world (similarity) or universal organizing principles of mind, and to what degree do they reflect specific goals, theories, and beliefs of the categorizer? This question was addressed in experiments concerned with categorization and reasoning among different types of tree experts (e.g., taxonomists, landscape workers, parks maintenance personnel). The results show an intriguing pattern of similarities and differences. Differences in sorting between taxonomists and maintenance workers reflect differences in weighting of morphological features. Landscape workers, in contrast, sort trees into goal-derived categories based on utilitarian concerns. These sorting patterns carry over into category-based reasoning for the taxonomists and maintenance personnel but not the landscape workers. These generalizations interact with taxonomic rank and suggest that the genus (or folk generic) level is relatively and in some cases absolutely privileged. Implications of these findings for theories of categorization are discussed.

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.

The Reasonable Woman in a Hostile Work Environment.

ERIC Educational Resources Information Center

Shoop, Robert J.

1992-01-01

Briefly traces the sociological and legal development of the hostile-work-environment concept, and discusses the "reasonable woman" standard as applied in two cases. The use of the "reasonable woman" standard marks a shift in judicial reasoning that makes the legal system more responsive to women. (79 references) (MLF)

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.

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.

Transformation based endorsement systems

NASA Technical Reports Server (NTRS)

Sudkamp, Thomas

1988-01-01

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

A dynamic case-based planning system for space station application

NASA Technical Reports Server (NTRS)

Oppacher, F.; Deugo, D.

1988-01-01

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

Overcoming limitations of model-based diagnostic reasoning systems

NASA Technical Reports Server (NTRS)

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

1989-01-01

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

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…

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.

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…

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

PubMed

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

2014-01-01

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

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2014-01-01

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

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.

Evolution. A case of system dynamics.

PubMed

Apáthy, Z

1990-01-01

It is contended that the Darwinian theory of evolution is merely a special case of the obsolete Newtonian paradigm. A modern vision of reality, consistent with structuralism in biology, is presented. Some well-known neo-Darwinist explanations of the evolutionary process are quoted accompanied by structuralist interpretations of the same cases. These lead to a different 'mechanism' of evolution, based on internal factors, consistent with contemporary science. It is argued that a great number of specialists who dismiss the Darwinian theory of evolution share a common reason for rejecting it, but differ widely in guessing the motivating factor or factors of evolution.

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

A knowledge-based system for prototypical reasoning

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

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.

A case-based reasoning view of thrombophilia risk.

PubMed

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

2016-08-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Ontology-Based Method for Fault Diagnosis of Loaders.

PubMed

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

2018-02-28

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

Ontology-Based Method for Fault Diagnosis of Loaders

PubMed Central

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

2018-01-01

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

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

NASA Astrophysics Data System (ADS)

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

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

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

The impact of occupational health service network and reporting system in Taiwan.

PubMed

Chu, Po-Ching; Fuh, Hwan-Ran; Luo, Jiin-Chyuan; Du, Chung-Li; Chuang, Hung-Yi; Guo, How-Ran; Liu, Chiu-Shong; Su, Chien-Tien; Tang, Feng-Cheng; Chen, Chun-Chieh; Yang, Hsiao-Yu; Guo, Yue Leon

2013-01-01

Underreporting occupational disease cases has been a long-standing problem in Taiwan, which hinders the progress in occupational health and safety. To address this problem, the government has founded the Network of Occupational Diseases and Injuries Service (NODIS) for occupational disease and injury services and established a new Internet-based reporting system. The aims of this study are to analyze the possible influence of the NODIS, comprised of Center for Occupational Disease and Injury Services and their local network hospitals, on compensable occupational diseases and describe the distribution of occupational diseases across occupations and industries from 2005 to 2010 in Taiwan. We conducted a secondary analysis of two datasets, including the NODIS reporting dataset and the National Labor Insurance scheme's dataset of compensated cases. For the NODIS dataset, demographics, disease distribution, and the time trends of occupational diseases were analyzed. The data of the Labor Insurance dataset was used to calculate the annual incidence of compensated cases. Furthermore, the annual incidence of reported occupational diseases from the NODIS was further compared with the annual incidence of compensable occupational diseases from the compensated dataset during the same period. After the establishment of the NODIS, the two annual incidence rates of reported and compensable occupational disease cases have increased by 1.2 and 2.0 folds from 2007 to 2010, respectively. The reason for this increased reporting may be the implementation of the new government-funded Internet-based system. The reason for the increased compensable cases may be the increasing availability of hospitals and clinics to provide occupational health services. During the 2008-2010 period, the most frequently reported occupational diseases were carpal tunnel syndrome, lumbar disc disorder, upper limb musculoskeletal disorders, and contact dermatitis. The new network and reporting system was successful in providing more occupational health services, providing more workers with compensation for occupational diseases, and reducing underreporting of occupational diseases. Therefore, the experience in Taiwan could serve as an example for other newly developed countries in a similar situation.

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...

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.

Real-time passenger counting by active linear cameras

NASA Astrophysics Data System (ADS)

Khoudour, Louahdi; Duvieubourg, Luc; Deparis, Jean-Pierre

1996-03-01

The companies operating subways are very much concerned with counting the passengers traveling through their transport systems. One of the most widely used systems for counting passengers consists of a mechanical gate equipped with a counter. However, such simple systems are not able to count passengers jumping above the gates. Moreover, passengers carrying large luggage or bags may meet some difficulties when going through such gates. The ideal solution is a contact-free counting system that would bring more comfort of use for the passengers. For these reasons, we propose to use a video processing system instead of these mechanical gates. The optical sensors discussed in this paper offer several advantages including well defined detection areas, fast response time and reliable counting capability. A new technology has been developed and tested, based on linear cameras. Preliminary results show that this system is very efficient when the passengers crossing the optical gate are well separated. In other cases, such as in compact crowd conditions, reasonable accuracy has been demonstrated. These results are illustrated by means of a number of sequences shot in field conditions. It is our belief that more precise measurements could be achieved, in the case of compact crowd, by other algorithms and acquisition techniques of the line images that we are presently developing.

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

PubMed

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

2010-04-01

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

The need for the use of XACML access control policy in a distributed EHR and some performance considerations.

PubMed

Sucurovic, Snezana; Milutinovic, Veljko

2008-01-01

The Internet based distributed large scale information systems implements attribute based access control (ABAC) rather than Role Based Access Control (RBAC). The reason is that the Internet is identity less and that ABAC scales better. EXtensible Access Control Markup Language is standardized language for writing access control policies, access control requests and access control responses in ABAC. XACML can provide decentralized administration and credentials distribution. In year 2002 version of CEN ENV 13 606 attributes have been attached to EHCR components and in such a system ABAC and XACML have been easy to implement. This paper presents writing XACML policies in the case when attributes are in hierarchical structure. It is presented two possible solutions to write XACML policy in that case and that the solution when set functions are used is more compact and provides 10% better performances.

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.

A Menu-Driven Interface to Unix-Based Resources

PubMed Central

Evans, Elizabeth A.

1989-01-01

Unix has often been overlooked in the past as a viable operating system for anyone other than computer scientists. Its terseness, non-mnemonic nature of the commands, and the lack of user-friendly software to run under it are but a few of the user-related reasons which have been cited. It is, nevertheless, the operating system of choice in many cases. This paper describes a menu-driven interface to Unix which provides user-friendlier access to the software resources available on the computers running under Unix.

41 CFR 102-80.150 - What is meant by “reasonable worst case fire scenario”?

Code of Federal Regulations, 2011 CFR

2011-01-01

... 41 Public Contracts and Property Management 3 2011-01-01 2011-01-01 false What is meant by âreasonable worst case fire scenarioâ? 102-80.150 Section 102-80.150 Public Contracts and Property Management Federal Property Management Regulations System (Continued) FEDERAL MANAGEMENT REGULATION REAL PROPERTY 80...

41 CFR 102-80.150 - What is meant by “reasonable worst case fire scenario”?

Code of Federal Regulations, 2010 CFR

2010-07-01

... 41 Public Contracts and Property Management 3 2010-07-01 2010-07-01 false What is meant by âreasonable worst case fire scenarioâ? 102-80.150 Section 102-80.150 Public Contracts and Property Management Federal Property Management Regulations System (Continued) FEDERAL MANAGEMENT REGULATION REAL PROPERTY 80...

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

Vehicle Integrated Prognostic Reasoner (VIPR) 2010 Annual Final Report

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

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

PubMed

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

2012-12-01

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

Improving end of life care: an information systems approach to reducing medical errors.

PubMed

Tamang, S; Kopec, D; Shagas, G; Levy, K

2005-01-01

Chronic and terminally ill patients are disproportionately affected by medical errors. In addition, the elderly suffer more preventable adverse events than younger patients. Targeting system wide "error-reducing" reforms to vulnerable populations can significantly reduce the incidence and prevalence of human error in medical practice. Recent developments in health informatics, particularly the application of artificial intelligence (AI) techniques such as data mining, neural networks, and case-based reasoning (CBR), presents tremendous opportunities for mitigating error in disease diagnosis and patient management. Additionally, the ubiquity of the Internet creates the possibility of an almost ideal network for the dissemination of medical information. We explore the capacity and limitations of web-based palliative information systems (IS) to transform the delivery of care, streamline processes and improve the efficiency and appropriateness of medical treatment. As a result, medical error(s) that occur with patients dealing with severe, chronic illness and the frail elderly can be reduced.The palliative model grew out of the need for pain relief and comfort measures for patients diagnosed with cancer. Applied definitions of palliative care extend this convention, but there is no widely accepted definition. This research will discuss the development life cycle of two palliative information systems: the CONFER QOLP management information system (MIS), currently used by a community-based palliative care program in Brooklyn, New York, and the CAREN case-based reasoning prototype. CONFER is a web platform based on the idea of "eCare". CONFER uses XML (extensible mark-up language), a W3C-endorced standard mark up to define systems data. The second system, CAREN, is a CBR prototype designed for palliative care patients in the cancer trajectory. CBR is a technique, which tries to exploit the similarities of two situations and match decision-making to the best-known precedent cases. The prototype uses the opensource CASPIAN shell developed by the University of Aberystwyth, Wales and is available by anonymous FTP. We will discuss and analyze the preliminary results we have obtained using this CBR tool. Our research suggests that automated information systems can be used to improve the quality of care at the end of life and disseminate expert level 'know how' to palliative care clinicians. We will present how our CBR prototype can be successfully deployed, capable of securely transferring information using a Secure File Transfer Protocol (SFTP) and using a JAVA CBR engine.

Application of a temporal reasoning framework tool in analysis of medical device adverse events.

PubMed

Clark, Kimberly K; Sharma, Deepak K; Chute, Christopher G; Tao, Cui

2011-01-01

The Clinical Narrative Temporal Relation Ontology (CNTRO)1 project offers a semantic-web based reasoning framework, which represents temporal events and relationships within clinical narrative texts, and infer new knowledge over them. In this paper, the CNTRO reasoning framework is applied to temporal analysis of medical device adverse event files. One specific adverse event was used as a test case: late stent thrombosis. Adverse event narratives were obtained from the Food and Drug Administration's (FDA) Manufacturing and User Facility Device Experience (MAUDE) database2. 15 adverse event files in which late stent thrombosis was confirmed were randomly selected across multiple drug eluting stent devices. From these files, 81 events and 72 temporal relations were annotated. 73 temporal questions were generated, of which 65 were correctly answered by the CNTRO system. This results in an overall accuracy of 89%. This system should be pursued further to continue assessing its potential benefits in temporal analysis of medical device adverse events.

Hybrid diagnostic system: beacon-based exception analysis for multimissions - Livingstone integration

NASA Technical Reports Server (NTRS)

Park, Han G.; Cannon, Howard; Bajwa, Anupa; Mackey, Ryan; James, Mark; Maul, William

2004-01-01

This paper describes the initial integration of a hybrid reasoning system utilizing a continuous domain feature-based detector, Beacon-based Exceptions Analysis for Multimissions (BEAM), and a discrete domain model-based reasoner, Livingstone.

Intelligent agents for adaptive security market surveillance

NASA Astrophysics Data System (ADS)

Chen, Kun; Li, Xin; Xu, Baoxun; Yan, Jiaqi; Wang, Huaiqing

2017-05-01

Market surveillance systems have increasingly gained in usage for monitoring trading activities in stock markets to maintain market integrity. Existing systems primarily focus on the numerical analysis of market activity data and generally ignore textual information. To fulfil the requirements of information-based surveillance, a multi-agent-based architecture that uses agent intercommunication and incremental learning mechanisms is proposed to provide a flexible and adaptive inspection process. A prototype system is implemented using the techniques of text mining and rule-based reasoning, among others. Based on experiments in the scalping surveillance scenario, the system can identify target information evidence up to 87.50% of the time and automatically identify 70.59% of cases depending on the constraints on the available information sources. The results of this study indicate that the proposed information surveillance system is effective. This study thus contributes to the market surveillance literature and has significant practical implications.

Workflow technology: the new frontier. How to overcome the barriers and join the future.

PubMed

Shefter, Susan M

2006-01-01

Hospitals are catching up to the business world in the introduction of technology systems that support professional practice and workflow. The field of case management is highly complex and interrelates with diverse groups in diverse locations. The last few years have seen the introduction of Workflow Technology Tools, which can improve the quality and efficiency of discharge planning by the case manager. Despite the availability of these wonderful new programs, many case managers are hesitant to adopt the new technology and workflow. For a myriad of reasons, a computer-based workflow system can seem like a brick wall. This article discusses, from a practitioner's point of view, how professionals can gain confidence and skill to get around the brick wall and join the future.

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.

Logic Design Pathology and Space Flight Electronics

NASA Technical Reports Server (NTRS)

Katz, Richard; Barto, Rod L.; Erickson, K.

1997-01-01

Logic design errors have been observed in space flight missions and the final stages of ground test. The technologies used by designers and their design/analysis methodologies will be analyzed. This will give insight to the root causes of the failures. These technologies include discrete integrated circuit based systems, systems based on field and mask programmable logic, and the use computer aided engineering (CAE) systems. State-of-the-art (SOTA) design tools and methodologies will be analyzed with respect to high-reliability spacecraft design and potential pitfalls are discussed. Case studies of faults from large expensive programs to "smaller, faster, cheaper" missions will be used to explore the fundamental reasons for logic design problems.

A Legal Negotiatiton Support System Based on A Diagram

NASA Astrophysics Data System (ADS)

Nitta, Katsumi; Shibasaki, Masato; Yasumura, Yoshiaki; Hasegawa, Ryuzo; Fujita, Hiroshi; Koshimura, Miyuki; Inoue, Katsumi; Shirai, Yasuyuki; Komatsu, Hiroshi

We present an overview of a legal negotiation support system, ANS (Argumentation based Negotiation support System). ANS consists of a user interface, three inference engines, a database of old cases, and two decision support modules. The ANS users negotiates or disputes with others via a computer network. The negotiation status is managed in the form of the negotiation diagram. The negotiation diagram is an extension of Toulmin’s argument diagram, and it contains all arguments insisted by participants. The negotiation protocols are defined as operations to the negotiation diagram. By exchanging counter arguments each other, the negotiation diagram grows up. Nonmonotonic reasoning using rule priorities are applied to the negotiation diagram.

Reflexive reasoning for distributed real-time systems

NASA Technical Reports Server (NTRS)

Goldstein, David

1994-01-01

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

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.

[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.

Evaluating the roles of the inferior frontal gyrus and superior parietal lobule in deductive reasoning: an rTMS study.

PubMed

Tsujii, Takeo; Sakatani, Kaoru; Masuda, Sayako; Akiyama, Takekazu; Watanabe, Shigeru

2011-09-15

This study used off-line repetitive transcranial magnetic stimulation (rTMS) to examine the roles of the superior parietal lobule (SPL) and inferior frontal gyrus (IFG) in a deductive reasoning task. Subjects performed a categorical syllogistic reasoning task involving congruent, incongruent, and abstract trials. Twenty four subjects received magnetic stimulation to the SPL region prior to the task. In the other 24 subjects, TMS was administered to the IFG region before the task. Stimulation lasted for 10min, with an inter-pulse frequency of 1Hz. We found that bilateral SPL (Brodmann area (BA) 7) stimulation disrupted performance on abstract and incongruent reasoning. Left IFG (BA 45) stimulation impaired congruent reasoning performance while paradoxically facilitating incongruent reasoning performance. This resulted in the elimination of the belief-bias. In contrast, right IFG stimulation only impaired incongruent reasoning performance, thus enhancing the belief-bias effect. These findings are largely consistent with the dual-process theory of reasoning, which proposes the existence of two different human reasoning systems: a belief-based heuristic system; and a logic-based analytic system. The present findings suggest that the left language-related IFG (BA 45) may correspond to the heuristic system, while bilateral SPL may underlie the analytic system. The right IFG may play a role in blocking the belief-based heuristic system for solving incongruent reasoning trials. This study could offer an insight about functional roles of distributed brain systems in human deductive reasoning by utilizing the rTMS approach. Copyright © 2011 Elsevier Inc. All rights reserved.

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…

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

PubMed

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

2008-08-26

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

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

PubMed Central

Gustafsson, Marie; Jontell, Mats; Torgersson, Olof

2008-01-01

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

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

Improving Vision-Based Motor Rehabilitation Interactive Systems for Users with Disabilities Using Mirror Feedback

PubMed Central

Martínez-Bueso, Pau; Moyà-Alcover, Biel

2014-01-01

Observation is recommended in motor rehabilitation. For this reason, the aim of this study was to experimentally test the feasibility and benefit of including mirror feedback in vision-based rehabilitation systems: we projected the user on the screen. We conducted a user study by using a previously evaluated system that improved the balance and postural control of adults with cerebral palsy. We used a within-subjects design with the two defined feedback conditions (mirror and no-mirror) with two different groups of users (8 with disabilities and 32 without disabilities) using usability measures (time-to-start (T s) and time-to-complete (T c)). A two-tailed paired samples t-test confirmed that in case of disabilities the mirror feedback facilitated the interaction in vision-based systems for rehabilitation. The measured times were significantly worse in the absence of the user's own visual feedback (T s = 7.09 (P < 0.001) and T c = 4.48 (P < 0.005)). In vision-based interaction systems, the input device is the user's own body; therefore, it makes sense that feedback should be related to the body of the user. In case of disabilities the mirror feedback mechanisms facilitated the interaction in vision-based systems for rehabilitation. Results recommends developers and researchers use this improvement in vision-based motor rehabilitation interactive systems. PMID:25295310

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…

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

PubMed

Price, Morgan

2016-10-04

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

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

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

Statistical inference and Aristotle's Rhetoric.

PubMed

Macdonald, Ranald R

2004-11-01

Formal logic operates in a closed system where all the information relevant to any conclusion is present, whereas this is not the case when one reasons about events and states of the world. Pollard and Richardson drew attention to the fact that the reasoning behind statistical tests does not lead to logically justifiable conclusions. In this paper statistical inferences are defended not by logic but by the standards of everyday reasoning. Aristotle invented formal logic, but argued that people mostly get at the truth with the aid of enthymemes--incomplete syllogisms which include arguing from examples, analogies and signs. It is proposed that statistical tests work in the same way--in that they are based on examples, invoke the analogy of a model and use the size of the effect under test as a sign that the chance hypothesis is unlikely. Of existing theories of statistical inference only a weak version of Fisher's takes this into account. Aristotle anticipated Fisher by producing an argument of the form that there were too many cases in which an outcome went in a particular direction for that direction to be plausibly attributed to chance. We can therefore conclude that Aristotle would have approved of statistical inference and there is a good reason for calling this form of statistical inference classical.

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

DTIC Science & Technology

2016-11-01

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

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

PubMed

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

2008-07-01

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

Developing a framework for qualitative engineering: Research in design and analysis of complex structural systems

NASA Technical Reports Server (NTRS)

Franck, Bruno M.

1990-01-01

The research is focused on automating the evaluation of complex structural systems, whether for the design of a new system or the analysis of an existing one, by developing new structural analysis techniques based on qualitative reasoning. The problem is to identify and better understand: (1) the requirements for the automation of design, and (2) the qualitative reasoning associated with the conceptual development of a complex system. The long-term objective is to develop an integrated design-risk assessment environment for the evaluation of complex structural systems. The scope of this short presentation is to describe the design and cognition components of the research. Design has received special attention in cognitive science because it is now identified as a problem solving activity that is different from other information processing tasks (1). Before an attempt can be made to automate design, a thorough understanding of the underlying design theory and methodology is needed, since the design process is, in many cases, multi-disciplinary, complex in size and motivation, and uses various reasoning processes involving different kinds of knowledge in ways which vary from one context to another. The objective is to unify all the various types of knowledge under one framework of cognition. This presentation focuses on the cognitive science framework that we are using to represent the knowledge aspects associated with the human mind's abstraction abilities and how we apply it to the engineering knowledge and engineering reasoning in design.

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.

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.

Reinventing Solutions to Systems of Linear Differential Equations: A Case of Emergent Models Involving Analytic Expressions

ERIC Educational Resources Information Center

Rasmussen, Chris; Blumenfeld, Howard

2007-01-01

An enduring challenge in mathematics education is to create learning environments in which students generate, refine, and extend their intuitive and informal ways of reasoning to more sophisticated and formal ways of reasoning. Pressing concerns for research, therefore, are to detail students' progressively sophisticated ways of reasoning and…

Comprehension and retrieval of failure cases in airborne observatories

NASA Technical Reports Server (NTRS)

Alvarado, Sergio J.; Mock, Kenrick J.

1995-01-01

This paper describes research dealing with the computational problem of analyzing and repairing failures of electronic and mechanical systems of telescopes in NASA's airborne observatories, such as KAO (Kuiper Airborne Observatory) and SOFIA (Stratospheric Observatory for Infrared Astronomy). The research has resulted in the development of an experimental system that acquires knowledge of failure analysis from input text, and answers questions regarding failure detection and correction. The system's design builds upon previous work on text comprehension and question answering, including: knowledge representation for conceptual analysis of failure descriptions, strategies for mapping natural language into conceptual representations, case-based reasoning strategies for memory organization and indexing, and strategies for memory search and retrieval. These techniques have been combined into a model that accounts for: (a) how to build a knowledge base of system failures and repair procedures from descriptions that appear in telescope-operators' logbooks and FMEA (failure modes and effects analysis) manuals; and (b) how to use that knowledge base to search and retrieve answers to questions about causes and effects of failures, as well as diagnosis and repair procedures. This model has been implemented in FANSYS (Failure ANalysis SYStem), a prototype text comprehension and question answering program for failure analysis.

Comprehension and retrieval of failure cases in airborne observatories

NASA Astrophysics Data System (ADS)

Alvarado, Sergio J.; Mock, Kenrick J.

1995-05-01

This paper describes research dealing with the computational problem of analyzing and repairing failures of electronic and mechanical systems of telescopes in NASA's airborne observatories, such as KAO (Kuiper Airborne Observatory) and SOFIA (Stratospheric Observatory for Infrared Astronomy). The research has resulted in the development of an experimental system that acquires knowledge of failure analysis from input text, and answers questions regarding failure detection and correction. The system's design builds upon previous work on text comprehension and question answering, including: knowledge representation for conceptual analysis of failure descriptions, strategies for mapping natural language into conceptual representations, case-based reasoning strategies for memory organization and indexing, and strategies for memory search and retrieval. These techniques have been combined into a model that accounts for: (a) how to build a knowledge base of system failures and repair procedures from descriptions that appear in telescope-operators' logbooks and FMEA (failure modes and effects analysis) manuals; and (b) how to use that knowledge base to search and retrieve answers to questions about causes and effects of failures, as well as diagnosis and repair procedures. This model has been implemented in FANSYS (Failure ANalysis SYStem), a prototype text comprehension and question answering program for failure analysis.

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

ERIC Educational Resources Information Center

Tawfik, Andrew; Jonassen, David

2013-01-01

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

Teaching clinical reasoning: case-based and coached.

PubMed

Kassirer, Jerome P

2010-07-01

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

Wireless control system for two-axis linear oscillating motion applying CBR technology

NASA Astrophysics Data System (ADS)

Kuzyakov, O. N.; Andreeva, M. A.

2018-03-01

The paper presents the aspects of elaborating a movement control system. The system is to implement determination of movement characteristics of the object controlled, which performs an oscillating linear motion in a two-axis direction. The system has an electronic-optical principle of action: light receivers are attached to a controlled object, and a laser light emitter is attached to a static construction. While the object performs movement along the construction, the light emitter signal is registered by light receivers, based on which determination of the object position and characteristic of its movement are performed. An algorithm of system implementation is elaborated. Signal processing is performed on the basis of the case-based reasoning method. The system is to be used in machine-building industry in controlling relative displacement of the dynamic object or its assembly.

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/.

Case-Based Multi-Sensor Intrusion Detection

NASA Astrophysics Data System (ADS)

Schwartz, Daniel G.; Long, Jidong

2009-08-01

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

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.

Computer Science and Statistics. Proceedings of the Symposium on the Interface (18th) Held on March 19-21, 1986 in Fort Collins, Colorado.

DTIC Science & Technology

1987-08-26

example, expert systems research would benefit examples are the Acute Renal Failure [15] system, the if it could attract statisticians to assist in...research projects including the Acute Renal Failure [15] system, the 6. EXPLAINING COMPLEX REASONING INTERNIST-] [22] system for diagnosis within the...the MEDAS and Acute Renal Failure systems. task at any point in reasoning about a case is constrained to Entropy-discriminate makes use of a measure

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.

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-02-17

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

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.

TEXSYS. [a knowledge based system for the Space Station Freedom thermal control system test-bed

NASA Technical Reports Server (NTRS)

Bull, John

1990-01-01

The Systems Autonomy Demonstration Project has recently completed a major test and evaluation of TEXSYS, a knowledge-based system (KBS) which demonstrates real-time control and FDIR for the Space Station Freedom thermal control system test-bed. TEXSYS is the largest KBS ever developed by NASA and offers a unique opportunity for the study of technical issues associated with the use of advanced KBS concepts including: model-based reasoning and diagnosis, quantitative and qualitative reasoning, integrated use of model-based and rule-based representations, temporal reasoning, and scale-up performance issues. TEXSYS represents a major achievement in advanced automation that has the potential to significantly influence Space Station Freedom's design for the thermal control system. An overview of the Systems Autonomy Demonstration Project, the thermal control system test-bed, the TEXSYS architecture, preliminary test results, and thermal domain expert feedback are presented.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Building Citywide Systems for Quality: A Guide and Case Studies for Afterschool Leaders

ERIC Educational Resources Information Center

Yohalem, Nicole; Devaney, Elizabeth; Smith, Charles; Wilson-Ahlstrom, Alicia

2012-01-01

A quality improvement system (QIS) is an intentional effort to raise the quality of afterschool programming in an ongoing, organized fashion. There are a number of reasons the QIS is gaining popularity. The main reasons community leaders are drawn to improving quality is that they know that 1) higher quality programs will mean better experiences…

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

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.

Facilitating the transition from physiology to hospital wards through an interdisciplinary case study of septic shock.

PubMed

Li, Albert S; Berger, Kenneth I; Schwartz, David R; Slater, William R; Goldfarb, David S

2014-04-12

In order to develop clinical reasoning, medical students must be able to integrate knowledge across traditional subject boundaries and multiple disciplines. At least two dimensions of integration have been identified: horizontal integration, bringing together different disciplines in considering a topic; and vertical integration, bridging basic science and clinical practice. Much attention has been focused on curriculum overhauls, but our approach is to facilitate horizontal and vertical integration on a smaller scale through an interdisciplinary case study discussion and then to assess its utility. An interdisciplinary case study discussion about a critically ill patient was implemented at the end of an organ system-based, basic sciences module at New York University School of Medicine. Three clinical specialists-a cardiologist, a pulmonologist, and a nephrologist-jointly led a discussion about a complex patient in the intensive care unit with multiple medical problems secondary to septic shock. The discussion emphasized the physiologic underpinnings behind the patient's presentation and the physiologic considerations across the various systems in determining proper treatment. The discussion also highlighted the interdependence between the cardiovascular, respiratory, and renal systems, which were initially presented in separate units. After the session students were given a brief, anonymous three-question free-response questionnaire in which they were asked to evaluate and freely comment on the exercise. Students not only took away physiological principles but also gained an appreciation for various thematic lessons for bringing basic science to the bedside, especially horizontal and vertical integration. The response of the participants was overwhelmingly positive with many indicating that the exercise integrated the material across organ systems, and strengthened their appreciation of the role of physiology in understanding disease presentations and guiding appropriate therapy. Horizontal and vertical integration can be presented effectively through a single-session case study, with complex patient cases involving multiple organ systems providing students opportunities to integrate their knowledge across organ systems while emphasizing the importance of physiology in clinical reasoning. Furthermore, having several clinicians from different specialties discuss the case together can reinforce the matter of integration across multiple organ systems and disciplines in students' minds.

Facilitating the transition from physiology to hospital wards through an interdisciplinary case study of septic shock

PubMed Central

2014-01-01

Background In order to develop clinical reasoning, medical students must be able to integrate knowledge across traditional subject boundaries and multiple disciplines. At least two dimensions of integration have been identified: horizontal integration, bringing together different disciplines in considering a topic; and vertical integration, bridging basic science and clinical practice. Much attention has been focused on curriculum overhauls, but our approach is to facilitate horizontal and vertical integration on a smaller scale through an interdisciplinary case study discussion and then to assess its utility. Methods An interdisciplinary case study discussion about a critically ill patient was implemented at the end of an organ system-based, basic sciences module at New York University School of Medicine. Three clinical specialists—a cardiologist, a pulmonologist, and a nephrologist—jointly led a discussion about a complex patient in the intensive care unit with multiple medical problems secondary to septic shock. The discussion emphasized the physiologic underpinnings behind the patient’s presentation and the physiologic considerations across the various systems in determining proper treatment. The discussion also highlighted the interdependence between the cardiovascular, respiratory, and renal systems, which were initially presented in separate units. After the session students were given a brief, anonymous three-question free-response questionnaire in which they were asked to evaluate and freely comment on the exercise. Results Students not only took away physiological principles but also gained an appreciation for various thematic lessons for bringing basic science to the bedside, especially horizontal and vertical integration. The response of the participants was overwhelmingly positive with many indicating that the exercise integrated the material across organ systems, and strengthened their appreciation of the role of physiology in understanding disease presentations and guiding appropriate therapy. Conclusions Horizontal and vertical integration can be presented effectively through a single-session case study, with complex patient cases involving multiple organ systems providing students opportunities to integrate their knowledge across organ systems while emphasizing the importance of physiology in clinical reasoning. Furthermore, having several clinicians from different specialties discuss the case together can reinforce the matter of integration across multiple organ systems and disciplines in students’ minds. PMID:24725336

Development of an Expert System for Representing Procedural Knowledge

NASA Technical Reports Server (NTRS)

Georgeff, Michael P.; Lansky, Amy L.

1985-01-01

A high level of automation is of paramount importance in most space operations. It is critical for unmanned missions and greatly increases the effectiveness of manned missions. However, although many functions can be automated by using advanced engineering techniques, others require complex reasoning, sensing, and manipulatory capabilities that go beyond this technology. Automation of fault diagnosis and malfunction handling is a case in point. The military have long been interested in this problem, and have developed automatic test equipment to aid in the maintenance of complex military hardware. These systems are all based on conventional software and engineering techniques. However, the effectiveness of such test equipment is severely limited. The equipment is inflexible and unresponsive to the skill level of the technicians using it. The diagnostic procedures cannot be matched to the exigencies of the current situation nor can they cope with reconfiguration or modification of the items under test. The diagnosis cannot be guided by useful advice from technicians and, when a fault cannot be isolated, no explanation is given as to the cause of failure. Because these systems perform a prescribed sequence of tests, they cannot utilize knowledge of a particular situation to focus attention on more likely trouble spots. Consequently, real-time performance is highly unsatisfactory. Furthermore, the cost of developing test software is substantial and time to maturation is excessive. Significant advances in artificial intelligence (AI) have recently led to the development of powerful and flexible reasoning systems, known as expert or knowledge-based systems. We have devised a powerful and theoretically sound scheme for representing and reasoning about procedural knowledge.

Petroleum Dependency: The Case to Replace the Internal Combustion Engine

DTIC Science & Technology

2015-02-17

at Ft. Benning, Georgia where he was commissioned an Ordnance Officer. During his career, COL Melton served as a Maintenance Platoon Leader/ Shop ...reasons to stay with the ICE, there are greater reasons to explore alternatives. In fact, there is no logical reason to stay with the antiquated ...hydrogen fueling systems while antiquated vehicle platform inventories dwindle away. 50

MTK: An AI tool for model-based reasoning

NASA Technical Reports Server (NTRS)

Erickson, William K.; Rudokas, Mary R.

1988-01-01

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

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

Knowledge Representation and Ontologies

NASA Astrophysics Data System (ADS)

Grimm, Stephan

Knowledge representation and reasoning aims at designing computer systems that reason about a machine-interpretable representation of the world. Knowledge-based systems have a computational model of some domain of interest in which symbols serve as surrogates for real world domain artefacts, such as physical objects, events, relationships, etc. [1]. The domain of interest can cover any part of the real world or any hypothetical system about which one desires to represent knowledge for com-putational purposes. A knowledge-based system maintains a knowledge base, which stores the symbols of the computational model in the form of statements about the domain, and it performs reasoning by manipulating these symbols. Applications can base their decisions on answers to domain-relevant questions posed to a knowledge base.

An IT Architecture for Systems Medicine.

PubMed

Ganzinger, Matthias; Gietzelt, Matthias; Karmen, Christian; Firnkorn, Daniel; Knaup, Petra

2015-01-01

Systems medicine aims to support treatment of complex diseases like cancer by integrating all available data for the disease. To provide such a decision support in clinical practice, a suitable IT architecture is necessary. We suggest a generic architecture comprised of the following three layers: data representation, decision support, and user interface. For the systems medicine research project "Clinically-applicable, omics-based assessment of survival, side effects, and targets in multiple myeloma" (CLIOMMICS) we developed a concrete instance of the generic architecture. We use i2b2 for representing the harmonized data. Since no deterministic model exists for multiple myeloma we use case-based reasoning for decision support. For clinical practice, visualizations of the results must be intuitive and clear. At the same time, they must communicate the uncertainty immanent in stochastic processes. Thus, we develop a specific user interface for systems medicine based on the web portal software Liferay.

Water resources planning based on complex system dynamics: A case study of Tianjin city

NASA Astrophysics Data System (ADS)

Zhang, X. H.; Zhang, H. W.; Chen, B.; Chen, G. Q.; Zhao, X. H.

2008-12-01

A complex system dynamic (SD) model focusing on water resources, termed as TianjinSD, is developed for the integrated and scientific management of the water resources of Tianjin, which contains information feedback that governs interactions in the system and is capable of synthesizing component-level knowledge into system behavior simulation at an integrated level, thus presenting reasonable predictive results for policy-making on water resources allocation and management. As for the Tianjin city, interactions among 96 components for 12 years are explored and four planning alternatives are chosen, one of which is based on the conventional mode assuming that the existing pattern of human activities will be prevailed, while the others are alternative planning designs based on the interaction of local authorities and planning researchers. Optimal mode is therefore obtained according to different scenarios when compared the simulation results for evaluation of different decisions and dynamic consequences.

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

PubMed

Gissel, A; Knauth, P

1998-01-01

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

Research on the influence of parking charging strategy based on multi-level extension theory of group decision making

NASA Astrophysics Data System (ADS)

Cheng, Fen; Hu, Wanxin

2017-05-01

Based on analysis of the impact of the experience of parking policy at home and abroad, design the impact analysis process of parking strategy. First, using group decision theory to create a parking strategy index system and calculate its weight. Index system includes government, parking operators and travelers. Then, use a multi-level extension theory to analyze the CBD parking strategy. Assess the parking strategy by calculating the correlation of each indicator. Finally, assess the strategy of parking charges through a case. Provide a scientific and reasonable basis for assessing parking strategy. The results showed that the model can effectively analyze multi-target, multi-property parking policy evaluation.

Canine parvovirus in Australia: A comparative study of reported rural and urban cases.

PubMed

Zourkas, Elaine; Ward, Michael P; Kelman, Mark

2015-12-31

Canine parvovirus (CPV) is a highly contagious and often fatal disease reported worldwide. Outbreaks occur throughout Australia, and it has been suggested that disproportionally more CPV cases occur in rural locations. However, evidence to support this suggestion-and possible reasons for such a predisposition-has not existed until now. In this study a total of 4870 CPV cases reported from an Australian disease surveillance system between September 2009 and July 2014 were analysed. Australian postcodes were classified as rural or urban (based on human population density) and reported CPV cases were then categorised as rural or urban based on their reported home postcode. Parvovirus cases were predominately young (<12 months), entire, unvaccinated, mixed-breed dogs. More than twice as many of the reported cases were from a rural area (3321 cases) compared to an urban area (1549 cases). The overall case fatality rate was 47.2%; it was higher for those CPV cases reported from urban areas (50.6%) than rural areas (45.5%). A greater proportion of rural cases were younger, entire dogs compared to urban cases. The final multivariable model of CPV cases being reported from a rural area included age (<12 months) and vaccination status (never vaccinated) as significant predictors. Poor socioeconomic status might be a reason for the decision of rural owners not to vaccinate their dogs as readily as urban owners. The excess reporting of rural CPV cases compared to urban cases and the predictive risk factors identified in this study can be used by veterinarians to reduce the incidence of CPV by educating owners about the disease and promoting better vaccination programs in rural areas. This study also supports that the increased risk of CPV in rural areas may necessitate a need for increased vigilance around preventing CPV disease spread, additional care with puppies which are the most susceptible to this disease and tighter vaccination protocols, compared to urban areas. Copyright © 2015 Elsevier B.V. All rights reserved.

The Evidence-Based Reasoning Framework: Assessing Scientific Reasoning

ERIC Educational Resources Information Center

Brown, Nathaniel J. S.; Furtak, Erin Marie; Timms, Michael; Nagashima, Sam O.; Wilson, Mark

2010-01-01

Recent science education reforms have emphasized the importance of students engaging with and reasoning from evidence to develop scientific explanations. A number of studies have created frameworks based on Toulmin's (1958/2003) argument pattern, whereas others have developed systems for assessing the quality of students' reasoning to support…

Evaluation of radiosurgery techniques–Cone-based linac radiosurgery vs tomotherapy-based radiosurgery

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

Yip, Ho Yin, E-mail: hoyinyip@yahoo.com.hk; Mui, Wing Lun A.; Lee, Joseph W.Y.

2013-07-01

Performances of radiosurgery of intracranial lesions between cone-based Linac system and Tomotherapy-based system were compared in terms of dosimetry and time. Twelve patients with single intracranial lesion treated with cone-based Linac radiosurgery system from 2005 to 2009 were replanned for Tomotherapy-based radiosurgery treatment. The conformity index, homogeneity index (HI), and gradient score index (GSI) of each case was calculated. The Wilcoxon matched-pair test was used to compare the 3 indices between both systems. The cases with regular target (n = 6) and those with irregular target (n = 6) were further analyzed separately. The estimated treatment time between both systemsmore » was also compared. Significant differences were found in HI (p = 0.05) and in GSI (p = 0.03) for the whole group. Cone-based radiosurgery was better in GSI whereas Tomotherapy-based radiosurgery was better in HI. Cone-based radiosurgery was better in conformity index (p = 0.03) and GSI (p = 0.03) for regular targets, whereas Tomotherapy-based radiosurgery system performed significantly better in HI (p = 0.03) for irregular targets. The estimated total treatment time for Tomotherapy-based radiosurgery ranged from 24 minutes to 35 minutes, including 15 minutes of pretreatment megavoltage computed tomography (MVCT) and image registration, whereas that for cone-based radiosurgery ranged from 15 minutes for 1 isocenter to 75 minutes for 5 isocenters. As a rule of thumb, Tomotherapy-based radiosurgery system should be the first-line treatment for irregular lesions because of better dose homogeneity and shorter treatment time. Cone-based Linac radiosurgery system should be the treatment of choice for regular targets because of the better dose conformity, rapid dose fall-off, and reasonable treatment time.« less

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

NASA Technical Reports Server (NTRS)

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

2003-01-01

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

A medico-legal review of cases involving quadriplegia following cervical spine surgery: Is there an argument for a no-fault compensation system?

PubMed

Epstein, Nancy E

2010-04-07

To determine whether patients who become quadriplegic following cervical spine surgery are adequately compensated by our present medico-legal system. The outcomes of malpractice suits obtained from Verdict Search (East Islip, NY, USA), a medico-legal journal, were evaluated over a 20-year period. Although the present malpractice system generously rewards many quadriplegic patients with substantial settlements/ Plaintiffs' verdicts, a subset receive lesser reimbursements (verdicts/settlements], while others with defense verdicts receive no compensatory damages. Utilizing Verdict Search, 54 cases involving quadriplegia following cervical spine surgery were reviewed for a 20-year interval (1988-2008). The reason(s) for the suit, the defendants, the legal outcome, and the time to outcome were identified. Operations included 25 anterior cervical procedures, 22 posterior cervical operations, 1 circumferential cervical procedure, and 6 cases in which the cervical operations were not defined. The four most prominent legal allegations for suits included negligent surgery (47 cases), lack of informed consent (23 cases), failure to diagnose/treat (33 cases), and failure to brace (15 cases). Forty-four of the 54 suits included spine surgeons. There were 19 Plaintiffs' verdicts (average US $5.9 million, range US $540,000-US $18.4 million), and 20 settlements (average US $2.8 million, range US $66,500-US $12.0 million). Fifteen quadriplegic patients with defense verdicts received no compensatory damages. The average time to verdicts/settlements was 4.3 years. For 54 patients who were quadriplegic following cervical spine surgery, 15 (28%) with defense verdicts received no compensatory damages. Under a No-Fault system, quadriplegic patients would qualify for a "reasonable" level of compensation over a "shorter" time frame.

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.

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

PubMed

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

2017-10-01

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

Case-based reasoning emulation of persons for wheelchair navigation.

PubMed

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

2012-10-01

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

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

NASA Astrophysics Data System (ADS)

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

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

An advanced artificial intelligence tool for menu design.

PubMed

Khan, Abdus Salam; Hoffmann, Achim

2003-01-01

The computer-assisted menu design still remains a difficult task. Usually knowledge that aids in menu design by a computer is hard-coded and because of that a computerised menu planner cannot handle the menu design problem for an unanticipated client. To address this problem we developed a menu design tool, MIKAS (menu construction using incremental knowledge acquisition system), an artificial intelligence system that allows the incremental development of a knowledge-base for menu design. We allow an incremental knowledge acquisition process in which the expert is only required to provide hints to the system in the context of actual problem instances during menu design using menus stored in a so-called Case Base. Our system incorporates Case-Based Reasoning (CBR), an Artificial Intelligence (AI) technique developed to mimic human problem solving behaviour. Ripple Down Rules (RDR) are a proven technique for the acquisition of classification knowledge from expert directly while they are using the system, which complement CBR in a very fruitful way. This combination allows the incremental improvement of the menu design system while it is already in routine use. We believe MIKAS allows better dietary practice by leveraging a dietitian's skills and expertise. As such MIKAS has the potential to be helpful for any institution where dietary advice is practised.

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

PubMed

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

2005-01-01

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

Prevalence of and Reasons for Patients Leaving Against Medical Advice from Paediatric Wards in Oman.

PubMed

Al-Ghafri, Mohamed; Al-Bulushi, Abdullah; Al-Qasmi, Ahmed

2016-02-01

The objective of this study was to determine the prevalence of and reasons for patients leaving against medical advice (LAMA) in a paediatric setting in Oman. This retrospective study was carried out between January 2007 and December 2009 and assessed patients who left the paediatric wards at the Royal Hospital, Muscat, Oman, against medical advice. Of 11,482 regular discharges, there were 183 cases of LAMA (prevalence: 1.6%). Dissatisfaction with treatment and a desire to seek a second opinion were collectively the most cited reasons for LAMA according to data from the hospital's electronic system (27.9%) and telephone conversations with patients' parents (55.0%). No reasons for LAMA were documented in the hospital's electronic system for 109 patients (59.6%). The low observed prevalence of LAMA suggests good medical practice at the Royal Hospital. This study indicates the need for thorough documentation of all LAMA cases to ensure the availability of high-quality data for healthcare workers involved in preventing LAMA.

Imagination, distributed responsibility and vulnerable technological systems: the case of Snorre A.

PubMed

Coeckelbergh, Mark; Wackers, Ger

2007-06-01

An influential approach to engineering ethics is based on codes of ethics and the application of moral principles by individual practitioners. However, to better understand the ethical problems of complex technological systems and the moral reasoning involved in such contexts, we need other tools as well. In this article, we consider the role of imagination and develop a concept of distributed responsibility in order to capture a broader range of human abilities and dimensions of moral responsibility. We show that in the case of Snorre A, a near-disaster with an oil and gas production installation, imagination played a crucial and morally relevant role in how the crew coped with the crisis. For example, we discuss the role of scenarios and images in the moral reasoning and discussion of the platform crew in coping with the crisis. Moreover, we argue that responsibility for increased system vulnerability, turning an undesired event into a near-disaster, should not be ascribed exclusively, for example to individual engineers alone, but should be understood as distributed between various actors, levels and times. We conclude that both managers and engineers need imagination to transcend their disciplinary perspectives in order to improve the robustness of their organisations and to be better prepared for crisis situations. We recommend that education and training programmes should be transformed accordingly.

[Cognitive errors in diagnostic decision making].

PubMed

Gäbler, Martin

2017-10-01

Approximately 10-15% of our diagnostic decisions are faulty and may lead to unfavorable and dangerous outcomes, which could be avoided. These diagnostic errors are mainly caused by cognitive biases in the diagnostic reasoning process.Our medical diagnostic decision-making is based on intuitive "System 1" and analytical "System 2" diagnostic decision-making and can be deviated by unconscious cognitive biases.These deviations can be positively influenced on a systemic and an individual level. For the individual, metacognition (internal withdrawal from the decision-making process) and debiasing strategies, such as verification, falsification and rule out worst-case scenarios, can lead to improved diagnostic decisions making.

A Study to Improve the Brazilian Air Force’s Material Management System

DTIC Science & Technology

1991-12-01

of Technology, in June 1990. Permanent Address: Base A6rea de Sio Paulo Instituto de Logistica da Aerongutica 07181 Guarulhos Sio Paulo Brazil 160 Vita...orders instead of more frequent smaller ones, and transportation from vendor to depot, which includes international fees in most cases, would be...optimized by the same reason. The transportation from depots to final users would not be affected, since only changes of depots and changes of material

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

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

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

PubMed

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

2017-01-01

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

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

PubMed

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

2018-01-01

It is a common educational practice for medical students to engage in case-based learning (CBL) exercises by working through clinical cases that have been developed by faculty. While such faculty-developed exercises have educational strengths, there are at least two major drawbacks to learning by this method: the number and diversity of cases is often limited; and students decrease their engagement with CBL cases as they grow accustomed to the teaching method. We sought to explore whether student case creation can address both of these limitations. We also compared student case creation to traditional clinical reasoning sessions in regard to tutorial group effectiveness, perceived gains in clinical reasoning, and quality of student-faculty interaction. Ten first-year medical students participated in a feasibility study wherein they worked in small groups to develop their own patient case around a preassigned diagnosis. Faculty provided feedback on case quality afterwards. Students completed pre- and post-self-assessment surveys. Students and faculty also participated in separate focus groups to compare their case creation experience to traditional CBL sessions. Students reported high levels of team engagement and peer learning, as well as increased ownership over case content and understanding of clinical reasoning nuances. However, students also reported decreases in student-faculty interaction and the use of visual aids ( P < 0.05). The results of our feasibility study suggest that student-generated cases can be a valuable adjunct to traditional clinical reasoning instruction by increasing content ownership, encouraging student-directed learning, and providing opportunities to explore clinical nuances. However, these gains may reduce student-faculty interaction. Future studies may be able to identify an improved model of faculty participation, the ideal timing for incorporation of this method in a medical curriculum, and a more rigorous assessment of the impact of student case creation on the development of clinical reasoning skills.

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

PubMed Central

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

2018-01-01

Background It is a common educational practice for medical students to engage in case-based learning (CBL) exercises by working through clinical cases that have been developed by faculty. While such faculty-developed exercises have educational strengths, there are at least two major drawbacks to learning by this method: the number and diversity of cases is often limited; and students decrease their engagement with CBL cases as they grow accustomed to the teaching method. We sought to explore whether student case creation can address both of these limitations. We also compared student case creation to traditional clinical reasoning sessions in regard to tutorial group effectiveness, perceived gains in clinical reasoning, and quality of student–faculty interaction. Methods Ten first-year medical students participated in a feasibility study wherein they worked in small groups to develop their own patient case around a preassigned diagnosis. Faculty provided feedback on case quality afterwards. Students completed pre- and post-self-assessment surveys. Students and faculty also participated in separate focus groups to compare their case creation experience to traditional CBL sessions. Results Students reported high levels of team engagement and peer learning, as well as increased ownership over case content and understanding of clinical reasoning nuances. However, students also reported decreases in student–faculty interaction and the use of visual aids (P < 0.05). Conclusion The results of our feasibility study suggest that student-generated cases can be a valuable adjunct to traditional clinical reasoning instruction by increasing content ownership, encouraging student-directed learning, and providing opportunities to explore clinical nuances. However, these gains may reduce student–faculty interaction. Future studies may be able to identify an improved model of faculty participation, the ideal timing for incorporation of this method in a medical curriculum, and a more rigorous assessment of the impact of student case creation on the development of clinical reasoning skills. PMID:29692641

Heating Analysis in Constant-pressure Hydraulic System based on Energy Analysis

NASA Astrophysics Data System (ADS)

Wu, Chao; Xu, Cong; Mao, Xuyao; Li, Bin; Hu, Junhua; Liu, Yiou

2017-12-01

Hydraulic systems are widely used in industrial applications, but the problem of heating has become an important reason to restrict the promotion of hydraulic technology. The high temperature, will seriously affect the operation of the hydraulic system, even cause stuck and other serious failure. Based on the analysis of the heat damage of the hydraulic system, this paper gives the reasons for this problem, and it is showed by the application that the energy analysis can accurately locate the main reasons for the heating of the hydraulic system, which can give strong practical guidance.

Autonomous Distributed Congestion Control Scheme in WCDMA Network

NASA Astrophysics Data System (ADS)

Ahmad, Hafiz Farooq; Suguri, Hiroki; Choudhary, Muhammad Qaisar; Hassan, Ammar; Liaqat, Ali; Khan, Muhammad Umer

Wireless technology has become widely popular and an important means of communication. A key issue in delivering wireless services is the problem of congestion which has an adverse impact on the Quality of Service (QoS), especially timeliness. Although a lot of work has been done in the context of RRM (Radio Resource Management), the deliverance of quality service to the end user still remains a challenge. Therefore there is need for a system that provides real-time services to the users through high assurance. We propose an intelligent agent-based approach to guarantee a predefined Service Level Agreement (SLA) with heterogeneous user requirements for appropriate bandwidth allocation in QoS sensitive cellular networks. The proposed system architecture exploits Case Based Reasoning (CBR) technique to handle RRM process of congestion management. The system accomplishes predefined SLA through the use of Retrieval and Adaptation Algorithm based on CBR case library. The proposed intelligent agent architecture gives autonomy to Radio Network Controller (RNC) or Base Station (BS) in accepting, rejecting or buffering a connection request to manage system bandwidth. Instead of simply blocking the connection request as congestion hits the system, different buffering durations are allocated to diverse classes of users based on their SLA. This increases the opportunity of connection establishment and reduces the call blocking rate extensively in changing environment. We carry out simulation of the proposed system that verifies efficient performance for congestion handling. The results also show built-in dynamism of our system to cater for variety of SLA requirements.

Production system with process quality control: modelling and application

NASA Astrophysics Data System (ADS)

Tsou, Jia-Chi

2010-07-01

Over the past decade, there has been a great deal of research dedicated to the study of quality and the economics of production. In this article, we develop a dynamic model which is based on the hypothesis of a traditional economic production quantity model. Taguchi's cost of poor quality is used to evaluate the cost of poor quality in the dynamic production system. A practical case from the automotive industry, which uses the Six-sigma DMAIC methodology, is discussed to verify the proposed model. This study shows that there is an optimal value of quality investment to make the production system reach a reasonable quality level and minimise the production cost. Based on our model, the management can adjust its investment in quality improvement to generate considerable financial return.

A Design of Product Collaborative Online Configuration Model

NASA Astrophysics Data System (ADS)

Wang, Xiaoguo; Zheng, Jin; Zeng, Qian

According to the actual needs of mass customization, the personalization of product and its collaborative design, the paper analyzes and studies the working mechanism of modular-based product configuration technology and puts forward an information model of modular product family. Combined with case-based reasoning techniques (CBR) and the constraint satisfaction problem solving techniques (CSP), we design and study the algorithm for product configuration, and analyze its time complexity. A car chassis is made as the application object, we provide a prototype system of online configuration. Taking advantage of this system, designers can make appropriate changes on the existing programs in accordance with the demand. This will accelerate all aspects of product development and shorten the product cycle. Also the system will provide a strong technical support for enterprises to improve their market competitiveness.

Monitoring Reasons for Encounter via an Electronic Patient Record System: the Case of a Rural Practice Initiative

PubMed Central

Klinis, Spyridon; Markaki, Adelais; Kounalakis, Dimitrios; Symvoulakis, Emmanouil K.

2012-01-01

The objective of this brief communication was to tabulate common reasons for encounter in a Greek rural general practice, as result of a recently adopted electronic patient record (EPR) application. Twenty encounter reasons accounted for 3,797 visits (61% of all patient encounters), whereas 565 other reasons accounted for the remaining 2,429 visits (39%). Number one reason for encounter was health maintenance or disease prevention seeking services, including screening examinations for malignancies, immunization and provision of medical opinion reports. Hypertension, lipid disorder and ischemic heart disease without angina were among the most common reasons for seeking care. A strengths/weaknesses/opportunities/threats (SWOT) analysis on the key role of an EPR system in collecting data from rural and remote primary health care settings is also presented. PMID:23091407

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.

Proceedings of the Seventh International Symposium on Methodologies for Intelligent Systems (Poster Session)

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

Harber, K.S.

1993-05-01

This report contains the following papers: Implications in vivid logic; a self-learning bayesian expert system; a natural language generation system for a heterogeneous distributed database system; competence-switching'' managed by intelligent systems; strategy acquisition by an artificial neural network: Experiments in learning to play a stochastic game; viewpoints and selective inheritance in object-oriented modeling; multivariate discretization of continuous attributes for machine learning; utilization of the case-based reasoning method to resolve dynamic problems; formalization of an ontology of ceramic science in CLASSIC; linguistic tools for intelligent systems; an application of rough sets in knowledge synthesis; and a relational model for imprecise queries.more » These papers have been indexed separately.« less

Proceedings of the Seventh International Symposium on Methodologies for Intelligent Systems (Poster Session)

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

Harber, K.S.

1993-05-01

This report contains the following papers: Implications in vivid logic; a self-learning Bayesian Expert System; a natural language generation system for a heterogeneous distributed database system; ``competence-switching`` managed by intelligent systems; strategy acquisition by an artificial neural network: Experiments in learning to play a stochastic game; viewpoints and selective inheritance in object-oriented modeling; multivariate discretization of continuous attributes for machine learning; utilization of the case-based reasoning method to resolve dynamic problems; formalization of an ontology of ceramic science in CLASSIC; linguistic tools for intelligent systems; an application of rough sets in knowledge synthesis; and a relational model for imprecise queries.more » These papers have been indexed separately.« less

"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…

Validating agent oriented methodology (AOM) for netlogo modelling and simulation

NASA Astrophysics Data System (ADS)

WaiShiang, Cheah; Nissom, Shane; YeeWai, Sim; Sharbini, Hamizan

2017-10-01

AOM (Agent Oriented Modeling) is a comprehensive and unified agent methodology for agent oriented software development. AOM methodology was proposed to aid developers with the introduction of technique, terminology, notation and guideline during agent systems development. Although AOM methodology is claimed to be capable of developing a complex real world system, its potential is yet to be realized and recognized by the mainstream software community and the adoption of AOM is still at its infancy. Among the reason is that there are not much case studies or success story of AOM. This paper presents two case studies on the adoption of AOM for individual based modelling and simulation. It demonstrate how the AOM is useful for epidemiology study and ecological study. Hence, it further validate the AOM in a qualitative manner.

Expert Witness: A system for developing expert medical testimony

NASA Technical Reports Server (NTRS)

Lewandowski, Raymond; Perkins, David; Leasure, David

1994-01-01

Expert Witness in an expert system designed to assist attorneys and medical experts in determining the merit of medical malpractice claims in the area of obstetrics. It substitutes the time of the medical expert with the time of a paralegal assistant guided by the expert system during the initial investigation of the medical records and patient interviews. The product of the system is a narrative transcript containing important data, immediate conclusions from the data, and overall conclusions of the case that the attorney and medical expert use to make decisions about whether and how to proceed with the case. The transcript may also contain directives for gathering additional information needed for the case. The system is a modified heuristic classifier and is implemented using over 600 CLIPS rules together with a C-based user interface. The data abstraction and solution refinement are implemented directly using forward chaining production and matching. The use of CLIPS and C is essential to delivering a system that runs on a generic PC platform. The direct implementation in CLIPS together with locality of inference ensures that the system will scale gracefully. Two years of use has revealed no errors in the reasoning.

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.

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.

Towards Measurement of Confidence in Safety Cases

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

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.

Energy Optimization Using a Case-Based Reasoning Strategy

PubMed Central

Herrera-Viedma, Enrique

2018-01-01

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

Energy Optimization Using a Case-Based Reasoning Strategy.

PubMed

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

2018-03-15

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

Choosing Open Source ERP Systems: What Reasons Are There For Doing So?

NASA Astrophysics Data System (ADS)

Johansson, Björn; Sudzina, Frantisek

Enterprise resource planning (ERP) systems attract a high attention and open source software does it as well. The question is then if, and if so, when do open source ERP systems take off. The paper describes the status of open source ERP systems. Based on literature review of ERP system selection criteria based on Web of Science articles, it discusses reported reasons for choosing open source or proprietary ERP systems. Last but not least, the article presents some conclusions that could act as input for future research. The paper aims at building up a foundation for the basic question: What are the reasons for an organization to adopt open source ERP systems.

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

PubMed Central

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

2017-01-01

Objectives Important differences exist between closed-system and open-system e-cigarettes, but it is unknown whether online companies are marketing these devices differently and whether consumer reasons for using e-cigarettes vary by device type. This paper compares Internet-based advertising claims of closed- versus open-system products, and evaluates US consumers’ reasons for using closed- versus open-system e-cigarettes. Methods Internet sites selling exclusively closed (N = 130) or open (N = 129) e-cigarettes in December 2013–January 2014 were coded for advertising claims. Current users (≥18 years old) of exclusively closed or open e-cigarettes (N = 860) in a nationally representative online survey in February–March 2014 provided their main reason for using e-cigarettes. Results Internet sites that exclusively sold closed-system e-cigarettes were more likely to make cigarette-related claims such as e-cigarettes being healthier and cheaper than cigarettes (ps < .0001) compared to sites selling open systems. Many sites implied their products could help smokers quit. Exclusive users of both systems endorsed cessation as their top reason. Closed-system users were more likely to report their reason as “use where smoking is banned.” Conclusions Although promotion of e-cigarettes as cessation aids is prohibited, consumers of both systems endorsed smoking cessation as their top reason for using e-cigarettes. PMID:29104902

Approximate reasoning using terminological models

NASA Technical Reports Server (NTRS)

Yen, John; Vaidya, Nitin

1992-01-01

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

Applying knowledge compilation techniques to model-based reasoning

NASA Technical Reports Server (NTRS)

Keller, Richard M.

1991-01-01

Researchers in the area of knowledge compilation are developing general purpose techniques for improving the efficiency of knowledge-based systems. In this article, an attempt is made to define knowledge compilation, to characterize several classes of knowledge compilation techniques, and to illustrate how some of these techniques can be applied to improve the performance of model-based reasoning systems.

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.

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.

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

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

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

PubMed Central

2011-01-01

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

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

PubMed

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

2011-10-27

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

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.

GreenVMAS: Virtual Organization Based Platform for Heating Greenhouses Using Waste Energy from Power Plants.

PubMed

González-Briones, Alfonso; Chamoso, Pablo; Yoe, Hyun; Corchado, Juan M

2018-03-14

The gradual depletion of energy resources makes it necessary to optimize their use and to reuse them. Although great advances have already been made in optimizing energy generation processes, many of these processes generate energy that inevitably gets wasted. A clear example of this are nuclear, thermal and carbon power plants, which lose a large amount of energy that could otherwise be used for different purposes, such as heating greenhouses. The role of GreenVMAS is to maintain the required temperature level in greenhouses by using the waste energy generated by power plants. It incorporates a case-based reasoning system, virtual organizations and algorithms for data analysis and for efficient interaction with sensors and actuators. The system is context aware and scalable as it incorporates an artificial neural network, this means that it can operate correctly even if the number and characteristics of the greenhouses participating in the case study change. The architecture was evaluated empirically and the results show that the user's energy bill is greatly reduced with the implemented system.

GreenVMAS: Virtual Organization Based Platform for Heating Greenhouses Using Waste Energy from Power Plants

PubMed Central

Yoe, Hyun

2018-01-01

The gradual depletion of energy resources makes it necessary to optimize their use and to reuse them. Although great advances have already been made in optimizing energy generation processes, many of these processes generate energy that inevitably gets wasted. A clear example of this are nuclear, thermal and carbon power plants, which lose a large amount of energy that could otherwise be used for different purposes, such as heating greenhouses. The role of GreenVMAS is to maintain the required temperature level in greenhouses by using the waste energy generated by power plants. It incorporates a case-based reasoning system, virtual organizations and algorithms for data analysis and for efficient interaction with sensors and actuators. The system is context aware and scalable as it incorporates an artificial neural network, this means that it can operate correctly even if the number and characteristics of the greenhouses participating in the case study change. The architecture was evaluated empirically and the results show that the user’s energy bill is greatly reduced with the implemented system. PMID:29538351

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.

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

PubMed

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

2011-09-01

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

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.

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.

The Kaiser Permanente shoulder arthroplasty registry: results from 6,336 primary shoulder arthroplasties.

PubMed

Dillon, Mark T; Ake, Christopher F; Burke, Mary F; Singh, Anshuman; Yian, Edward H; Paxton, Elizabeth W; Navarro, Ronald A

2015-06-01

Shoulder arthroplasty is being performed in the United States with increasing frequency. We describe the medium-term findings from a large integrated healthcare system shoulder arthroplasty registry. Shoulder arthroplasty cases registered between January 2005 and June 2013 were included for analysis. The registry included patient characteristics, surgical information, implant data, attrition, and patient outcomes such as surgical site infections, venous thromboembolism, and revision procedures. During the study period, 6,336 primary cases were registered. Median follow-up time for all primaries was 3.3 years; 461 cases were lost to follow-up by ending of health plan membership. Primary cases were predominantly female (56%) and white (81%), with an average age of 70 years. The most common reason for surgery was osteoarthritis in 60% of cases, followed by acute fracture (17%) and rotator cuff tear arthropathy (15%). In elective shoulder arthroplasty procedures, 200 all-cause revisions (4%) were reported, with glenoid wear being the most common reason. Most arthroplasties were elective procedures: over half performed for osteoarthritis. Glenoid wear was the most common reason for revision of primary shoulder arthroplasty in elective cases.

Reducing the Conflict Factors Strategies in Question Answering System

NASA Astrophysics Data System (ADS)

Suwarningsih, W.; Purwarianti, A.; Supriana, I.

2017-03-01

A rule-based system is prone to conflict as new knowledge every time will emerge and indirectly must sign in to the knowledge base that is used by the system. A conflict occurred between the rules in the knowledge base can lead to the errors of reasoning or reasoning circulation. Therefore, when added, the new rules will lead to conflict with other rules, and the only rules that really can be added to the knowledge base. From these conditions, this paper aims to propose a conflict resolution strategy for a medical debriefing system by analyzing scenarios based upon the runtime to improve the efficiency and reliability of systems.

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)

Defining and describing birth centres in the Netherlands - a component study of the Dutch Birth Centre Study.

PubMed

Hermus, M A A; Boesveld, I C; Hitzert, M; Franx, A; de Graaf, J P; Steegers, E A P; Wiegers, T A; van der Pal-de Bruin, K M

2017-07-03

During the last decade, a rapid increase of birth locations for low-risk births, other than conventional obstetric units, has been seen in the Netherlands. Internationally some of such locations are called birth centres. The varying international definitions for birth centres are not directly applicable for use within the Dutch obstetric system. A standard definition for a birth centre in the Netherlands is lacking. This study aimed to develop a definition of birth centres for use in the Netherlands, to identify these centres and to describe their characteristics. International definitions of birth centres were analysed to find common descriptions. In July 2013 the Dutch Birth Centre Questionnaire was sent to 46 selected Dutch birth locations that might qualify as birth centre. Questions included: location, reason for establishment, women served, philosophies, facilities that support physiological birth, hotel-facilities, management, environment and transfer procedures in case of referral. Birth centres were visited to confirm the findings from the Dutch Birth Centre Questionnaire and to measure distance and time in case of referral to obstetric care. From all 46 birth locations the questionnaires were received. Based on this information a Dutch definition of a birth centre was constructed. This definition reads: "Birth centres are midwifery-managed locations that offer care to low risk women during labour and birth. They have a homelike environment and provide facilities to support physiological birth. Community midwives take primary professional responsibility for care. In case of referral the obstetric caregiver takes over the professional responsibility of care." Of the 46 selected birth locations 23 fulfilled this definition. Three types of birth centres were distinguished based on their location in relation to the nearest obstetric unit: freestanding (n = 3), alongside (n = 14) and on-site (n = 6). Transfer in case of referral was necessary for all freestanding and alongside birth centres. Birth centres varied in their reason for establishment and their characteristics. Twenty-three Dutch birth centres were identified and divided into three different types based on location according to the situation in September 2013. Birth centres differed in their reason for establishment, facilities, philosophies, staffing and service delivery.

Qualitative Discovery in Medical Databases

NASA Technical Reports Server (NTRS)

Maluf, David A.

2000-01-01

Implication rules have been used in uncertainty reasoning systems to confirm and draw hypotheses or conclusions. However a major bottleneck in developing such systems lies in the elicitation of these rules. This paper empirically examines the performance of evidential inferencing with implication networks generated using a rule induction tool called KAT. KAT utilizes an algorithm for the statistical analysis of empirical case data, and hence reduces the knowledge engineering efforts and biases in subjective implication certainty assignment. The paper describes several experiments in which real-world diagnostic problems were investigated; namely, medical diagnostics. In particular, it attempts to show that: (1) with a limited number of case samples, KAT is capable of inducing implication networks useful for making evidential inferences based on partial observations, and (2) observation driven by a network entropy optimization mechanism is effective in reducing the uncertainty of predicted events.

Elderly Healthcare Monitoring Using an Avatar-Based 3D Virtual Environment

PubMed Central

Pouke, Matti; Häkkilä, Jonna

2013-01-01

Homecare systems for elderly people are becoming increasingly important due to both economic reasons as well as patients’ preferences. Sensor-based surveillance technologies are an expected future trend, but research so far has devoted little attention to the User Interface (UI) design of such systems and the user-centric design approach. In this paper, we explore the possibilities of an avatar-based 3D visualization system, which exploits wearable sensors and human activity simulations. We present a technical prototype and the evaluation of alternative concept designs for UIs based on a 3D virtual world. The evaluation was conducted with homecare providers through focus groups and an online survey. Our results show firstly that systems taking advantage of 3D virtual world visualization techniques have potential especially due to the privacy preserving and simplified information presentation style, and secondly that simple representations and glancability should be emphasized in the design. The identified key use cases highlight that avatar-based 3D presentations can be helpful if they provide an overview as well as details on demand. PMID:24351747

Automated extraction of knowledge for model-based diagnostics

NASA Technical Reports Server (NTRS)

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

1990-01-01

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

Alzheimer's disease and the law: positive and negative consequences of structural stigma and labeling in the legal system.

PubMed

Werner, Perla; Doron, Israel Issi

2017-11-01

To explore the meaning and consequences of labeling on structural stigma in the context of Alzheimer's disease (AD) in the legal system. This qualitative study was made up of three focus groups including social workers and lawyers (n = 26). Participants were asked to report their experience in circumstances in which persons with AD and their family members engage with the legal system. Thematic analysis using the constant comparative method was used. The discussions in the focus groups raised two overall themes. (1) The significance of the medical diagnostic labeling of AD in the legal system and (2) the consequences of labeling of AD within the legal system. This last theme included four sub-themes: (a) negative consequences of labeling; (b) reasons associated with negative consequences of labeling; (c) positive consequences of labeling; and (d) reasons associated with positive consequences of labeling. Findings of the study provide a first foundation for future research on the meaning and consequences of labeling in legal cases involving persons with AD. They suggest that increasing judges' knowledge about AD and reforming the existing 'status-based' legal capacity legislation might benefit by limiting the legal weight given today to the medical diagnosis.

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

PubMed

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

2017-01-01

Capturing complete medical knowledge is challenging-often due to incomplete patient Electronic Health Records (EHR), but also because of valuable, tacit medical knowledge hidden away in physicians' experiences. To extend the coverage of incomplete medical knowledge-based systems beyond their deductive closure, and thus enhance their decision-support capabilities, we argue that innovative, multi-strategy reasoning approaches should be applied. In particular, plausible reasoning mechanisms apply patterns from human thought processes, such as generalization, similarity and interpolation, based on attributional, hierarchical, and relational knowledge. Plausible reasoning mechanisms include inductive reasoning , which generalizes the commonalities among the data to induce new rules, and analogical reasoning , which is guided by data similarities to infer new facts. By further leveraging rich, biomedical Semantic Web ontologies to represent medical knowledge, both known and tentative, we increase the accuracy and expressivity of plausible reasoning, and cope with issues such as data heterogeneity, inconsistency and interoperability. In this paper, we present a Semantic Web-based, multi-strategy reasoning approach, which integrates deductive and plausible reasoning and exploits Semantic Web technology to solve complex clinical decision support queries. We evaluated our system using a real-world medical dataset of patients with hepatitis, from which we randomly removed different percentages of data (5%, 10%, 15%, and 20%) to reflect scenarios with increasing amounts of incomplete medical knowledge. To increase the reliability of the results, we generated 5 independent datasets for each percentage of missing values, which resulted in 20 experimental datasets (in addition to the original dataset). The results show that plausibly inferred knowledge extends the coverage of the knowledge base by, on average, 2%, 7%, 12%, and 16% for datasets with, respectively, 5%, 10%, 15%, and 20% of missing values. This expansion in the KB coverage allowed solving complex disease diagnostic queries that were previously unresolvable, without losing the correctness of the answers. However, compared to deductive reasoning, data-intensive plausible reasoning mechanisms yield a significant performance overhead. We observed that plausible reasoning approaches, by generating tentative inferences and leveraging domain knowledge of experts, allow us to extend the coverage of medical knowledge bases, resulting in improved clinical decision support. Second, by leveraging OWL ontological knowledge, we are able to increase the expressivity and accuracy of plausible reasoning methods. Third, our approach is applicable to clinical decision support systems for a range of chronic diseases.

Consultant-based otolaryngology emergency service: a five-year experience.

PubMed

Barnes, M L; Hussain, S S M

2011-12-01

To present our experience of running a consultant-based otolaryngology emergency care service for more than five years. In 2003, we developed a system of consultant-based emergency service: consultants spent a week on-call providing a dedicated emergency service, with routine commitments cancelled. Our new system had advantages over traditional working practices in terms of consultant involvement, trainee education, continuity and efficiency. It also reduced disruption to elective commitments for both consultants and registrars. This system was fundamental to the successful review of all urgent (and in future elective) cases within target periods. Only 31 per cent of new referrals to the consultant emergency clinics required a further appointment. Good teamwork and flexibility in working arrangements have been essential to the success of this service. Given that health service changes have reduced junior trainee working hours and numbers, and that patients increasingly expect to be treated by trained doctors, our new consultant-based emergency service has merit. Although implementation in other units may differ, we recommend this new service, for the above reasons.

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

Multimodal navigated skull base tumor resection using image-based vascular and cranial nerve segmentation: A prospective pilot study.

PubMed

Dolati, Parviz; Gokoglu, Abdulkerim; Eichberg, Daniel; Zamani, Amir; Golby, Alexandra; Al-Mefty, Ossama

2015-01-01

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. 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. 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. 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.

Still-Born Autonomy Insurance Plan in Quebec: An Example of a Public Long-Term Care Insurance System in Canada.

PubMed

Hébert, Réjean

2016-01-01

Funding long-term care (LTC) is a challenge under the existing Beveridgean universal healthcare system. The Autonomy Insurance (AI) plan developed in Quebec was an attempt to introduce public LTC insurance into our healthcare system. The AI benefit was based on an assessment of the needs of older people and those with disabilities using a disability scale (SMAF) and case-mix classification system (Iso-SMAF Profiles). Under the plan, the benefit would be used to fund public institutions or purchase services from private organizations. Case managers were responsible for assessments and helping users and their families plan services and decide how to use the AI benefit. Funding AI was based on general tax revenues without capitalized funding, under a separate protected budget program. Projections were made for the additional budget needed to support AI, which would have mitigated the forecast increase in LTC spending due to population aging. All the legal, administrative, funding, training and contractual issues were dealt with, for implementation of the plan in April 2015. Unfortunately, the project was still-born for political reasons, but it demonstrates the feasibility of this essential innovation for Canada.

[Definition of hospital discharge, serious injury and death from traffic injuries].

PubMed

Pérez, Katherine; Seguí-Gómez, María; Arrufat, Vita; Barberia, Eneko; Cabeza, Elena; Cirera, Eva; Gil, Mercedes; Martín, Carlos; Novoa, Ana M; Olabarría, Marta; Lardelli, Pablo; Suelves, Josep Maria; Santamariña-Rubio, Elena

2014-01-01

Road traffic injury surveillance involves methodological difficulties due, among other reasons, to the lack of consensus criteria for case definition. Police records have usually been the main source of information for monitoring traffic injuries, while health system data has hardly been used. Police records usually include comprehensive information on the characteristics of the crash, but often underreport injury cases and do not collect reliable information on the severity of injuries. However, statistics on severe traffic injuries have been based almost exclusively on police data. The aim of this paper is to propose criteria based on medical records to define: a) "Hospital discharge for traffic injuries", b) "Person with severe traffic injury", and c) "Death from traffic injuries" in order to homogenize the use of these sources. Copyright © 2014. Published by Elsevier Espana.

Medical education and cognitive continuum theory: an alternative perspective on medical problem solving and clinical reasoning.

PubMed

Custers, Eugène J F M

2013-08-01

Recently, human reasoning, problem solving, and decision making have been viewed as products of two separate systems: "System 1," the unconscious, intuitive, or nonanalytic system, and "System 2," the conscious, analytic, or reflective system. This view has penetrated the medical education literature, yet the idea of two independent dichotomous cognitive systems is not entirely without problems.This article outlines the difficulties of this "two-system view" and presents an alternative, developed by K.R. Hammond and colleagues, called cognitive continuum theory (CCT). CCT is featured by three key assumptions. First, human reasoning, problem solving, and decision making can be arranged on a cognitive continuum, with pure intuition at one end, pure analysis at the other, and a large middle ground called "quasirationality." Second, the nature and requirements of the cognitive task, as perceived by the person performing the task, determine to a large extent whether a task will be approached more intuitively or more analytically. Third, for optimal task performance, this approach needs to match the cognitive properties and requirements of the task. Finally, the author makes a case that CCT is better able than a two-system view to describe medical problem solving and clinical reasoning and that it provides clear clues for how to organize training in clinical reasoning.

The Brain Network for Deductive Reasoning: A Quantitative Meta-analysis of 28 Neuroimaging Studies

PubMed Central

Prado, Jérôme; Chadha, Angad; Booth, James R.

2011-01-01

Over the course of the past decade, contradictory claims have been made regarding the neural bases of deductive reasoning. Researchers have been puzzled by apparent inconsistencies in the literature. Some have even questioned the effectiveness of the methodology used to study the neural bases of deductive reasoning. However, the idea that neuroimaging findings are inconsistent is not based on any quantitative evidence. Here, we report the results of a quantitative meta-analysis of 28 neuroimaging studies of deductive reasoning published between 1997 and 2010, combining 382 participants. Consistent areas of activations across studies were identified using the multilevel kernel density analysis method. We found that results from neuroimaging studies are more consistent than what has been previously assumed. Overall, studies consistently report activations in specific regions of a left fronto-parietal system, as well as in the left Basal Ganglia. This brain system can be decomposed into three subsystems that are specific to particular types of deductive arguments: relational, categorical, and propositional. These dissociations explain inconstancies in the literature. However, they are incompatible with the notion that deductive reasoning is supported by a single cognitive system relying either on visuospatial or rule-based mechanisms. Our findings provide critical insight into the cognitive organization of deductive reasoning and need to be accounted for by cognitive theories. PMID:21568632

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

NASA Astrophysics Data System (ADS)

Huang, Chao-Hui; Racoceanu, Daniel

2017-03-01

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

78 FR 2695 - Privacy Act of 1974; System of Records

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-14

... data elements used in the Workplace Environment Tracking System (WETS), a new electronic national..., Workplace Harassment Fact Finding, Threat Assessment Case Tracking, and Workplace Environment Intervention... tracking system for these four processes will reasonably assure that workplace harassment policies and...

Automated Assume-Guarantee Reasoning for Omega-Regular Systems and Specifications

NASA Technical Reports Server (NTRS)

Chaki, Sagar; Gurfinkel, Arie

2010-01-01

We develop a learning-based automated Assume-Guarantee (AG) reasoning framework for verifying omega-regular properties of concurrent systems. We study the applicability of non-circular (AGNC) and circular (AG-C) AG proof rules in the context of systems with infinite behaviors. In particular, we show that AG-NC is incomplete when assumptions are restricted to strictly infinite behaviors, while AG-C remains complete. We present a general formalization, called LAG, of the learning based automated AG paradigm. We show how existing approaches for automated AG reasoning are special instances of LAG.We develop two learning algorithms for a class of systems, called infinite regular systems, that combine finite and infinite behaviors. We show that for infinity-regular systems, both AG-NC and AG-C are sound and complete. Finally, we show how to instantiate LAG to do automated AG reasoning for infinite regular, and omega-regular, systems using both AG-NC and AG-C as proof rules

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

NASA Technical Reports Server (NTRS)

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

1992-01-01

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

Examining the Influence of Context and Professional Culture on Clinical Reasoning Through Rhetorical-Narrative Analysis.

PubMed

Peters, Amanda; Vanstone, Meredith; Monteiro, Sandra; Norman, Geoff; Sherbino, Jonathan; Sibbald, Matthew

2017-05-01

According to the dual process model of reasoning, physicians make diagnostic decisions using two mental systems: System 1, which is rapid, unconscious, and intuitive, and System 2, which is slow, rational, and analytical. Currently, little is known about physicians' use of System 1 or intuitive reasoning in practice. In a qualitative study of clinical reasoning, physicians were asked to tell stories about times when they used intuitive reasoning while working up an acutely unwell patient, and we combine socio-narratology and rhetorical theory to analyze physicians' stories. Our analysis reveals that in describing their work, physicians draw on two competing narrative structures: one that is aligned with an evidence-based medicine approach valuing System 2 and one that is aligned with cooperative decision making involving others in the clinical environment valuing System 1. Our findings support an understanding of clinical reasoning as distributed, contextual, and influenced by professional culture.

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

Model-based reasoning for system and software engineering: The Knowledge From Pictures (KFP) environment

NASA Technical Reports Server (NTRS)

Bailin, Sydney; Paterra, Frank; Henderson, Scott; Truszkowski, Walt

1993-01-01

This paper presents a discussion of current work in the area of graphical modeling and model-based reasoning being undertaken by the Automation Technology Section, Code 522.3, at Goddard. The work was initially motivated by the growing realization that the knowledge acquisition process was a major bottleneck in the generation of fault detection, isolation, and repair (FDIR) systems for application in automated Mission Operations. As with most research activities this work started out with a simple objective: to develop a proof-of-concept system demonstrating that a draft rule-base for a FDIR system could be automatically realized by reasoning from a graphical representation of the system to be monitored. This work was called Knowledge From Pictures (KFP) (Truszkowski et. al. 1992). As the work has successfully progressed the KFP tool has become an environment populated by a set of tools that support a more comprehensive approach to model-based reasoning. This paper continues by giving an overview of the graphical modeling objectives of the work, describing the three tools that now populate the KFP environment, briefly presenting a discussion of related work in the field, and by indicating future directions for the KFP environment.

[Malaria in Poland in 2009].

PubMed

Stepiń, Małgorzata

2011-01-01

In Poland in 2009 were reported 22 malaria cases confirmed according to the EU case definition for the purposes of routine surveillance system. All of them were imported, including 1 case of recrudescence, 86% from Africa. In 18 cases P falciparum etiology was confirmed and in 2--P vivax, in 1--P ovale and 1 P malariae. Most cases occurred in the age group 21-40 years, there were 21 cases in males and 1 in female. Common reasons for travel to endemic countries were work-related visits (14 cases) and tourism (6 cases), one person who visited the family and in one case unknown reason for travel. Three persons used chemoprophylaxis during their travel but only one of them appropriately, relevant information was missing in 5 cases. Clinical course was severe in 7 cases of P falciparum malaria and medium-severe in one case. In 2009, there were no malaria deaths in Poland. Education on the prevention of malaria and pretravel health advising is still greatly needed.

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.

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

USGS Publications Warehouse

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

2018-01-01

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

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

PubMed

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

2018-01-01

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

Fault diagnosis

NASA Technical Reports Server (NTRS)

Abbott, Kathy

1990-01-01

The objective of the research in this area of fault management is to develop and implement a decision aiding concept for diagnosing faults, especially faults which are difficult for pilots to identify, and to develop methods for presenting the diagnosis information to the flight crew in a timely and comprehensible manner. The requirements for the diagnosis concept were identified by interviewing pilots, analyzing actual incident and accident cases, and examining psychology literature on how humans perform diagnosis. The diagnosis decision aiding concept developed based on those requirements takes abnormal sensor readings as input, as identified by a fault monitor. Based on these abnormal sensor readings, the diagnosis concept identifies the cause or source of the fault and all components affected by the fault. This concept was implemented for diagnosis of aircraft propulsion and hydraulic subsystems in a computer program called Draphys (Diagnostic Reasoning About Physical Systems). Draphys is unique in two important ways. First, it uses models of both functional and physical relationships in the subsystems. Using both models enables the diagnostic reasoning to identify the fault propagation as the faulted system continues to operate, and to diagnose physical damage. Draphys also reasons about behavior of the faulted system over time, to eliminate possibilities as more information becomes available, and to update the system status as more components are affected by the fault. The crew interface research is examining display issues associated with presenting diagnosis information to the flight crew. One study examined issues for presenting system status information. One lesson learned from that study was that pilots found fault situations to be more complex if they involved multiple subsystems. Another was pilots could identify the faulted systems more quickly if the system status was presented in pictorial or text format. Another study is currently under way to examine pilot mental models of the aircraft subsystems and their use in diagnosis tasks. Future research plans include piloted simulation evaluation of the diagnosis decision aiding concepts and crew interface issues. Information is given in viewgraph form.

Practical and generalizable architecture for an intelligent tutoring system

NASA Astrophysics Data System (ADS)

Kaplan, Randy M.; Trenholm, Harriet

1993-03-01

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

32 CFR 37.705 - What standards do I include for purchasing systems of for-profit firms?

Code of Federal Regulations, 2011 CFR

2011-07-01

... SECRETARY OF DEFENSE DoD GRANT AND AGREEMENT REGULATIONS TECHNOLOGY INVESTMENT AGREEMENTS Award Terms... programmatic or business reasons to do otherwise (in which case you must document the reasons in the award file... orders or Governmentwide regulations (see appendix E to this part for a list of those requirements). (c...

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

PubMed

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

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

A GIS-based modeling system for petroleum waste management. Geographical information system.

PubMed

Chen, Z; Huang, G H; Li, J B

2003-01-01

With an urgent need for effective management of petroleum-contaminated sites, a GIS-aided simulation (GISSIM) system is presented in this study. The GISSIM contains two components: an advanced 3D numerical model and a geographical information system (GIS), which are integrated within a general framework. The modeling component undertakes simulation for the fate of contaminants in subsurface unsaturated and saturated zones. The GIS component is used in three areas throughout the system development and implementation process: (i) managing spatial and non-spatial databases; (ii) linking inputs, model, and outputs; and (iii) providing an interface between the GISSIM and its users. The developed system is applied to a North American case study. Concentrations of benzene, toluene, and xylenes in groundwater under a petroleum-contaminated site are dynamically simulated. Reasonable outputs have been obtained and presented graphically. They provide quantitative and scientific bases for further assessment of site-contamination impacts and risks, as well as decisions on practical remediation actions.

Toward sensor-based context aware systems.

PubMed

Sakurai, Yoshitaka; Takada, Kouhei; Anisetti, Marco; Bellandi, Valerio; Ceravolo, Paolo; Damiani, Ernesto; Tsuruta, Setsuo

2012-01-01

This paper proposes a methodology for sensor data interpretation that can combine sensor outputs with contexts represented as sets of annotated business rules. Sensor readings are interpreted to generate events labeled with the appropriate type and level of uncertainty. Then, the appropriate context is selected. Reconciliation of different uncertainty types is achieved by a simple technique that moves uncertainty from events to business rules by generating combs of standard Boolean predicates. Finally, context rules are evaluated together with the events to take a decision. The feasibility of our idea is demonstrated via a case study where a context-reasoning engine has been connected to simulated heartbeat sensors using prerecorded experimental data. We use sensor outputs to identify the proper context of operation of a system and trigger decision-making based on context information.

A situated reasoning architecture for space-based repair and replace tasks

NASA Technical Reports Server (NTRS)

Bloom, Ben; Mcgrath, Debra; Sanborn, Jim

1989-01-01

Space-based robots need low level control for collision detection and avoidance, short-term load management, fine-grained motion, and other physical tasks. In addition, higher level control is required to focus strategic decision making as missions are assigned and carried out. Reasoning and control must be responsive to ongoing changes in the environment. Research aimed at bridging the gap between high level artificial intelligence (AI) planning techniques and task-level robot programming for telerobotic systems is described. Situated reasoning is incorporated into AI and Robotics systems in order to coordinate a robot's activity within its environment. An integrated system under development in a component maintenance domain is described. It is geared towards replacing worn and/or failed Orbital Replacement Units (ORUs) designed for use aboard NASA's Space Station Freedom based on the collection of components available at a given time. High level control reasons in component space in order to maximize the number operational component-cells over time, while the task-level controls sensors and effectors, detects collisions, and carries out pick and place tasks in physical space. Situated reasoning is used throughout the system to cope with component failures, imperfect information, and unexpected events.

Knowledge elicitation for an operator assistant system in process control tasks

NASA Technical Reports Server (NTRS)

Boy, Guy A.

1988-01-01

A knowledge based system (KBS) methodology designed to study human machine interactions and levels of autonomy in allocation of process control tasks is presented. Users are provided with operation manuals to assist them in normal and abnormal situations. Unfortunately, operation manuals usually represent only the functioning logic of the system to be controlled. The user logic is often totally different. A method is focused on which illicits user logic to refine a KBS shell called an Operator Assistant (OA). If the OA is to help the user, it is necessary to know what level of autonomy gives the optimal performance of the overall man-machine system. For example, for diagnoses that must be carried out carefully by both the user and the OA, interactions are frequent, and processing is mostly sequential. Other diagnoses can be automated, in which the case the OA must be able to explain its reasoning in an appropriate level of detail. OA structure was used to design a working KBS called HORSES (Human Orbital Refueling System Expert System). Protocol analysis of pilots interacting with this system reveals that the a-priori analytical knowledge becomes more structured with training and the situation patterns more complex and dynamic. This approach can improve the a-priori understanding of human and automatic reasoning.

Heuristic thinking and human intelligence: a commentary on Marewski, Gaissmaier and Gigerenzer.

PubMed

Evans, Jonathan St B T; Over, David E

2010-05-01

Marewski, Gaissmaier and Gigerenzer (2009) present a review of research on fast and frugal heuristics, arguing that complex problems are best solved by simple heuristics, rather than the application of knowledge and logical reasoning. We argue that the case for such heuristics is overrated. First, we point out that heuristics can often lead to biases as well as effective responding. Second, we show that the application of logical reasoning can be both necessary and relatively simple. Finally, we argue that the evidence for a logical reasoning system that co-exists with simpler heuristic forms of thinking is overwhelming. Not only is it implausible a priori that we would have evolved such a system that is of no use to us, but extensive evidence from the literature on dual processing in reasoning and judgement shows that many problems can only be solved when this form of reasoning is used to inhibit and override heuristic thinking.

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

Model-based diagnostics for Space Station Freedom

NASA Technical Reports Server (NTRS)

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

1991-01-01

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

ATS displays: A reasoning visualization tool for expert systems

NASA Technical Reports Server (NTRS)

Selig, William John; Johannes, James D.

1990-01-01

Reasoning visualization is a useful tool that can help users better understand the inherently non-sequential logic of an expert system. While this is desirable in most all expert system applications, it is especially so for such critical systems as those destined for space-based operations. A hierarchical view of the expert system reasoning process and some characteristics of these various levels is presented. Also presented are Abstract Time Slice (ATS) displays, a tool to visualize the plethora of interrelated information available at the host inferencing language level of reasoning. The usefulness of this tool is illustrated with some examples from a prototype potable water expert system for possible use aboard Space Station Freedom.

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.

Reasoning about real-time systems with temporal interval logic constraints on multi-state automata

NASA Technical Reports Server (NTRS)

Gabrielian, Armen

1991-01-01

Models of real-time systems using a single paradigm often turn out to be inadequate, whether the paradigm is based on states, rules, event sequences, or logic. A model-based approach to reasoning about real-time systems is presented in which a temporal interval logic called TIL is employed to define constraints on a new type of high level automata. The combination, called hierarchical multi-state (HMS) machines, can be used to model formally a real-time system, a dynamic set of requirements, the environment, heuristic knowledge about planning-related problem solving, and the computational states of the reasoning mechanism. In this framework, mathematical techniques were developed for: (1) proving the correctness of a representation; (2) planning of concurrent tasks to achieve goals; and (3) scheduling of plans to satisfy complex temporal constraints. HMS machines allow reasoning about a real-time system from a model of how truth arises instead of merely depending of what is true in a system.

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

Rainer, Leo I.; Hoeschele, Marc A.; Apte, Michael G.

This report addresses the results of detailed monitoring completed under Program Element 6 of Lawrence Berkeley National Laboratory's High Performance Commercial Building Systems (HPCBS) PIER program. The purpose of the Energy Simulations and Projected State-Wide Energy Savings project is to develop reasonable energy performance and cost models for high performance relocatable classrooms (RCs) across California climates. A key objective of the energy monitoring was to validate DOE2 simulations for comparison to initial DOE2 performance projections. The validated DOE2 model was then used to develop statewide savings projections by modeling base case and high performance RC operation in the 16 Californiamore » climate zones. The primary objective of this phase of work was to utilize detailed field monitoring data to modify DOE2 inputs and generate performance projections based on a validated simulation model. Additional objectives include the following: (1) Obtain comparative performance data on base case and high performance HVAC systems to determine how they are operated, how they perform, and how the occupants respond to the advanced systems. This was accomplished by installing both HVAC systems side-by-side (i.e., one per module of a standard two module, 24 ft by 40 ft RC) on the study RCs and switching HVAC operating modes on a weekly basis. (2) Develop projected statewide energy and demand impacts based on the validated DOE2 model. (3) Develop cost effectiveness projections for the high performance HVAC system in the 16 California climate zones.« less

Toward cognitive pipelines of medical assistance algorithms.

PubMed

Philipp, Patrick; Maleshkova, Maria; Katic, Darko; Weber, Christian; Götz, Michael; Rettinger, Achim; Speidel, Stefanie; Kämpgen, Benedikt; Nolden, Marco; Wekerle, Anna-Laura; Dillmann, Rüdiger; Kenngott, Hannes; Müller, Beat; Studer, Rudi

2016-09-01

Assistance algorithms for medical tasks have great potential to support physicians with their daily work. However, medicine is also one of the most demanding domains for computer-based support systems, since medical assistance tasks are complex and the practical experience of the physician is crucial. Recent developments in the area of cognitive computing appear to be well suited to tackle medicine as an application domain. We propose a system based on the idea of cognitive computing and consisting of auto-configurable medical assistance algorithms and their self-adapting combination. The system enables automatic execution of new algorithms, given they are made available as Medical Cognitive Apps and are registered in a central semantic repository. Learning components can be added to the system to optimize the results in the cases when numerous Medical Cognitive Apps are available for the same task. Our prototypical implementation is applied to the areas of surgical phase recognition based on sensor data and image progressing for tumor progression mappings. Our results suggest that such assistance algorithms can be automatically configured in execution pipelines, candidate results can be automatically scored and combined, and the system can learn from experience. Furthermore, our evaluation shows that the Medical Cognitive Apps are providing the correct results as they did for local execution and run in a reasonable amount of time. The proposed solution is applicable to a variety of medical use cases and effectively supports the automated and self-adaptive configuration of cognitive pipelines based on medical interpretation algorithms.

Intrusive and Non-Intrusive Instruction in Dynamic Skill Training.

DTIC Science & Technology

1981-10-01

less sensitive to the processing load imposed by the dynaic task together with instructional feedback processing than were the decison - making and...betwee computer based instruction of knowledge systems and computer based instruction of dynamic skills. There is reason to expect that the findings of...knowledge 3Ytm and computer based instruction of dynlamic skill.. There is reason to expect that the findings of research on knowledge system

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.

[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.

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

PubMed

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

2011-08-22

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

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

PubMed Central

2011-01-01

Background We address the goal of curating observations from published experiments in a generalizable form; reasoning over these observations to generate interpretations and then querying this interpreted knowledge to supply the supporting evidence. We present web-application software as part of the 'BioScholar' project (R01-GM083871) that fully instantiates this process for a well-defined domain: using tract-tracing experiments to study the neural connectivity of the rat brain. Results The main contribution of this work is to provide the first instantiation of a knowledge representation for experimental observations called 'Knowledge Engineering from Experimental Design' (KEfED) based on experimental variables and their interdependencies. The software has three parts: (a) the KEfED model editor - a design editor for creating KEfED models by drawing a flow diagram of an experimental protocol; (b) the KEfED data interface - a spreadsheet-like tool that permits users to enter experimental data pertaining to a specific model; (c) a 'neural connection matrix' interface that presents neural connectivity as a table of ordinal connection strengths representing the interpretations of tract-tracing data. This tool also allows the user to view experimental evidence pertaining to a specific connection. BioScholar is built in Flex 3.5. It uses Persevere (a noSQL database) as a flexible data store and PowerLoom® (a mature First Order Logic reasoning system) to execute queries using spatial reasoning over the BAMS neuroanatomical ontology. Conclusions We first introduce the KEfED approach as a general approach and describe its possible role as a way of introducing structured reasoning into models of argumentation within new models of scientific publication. We then describe the design and implementation of our example application: the BioScholar software. This is presented as a possible biocuration interface and supplementary reasoning toolkit for a larger, more specialized bioinformatics system: the Brain Architecture Management System (BAMS). PMID:21859449

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

The selenium content of SEPP1 versus selenium requirements in vertebrates

PubMed Central

Hamre, Kristin; Ellingsen, Ståle

2015-01-01

Selenoprotein P (SEPP1) distributes selenium (Se) throughout the body via the circulatory system. For vertebrates, the Se content of SEPP1 varies from 7 to 18 Se atoms depending on the species, but the reason for this variation remains unclear. Herein we provide evidence that vertebrate SEPP1 Sec content correlates positively with Se requirements. As the Se content of full length SEPP1 is genetically determined, this presents a unique case where a nutrient requirement can be predicted based on genomic sequence information. PMID:26734501

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.

4onse: four times open & non-conventional technology for sensing the environment

NASA Astrophysics Data System (ADS)

Cannata, Massimiliano; Ratnayake, Rangageewa; Antonovic, Milan; Strigaro, Daniele; Cardoso, Mirko; Hoffmann, Marcus

2017-04-01

The availability of complete, quality and dense monitoring hydro-meteorological data is essential to address a number of practical issues including, but not limited to, flood-water and urban drainage management, climate change impact assessment, early warning and risk management, now-casting and weather predictions. Thanks to the recent technological advances such as Internet Of Things, Big Data and Ubiquitous Internet, non-conventional monitoring systems based on open technologies and low cost sensors may represent a great opportunity either as a complement of authoritative monitoring network or as a vital source of information wherever existing monitoring networks are in decline or completely missing. Nevertheless, scientific literature on such a kind of open and non-conventional monitoring systems is still limited and often relates to prototype engineering and testing in rather limited case studies. For this reason the 4onse project aims at integrating existing open technologies in the field of Free & Open Source Software, Open Hardware, Open Data, and Open Standards and evaluate this kind of system in a real case (about 30 stations) for a medium period of 2 years to better scientifically understand strengths, criticalities and applicabilities in terms of data quality; system durability; management costs; performances; sustainability. The ultimate objective is to contribute in non-conventional monitoring systems adoption based on four open technologies.

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.

Software engineering risk factors in the implementation of a small electronic medical record system: the problem of scalability.

PubMed

Chiang, Michael F; Starren, Justin B

2002-01-01

The successful implementation of clinical information systems is difficult. In examining the reasons and potential solutions for this problem, the medical informatics community may benefit from the lessons of a rich body of software engineering and management literature about the failure of software projects. Based on previous studies, we present a conceptual framework for understanding the risk factors associated with large-scale projects. However, the vast majority of existing literature is based on large, enterprise-wide systems, and it unclear whether those results may be scaled down and applied to smaller projects such as departmental medical information systems. To examine this issue, we discuss the case study of a delayed electronic medical record implementation project in a small specialty practice at Columbia-Presbyterian Medical Center. While the factors contributing to the delay of this small project share some attributes with those found in larger organizations, there are important differences. The significance of these differences for groups implementing small medical information systems is discussed.

An infrastructure for ontology-based information systems in biomedicine: RICORDO case study.

PubMed

Wimalaratne, Sarala M; Grenon, Pierre; Hoehndorf, Robert; Gkoutos, Georgios V; de Bono, Bernard

2012-02-01

The article presents an infrastructure for supporting the semantic interoperability of biomedical resources based on the management (storing and inference-based querying) of their ontology-based annotations. This infrastructure consists of: (i) a repository to store and query ontology-based annotations; (ii) a knowledge base server with an inference engine to support the storage of and reasoning over ontologies used in the annotation of resources; (iii) a set of applications and services allowing interaction with the integrated repository and knowledge base. The infrastructure is being prototyped and developed and evaluated by the RICORDO project in support of the knowledge management of biomedical resources, including physiology and pharmacology models and associated clinical data. The RICORDO toolkit and its source code are freely available from http://ricordo.eu/relevant-resources. sarala@ebi.ac.uk.

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

NASA Technical Reports Server (NTRS)

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

1988-01-01

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

Case for a field-programmable gate array multicore hybrid machine for an image-processing application

NASA Astrophysics Data System (ADS)

Rakvic, Ryan N.; Ives, Robert W.; Lira, Javier; Molina, Carlos

2011-01-01

General purpose computer designers have recently begun adding cores to their processors in order to increase performance. For example, Intel has adopted a homogeneous quad-core processor as a base for general purpose computing. PlayStation3 (PS3) game consoles contain a multicore heterogeneous processor known as the Cell, which is designed to perform complex image processing algorithms at a high level. Can modern image-processing algorithms utilize these additional cores? On the other hand, modern advancements in configurable hardware, most notably field-programmable gate arrays (FPGAs) have created an interesting question for general purpose computer designers. Is there a reason to combine FPGAs with multicore processors to create an FPGA multicore hybrid general purpose computer? Iris matching, a repeatedly executed portion of a modern iris-recognition algorithm, is parallelized on an Intel-based homogeneous multicore Xeon system, a heterogeneous multicore Cell system, and an FPGA multicore hybrid system. Surprisingly, the cheaper PS3 slightly outperforms the Intel-based multicore on a core-for-core basis. However, both multicore systems are beaten by the FPGA multicore hybrid system by >50%.

Open architectures for formal reasoning and deductive technologies for software development

NASA Technical Reports Server (NTRS)

Mccarthy, John; Manna, Zohar; Mason, Ian; Pnueli, Amir; Talcott, Carolyn; Waldinger, Richard

1994-01-01

The objective of this project is to develop an open architecture for formal reasoning systems. One goal is to provide a framework with a clear semantic basis for specification and instantiation of generic components; construction of complex systems by interconnecting components; and for making incremental improvements and tailoring to specific applications. Another goal is to develop methods for specifying component interfaces and interactions to facilitate use of existing and newly built systems as 'off the shelf' components, thus helping bridge the gap between producers and consumers of reasoning systems. In this report we summarize results in several areas: our data base of reasoning systems; a theory of binding structures; a theory of components of open systems; a framework for specifying components of open reasoning system; and an analysis of the integration of rewriting and linear arithmetic modules in Boyer-Moore using the above framework.

In Their Own Words: A Text Analytics Investigation of College Course Attrition

ERIC Educational Resources Information Center

Michalski, Greg V.

2014-01-01

Excessive course attrition is costly to both the student and the institution. While most institutions have systems to quantify and report the numbers, far less attention is typically paid to each student's reason(s) for withdrawal. In this case study, text analytics was used to analyze a large set of open-ended written comments in which students…

Expert Recommender: Designing for a Network Organization

NASA Astrophysics Data System (ADS)

Reichling, Tim; Veith, Michael; Wulf, Volker

Recent knowledge management initiatives focus on expertise sharing within formal organizational units and informal communities of practice. Expert recommender systems seem to be a promising tool in support of these initiatives. This paper presents experiences in designing an expert recommender system for a knowledge- intensive organization, namely the National Industry Association (NIA). Field study results provide a set of specific design requirements. Based on these requirements, we have designed an expert recommender system which is integrated into the specific software infrastructure of the organizational setting. The organizational setting is, as we will show, specific for historical, political, and economic reasons. These particularities influence the employees’ organizational and (inter-)personal needs within this setting. The paper connects empirical findings of a long-term case study with design experiences of an expertise recommender system.

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.

Modeling operational behavior of a disassembly line

NASA Astrophysics Data System (ADS)

Kizilkaya, Elif A.; Gupta, Surendra M.

2004-12-01

In this paper we present a dynamic kanban (pull) system specifically developed for disassembly lines. This type of kanban system is much more complex than the traditional kanban system used in assembly lines. For instance, unlike the assembly line where the external demand occurs only at the last station, the demands in the disassembly case also occur at any of the intermittent stations. The reason is that as a product moves on the disassembly line, various parts are disassembled at every station and accumulated at that station. Therefore, there are as many demand sources as there are number of parts. We consider a case example involving the end-of-life products. Based on the precedence relationships and other criteria such as hazardous properties of the parts, we balance the disassembly line. The results of the disassembly line-balancing problem (DLBP) are used as input to the proposed dynamic kanban system for disassembly line (DKSDL). We compare the performance of the DKSDL to the modified kanban system for disassembly line (MKSDL), which was previously introduced by the authors. We show, via simulation, that the DKSDL is far superior to MKSDL considered.

Horizontal and vertical integration of academic disciplines in the medical school curriculum.

PubMed

Vidic, Branislav; Weitlauf, Harry M

2002-05-01

A rapid expansion of new scientific information and the introduction of new technology in operative and diagnostic medicine has marked the last several decades. Medical educators, because of and parallel to these developments, initiated a search for a more effective system of presenting core material to medical students. The new educational trends, although varying somewhat from one institution to another, concentrated on the following pedagogical shifts: 1) expansion of conceptual presentation of material at the expense of detail-oriented education; 2) amplification of an integrated approach, as opposed to subject-oriented instruction; 3) scheduling of elective courses to compliment required courses in the curriculum; and 4) institution of small group instruction (i.e., problem-based learning) to actively involve students in the educational process and to develop deductive reasoning based on clinical cases. The future pedagogical system in medical schools will most likely be a combination of "classical" presentation of material combined with concept-oriented, subject-integrated and small group instruction based on either hypothetical or real clinical cases. It is imperative for the success of the new curriculum, however, that certain criteria are satisfied: 1) reorganize basic science departments to determine course ownership; 2) establish a reward system for teaching faculty; and 3) establish new course objectives. Copyright 2002 Wiley-Liss, Inc.

Cognitive and attentional functioning in adolescents and young adults with Tetralogy of Fallot and d-transposition of the great arteries.

PubMed

Murphy, Lexa K; Compas, Bruce E; Reeslund, Kristen L; Gindville, Melissa C; Mah, May Ling; Markham, Larry W; Jordan, Lori C

2017-01-01

The objective of this study is to investigate cognitive and attentional function in adolescents and young adults with operated congenital heart disease. Previous research has indicated that children with congenital heart disease have deficits in broad areas of cognitive function. However, less attention has been given to survivors as they grow into adolescence and early adulthood. The participants were 18 non-syndromic adolescents and young adults with tetralogy of Fallot and d-transposition of the great arteries that required cardiac surgery before the age of 5 years, and 18 healthy, unaffected siblings (11-22 years of age for both groups). Cases with congenital heart disease and their siblings were administered Wechsler Intelligence scales and reported attention problems using the Achenbach System of Empirically Based Assessments. Cases were compared to both healthy siblings and established norms. Cases performed significantly lower than siblings on full scale IQ and processing speed, and significantly lower than norms on perceptual reasoning. Cases also reported more attention problems compared to both siblings and norms. Effect sizes varied with medium-to-large effects for processing speed, perceptual reasoning, working memory, and attention problems. Findings suggest that neurocognitive function may continue to be affected for congenital heart disease survivors in adolescence and young adulthood, and that comparisons to established norms may underestimate neurocognitive vulnerabilities.

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

PubMed Central

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

2015-01-01

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

Case-based retrieval framework for gene expression data.

PubMed

Anaissi, Ali; Goyal, Madhu; Catchpoole, Daniel R; Braytee, Ali; Kennedy, Paul J

2015-01-01

The process of retrieving similar cases in a case-based reasoning system is considered a big challenge for gene expression data sets. The huge number of gene expression values generated by microarray technology leads to complex data sets and similarity measures for high-dimensional data are problematic. Hence, gene expression similarity measurements require numerous machine-learning and data-mining techniques, such as feature selection and dimensionality reduction, to be incorporated into the retrieval process. This article proposes a case-based retrieval framework that uses a k-nearest-neighbor classifier with a weighted-feature-based similarity to retrieve previously treated patients based on their gene expression profiles. The herein-proposed methodology is validated on several data sets: a childhood leukemia data set collected from The Children's Hospital at Westmead, as well as the Colon cancer, the National Cancer Institute (NCI), and the Prostate cancer data sets. Results obtained by the proposed framework in retrieving patients of the data sets who are similar to new patients are as follows: 96% accuracy on the childhood leukemia data set, 95% on the NCI data set, 93% on the Colon cancer data set, and 98% on the Prostate cancer data set. The designed case-based retrieval framework is an appropriate choice for retrieving previous patients who are similar to a new patient, on the basis of their gene expression data, for better diagnosis and treatment of childhood leukemia. Moreover, this framework can be applied to other gene expression data sets using some or all of its steps.

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.

Description of hospitalized cases of influenza A(H1N1)pdm09 infection on the basis of the national hospitalized-case surveillance, 2009-2010, Japan.

PubMed

Shimada, Tomoe; Sunagawa, Tomimasa; Taniguchi, Kiyosu; Yahata, Yuichiro; Kamiya, Hajime; Yamamoto, Kumi Ueno; Yasui, Yoshinori; Okabe, Nobuhiko

2015-01-01

This study reports the epidemiological characteristics of hospitalized cases of influenza A(H1N1)pdm09 infection analyzed on the basis of surveillance data collected from July 24, 2009, the date on which the hospital-based surveillance of influenza cases was implemented in Japan, to September 5, 2010. During the study period, 13,581 confirmed cases were reported. Among those cases with information regarding the reason for hospitalization, 39% were admitted to hospitals for non-therapeutic purposes such as medical observation and laboratory testing. The overall hospitalization rate was 5.8 cases per 100,000 population when cases hospitalized for non-therapeutic purposes were excluded. While those aged under 20 years accounted for over 85% of hospitalized cases, the largest proportion of fatal cases was observed in those aged over 65 years. The overall case fatality rate for all hospitalized cases was 1.5%. The year-round surveillance for hospitalized influenza-like illness cases was launched in 2011, and it was expected that this surveillance system could add value by monitoring changes in the epidemiological characteristics of hospitalized cases of seasonal influenza.

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

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.

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.

Skin-deep diagnosis: affective bias and zebra retreat complicating the diagnosis of systemic sclerosis.

PubMed

Miller, Chad S

2013-01-01

Nearly half of medical errors can be attributed to an error of clinical reasoning or decision making. It is estimated that the correct diagnosis is missed or delayed in between 5% and 14% of acute hospital admissions. Through understanding why and how physicians make these errors, it is hoped that strategies can be developed to decrease the number of these errors. In the present case, a patient presented with dyspnea, gastrointestinal symptoms and weight loss; the diagnosis was initially missed when the treating physicians took mental short cuts and used heuristics as in this case. Heuristics have an inherent bias that can lead to faulty reasoning or conclusions, especially in complex or difficult cases. Affective bias, which is the overinvolvement of emotion in clinical decision making, limited the available information for diagnosis because of the hesitancy to acquire a full history and perform a complete physical examination in this patient. Zebra retreat, another type of bias, is when a rare diagnosis figures prominently on the differential diagnosis but the physician retreats for various reasons. Zebra retreat also factored in the delayed diagnosis. Through the description of these clinical reasoning errors in an actual case, it is hoped that future errors can be prevented or inspiration for additional research in this area will develop.

An Efficient Model-based Diagnosis Engine for Hybrid Systems Using Structural Model Decomposition

NASA Technical Reports Server (NTRS)

Bregon, Anibal; Narasimhan, Sriram; Roychoudhury, Indranil; Daigle, Matthew; Pulido, Belarmino

2013-01-01

Complex hybrid systems are present in a large range of engineering applications, like mechanical systems, electrical circuits, or embedded computation systems. The behavior of these systems is made up of continuous and discrete event dynamics that increase the difficulties for accurate and timely online fault diagnosis. The Hybrid Diagnosis Engine (HyDE) offers flexibility to the diagnosis application designer to choose the modeling paradigm and the reasoning algorithms. The HyDE architecture supports the use of multiple modeling paradigms at the component and system level. However, HyDE faces some problems regarding performance in terms of complexity and time. Our focus in this paper is on developing efficient model-based methodologies for online fault diagnosis in complex hybrid systems. To do this, we propose a diagnosis framework where structural model decomposition is integrated within the HyDE diagnosis framework to reduce the computational complexity associated with the fault diagnosis of hybrid systems. As a case study, we apply our approach to a diagnostic testbed, the Advanced Diagnostics and Prognostics Testbed (ADAPT), using real data.

An adaptable architecture for patient cohort identification from diverse data sources.

PubMed

Bache, Richard; Miles, Simon; Taweel, Adel

2013-12-01

We define and validate an architecture for systems that identify patient cohorts for clinical trials from multiple heterogeneous data sources. This architecture has an explicit query model capable of supporting temporal reasoning and expressing eligibility criteria independently of the representation of the data used to evaluate them. The architecture has the key feature that queries defined according to the query model are both pre and post-processed and this is used to address both structural and semantic heterogeneity. The process of extracting the relevant clinical facts is separated from the process of reasoning about them. A specific instance of the query model is then defined and implemented. We show that the specific instance of the query model has wide applicability. We then describe how it is used to access three diverse data warehouses to determine patient counts. Although the proposed architecture requires greater effort to implement the query model than would be the case for using just SQL and accessing a data-based management system directly, this effort is justified because it supports both temporal reasoning and heterogeneous data sources. The query model only needs to be implemented once no matter how many data sources are accessed. Each additional source requires only the implementation of a lightweight adaptor. The architecture has been used to implement a specific query model that can express complex eligibility criteria and access three diverse data warehouses thus demonstrating the feasibility of this approach in dealing with temporal reasoning and data heterogeneity.

[Agricultural policies and farming systems: A case study of landscape changes in Shizuitou Village in the recent four decades].

PubMed

Wang, Xiao-jun; Zhou, Yang; Yan, Yan-bin; Li, Lei

2015-01-01

Agricultural policy in China's rural heartland is driving profound changes to traditional farming systems. A case study covering four decades mapped and recorded farming patterns and processes in Shizuitou Village, a rural village in northwest Shanxi. An integrated geospatial methodology from geography and anthropology was employed in the case study to record the changing dynamics of farming systems in Shizuitou Village to discover the long-term impacts of China's agricultural policies on village farming systems. Positive and negative impacts of agricultural policies on village farming systems were mapped, inventoried and evaluated using Participatory Geographic Information Systems (PGIS). The results revealed traditional polycultures are being gradually replaced by industrialized monocultures. The driving forces behind these farming changes come from a series of government agricultural policies aiming at modernization of farming systems in China. The goal of these policies was to spur rapid development of industrial agriculture under the guise of modernization but is leading to the decay of traditional farming systems in the village that maintained local food security with healthy land for hundreds of years. The paper concluded with a recommendation that in future, agricultural policy makers should strike a more reasonable balance between short-term agricultural profits and long-term farming sustainability based on the principles of ecological sustainable development under the context of global changes.

Medicine shortages--a study of community pharmacies in Finland.

PubMed

Heiskanen, K; Ahonen, R; Karttunen, P; Kanerva, R; Timonen, J

2015-02-01

To explore the frequency, the reasons behind, and the consequences of medicine shortages in Finnish community pharmacies. During the 27-day study period in the autumn of 2013, randomly selected pharmacies reported on medicines that were in short supply from orders made to wholesalers. Altogether 129 (66%, n=195) pharmacies participated in the study, and the study material consisted of 3311 report forms. Of the study pharmacies, 79.8% had medicine shortages daily or almost daily. Medicines in short supply were most commonly medicines that affect the nervous system (30.8%) and the cardiovascular system (17.5%). The reason behind the shortage was reported to the pharmacies in 11.2% of the shortage cases. The medicine shortages caused problems for the pharmacies in 33.0% of the cases. In most cases (67.0%) the medicine shortages did not cause problems for the pharmacies, usually because a substitutable product was available (48.5%). Medicine shortages are common in Finnish community pharmacies. Medicines in short supply were commonly used medicines. The reason behind the shortage was rarely told to the pharmacies. Medicine shortages caused problems for the pharmacies in one-third of all the shortage cases. These shortages may be significant for the customers or the pharmacies, as they cause customer dissatisfaction and increase the workload of the pharmacy staff. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

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.

The start of lightning: Evidence of bidirectional lightning initiation.

PubMed

Montanyà, Joan; van der Velde, Oscar; Williams, Earle R

2015-10-16

Lightning flashes are known to initiate in regions of strong electric fields inside thunderstorms, between layers of positively and negatively charged precipitation particles. For that reason, lightning inception is typically hidden from sight of camera systems used in research. Other technology such as lightning mapping systems based on radio waves can typically detect only some aspects of the lightning initiation process and subsequent development of positive and negative leaders. We report here a serendipitous recording of bidirectional lightning initiation in virgin air under the cloud base at ~11,000 images per second, and the differences in characteristics of opposite polarity leader sections during the earliest stages of the discharge. This case reveals natural lightning initiation, propagation and a return stroke as in negative cloud-to-ground flashes, upon connection to another lightning channel - without any masking by cloud.

Conditional Outlier Detection for Clinical Alerting

PubMed Central

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

2010-01-01

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

Conditional outlier detection for clinical alerting.

PubMed

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

2010-11-13

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

Model-Based Reasoning in the Detection of Satellite Anomalies

DTIC Science & Technology

1990-12-01

Conference on Artificial Intellegence . 1363-1368. Detroit, Michigan, August 89. Chu, Wei-Hai. "Generic Expert System Shell for Diagnostic Reasoning... Intellegence . 1324-1330. Detroit, Michigan, August 89. de Kleer, Johan and Brian C. Williams. "Diagnosing Multiple Faults," Artificial Intellegence , 32(1): 97...Benjamin Kuipers. "Model-Based Monitoring of Dynamic Systems," Proceedings of the Eleventh Intematianal Joint Conference on Artificial Intellegence . 1238

Framework for teleoperated microassembly systems

NASA Astrophysics Data System (ADS)

Reinhart, Gunther; Anton, Oliver; Ehrenstrasser, Michael; Patron, Christian; Petzold, Bernd

2002-02-01

Manual assembly of minute parts is currently done using simple devices such as tweezers or magnifying glasses. The operator therefore requires a great deal of concentration for successful assembly. Teleoperated micro-assembly systems are a promising method for overcoming the scaling barrier. However, most of today's telepresence systems are based on proprietary and one-of-a-kind solutions. Frameworks which supply the basic functions of a telepresence system, e.g. to establish flexible communication links that depend on bandwidth requirements or to synchronize distributed components, are not currently available. Large amounts of time and money have to be invested in order to create task-specific teleoperated micro-assembly systems from scratch. For this reason, an object-oriented framework for telepresence systems that is based on CORBA as a common middleware was developed at the Institute for Machine Tools and Industrial Management (iwb). The framework is based on a distributed architectural concept and is realized in C++. External hardware components such as haptic, video or sensor devices are coupled to the system by means of defined software interfaces. In this case, the special requirements of teleoperation systems have to be considered, e.g. dynamic parameter settings for sensors during operation. Consequently, an architectural concept based on logical sensors has been developed to achieve maximum flexibility and to enable a task-oriented integration of hardware components.

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.

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...

Enhancing Three-dimensional Movement Control System for Assemblies of Machine-Building Facilities

NASA Astrophysics Data System (ADS)

Kuzyakov, O. N.; Andreeva, M. A.

2018-01-01

Aspects of enhancing three-dimensional movement control system are given in the paper. Such system is to be used while controlling assemblies of machine-building facilities, which is a relevant issue. The base of the system known is three-dimensional movement control device with optical principle of action. The device consists of multi point light emitter and light receiver matrix. The processing of signals is enhanced to increase accuracy of measurements by switching from discrete to analog signals. Light receiver matrix is divided into four areas, and the output value of each light emitter in each matrix area is proportional to its luminance level. Thus, determing output electric signal value of each light emitter in corresponding area leads to determing position of multipoint light emitter and position of object tracked. This is done by using Case-based reasoning method, the precedent in which is described as integral signal value of each matrix area, coordinates of light receivers, which luminance level is high, and decision to be made in this situation.

Artificial neural networks and approximate reasoning for intelligent control in space

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1991-01-01

A method is introduced for learning to refine the control rules of approximate reasoning-based controllers. A reinforcement-learning technique is used in conjunction with a multi-layer neural network model of an approximate reasoning-based controller. The model learns by updating its prediction of the physical system's behavior. The model can use the control knowledge of an experienced operator and fine-tune it through the process of learning. Some of the space domains suitable for applications of the model such as rendezvous and docking, camera tracking, and tethered systems control are discussed.

An interval logic for higher-level temporal reasoning

NASA Technical Reports Server (NTRS)

Schwartz, R. L.; Melliar-Smith, P. M.; Vogt, F. H.; Plaisted, D. A.

1983-01-01

Prior work explored temporal logics, based on classical modal logics, as a framework for specifying and reasoning about concurrent programs, distributed systems, and communications protocols, and reported on efforts using temporal reasoning primitives to express very high level abstract requirements that a program or system is to satisfy. Based on experience with those primitives, this report describes an Interval Logic that is more suitable for expressing such higher level temporal properties. The report provides a formal semantics for the Interval Logic, and several examples of its use. A description of decision procedures for the logic is also included.

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.

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…

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

NASA Astrophysics Data System (ADS)

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

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

Accident diagnosis system based on real-time decision tree expert system

NASA Astrophysics Data System (ADS)

Nicolau, Andressa dos S.; Augusto, João P. da S. C.; Schirru, Roberto

2017-06-01

Safety is one of the most studied topics when referring to power stations. For that reason, sensors and alarms develop an important role in environmental and human protection. When abnormal event happens, it triggers a chain of alarms that must be, somehow, checked by the control room operators. In this case, diagnosis support system can help operators to accurately identify the possible root-cause of the problem in short time. In this article, we present a computational model of a generic diagnose support system based on artificial intelligence, that was applied on the dataset of two real power stations: Angra1 Nuclear Power Plant and Santo Antônio Hydroelectric Plant. The proposed system processes all the information logged in the sequence of events before a shutdown signal using the expert's knowledge inputted into an expert system indicating the chain of events, from the shutdown signal to its root-cause. The results of both applications showed that the support system is a potential tool to help the control room operators identify abnormal events, as accidents and consequently increase the safety.

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

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

Vehicle-Level Reasoning Systems: Integrating System-Wide Data to Estimate the Instantaneous Health State

NASA Technical Reports Server (NTRS)

Srivastava, Ashok N.; Mylaraswmay, Dinkar; Mah, Robert W.; Cooper, Eric G.

2011-01-01

At the aircraft level, a Vehicle-Level Reasoning System (VLRS) can be developed to provide aircraft with at least two significant capabilities: improvement of aircraft safety due to enhanced monitoring and reasoning about the aircrafts health state, and also potential cost savings by enabling Condition Based Maintenance (CBM). Along with the benefits of CBM, an important challenge facing aviation safety today is safeguarding against system and component failures and malfunctions. Faults can arise in one or more aircraft subsystem their effects in one system may propagate to other subsystems, and faults may interact.

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.

Analyzing the politico-moral foundations of the Iran’s health system based on theories of justice

PubMed Central

Akrami, Forouzan; Abbasi, Mahmoud; Karimi, Abbas; Shahrivari, Akbar; Majdzadeh, Reza; Zali, Alireza

2017-01-01

Public health ethics is a field that covers both factual and ethical issues in health policy and science, and has positive obligations to improve the well-being of populations and reduce social inequalities. It is obvious that various philosophies and moral theories can differently shape the framework of public health ethics. For this reason, the present study reviewed theories of justice in order to analyze and criticize Iran’s general health policies document, served in 14 Articles in 2014. Furthermore, it explored egalitarianism as the dominant theory in the political philosophy of the country’s health care system. According to recent theories of justice, however, health policies must address well-being and its basic dimensions such as health, reasoning, autonomy, and the role of the involved agencies and social institutions in order to achieve social justice beyond distributive justice. Moreover, policy-making in the field of health and biomedical sciences based on Islamic culture necessitates a theory of social justice in the light of theological ethics. Educating people about their rights and duties, increasing their knowledge on individual agency, autonomy, and the role of the government, and empowering them will help achieve social justice. It is recommended to design and implement a strategic plan following each of these policies, based on the above-mentioned values and in collaboration with other sectors, to clarify the procedures in every case. PMID:29291037

Analyzing the politico-moral foundations of the Iran's health system based on theories of justice.

PubMed

Akrami, Forouzan; Abbasi, Mahmoud; Karimi, Abbas; Shahrivari, Akbar; Majdzadeh, Reza; Zali, Alireza

2017-01-01

Public health ethics is a field that covers both factual and ethical issues in health policy and science, and has positive obligations to improve the well-being of populations and reduce social inequalities. It is obvious that various philosophies and moral theories can differently shape the framework of public health ethics. For this reason, the present study reviewed theories of justice in order to analyze and criticize Iran's general health policies document, served in 14 Articles in 2014. Furthermore, it explored egalitarianism as the dominant theory in the political philosophy of the country's health care system. According to recent theories of justice, however, health policies must address well-being and its basic dimensions such as health, reasoning, autonomy, and the role of the involved agencies and social institutions in order to achieve social justice beyond distributive justice. Moreover, policy-making in the field of health and biomedical sciences based on Islamic culture necessitates a theory of social justice in the light of theological ethics. Educating people about their rights and duties, increasing their knowledge on individual agency, autonomy, and the role of the government, and empowering them will help achieve social justice. It is recommended to design and implement a strategic plan following each of these policies, based on the above-mentioned values and in collaboration with other sectors, to clarify the procedures in every case.

Integration of midwives into the Quebec health care system. L'Equipe d'Evaluation des Projets-Pilotes Sages-Femmes.

PubMed

Collin, J; Blais, R; White, D; Demers, A; Desbiens, F

2000-01-01

This paper reports on one aspect of the evaluation of the midwifery pilot projects in Quebec: the identification of the professional and organizational factors, as well as the mode of integrating midwives into the maternity care system, that would promote the best outcomes and the autonomy of midwives. The research strategy involved a multiple-case study, in which each midwifery pilot project represented a case. Based on a qualitative approach, the study employed various sources of data: individual interviews and focus groups with key informants, site observations and analyses of written documents. Results show that midwives were poorly integrated into the health care system during the evaluation. Four main reasons were identified: lack of knowledge about the practice of midwifery on the part of other health care providers; deficiencies in the legal and organizational structure of the pilot projects; competition over professional territories; and gaps between the midwives' and other providers' professional cultures. Recommendations are provided to facilitate the integration of midwives into the health care system.

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

NASA Technical Reports Server (NTRS)

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

1986-01-01

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

Primary central nervous system diffuse large B-cell lymphoma shows an activated B-cell-like phenotype with co-expression of C-MYC, BCL-2, and BCL-6.

PubMed

Li, Xiaomei; Huang, Ying; Bi, Chengfeng; Yuan, Ji; He, Hong; Zhang, Hong; Yu, QiuBo; Fu, Kai; Li, Dan

2017-06-01

Diffuse large B-cell lymphoma (DLBCL) is the most common non-Hodgkin lymphoma, whose main prognostic factor is closely related to germinal center B-cell-like subtype (GCB- DLBCL) or activated B-cell-like type (non-GCB-DLBCL). The most common type of primary central nervous system lymphoma is diffuse large B-cell type with poor prognosis and the reason is unclear. This study aims to stratify primary central nervous system diffuse large B-cell lymphoma (PCNS-DLBCL) according to the cell-of-origin (COO) and to investigate the multiple proteins expression of C-MYC, BCL-6, BCL-2, TP53, further to elucidate the reason why primary central nervous system diffuse large B-cell lymphoma possesses a poor clinical outcome as well. Nineteen cases of primary central nervous system DLBCL were stratified according to immunostaining algorithms of Hans, Choi and Meyer (Tally) and we investigated the multiple proteins expression of C-MYC, BCL-6, BCL-2, TP53. The Epstein-Barr virus and Borna disease virus infection were also detected. Among nineteen cases, most (15-17 cases) were assigned to the activated B-cell-like subtype, highly expression of C-MYC (15 cases, 78.9%), BCL-2 (10 cases, 52.6%), BCL-6 (15 cases, 78.9%). Unfortunately, two cases were positive for PD-L1 while PD-L2 was not expressed in any case. Two cases infected with BDV but no one infected with EBV. In conclusion, most primary central nervous system DLBCLs show an activated B-cell-like subtype characteristic and have multiple expressions of C-MYC, BCL-2, BCL-6 protein, these features might be significant factor to predict the outcome and guide treatment of PCNS-DLBCLs. Copyright © 2017 Elsevier GmbH. All rights reserved.

SiC: An Agent Based Architecture for Preventing and Detecting Attacks to Ubiquitous Databases

NASA Astrophysics Data System (ADS)

Pinzón, Cristian; de Paz, Yanira; Bajo, Javier; Abraham, Ajith; Corchado, Juan M.

One of the main attacks to ubiquitous databases is the structure query language (SQL) injection attack, which causes severe damages both in the commercial aspect and in the user’s confidence. This chapter proposes the SiC architecture as a solution to the SQL injection attack problem. This is a hierarchical distributed multiagent architecture, which involves an entirely new approach with respect to existing architectures for the prevention and detection of SQL injections. SiC incorporates a kind of intelligent agent, which integrates a case-based reasoning system. This agent, which is the core of the architecture, allows the application of detection techniques based on anomalies as well as those based on patterns, providing a great degree of autonomy, flexibility, robustness and dynamic scalability. The characteristics of the multiagent system allow an architecture to detect attacks from different types of devices, regardless of the physical location. The architecture has been tested on a medical database, guaranteeing safe access from various devices such as PDAs and notebook computers.

SAMS--a systems architecture for developing intelligent health information systems.

PubMed

Yılmaz, Özgün; Erdur, Rıza Cenk; Türksever, Mustafa

2013-12-01

In this paper, SAMS, a novel health information system architecture for developing intelligent health information systems is proposed and also some strategies for developing such systems are discussed. The systems fulfilling this architecture will be able to store electronic health records of the patients using OWL ontologies, share patient records among different hospitals and provide physicians expertise to assist them in making decisions. The system is intelligent because it is rule-based, makes use of rule-based reasoning and has the ability to learn and evolve itself. The learning capability is provided by extracting rules from previously given decisions by the physicians and then adding the extracted rules to the system. The proposed system is novel and original in all of these aspects. As a case study, a system is implemented conforming to SAMS architecture for use by dentists in the dental domain. The use of the developed system is described with a scenario. For evaluation, the developed dental information system will be used and tried by a group of dentists. The development of this system proves the applicability of SAMS architecture. By getting decision support from a system derived from this architecture, the cognitive gap between experienced and inexperienced physicians can be compensated. Thus, patient satisfaction can be achieved, inexperienced physicians are supported in decision making and the personnel can improve their knowledge. A physician can diagnose a case, which he/she has never diagnosed before, using this system. With the help of this system, it will be possible to store general domain knowledge in this system and the personnel's need to medical guideline documents will be reduced.

Deep-reasoning fault diagnosis - An aid and a model

NASA Technical Reports Server (NTRS)

Yoon, Wan Chul; Hammer, John M.

1988-01-01

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

Knowledge-based reasoning in the Paladin tactical decision generation system

NASA Technical Reports Server (NTRS)

Chappell, Alan R.

1993-01-01

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

Emotional learning and the development of differential moralities: implications from research on psychopathy.

PubMed

Blair, R James R; White, Stuart F; Meffert, Harma; Hwang, Soonjo

2013-09-01

In this paper, we will argue that (1) four classes of norm can be distinguished from a neuro-cognitive perspective; (2) learning the prohibitive power of these norms relies on relatively independent emotional systems; (3) individuals with psychopathy show selective impairment for one of these emotional learning systems and two classes of norm: care based and justice based; and (4) while emotional learning systems are necessary for appropriate moral development/reasoning, they are not sufficient for moral development/reasoning.

Factors Affecting the Adoption of an E-Assessment System

ERIC Educational Resources Information Center

McCann, Ann L.

2010-01-01

A case study was conducted in 2006-07 to explore how one US campus implemented a centralised e-assessment system. The study specifically measured the extent of adoption by faculty members, identified their reasons for adoption and evaluated the impact on teaching and learning. The purposes of the system, entitled researching learning (REAL, a…

Dual Rationality and Deliberative Agents

NASA Astrophysics Data System (ADS)

Debenham, John; Sierra, Carles

Human agents deliberate using models based on reason for only a minute proportion of the decisions that they make. In stark contrast, the deliberation of artificial agents is heavily dominated by formal models based on reason such as game theory, decision theory and logic—despite that fact that formal reasoning will not necessarily lead to superior real-world decisions. Further the Nobel Laureate Friedrich Hayek warns us of the ‘fatal conceit’ in controlling deliberative systems using models based on reason as the particular model chosen will then shape the system’s future and either impede, or eventually destroy, the subtle evolutionary processes that are an integral part of human systems and institutions, and are crucial to their evolution and long-term survival. We describe an architecture for artificial agents that is founded on Hayek’s two rationalities and supports the two forms of deliberation used by mankind.

Innovation in Distance Education Learning Systems: The Case of the National Correspondence Institute of Tanzania, 1972-2002

ERIC Educational Resources Information Center

Mutanyatta, J. N. S.

2008-01-01

The paper attempts to provide relevant data on the achievements, albeit quantitatively, of the National Correspondence Institute of Tanzania over the past 30 years as a case study in distance education innovation. The case-study data reveal reasons for the near collapse of the distance education programme during the 1990s, and the renewed policy…

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.

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

NASA Astrophysics Data System (ADS)

Moosavi, Sadredin

2014-05-01

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

Neural correlates of dual-task effect on belief-bias syllogistic reasoning: a near-infrared spectroscopy study.

PubMed

Tsujii, Takeo; Watanabe, Shigeru

2009-09-01

Recent dual-process reasoning theories have explained the belief-bias effect, the tendency for human reasoning to be erroneously biased when logical conclusions are incongruent with beliefs about the world, by proposing a belief-based automatic heuristic system and logic-based demanding analytic system. Although these claims are supported by the behavioral finding that high-load secondary tasks enhance the belief-bias effect, the neural correlates of dual-task reasoning remain unknown. The present study therefore examined the relationship between dual-task effect and activity in the inferior frontal cortex (IFC) during belief-bias reasoning by near-infrared spectroscopy (NIRS). Forty-eight subjects participated in this study (MA=23.46 years). They were required to perform congruent and incongruent reasoning trials while responding to high- and low-load secondary tasks. Behavioral analysis showed that the high-load secondary task impaired only incongruent reasoning performance. NIRS analysis found that the high-load secondary task decreased right IFC activity during incongruent trials. Correlation analysis showed that subjects with enhanced right IFC activity could perform better in the incongruent reasoning trials, though subjects for whom right IFC activity was impaired by the secondary task could not maintain better reasoning performance. These findings suggest that the right IFC may be responsible for the dual-task effect in conflicting reasoning processes. When secondary tasks impair right IFC activity, subjects may rely on the automatic heuristic system, which results in belief-bias responses. We therefore offer the first demonstration of neural correlates of dual-task effect on IFC activity in belief-bias reasoning.

Boilermodel: A Qualitative Model-Based Reasoning System Implemented in Ada

DTIC Science & Technology

1991-09-01

comple- ment to shipboard engineering training. Accesion For NTIS CRA&I DTIO I A3 f_- Unairmoui1ccd [i Justification By ................... Distribut;or, I...investment (in terms of man-hours lost, equipment maintenance, materials, etc.) for initial training. On- going training is also required to sustain a...REASONING FROM MODELS Model-based expert systems have been written in many languages and for many different architectures . Knowledge representation also

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...

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.

Wetting of Functionalized Polyethylene Film Having Ionizable Organic Acids and Bases at the Polymer-Water Interface: Relations between Functional Group Polarity, Extent of Ionization, and Contact Angle with Water.

DTIC Science & Technology

1988-03-01

functional grouos in the interface contribute independently to the interfacial free energy is inaccurate, but leads to a tractable and physically reasonable...nonpolar, non -ionizable groups. As a limiting case, we consider a system *. containing only one type of polar and one type of nonpolar group (eq 9) with A...groups (protonition or deprotonation): these equations apply to both non - ionizable groups and to PE-CO 2H and PE-NR 2H + . Assuming that Figure 3

[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.

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

Pin, F.G.; Bender, S.R.

Most fuzzy logic-based reasoning schemes developed for robot control are fully reactive, i.e., the reasoning modules consist of fuzzy rule bases that represent direct mappings from the stimuli provided by the perception systems to the responses implemented by the motion controllers. Due to their totally reactive nature, such reasoning systems can encounter problems such as infinite loops and limit cycles. In this paper, we proposed an approach to remedy these problems by adding a memory and memory-related behaviors to basic reactive systems. Three major types of memory behaviors are addressed: memory creation, memory management, and memory utilization. These are firstmore » presented, and examples of their implementation for the recognition of limit cycles during the navigation of an autonomous robot in a priori unknown environments are then discussed.« less

How to apply clinical cases and medical literature in the framework of a modified "failure mode and effects analysis" as a clinical reasoning tool--an illustration using the human biliary system.

PubMed

Wong, Kam Cheong

2016-04-06

Clinicians use various clinical reasoning tools such as Ishikawa diagram to enhance their clinical experience and reasoning skills. Failure mode and effects analysis, which is an engineering methodology in origin, can be modified and applied to provide inputs into an Ishikawa diagram. The human biliary system is used to illustrate a modified failure mode and effects analysis. The anatomical and physiological processes of the biliary system are reviewed. Failure is defined as an abnormality caused by infective, inflammatory, obstructive, malignancy, autoimmune and other pathological processes. The potential failures, their effect(s), main clinical features, and investigation that can help a clinician to diagnose at each anatomical part and physiological process are reviewed and documented in a modified failure mode and effects analysis table. Relevant medical and surgical cases are retrieved from the medical literature and weaved into the table. A total of 80 clinical cases which are relevant to the modified failure mode and effects analysis for the human biliary system have been reviewed and weaved into a designated table. The table is the backbone and framework for further expansion. Reviewing and updating the table is an iterative and continual process. The relevant clinical features in the modified failure mode and effects analysis are then extracted and included in the relevant Ishikawa diagram. This article illustrates an application of engineering methodology in medicine, and it sows the seeds of potential cross-pollination between engineering and medicine. Establishing a modified failure mode and effects analysis can be a teamwork project or self-directed learning process, or a mix of both. Modified failure mode and effects analysis can be deployed to obtain inputs for an Ishikawa diagram which in turn can be used to enhance clinical experiences and clinical reasoning skills for clinicians, medical educators, and students.

StarPlan: A model-based diagnostic system for spacecraft

NASA Technical Reports Server (NTRS)

Heher, Dennis; Pownall, Paul

1990-01-01

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

Emotion in the Law and the Lab: The Case of Graphic Cigarette Warnings

PubMed Central

Peters, Ellen; Evans, Abigail T.; Hemmerich, Natalie; Berman, Micah

2017-01-01

The decision in RJ Reynolds vs. FDA (2012) to invalidate FDA’s proposed graphic health warnings was based in part on the reasoning that the proposed graphic warnings cued emotional responses and therefore could not be considered “factual.” However, this reasoning demonstrated the courts’ fundamental misunderstanding of current behavioral-science research. In contrast to the courts’ artificial separation of emotions from fact, we synthesize and interpret relevant research in basic decision sciences and describe an evidence-based characterization of how emotions influence consumer decision making through multiple mechanisms. We then explore how behavioral research gets “lost in translation” in the legal process and recommend ways that behavioral scientists can work with attorneys to remedy this problem. In order for science-based tobacco regulation to survive legal challenges from the tobacco industry, courts must have access to and be able to understand and apply the relevant research. Accordingly, behavioral laboratory researchers must consider the courts as an additional audience when designing research and reporting results. Researchers wishing to influence policy should also work closely with public health lawyers to have the greatest impact on the legal system. PMID:29057296

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…

KA-SB: from data integration to large scale reasoning

PubMed Central

Roldán-García, María del Mar; Navas-Delgado, Ismael; Kerzazi, Amine; Chniber, Othmane; Molina-Castro, Joaquín; Aldana-Montes, José F

2009-01-01

Background The analysis of information in the biological domain is usually focused on the analysis of data from single on-line data sources. Unfortunately, studying a biological process requires having access to disperse, heterogeneous, autonomous data sources. In this context, an analysis of the information is not possible without the integration of such data. Methods KA-SB is a querying and analysis system for final users based on combining a data integration solution with a reasoner. Thus, the tool has been created with a process divided into two steps: 1) KOMF, the Khaos Ontology-based Mediator Framework, is used to retrieve information from heterogeneous and distributed databases; 2) the integrated information is crystallized in a (persistent and high performance) reasoner (DBOWL). This information could be further analyzed later (by means of querying and reasoning). Results In this paper we present a novel system that combines the use of a mediation system with the reasoning capabilities of a large scale reasoner to provide a way of finding new knowledge and of analyzing the integrated information from different databases, which is retrieved as a set of ontology instances. This tool uses a graphical query interface to build user queries easily, which shows a graphical representation of the ontology and allows users o build queries by clicking on the ontology concepts. Conclusion These kinds of systems (based on KOMF) will provide users with very large amounts of information (interpreted as ontology instances once retrieved), which cannot be managed using traditional main memory-based reasoners. We propose a process for creating persistent and scalable knowledgebases from sets of OWL instances obtained by integrating heterogeneous data sources with KOMF. This process has been applied to develop a demo tool , which uses the BioPax Level 3 ontology as the integration schema, and integrates UNIPROT, KEGG, CHEBI, BRENDA and SABIORK databases. PMID:19796402

Computer-assisted learning and simulation systems in dentistry--a challenge to society.

PubMed

Welk, A; Splieth, Ch; Wierinck, E; Gilpatrick, R O; Meyer, G

2006-07-01

Computer technology is increasingly used in practical training at universities. However, in spite of their potential, computer-assisted learning (CAL) and computer-assisted simulation (CAS) systems still appear to be underutilized in dental education. Advantages, challenges, problems, and solutions of computer-assisted learning and simulation in dentistry are discussed by means of MEDLINE, open Internet platform searches, and key results of a study among German dental schools. The advantages of computer-assisted learning are seen for example in self-paced and self-directed learning and increased motivation. It is useful for both objective theoretical and practical tests and for training students to handle complex cases. CAL can lead to more structured learning and can support training in evidence-based decision-making. The reasons for the still relatively rare implementation of CAL/CAS systems in dental education include an inability to finance, lack of studies of CAL/CAS, and too much effort required to integrate CAL/CAS systems into the curriculum. To overcome the reasons for the relative low degree of computer technology use, we should strive for multicenter research and development projects monitored by the appropriate national and international scientific societies, so that the potential of computer technology can be fully realized in graduate, postgraduate, and continuing dental education.

Combined Case of Blood-Injury-Injection Phobia and Social Phobia: Behavior Therapy Management and Effectiveness through Tilt Test

PubMed Central

Ferenidou, Fotini; Chalimourdas, Theodoros; Antonakis, Velissarios; Vaidakis, Nikolaos; Papadimitriou, Georgios

2012-01-01

The efficacy of behavior therapy based mainly on real-life exposure situations as well as applied tension was examined for a combined case of blood-injury-injection (BII) phobia and social anxiety disorder. Treatment involved 28 behavior therapy sessions, while applied tension technique was also described and practiced. The specific contribution of social skills techniques, fantasy, and real-life situations exposure was examined in a single case design. The subject was a 39-year-old male with anxiety symptoms when confronting an audience, as well as symptoms of the autonomic nervous system (bradycardia and syncope), which were better explained by BII. All self-report measures regarding fear, social phobia, and anxiety were reduced after behavior therapy and remained maintained at followup, while BII decreased further after applied tension techniques. The contribution of behavior therapy to the overall outcome of the case is considered significant for many reasons that are discussed in the pape. PMID:23304602

Analysis of household refrigerators for different testing standards

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

Bansal, P.K.; McGill, I.

This study highlights the salient differences among various testing standards for household refrigerator-freezers and proposes a methodology for predicting the performance of a single evaporator-based vapor-compression refrigeration system (either refrigerator or freezer) from one test standard (where the test data are available-the reference case) to another (the alternative case). The standards studied during this investigation include the Australian-New Zealand Standard (ANZS), the International Standard (ISO), the American National Standard (ANSI), the Japanese Industrial Standard (JIS), and the Chinese National Standard (CNS). A simple analysis in conjunction with the BICYCLE model (Bansal and Rice 1993) is used to calculate the energymore » consumption of two refrigerator cabinets from the reference case to the alternative cases. The proposed analysis includes the effect of door openings (as required by the JIS) as well as defrost heaters. The analytical results are found to agree reasonably well with the experimental observations for translating energy consumption information from one standard to another.« less

Real-time automated failure identification in the Control Center Complex (CCC)

NASA Technical Reports Server (NTRS)

Kirby, Sarah; Lauritsen, Janet; Pack, Ginger; Ha, Anhhoang; Jowers, Steven; Mcnenny, Robert; Truong, The; Dell, James

1993-01-01

A system which will provide real-time failure management support to the Space Station Freedom program is described. The system's use of a simplified form of model based reasoning qualifies it as an advanced automation system. However, it differs from most such systems in that it was designed from the outset to meet two sets of requirements. First, it must provide a useful increment to the fault management capabilities of the Johnson Space Center (JSC) Control Center Complex (CCC) Fault Detection Management system. Second, it must satisfy CCC operational environment constraints such as cost, computer resource requirements, verification, and validation, etc. The need to meet both requirement sets presents a much greater design challenge than would have been the case had functionality been the sole design consideration. The choice of technology, discussing aspects of that choice and the process for migrating it into the control center is overviewed.

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.

Integration of perception and reasoning in fast neural modules

NASA Technical Reports Server (NTRS)

Fritz, David G.

1989-01-01

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

47 CFR 76.934 - Small systems and small cable companies.

Code of Federal Regulations, 2012 CFR

2012-10-01

... rules, or membership fees in social service, recreational or athletic clubs or associations. (ii) The... base, and reasonable rate of return on the basis of reasonable, good faith estimates. (5) After the... responsive documents that are missing or destroyed. (iii) A system may file with the Media Bureau an...

47 CFR 76.934 - Small systems and small cable companies.

Code of Federal Regulations, 2014 CFR

2014-10-01

... rules, or membership fees in social service, recreational or athletic clubs or associations. (ii) The... base, and reasonable rate of return on the basis of reasonable, good faith estimates. (5) After the... responsive documents that are missing or destroyed. (iii) A system may file with the Media Bureau an...

47 CFR 76.934 - Small systems and small cable companies.

Code of Federal Regulations, 2011 CFR

2011-10-01

... rules, or membership fees in social service, recreational or athletic clubs or associations. (ii) The... base, and reasonable rate of return on the basis of reasonable, good faith estimates. (5) After the... responsive documents that are missing or destroyed. (iii) A system may file with the Media Bureau an...

47 CFR 76.934 - Small systems and small cable companies.

Code of Federal Regulations, 2010 CFR

2010-10-01

... rules, or membership fees in social service, recreational or athletic clubs or associations. (ii) The... base, and reasonable rate of return on the basis of reasonable, good faith estimates. (5) After the... responsive documents that are missing or destroyed. (iii) A system may file with the Media Bureau an...

47 CFR 76.934 - Small systems and small cable companies.

Code of Federal Regulations, 2013 CFR

2013-10-01

... rules, or membership fees in social service, recreational or athletic clubs or associations. (ii) The... base, and reasonable rate of return on the basis of reasonable, good faith estimates. (5) After the... responsive documents that are missing or destroyed. (iii) A system may file with the Media Bureau an...

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.

Use of e-mail for Parkinson's disease consultations: Are answers just a clic away?

PubMed

Viedma-Guiard, E; Agüero, P; Crespo-Araico, L; Estévez-Fraga, C; Sánchez-Díez, G; López-Sendón, J L; Aviles-Olmos, I; García-Ribas, G; Palacios Romero, M L; Masjuan Vallejo, J; Martínez-Castrillo, J C; Alonso-Cánovas, A

2018-03-01

The clinical problems of patients with movement disorders (MD) are complex, and the duration and frequency of face-to-face consultations may be insufficient to meet their needs. We analysed the implementation of an e-mail-based query service for our MD unit's patients and their primary care physicians (PCPs). We retrospectively reviewed all consecutive emails sent and received over a period of 4 months, one year after implementation of the e-mail inquiry system. All patients received the during consultations, and PCPs, during scheduled informative meetings. We recorded and later analysed the profile of the questioner, patients' demographic and clinical data, number of queries, reason for consultation, and actions taken. From 1 January 2015 to 30 April 2015, the service received 137 emails from 63 patients (43% male, mean age 71±10.5) diagnosed with Parkinson's disease (76%), atypical parkinsonism (10%), and others (14%); 116 responses were sent. Twenty (32%) emails were written by patients, 38 (60%) by their caregivers, and 5 (8%) by their PCPs. The reasons for consultation were clinical in 50 cases (80%): 16 (32%) described clinical deterioration, 14 (28%) onset of new symptoms, and 20 (40%) side effects or concerns about medications. In 13 cases (20%), the query was bureaucratic: 11 were related to appointments (85%) and 2 were requests for clinical reports (15%). In response, new appointments were scheduled in 9 cases (14%), while the rest of the questions were answered by email. Patients were satisfied overall and the additional care burden on specialists was not excessive. Implementing an e-mail-based consultation system is feasible in MD units. It facilitates both communication between neurologists and patients and continued care in the primary care setting. Copyright © 2016 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

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

NASA Astrophysics Data System (ADS)

Dounas-Frazer, Dimitri

2016-05-01

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

Limitations and obstacles of the spontaneous adverse drugs reactions reporting: Two “challenging” case reports

PubMed Central

Palleria, Caterina; Leporini, Christian; Chimirri, Serafina; Marrazzo, Giuseppina; Sacchetta, Sabrina; Bruno, Lucrezia; Lista, Rosaria M.; Staltari, Orietta; Scuteri, Antonio; Scicchitano, Francesca; Russo, Emilio

2013-01-01

Introduction: Nowadays, based on several epidemiological data, iatrogenic disease is an emerging public health problem, especially in industrialized countries. Adverse drugs reactions (ADRs) are extremely common and, therefore, clinically, socially, and economically worthy of attention. Spontaneous reporting system for suspected ADRs represents the cornerstone of the pharmacovigilance, because it allows rapid detection of potential alarm signals related to drugs use. However, spontaneous reporting system shows several limitations, which are mainly related to under-reporting. In this paper, we describe two particular case reports, which emphasize some reasons of under-reporting and other common criticisms of spontaneous reporting systems. Materials and Methods: We performed a computer-aided search of Medline, PubMed, Embase, Cochrane library databases, national and international databases of suspected ADRs reports in order to identify previous published case reports and spontaneous reports about the ADRs reviewed in this paper, and to examine the role of suspected drugs in the pathogenesis of the described adverse reactions. Results: First, we reported a case of tizanidine-induced hemorrhagic cystitis. In the second case report, we presented an episode of asthma exacerbation after taking bimatoprost. Through the review of these two cases, we highlighted some common criticisms of spontaneous reporting systems: under-reporting and false causality attribution. Discussion and Conclusion: Healthcare workers sometimes do not report ADRs because it is challenging to establish with certainty the causal relationship between drug and adverse reaction; however, according to a key principle of pharmacovigilance, it is always better to report even a suspicion to generate an alarm in the interest of protecting public health. PMID:24347986

Limitations and obstacles of the spontaneous adverse drugs reactions reporting: Two "challenging" case reports.

PubMed

Palleria, Caterina; Leporini, Christian; Chimirri, Serafina; Marrazzo, Giuseppina; Sacchetta, Sabrina; Bruno, Lucrezia; Lista, Rosaria M; Staltari, Orietta; Scuteri, Antonio; Scicchitano, Francesca; Russo, Emilio

2013-12-01

Nowadays, based on several epidemiological data, iatrogenic disease is an emerging public health problem, especially in industrialized countries. Adverse drugs reactions (ADRs) are extremely common and, therefore, clinically, socially, and economically worthy of attention. Spontaneous reporting system for suspected ADRs represents the cornerstone of the pharmacovigilance, because it allows rapid detection of potential alarm signals related to drugs use. However, spontaneous reporting system shows several limitations, which are mainly related to under-reporting. In this paper, we describe two particular case reports, which emphasize some reasons of under-reporting and other common criticisms of spontaneous reporting systems. We performed a computer-aided search of Medline, PubMed, Embase, Cochrane library databases, national and international databases of suspected ADRs reports in order to identify previous published case reports and spontaneous reports about the ADRs reviewed in this paper, and to examine the role of suspected drugs in the pathogenesis of the described adverse reactions. First, we reported a case of tizanidine-induced hemorrhagic cystitis. In the second case report, we presented an episode of asthma exacerbation after taking bimatoprost. Through the review of these two cases, we highlighted some common criticisms of spontaneous reporting systems: under-reporting and false causality attribution. Healthcare workers sometimes do not report ADRs because it is challenging to establish with certainty the causal relationship between drug and adverse reaction; however, according to a key principle of pharmacovigilance, it is always better to report even a suspicion to generate an alarm in the interest of protecting public health.

The Weyl law for contractive maps

NASA Astrophysics Data System (ADS)

Spina, Maria E.; Rivas, Alejandro M. F.; Carlo, Gabriel

2013-11-01

We find an empirical Weyl law followed by the eigenvalues of contractive maps. An important property is that it is mainly insensitive to the dimension of the corresponding invariant classical set, the strange attractor. The usual explanation for the fractal Weyl law emergence in scattering systems (i.e., having a projective opening) is based on the classical phase space distributions evolved up to the quantum to classical correspondence (Ehrenfest) time. In the contractive case this reasoning fails to describe it. Instead, we conjecture that the support for this behavior is essentially given by the strong non-orthogonality of the eigenvectors of the contractive superoperator. We test the validity of the Weyl law and this conjecture on two paradigmatic systems, the dissipative baker and kicked top maps.

Analytic and Heuristic Processing Influences on Adolescent Reasoning and Decision-Making.

ERIC Educational Resources Information Center

Klaczynski, Paul A.

2001-01-01

Examined the relationship between age and the normative/descriptive gap--the discrepancy between actual reasoning and traditional standards for reasoning. Found that middle adolescents performed closer to normative ideals than early adolescents. Factor analyses suggested that performance was based on two processing systems, analytic and heuristic…

Model-Based Reasoning

ERIC Educational Resources Information Center

Ifenthaler, Dirk; Seel, Norbert M.

2013-01-01

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

An evaluation of a real-time fault diagnosis expert system for aircraft applications

NASA Technical Reports Server (NTRS)

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

1987-01-01

A fault monitoring and diagnosis expert system called Faultfinder was conceived and developed to detect and diagnose in-flight failures in an aircraft. Faultfinder is an automated intelligent aid whose purpose is to assist the flight crew in fault monitoring, fault diagnosis, and recovery planning. The present implementation of this concept performs monitoring and diagnosis for a generic aircraft's propulsion and hydraulic subsystems. This implementation is capable of detecting and diagnosing failures of known and unknown (i.e., unforseeable) type in a real-time environment. Faultfinder uses both rule-based and model-based reasoning strategies which operate on causal, temporal, and qualitative information. A preliminary evaluation is made of the diagnostic concepts implemented in Faultfinder. The evaluation used actual aircraft accident and incident cases which were simulated to assess the effectiveness of Faultfinder in detecting and diagnosing failures. Results of this evaluation, together with the description of the current Faultfinder implementation, are presented.

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.

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

NASA Technical Reports Server (NTRS)

Nelson, Kyle S.; Hadden, George D.

1992-01-01

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

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…

Neural correlates of belief-bias reasoning under time pressure: a near-infrared spectroscopy study.

PubMed

Tsujii, Takeo; Watanabe, Shigeru

2010-04-15

The dual-process theory of reasoning explained the belief-bias effect, the tendency for human reasoning to be erroneously biased when logical conclusions are incongruent with belief about the world, by proposing a belief-based fast heuristic system and a logic-based slow analytic system. Although the claims were supported by behavioral findings that the belief-bias effect was enhanced when subjects were not given sufficient time for reasoning, the neural correlates were still unknown. The present study therefore examined the relationship between the time-pressure effect and activity in the inferior frontal cortex (IFC) during belief-bias reasoning using near-infrared spectroscopy (NIRS). Forty-eight subjects performed congruent and incongruent reasoning tasks, involving long-span (20 s) and short-span trials (10 s). Behavioral analysis found that only incongruent reasoning performance was impaired by the time-pressure of short-span trials. NIRS analysis found that the time-pressure decreased right IFC activity during incongruent trials. Correlation analysis showed that subjects with enhanced right IFC activity could perform better in incongruent trials, while subjects for whom the right IFC activity was impaired by the time-pressure could not maintain better reasoning performance. These findings suggest that the right IFC may be responsible for the time-pressure effect in conflicting reasoning processes. When the right IFC activity was impaired in the short-span trials in which subjects were not given sufficient time for reasoning, the subjects may rely on the fast heuristic system, which result in belief-bias responses. We therefore offer the first demonstration of neural correlates of time-pressure effect on the IFC activity in belief-bias reasoning. Copyright 2009 Elsevier Inc. All rights reserved.

Evaluating model accuracy for model-based reasoning

NASA Technical Reports Server (NTRS)

Chien, Steve; Roden, Joseph

1992-01-01

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

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.

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…

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

PubMed

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

2016-11-01

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

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

PubMed

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

2018-06-14

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

Technological innovations in the development of cardiovascular clinical information systems.

PubMed

Hsieh, Nan-Chen; Chang, Chung-Yi; Lee, Kuo-Chen; Chen, Jeen-Chen; Chan, Chien-Hui

2012-04-01

Recent studies have shown that computerized clinical case management and decision support systems can be used to assist surgeons in the diagnosis of disease, optimize surgical operation, aid in drug therapy and decrease the cost of medical treatment. Therefore, medical informatics has become an extensive field of research and many of these approaches have demonstrated potential value for improving medical quality. The aim of this study was to develop a web-based cardiovascular clinical information system (CIS) based on innovative techniques, such as electronic medical records, electronic registries and automatic feature surveillance schemes, to provide effective tools and support for clinical care, decision-making, biomedical research and training activities. The CIS developed for this study contained monitoring, surveillance and model construction functions. The monitoring layer function provided a visual user interface. At the surveillance and model construction layers, we explored the application of model construction and intelligent prognosis to aid in making preoperative and postoperative predictions. With the use of the CIS, surgeons can provide reasonable conclusions and explanations in uncertain environments.

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.

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.

An adaptable architecture for patient cohort identification from diverse data sources

PubMed Central

Bache, Richard; Miles, Simon; Taweel, Adel

2013-01-01

Objective We define and validate an architecture for systems that identify patient cohorts for clinical trials from multiple heterogeneous data sources. This architecture has an explicit query model capable of supporting temporal reasoning and expressing eligibility criteria independently of the representation of the data used to evaluate them. Method The architecture has the key feature that queries defined according to the query model are both pre and post-processed and this is used to address both structural and semantic heterogeneity. The process of extracting the relevant clinical facts is separated from the process of reasoning about them. A specific instance of the query model is then defined and implemented. Results We show that the specific instance of the query model has wide applicability. We then describe how it is used to access three diverse data warehouses to determine patient counts. Discussion Although the proposed architecture requires greater effort to implement the query model than would be the case for using just SQL and accessing a data-based management system directly, this effort is justified because it supports both temporal reasoning and heterogeneous data sources. The query model only needs to be implemented once no matter how many data sources are accessed. Each additional source requires only the implementation of a lightweight adaptor. Conclusions The architecture has been used to implement a specific query model that can express complex eligibility criteria and access three diverse data warehouses thus demonstrating the feasibility of this approach in dealing with temporal reasoning and data heterogeneity. PMID:24064442

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.

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.

Numerical simulation of CdTe vertical Bridgman growth

NASA Astrophysics Data System (ADS)

Ouyang, Hong; Shyy, Wei

1997-04-01

Numerical simulation has been conducted for steady-state Bridgman growth of the CdTe crystal with two ampoule configurations, namely, flat base and semi-spherical base. The present model accounts for conduction, convection and radiation, as well as phase change dynamics. The enthalpy formulation for phase change has been incorporated into a pressure-based algorithm with multi-zone curvilinear grid systems. The entire system which consists of the furnace enclosure wall, the encapsulated gas and the ampoule, contains irregularly configured domains. To meet the competing needs of producing accurate solutions with reasonable computing resources, a two-level approach is employed. The present study reveals that although the two ampoule configurations are quite different, their influence on the melt-solid interface shape is modest, and the undesirable concave interface appears in both cases. Since the interface shape strongly depends on thermal conductivities between the melt and the crystal, as well as ampoule wall temperature, accurate prescriptions of materials transport properties and operating environment are crucial for successful numerical predictions.

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…

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

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

PubMed

Suebnukarn, Siriwan

2009-10-01

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

[The syndrome of Cotard: an overview].

PubMed

Van den Eynde, F; Debruyne, H; Portzky, M; De Saedeleer, S; Audenaert, K

2008-01-01

There is increasing controversy about whether psychiatric illnesses should be divided into categories. One of the reasons is that such a categorial system, by its very nature, cannot provide a detailed description of specific psychopathological symptoms. A patient with Cotard's syndrome, for instance, is characterised by a nihilistic delusion relating to his own body and the syndrome does not fit into any one category. We report on a case of Cotard's syndrome encountered at our clinic. To provide an overview of the characteristics of Cotard's syndrome, including its history, phenomenology, pathogenesis and treatment. A Medline search was conducted for the period 1980-2006 using the search term 'Cotard$'. This resulted in 68 publications, of which 18 were not used. Cross-references were used as well. Cotard's syndrome cannot be fitted unambiguously into any one category of the current classification system. Current evidence regarding Cotard's syndrome is based mainly on case studies and therefore no clarity can be obtained about the various aspects of the syndrome, such as prevalence, pathogenesis, treatment.

Evaluation of an interactive case simulation system in dermatology and venereology for medical students

PubMed Central

Wahlgren, Carl-Fredrik; Edelbring, Samuel; Fors, Uno; Hindbeck, Hans; Ståhle, Mona

2006-01-01

Background Most of the many computer resources used in clinical teaching of dermatology and venereology for medical undergraduates are information-oriented and focus mostly on finding a "correct" multiple-choice alternative or free-text answer. We wanted to create an interactive computer program, which facilitates not only factual recall but also clinical reasoning. Methods Through continuous interaction with students, a new computerised interactive case simulation system, NUDOV, was developed. It is based on authentic cases and contains images of real patients, actors and healthcare providers. The student selects a patient and proposes questions for medical history, examines the skin, and suggests investigations, diagnosis, differential diagnoses and further management. Feedback is given by comparing the user's own suggestions with those of a specialist. In addition, a log file of the student's actions is recorded. The program includes a large number of images, video clips and Internet links. It was evaluated with a student questionnaire and by randomising medical students to conventional teaching (n = 85) or conventional teaching plus NUDOV (n = 31) and comparing the results of the two groups in a final written examination. Results The questionnaire showed that 90% of the NUDOV students stated that the program facilitated their learning to a large/very large extent, and 71% reported that extensive working with authentic computerised cases made it easier to understand and learn about diseases and their management. The layout, user-friendliness and feedback concept were judged as good/very good by 87%, 97%, and 100%, respectively. Log files revealed that the students, in general, worked with each case for 60–90 min. However, the intervention group did not score significantly better than the control group in the written examination. Conclusion We created a computerised case simulation program allowing students to manage patients in a non-linear format supporting the clinical reasoning process. The student gets feedback through comparison with a specialist, eliminating the need for external scoring or correction. The model also permits discussion of case processing, since all transactions are stored in a log file. The program was highly appreciated by the students, but did not significantly improve their performance in the written final examination. PMID:16907972

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

Techniques and implementation of the embedded rule-based expert system using Ada

NASA Technical Reports Server (NTRS)

Liberman, Eugene M.; Jones, Robert E.

1991-01-01

Ada is becoming an increasingly popular programming language for large Government-funded software projects. Ada with its portability, transportability, and maintainability lends itself well to today's complex programming environment. In addition, expert systems have also assured a growing role in providing human-like reasoning capability and expertise for computer systems. The integration of expert system technology with Ada programming language, specifically a rule-based expert system using an ART-Ada (Automated Reasoning Tool for Ada) system shell is discussed. The NASA Lewis Research Center was chosen as a beta test site for ART-Ada. The test was conducted by implementing the existing Autonomous Power EXpert System (APEX), a Lisp-base power expert system, in ART-Ada. Three components, the rule-based expert system, a graphics user interface, and communications software make up SMART-Ada (Systems fault Management with ART-Ada). The main objective, to conduct a beta test on the ART-Ada rule-based expert system shell, was achieved. The system is operational. New Ada tools will assist in future successful projects. ART-Ada is one such tool and is a viable alternative to the straight Ada code when an application requires a rule-based or knowledge-based approach.

Experimental performances of a battery thermal management system using a phase change material

NASA Astrophysics Data System (ADS)

Hémery, Charles-Victor; Pra, Franck; Robin, Jean-François; Marty, Philippe

2014-12-01

Li-ion batteries are leading candidates for mobility because electric vehicles (EV) are an environmentally friendly mean of transport. With age, Li-ion cells show a more resistive behavior leading to extra heat generation. Another kind of problem called thermal runway arises when the cell is too hot, what happens in case of overcharge or short circuit. In order to evaluate the effect of these defects at the whole battery scale, an air-cooled battery module was built and tested, using electrical heaters instead of real cells for safety reasons. A battery thermal management system based on a phase change material is developed in that study. This passive system is coupled with an active liquid cooling system in order to initialize the battery temperature at the melting of the PCM. This initialization, or PCM solidification, can be performed during a charge for example, in other words when the energy from the network is available.

Dynamic analysis for solid waste management systems: an inexact multistage integer programming approach.

PubMed

Li, Yongping; Huang, Guohe

2009-03-01

In this study, a dynamic analysis approach based on an inexact multistage integer programming (IMIP) model is developed for supporting municipal solid waste (MSW) management under uncertainty. Techniques of interval-parameter programming and multistage stochastic programming are incorporated within an integer-programming framework. The developed IMIP can deal with uncertainties expressed as probability distributions and interval numbers, and can reflect the dynamics in terms of decisions for waste-flow allocation and facility-capacity expansion over a multistage context. Moreover, the IMIP can be used for analyzing various policy scenarios that are associated with different levels of economic consequences. The developed method is applied to a case study of long-term waste-management planning. The results indicate that reasonable solutions have been generated for binary and continuous variables. They can help generate desired decisions of system-capacity expansion and waste-flow allocation with a minimized system cost and maximized system reliability.

Temporal reasoning over clinical text: the state of the art

PubMed Central

Sun, Weiyi; Rumshisky, Anna; Uzuner, Ozlem

2013-01-01

Objectives To provide an overview of the problem of temporal reasoning over clinical text and to summarize the state of the art in clinical natural language processing for this task. Target audience This overview targets medical informatics researchers who are unfamiliar with the problems and applications of temporal reasoning over clinical text. Scope We review the major applications of text-based temporal reasoning, describe the challenges for software systems handling temporal information in clinical text, and give an overview of the state of the art. Finally, we present some perspectives on future research directions that emerged during the recent community-wide challenge on text-based temporal reasoning in the clinical domain. PMID:23676245

Evaluating the automated blood glucose pattern detection and case-retrieval modules of the 4 Diabetes Support System.

PubMed

Schwartz, Frank L; Vernier, Stanley J; Shubrook, Jay H; Marling, Cynthia R

2010-11-01

We have developed a prototypical case-based reasoning system to enhance management of patients with type 1 diabetes mellitus (T1DM). The system is capable of automatically analyzing large volumes of life events, self-monitoring of blood glucose readings, continuous glucose monitoring system results, and insulin pump data to detect clinical problems. In a preliminary study, manual entry of large volumes of life-event and other data was too burdensome for patients. In this study, life-event and pump data collection were automated, and then the system was reevaluated. Twenty-three adult T1DM patients on insulin pumps completed the five-week study. A usual daily schedule was entered into the database, and patients were only required to upload their insulin pump data to Medtronic's CareLink® Web site weekly. Situation assessment routines were run weekly for each participant to detect possible problems, and once the trial was completed, the case-retrieval module was tested. Using the situation assessment routines previously developed, the system found 295 possible problems. The enhanced system detected only 2.6 problems per patient per week compared to 4.9 problems per patient per week in the preliminary study (p=.017). Problems detected by the system were correctly identified in 97.9% of the cases, and 96.1% of these were clinically useful. With less life-event data, the system is unable to detect certain clinical problems and detects fewer problems overall. Additional work is needed to provide device/software interfaces that allow patients to provide this data quickly and conveniently. © 2010 Diabetes Technology Society.

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.

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...

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

PubMed

Rotor, Esmerita R; Capio, Catherine M

2018-03-01

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

MESA: An Interactive Modeling and Simulation Environment for Intelligent Systems Automation

NASA Technical Reports Server (NTRS)

Charest, Leonard

1994-01-01

This report describes MESA, a software environment for creating applications that automate NASA mission opterations. MESA enables intelligent automation by utilizing model-based reasoning techniques developed in the field of Artificial Intelligence. Model-based reasoning techniques are realized in Mesa through native support of causal modeling and discrete event simulation.

The mathematical bases for qualitative reasoning

NASA Technical Reports Server (NTRS)

Kalagnanam, Jayant; Simon, Herbert A.; Iwasaki, Yumi

1991-01-01

The practices of researchers in many fields who use qualitative reasoning are summarized and explained. The goal is to gain an understanding of the formal assumptions and mechanisms that underlie this kind of analysis. The explanations given are based on standard mathematical formalisms, particularly on ordinal properties, continuous differentiable functions, and the mathematics of nonlinear dynamic systems.

Investigating Image-Based Perception and Reasoning in Geometry

ERIC Educational Resources Information Center

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

2009-01-01

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

Laundry detergent pod ingestions: is there a need for endoscopy?

PubMed

Smith, Erika; Liebelt, Erica; Nogueira, Jan

2014-09-01

Laundry detergent pod (LDP) exposures in children have resulted in several referrals to the emergency department. Signs and symptoms can include gastrointestinal symptoms (vomiting, drooling), neurological symptoms (depressed sensorium), or metabolic changes (lactic acidosis). There is limited literature on esophageal injury following LDP ingestions. We reviewed three cases of pediatric LDP ingestions that underwent an upper endoscopy in a tertiary care pediatric hospital. All of our patients were younger than 3 years old. The upper endoscopies revealed superficial esophageal erosions in two patients and erythema in the other. None of the patients had oral burns. Two of them developed swallowing dysfunction. Follow-up upper GI studies were normal. Our three patients ingested laundry detergent pods and all of them developed some degree of esophageal injury despite the absence of oral erythema, ulcers, or swelling. A review of literature suggests LDP exposures are more severe than non-pod detergents. Reasons as to why this may be remain unclear, although investigation into the ingredients and mode of delivery may help us to better understand. In a literature review, no esophageal strictures have been reported after LDP ingestion. We reviewed esophageal injury classification systems in an attempt to predict who may be at greatest risk for stricture based on initial findings. Our case series demonstrates it is hard to predict esophageal injury based on signs and symptoms. Based on a literature review, long-term esophageal stricture is unlikely, but if gastrointestinal symptoms persist, it is reasonable to evaluate with an upper endoscopy. Larger studies are needed.

Orthopedics coding and funding.

PubMed

Baron, S; Duclos, C; Thoreux, P

2014-02-01

The French tarification à l'activité (T2A) prospective payment system is a financial system in which a health-care institution's resources are based on performed activity. Activity is described via the PMSI medical information system (programme de médicalisation du système d'information). The PMSI classifies hospital cases by clinical and economic categories known as diagnosis-related groups (DRG), each with an associated price tag. Coding a hospital case involves giving as realistic a description as possible so as to categorize it in the right DRG and thus ensure appropriate payment. For this, it is essential to understand what determines the pricing of inpatient stay: namely, the code for the surgical procedure, the patient's principal diagnosis (reason for admission), codes for comorbidities (everything that adds to management burden), and the management of the length of inpatient stay. The PMSI is used to analyze the institution's activity and dynamism: change on previous year, relation to target, and comparison with competing institutions based on indicators such as the mean length of stay performance indicator (MLS PI). The T2A system improves overall care efficiency. Quality of care, however, is not presently taken account of in the payment made to the institution, as there are no indicators for this; work needs to be done on this topic. Copyright © 2014. Published by Elsevier Masson SAS.

Comparison of ultra-congruent mobile- and fixed-bearing navigation-assisted total knee arthroplasty with minimum 5-year follow-up.

PubMed

Kim, Seong Hwan; Lim, Jung-Won; Ko, Young-Bong; Song, Min-Gu; Lee, Han-Jun

2016-11-01

The purpose of this study was to compare the midterm outcomes between fixed and mobile ultra-congruent (UC) bearings in total knee arthroplasty (TKA). This is a retrospective matched-pairs case-control study of patients who underwent primary navigation-assisted TKA with a minimum 5-year follow-up. A total of 182 cases involved the fixed UC bearing system as Group 1 and 101 cases involved mobile UC bearing system group as Group 2. After 1:1 matching, 73 knees in each group were enrolled. Clinical and radiographic outcomes were evaluated. The overall survival was 143 of 146 cases (97.9 %) at final follow-up, and 72 of 73 cases (96.3 %) in Group 1 and 71 of 73 cases (95.8 %) in Group 2 at final follow-up based on an endpoint of revision surgery. The reasons of revision TKA were periprosthetic fracture in Group 1, infection and bearing dislocation in Group 2. There was no statistical difference in Hospital for Special Surgery (HSS) scores, Knee Society Scores (KSS), WOMAC index score evaluations between groups. This study demonstrated that the fixed-bearing UC prosthesis could provide satisfactory performance compared with that of the mobile-bearing UC prosthesis with minimum 5-year follow-up. The fixed-bearing UC prosthesis could be considered in navigation-assisted TKA with theoretical advantages of UC design. IV.

Suspect until Proven Guilty a Problematization of State Dossier Systems via Two Case Studies: The United States and China

ERIC Educational Resources Information Center

Farrall, Kenneth N.

2009-01-01

This dissertation problematizes the "state dossier system" (SDS): the production and accumulation of personal information on citizen subjects exceeding the reasonable bounds of risk management. SDS--comprising interconnecting subsystems of records and identification--damage individual autonomy and self-determination, impacting not only…

Changing Minds by Reasoning About Belief Revision: A Challenge for Cognitive Systems

DTIC Science & Technology

2013-12-01

this case, his dialog moves could include highlighting unintended relationships suggested by the logo (e.g., that a competitor’s logo is an octopus , a...others, a cognitive system must, at a minimum, be able to entertain beliefs about their beliefs. Any movement at all toward more sophisticated scenarios

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.

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

Shahrukh, Hassan; Oyedun, Adetoyese Olajire; Kumar, Amit

Here, a process model was developed to determine the net energy ratio (NER) for production of pellets from steam pretreated agricultural residue (AR) and energy crop (i.e. switchgrass in this case). The NER is a ratio of the net energy output to the total net energy input from non-renewable energy sources into a system. Scenarios were developed to measure the effects of temperature and level of steam pretreatment on the NER of steam pretreated AR- and switch grass-based pellets. The NER for the base case at 6 kg h -1 is 1.76 and 1.37 for steam-pretreated AR- and switchgrass-based pellets,more » respectively. The reason behind the difference is that more energy is required to dry switchgrass pellets than AR pellets. The sensitivity analysis for the model shows that the optimum temperature for steam pretreatment is 160 C with 50% pretreatment (half the feedstock is pretreated, while the rest is undergoes regular pelletization). The uncertainty results for NER for steam pretreated AR and switch grass pellets are 1.62 ± 0.10 and 1.42 ± 0.11, respectively.« less

Treatment of severe fluoroacetamide poisoning in patient with combined multiple organ dysfunction syndrome by evidence-based integrated Chinese and Western medicines: A case report.

PubMed

Wen, Wanxin; Gao, Hongxia; Kang, Nini; Lu, Aili; Qian, Caiwen; Zhao, Yuanqi

2017-07-01

Fluoroacetamide poisoning is the acute and severe disease of human, which leads to nervous, digestive, and cardiovascular system damage or even death in a short period of time. We report a case of a 65-year-old woman with loss of consciousness, nausea, and vomiting who was sent to the hospital by passers-by. She was diagnosed with severe fluoroacetamide poisoning with combined multiple organ dysfunction syndrome. When the diagnosis was unclear, we gave gastric lavage, support and symptomatic treatment, and closely with the vital sign. When the diagnosis was clear, based on the evidence of retrieved, muscle injection of acetamide, calcium gluconate, and vitamin C. Traditional Chinese medicine aspect, oral administration of mung bean soup of glycyrrhizae and Da-Cheng-Qi decoction enema. By setting reasonable treatment for patients, she had no special discomfort and complications after treatment. Besides, through 1-month follow-up, it was confirmed that the treatments were effective. Evidence-based integrated Chinese and Western medicines can effectively improve the therapeutic effects in severe fluoroacetamide-poisoned patients with combined MODS.

A Web-based Examination System Based on PHP+MySQL.

PubMed

Wen, Ji; Zhang, Yang; Yan, Yong; Xia, Shunren

2005-01-01

The design and implementation of web-based examination system constructed by PHP and MySQL is presented in this paper. Three primary parts, including students',teachers' and administrators', are introduced and analyzed in detail. Initial application has demonstrated the system's feasibility and reasonability.^*

Central nervous system granulomastous phlebitis with limited extracranial involvement of the heart and lungs: An autopsy case.

PubMed

Mlakar, Jernej; Zorman, Jerneja Videčnik; Matičič, Mojca; Vrabec, Matej; Alibegović, Armin; Popović, Mara

2016-02-01

Primary angiitis of the central nervous system is a rare condition, usually with an insidious onset. There is a wide variety of histological types (granulomatous, lymphocytic or necrotizing vasculitis) and types of vessel involved (arteries, veins or both). Most cases are idiopathic. We describe a first case of idiopathic granulomatous central nervous system phlebitis with additional limited involvement of the heart and lung, exclusively affecting small and medium sized veins in a 22-year-old woman, presenting as a sub acute headache. The reasons for this peculiar limitation of inflammation to the veins and the involvement of the heart and lungs are unknown. © 2015 Japanese Society of Neuropathology.

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.

UM-PRS: An implementation of the procedural reasoning system for multirobot applications

NASA Technical Reports Server (NTRS)

Lee, Jaeho; Huber, Marcus J.; Durfee, Edmund H.; Kenny, Patrick G.

1994-01-01

The Procedural Reasoning System (PRS) is used in applications where predetermined situations might arise. The UM-PRS provides a reasoning system that represents robotic applications even in unpredictable domains, such as the robotic reconnaissance task domain outlined here. UM-PRS incorporates a changing context, rather than relying solely on a prearranged plan. The UM-PRS here provides representation important in the reasoning and interface between a mission plan and the executable map of an outdoor vehicle that changes its behavior based on what it comes in contact with in its environment. PRS is thus used in the dynamic control of such a vehicle, providing the basis for coordinating the joint task of multiple robotic vehicles by the their individual observations and representation.

Conceptual Representations for Transfer: A Case Study Tracing Back and Looking Forward

ERIC Educational Resources Information Center

Sinha, Suparna; Gray, Steven; Hmelo-Silver, Cindy E.; Jordan, Rebecca; Eberbach, Catherine; Goel, Ashok; Rugaber, Spencer

2013-01-01

A primary goal of instruction is to prepare learners to transfer their knowledge and skills to new contexts, but how far this transfer goes is an open question. In the research reported here, we seek to explain a case of transfer through examining the processes by which a conceptual representation used to reason about complex systems was…

Comparing features sets for content-based image retrieval in a medical-case database

NASA Astrophysics Data System (ADS)

Muller, Henning; Rosset, Antoine; Vallee, Jean-Paul; Geissbuhler, Antoine

2004-04-01

Content-based image retrieval systems (CBIRSs) have frequently been proposed for the use in medical image databases and PACS. Still, only few systems were developed and used in a real clinical environment. It rather seems that medical professionals define their needs and computer scientists develop systems based on data sets they receive with little or no interaction between the two groups. A first study on the diagnostic use of medical image retrieval also shows an improvement in diagnostics when using CBIRSs which underlines the potential importance of this technique. This article explains the use of an open source image retrieval system (GIFT - GNU Image Finding Tool) for the retrieval of medical images in the medical case database system CasImage that is used in daily, clinical routine in the university hospitals of Geneva. Although the base system of GIFT shows an unsatisfactory performance, already little changes in the feature space show to significantly improve the retrieval results. The performance of variations in feature space with respect to color (gray level) quantizations and changes in texture analysis (Gabor filters) is compared. Whereas stock photography relies mainly on colors for retrieval, medical images need a large number of gray levels for successful retrieval, especially when executing feedback queries. The results also show that a too fine granularity in the gray levels lowers the retrieval quality, especially with single-image queries. For the evaluation of the retrieval peformance, a subset of the entire case database of more than 40,000 images is taken with a total of 3752 images. Ground truth was generated by a user who defined the expected query result of a perfect system by selecting images relevant to a given query image. The results show that a smaller number of gray levels (32 - 64) leads to a better retrieval performance, especially when using relevance feedback. The use of more scales and directions for the Gabor filters in the texture analysis also leads to improved results but response time is going up equally due to the larger feature space. CBIRSs can be of great use in managing large medical image databases. They allow to find images that might otherwise be lost for research and publications. They also give students students the possibility to navigate within large image repositories. In the future, CBIR might also become more important in case-based reasoning and evidence-based medicine to support the diagnostics because first studies show good results.

Emotional see-saw affects rationality of decision-making: Evidence for metacognitive impairments.

PubMed

Folwarczny, Michał; Kaczmarek, Magdalena C; Doliński, Dariusz; Szczepanowski, Remigiusz

2018-05-01

This research investigated the cognitive mechanisms that underlie impairments in human reasoning triggered by the emotional see-saw technique. It has previously been stated that such manipulation is effective as it presumably induces a mindless state and cognitive deficits in compliant individuals. Based on the dual-system architecture of reasoning (system 2) and affective decision-making (system 1), we challenged the previous theoretical account by indicating that the main source of compliance is impairment of the meta-reasoning system when rapid affective changes occur. To examine this hypothesis, we manipulated affective feelings (system 1 processing) by violating participants' expectations regarding reward and performance in a go/no-go task in which individuals were to inhibit their responses to earn money. Aside from the go/no-go performance, we measured rationality (meta-reasoning system 2) in decision-making by asking participants to comply with a nonsensical request. We found that participants who were exposed to meta-reasoning impairments due to the emotional see-saw phenomenon exhibited mindless behavior. Copyright © 2018 Elsevier B.V. All rights reserved.

Certification Strategies using Run-Time Safety Assurance for Part 23 Autopilot Systems

NASA Technical Reports Server (NTRS)

Hook, Loyd R.; Clark, Matthew; Sizoo, David; Skoog, Mark A.; Brady, James

2016-01-01

Part 23 aircraft operation, and in particular general aviation, is relatively unsafe when compared to other common forms of vehicle travel. Currently, there exists technologies that could increase safety statistics for these aircraft; however, the high burden and cost of performing the requisite safety critical certification processes for these systems limits their proliferation. For this reason, many entities, including the Federal Aviation Administration, NASA, and the US Air Force, are considering new options for certification for technologies that will improve aircraft safety. Of particular interest, are low cost autopilot systems for general aviation aircraft, as these systems have the potential to positively and significantly affect safety statistics. This paper proposes new systems and techniques, leveraging run-time verification, for the assurance of general aviation autopilot systems, which would be used to supplement the current certification process and provide a viable path for near-term low-cost implementation. In addition, discussions on preliminary experimentation and building the assurance case for a system, based on these principles, is provided.

Computer Based Intelligence Support: An Integrated Expert System and Decision Support Systems Approach

DTIC Science & Technology

1988-06-01

and for that reason has received considerable attention recently. Of particular interest in this research Is the work of Toulmin et. al. [19793 In...whenever we make a claim there must be some grounds in which to base our conclusion, Toulmin states that our thoughts are generally directed from the...WARRANT will be the absolute reason to believe the CLAIM on the basis of the GROUNDS. For that, Toulmin allows for further BACKING which, in his

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…

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

PubMed

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

2006-01-01

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

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.

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

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

PubMed

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

2017-01-11

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

Cognitive success: instrumental justifications of normative systems of reasoning.

PubMed

Schurz, Gerhard

2014-01-01

In the first part of the paper (sec. 1-4), I argue that Elqayam and Evan's (2011) distinction between normative and instrumental conceptions of cognitive rationality corresponds to deontological vs. teleological accounts in meta-ethics. I suggest that Elqayam and Evans' distinction be replaced by the distinction between a-priori intuition-based vs. a-posteriori success-based accounts of cognitive rationality. The value of cognitive success lies in its instrumental rationality for almost-all practical purposes. In the second part (sec. 5-7), I point out that the Elqayam and Evans's distinction between normative and instrumental rationality is coupled with a second distinction: between logically general vs. locally adaptive accounts of rationality. I argue that these are two independent distinctions that should be treated as independent dimensions. I also demonstrate that logically general systems of reasoning can be instrumentally justified. However, such systems can only be cognitively successful if they are paired with successful inductive reasoning, which is the area where the program of adaptive (ecological) rationality emerged, because there are no generally optimal inductive reasoning methods. I argue that the practical necessity of reasoning under changing environments constitutes a dilemma for ecological rationality, which I attempt to solve within a dual account of rationality.

TermGenie – a web-application for pattern-based ontology class generation

DOE PAGES

Dietze, Heiko; Berardini, Tanya Z.; Foulger, Rebecca E.; ...

2014-01-01

Biological ontologies are continually growing and improving from requests for new classes (terms) by biocurators. These ontology requests can frequently create bottlenecks in the biocuration process, as ontology developers struggle to keep up, while manually processing these requests and create classes. TermGenie allows biocurators to generate new classes based on formally specified design patterns or templates. The system is web-based and can be accessed by any authorized curator through a web browser. Automated rules and reasoning engines are used to ensure validity, uniqueness and relationship to pre-existing classes. In the last 4 years the Gene Ontology TermGenie generated 4715 newmore » classes, about 51.4% of all new classes created. The immediate generation of permanent identifiers proved not to be an issue with only 70 (1.4%) obsoleted classes. Lastly, TermGenie is a web-based class-generation system that complements traditional ontology development tools. All classes added through pre-defined templates are guaranteed to have OWL equivalence axioms that are used for automatic classification and in some cases inter-ontology linkage. At the same time, the system is simple and intuitive and can be used by most biocurators without extensive training.« less

TermGenie – a web-application for pattern-based ontology class generation

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

Dietze, Heiko; Berardini, Tanya Z.; Foulger, Rebecca E.

Biological ontologies are continually growing and improving from requests for new classes (terms) by biocurators. These ontology requests can frequently create bottlenecks in the biocuration process, as ontology developers struggle to keep up, while manually processing these requests and create classes. TermGenie allows biocurators to generate new classes based on formally specified design patterns or templates. The system is web-based and can be accessed by any authorized curator through a web browser. Automated rules and reasoning engines are used to ensure validity, uniqueness and relationship to pre-existing classes. In the last 4 years the Gene Ontology TermGenie generated 4715 newmore » classes, about 51.4% of all new classes created. The immediate generation of permanent identifiers proved not to be an issue with only 70 (1.4%) obsoleted classes. Lastly, TermGenie is a web-based class-generation system that complements traditional ontology development tools. All classes added through pre-defined templates are guaranteed to have OWL equivalence axioms that are used for automatic classification and in some cases inter-ontology linkage. At the same time, the system is simple and intuitive and can be used by most biocurators without extensive training.« less

TermGenie - a web-application for pattern-based ontology class generation.

PubMed

Dietze, Heiko; Berardini, Tanya Z; Foulger, Rebecca E; Hill, David P; Lomax, Jane; Osumi-Sutherland, David; Roncaglia, Paola; Mungall, Christopher J

2014-01-01

Biological ontologies are continually growing and improving from requests for new classes (terms) by biocurators. These ontology requests can frequently create bottlenecks in the biocuration process, as ontology developers struggle to keep up, while manually processing these requests and create classes. TermGenie allows biocurators to generate new classes based on formally specified design patterns or templates. The system is web-based and can be accessed by any authorized curator through a web browser. Automated rules and reasoning engines are used to ensure validity, uniqueness and relationship to pre-existing classes. In the last 4 years the Gene Ontology TermGenie generated 4715 new classes, about 51.4% of all new classes created. The immediate generation of permanent identifiers proved not to be an issue with only 70 (1.4%) obsoleted classes. TermGenie is a web-based class-generation system that complements traditional ontology development tools. All classes added through pre-defined templates are guaranteed to have OWL equivalence axioms that are used for automatic classification and in some cases inter-ontology linkage. At the same time, the system is simple and intuitive and can be used by most biocurators without extensive training.