Knowledge management impact of information technology Web 2.0/3.0. The case study of agent software technology usability in knowledge management system

NASA Astrophysics Data System (ADS)

Sołtysik-Piorunkiewicz, Anna

2015-02-01

How we can measure the impact of internet technology Web 2.0/3.0 for knowledge management? How we can use the Web 2.0/3.0 technologies for generating, evaluating, sharing, organizing knowledge in knowledge-based organization? How we can evaluate it from user-centered perspective? Article aims to provide a method for evaluate the usability of web technologies to support knowledge management in knowledge-based organizations of the various stages of the cycle knowledge management, taking into account: generating knowledge, evaluating knowledge, sharing knowledge, etc. for the modern Internet technologies based on the example of agent technologies. The method focuses on five areas of evaluation: GUI, functional structure, the way of content publication, organizational aspect, technological aspect. The method is based on the proposed indicators relating respectively to assess specific areas of evaluation, taking into account the individual characteristics of the scoring. Each of the features identified in the evaluation is judged first point wise, then this score is subject to verification and clarification by means of appropriate indicators of a given feature. The article proposes appropriate indicators to measure the impact of Web 2.0/3.0 technologies for knowledge management and verification them in an example of agent technology usability in knowledge management system.

A diagnostic prototype of the potable water subsystem of the Space Station Freedom ECLSS

NASA Technical Reports Server (NTRS)

Lukefahr, Brenda D.; Rochowiak, Daniel M.; Benson, Brian L.; Rogers, John S.; Mckee, James W.

1989-01-01

In analyzing the baseline Environmental Control and Life Support System (ECLSS) command and control architecture, various processes are found which would be enhanced by the use of knowledge based system methods of implementation. The most suitable process for prototyping using rule based methods are documented, while domain knowledge resources and other practical considerations are examined. Requirements for a prototype rule based software system are documented. These requirements reflect Space Station Freedom ECLSS software and hardware development efforts, and knowledge based system requirements. A quick prototype knowledge based system environment is researched and developed.

Machine intelligence and autonomy for aerospace systems

NASA Technical Reports Server (NTRS)

Heer, Ewald (Editor); Lum, Henry (Editor)

1988-01-01

The present volume discusses progress toward intelligent robot systems in aerospace applications, NASA Space Program automation and robotics efforts, the supervisory control of telerobotics in space, machine intelligence and crew/vehicle interfaces, expert-system terms and building tools, and knowledge-acquisition for autonomous systems. Also discussed are methods for validation of knowledge-based systems, a design methodology for knowledge-based management systems, knowledge-based simulation for aerospace systems, knowledge-based diagnosis, planning and scheduling methods in AI, the treatment of uncertainty in AI, vision-sensing techniques in aerospace applications, image-understanding techniques, tactile sensing for robots, distributed sensor integration, and the control of articulated and deformable space structures.

A rule-based named-entity recognition method for knowledge extraction of evidence-based dietary recommendations

PubMed Central

2017-01-01

Evidence-based dietary information represented as unstructured text is a crucial information that needs to be accessed in order to help dietitians follow the new knowledge arrives daily with newly published scientific reports. Different named-entity recognition (NER) methods have been introduced previously to extract useful information from the biomedical literature. They are focused on, for example extracting gene mentions, proteins mentions, relationships between genes and proteins, chemical concepts and relationships between drugs and diseases. In this paper, we present a novel NER method, called drNER, for knowledge extraction of evidence-based dietary information. To the best of our knowledge this is the first attempt at extracting dietary concepts. DrNER is a rule-based NER that consists of two phases. The first one involves the detection and determination of the entities mention, and the second one involves the selection and extraction of the entities. We evaluate the method by using text corpora from heterogeneous sources, including text from several scientifically validated web sites and text from scientific publications. Evaluation of the method showed that drNER gives good results and can be used for knowledge extraction of evidence-based dietary recommendations. PMID:28644863

Research and application of knowledge resources network for product innovation.

PubMed

Li, Chuan; Li, Wen-qiang; Li, Yan; Na, Hui-zhen; Shi, Qian

2015-01-01

In order to enhance the capabilities of knowledge service in product innovation design service platform, a method of acquiring knowledge resources supporting for product innovation from the Internet and providing knowledge active push is proposed. Through knowledge modeling for product innovation based on ontology, the integrated architecture of knowledge resources network is put forward. The technology for the acquisition of network knowledge resources based on focused crawler and web services is studied. Knowledge active push is provided for users by user behavior analysis and knowledge evaluation in order to improve users' enthusiasm for participation in platform. Finally, an application example is illustrated to prove the effectiveness of the method.

Translating three states of knowledge--discovery, invention, and innovation

PubMed Central

2010-01-01

Background Knowledge Translation (KT) has historically focused on the proper use of knowledge in healthcare delivery. A knowledge base has been created through empirical research and resides in scholarly literature. Some knowledge is amenable to direct application by stakeholders who are engaged during or after the research process, as shown by the Knowledge to Action (KTA) model. Other knowledge requires multiple transformations before achieving utility for end users. For example, conceptual knowledge generated through science or engineering may become embodied as a technology-based invention through development methods. The invention may then be integrated within an innovative device or service through production methods. To what extent is KT relevant to these transformations? How might the KTA model accommodate these additional development and production activities while preserving the KT concepts? Discussion Stakeholders adopt and use knowledge that has perceived utility, such as a solution to a problem. Achieving a technology-based solution involves three methods that generate knowledge in three states, analogous to the three classic states of matter. Research activity generates discoveries that are intangible and highly malleable like a gas; development activity transforms discoveries into inventions that are moderately tangible yet still malleable like a liquid; and production activity transforms inventions into innovations that are tangible and immutable like a solid. The paper demonstrates how the KTA model can accommodate all three types of activity and address all three states of knowledge. Linking the three activities in one model also illustrates the importance of engaging the relevant stakeholders prior to initiating any knowledge-related activities. Summary Science and engineering focused on technology-based devices or services change the state of knowledge through three successive activities. Achieving knowledge implementation requires methods that accommodate these three activities and knowledge states. Accomplishing beneficial societal impacts from technology-based knowledge involves the successful progression through all three activities, and the effective communication of each successive knowledge state to the relevant stakeholders. The KTA model appears suitable for structuring and linking these processes. PMID:20205873

Combining Open-domain and Biomedical Knowledge for Topic Recognition in Consumer Health Questions.

PubMed

Mrabet, Yassine; Kilicoglu, Halil; Roberts, Kirk; Demner-Fushman, Dina

2016-01-01

Determining the main topics in consumer health questions is a crucial step in their processing as it allows narrowing the search space to a specific semantic context. In this paper we propose a topic recognition approach based on biomedical and open-domain knowledge bases. In the first step of our method, we recognize named entities in consumer health questions using an unsupervised method that relies on a biomedical knowledge base, UMLS, and an open-domain knowledge base, DBpedia. In the next step, we cast topic recognition as a binary classification problem of deciding whether a named entity is the question topic or not. We evaluated our approach on a dataset from the National Library of Medicine (NLM), introduced in this paper, and another from the Genetic and Rare Disease Information Center (GARD). The combination of knowledge bases outperformed the results obtained by individual knowledge bases by up to 16.5% F1 and achieved state-of-the-art performance. Our results demonstrate that combining open-domain knowledge bases with biomedical knowledge bases can lead to a substantial improvement in understanding user-generated health content.

Argumentation Based Joint Learning: A Novel Ensemble Learning Approach

PubMed Central

Xu, Junyi; Yao, Li; Li, Le

2015-01-01

Recently, ensemble learning methods have been widely used to improve classification performance in machine learning. In this paper, we present a novel ensemble learning method: argumentation based multi-agent joint learning (AMAJL), which integrates ideas from multi-agent argumentation, ensemble learning, and association rule mining. In AMAJL, argumentation technology is introduced as an ensemble strategy to integrate multiple base classifiers and generate a high performance ensemble classifier. We design an argumentation framework named Arena as a communication platform for knowledge integration. Through argumentation based joint learning, high quality individual knowledge can be extracted, and thus a refined global knowledge base can be generated and used independently for classification. We perform numerous experiments on multiple public datasets using AMAJL and other benchmark methods. The results demonstrate that our method can effectively extract high quality knowledge for ensemble classifier and improve the performance of classification. PMID:25966359

Segmentation of medical images using explicit anatomical knowledge

NASA Astrophysics Data System (ADS)

Wilson, Laurie S.; Brown, Stephen; Brown, Matthew S.; Young, Jeanne; Li, Rongxin; Luo, Suhuai; Brandt, Lee

1999-07-01

Knowledge-based image segmentation is defined in terms of the separation of image analysis procedures and representation of knowledge. Such architecture is particularly suitable for medical image segmentation, because of the large amount of structured domain knowledge. A general methodology for the application of knowledge-based methods to medical image segmentation is described. This includes frames for knowledge representation, fuzzy logic for anatomical variations, and a strategy for determining the order of segmentation from the modal specification. This method has been applied to three separate problems, 3D thoracic CT, chest X-rays and CT angiography. The application of the same methodology to such a range of applications suggests a major role in medical imaging for segmentation methods incorporating representation of anatomical knowledge.

System and method for knowledge based matching of users in a network

DOEpatents

Verspoor, Cornelia Maria [Santa Fe, NM; Sims, Benjamin Hayden [Los Alamos, NM; Ambrosiano, John Joseph [Los Alamos, NM; Cleland, Timothy James [Los Alamos, NM

2011-04-26

A knowledge-based system and methods to matchmaking and social network extension are disclosed. The system is configured to allow users to specify knowledge profiles, which are collections of concepts that indicate a certain topic or area of interest selected from an. The system utilizes the knowledge model as the semantic space within which to compare similarities in user interests. The knowledge model is hierarchical so that indications of interest in specific concepts automatically imply interest in more general concept. Similarity measures between profiles may then be calculated based on suitable distance formulas within this space.

Participatory approach to the development of a knowledge base for problem-solving in diabetes self-management

PubMed Central

Cole-Lewis, Heather J.; Smaldone, Arlene M.; Davidson, Patricia R.; Kukafka, Rita; Tobin, Jonathan N.; Cassells, Andrea; Mynatt, Elizabeth D.; Hripcsak, George; Mamykina, Lena

2015-01-01

Objective To develop an expandable knowledge base of reusable knowledge related to self-management of diabetes that can be used as a foundation for patient-centric decision support tools. Materials and methods The structure and components of the knowledge base were created in participatory design with academic diabetes educators using knowledge acquisition methods. The knowledge base was validated using scenario-based approach with practicing diabetes educators and individuals with diabetes recruited from Community Health Centers (CHCs) serving economically disadvantaged communities and ethnic minorities in New York. Results The knowledge base includes eight glycemic control problems, over 150 behaviors known to contribute to these problems coupled with contextual explanations, and over 200 specific action-oriented self-management goals for correcting problematic behaviors, with corresponding motivational messages. The validation of the knowledge base suggested high level of completeness and accuracy, and identified improvements in cultural appropriateness. These were addressed in new iterations of the knowledge base. Discussion The resulting knowledge base is theoretically grounded, incorporates practical and evidence-based knowledge used by diabetes educators in practice settings, and allows for personally meaningful choices by individuals with diabetes. Participatory design approach helped researchers to capture implicit knowledge of practicing diabetes educators and make it explicit and reusable. Conclusion The knowledge base proposed here is an important step towards development of new generation patient-centric decision support tools for facilitating chronic disease self-management. While this knowledge base specifically targets diabetes, its overall structure and composition can be generalized to other chronic conditions. PMID:26547253

Word sense disambiguation in the clinical domain: a comparison of knowledge-rich and knowledge-poor unsupervised methods

PubMed Central

Chasin, Rachel; Rumshisky, Anna; Uzuner, Ozlem; Szolovits, Peter

2014-01-01

Objective To evaluate state-of-the-art unsupervised methods on the word sense disambiguation (WSD) task in the clinical domain. In particular, to compare graph-based approaches relying on a clinical knowledge base with bottom-up topic-modeling-based approaches. We investigate several enhancements to the topic-modeling techniques that use domain-specific knowledge sources. Materials and methods The graph-based methods use variations of PageRank and distance-based similarity metrics, operating over the Unified Medical Language System (UMLS). Topic-modeling methods use unlabeled data from the Multiparameter Intelligent Monitoring in Intensive Care (MIMIC II) database to derive models for each ambiguous word. We investigate the impact of using different linguistic features for topic models, including UMLS-based and syntactic features. We use a sense-tagged clinical dataset from the Mayo Clinic for evaluation. Results The topic-modeling methods achieve 66.9% accuracy on a subset of the Mayo Clinic's data, while the graph-based methods only reach the 40–50% range, with a most-frequent-sense baseline of 56.5%. Features derived from the UMLS semantic type and concept hierarchies do not produce a gain over bag-of-words features in the topic models, but identifying phrases from UMLS and using syntax does help. Discussion Although topic models outperform graph-based methods, semantic features derived from the UMLS prove too noisy to improve performance beyond bag-of-words. Conclusions Topic modeling for WSD provides superior results in the clinical domain; however, integration of knowledge remains to be effectively exploited. PMID:24441986

37: COMPARISON OF TWO METHODS: TBL-BASED AND LECTURE-BASED LEARNING IN NURSING CARE OF PATIENTS WITH DIABETES IN NURSING STUDENTS

PubMed Central

Khodaveisi, Masoud; Qaderian, Khosro; Oshvandi, Khodayar; Soltanian, Ali Reza; Vardanjani, Mehdi molavi

2017-01-01

Background and aims learning plays an important role in developing nursing skills and right care-taking. The Present study aims to evaluate two learning methods based on team –based learning and lecture-based learning in learning care-taking of patients with diabetes in nursing students. Method In this quasi-experimental study, 64 students in term 4 in nursing college of Bukan and Miandoab were included in the study based on knowledge and performance questionnaire including 15 questions based on knowledge and 5 questions based on performance on care-taking in patients with diabetes were used as data collection tool whose reliability was confirmed by cronbach alpha (r=0.83) by the researcher. To compare the mean score of knowledge and performance in each group in pre-test step and post-test step, pair –t test and to compare mean of scores in two groups of control and intervention, the independent t- test was used. Results There was not significant statistical difference between two groups in pre terms of knowledge and performance score (p=0.784). There was significant difference between the mean of knowledge scores and diabetes performance in the post-test in the team-based learning group and lecture-based learning group (p=0.001). There was significant difference between the mean score of knowledge of diabetes care in pre-test and post-test in base learning groups (p=0.001). Conclusion In both methods team-based and lecture-based learning approaches resulted in improvement in learning in students, but the rate of learning in the team-based learning approach is greater compared to that of lecture-based learning and it is recommended that this method be used as a higher education method in the education of students.

Comparison of clinical knowledge bases for summarization of electronic health records.

PubMed

McCoy, Allison B; Sittig, Dean F; Wright, Adam

2013-01-01

Automated summarization tools that create condition-specific displays may improve clinician efficiency. These tools require new kinds of knowledge that is difficult to obtain. We compared five problem-medication pair knowledge bases generated using four previously described knowledge base development approaches. The number of pairs in the resulting mapped knowledge bases varied widely due to differing mapping techniques from the source terminologies, ranging from 2,873 to 63,977,738 pairs. The number of overlapping pairs across knowledge bases was low, with one knowledge base having half of the pairs overlapping with another knowledge base, and most having less than a third overlapping. Further research is necessary to better evaluate the knowledge bases independently in additional settings, and to identify methods to integrate the knowledge bases.

Research and Application of Knowledge Resources Network for Product Innovation

PubMed Central

Li, Chuan; Li, Wen-qiang; Li, Yan; Na, Hui-zhen; Shi, Qian

2015-01-01

In order to enhance the capabilities of knowledge service in product innovation design service platform, a method of acquiring knowledge resources supporting for product innovation from the Internet and providing knowledge active push is proposed. Through knowledge modeling for product innovation based on ontology, the integrated architecture of knowledge resources network is put forward. The technology for the acquisition of network knowledge resources based on focused crawler and web services is studied. Knowledge active push is provided for users by user behavior analysis and knowledge evaluation in order to improve users' enthusiasm for participation in platform. Finally, an application example is illustrated to prove the effectiveness of the method. PMID:25884031

Development and evaluation of a crowdsourcing methodology for knowledge base construction: identifying relationships between clinical problems and medications

PubMed Central

Wright, Adam; Laxmisan, Archana; Ottosen, Madelene J; McCoy, Jacob A; Butten, David; Sittig, Dean F

2012-01-01

Objective We describe a novel, crowdsourcing method for generating a knowledge base of problem–medication pairs that takes advantage of manually asserted links between medications and problems. Methods Through iterative review, we developed metrics to estimate the appropriateness of manually entered problem–medication links for inclusion in a knowledge base that can be used to infer previously unasserted links between problems and medications. Results Clinicians manually linked 231 223 medications (55.30% of prescribed medications) to problems within the electronic health record, generating 41 203 distinct problem–medication pairs, although not all were accurate. We developed methods to evaluate the accuracy of the pairs, and after limiting the pairs to those meeting an estimated 95% appropriateness threshold, 11 166 pairs remained. The pairs in the knowledge base accounted for 183 127 total links asserted (76.47% of all links). Retrospective application of the knowledge base linked 68 316 medications not previously linked by a clinician to an indicated problem (36.53% of unlinked medications). Expert review of the combined knowledge base, including inferred and manually linked problem–medication pairs, found a sensitivity of 65.8% and a specificity of 97.9%. Conclusion Crowdsourcing is an effective, inexpensive method for generating a knowledge base of problem–medication pairs that is automatically mapped to local terminologies, up-to-date, and reflective of local prescribing practices and trends. PMID:22582202

Ontological modelling of knowledge management for human-machine integrated design of ultra-precision grinding machine

NASA Astrophysics Data System (ADS)

Hong, Haibo; Yin, Yuehong; Chen, Xing

2016-11-01

Despite the rapid development of computer science and information technology, an efficient human-machine integrated enterprise information system for designing complex mechatronic products is still not fully accomplished, partly because of the inharmonious communication among collaborators. Therefore, one challenge in human-machine integration is how to establish an appropriate knowledge management (KM) model to support integration and sharing of heterogeneous product knowledge. Aiming at the diversity of design knowledge, this article proposes an ontology-based model to reach an unambiguous and normative representation of knowledge. First, an ontology-based human-machine integrated design framework is described, then corresponding ontologies and sub-ontologies are established according to different purposes and scopes. Second, a similarity calculation-based ontology integration method composed of ontology mapping and ontology merging is introduced. The ontology searching-based knowledge sharing method is then developed. Finally, a case of human-machine integrated design of a large ultra-precision grinding machine is used to demonstrate the effectiveness of the method.

A comparison of two differential methods for nutrition education in elementary school: lecture-and experience-based learning program.

PubMed

Jung, Lan-Hee; Choi, Jeong-Hwa; Bang, Hyun-Mi; Shin, Jun-Ho; Heo, Young-Ran

2015-02-01

This research was conducted to compare lecture-and experience-based methods of nutritional education as well as provide fundamental data for developing an effective nutritional education program in elementary schools. A total of 110 students in three elementary schools in Jeollanam-do were recruited and randomly distributed in lecture-and experience-based groups. The effects of education on students' dietary knowledge, dietary behaviors, and dietary habits were analyzed using a pre/post-test. Lecture-and experience-based methods did not significantly alter total scores for dietary knowledge in any group, although lecture-based method led to improvement for some detailed questions. In the experience-based group, subjects showed significant alteration of dietary behaviors, whereas lecture-based method showed alteration of dietary habits. These outcomes suggest that lecture-and experience-based methods led to differential improvement of students' dietary habits, behaviors, and knowledge. To obtain better nutritional education results, both lectures and experiential activities need to be considered.

A Method for Cognitive Task Analysis

DTIC Science & Technology

1992-07-01

A method for cognitive task analysis is described based on the notion of ’generic tasks’. The method distinguishes three layers of analysis. At the...model for applied areas such as the development of knowledge-based systems and training, are discussed. Problem solving, Cognitive Task Analysis , Knowledge, Strategies.

Ontology-based configuration of problem-solving methods and generation of knowledge-acquisition tools: application of PROTEGE-II to protocol-based decision support.

PubMed

Tu, S W; Eriksson, H; Gennari, J H; Shahar, Y; Musen, M A

1995-06-01

PROTEGE-II is a suite of tools and a methodology for building knowledge-based systems and domain-specific knowledge-acquisition tools. In this paper, we show how PROTEGE-II can be applied to the task of providing protocol-based decision support in the domain of treating HIV-infected patients. To apply PROTEGE-II, (1) we construct a decomposable problem-solving method called episodic skeletal-plan refinement, (2) we build an application ontology that consists of the terms and relations in the domain, and of method-specific distinctions not already captured in the domain terms, and (3) we specify mapping relations that link terms from the application ontology to the domain-independent terms used in the problem-solving method. From the application ontology, we automatically generate a domain-specific knowledge-acquisition tool that is custom-tailored for the application. The knowledge-acquisition tool is used for the creation and maintenance of domain knowledge used by the problem-solving method. The general goal of the PROTEGE-II approach is to produce systems and components that are reusable and easily maintained. This is the rationale for constructing ontologies and problem-solving methods that can be composed from a set of smaller-grained methods and mechanisms. This is also why we tightly couple the knowledge-acquisition tools to the application ontology that specifies the domain terms used in the problem-solving systems. Although our evaluation is still preliminary, for the application task of providing protocol-based decision support, we show that these goals of reusability and easy maintenance can be achieved. We discuss design decisions and the tradeoffs that have to be made in the development of the system.

Software-engineering challenges of building and deploying reusable problem solvers.

PubMed

O'Connor, Martin J; Nyulas, Csongor; Tu, Samson; Buckeridge, David L; Okhmatovskaia, Anna; Musen, Mark A

2009-11-01

Problem solving methods (PSMs) are software components that represent and encode reusable algorithms. They can be combined with representations of domain knowledge to produce intelligent application systems. A goal of research on PSMs is to provide principled methods and tools for composing and reusing algorithms in knowledge-based systems. The ultimate objective is to produce libraries of methods that can be easily adapted for use in these systems. Despite the intuitive appeal of PSMs as conceptual building blocks, in practice, these goals are largely unmet. There are no widely available tools for building applications using PSMs and no public libraries of PSMs available for reuse. This paper analyzes some of the reasons for the lack of widespread adoptions of PSM techniques and illustrate our analysis by describing our experiences developing a complex, high-throughput software system based on PSM principles. We conclude that many fundamental principles in PSM research are useful for building knowledge-based systems. In particular, the task-method decomposition process, which provides a means for structuring knowledge-based tasks, is a powerful abstraction for building systems of analytic methods. However, despite the power of PSMs in the conceptual modeling of knowledge-based systems, software engineering challenges have been seriously underestimated. The complexity of integrating control knowledge modeled by developers using PSMs with the domain knowledge that they model using ontologies creates a barrier to widespread use of PSM-based systems. Nevertheless, the surge of recent interest in ontologies has led to the production of comprehensive domain ontologies and of robust ontology-authoring tools. These developments present new opportunities to leverage the PSM approach.

Software-engineering challenges of building and deploying reusable problem solvers

PubMed Central

O’CONNOR, MARTIN J.; NYULAS, CSONGOR; TU, SAMSON; BUCKERIDGE, DAVID L.; OKHMATOVSKAIA, ANNA; MUSEN, MARK A.

2012-01-01

Problem solving methods (PSMs) are software components that represent and encode reusable algorithms. They can be combined with representations of domain knowledge to produce intelligent application systems. A goal of research on PSMs is to provide principled methods and tools for composing and reusing algorithms in knowledge-based systems. The ultimate objective is to produce libraries of methods that can be easily adapted for use in these systems. Despite the intuitive appeal of PSMs as conceptual building blocks, in practice, these goals are largely unmet. There are no widely available tools for building applications using PSMs and no public libraries of PSMs available for reuse. This paper analyzes some of the reasons for the lack of widespread adoptions of PSM techniques and illustrate our analysis by describing our experiences developing a complex, high-throughput software system based on PSM principles. We conclude that many fundamental principles in PSM research are useful for building knowledge-based systems. In particular, the task–method decomposition process, which provides a means for structuring knowledge-based tasks, is a powerful abstraction for building systems of analytic methods. However, despite the power of PSMs in the conceptual modeling of knowledge-based systems, software engineering challenges have been seriously underestimated. The complexity of integrating control knowledge modeled by developers using PSMs with the domain knowledge that they model using ontologies creates a barrier to widespread use of PSM-based systems. Nevertheless, the surge of recent interest in ontologies has led to the production of comprehensive domain ontologies and of robust ontology-authoring tools. These developments present new opportunities to leverage the PSM approach. PMID:23565031

Beacon- and Schema-Based Method for Recognizing Algorithms from Students' Source Code

ERIC Educational Resources Information Center

Taherkhani, Ahmad; Malmi, Lauri

2013-01-01

In this paper, we present a method for recognizing algorithms from students programming submissions coded in Java. The method is based on the concept of "programming schemas" and "beacons". Schemas are high-level programming knowledge with detailed knowledge abstracted out, and beacons are statements that imply specific…

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.

Web-Based Instruction on Preservice Teachers' Knowledge of Fraction Operations

ERIC Educational Resources Information Center

Lin, Cheng-Yao

2010-01-01

This study determines whether web-based instruction (WBI) represents an improved method for helping preservice teachers learn procedural and conceptual knowledge of fractions.. The purpose was to compare the effectiveness of web-based instruction (WBI) with the traditional lecture in mathematics content and methods for the elementary school…

Knowledge acquisition for temporal abstraction.

PubMed

Stein, A; Musen, M A; Shahar, Y

1996-01-01

Temporal abstraction is the task of detecting relevant patterns in data over time. The knowledge-based temporal-abstraction method uses knowledge about a clinical domain's contexts, external events, and parameters to create meaningful interval-based abstractions from raw time-stamped clinical data. In this paper, we describe the acquisition and maintenance of domain-specific temporal-abstraction knowledge. Using the PROTEGE-II framework, we have designed a graphical tool for acquiring temporal knowledge directly from expert physicians, maintaining the knowledge in a sharable form, and converting the knowledge into a suitable format for use by an appropriate problem-solving method. In initial tests, the tool offered significant gains in our ability to rapidly acquire temporal knowledge and to use that knowledge to perform automated temporal reasoning.

Computer game-based and traditional learning method: a comparison regarding students’ knowledge retention

PubMed Central

2013-01-01

Background Educational computer games are examples of computer-assisted learning objects, representing an educational strategy of growing interest. Given the changes in the digital world over the last decades, students of the current generation expect technology to be used in advancing their learning requiring a need to change traditional passive learning methodologies to an active multisensory experimental learning methodology. The objective of this study was to compare a computer game-based learning method with a traditional learning method, regarding learning gains and knowledge retention, as means of teaching head and neck Anatomy and Physiology to Speech-Language and Hearing pathology undergraduate students. Methods Students were randomized to participate to one of the learning methods and the data analyst was blinded to which method of learning the students had received. Students’ prior knowledge (i.e. before undergoing the learning method), short-term knowledge retention and long-term knowledge retention (i.e. six months after undergoing the learning method) were assessed with a multiple choice questionnaire. Students’ performance was compared considering the three moments of assessment for both for the mean total score and for separated mean scores for Anatomy questions and for Physiology questions. Results Students that received the game-based method performed better in the pos-test assessment only when considering the Anatomy questions section. Students that received the traditional lecture performed better in both post-test and long-term post-test when considering the Anatomy and Physiology questions. Conclusions The game-based learning method is comparable to the traditional learning method in general and in short-term gains, while the traditional lecture still seems to be more effective to improve students’ short and long-term knowledge retention. PMID:23442203

Comparison of Knowledge and Attitudes Using Computer-Based and Face-to-Face Personal Hygiene Training Methods in Food Processing Facilities

ERIC Educational Resources Information Center

Fenton, Ginger D.; LaBorde, Luke F.; Radhakrishna, Rama B.; Brown, J. Lynne; Cutter, Catherine N.

2006-01-01

Computer-based training is increasingly favored by food companies for training workers due to convenience, self-pacing ability, and ease of use. The objectives of this study were to determine if personal hygiene training, offered through a computer-based method, is as effective as a face-to-face method in knowledge acquisition and improved…

Knowledge-based reconstruction for measurement of right ventricular volumes on cardiovascular magnetic resonance images in a mixed population.

PubMed

Pieterman, Elise D; Budde, Ricardo P J; Robbers-Visser, Daniëlle; van Domburg, Ron T; Helbing, Willem A

2017-09-01

Follow-up of right ventricular performance is important for patients with congenital heart disease. Cardiac magnetic resonance imaging is optimal for this purpose. However, observer-dependency of manual analysis of right ventricular volumes limit its use. Knowledge-based reconstruction is a new semiautomatic analysis tool that uses a database including knowledge of right ventricular shape in various congenital heart diseases. We evaluated whether knowledge-based reconstruction is a good alternative for conventional analysis. To assess the inter- and intra-observer variability and agreement of knowledge-based versus conventional analysis of magnetic resonance right ventricular volumes, analysis was done by two observers in a mixed group of 22 patients with congenital heart disease affecting right ventricular loading conditions (dextro-transposition of the great arteries and right ventricle to pulmonary artery conduit) and a group of 17 healthy children. We used Bland-Altman analysis and coefficient of variation. Comparison between the conventional method and the knowledge-based method showed a systematically higher volume for the latter group. We found an overestimation for end-diastolic volume (bias -40 ± 24 mL, r = .956), end-systolic volume (bias -34 ± 24 mL, r = .943), stroke volume (bias -6 ± 17 mL, r = .735) and an underestimation of ejection fraction (bias 7 ± 7%, r = .671) by knowledge-based reconstruction. The intra-observer variability of knowledge-based reconstruction varied with a coefficient of variation of 9% for end-diastolic volume and 22% for stroke volume. The same trend was noted for inter-observer variability. A systematic difference (overestimation) was noted for right ventricular size as assessed with knowledge-based reconstruction compared with conventional methods for analysis. Observer variability for the new method was comparable to what has been reported for the right ventricle in children and congenital heart disease with conventional analysis. © 2017 Wiley Periodicals, Inc.

Predicting links based on knowledge dissemination in complex network

NASA Astrophysics Data System (ADS)

Zhou, Wen; Jia, Yifan

2017-04-01

Link prediction is the task of mining the missing links in networks or predicting the next vertex pair to be connected by a link. A lot of link prediction methods were inspired by evolutionary processes of networks. In this paper, a new mechanism for the formation of complex networks called knowledge dissemination (KD) is proposed with the assumption of knowledge disseminating through the paths of a network. Accordingly, a new link prediction method-knowledge dissemination based link prediction (KDLP)-is proposed to test KD. KDLP characterizes vertex similarity based on knowledge quantity (KQ) which measures the importance of a vertex through H-index. Extensive numerical simulations on six real-world networks demonstrate that KDLP is a strong link prediction method which performs at a higher prediction accuracy than four well-known similarity measures including common neighbors, local path index, average commute time and matrix forest index. Furthermore, based on the common conclusion that an excellent link prediction method reveals a good evolving mechanism, the experiment results suggest that KD is a considerable network evolving mechanism for the formation of complex networks.

Knowledge modeling of coal mining equipments based on ontology

NASA Astrophysics Data System (ADS)

Zhang, Baolong; Wang, Xiangqian; Li, Huizong; Jiang, Miaomiao

2017-06-01

The problems of information redundancy and sharing are universe in coal mining equipment management. In order to improve the using efficiency of knowledge of coal mining equipments, this paper proposed a new method of knowledge modeling based on ontology. On the basis of analyzing the structures and internal relations of coal mining equipment knowledge, taking OWL as ontology construct language, the ontology model of coal mining equipment knowledge is built with the help of Protégé 4.3 software tools. The knowledge description method will lay the foundation for the high effective knowledge management and sharing, which is very significant for improving the production management level of coal mining enterprises.

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…

Developing and Assessing Teachers' Knowledge of Game-Based Learning

ERIC Educational Resources Information Center

Shah, Mamta; Foster, Aroutis

2015-01-01

Research focusing on the development and assessment of teacher knowledge in game-based learning is in its infancy. A mixed-methods study was undertaken to educate pre-service teachers in game-based learning using the Game Network Analysis (GaNA) framework. Fourteen pre-service teachers completed a methods course, which prepared them in game…

A flower image retrieval method based on ROI feature.

PubMed

Hong, An-Xiang; Chen, Gang; Li, Jun-Li; Chi, Zhe-Ru; Zhang, Dan

2004-07-01

Flower image retrieval is a very important step for computer-aided plant species recognition. In this paper, we propose an efficient segmentation method based on color clustering and domain knowledge to extract flower regions from flower images. For flower retrieval, we use the color histogram of a flower region to characterize the color features of flower and two shape-based features sets, Centroid-Contour Distance (CCD) and Angle Code Histogram (ACH), to characterize the shape features of a flower contour. Experimental results showed that our flower region extraction method based on color clustering and domain knowledge can produce accurate flower regions. Flower retrieval results on a database of 885 flower images collected from 14 plant species showed that our Region-of-Interest (ROI) based retrieval approach using both color and shape features can perform better than a method based on the global color histogram proposed by Swain and Ballard (1991) and a method based on domain knowledge-driven segmentation and color names proposed by Das et al.(1999).

The research on construction and application of machining process knowledge base

NASA Astrophysics Data System (ADS)

Zhao, Tan; Qiao, Lihong; Qie, Yifan; Guo, Kai

2018-03-01

In order to realize the application of knowledge in machining process design, from the perspective of knowledge in the application of computer aided process planning(CAPP), a hierarchical structure of knowledge classification is established according to the characteristics of mechanical engineering field. The expression of machining process knowledge is structured by means of production rules and the object-oriented methods. Three kinds of knowledge base models are constructed according to the representation of machining process knowledge. In this paper, the definition and classification of machining process knowledge, knowledge model, and the application flow of the process design based on the knowledge base are given, and the main steps of the design decision of the machine tool are carried out as an application by using the knowledge base.

Rethinking knowledge and pedagogy in dental education.

PubMed

Whipp, J L; Ferguson, D J; Wells, L M; Iacopino, A M

2000-12-01

Dentistry as a profession has often been considered both art and science. Traditional dental education has attempted to address both; however, in many places only the science of dentistry is emphasized. The move toward competency-based curricula in dental education requires an expansion of what constitutes meaningful knowledge in the curriculum and what pedagogies best support that curriculum. The scientific and technical knowledge considered foundational to clinical practice is not sufficient to teach competencies associated with the art of dentistry. Habermas, a social scientist, offers a way of looking beyond technical knowledge to consider two other forms of knowledge: practical and emancipatory. Pedagogy that supports development of practical and emancipatory knowledge includes problem-based learning and case methods, heuristics, reflective practica, journals, storytelling, and performance-based assessment methods. These important teaching strategies are being integrated into various dental curricula including a new competency-based dental curriculum at Marquette University's School of Dentistry. It will be critical for dental educators to continue developing these methods to provide efficient and effective education for future practitioners in both the art and science of dentistry.

Computer game-based and traditional learning method: a comparison regarding students' knowledge retention.

PubMed

Rondon, Silmara; Sassi, Fernanda Chiarion; Furquim de Andrade, Claudia Regina

2013-02-25

Educational computer games are examples of computer-assisted learning objects, representing an educational strategy of growing interest. Given the changes in the digital world over the last decades, students of the current generation expect technology to be used in advancing their learning requiring a need to change traditional passive learning methodologies to an active multisensory experimental learning methodology. The objective of this study was to compare a computer game-based learning method with a traditional learning method, regarding learning gains and knowledge retention, as means of teaching head and neck Anatomy and Physiology to Speech-Language and Hearing pathology undergraduate students. Students were randomized to participate to one of the learning methods and the data analyst was blinded to which method of learning the students had received. Students' prior knowledge (i.e. before undergoing the learning method), short-term knowledge retention and long-term knowledge retention (i.e. six months after undergoing the learning method) were assessed with a multiple choice questionnaire. Students' performance was compared considering the three moments of assessment for both for the mean total score and for separated mean scores for Anatomy questions and for Physiology questions. Students that received the game-based method performed better in the pos-test assessment only when considering the Anatomy questions section. Students that received the traditional lecture performed better in both post-test and long-term post-test when considering the Anatomy and Physiology questions. The game-based learning method is comparable to the traditional learning method in general and in short-term gains, while the traditional lecture still seems to be more effective to improve students' short and long-term knowledge retention.

The Relationship between Agriculture Knowledge Bases for Teaching and Sources of Knowledge

ERIC Educational Resources Information Center

Rice, Amber H.; Kitchel, Tracy

2015-01-01

The purpose of this study was to describe the agriculture knowledge bases for teaching of agriculture teachers and to see if a relationship existed between years of teaching experience, sources of knowledge, and development of pedagogical content knowledge (PCK), using quantitative methods. A model of PCK from mathematics was utilized as a…

Enhancing Student Learning in Knowledge-Based Courses: Integrating Team-Based Learning in Mass Communication Theory Classes

ERIC Educational Resources Information Center

Han, Gang; Newell, Jay

2014-01-01

This study explores the adoption of the team-based learning (TBL) method in knowledge-based and theory-oriented journalism and mass communication (J&MC) courses. It first reviews the origin and concept of TBL, the relevant theories, and then introduces the TBL method and implementation, including procedures and assessments, employed in an…

Reconstruction of metabolic pathways by combining probabilistic graphical model-based and knowledge-based methods

PubMed Central

2014-01-01

Automatic reconstruction of metabolic pathways for an organism from genomics and transcriptomics data has been a challenging and important problem in bioinformatics. Traditionally, known reference pathways can be mapped into an organism-specific ones based on its genome annotation and protein homology. However, this simple knowledge-based mapping method might produce incomplete pathways and generally cannot predict unknown new relations and reactions. In contrast, ab initio metabolic network construction methods can predict novel reactions and interactions, but its accuracy tends to be low leading to a lot of false positives. Here we combine existing pathway knowledge and a new ab initio Bayesian probabilistic graphical model together in a novel fashion to improve automatic reconstruction of metabolic networks. Specifically, we built a knowledge database containing known, individual gene / protein interactions and metabolic reactions extracted from existing reference pathways. Known reactions and interactions were then used as constraints for Bayesian network learning methods to predict metabolic pathways. Using individual reactions and interactions extracted from different pathways of many organisms to guide pathway construction is new and improves both the coverage and accuracy of metabolic pathway construction. We applied this probabilistic knowledge-based approach to construct the metabolic networks from yeast gene expression data and compared its results with 62 known metabolic networks in the KEGG database. The experiment showed that the method improved the coverage of metabolic network construction over the traditional reference pathway mapping method and was more accurate than pure ab initio methods. PMID:25374614

A collaborative filtering-based approach to biomedical knowledge discovery.

PubMed

Lever, Jake; Gakkhar, Sitanshu; Gottlieb, Michael; Rashnavadi, Tahereh; Lin, Santina; Siu, Celia; Smith, Maia; Jones, Martin R; Krzywinski, Martin; Jones, Steven J M; Wren, Jonathan

2018-02-15

The increase in publication rates makes it challenging for an individual researcher to stay abreast of all relevant research in order to find novel research hypotheses. Literature-based discovery methods make use of knowledge graphs built using text mining and can infer future associations between biomedical concepts that will likely occur in new publications. These predictions are a valuable resource for researchers to explore a research topic. Current methods for prediction are based on the local structure of the knowledge graph. A method that uses global knowledge from across the knowledge graph needs to be developed in order to make knowledge discovery a frequently used tool by researchers. We propose an approach based on the singular value decomposition (SVD) that is able to combine data from across the knowledge graph through a reduced representation. Using cooccurrence data extracted from published literature, we show that SVD performs better than the leading methods for scoring discoveries. We also show the diminishing predictive power of knowledge discovery as we compare our predictions with real associations that appear further into the future. Finally, we examine the strengths and weaknesses of the SVD approach against another well-performing system using several predicted associations. All code and results files for this analysis can be accessed at https://github.com/jakelever/knowledgediscovery. sjones@bcgsc.ca. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Using Topdown Conceptual Analysis To Accelerate The Learning Of New Domains For Knowledge Engineers & Domain Experts

NASA Astrophysics Data System (ADS)

Xuan, Albert L.; Shinghal, Rajjan

1989-03-01

As the need for knowledge-based systems increases, an increasing number of domain experts are becoming interested in taking more active part in the building of knowledge-based systems. However, such a domain expert often must deal with a large number of unfamiliar terms concepts, facts, procedures and principles based on different approaches and schools of thought. He (for brevity, we shall use masculine pronouns for both genders) may need the help of a knowledge engineer (KE) in building the knowledge-based system but may encounter a number of problems. For instance, much of the early interaction between him and the knowl edge engineer may be spent in educating each other about their seperate kinds of expertise. Since the knowledge engineer will usually be ignorant of the knowledge domain while the domain expert (DE) will have little knowledge about knowledge-based systems, a great deal of time will be wasted on these issues ad the DE and the KE train each other to the point where a fruitful interaction can occur. In some situations, it may not even be possible for the DE to find a suitable KE to work with because he has no time to train the latter in his domain. This will engender the need for the DE to be more knowledgeable about knowledge-based systems and for the KE to find methods and techniques which will allow them to learn new domains as fast as they can. In any event, it is likely that the process of building knowledge-based systems will be smooth, er and more efficient if the domain expert is knowledgeable about the methods and techniques of knowledge-based systems building.

A Comparison of Functional Models for Use in the Function-Failure Design Method

NASA Technical Reports Server (NTRS)

Stock, Michael E.; Stone, Robert B.; Tumer, Irem Y.

2006-01-01

When failure analysis and prevention, guided by historical design knowledge, are coupled with product design at its conception, shorter design cycles are possible. By decreasing the design time of a product in this manner, design costs are reduced and the product will better suit the customer s needs. Prior work indicates that similar failure modes occur with products (or components) with similar functionality. To capitalize on this finding, a knowledge base of historical failure information linked to functionality is assembled for use by designers. One possible use for this knowledge base is within the Elemental Function-Failure Design Method (EFDM). This design methodology and failure analysis tool begins at conceptual design and keeps the designer cognizant of failures that are likely to occur based on the product s functionality. The EFDM offers potential improvement over current failure analysis methods, such as FMEA, FMECA, and Fault Tree Analysis, because it can be implemented hand in hand with other conceptual design steps and carried throughout a product s design cycle. These other failure analysis methods can only truly be effective after a physical design has been completed. The EFDM however is only as good as the knowledge base that it draws from, and therefore it is of utmost importance to develop a knowledge base that will be suitable for use across a wide spectrum of products. One fundamental question that arises in using the EFDM is: At what level of detail should functional descriptions of components be encoded? This paper explores two approaches to populating a knowledge base with actual failure occurrence information from Bell 206 helicopters. Functional models expressed at various levels of detail are investigated to determine the necessary detail for an applicable knowledge base that can be used by designers in both new designs as well as redesigns. High level and more detailed functional descriptions are derived for each failed component based on NTSB accident reports. To best record this data, standardized functional and failure mode vocabularies are used. Two separate function-failure knowledge bases are then created aid compared. Results indicate that encoding failure data using more detailed functional models allows for a more robust knowledge base. Interestingly however, when applying the EFDM, high level descriptions continue to produce useful results when using the knowledge base generated from the detailed functional models.

Delivering spacecraft control centers with embedded knowledge-based systems: The methodology issue

NASA Technical Reports Server (NTRS)

Ayache, S.; Haziza, M.; Cayrac, D.

1994-01-01

Matra Marconi Space (MMS) occupies a leading place in Europe in the domain of satellite and space data processing systems. The maturity of the knowledge-based systems (KBS) technology, the theoretical and practical experience acquired in the development of prototype, pre-operational and operational applications, make it possible today to consider the wide operational deployment of KBS's in space applications. In this perspective, MMS has to prepare the introduction of the new methods and support tools that will form the basis of the development of such systems. This paper introduces elements of the MMS methodology initiatives in the domain and the main rationale that motivated the approach. These initiatives develop along two main axes: knowledge engineering methods and tools, and a hybrid method approach for coexisting knowledge-based and conventional developments.

A knowledge-driven approach to biomedical document conceptualization.

PubMed

Zheng, Hai-Tao; Borchert, Charles; Jiang, Yong

2010-06-01

Biomedical document conceptualization is the process of clustering biomedical documents based on ontology-represented domain knowledge. The result of this process is the representation of the biomedical documents by a set of key concepts and their relationships. Most of clustering methods cluster documents based on invariant domain knowledge. The objective of this work is to develop an effective method to cluster biomedical documents based on various user-specified ontologies, so that users can exploit the concept structures of documents more effectively. We develop a flexible framework to allow users to specify the knowledge bases, in the form of ontologies. Based on the user-specified ontologies, we develop a key concept induction algorithm, which uses latent semantic analysis to identify key concepts and cluster documents. A corpus-related ontology generation algorithm is developed to generate the concept structures of documents. Based on two biomedical datasets, we evaluate the proposed method and five other clustering algorithms. The clustering results of the proposed method outperform the five other algorithms, in terms of key concept identification. With respect to the first biomedical dataset, our method has the F-measure values 0.7294 and 0.5294 based on the MeSH ontology and gene ontology (GO), respectively. With respect to the second biomedical dataset, our method has the F-measure values 0.6751 and 0.6746 based on the MeSH ontology and GO, respectively. Both results outperforms the five other algorithms in terms of F-measure. Based on the MeSH ontology and GO, the generated corpus-related ontologies show informative conceptual structures. The proposed method enables users to specify the domain knowledge to exploit the conceptual structures of biomedical document collections. In addition, the proposed method is able to extract the key concepts and cluster the documents with a relatively high precision. Copyright 2010 Elsevier B.V. All rights reserved.

A Knowledge Navigation Method for the Domain of Customers' Services of Mobile Communication Corporations in China

NASA Astrophysics Data System (ADS)

Wu, Jiangning; Wang, Xiaohuan

Rapidly increasing amount of mobile phone users and types of services leads to a great accumulation of complaining information. How to use this information to enhance the quality of customers' services is a big issue at present. To handle this kind of problem, the paper presents an approach to construct a domain knowledge map for navigating the explicit and tacit knowledge in two ways: building the Topic Map-based explicit knowledge navigation model, which includes domain TM construction, a semantic topic expansion algorithm and VSM-based similarity calculation; building Social Network Analysis-based tacit knowledge navigation model, which includes a multi-relational expert navigation algorithm and the criterions to evaluate the performance of expert networks. In doing so, both the customer managers and operators in call centers can find the appropriate knowledge and experts quickly and exactly. The experimental results show that the above method is very powerful for knowledge navigation.

Is Student Knowledge of Anatomy Affected by a Problem-Based Learning Approach? A Review

ERIC Educational Resources Information Center

Williams, Jonathan M.

2014-01-01

A fundamental understanding of anatomy is critical for students on many health science courses. It has been suggested that a problem-based approach to learning anatomy may result in deficits in foundation knowledge. The aim of this review is to compare traditional didactic methods with problem-based learning methods for obtaining anatomy…

Local knowledge: Empirical Fact to Develop Community Based Disaster Risk Management Concept for Community Resilience at Mangkang Kulon Village, Semarang City

NASA Astrophysics Data System (ADS)

Kapiarsa, A. B.; Sariffuddin, S.

2018-02-01

Local knowledge in disaster management should not be neglected in developing community resilience. The circular relation between humans and their living habitat and community social relation have developed the local knowledge namely specialized knowledge, shared knowledge, and common knowledge. Its correlation with community-based disaster management has become an important discussion specially to answer can local knowledge underlie community-based disaster risk reduction concept development? To answer this question, this research used mix-method. Interview and crosstab method for 73 respondents with 90% trust rate were used to determine the correlation between local knowledge and community characteristics. This research found out that shared knowledge dominated community local knowledge (77%). While common knowledge and specialized knowledge were sequentially 8% and 15%. The high score of shared value (77%) indicated that local knowledge was occurred in household level and not yet indicated in community level. Shared knowledge was found in 3 phases of the resilient community in dealing with disaster, namely mitigation, emergency response, and recovery phase. This research, therefore, has opened a new scientific discussion on the self-help concept in community-help concept in CBDRM concept development in Indonesia.

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

NASA Technical Reports Server (NTRS)

Lambright, Jonathan Paul

1996-01-01

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

SemaTyP: a knowledge graph based literature mining method for drug discovery.

PubMed

Sang, Shengtian; Yang, Zhihao; Wang, Lei; Liu, Xiaoxia; Lin, Hongfei; Wang, Jian

2018-05-30

Drug discovery is the process through which potential new medicines are identified. High-throughput screening and computer-aided drug discovery/design are the two main drug discovery methods for now, which have successfully discovered a series of drugs. However, development of new drugs is still an extremely time-consuming and expensive process. Biomedical literature contains important clues for the identification of potential treatments. It could support experts in biomedicine on their way towards new discoveries. Here, we propose a biomedical knowledge graph-based drug discovery method called SemaTyP, which discovers candidate drugs for diseases by mining published biomedical literature. We first construct a biomedical knowledge graph with the relations extracted from biomedical abstracts, then a logistic regression model is trained by learning the semantic types of paths of known drug therapies' existing in the biomedical knowledge graph, finally the learned model is used to discover drug therapies for new diseases. The experimental results show that our method could not only effectively discover new drug therapies for new diseases, but also could provide the potential mechanism of action of the candidate drugs. In this paper we propose a novel knowledge graph based literature mining method for drug discovery. It could be a supplementary method for current drug discovery methods.

Research on Knowledge-Based Optimization Method of Indoor Location Based on Low Energy Bluetooth

NASA Astrophysics Data System (ADS)

Li, C.; Li, G.; Deng, Y.; Wang, T.; Kang, Z.

2017-09-01

With the rapid development of LBS (Location-based Service), the demand for commercialization of indoor location has been increasing, but its technology is not perfect. Currently, the accuracy of indoor location, the complexity of the algorithm, and the cost of positioning are hard to be simultaneously considered and it is still restricting the determination and application of mainstream positioning technology. Therefore, this paper proposes a method of knowledge-based optimization of indoor location based on low energy Bluetooth. The main steps include: 1) The establishment and application of a priori and posterior knowledge base. 2) Primary selection of signal source. 3) Elimination of positioning gross error. 4) Accumulation of positioning knowledge. The experimental results show that the proposed algorithm can eliminate the signal source of outliers and improve the accuracy of single point positioning in the simulation data. The proposed scheme is a dynamic knowledge accumulation rather than a single positioning process. The scheme adopts cheap equipment and provides a new idea for the theory and method of indoor positioning. Moreover, the performance of the high accuracy positioning results in the simulation data shows that the scheme has a certain application value in the commercial promotion.

Construction of dynamic stochastic simulation models using knowledge-based techniques

NASA Technical Reports Server (NTRS)

Williams, M. Douglas; Shiva, Sajjan G.

1990-01-01

Over the past three decades, computer-based simulation models have proven themselves to be cost-effective alternatives to the more structured deterministic methods of systems analysis. During this time, many techniques, tools and languages for constructing computer-based simulation models have been developed. More recently, advances in knowledge-based system technology have led many researchers to note the similarities between knowledge-based programming and simulation technologies and to investigate the potential application of knowledge-based programming techniques to simulation modeling. The integration of conventional simulation techniques with knowledge-based programming techniques is discussed to provide a development environment for constructing knowledge-based simulation models. A comparison of the techniques used in the construction of dynamic stochastic simulation models and those used in the construction of knowledge-based systems provides the requirements for the environment. This leads to the design and implementation of a knowledge-based simulation development environment. These techniques were used in the construction of several knowledge-based simulation models including the Advanced Launch System Model (ALSYM).

Examining Information Problem-Solving, Knowledge, and Application Gains within Two Instructional Methods: Problem-Based and Computer-Mediated Participatory Simulation

ERIC Educational Resources Information Center

Newell, Terrance S.

2008-01-01

This study compared the effectiveness of two instructional methods--problem-based instruction within a face-to-face context and computer-mediated participatory simulation--in increasing students' content knowledge and application gains in the area of information problem-solving. The instructional methods were implemented over a four-week period. A…

Utilizing knowledge base of amino acids structural neighborhoods to predict protein-protein interaction sites.

PubMed

Jelínek, Jan; Škoda, Petr; Hoksza, David

2017-12-06

Protein-protein interactions (PPI) play a key role in an investigation of various biochemical processes, and their identification is thus of great importance. Although computational prediction of which amino acids take part in a PPI has been an active field of research for some time, the quality of in-silico methods is still far from perfect. We have developed a novel prediction method called INSPiRE which benefits from a knowledge base built from data available in Protein Data Bank. All proteins involved in PPIs were converted into labeled graphs with nodes corresponding to amino acids and edges to pairs of neighboring amino acids. A structural neighborhood of each node was then encoded into a bit string and stored in the knowledge base. When predicting PPIs, INSPiRE labels amino acids of unknown proteins as interface or non-interface based on how often their structural neighborhood appears as interface or non-interface in the knowledge base. We evaluated INSPiRE's behavior with respect to different types and sizes of the structural neighborhood. Furthermore, we examined the suitability of several different features for labeling the nodes. Our evaluations showed that INSPiRE clearly outperforms existing methods with respect to Matthews correlation coefficient. In this paper we introduce a new knowledge-based method for identification of protein-protein interaction sites called INSPiRE. Its knowledge base utilizes structural patterns of known interaction sites in the Protein Data Bank which are then used for PPI prediction. Extensive experiments on several well-established datasets show that INSPiRE significantly surpasses existing PPI approaches.

On construction method of shipborne and airborne radar intelligence and related equipment knowledge graph

NASA Astrophysics Data System (ADS)

Hao, Ruizhe; Huang, Jian

2017-08-01

Knowledge graph construction in military intelligence domain is sprouting but technically immature. This paper presents a method to construct the heterogeneous knowledge graph in the field of shipborne and airborne radar and equipment. Based on the expert knowledge and the up-to-date Internet open source information, we construct the knowledge graph of radar characteristic information and the equipment respectively, and establish relationships between two graphs, providing the pipeline and method for the intelligence organization and management in the context of the crowding battlefields big data.

Selection of Construction Methods: A Knowledge-Based Approach

PubMed Central

Skibniewski, Miroslaw

2013-01-01

The appropriate selection of construction methods to be used during the execution of a construction project is a major determinant of high productivity, but sometimes this selection process is performed without the care and the systematic approach that it deserves, bringing negative consequences. This paper proposes a knowledge management approach that will enable the intelligent use of corporate experience and information and help to improve the selection of construction methods for a project. Then a knowledge-based system to support this decision-making process is proposed and described. To define and design the system, semistructured interviews were conducted within three construction companies with the purpose of studying the way that the method' selection process is carried out in practice and the knowledge associated with it. A prototype of a Construction Methods Knowledge System (CMKS) was developed and then validated with construction industry professionals. As a conclusion, the CMKS was perceived as a valuable tool for construction methods' selection, by helping companies to generate a corporate memory on this issue, reducing the reliance on individual knowledge and also the subjectivity of the decision-making process. The described benefits as provided by the system favor a better performance of construction projects. PMID:24453925

Expert Knowledge-Based Automatic Sleep Stage Determination by Multi-Valued Decision Making Method

NASA Astrophysics Data System (ADS)

Wang, Bei; Sugi, Takenao; Kawana, Fusae; Wang, Xingyu; Nakamura, Masatoshi

In this study, an expert knowledge-based automatic sleep stage determination system working on a multi-valued decision making method is developed. Visual inspection by a qualified clinician is adopted to obtain the expert knowledge database. The expert knowledge database consists of probability density functions of parameters for various sleep stages. Sleep stages are determined automatically according to the conditional probability. Totally, four subjects were participated. The automatic sleep stage determination results showed close agreements with the visual inspection on sleep stages of awake, REM (rapid eye movement), light sleep and deep sleep. The constructed expert knowledge database reflects the distributions of characteristic parameters which can be adaptive to variable sleep data in hospitals. The developed automatic determination technique based on expert knowledge of visual inspection can be an assistant tool enabling further inspection of sleep disorder cases for clinical practice.

Method and system for knowledge discovery using non-linear statistical analysis and a 1st and 2nd tier computer program

DOEpatents

Hively, Lee M [Philadelphia, TN

2011-07-12

The invention relates to a method and apparatus for simultaneously processing different sources of test data into informational data and then processing different categories of informational data into knowledge-based data. The knowledge-based data can then be communicated between nodes in a system of multiple computers according to rules for a type of complex, hierarchical computer system modeled on a human brain.

Current Standardization and Cooperative Efforts Related to Industrial Information Infrastructures.

DTIC Science & Technology

1993-05-01

Data Management Systems: Components used to store, manage, and retrieve data. Data management includes knowledge bases, database management...Application Development Tools and Methods X/Open and POSIX APIs Integrated Design Support System (IDS) Knowledge -Based Systems (KBS) Application...IDEFlx) Yourdon Jackson System Design (JSD) Knowledge -Based Systems (KBSs) Structured Systems Development (SSD) Semantic Unification Meta-Model

What Do We Know and How Well Do We Know It? Identifying Practice-Based Insights in Education

ERIC Educational Resources Information Center

Miller, Barbara; Pasley, Joan

2012-01-01

Knowledge derived from practice forms a significant portion of the knowledge base in the education field, yet is not accessible using existing empirical research methods. This paper describes a systematic, rigorous, grounded approach to collecting and analysing practice-based knowledge using the authors' research in teacher leadership as an…

DataHub knowledge based assistance for science visualization and analysis using large distributed databases

NASA Technical Reports Server (NTRS)

Handley, Thomas H., Jr.; Collins, Donald J.; Doyle, Richard J.; Jacobson, Allan S.

1991-01-01

Viewgraphs on DataHub knowledge based assistance for science visualization and analysis using large distributed databases. Topics covered include: DataHub functional architecture; data representation; logical access methods; preliminary software architecture; LinkWinds; data knowledge issues; expert systems; and data management.

Eliciting and Representing High-Level Knowledge Requirements to Discover Ecological Knowledge in Flower-Visiting Data

PubMed Central

2016-01-01

Observations of individual organisms (data) can be combined with expert ecological knowledge of species, especially causal knowledge, to model and extract from flower–visiting data useful information about behavioral interactions between insect and plant organisms, such as nectar foraging and pollen transfer. We describe and evaluate a method to elicit and represent such expert causal knowledge of behavioral ecology, and discuss the potential for wider application of this method to the design of knowledge-based systems for knowledge discovery in biodiversity and ecosystem informatics. PMID:27851814

A semantic-based method for extracting concept definitions from scientific publications: evaluation in the autism phenotype domain.

PubMed

Hassanpour, Saeed; O'Connor, Martin J; Das, Amar K

2013-08-12

A variety of informatics approaches have been developed that use information retrieval, NLP and text-mining techniques to identify biomedical concepts and relations within scientific publications or their sentences. These approaches have not typically addressed the challenge of extracting more complex knowledge such as biomedical definitions. In our efforts to facilitate knowledge acquisition of rule-based definitions of autism phenotypes, we have developed a novel semantic-based text-mining approach that can automatically identify such definitions within text. Using an existing knowledge base of 156 autism phenotype definitions and an annotated corpus of 26 source articles containing such definitions, we evaluated and compared the average rank of correctly identified rule definition or corresponding rule template using both our semantic-based approach and a standard term-based approach. We examined three separate scenarios: (1) the snippet of text contained a definition already in the knowledge base; (2) the snippet contained an alternative definition for a concept in the knowledge base; and (3) the snippet contained a definition not in the knowledge base. Our semantic-based approach had a higher average rank than the term-based approach for each of the three scenarios (scenario 1: 3.8 vs. 5.0; scenario 2: 2.8 vs. 4.9; and scenario 3: 4.5 vs. 6.2), with each comparison significant at the p-value of 0.05 using the Wilcoxon signed-rank test. Our work shows that leveraging existing domain knowledge in the information extraction of biomedical definitions significantly improves the correct identification of such knowledge within sentences. Our method can thus help researchers rapidly acquire knowledge about biomedical definitions that are specified and evolving within an ever-growing corpus of scientific publications.

Ontology-based structured cosine similarity in document summarization: with applications to mobile audio-based knowledge management.

PubMed

Yuan, Soe-Tsyr; Sun, Jerry

2005-10-01

Development of algorithms for automated text categorization in massive text document sets is an important research area of data mining and knowledge discovery. Most of the text-clustering methods were grounded in the term-based measurement of distance or similarity, ignoring the structure of the documents. In this paper, we present a novel method named structured cosine similarity (SCS) that furnishes document clustering with a new way of modeling on document summarization, considering the structure of the documents so as to improve the performance of document clustering in terms of quality, stability, and efficiency. This study was motivated by the problem of clustering speech documents (of no rich document features) attained from the wireless experience oral sharing conducted by mobile workforce of enterprises, fulfilling audio-based knowledge management. In other words, this problem aims to facilitate knowledge acquisition and sharing by speech. The evaluations also show fairly promising results on our method of structured cosine similarity.

Using ontologies to model human navigation behavior in information networks: A study based on Wikipedia.

PubMed

Lamprecht, Daniel; Strohmaier, Markus; Helic, Denis; Nyulas, Csongor; Tudorache, Tania; Noy, Natalya F; Musen, Mark A

The need to examine the behavior of different user groups is a fundamental requirement when building information systems. In this paper, we present Ontology-based Decentralized Search (OBDS), a novel method to model the navigation behavior of users equipped with different types of background knowledge. Ontology-based Decentralized Search combines decentralized search, an established method for navigation in social networks, and ontologies to model navigation behavior in information networks. The method uses ontologies as an explicit representation of background knowledge to inform the navigation process and guide it towards navigation targets. By using different ontologies, users equipped with different types of background knowledge can be represented. We demonstrate our method using four biomedical ontologies and their associated Wikipedia articles. We compare our simulation results with base line approaches and with results obtained from a user study. We find that our method produces click paths that have properties similar to those originating from human navigators. The results suggest that our method can be used to model human navigation behavior in systems that are based on information networks, such as Wikipedia. This paper makes the following contributions: (i) To the best of our knowledge, this is the first work to demonstrate the utility of ontologies in modeling human navigation and (ii) it yields new insights and understanding about the mechanisms of human navigation in information networks.

Using ontologies to model human navigation behavior in information networks: A study based on Wikipedia

PubMed Central

Lamprecht, Daniel; Strohmaier, Markus; Helic, Denis; Nyulas, Csongor; Tudorache, Tania; Noy, Natalya F.; Musen, Mark A.

2015-01-01

The need to examine the behavior of different user groups is a fundamental requirement when building information systems. In this paper, we present Ontology-based Decentralized Search (OBDS), a novel method to model the navigation behavior of users equipped with different types of background knowledge. Ontology-based Decentralized Search combines decentralized search, an established method for navigation in social networks, and ontologies to model navigation behavior in information networks. The method uses ontologies as an explicit representation of background knowledge to inform the navigation process and guide it towards navigation targets. By using different ontologies, users equipped with different types of background knowledge can be represented. We demonstrate our method using four biomedical ontologies and their associated Wikipedia articles. We compare our simulation results with base line approaches and with results obtained from a user study. We find that our method produces click paths that have properties similar to those originating from human navigators. The results suggest that our method can be used to model human navigation behavior in systems that are based on information networks, such as Wikipedia. This paper makes the following contributions: (i) To the best of our knowledge, this is the first work to demonstrate the utility of ontologies in modeling human navigation and (ii) it yields new insights and understanding about the mechanisms of human navigation in information networks. PMID:26568745

Instructional Design as Knowledge Management: A Knowledge-in-Practice Approach to Choosing Instructional Methods

ERIC Educational Resources Information Center

McIver, Derrick; Fitzsimmons, Stacey; Flanagan, David

2016-01-01

Decisions about instructional methods are becoming more complex, with options ranging from problem sets to experiential service-learning projects. However, instructors not trained in instructional design may make these important decisions based on convenience, comfort, or trends. Instead, this article draws on the knowledge management literature…

Comparing the effect of group-based and compact disk-based training on midwives’ knowledge and attitude toward domestic violence in women of reproductive age

PubMed Central

Vakily, Masoomeh; Noroozi, Mahnaz; Yamani, Nikoo

2017-01-01

BACKGROUND: Training the health personnel about domestic violence would cause them to investigate and evaluate this issue more than before. Considering the new educational approaches for transferring knowledge, the goal of this research was to compare the effect of group-based and compact disk (CD)-based training on midwives’ knowledge and attitude toward domestic violence. METHODS: In this clinical experiment, seventy midwives working at health centers and hospitals of Isfahan were randomly allocated into two classes of group-based and CD-based trainings and were trained in the fields of recognition, prevention, and management of domestic violence. Data were collected by questionnaires which were completed by the midwives for evaluation of their knowledge and attitude. RESULTS: The mean score of midwives’ knowledge and attitude toward domestic violence had a meaningful increase after the training (16.1, 46.9) compared to the score of before the training (12.1, 39.1) in both of the classes (group-based training: 17.7, 45.4) (CD-based training: 11.7, 38.6). No meaningful difference was observed between the two groups regarding midwives’ attitude toward domestic violence after the intervention; however, regarding their knowledge level, the difference was statistically meaningful (P = 0.001), and this knowledge increase was more in the CD-based training group. CONCLUSIONS: In spite of the effectiveness of both of the training methods in promoting midwives’ knowledge and attitude about domestic violence, training with CD was more effective in increasing their knowledge; as a result, considering the benefits of CD-based training such as cost-effectiveness and possibility of use at any time, it is advised to be used in training programs for the health personnel. PMID:28852660

The effect of the PROSPER partnership model on cultivating local stakeholder knowledge of evidence-based programs: a five-year longitudinal study of 28 communities.

PubMed

Crowley, D Max; Greenberg, Mark T; Feinberg, Mark E; Spoth, Richard L; Redmond, Cleve R

2012-02-01

A substantial challenge in improving public health is how to facilitate the local adoption of evidence-based interventions (EBIs). To do so, an important step is to build local stakeholders' knowledge and decision-making skills regarding the adoption and implementation of EBIs. One EBI delivery system, called PROSPER (PROmoting School-community-university Partnerships to Enhance Resilience), has effectively mobilized community prevention efforts, implemented prevention programming with quality, and consequently decreased youth substance abuse. While these results are encouraging, another objective is to increase local stakeholder knowledge of best practices for adoption, implementation and evaluation of EBIs. Using a mixed methods approach, we assessed local stakeholder knowledge of these best practices over 5 years, in 28 intervention and control communities. Results indicated that the PROSPER partnership model led to significant increases in expert knowledge regarding the selection, implementation, and evaluation of evidence-based interventions. Findings illustrate the limited programming knowledge possessed by members of local prevention efforts, the difficulty of complete knowledge transfer, and highlight one method for cultivating that knowledge.

A Map-Based Service Supporting Different Types of Geographic Knowledge for the Public

PubMed Central

Zhou, Mengjie; Wang, Rui; Tian, Jing; Ye, Ning; Mai, Shumin

2016-01-01

The internet enables the rapid and easy creation, storage, and transfer of knowledge; however, services that transfer geographic knowledge and facilitate the public understanding of geographic knowledge are still underdeveloped to date. Existing online maps (or atlases) can support limited types of geographic knowledge. In this study, we propose a framework for map-based services to represent and transfer different types of geographic knowledge to the public. A map-based service provides tools to ensure the effective transfer of geographic knowledge. We discuss the types of geographic knowledge that should be represented and transferred to the public, and we propose guidelines and a method to represent various types of knowledge through a map-based service. To facilitate the effective transfer of geographic knowledge, tools such as auxiliary background knowledge and auxiliary map-reading tools are provided through interactions with maps. An experiment conducted to illustrate our idea and to evaluate the usefulness of the map-based service is described; the results demonstrate that the map-based service is useful for transferring different types of geographic knowledge. PMID:27045314

A Map-Based Service Supporting Different Types of Geographic Knowledge for the Public.

PubMed

Zhou, Mengjie; Wang, Rui; Tian, Jing; Ye, Ning; Mai, Shumin

2016-01-01

The internet enables the rapid and easy creation, storage, and transfer of knowledge; however, services that transfer geographic knowledge and facilitate the public understanding of geographic knowledge are still underdeveloped to date. Existing online maps (or atlases) can support limited types of geographic knowledge. In this study, we propose a framework for map-based services to represent and transfer different types of geographic knowledge to the public. A map-based service provides tools to ensure the effective transfer of geographic knowledge. We discuss the types of geographic knowledge that should be represented and transferred to the public, and we propose guidelines and a method to represent various types of knowledge through a map-based service. To facilitate the effective transfer of geographic knowledge, tools such as auxiliary background knowledge and auxiliary map-reading tools are provided through interactions with maps. An experiment conducted to illustrate our idea and to evaluate the usefulness of the map-based service is described; the results demonstrate that the map-based service is useful for transferring different types of geographic knowledge.

Knowledge into learning: comparing lecture, e-learning and self-study take-home packet instructional methodologies with nurses.

PubMed

Soper, Tracey

2017-04-01

The aim of this quantitative experimental study was to examine which of three instructional methodologies of traditional lecture, online electronic learning (e-learning) and self-study take-home packets are effective in knowledge acquisition of professional registered nurses. A true experimental design was conducted to contrast the knowledge acquisition of 87 registered nurses randomly selected. A 40-item Acute Coronary Syndrome (ACS) true/false test was used to measure knowledge acquisition. Based on 0.05 significance level, the ANOVA test revealed that there was no difference in knowledge acquisition by registered nurses based on which of three learning instructional method they were assigned. It can be concluded that while all of these instructional methods were equally effective in knowledge acquisition, these methods may not be equally cost- and time-effective. The study was able to determine that there were no significant differences in knowledge acquisition of nurses between the three instructional methodologies. The study also found that all groups scored at the acceptable level for certification. It can be concluded that all of these instructional methods were equally effective in knowledge acquisition but are not equally cost- and time-effective. Therefore, hospital educators may wish to formulate policies regarding choice of instructional method that take into account the efficient use of nurses' time and institutional resources.

Utilizing Expert Knowledge in Estimating Future STS Costs

NASA Technical Reports Server (NTRS)

Fortner, David B.; Ruiz-Torres, Alex J.

2004-01-01

A method of estimating the costs of future space transportation systems (STSs) involves classical activity-based cost (ABC) modeling combined with systematic utilization of the knowledge and opinions of experts to extend the process-flow knowledge of existing systems to systems that involve new materials and/or new architectures. The expert knowledge is particularly helpful in filling gaps that arise in computational models of processes because of inconsistencies in historical cost data. Heretofore, the costs of planned STSs have been estimated following a "top-down" approach that tends to force the architectures of new systems to incorporate process flows like those of the space shuttles. In this ABC-based method, one makes assumptions about the processes, but otherwise follows a "bottoms up" approach that does not force the new system architecture to incorporate a space-shuttle-like process flow. Prototype software has been developed to implement this method. Through further development of software, it should be possible to extend the method beyond the space program to almost any setting in which there is a need to estimate the costs of a new system and to extend the applicable knowledge base in order to make the estimate.

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

Incorporating linguistic knowledge for learning distributed word representations.

PubMed

Wang, Yan; Liu, Zhiyuan; Sun, Maosong

2015-01-01

Combined with neural language models, distributed word representations achieve significant advantages in computational linguistics and text mining. Most existing models estimate distributed word vectors from large-scale data in an unsupervised fashion, which, however, do not take rich linguistic knowledge into consideration. Linguistic knowledge can be represented as either link-based knowledge or preference-based knowledge, and we propose knowledge regularized word representation models (KRWR) to incorporate these prior knowledge for learning distributed word representations. Experiment results demonstrate that our estimated word representation achieves better performance in task of semantic relatedness ranking. This indicates that our methods can efficiently encode both prior knowledge from knowledge bases and statistical knowledge from large-scale text corpora into a unified word representation model, which will benefit many tasks in text mining.

Incorporating Linguistic Knowledge for Learning Distributed Word Representations

PubMed Central

Wang, Yan; Liu, Zhiyuan; Sun, Maosong

2015-01-01

Combined with neural language models, distributed word representations achieve significant advantages in computational linguistics and text mining. Most existing models estimate distributed word vectors from large-scale data in an unsupervised fashion, which, however, do not take rich linguistic knowledge into consideration. Linguistic knowledge can be represented as either link-based knowledge or preference-based knowledge, and we propose knowledge regularized word representation models (KRWR) to incorporate these prior knowledge for learning distributed word representations. Experiment results demonstrate that our estimated word representation achieves better performance in task of semantic relatedness ranking. This indicates that our methods can efficiently encode both prior knowledge from knowledge bases and statistical knowledge from large-scale text corpora into a unified word representation model, which will benefit many tasks in text mining. PMID:25874581

The effects of various instructional methods on retention of knowledge about pressure ulcers among critical care and medical-surgical nurses.

PubMed

Cox, Jill; Roche, Sharon; Van Wynen, Elizabeth

2011-02-01

To determine whether there was a difference in retention of knowledge about pressure ulcers with a traditional lecture versus computer-based instruction. A quasi-experimental, pretest/posttest design was used. Medical-surgical and critical care nurses (N = 60) were randomly assigned to a lecture, to computer-based instruction, or to a control group. Study participants were given the pressure ulcer knowledge test before and immediately after the program and at 3-month and 6-month intervals. Analysis of variance showed statistically significant differences in pretest and posttest scores [F(2, 57) = 35.784, p = .000] and in posttest to 3-month scores [F(2, 57) = 18.427, p = .000] among the three groups. The most significant loss of pressure ulcer knowledge, regardless of educational method, occurred within the first 3 months. Based on these findings, quarterly education in pressure ulcer prevention is recommended to maintain knowledge. Computer-based instruction is a viable option for acquisition and retention of knowledge about pressure ulcer prevention. Copyright 2011, SLACK Incorporated.

Evolutionary Local Search of Fuzzy Rules through a novel Neuro-Fuzzy encoding method.

PubMed

Carrascal, A; Manrique, D; Ríos, J; Rossi, C

2003-01-01

This paper proposes a new approach for constructing fuzzy knowledge bases using evolutionary methods. We have designed a genetic algorithm that automatically builds neuro-fuzzy architectures based on a new indirect encoding method. The neuro-fuzzy architecture represents the fuzzy knowledge base that solves a given problem; the search for this architecture takes advantage of a local search procedure that improves the chromosomes at each generation. Experiments conducted both on artificially generated and real world problems confirm the effectiveness of the proposed approach.

The Influence of Science Knowledge Structures on Children's Success in Solving Academic Problems.

ERIC Educational Resources Information Center

Champagne, Audrey B.; And Others

Presented is a study of eighth-grade students' academic problem-solving ability based on their knowledge structures, or their information stored in semantic or long-term memory. The authors describe a technique that they developed to probe knowledge structures with an extension of the card-sort method. The method, known as the Concept Structure…

Knowledge-Driven Event Extraction in Russian: Corpus-Based Linguistic Resources

PubMed Central

Solovyev, Valery; Ivanov, Vladimir

2016-01-01

Automatic event extraction form text is an important step in knowledge acquisition and knowledge base population. Manual work in development of extraction system is indispensable either in corpus annotation or in vocabularies and pattern creation for a knowledge-based system. Recent works have been focused on adaptation of existing system (for extraction from English texts) to new domains. Event extraction in other languages was not studied due to the lack of resources and algorithms necessary for natural language processing. In this paper we define a set of linguistic resources that are necessary in development of a knowledge-based event extraction system in Russian: a vocabulary of subordination models, a vocabulary of event triggers, and a vocabulary of Frame Elements that are basic building blocks for semantic patterns. We propose a set of methods for creation of such vocabularies in Russian and other languages using Google Books NGram Corpus. The methods are evaluated in development of event extraction system for Russian. PMID:26955386

The Application of Linear and Nonlinear Water Tanks Case Study in Teaching of Process Control

NASA Astrophysics Data System (ADS)

Li, Xiangshun; Li, Zhiang

2018-02-01

In the traditional process control teaching, the importance of passing knowledge is emphasized while the development of creative and practical abilities of students is ignored. Traditional teaching methods are not very helpful to breed a good engineer. Case teaching is a very useful way to improve students’ innovative and practical abilities. In the traditional case teaching, knowledge points are taught separately based on different examples or no examples, thus it is very hard to setup the whole knowledge structure. Though all the knowledge is learned, how to use the knowledge to solve engineering problems keeps challenging for students. In this paper, the linear and nonlinear tanks are taken as illustrative examples which involves several knowledge points of process control. The application method of each knowledge point is discussed in detail and simulated. I believe the case-based study will be helpful for students.

A novel knowledge-based potential for RNA 3D structure evaluation

NASA Astrophysics Data System (ADS)

Yang, Yi; Gu, Qi; Zhang, Ben-Gong; Shi, Ya-Zhou; Shao, Zhi-Gang

2018-03-01

Ribonucleic acids (RNAs) play a vital role in biology, and knowledge of their three-dimensional (3D) structure is required to understand their biological functions. Recently structural prediction methods have been developed to address this issue, but a series of RNA 3D structures are generally predicted by most existing methods. Therefore, the evaluation of the predicted structures is generally indispensable. Although several methods have been proposed to assess RNA 3D structures, the existing methods are not precise enough. In this work, a new all-atom knowledge-based potential is developed for more accurately evaluating RNA 3D structures. The potential not only includes local and nonlocal interactions but also fully considers the specificity of each RNA by introducing a retraining mechanism. Based on extensive test sets generated from independent methods, the proposed potential correctly distinguished the native state and ranked near-native conformations to effectively select the best. Furthermore, the proposed potential precisely captured RNA structural features such as base-stacking and base-pairing. Comparisons with existing potential methods show that the proposed potential is very reliable and accurate in RNA 3D structure evaluation. Project supported by the National Science Foundation of China (Grants Nos. 11605125, 11105054, 11274124, and 11401448).

Governance for public health and health equity: The Tröndelag model for public health work.

PubMed

Lillefjell, Monica; Magnus, Eva; Knudtsen, Margunn SkJei; Wist, Guri; Horghagen, Sissel; Espnes, Geir Arild; Maass, Ruca; Anthun, Kirsti Sarheim

2018-06-01

Multi-sectoral governance of population health is linked to the realization that health is the property of many societal systems. This study aims to contribute knowledge and methods that can strengthen the capacities of municipalities regarding how to work more systematically, knowledge-based and multi-sectoral in promoting health and health equity in the population. Process evaluation was conducted, applying a mixed-methods research design, combining qualitative and quantitative data collection methods. Processes strengthening systematic and multi-sectoral development, implementation and evaluation of research-based measures to promote health, quality of life, and health equity in, for and with municipalities were revealed. A step-by-step model, that emphasizes the promotion of knowledge-based, systematic, multi-sectoral public health work, as well as joint ownership of local resources, initiatives and policies has been developed. Implementation of systematic, knowledge-based and multi-sectoral governance of public health measures in municipalities demand shared understanding of the challenges, updated overview of the population health and impact factors, anchoring in plans, new skills and methods for selection and implementation of measures, as well as development of trust, ownership, shared ethics and goals among those involved.

Auditing Knowledge toward Leveraging Organizational IQ in Healthcare Organizations

PubMed Central

Shahmoradi, Leila; Farzaneh Nejad, Ahmadreza

2016-01-01

Objectives In this study, a knowledge audit was conducted based on organizational intelligence quotient (OIQ) principles of Iran's Ministry of Health and Medical Education (MOHME) to determine levers that can enhance OIQ in healthcare. Methods The mixed method study was conducted within the MOHME. The study population consisted of 15 senior managers and policymakers. A tool based on literature review and panel expert opinions was developed to perform a knowledge audit. Results The significant results of this auditing revealed the following: lack of defined standard processes for organizing knowledge management (KM), lack of a knowledge map, absence of a trustee to implement KM, absence of specialists to produce a knowledge map, individuals' unwillingness to share knowledge, implicitness of knowledge format, occasional nature of knowledge documentation for repeated use, lack of a mechanism to determine repetitive tasks, lack of a reward system for the formation of communities, groups and networks, non-updatedness of the available knowledge, and absence of commercial knowledge. Conclusions The analysis of the audit findings revealed that three levers for enhancing OIQ, including structure and process, organizational culture, and information technology must be created or modified. PMID:27200221

Knowledge Acquisition of Generic Queries for Information Retrieval

PubMed Central

Seol, Yoon-Ho; Johnson, Stephen B.; Cimino, James J.

2002-01-01

Several studies have identified clinical questions posed by health care professionals to understand the nature of information needs during clinical practice. To support access to digital information sources, it is necessary to integrate the information needs with a computer system. We have developed a conceptual guidance approach in information retrieval, based on a knowledge base that contains the patterns of information needs. The knowledge base uses a formal representation of clinical questions based on the UMLS knowledge sources, called the Generic Query model. To improve the coverage of the knowledge base, we investigated a method for extracting plausible clinical questions from the medical literature. This poster presents the Generic Query model, shows how it is used to represent the patterns of clinical questions, and describes the framework used to extract knowledge from the medical literature.

Sphinx: merging knowledge-based and ab initio approaches to improve protein loop prediction

PubMed Central

Marks, Claire; Nowak, Jaroslaw; Klostermann, Stefan; Georges, Guy; Dunbar, James; Shi, Jiye; Kelm, Sebastian

2017-01-01

Abstract Motivation: Loops are often vital for protein function, however, their irregular structures make them difficult to model accurately. Current loop modelling algorithms can mostly be divided into two categories: knowledge-based, where databases of fragments are searched to find suitable conformations and ab initio, where conformations are generated computationally. Existing knowledge-based methods only use fragments that are the same length as the target, even though loops of slightly different lengths may adopt similar conformations. Here, we present a novel method, Sphinx, which combines ab initio techniques with the potential extra structural information contained within loops of a different length to improve structure prediction. Results: We show that Sphinx is able to generate high-accuracy predictions and decoy sets enriched with near-native loop conformations, performing better than the ab initio algorithm on which it is based. In addition, it is able to provide predictions for every target, unlike some knowledge-based methods. Sphinx can be used successfully for the difficult problem of antibody H3 prediction, outperforming RosettaAntibody, one of the leading H3-specific ab initio methods, both in accuracy and speed. Availability and Implementation: Sphinx is available at http://opig.stats.ox.ac.uk/webapps/sphinx. Contact: deane@stats.ox.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28453681

Sphinx: merging knowledge-based and ab initio approaches to improve protein loop prediction.

PubMed

Marks, Claire; Nowak, Jaroslaw; Klostermann, Stefan; Georges, Guy; Dunbar, James; Shi, Jiye; Kelm, Sebastian; Deane, Charlotte M

2017-05-01

Loops are often vital for protein function, however, their irregular structures make them difficult to model accurately. Current loop modelling algorithms can mostly be divided into two categories: knowledge-based, where databases of fragments are searched to find suitable conformations and ab initio, where conformations are generated computationally. Existing knowledge-based methods only use fragments that are the same length as the target, even though loops of slightly different lengths may adopt similar conformations. Here, we present a novel method, Sphinx, which combines ab initio techniques with the potential extra structural information contained within loops of a different length to improve structure prediction. We show that Sphinx is able to generate high-accuracy predictions and decoy sets enriched with near-native loop conformations, performing better than the ab initio algorithm on which it is based. In addition, it is able to provide predictions for every target, unlike some knowledge-based methods. Sphinx can be used successfully for the difficult problem of antibody H3 prediction, outperforming RosettaAntibody, one of the leading H3-specific ab initio methods, both in accuracy and speed. Sphinx is available at http://opig.stats.ox.ac.uk/webapps/sphinx. deane@stats.ox.ac.uk. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press.

Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships

PubMed Central

2010-01-01

Background The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. While early methods for discovery of transcriptional regulation relationships from microarray data often focused on the high-throughput experimental data alone, more recent approaches have explored the integration of external knowledge bases of gene interactions. Results In this work, we develop an algorithm that provides improved performance in the prediction of transcriptional regulatory relationships by supplementing the analysis of microarray data with a new method of integrating information from an existing knowledge base. Using a well-known dataset of yeast microarrays and the Yeast Proteome Database, a comprehensive collection of known information of yeast genes, we show that knowledge-based predictions demonstrate better sensitivity and specificity in inferring new transcriptional interactions than predictions from microarray data alone. We also show that comprehensive, direct and high-quality knowledge bases provide better prediction performance. Comparison of our results with ChIP-chip data and growth fitness data suggests that our predicted genome-wide regulatory pairs in yeast are reasonable candidates for follow-up biological verification. Conclusion High quality, comprehensive, and direct knowledge bases, when combined with appropriate bioinformatic algorithms, can significantly improve the discovery of gene regulatory relationships from high throughput gene expression data. PMID:20122245

Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships.

PubMed

Seok, Junhee; Kaushal, Amit; Davis, Ronald W; Xiao, Wenzhong

2010-01-18

The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. While early methods for discovery of transcriptional regulation relationships from microarray data often focused on the high-throughput experimental data alone, more recent approaches have explored the integration of external knowledge bases of gene interactions. In this work, we develop an algorithm that provides improved performance in the prediction of transcriptional regulatory relationships by supplementing the analysis of microarray data with a new method of integrating information from an existing knowledge base. Using a well-known dataset of yeast microarrays and the Yeast Proteome Database, a comprehensive collection of known information of yeast genes, we show that knowledge-based predictions demonstrate better sensitivity and specificity in inferring new transcriptional interactions than predictions from microarray data alone. We also show that comprehensive, direct and high-quality knowledge bases provide better prediction performance. Comparison of our results with ChIP-chip data and growth fitness data suggests that our predicted genome-wide regulatory pairs in yeast are reasonable candidates for follow-up biological verification. High quality, comprehensive, and direct knowledge bases, when combined with appropriate bioinformatic algorithms, can significantly improve the discovery of gene regulatory relationships from high throughput gene expression data.

Declarative and Dynamic Pedagogical Content Knowledge as Elicited through Two Video-Based Interview Methods

ERIC Educational Resources Information Center

Alonzo, Alicia C.; Kim, Jiwon

2016-01-01

Although pedagogical content knowledge (PCK) has become widely recognized as an essential part of the knowledge base for teaching, empirical evidence demonstrating a connection between PCK and teaching practice or student learning outcomes is mixed. In response, we argue for further attention to the measurement of dynamic (spontaneous or flexible,…

Health-Related Fitness Knowledge Development through Project-Based Learning

ERIC Educational Resources Information Center

Hastle, Peter A.; Chen, Senlin; Guarino, Anthony J.

2017-01-01

Purpose: The purpose of this study was to examine the process and outcome of an intervention using the project-based learning (PBL) model to increase students' health-related fitness (HRF) knowledge. Method: The participants were 185 fifth-grade students from three schools in Alabama (PBL group: n = 109; control group: n = 76). HRF knowledge was…

Classifying Web Pages by Using Knowledge Bases for Entity Retrieval

NASA Astrophysics Data System (ADS)

Kiritani, Yusuke; Ma, Qiang; Yoshikawa, Masatoshi

In this paper, we propose a novel method to classify Web pages by using knowledge bases for entity search, which is a kind of typical Web search for information related to a person, location or organization. First, we map a Web page to entities according to the similarities between the page and the entities. Various methods for computing such similarity are applied. For example, we can compute the similarity between a given page and a Wikipedia article describing a certain entity. The frequency of an entity appearing in the page is another factor used in computing the similarity. Second, we construct a directed acyclic graph, named PEC graph, based on the relations among Web pages, entities, and categories, by referring to YAGO, a knowledge base built on Wikipedia and WordNet. Finally, by analyzing the PEC graph, we classify Web pages into categories. The results of some preliminary experiments validate the methods proposed in this paper.

Epistemic Beliefs of Middle and High School Students in a Problem-Based, Scientific Inquiry Unit: An Exploratory, Mixed Methods Study

ERIC Educational Resources Information Center

Gu, Jiangyue

2016-01-01

Epistemic beliefs are individuals' beliefs about the nature of knowledge, how knowledge is constructed, and how knowledge can be justified. This study employed a mixed-methods approach to examine: (a) middle and high school students' self-reported epistemic beliefs (quantitative) and epistemic beliefs revealed from practice (qualitative) during a…

Ontology-guided data preparation for discovering genotype-phenotype relationships.

PubMed

Coulet, Adrien; Smaïl-Tabbone, Malika; Benlian, Pascale; Napoli, Amedeo; Devignes, Marie-Dominique

2008-04-25

Complexity and amount of post-genomic data constitute two major factors limiting the application of Knowledge Discovery in Databases (KDD) methods in life sciences. Bio-ontologies may nowadays play key roles in knowledge discovery in life science providing semantics to data and to extracted units, by taking advantage of the progress of Semantic Web technologies concerning the understanding and availability of tools for knowledge representation, extraction, and reasoning. This paper presents a method that exploits bio-ontologies for guiding data selection within the preparation step of the KDD process. We propose three scenarios in which domain knowledge and ontology elements such as subsumption, properties, class descriptions, are taken into account for data selection, before the data mining step. Each of these scenarios is illustrated within a case-study relative to the search of genotype-phenotype relationships in a familial hypercholesterolemia dataset. The guiding of data selection based on domain knowledge is analysed and shows a direct influence on the volume and significance of the data mining results. The method proposed in this paper is an efficient alternative to numerical methods for data selection based on domain knowledge. In turn, the results of this study may be reused in ontology modelling and data integration.

Hubble Space Telescope Design Engineering Knowledgebase (HSTDEK)

NASA Technical Reports Server (NTRS)

Johannes, James D.; Everetts, Clark

1989-01-01

The research covered here pays specific attention to the development of tools to assist knowledge engineers in acquiring knowledge and to assist other technical, engineering, and management personnel in automatically performing knowledge capture as part of their everyday work without adding any extra work to what they already do. Requirements for data products, the knowledge base, and methods for mapping knowledge in the documents onto the knowledge representations are discussed, as are some of the difficulties of capturing in the knowledge base the structure of the design process itself, along with a model of the system designed. The capture of knowledge describing the interactions of different components is also discussed briefly.

Using Quality Management Methods in Knowledge-Based Organizations. An Approach to the Application of the Taguchi Method to the Process of Pressing Tappets into Anchors

NASA Astrophysics Data System (ADS)

Ţîţu, M. A.; Pop, A. B.; Ţîţu, Ș

2017-06-01

This paper presents a study on the modelling and optimization of certain variables by using the Taguchi Method with a view to modelling and optimizing the process of pressing tappets into anchors, process conducted in an organization that promotes knowledge-based management. The paper promotes practical concepts of the Taguchi Method and describes the way in which the objective functions are obtained and used during the modelling and optimization of the process of pressing tappets into the anchors.

Using the Socratic Method in Secondary Teaching.

ERIC Educational Resources Information Center

Schoeman, Stephen

1997-01-01

Students are more accustomed to receiving knowledge than to questioning knowledge, challenging underlying assumptions, and seeing inconsistencies and irrelevancies. The Socratic method requires teachers to challenge students' critical thinking abilities by developing questions based on analogies and hypothetical situations. Although the Socratic…

Measuring Teachers' Pedagogical Content Knowledge in Primary Technology Education

ERIC Educational Resources Information Center

Rohaan, Ellen J.; Taconis, Ruurd; Jochems, Wim M. G.

2009-01-01

Pedagogical content knowledge is found to be a crucial part of the knowledge base for teaching. Studies in the field of primary technology education showed that this domain of teacher knowledge is related to pupils' increased learning, motivation, and interest. The common methods to investigate teachers' pedagogical content knowledge are often…

Research of Litchi Diseases Diagnosis Expertsystem Based on Rbr and Cbr

NASA Astrophysics Data System (ADS)

Xu, Bing; Liu, Liqun

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

Theatre as a Vehicle for Mobilizing Knowledge in Education

ERIC Educational Resources Information Center

Segedin, Lauren

2017-01-01

In the field of education, there has been an increased emphasis on evidence-based practice. Yet, traditional dissemination methods continue to be used. Using more creative and innovative strategies to disseminate research are needed. Theatre is one such method. Stemming from the research on knowledge mobilization and theatre as a method for social…

Towards an Obesity-Cancer Knowledge Base: Biomedical Entity Identification and Relation Detection

PubMed Central

Lossio-Ventura, Juan Antonio; Hogan, William; Modave, François; Hicks, Amanda; Hanna, Josh; Guo, Yi; He, Zhe; Bian, Jiang

2017-01-01

Obesity is associated with increased risks of various types of cancer, as well as a wide range of other chronic diseases. On the other hand, access to health information activates patient participation, and improve their health outcomes. However, existing online information on obesity and its relationship to cancer is heterogeneous ranging from pre-clinical models and case studies to mere hypothesis-based scientific arguments. A formal knowledge representation (i.e., a semantic knowledge base) would help better organizing and delivering quality health information related to obesity and cancer that consumers need. Nevertheless, current ontologies describing obesity, cancer and related entities are not designed to guide automatic knowledge base construction from heterogeneous information sources. Thus, in this paper, we present methods for named-entity recognition (NER) to extract biomedical entities from scholarly articles and for detecting if two biomedical entities are related, with the long term goal of building a obesity-cancer knowledge base. We leverage both linguistic and statistical approaches in the NER task, which supersedes the state-of-the-art results. Further, based on statistical features extracted from the sentences, our method for relation detection obtains an accuracy of 99.3% and a f-measure of 0.993. PMID:28503356

Participatory approach to the development of a knowledge base for problem-solving in diabetes self-management.

PubMed

Cole-Lewis, Heather J; Smaldone, Arlene M; Davidson, Patricia R; Kukafka, Rita; Tobin, Jonathan N; Cassells, Andrea; Mynatt, Elizabeth D; Hripcsak, George; Mamykina, Lena

2016-01-01

To develop an expandable knowledge base of reusable knowledge related to self-management of diabetes that can be used as a foundation for patient-centric decision support tools. The structure and components of the knowledge base were created in participatory design with academic diabetes educators using knowledge acquisition methods. The knowledge base was validated using scenario-based approach with practicing diabetes educators and individuals with diabetes recruited from Community Health Centers (CHCs) serving economically disadvantaged communities and ethnic minorities in New York. The knowledge base includes eight glycemic control problems, over 150 behaviors known to contribute to these problems coupled with contextual explanations, and over 200 specific action-oriented self-management goals for correcting problematic behaviors, with corresponding motivational messages. The validation of the knowledge base suggested high level of completeness and accuracy, and identified improvements in cultural appropriateness. These were addressed in new iterations of the knowledge base. The resulting knowledge base is theoretically grounded, incorporates practical and evidence-based knowledge used by diabetes educators in practice settings, and allows for personally meaningful choices by individuals with diabetes. Participatory design approach helped researchers to capture implicit knowledge of practicing diabetes educators and make it explicit and reusable. The knowledge base proposed here is an important step towards development of new generation patient-centric decision support tools for facilitating chronic disease self-management. While this knowledge base specifically targets diabetes, its overall structure and composition can be generalized to other chronic conditions. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Recommendation Techniques for Drug-Target Interaction Prediction and Drug Repositioning.

PubMed

Alaimo, Salvatore; Giugno, Rosalba; Pulvirenti, Alfredo

2016-01-01

The usage of computational methods in drug discovery is a common practice. More recently, by exploiting the wealth of biological knowledge bases, a novel approach called drug repositioning has raised. Several computational methods are available, and these try to make a high-level integration of all the knowledge in order to discover unknown mechanisms. In this chapter, we review drug-target interaction prediction methods based on a recommendation system. We also give some extensions which go beyond the bipartite network case.

Novel keyword co-occurrence network-based methods to foster systematic reviews of scientific literature.

PubMed

Radhakrishnan, Srinivasan; Erbis, Serkan; Isaacs, Jacqueline A; Kamarthi, Sagar

2017-01-01

Systematic reviews of scientific literature are important for mapping the existing state of research and highlighting further growth channels in a field of study, but systematic reviews are inherently tedious, time consuming, and manual in nature. In recent years, keyword co-occurrence networks (KCNs) are exploited for knowledge mapping. In a KCN, each keyword is represented as a node and each co-occurrence of a pair of words is represented as a link. The number of times that a pair of words co-occurs in multiple articles constitutes the weight of the link connecting the pair. The network constructed in this manner represents cumulative knowledge of a domain and helps to uncover meaningful knowledge components and insights based on the patterns and strength of links between keywords that appear in the literature. In this work, we propose a KCN-based approach that can be implemented prior to undertaking a systematic review to guide and accelerate the review process. The novelty of this method lies in the new metrics used for statistical analysis of a KCN that differ from those typically used for KCN analysis. The approach is demonstrated through its application to nano-related Environmental, Health, and Safety (EHS) risk literature. The KCN approach identified the knowledge components, knowledge structure, and research trends that match with those discovered through a traditional systematic review of the nanoEHS field. Because KCN-based analyses can be conducted more quickly to explore a vast amount of literature, this method can provide a knowledge map and insights prior to undertaking a rigorous traditional systematic review. This two-step approach can significantly reduce the effort and time required for a traditional systematic literature review. The proposed KCN-based pre-systematic review method is universal. It can be applied to any scientific field of study to prepare a knowledge map.

Novel keyword co-occurrence network-based methods to foster systematic reviews of scientific literature

PubMed Central

Isaacs, Jacqueline A.

2017-01-01

Systematic reviews of scientific literature are important for mapping the existing state of research and highlighting further growth channels in a field of study, but systematic reviews are inherently tedious, time consuming, and manual in nature. In recent years, keyword co-occurrence networks (KCNs) are exploited for knowledge mapping. In a KCN, each keyword is represented as a node and each co-occurrence of a pair of words is represented as a link. The number of times that a pair of words co-occurs in multiple articles constitutes the weight of the link connecting the pair. The network constructed in this manner represents cumulative knowledge of a domain and helps to uncover meaningful knowledge components and insights based on the patterns and strength of links between keywords that appear in the literature. In this work, we propose a KCN-based approach that can be implemented prior to undertaking a systematic review to guide and accelerate the review process. The novelty of this method lies in the new metrics used for statistical analysis of a KCN that differ from those typically used for KCN analysis. The approach is demonstrated through its application to nano-related Environmental, Health, and Safety (EHS) risk literature. The KCN approach identified the knowledge components, knowledge structure, and research trends that match with those discovered through a traditional systematic review of the nanoEHS field. Because KCN-based analyses can be conducted more quickly to explore a vast amount of literature, this method can provide a knowledge map and insights prior to undertaking a rigorous traditional systematic review. This two-step approach can significantly reduce the effort and time required for a traditional systematic literature review. The proposed KCN-based pre-systematic review method is universal. It can be applied to any scientific field of study to prepare a knowledge map. PMID:28328983

Structural and Network-based Methods for Knowledge-Based Systems

DTIC Science & Technology

2011-12-01

depth) provide important information about knowledge gaps in the KB. For example, if SuccessEstimate (causes-EventEvent, Typhoid - Fever , 1, 3) is...equal to 0, it points toward lack of biological knowledge about Typhoid - Fever in our KB. Similar information can also be obtained from the...position of the consequent. ⋃ ( ( ) ) Therefore, if Q does not contain Typhoid - Fever , then obtaining

Developing Evidence for Public Health Policy and Practice: The Implementation of a Knowledge Translation Approach in a Staged, Multi-Methods Study in England, 2007-09

ERIC Educational Resources Information Center

South, Jane; Cattan, Mima

2014-01-01

Effective knowledge translation processes are critical for the development of evidence-based public health policy and practice. This paper reports on the design and implementation of an innovative approach to knowledge translation within a mixed methods study on lay involvement in public health programme delivery. The study design drew on…

Evidence-Based Administration for Decision Making in the Framework of Knowledge Strategic Management

ERIC Educational Resources Information Center

Del Junco, Julio Garcia; Zaballa, Rafael De Reyna; de Perea, Juan Garcia Alvarez

2010-01-01

Purpose: This paper seeks to present a model based on evidence-based administration (EBA), which aims to facilitate the creation, transformation and diffusion of knowledge in learning organizations. Design/methodology/approach: A theoretical framework is proposed based on EBA and the case method. Accordingly, an empirical study was carried out in…

Fuzzy and neural control

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1992-01-01

Fuzzy logic and neural networks provide new methods for designing control systems. Fuzzy logic controllers do not require a complete analytical model of a dynamic system and can provide knowledge-based heuristic controllers for ill-defined and complex systems. Neural networks can be used for learning control. In this chapter, we discuss hybrid methods using fuzzy logic and neural networks which can start with an approximate control knowledge base and refine it through reinforcement learning.

Exploration and implementation of ontology-based cultural relic knowledge map integration platform

NASA Astrophysics Data System (ADS)

Yang, Weiqiang; Dong, Yiqiang

2018-05-01

To help designers to better carry out creative design and improve the ability of searching traditional cultural relic information, the ontology-based knowledge map construction method was explored and an integrated platform for cultural relic knowledge map was developed. First of all, the construction method of the ontology of cultural relics was put forward, and the construction of the knowledge map of cultural relics was completed based on the constructed cultural relic otology. Then, a personalized semantic retrieval framework for creative design was proposed. Finally, the integrated platform of the knowledge map of cultural relics was designed and realized. The platform was divided into two parts. One was the foreground display system, which was used for designers to search and browse cultural relics. The other was the background management system, which was for cultural experts to manage cultural relics' knowledge. The research results showed that the platform designed could improve the retrieval ability of cultural relic information. To sum up, the platform can provide a good support for the designer's creative design.

Evaluating an education/training module to foster knowledge of cockpit weather technology.

PubMed

Cobbett, Erin A; Blickensderfer, Elizabeth L; Lanicci, John

2014-10-01

Previous research has indicated that general aviation (GA) pilots may use the sophisticated meteorological information available to them via a variety of Next-Generation Weather Radar (NEXRAD) based weather products in a manner that actually decreases flight safety. The current study examined an education/training method designed to enable GA pilots to use NEXRAD-based products effectively in convective weather situations. The training method was lecture combined with paper-based scenario exercises. A multivariate analysis of variance revealed that subjects in the training condition performed significantly better than did subjects in the control condition on several knowledge and attitude measures. Subjects in the training condition improved from a mean score of 66% to 80% on the radar-knowledge test and from 62% to 75% on the scenario-knowledge test. Although additional research is needed, these results demonstrated that pilots can benefit from a well-designed education/training program involving specific areas of aviation weather-related knowledge.

Developing a geoscience knowledge framework for a national geological survey organisation

NASA Astrophysics Data System (ADS)

Howard, Andrew S.; Hatton, Bill; Reitsma, Femke; Lawrie, Ken I. G.

2009-04-01

Geological survey organisations (GSOs) are established by most nations to provide a geoscience knowledge base for effective decision-making on mitigating the impacts of natural hazards and global change, and on sustainable management of natural resources. The value of the knowledge base as a national asset is continually enhanced by the exchange of knowledge between GSOs as data and information providers and the stakeholder community as knowledge 'users and exploiters'. Geological maps and associated narrative texts typically form the core of national geoscience knowledge bases, but have some inherent limitations as methods of capturing and articulating knowledge. Much knowledge about the three-dimensional (3D) spatial interpretation and its derivation and uncertainty, and the wider contextual value of the knowledge, remains intangible in the minds of the mapping geologist in implicit and tacit form. To realise the value of these knowledge assets, the British Geological Survey (BGS) has established a workflow-based cyber-infrastructure to enhance its knowledge management and exchange capability. Future geoscience surveys in the BGS will contribute to a national, 3D digital knowledge base on UK geology, with the associated implicit and tacit information captured as metadata, qualitative assessments of uncertainty, and documented workflows and best practice. Knowledge-based decision-making at all levels of society requires both the accessibility and reliability of knowledge to be enhanced in the grid-based world. Establishment of collaborative cyber-infrastructures and ontologies for geoscience knowledge management and exchange will ensure that GSOs, as knowledge-based organisations, can make their contribution to this wider goal.

Evaluation Criteria for Competency-Based Syllabi: A Chilean Case Study Applying Mixed Methods

ERIC Educational Resources Information Center

Jerez, Oscar; Valenzuela, Leslier; Pizarro, Veronica; Hasbun, Beatriz; Valenzuela, Gabriela; Orsini, Cesar

2016-01-01

In recent decades, higher education institutions worldwide have been moving from knowledge-based to competence-based curricula. One of the greatest challenges in this transition is the difficulty in changing the knowledge-oriented practices of teachers. This study evaluates the consistency between syllabus design and the requirements imposed by a…

New knowledge-based genetic algorithm for excavator boom structural optimization

NASA Astrophysics Data System (ADS)

Hua, Haiyan; Lin, Shuwen

2014-03-01

Due to the insufficiency of utilizing knowledge to guide the complex optimal searching, existing genetic algorithms fail to effectively solve excavator boom structural optimization problem. To improve the optimization efficiency and quality, a new knowledge-based real-coded genetic algorithm is proposed. A dual evolution mechanism combining knowledge evolution with genetic algorithm is established to extract, handle and utilize the shallow and deep implicit constraint knowledge to guide the optimal searching of genetic algorithm circularly. Based on this dual evolution mechanism, knowledge evolution and population evolution can be connected by knowledge influence operators to improve the configurability of knowledge and genetic operators. Then, the new knowledge-based selection operator, crossover operator and mutation operator are proposed to integrate the optimal process knowledge and domain culture to guide the excavator boom structural optimization. Eight kinds of testing algorithms, which include different genetic operators, are taken as examples to solve the structural optimization of a medium-sized excavator boom. By comparing the results of optimization, it is shown that the algorithm including all the new knowledge-based genetic operators can more remarkably improve the evolutionary rate and searching ability than other testing algorithms, which demonstrates the effectiveness of knowledge for guiding optimal searching. The proposed knowledge-based genetic algorithm by combining multi-level knowledge evolution with numerical optimization provides a new effective method for solving the complex engineering optimization problem.

Web-video-mining-supported workflow modeling for laparoscopic surgeries.

PubMed

Liu, Rui; Zhang, Xiaoli; Zhang, Hao

2016-11-01

As quality assurance is of strong concern in advanced surgeries, intelligent surgical systems are expected to have knowledge such as the knowledge of the surgical workflow model (SWM) to support their intuitive cooperation with surgeons. For generating a robust and reliable SWM, a large amount of training data is required. However, training data collected by physically recording surgery operations is often limited and data collection is time-consuming and labor-intensive, severely influencing knowledge scalability of the surgical systems. The objective of this research is to solve the knowledge scalability problem in surgical workflow modeling with a low cost and labor efficient way. A novel web-video-mining-supported surgical workflow modeling (webSWM) method is developed. A novel video quality analysis method based on topic analysis and sentiment analysis techniques is developed to select high-quality videos from abundant and noisy web videos. A statistical learning method is then used to build the workflow model based on the selected videos. To test the effectiveness of the webSWM method, 250 web videos were mined to generate a surgical workflow for the robotic cholecystectomy surgery. The generated workflow was evaluated by 4 web-retrieved videos and 4 operation-room-recorded videos, respectively. The evaluation results (video selection consistency n-index ≥0.60; surgical workflow matching degree ≥0.84) proved the effectiveness of the webSWM method in generating robust and reliable SWM knowledge by mining web videos. With the webSWM method, abundant web videos were selected and a reliable SWM was modeled in a short time with low labor cost. Satisfied performances in mining web videos and learning surgery-related knowledge show that the webSWM method is promising in scaling knowledge for intelligent surgical systems. Copyright © 2016 Elsevier B.V. All rights reserved.

Computer Aided Program Synthesis.

DTIC Science & Technology

1980-01-01

Representations 18 .2 Refinements and Reductions 18.:2.3 Dependenc ies 20 3.3 The Programming Knowledge Base 21 3.4 Linguistic Knowledge 22 3.5...strategy selection knowledge, i.e. knowledge representing a context sensitive discrimination among alternate methods; and knowledge of logical...program, each supplying his expertise. The client describes his task to the consultant and supplies answers and explanations to the consultant’s

Use of metaknowledge in the verification of knowledge-based systems

NASA Technical Reports Server (NTRS)

Morell, Larry J.

1989-01-01

Knowledge-based systems are modeled as deductive systems. The model indicates that the two primary areas of concern in verification are demonstrating consistency and completeness. A system is inconsistent if it asserts something that is not true of the modeled domain. A system is incomplete if it lacks deductive capability. Two forms of consistency are discussed along with appropriate verification methods. Three forms of incompleteness are discussed. The use of metaknowledge, knowledge about knowledge, is explored in connection to each form of incompleteness.

Exchanging clinical knowledge via Internet.

PubMed

Buchan, I E; Hanka, R

1997-11-01

The need for effective and efficient exchange of clinical knowledge is increasing. Paper based methods for managing clinical knowledge are not meeting the demand for knowledge and this has undoubtedly contributed to the widely reported failures of clinical guidelines. Internet affords both opportunities and dangers for clinical knowledge. Systems such as Wax have demonstrated the importance of intuitive structure in the management of knowledge. We report on a new initiative for the global management of clinical knowledge.

Knowledge-based processing for aircraft flight control

NASA Technical Reports Server (NTRS)

Painter, John H.; Glass, Emily; Economides, Gregory; Russell, Paul

1994-01-01

This Contractor Report documents research in Intelligent Control using knowledge-based processing in a manner dual to methods found in the classic stochastic decision, estimation, and control discipline. Such knowledge-based control has also been called Declarative, and Hybid. Software architectures were sought, employing the parallelism inherent in modern object-oriented modeling and programming. The viewpoint adopted was that Intelligent Control employs a class of domain-specific software architectures having features common over a broad variety of implementations, such as management of aircraft flight, power distribution, etc. As much attention was paid to software engineering issues as to artificial intelligence and control issues. This research considered that particular processing methods from the stochastic and knowledge-based worlds are duals, that is, similar in a broad context. They provide architectural design concepts which serve as bridges between the disparate disciplines of decision, estimation, control, and artificial intelligence. This research was applied to the control of a subsonic transport aircraft in the airport terminal area.

Computer Assisted Multi-Center Creation of Medical Knowledge Bases

PubMed Central

Giuse, Nunzia Bettinsoli; Giuse, Dario A.; Miller, Randolph A.

1988-01-01

Computer programs which support different aspects of medical care have been developed in recent years. Their capabilities range from diagnosis to medical imaging, and include hospital management systems and therapy prescription. In spite of their diversity these systems have one commonality: their reliance on a large body of medical knowledge in computer-readable form. This knowledge enables such programs to draw inferences, validate hypotheses, and in general to perform their intended task. As has been clear to developers of such systems, however, the creation and maintenance of medical knowledge bases are very expensive. Practical and economical difficulties encountered during this long-term process have discouraged most attempts. This paper discusses knowledge base creation and maintenance, with special emphasis on medical applications. We first describe the methods currently used and their limitations. We then present our recent work on developing tools and methodologies which will assist in the process of creating a medical knowledge base. We focus, in particular, on the possibility of multi-center creation of the knowledge base.

Voice-enabled Knowledge Engine using Flood Ontology and Natural Language Processing

NASA Astrophysics Data System (ADS)

Sermet, M. Y.; Demir, I.; Krajewski, W. F.

2015-12-01

The Iowa Flood Information System (IFIS) is a web-based platform developed by the Iowa Flood Center (IFC) to provide access to flood inundation maps, real-time flood conditions, flood forecasts, flood-related data, information and interactive visualizations for communities in Iowa. The IFIS is designed for use by general public, often people with no domain knowledge and limited general science background. To improve effective communication with such audience, we have introduced a voice-enabled knowledge engine on flood related issues in IFIS. Instead of navigating within many features and interfaces of the information system and web-based sources, the system provides dynamic computations based on a collection of built-in data, analysis, and methods. The IFIS Knowledge Engine connects to real-time stream gauges, in-house data sources, analysis and visualization tools to answer natural language questions. Our goal is the systematization of data and modeling results on flood related issues in Iowa, and to provide an interface for definitive answers to factual queries. The goal of the knowledge engine is to make all flood related knowledge in Iowa easily accessible to everyone, and support voice-enabled natural language input. We aim to integrate and curate all flood related data, implement analytical and visualization tools, and make it possible to compute answers from questions. The IFIS explicitly implements analytical methods and models, as algorithms, and curates all flood related data and resources so that all these resources are computable. The IFIS Knowledge Engine computes the answer by deriving it from its computational knowledge base. The knowledge engine processes the statement, access data warehouse, run complex database queries on the server-side and return outputs in various formats. This presentation provides an overview of IFIS Knowledge Engine, its unique information interface and functionality as an educational tool, and discusses the future plans for providing knowledge on flood related issues and resources. IFIS Knowledge Engine provides an alternative access method to these comprehensive set of tools and data resources available in IFIS. Current implementation of the system accepts free-form input and voice recognition capabilities within browser and mobile applications.

Design and Implementation of a Simulation-Based Learning System for International Trade

ERIC Educational Resources Information Center

Luo, Guo-Heng; Liu, Eric Zhi-Feng; Kuo, Hung-Wei; Yuan, Shyan-Ming

2014-01-01

In the traditional instructional method used in international trade, teachers provide knowledge to learners by lecturing using slides and setting assignments; however, these methods merely deliver international trade knowledge rather than facilitating student development of relevant skills. To solve these problems, we proposed a simulation-based…

Knowledge Activation and Schema Construction.

ERIC Educational Resources Information Center

Alvarez, Marino C.

This study examined how instruction that encourages critical thinking about what has been read can lead to incorporated knowledge that can be retrieved and applied to other related settings. Case-based learning (an instructional method long used with graduate business, law, and medical students) is one method that can be used to foster critical…

Methodology for testing and validating knowledge bases

NASA Technical Reports Server (NTRS)

Krishnamurthy, C.; Padalkar, S.; Sztipanovits, J.; Purves, B. R.

1987-01-01

A test and validation toolset developed for artificial intelligence programs is described. The basic premises of this method are: (1) knowledge bases have a strongly declarative character and represent mostly structural information about different domains, (2) the conditions for integrity, consistency, and correctness can be transformed into structural properties of knowledge bases, and (3) structural information and structural properties can be uniformly represented by graphs and checked by graph algorithms. The interactive test and validation environment have been implemented on a SUN workstation.

Knowledge acquisition for medical diagnosis using collective intelligence.

PubMed

Hernández-Chan, G; Rodríguez-González, A; Alor-Hernández, G; Gómez-Berbís, J M; Mayer-Pujadas, M A; Posada-Gómez, R

2012-11-01

The wisdom of the crowds (WOC) is the process of taking into account the collective opinion of a group of individuals rather than a single expert to answer a question. Based on this assumption, the use of processes based on WOC techniques to collect new biomedical knowledge represents a challenging and cutting-edge trend on biomedical knowledge acquisition. The work presented in this paper shows a new schema to collect diagnosis information in Diagnosis Decision Support Systems (DDSS) based on collective intelligence and consensus methods.

Unbiased Protein Association Study on the Public Human Proteome Reveals Biological Connections between Co-Occurring Protein Pairs

PubMed Central

2017-01-01

Mass-spectrometry-based, high-throughput proteomics experiments produce large amounts of data. While typically acquired to answer specific biological questions, these data can also be reused in orthogonal ways to reveal new biological knowledge. We here present a novel method for such orthogonal data reuse of public proteomics data. Our method elucidates biological relationships between proteins based on the co-occurrence of these proteins across human experiments in the PRIDE database. The majority of the significantly co-occurring protein pairs that were detected by our method have been successfully mapped to existing biological knowledge. The validity of our novel method is substantiated by the extremely few pairs that can be mapped to existing knowledge based on random associations between the same set of proteins. Moreover, using literature searches and the STRING database, we were able to derive meaningful biological associations for unannotated protein pairs that were detected using our method, further illustrating that as-yet unknown associations present highly interesting targets for follow-up analysis. PMID:28480704

Knowledge acquisition from natural language for expert systems based on classification problem-solving methods

NASA Technical Reports Server (NTRS)

Gomez, Fernando

1989-01-01

It is shown how certain kinds of domain independent expert systems based on classification problem-solving methods can be constructed directly from natural language descriptions by a human expert. The expert knowledge is not translated into production rules. Rather, it is mapped into conceptual structures which are integrated into long-term memory (LTM). The resulting system is one in which problem-solving, retrieval and memory organization are integrated processes. In other words, the same algorithm and knowledge representation structures are shared by these processes. As a result of this, the system can answer questions, solve problems or reorganize LTM.

Drift-Free Position Estimation of Periodic or Quasi-Periodic Motion Using Inertial Sensors

PubMed Central

Latt, Win Tun; Veluvolu, Kalyana Chakravarthy; Ang, Wei Tech

2011-01-01

Position sensing with inertial sensors such as accelerometers and gyroscopes usually requires other aided sensors or prior knowledge of motion characteristics to remove position drift resulting from integration of acceleration or velocity so as to obtain accurate position estimation. A method based on analytical integration has previously been developed to obtain accurate position estimate of periodic or quasi-periodic motion from inertial sensors using prior knowledge of the motion but without using aided sensors. In this paper, a new method is proposed which employs linear filtering stage coupled with adaptive filtering stage to remove drift and attenuation. The prior knowledge of the motion the proposed method requires is only approximate band of frequencies of the motion. Existing adaptive filtering methods based on Fourier series such as weighted-frequency Fourier linear combiner (WFLC), and band-limited multiple Fourier linear combiner (BMFLC) are modified to combine with the proposed method. To validate and compare the performance of the proposed method with the method based on analytical integration, simulation study is performed using periodic signals as well as real physiological tremor data, and real-time experiments are conducted using an ADXL-203 accelerometer. Results demonstrate that the performance of the proposed method outperforms the existing analytical integration method. PMID:22163935

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

Scalable Learning for Geostatistics and Speaker Recognition

DTIC Science & Technology

2011-01-01

of prior knowledge of the model or due to improved robustness requirements). Both these methods have their own advantages and disadvantages. The use...application. If the data is well-correlated and low-dimensional, any prior knowledge available on the data can be used to build a parametric model. In the...absence of prior knowledge , non-parametric methods can be used. If the data is high-dimensional, PCA based dimensionality reduction is often the first

Knowledge Creation in Nursing Education

PubMed Central

Hassanian, Zahra Marzieh; Ahanchian, Mohammad Reza; Ahmadi, Suleiman; Gholizadeh, Rezvan Hossein; Karimi-Moonaghi, Hossein

2015-01-01

In today’s society, knowledge is recognized as a valuable social asset and the educational system is in search of a new strategy that allows them to construct their knowledge and experience. The purpose of this study was to explore the process of knowledge creation in nursing education. In the present study, the grounded theory approach was used. This method provides a comprehensive approach to collecting, organizing, and analyzing data. Data were obtained through 17 semi-structured interviews with nursing faculties and nursing students. Purposeful and theoretical sampling was conducted. Based on the method of Strauss and Corbin, the data were analyzed using fragmented, deep, and constant-comparative methods. The main categories included striving for growth and reduction of ambiguity, use of knowledge resources, dynamism of mind and social factors, converting knowledge, and creating knowledge. Knowledge was converted through mind processes, individual and group reflection, praxis and research, and resulted in the creation of nursing knowledge. Discrete nursing knowledge is gained through disconformity research in order to gain more individual advantages. The consequence of this analysis was gaining new knowledge. Knowledge management must be included in the mission and strategic planning of nursing education, and it should be planned through operational planning in order to create applicable knowledge. PMID:25716383

Enormous knowledge base of disease diagnosis criteria.

PubMed

Xiao, Z H; Xiao, Y H; Pei, J H

1995-01-01

One of the problems in the development of the medical knowledge systems is the limitations of the system's knowledge. It is a common expectation to increase the number of diseases contained in a system. Using a high density knowledge representation method designed by us, we have developed the Enormous Knowledge Base of Disease Diagnosis Criteria (EKBDDC). It contains diagnostic criteria of 1,001 diagnostic entities and describes nearly 4,000 items of diagnostic indicators. It is the core of a huge medical project--the Electronic-Brain Medical Erudite (EBME). This enormous knowledge base was implemented initially on a low-cost popular microcomputer, which can aid in the prompting of typical disease and in teaching of diagnosis. The knowledge base is easy to expand. One of the main goals of EKBDDC is to increase the number of diseases included in it as far as possible using a low-cost computer with a comparatively small storage capacity. For this, we have designed a high density knowledge representation method. Criteria of various diagnostic entities are respectively stored in different records of the knowledge base. Each diagnostic entity corresponds to a diagnostic criterion data set; each data set consists of some diagnostic criterion data values (Table 1); each data is composed of two parts: integer and decimal; the integral part is the coding number of the given diagnostic information, and the decimal part is the diagnostic value of this information to the disease indicated by corresponding record number. For example, 75.02: the integer 75 is the coding number of "hemorrhagic skin rash"; the decimal 0.02 is the diagnostic value of this manifestation for diagnosing allergic purpura. TABULAR DATA, SEE PUBLISHED ABSTRACT. The algebraic sum method, a special form of the weighted summation, is adopted as mathematical model. In EKBDDC, the diagnostic values, which represent the significance of the disease manifestations for diagnosing corresponding diseases, were determined empirically. It is of a great economical, practical, and technical significance to realize enormous knowledge bases of disease diagnosis criteria on a low-cost popular microcomputer. This is beneficial for the developing countries to popularize medical informatics. To create the enormous international computer-aided diagnosis system, one may jointly develop the unified modules of disease diagnosis criteria used to "inlay" relevant computer-aided diagnosis systems. It is just like assembling a house using prefabricated panels.

Innovative teaching methods for capacity building in knowledge translation

PubMed Central

2011-01-01

Background In some current healthcare settings, there is a noticeable absence of national institutions committed to the synthesis and use of evidence in healthcare decision- and policy-making. This absence creates a need to broaden the responsibilities of healthcare providers to include knowledge brokering and advocacy in order to optimize knowledge translation to other stakeholders, especially policy-makers. However, this process requires practitioners and researchers to acquire certain types of knowledge and skills. This article introduces two innovative methods for capacity building in knowledge translation (KT). Methods During a workshop aimed at preparing 21 trainers in evidence-based medicine, two innovative methods were used: (1) debate and (2) a knowledge translation project (KTP). The main objective of the debates approach was to strengthen participants' critical thinking abilities by requiring them to search for and appraise evidence and defend their arguments. The KTP was used to introduce participants to the essential steps of knowledge translation and to suggest an extended role for healthcare practitioners, i.e., using evidence to manage not only individual patients but also to a community of patients. Participants' performances were assessed according to a pre-designed scheme. At the end of the workshop, participants' opinions and experiences with the innovative teaching methods were evaluated based on their answers to a questionnaire and the results of small-group discussions. Results The participants performed well in both the debate and KTP methods. During post-workshop group discussions, they indicated that the debate approach had added a new dimension to their evidence-based medicine skills by adding purpose and motivation. However, they felt that their performances would have been better if they had been offered practical demonstrations of how to conduct the debate. The participants indicated that the KTP enhanced their understanding of the relationships between evidence and implementation, and motivated them to investigate public health problems in addition to individual patient problems. However, some participants maintained that these issues fell outside the scope of their role as doctors. Conclusion Debates and evidence implementation through KTP are generally well accepted by healthcare practitioners as methods by which they can improve their skills in KT. PMID:21999174

Method of Testing and Predicting Failures of Electronic Mechanical Systems

NASA Technical Reports Server (NTRS)

Iverson, David L.; Patterson-Hine, Frances A.

1996-01-01

A method employing a knowledge base of human expertise comprising a reliability model analysis implemented for diagnostic routines is disclosed. The reliability analysis comprises digraph models that determine target events created by hardware failures human actions, and other factors affecting the system operation. The reliability analysis contains a wealth of human expertise information that is used to build automatic diagnostic routines and which provides a knowledge base that can be used to solve other artificial intelligence problems.

Integrating clinicians, knowledge and data: expert-based cooperative analysis in healthcare decision support

PubMed Central

2010-01-01

Background Decision support in health systems is a highly difficult task, due to the inherent complexity of the process and structures involved. Method This paper introduces a new hybrid methodology Expert-based Cooperative Analysis (EbCA), which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge (IK) to improve decision support in healthcare systems. EbCA has been applied to two different case studies, showing its usability and versatility: 1) Bench-marking of small mental health areas based on technical efficiency estimated by EbCA-Data Envelopment Analysis (EbCA-DEA), and 2) Case-mix of schizophrenia based on functional dependency using Clustering Based on Rules (ClBR). In both cases comparisons towards classical procedures using qualitative explicit prior knowledge were made. Bayesian predictive validity measures were used for comparison with expert panels results. Overall agreement was tested by Intraclass Correlation Coefficient in case "1" and kappa in both cases. Results EbCA is a new methodology composed by 6 steps:. 1) Data collection and data preparation; 2) acquisition of "Prior Expert Knowledge" (PEK) and design of the "Prior Knowledge Base" (PKB); 3) PKB-guided analysis; 4) support-interpretation tools to evaluate results and detect inconsistencies (here Implicit Knowledg -IK- might be elicited); 5) incorporation of elicited IK in PKB and repeat till a satisfactory solution; 6) post-processing results for decision support. EbCA has been useful for incorporating PEK in two different analysis methods (DEA and Clustering), applied respectively to assess technical efficiency of small mental health areas and for case-mix of schizophrenia based on functional dependency. Differences in results obtained with classical approaches were mainly related to the IK which could be elicited by using EbCA and had major implications for the decision making in both cases. Discussion This paper presents EbCA and shows the convenience of completing classical data analysis with PEK as a mean to extract relevant knowledge in complex health domains. One of the major benefits of EbCA is iterative elicitation of IK.. Both explicit and tacit or implicit expert knowledge are critical to guide the scientific analysis of very complex decisional problems as those found in health system research. PMID:20920289

Constraint methods that accelerate free-energy simulations of biomolecules.

PubMed

Perez, Alberto; MacCallum, Justin L; Coutsias, Evangelos A; Dill, Ken A

2015-12-28

Atomistic molecular dynamics simulations of biomolecules are critical for generating narratives about biological mechanisms. The power of atomistic simulations is that these are physics-based methods that satisfy Boltzmann's law, so they can be used to compute populations, dynamics, and mechanisms. But physical simulations are computationally intensive and do not scale well to the sizes of many important biomolecules. One way to speed up physical simulations is by coarse-graining the potential function. Another way is to harness structural knowledge, often by imposing spring-like restraints. But harnessing external knowledge in physical simulations is problematic because knowledge, data, or hunches have errors, noise, and combinatoric uncertainties. Here, we review recent principled methods for imposing restraints to speed up physics-based molecular simulations that promise to scale to larger biomolecules and motions.

Enrichment assessment of multiple virtual screening strategies for Toll-like receptor 8 agonists based on a maximal unbiased benchmarking data set.

PubMed

Pei, Fen; Jin, Hongwei; Zhou, Xin; Xia, Jie; Sun, Lidan; Liu, Zhenming; Zhang, Liangren

2015-11-01

Toll-like receptor 8 agonists, which activate adaptive immune responses by inducing robust production of T-helper 1-polarizing cytokines, are promising candidates for vaccine adjuvants. As the binding site of toll-like receptor 8 is large and highly flexible, virtual screening by individual method has inevitable limitations; thus, a comprehensive comparison of different methods may provide insights into seeking effective strategy for the discovery of novel toll-like receptor 8 agonists. In this study, the performance of knowledge-based pharmacophore, shape-based 3D screening, and combined strategies was assessed against a maximum unbiased benchmarking data set containing 13 actives and 1302 decoys specialized for toll-like receptor 8 agonists. Prior structure-activity relationship knowledge was involved in knowledge-based pharmacophore generation, and a set of antagonists was innovatively used to verify the selectivity of the selected knowledge-based pharmacophore. The benchmarking data set was generated from our recently developed 'mubd-decoymaker' protocol. The enrichment assessment demonstrated a considerable performance through our selected three-layer virtual screening strategy: knowledge-based pharmacophore (Phar1) screening, shape-based 3D similarity search (Q4_combo), and then a Gold docking screening. This virtual screening strategy could be further employed to perform large-scale database screening and to discover novel toll-like receptor 8 agonists. © 2015 John Wiley & Sons A/S.

Diet and Colorectal Cancer Risk: Evaluation of a Nutrition Education Leaflet

ERIC Educational Resources Information Center

Dyer, K. J.; Fearon, K. C. H.; Buckner, K.; Richardson, R. A.

2005-01-01

Objective: To evaluate the effect of a needs-based, nutrition education leaflet on nutritional knowledge. Design: Comparison of nutritional knowledge levels before and after exposure to a nutrition education leaflet. Setting: A regional colorectal out-patient clinic in Edinburgh. Method: A nutrition education leaflet, based on an earlier…

Constructing Knowledge Bases: A Promising Instructional Tool.

ERIC Educational Resources Information Center

Trollip, Stanley R.; Lippert, Renate C.

1987-01-01

Argues that construction of knowledge bases is an instructional tool that encourages students' critical thinking in problem solving situations through metacognitive experiences. A study is described in which college students created expert systems to test the effectiveness of this method of instruction, and benefits for students and teachers are…

Ambulatory orthopaedic surgery patients' knowledge with internet-based education.

PubMed

Heikkinen, Katja; Leino-Kilpi, H; Salanterä, S

2012-01-01

There is a growing need for patient education and an evaluation of its outcomes. The aim of this study was to compare ambulatory orthopaedic surgery patients' knowledge with Internet-based education and face-to-face education with a nurse. The following hypothesis was proposed: Internet-based patient education (experiment) is as effective as face-to-face education with a nurse (control) in increasing patients' level of knowledge and sufficiency of knowledge. In addition, the correlations of demographic variables were tested. The patients were randomized to either an experiment group (n = 72) or a control group (n = 75). Empirical data were collected with two instruments. Patients in both groups showed improvement in their knowledge during their care. Patients in the experiment group improved their knowledge level significantly more in total than those patients in the control group. There were no differences in patients' sufficiency of knowledge between the groups. Knowledge was correlated especially with patients' age, gender and earlier ambulatory surgeries. As a conclusion, positive results concerning patients' knowledge could be achieved with the Internet-based education. The Internet is a viable method in ambulatory care.

A knowledge engineering taxonomy for intelligent tutoring system development

NASA Technical Reports Server (NTRS)

Fink, Pamela K.; Herren, L. Tandy

1993-01-01

This paper describes a study addressing the issue of developing an appropriate mapping of knowledge acquisition methods to problem types for intelligent tutoring system development. Recent research has recognized that knowledge acquisition methodologies are not general across problem domains; the effectiveness of a method for obtaining knowledge depends on the characteristics of the domain and problem solving task. Southwest Research Institute developed a taxonomy of problem types by evaluating the characteristics that discriminate between problems and grouping problems that share critical characteristics. Along with the problem taxonomy, heuristics that guide the knowledge acquisition process based on the characteristics of the class are provided.

Brain Tumor Segmentation Using Deep Belief Networks and Pathological Knowledge.

PubMed

Zhan, Tianming; Chen, Yi; Hong, Xunning; Lu, Zhenyu; Chen, Yunjie

2017-01-01

In this paper, we propose an automatic brain tumor segmentation method based on Deep Belief Networks (DBNs) and pathological knowledge. The proposed method is targeted against gliomas (both low and high grade) obtained in multi-sequence magnetic resonance images (MRIs). Firstly, a novel deep architecture is proposed to combine the multi-sequences intensities feature extraction with classification to get the classification probabilities of each voxel. Then, graph cut based optimization is executed on the classification probabilities to strengthen the spatial relationships of voxels. At last, pathological knowledge of gliomas is applied to remove some false positives. Our method was validated in the Brain Tumor Segmentation Challenge 2012 and 2013 databases (BRATS 2012, 2013). The performance of segmentation results demonstrates our proposal providing a competitive solution with stateof- the-art methods. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Formalization of the engineering science discipline - knowledge engineering

NASA Astrophysics Data System (ADS)

Peng, Xiao

Knowledge is the most precious ingredient facilitating aerospace engineering research and product development activities. Currently, the most common knowledge retention methods are paper-based documents, such as reports, books and journals. However, those media have innate weaknesses. For example, four generations of flying wing aircraft (Horten, Northrop XB-35/YB-49, Boeing BWB and many others) were mostly developed in isolation. The subsequent engineers were not aware of the previous developments, because these projects were documented such which prevented the next generation of engineers to benefit from the previous lessons learned. In this manner, inefficient knowledge retention methods have become a primary obstacle for knowledge transfer from the experienced to the next generation of engineers. In addition, the quality of knowledge itself is a vital criterion; thus, an accurate measure of the quality of 'knowledge' is required. Although qualitative knowledge evaluation criteria have been researched in other disciplines, such as the AAA criterion by Ernest Sosa stemming from the field of philosophy, a quantitative knowledge evaluation criterion needs to be developed which is capable to numerically determine the qualities of knowledge for aerospace engineering research and product development activities. To provide engineers with a high-quality knowledge management tool, the engineering science discipline Knowledge Engineering has been formalized to systematically address knowledge retention issues. This research undertaking formalizes Knowledge Engineering as follows: 1. Categorize knowledge according to its formats and representations for the first time, which serves as the foundation for the subsequent knowledge management function development. 2. Develop an efficiency evaluation criterion for knowledge management by analyzing the characteristics of both knowledge and the parties involved in the knowledge management processes. 3. Propose and develop an innovative Knowledge-Based System (KBS), AVD KBS, forming a systematic approach facilitating knowledge management. 4. Demonstrate the efficiency advantages of AVDKBS over traditional knowledge management methods via selected design case studies. This research formalizes, for the first time, Knowledge Engineering as a distinct discipline by delivering a robust and high-quality knowledge management and process tool, AVDKBS. Formalizing knowledge proves to significantly impact the effectiveness of aerospace knowledge retention and utilization.

Creative design inspired by biological knowledge: Technologies and methods

NASA Astrophysics Data System (ADS)

Tan, Runhua; Liu, Wei; Cao, Guozhong; Shi, Yuan

2018-05-01

Biological knowledge is becoming an important source of inspiration for developing creative solutions to engineering design problems and even has a huge potential in formulating ideas that can help firms compete successfully in a dynamic market. To identify the technologies and methods that can facilitate the development of biologically inspired creative designs, this research briefly reviews the existing biological-knowledge-based theories and methods and examines the application of biological-knowledge-inspired designs in various fields. Afterward, this research thoroughly examines the four dimensions of key technologies that underlie the biologically inspired design (BID) process. This research then discusses the future development trends of the BID process before presenting the conclusions.

A Study Combining Criticism and Qualitative Research Techniques for Appraising Classroom Media.

ERIC Educational Resources Information Center

Swartz, James D.

Qualitative criticism is a method of understanding things, actions, and events within a social framework. It is a method of acquiring knowledge to guide decision making based on local knowledge and a synthesis of principles from criticism and qualitative research. The function of qualitative criticism is centered with Richard Rorty's theoretical…

Does Project-Based Learning Enhance Iranian EFL Learners' Vocabulary Recall and Retention?

ERIC Educational Resources Information Center

Shafaei, Azadeh; Rahim, Hajar Abdul

2015-01-01

Vocabulary knowledge is an integral part of second/foreign language learning. Thus, using teaching methods that can help learners retain and expand their vocabulary knowledge is necessary to facilitate the language learning process. The current research investigated the effectiveness of an interactive classroom method, known as Project-Based…

Biomedical discovery acceleration, with applications to craniofacial development.

PubMed

Leach, Sonia M; Tipney, Hannah; Feng, Weiguo; Baumgartner, William A; Kasliwal, Priyanka; Schuyler, Ronald P; Williams, Trevor; Spritz, Richard A; Hunter, Lawrence

2009-03-01

The profusion of high-throughput instruments and the explosion of new results in the scientific literature, particularly in molecular biomedicine, is both a blessing and a curse to the bench researcher. Even knowledgeable and experienced scientists can benefit from computational tools that help navigate this vast and rapidly evolving terrain. In this paper, we describe a novel computational approach to this challenge, a knowledge-based system that combines reading, reasoning, and reporting methods to facilitate analysis of experimental data. Reading methods extract information from external resources, either by parsing structured data or using biomedical language processing to extract information from unstructured data, and track knowledge provenance. Reasoning methods enrich the knowledge that results from reading by, for example, noting two genes that are annotated to the same ontology term or database entry. Reasoning is also used to combine all sources into a knowledge network that represents the integration of all sorts of relationships between a pair of genes, and to calculate a combined reliability score. Reporting methods combine the knowledge network with a congruent network constructed from experimental data and visualize the combined network in a tool that facilitates the knowledge-based analysis of that data. An implementation of this approach, called the Hanalyzer, is demonstrated on a large-scale gene expression array dataset relevant to craniofacial development. The use of the tool was critical in the creation of hypotheses regarding the roles of four genes never previously characterized as involved in craniofacial development; each of these hypotheses was validated by further experimental work.

Contraceptive knowledge, perceptions, and concerns among men in Uganda.

PubMed

Thummalachetty, Nityanjali; Mathur, Sanyukta; Mullinax, Margo; DeCosta, Kelsea; Nakyanjo, Neema; Lutalo, Tom; Brahmbhatt, Heena; Santelli, John S

2017-10-10

Low contraceptive uptake and high unmet need for contraception remain significant issues in Uganda compared to neighboring countries such as Kenya, Ethiopia, and Rwanda. Although prior research on contraceptive uptake has indicated that male partners strongly influence women's decisions around contraceptive use, there is limited in-depth qualitative research on knowledge and concerns regarding modern contraceptive methods among Ugandan men. Using in-depth interviews (N = 41), this qualitative study investigated major sources of knowledge about contraception and perceptions of contraceptive side effects among married Ugandan men. Men primarily reported knowledge of contraceptives based on partner's experience of side effects, partner's knowledge from health providers and mass media campaigns, and partner's knowledge from her peers. Men were less likely to report contraceptive knowledge from health care providers, mass media campaigns, or peers. Men's concerns about various contraceptive methods were broadly associated with failure of the method to work properly, adverse health effects on women, and severe adverse health effects on children. Own or partner's human immunodeficiency virus (HIV) status did not impact on contraceptive knowledge. Overall, we found limited accurate knowledge about contraceptive methods among men in Uganda. Moreover, fears about the side effects of modern contraceptive methods appeared to be common among men. Family planning services in Uganda could be significantly strengthened by renewed efforts to focus on men's knowledge, fears, and misconceptions.

Towards a Semantic Web of Things: A Hybrid Semantic Annotation, Extraction, and Reasoning Framework for Cyber-Physical System.

PubMed

Wu, Zhenyu; Xu, Yuan; Yang, Yunong; Zhang, Chunhong; Zhu, Xinning; Ji, Yang

2017-02-20

Web of Things (WoT) facilitates the discovery and interoperability of Internet of Things (IoT) devices in a cyber-physical system (CPS). Moreover, a uniform knowledge representation of physical resources is quite necessary for further composition, collaboration, and decision-making process in CPS. Though several efforts have integrated semantics with WoT, such as knowledge engineering methods based on semantic sensor networks (SSN), it still could not represent the complex relationships between devices when dynamic composition and collaboration occur, and it totally depends on manual construction of a knowledge base with low scalability. In this paper, to addresses these limitations, we propose the semantic Web of Things (SWoT) framework for CPS (SWoT4CPS). SWoT4CPS provides a hybrid solution with both ontological engineering methods by extending SSN and machine learning methods based on an entity linking (EL) model. To testify to the feasibility and performance, we demonstrate the framework by implementing a temperature anomaly diagnosis and automatic control use case in a building automation system. Evaluation results on the EL method show that linking domain knowledge to DBpedia has a relative high accuracy and the time complexity is at a tolerant level. Advantages and disadvantages of SWoT4CPS with future work are also discussed.

Effective domain-dependent reuse in medical knowledge bases.

PubMed

Dojat, M; Pachet, F

1995-12-01

Knowledge reuse is now a critical issue for most developers of medical knowledge-based systems. As a rule, reuse is addressed from an ambitious, knowledge-engineering perspective that focuses on reusable general purpose knowledge modules, concepts, and methods. However, such a general goal fails to take into account the specific aspects of medical practice. From the point of view of the knowledge engineer, whose goal is to capture the specific features and intricacies of a given domain, this approach addresses the wrong level of generality. In this paper, we adopt a more pragmatic viewpoint, introducing the less ambitious goal of "domain-dependent limited reuse" and suggesting effective means of achieving it in practice. In a knowledge representation framework combining objects and production rules, we propose three mechanisms emerging from the combination of object-oriented programming and rule-based programming. We show these mechanisms contribute to achieve limited reuse and to introduce useful limited variations in medical expertise.

Validation of a Crowdsourcing Methodology for Developing a Knowledge Base of Related Problem-Medication Pairs

PubMed Central

Wright, A.; Krousel-Wood, M.; Thomas, E. J.; McCoy, J. A.; Sittig, D. F.

2015-01-01

Summary Background Clinical knowledge bases of problem-medication pairs are necessary for many informatics solutions that improve patient safety, such as clinical summarization. However, developing these knowledge bases can be challenging. Objective We sought to validate a previously developed crowdsourcing approach for generating a knowledge base of problem-medication pairs in a large, non-university health care system with a widely used, commercially available electronic health record. Methods We first retrieved medications and problems entered in the electronic health record by clinicians during routine care during a six month study period. Following the previously published approach, we calculated the link frequency and link ratio for each pair then identified a threshold cutoff for estimated problem-medication pair appropriateness through clinician review; problem-medication pairs meeting the threshold were included in the resulting knowledge base. We selected 50 medications and their gold standard indications to compare the resulting knowledge base to the pilot knowledge base developed previously and determine its recall and precision. Results The resulting knowledge base contained 26,912 pairs, had a recall of 62.3% and a precision of 87.5%, and outperformed the pilot knowledge base containing 11,167 pairs from the previous study, which had a recall of 46.9% and a precision of 83.3%. Conclusions We validated the crowdsourcing approach for generating a knowledge base of problem-medication pairs in a large non-university health care system with a widely used, commercially available electronic health record, indicating that the approach may be generalizable across healthcare settings and clinical systems. Further research is necessary to better evaluate the knowledge, to compare crowdsourcing with other approaches, and to evaluate if incorporating the knowledge into electronic health records improves patient outcomes. PMID:26171079

Knowledge representation by connection matrices: A method for the on-board implementation of large expert systems

NASA Technical Reports Server (NTRS)

Kellner, A.

1987-01-01

Extremely large knowledge sources and efficient knowledge access characterizing future real-life artificial intelligence applications represent crucial requirements for on-board artificial intelligence systems due to obvious computer time and storage constraints on spacecraft. A type of knowledge representation and corresponding reasoning mechanism is proposed which is particularly suited for the efficient processing of such large knowledge bases in expert systems.

Validation of highly reliable, real-time knowledge-based systems

NASA Technical Reports Server (NTRS)

Johnson, Sally C.

1988-01-01

Knowledge-based systems have the potential to greatly increase the capabilities of future aircraft and spacecraft and to significantly reduce support manpower needed for the space station and other space missions. However, a credible validation methodology must be developed before knowledge-based systems can be used for life- or mission-critical applications. Experience with conventional software has shown that the use of good software engineering techniques and static analysis tools can greatly reduce the time needed for testing and simulation of a system. Since exhaustive testing is infeasible, reliability must be built into the software during the design and implementation phases. Unfortunately, many of the software engineering techniques and tools used for conventional software are of little use in the development of knowledge-based systems. Therefore, research at Langley is focused on developing a set of guidelines, methods, and prototype validation tools for building highly reliable, knowledge-based systems. The use of a comprehensive methodology for building highly reliable, knowledge-based systems should significantly decrease the time needed for testing and simulation. A proven record of delivering reliable systems at the beginning of the highly visible testing and simulation phases is crucial to the acceptance of knowledge-based systems in critical applications.

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.

A quality of care issue: appropriate use and efficacy knowledge of five contraceptive methods: views of men and women living in low socioeconomic settlements of Karachi, Pakistan.

PubMed

Fikree, Fariyal F; Saleem, Sarah; Sami, Neelofar

2005-09-01

To assess knowledge regarding availability, affordability, appropriate use and efficacy for five non-permanent contraceptive methods. Married Muslim women and men (500 each) were randomly selected from two low socioeconomic settlements in Karachi, Pakistan. Interviews to assess their knowledge on a range of contraceptive and abortion themes were conducted. Four hundred men and 357 women were selected from this larger sample based on their knowledge of condoms, withdrawal, oral pills, injectables and IUDs. Nearly half of the sampled men (56%) and women (48%) were contraceptive users. Knowledge regarding contraception, a specific method, its availability and affordability was high. Appropriate use knowledge for condoms was 73% among men (users 78%, non-users 60%; p-value < or = 0.001 ) and 5% among women. Efficacy knowledge was generally poor. Low knowledge levels regarding appropriate use and efficacy even among contraceptive users suggests, that quality of family planning services should not be limited to service delivery issues but extend to appropriate use and efficacy knowledge levels among clients.

Information Sharing and Knowledge Sharing as Communicative Activities

ERIC Educational Resources Information Center

Savolainen, Reijo

2017-01-01

Introduction: This paper elaborates the picture of information sharing and knowledge sharing as forms of communicative activity. Method: A conceptual analysis was made to find out how researchers have approached information sharing and knowledge sharing from the perspectives of transmission and ritual. The findings are based on the analysis of one…

UK medical selection: lottery or meritocracy?

PubMed

Harris, Benjamin H L; Walsh, Jason L; Lammy, Simon

2015-02-01

From senior school through to consultancy, a plethora of assessments shape medical careers. Multiple methods of assessment are used to discriminate between applicants. Medical selection in the UK appears to be moving increasingly towards non-knowledge-based testing at all career stages. We review the evidence for non-knowledge-based tests and discuss their perceived benefits. We raise the question: is the current use of non-knowledge-based tests within the UK at risk of undermining more robust measures of medical school and postgraduate performance? © 2015 Royal College of Physicians.

Towards building a disease-phenotype knowledge base: extracting disease-manifestation relationship from literature

PubMed Central

Xu, Rong; Li, Li; Wang, QuanQiu

2013-01-01

Motivation: Systems approaches to studying phenotypic relationships among diseases are emerging as an active area of research for both novel disease gene discovery and drug repurposing. Currently, systematic study of disease phenotypic relationships on a phenome-wide scale is limited because large-scale machine-understandable disease–phenotype relationship knowledge bases are often unavailable. Here, we present an automatic approach to extract disease–manifestation (D-M) pairs (one specific type of disease–phenotype relationship) from the wide body of published biomedical literature. Data and Methods: Our method leverages external knowledge and limits the amount of human effort required. For the text corpus, we used 119 085 682 MEDLINE sentences (21 354 075 citations). First, we used D-M pairs from existing biomedical ontologies as prior knowledge to automatically discover D-M–specific syntactic patterns. We then extracted additional pairs from MEDLINE using the learned patterns. Finally, we analysed correlations between disease manifestations and disease-associated genes and drugs to demonstrate the potential of this newly created knowledge base in disease gene discovery and drug repurposing. Results: In total, we extracted 121 359 unique D-M pairs with a high precision of 0.924. Among the extracted pairs, 120 419 (99.2%) have not been captured in existing structured knowledge sources. We have shown that disease manifestations correlate positively with both disease-associated genes and drug treatments. Conclusions: The main contribution of our study is the creation of a large-scale and accurate D-M phenotype relationship knowledge base. This unique knowledge base, when combined with existing phenotypic, genetic and proteomic datasets, can have profound implications in our deeper understanding of disease etiology and in rapid drug repurposing. Availability: http://nlp.case.edu/public/data/DMPatternUMLS/ Contact: rxx@case.edu PMID:23828786

Lessons learned from participating in D3R 2016 Grand Challenge 2: compounds targeting the farnesoid X receptor

NASA Astrophysics Data System (ADS)

Duan, Rui; Xu, Xianjin; Zou, Xiaoqin

2018-01-01

D3R 2016 Grand Challenge 2 focused on predictions of binding modes and affinities for 102 compounds against the farnesoid X receptor (FXR). In this challenge, two distinct methods, a docking-based method and a template-based method, were employed by our team for the binding mode prediction. For the new template-based method, 3D ligand similarities were calculated for each query compound against the ligands in the co-crystal structures of FXR available in Protein Data Bank. The binding mode was predicted based on the co-crystal protein structure containing the ligand with the best ligand similarity score against the query compound. For the FXR dataset, the template-based method achieved a better performance than the docking-based method on the binding mode prediction. For the binding affinity prediction, an in-house knowledge-based scoring function ITScore2 and MM/PBSA approach were employed. Good performance was achieved for MM/PBSA, whereas the performance of ITScore2 was sensitive to ligand composition, e.g. the percentage of carbon atoms in the compounds. The sensitivity to ligand composition could be a clue for the further improvement of our knowledge-based scoring function.

n-Gram-Based Indexing for Korean Text Retrieval.

ERIC Educational Resources Information Center

Lee, Joon Ho; Cho, Hyun Yang; Park, Hyouk Ro

1999-01-01

Discusses indexing methods in Korean text retrieval and proposes a new indexing method based on n-grams which can handle compound nouns effectively without dictionaries and complex linguistic knowledge. Experimental results show that n-gram-based indexing is considerably faster than morpheme-based indexing, and also provides better retrieval…

ESTIMATION OF THE RATE OF VOC EMISSIONS FROM SOLVENT-BASED INDOOR COATING MATERIALS BASED ON PRODUCT FORMULATION

EPA Science Inventory

Two computational methods are proposed for estimation of the emission rate of volatile organic compounds (VOCs) from solvent-based indoor coating materials based on the knowledge of product formulation. The first method utilizes two previously developed mass transfer models with ...

Research on the construction of three level customer service knowledge graph

NASA Astrophysics Data System (ADS)

Cheng, Shi; Shen, Jiajie; Shi, Quan; Cheng, Xianyi

2017-09-01

With the explosion of knowledge and information of the enterprise and the growing demand for intelligent knowledge management and application and improve business performance the knowledge expression and processing of the enterprise has become a hot topic. Aim at the problems of the electric marketing customer service knowledge map (customer service knowledge map) in building theory and method, electric marketing knowledge map of three levels of customer service was discussed, and realizing knowledge reasoning based on Neo4j, achieve good results in practical application.

Fault diagnosis of sensor networked structures with multiple faults using a virtual beam based approach

NASA Astrophysics Data System (ADS)

Wang, H.; Jing, X. J.

2017-07-01

This paper presents a virtual beam based approach suitable for conducting diagnosis of multiple faults in complex structures with limited prior knowledge of the faults involved. The "virtual beam", a recently-proposed concept for fault detection in complex structures, is applied, which consists of a chain of sensors representing a vibration energy transmission path embedded in the complex structure. Statistical tests and adaptive threshold are particularly adopted for fault detection due to limited prior knowledge of normal operational conditions and fault conditions. To isolate the multiple faults within a specific structure or substructure of a more complex one, a 'biased running' strategy is developed and embedded within the bacterial-based optimization method to construct effective virtual beams and thus to improve the accuracy of localization. The proposed method is easy and efficient to implement for multiple fault localization with limited prior knowledge of normal conditions and faults. With extensive experimental results, it is validated that the proposed method can localize both single fault and multiple faults more effectively than the classical trust index subtract on negative add on positive (TI-SNAP) method.

CACTUS: Command and Control Training Using Knowledge-Based Simulations

ERIC Educational Resources Information Center

Hartley, Roger; Ravenscroft, Andrew; Williams, R. J.

2008-01-01

The CACTUS project was concerned with command and control training of large incidents where public order may be at risk, such as large demonstrations and marches. The training requirements and objectives of the project are first summarized justifying the use of knowledge-based computer methods to support and extend conventional training…

Teachers' Knowledge and Understanding of the Malaysian School-Based Oral English Assessment

ERIC Educational Resources Information Center

Sidhu, Gurnam Kaur; Fook, Chan Yuen; Mohamad, Azleena

2011-01-01

Purpose: The paper sought to investigate TESL teachers' knowledge and understanding of the Malaysian School Based Oral English Assessment (SBOEA) after five years into its implementation in upper secondary ESL classrooms in Malaysian public schools Method: The descriptive study involved a total of 80 TESL trained teachers from the 19 schools…

Innovative teaching methods for capacity building in knowledge translation.

PubMed

Wahabi, Hayfaa A; Al-Ansary, Lubna A

2011-10-14

In some current healthcare settings, there is a noticeable absence of national institutions committed to the synthesis and use of evidence in healthcare decision- and policy-making. This absence creates a need to broaden the responsibilities of healthcare providers to include knowledge brokering and advocacy in order to optimize knowledge translation to other stakeholders, especially policy-makers. However, this process requires practitioners and researchers to acquire certain types of knowledge and skills. This article introduces two innovative methods for capacity building in knowledge translation (KT). During a workshop aimed at preparing 21 trainers in evidence-based medicine, two innovative methods were used: (1) debate and (2) a knowledge translation project (KTP). The main objective of the debates approach was to strengthen participants' critical thinking abilities by requiring them to search for and appraise evidence and defend their arguments. The KTP was used to introduce participants to the essential steps of knowledge translation and to suggest an extended role for healthcare practitioners, i.e., using evidence to manage not only individual patients but also to a community of patients. Participants' performances were assessed according to a pre-designed scheme. At the end of the workshop, participants' opinions and experiences with the innovative teaching methods were evaluated based on their answers to a questionnaire and the results of small-group discussions. The participants performed well in both the debate and KTP methods. During post-workshop group discussions, they indicated that the debate approach had added a new dimension to their evidence-based medicine skills by adding purpose and motivation. However, they felt that their performances would have been better if they had been offered practical demonstrations of how to conduct the debate. The participants indicated that the KTP enhanced their understanding of the relationships between evidence and implementation, and motivated them to investigate public health problems in addition to individual patient problems. However, some participants maintained that these issues fell outside the scope of their role as doctors. Debates and evidence implementation through KTP are generally well accepted by healthcare practitioners as methods by which they can improve their skills in KT.

Testing an Adapted Modified Delphi Method: Synthesizing Multiple Stakeholder Ratings of Health Care Service Effectiveness.

PubMed

Escaron, Anne L; Chang Weir, Rosy; Stanton, Petra; Vangala, Sitaram; Grogan, Tristan R; Clarke, Robin M

2016-03-01

The Affordable Care Act incentivizes health systems for better meeting patient needs, but often guidance about patient preferences for particular health services is limited. All too often vulnerable patient populations are excluded from these decision-making settings. A community-based participatory approach harnesses the in-depth knowledge of those experiencing barriers to health care. We made three modifications to the RAND-UCLA appropriateness method, a modified Delphi approach, involving patients, adding an advisory council group to characterize existing knowledge in this little studied area, and using effectiveness rather than "appropriateness" as the basis for rating. As a proof of concept, we tested this method by examining the broadly delivered but understudied nonmedical services that community health centers provide. This method created discrete, new knowledge about these services by defining 6 categories and 112 unique services and by prioritizing among these services based on effectiveness using a 9-point scale. Consistent with the appropriateness method, we found statistical convergence of ratings among the panelists. Challenges include time commitment and adherence to a clear definition of effectiveness of services. This diverse stakeholder engagement method efficiently addresses gaps in knowledge about the effectiveness of health care services to inform population health management. © 2015 Society for Public Health Education.

Rule Extracting based on MCG with its Application in Helicopter Power Train Fault Diagnosis

NASA Astrophysics Data System (ADS)

Wang, M.; Hu, N. Q.; Qin, G. J.

2011-07-01

In order to extract decision rules for fault diagnosis from incomplete historical test records for knowledge-based damage assessment of helicopter power train structure. A method that can directly extract the optimal generalized decision rules from incomplete information based on GrC was proposed. Based on semantic analysis of unknown attribute value, the granule was extended to handle incomplete information. Maximum characteristic granule (MCG) was defined based on characteristic relation, and MCG was used to construct the resolution function matrix. The optimal general decision rule was introduced, with the basic equivalent forms of propositional logic, the rules were extracted and reduction from incomplete information table. Combined with a fault diagnosis example of power train, the application approach of the method was present, and the validity of this method in knowledge acquisition was proved.

Addressing the translational dilemma: dynamic knowledge representation of inflammation using agent-based modeling.

PubMed

An, Gary; Christley, Scott

2012-01-01

Given the panoply of system-level diseases that result from disordered inflammation, such as sepsis, atherosclerosis, cancer, and autoimmune disorders, understanding and characterizing the inflammatory response is a key target of biomedical research. Untangling the complex behavioral configurations associated with a process as ubiquitous as inflammation represents a prototype of the translational dilemma: the ability to translate mechanistic knowledge into effective therapeutics. A critical failure point in the current research environment is a throughput bottleneck at the level of evaluating hypotheses of mechanistic causality; these hypotheses represent the key step toward the application of knowledge for therapy development and design. Addressing the translational dilemma will require utilizing the ever-increasing power of computers and computational modeling to increase the efficiency of the scientific method in the identification and evaluation of hypotheses of mechanistic causality. More specifically, development needs to focus on facilitating the ability of non-computer trained biomedical researchers to utilize and instantiate their knowledge in dynamic computational models. This is termed "dynamic knowledge representation." Agent-based modeling is an object-oriented, discrete-event, rule-based simulation method that is well suited for biomedical dynamic knowledge representation. Agent-based modeling has been used in the study of inflammation at multiple scales. The ability of agent-based modeling to encompass multiple scales of biological process as well as spatial considerations, coupled with an intuitive modeling paradigm, suggest that this modeling framework is well suited for addressing the translational dilemma. This review describes agent-based modeling, gives examples of its applications in the study of inflammation, and introduces a proposed general expansion of the use of modeling and simulation to augment the generation and evaluation of knowledge by the biomedical research community at large.

GPs’ thoughts on prescribing medication and evidence-based knowledge: The benefit aspect is a strong motivator

PubMed Central

Skoglund, Ingmarie; Segesten, Kerstin; Björkelund, Cecilia

2007-01-01

Objective To describe GPs’ thoughts of prescribing medication and evidence-based knowledge (EBM) concerning drug therapy. Design Tape-recorded focus-group interviews transcribed verbatim and analysed using qualitative methods. Setting GPs from the south-eastern part of Västra Götaland, Sweden. Subjects A total of 16 GPs out of 178 from the south-eastern part of the region strategically chosen to represent urban and rural, male and female, long and short GP experience. Methods Transcripts were analysed using a descriptive qualitative method. Results The categories were: benefits, time and space, and expert knowledge. The benefit was a merge of positive elements, all aspects of the GPs’ tasks. Time and space were limitations for GPs’ tasks. EBM as a constituent of expert knowledge should be more customer adjusted to be able to be used in practice. Benefit was the most important category, existing in every decision-making situation for the GP. The core category was prompt and pragmatic benefit, which was the utmost benefit. Conclusion GPs’ thoughts on evidence-based medicine and prescribing medication were highly related to reflecting on benefit and results. The interviews indicated that prompt and pragmatic benefit is important for comprehending their thoughts. PMID:17497487

Design and Implementation of Hydrologic Process Knowledge-base Ontology: A case study for the Infiltration Process

NASA Astrophysics Data System (ADS)

Elag, M.; Goodall, J. L.

2013-12-01

Hydrologic modeling often requires the re-use and integration of models from different disciplines to simulate complex environmental systems. Component-based modeling introduces a flexible approach for integrating physical-based processes across disciplinary boundaries. Several hydrologic-related modeling communities have adopted the component-based approach for simulating complex physical systems by integrating model components across disciplinary boundaries in a workflow. However, it is not always straightforward to create these interdisciplinary models due to the lack of sufficient knowledge about a hydrologic process. This shortcoming is a result of using informal methods for organizing and sharing information about a hydrologic process. A knowledge-based ontology provides such standards and is considered the ideal approach for overcoming this challenge. The aims of this research are to present the methodology used in analyzing the basic hydrologic domain in order to identify hydrologic processes, the ontology itself, and how the proposed ontology is integrated with the Water Resources Component (WRC) ontology. The proposed ontology standardizes the definitions of a hydrologic process, the relationships between hydrologic processes, and their associated scientific equations. The objective of the proposed Hydrologic Process (HP) Ontology is to advance the idea of creating a unified knowledge framework for components' metadata by introducing a domain-level ontology for hydrologic processes. The HP ontology is a step toward an explicit and robust domain knowledge framework that can be evolved through the contribution of domain users. Analysis of the hydrologic domain is accomplished using the Formal Concept Approach (FCA), in which the infiltration process, an important hydrologic process, is examined. Two infiltration methods, the Green-Ampt and Philip's methods, were used to demonstrate the implementation of information in the HP ontology. Furthermore, a SPARQL service is provided for semantic-based querying of the ontology.

Rule-based mechanisms of learning for intelligent adaptive flight control

NASA Technical Reports Server (NTRS)

Handelman, David A.; Stengel, Robert F.

1990-01-01

How certain aspects of human learning can be used to characterize learning in intelligent adaptive control systems is investigated. Reflexive and declarative memory and learning are described. It is shown that model-based systems-theoretic adaptive control methods exhibit attributes of reflexive learning, whereas the problem-solving capabilities of knowledge-based systems of artificial intelligence are naturally suited for implementing declarative learning. Issues related to learning in knowledge-based control systems are addressed, with particular attention given to rule-based systems. A mechanism for real-time rule-based knowledge acquisition is suggested, and utilization of this mechanism within the context of failure diagnosis for fault-tolerant flight control is demonstrated.

Impact of school-based educational programs on sexual behaviors among adolescents in northern Italy.

PubMed

Bogani, Giorgio; Cromi, Antonella; Serati, Maurizio; Monti, Zelia; Apolloni, Chiara; Nardelli, Federica; Di Naro, Edoardo; Ghezzi, Fabio

2015-01-01

This article aimed to determine sexual behaviors among female and male adolescents in northern Italy. An anonymous self-administered questionnaire evaluating sexual attitudes was distributed in middle and high schools in northern Italy. Adolescents between 13 and 19 years of age were asked to participate at the survey. The study group included 664 participants. Overall, 164 (25%) adolescents had had at least one sexual intercourse. Among adolescents who have had sexual intercourse, 90 (55%) use condoms, 25 (15%) use hormonal contraception, and 49 (30%) do not use any contraception method. A total of 559 adolescents (84%) participated in school-based sexual education programs. This group had better knowledge on sexually transmitted diseases and contraception methods in comparison with adolescents who have never participated in such educational programs (p <.05), and no difference in high-risk sexual behaviors was observed (p = 1.0). School-based sexual education programs improve knowledge of sexual transmitted diseases and contraception methods. However, this knowledge does not correlate to high-risk sexual behaviors reduction.

Comparison of Electronic Learning Versus Lecture-based Learning in Improving Emergency Medicine Residents' Knowledge About Mild Induced Hypothermia After Cardiac Arrest.

PubMed

Soleimanpour, Maryam; Rahmani, Farzad; Naghizadeh Golzari, Mehrad; Ala, Alireza; Morteza Bagi, Hamid Reza; Mehdizadeh Esfanjani, Robab; Soleimanpour, Hassan

2017-08-01

The process of medical education depends on several issues such as training materials, students, professors, educational fields, and the applied technologies. The current study aimed at comparing the impacts of e-learning and lecture-based learning of mild induced hypothermia (MIH) after cardiac arrest on the increase of knowledge among emergency medicine residents. In a pre- and post-intervention study, MIH after cardiac arrest was taught to 44 emergency medicine residents. Residents were randomly divided into 2 groups. The first group included 21 participants (lecture-based learning) and the second had 23 participants (e-learning). A 19-item questionnaire with approved validity and reliability was employed as the pretest and posttest. Then, data were analyzed with SPSS software version 17.0. There was no statistically significant difference in terms of the learning method between the test scores of the 2 groups (P = 0.977). E-learning and lecture-based learning methods was effective in augmentation of residents of emergency medicine knowledge about MIH after cardiac arrest; nevertheless, there was no significant difference between these mentioned methods.

An empirically based model for knowledge management in health care organizations.

PubMed

Sibbald, Shannon L; Wathen, C Nadine; Kothari, Anita

2016-01-01

Knowledge management (KM) encompasses strategies, processes, and practices that allow an organization to capture, share, store, access, and use knowledge. Ideal KM combines different sources of knowledge to support innovation and improve performance. Despite the importance of KM in health care organizations (HCOs), there has been very little empirical research to describe KM in this context. This study explores KM in HCOs, focusing on the status of current intraorganizational KM. The intention is to provide insight for future studies and model development for effective KM implementation in HCOs. A qualitative methods approach was used to create an empirically based model of KM in HCOs. Methods included (a) qualitative interviews (n = 24) with senior leadership to identify types of knowledge important in these roles plus current information-seeking behaviors/needs and (b) in-depth case study with leaders in new executive positions (n = 2). The data were collected from 10 HCOs. Our empirically based model for KM was assessed for face and content validity. The findings highlight the paucity of formal KM in our sample HCOs. Organizational culture, leadership, and resources are instrumental in supporting KM processes. An executive's knowledge needs are extensive, but knowledge assets are often limited or difficult to acquire as much of the available information is not in a usable format. We propose an empirically based model for KM to highlight the importance of context (internal and external), and knowledge seeking, synthesis, sharing, and organization. Participants who reviewed the model supported its basic components and processes, and potential for incorporating KM into organizational processes. Our results articulate ways to improve KM, increase organizational learning, and support evidence-informed decision-making. This research has implications for how to better integrate evidence and knowledge into organizations while considering context and the role of organizational processes.

Does an outcome-based approach to continuing medical education improve physicians' competences in rational prescribing?

PubMed

Esmaily, Hamideh M; Savage, Carl; Vahidi, Rezagoli; Amini, Abolghasem; Dastgiri, Saeed; Hult, Hakan; Dahlgren, Lars Owe; Wahlstrom, Rolf

2009-11-01

Continuing medical education (CME) is compulsory in Iran, and traditionally it is lecture-based, which is mostly not successful. Outcome-based education has been proposed for CME programs. To evaluate the effectiveness of an outcome-based educational intervention with a new approach based on outcomes and aligned teaching methods, on knowledge and skills of general physicians (GPs) working in primary care compared with a concurrent CME program in the field of "Rational prescribing". The method used was cluster randomized controlled design. All GPs working in six cities in one province in Iran were invited to participate. The cities were matched and randomly divided into an intervention arm for education on rational prescribing with an outcome-based approach, and a control arm for a traditional program on the same topic. Knowledge and skills were assessed using a pre- and post-test, including case scenarios. In total, 112 GPs participated. There were significant improvements in knowledge and prescribing skills after the training in the intervention arm as well as in comparison with the changes in the control arm. The overall intervention effect was 26 percentage units. The introduction of an outcome-based approach in CME appears to be effective when creating programs to improve GPs' knowledge and skills.

Introduction of vertical integration and case-based learning in anatomy for undergraduate physical therapy and occupational therapy students.

PubMed

Parmar, Suresh K; Rathinam, Bertha A D

2011-01-01

The purpose of the present pilot study was to evaluate the benefits of innovative teaching methodologies introduced to final year occupational and physical therapy students in Christian Medical College in India. Students' satisfactions along the long-term retention of knowledge and clinical application of the respiratory anatomy have been assessed. The final year undergraduate physical therapy and occupational therapy students had respiratory anatomy teaching over two sessions. The teaching involved case-based learning and integrated anatomy lectures (vertical integration) with the Anatomy department. Pretest and immediate and follow-up post-tests were conducted to assess the effectiveness of the innovative methods. A feedback questionnaire was marked to grade case-based learning. The method of integrated and case-based teaching was appreciated and found to be useful in imparting knowledge to the students. Students retained the gained knowledge adequately and the same was inferred by statistically significant improvement in both post-test scores. Vertical integration of anatomy in the final year reinforces their existing knowledge of anatomy. Case-based learning may facilitate the development of effective and clinically sound therapists. Copyright © 2011 American Association of Anatomists.

Bridging the gap: simulations meet knowledge bases

NASA Astrophysics Data System (ADS)

King, Gary W.; Morrison, Clayton T.; Westbrook, David L.; Cohen, Paul R.

2003-09-01

Tapir and Krill are declarative languages for specifying actions and agents, respectively, that can be executed in simulation. As such, they bridge the gap between strictly declarative knowledge bases and strictly executable code. Tapir and Krill components can be combined to produce models of activity which can answer questions about mechanisms and processes using conventional inference methods and simulation. Tapir was used in DARPA's Rapid Knowledge Formation (RKF) project to construct models of military tactics from the Army Field Manual FM3-90. These were then used to build Courses of Actions (COAs) which could be critiqued by declarative reasoning or via Monte Carlo simulation. Tapir and Krill can be read and written by non-knowledge engineers making it an excellent vehicle for Subject Matter Experts to build and critique knowledge bases.

Impact of an Online Medical Internet Site on Knowledge and Practice of Health Care Providers: A Mixed Methods Study of the Spinal Cord Injury Rehabilitation Evidence Project

PubMed Central

Noonan, Vanessa K; Townson, Andrea F; Higgins, Caroline E; Rogers, Jess; Wolfe, Dalton L

2014-01-01

Background It is not known whether ongoing access to a broad-based Internet knowledge resource can influence the practice of health care providers. We undertook a study to evaluate the impact of a Web-based knowledge resource on increasing access to evidence and facilitating best practice of health care providers. Objective The objective of this study was to evaluate (1) the impact of the Spinal Cord Injury Rehabilitation Evidence (SCIRE) project on access to information for health care providers and researchers and (2) how SCIRE influenced health care providers' management of clients. Methods A 4-part mixed methods evaluation was undertaken: (1) monitoring website traffic and utilization using Google Analytics, (2) online survey of users who accessed the SCIRE website, (3) online survey of targeted end-users, that is, rehabilitation health care providers known to work with spinal cord injury (SCI) clients, as well as researchers, and (4) focus groups with health care providers who had previously accessed SCIRE. Results The online format allowed the content for a relatively specialized field to have far reach (eg, 26 countries and over 6500 users per month). The website survey and targeted end-user survey confirmed that health care providers, as well as researchers perceived that the website increased their access to SCI evidence. Access to SCIRE not only improved knowledge of SCI evidence but helped inform changes to the health providers’ clinical practice and improved their confidence in treating SCI clients. The SCIRE information directly influenced the health providers’ clinical decision making, in terms of choice of intervention, equipment needs, or assessment tool. Conclusions A Web-based knowledge resource may be a relatively inexpensive method to increase access to evidence-based information, increase knowledge of the evidence, inform changes to the health providers’ practice, and influence their clinical decision making. PMID:25537167

Deterministic and fuzzy-based methods to evaluate community resilience

NASA Astrophysics Data System (ADS)

Kammouh, Omar; Noori, Ali Zamani; Taurino, Veronica; Mahin, Stephen A.; Cimellaro, Gian Paolo

2018-04-01

Community resilience is becoming a growing concern for authorities and decision makers. This paper introduces two indicator-based methods to evaluate the resilience of communities based on the PEOPLES framework. PEOPLES is a multi-layered framework that defines community resilience using seven dimensions. Each of the dimensions is described through a set of resilience indicators collected from literature and they are linked to a measure allowing the analytical computation of the indicator's performance. The first method proposed in this paper requires data on previous disasters as an input and returns as output a performance function for each indicator and a performance function for the whole community. The second method exploits a knowledge-based fuzzy modeling for its implementation. This method allows a quantitative evaluation of the PEOPLES indicators using descriptive knowledge rather than deterministic data including the uncertainty involved in the analysis. The output of the fuzzy-based method is a resilience index for each indicator as well as a resilience index for the community. The paper also introduces an open source online tool in which the first method is implemented. A case study illustrating the application of the first method and the usage of the tool is also provided in the paper.

Exploring the Associations among Nutrition, Science, and Mathematics Knowledge for an Integrative, Food-Based Curriculum

ERIC Educational Resources Information Center

Stage, Virginia C.; Kolasa, Kathryn M.; Díaz, Sebastián R.; Duffrin, Melani W.

2018-01-01

Background: Explore associations between nutrition, science, and mathematics knowledge to provide evidence that integrating food/nutrition education in the fourth-grade curriculum may support gains in academic knowledge. Methods: Secondary analysis of a quasi-experimental study. Sample included 438 students in 34 fourth-grade classrooms across…

Reasons and Methods to Learn the Management

ERIC Educational Resources Information Center

Li, Hongxin; Ding, Mengchun

2010-01-01

Reasons for learning the management include (1) perfecting the knowledge structure, (2) the management is the base of all organizations, (3) one person may be the manager or the managed person, (4) the management is absolutely not simple knowledge, and (5) the learning of the theoretical knowledge of the management can not be replaced by the…

Machine Methods for Acquiring, Learning, and Applying Knowledge.

ERIC Educational Resources Information Center

Hayes-Roth, Frederick; And Others

A research plan for identifying and acting upon constraints that impede the development of knowledge-based intelligent systems is described. The two primary problems identified are knowledge programming, the task of which is to create an intelligent system that does what an expert says it should, and learning, the problem requiring the criticizing…

Development of a Comprehensive Heart Disease Knowledge Questionnaire

ERIC Educational Resources Information Center

Bergman, Hannah E.; Reeve, Bryce B.; Moser, Richard P.; Scholl, Sarah; Klein, William M. P.

2011-01-01

Background: Heart disease is the number one killer of both men and women in the United States, yet a comprehensive and evidence-based heart disease knowledge assessment is currently not available. Purpose: This paper describes the two-phase development of a novel heart disease knowledge questionnaire. Methods: After review and critique of the…

Pre-Service and In-Service Teachers' Metacognitive Knowledge about Problem-Solving Strategies

ERIC Educational Resources Information Center

Metallidou, Panayiota

2009-01-01

The present study based on Antonietti, A., Ignazi, S., & Perego, P. (2000). Metacognitive knowledge about problem-solving methods. "British Journal of Educational Psychology, 70", 1-16 methodology with the aim to examine primary school teachers' metacognitive knowledge about problem-solving strategies. A sample of 338 in-service (172) and…

Developing knowledge intensive ideas in engineering education: the application of camp methodology

NASA Astrophysics Data System (ADS)

Heidemann Lassen, Astrid; Løwe Nielsen, Suna

2011-11-01

Background: Globalization, technological advancement, environmental problems, etc. challenge organizations not just to consider cost-effectiveness, but also to develop new ideas in order to build competitive advantages. Hence, methods to deliberately enhance creativity and facilitate its processes of development must also play a central role in engineering education. However, so far the engineering education literature provides little attention to the important discussion of how to develop knowledge intensive ideas based on creativity methods and concepts. Purpose: The purpose of this article is to investigate how to design creative camps from which knowledge intensive ideas can unfold. Design/method/sample: A framework on integration of creativity and knowledge intensity is first developed, and then tested through the planning, execution and evaluation of a specialized creativity camp with focus on supply chain management. Detailed documentation of the learning processes of the participating 49 engineering and business students is developed through repeated interviews during the process as well as a survey. Results: The research illustrates the process of development of ideas, and how the participants through interdisciplinary collaboration, cognitive flexibility and joint ownership develop highly innovative and knowledge-intensive ideas, with direct relevance for the four companies whose problems they address. Conclusions: The article demonstrates how the creativity camp methodology holds the potential of combining advanced academic knowledge and creativity, to produce knowledge intensive ideas, when the design is based on ideas of experiential learning as well as creativity principles. This makes the method a highly relevant learning approach for engineering students in the search for skills to both develop and implement innovative ideas.

Randomized Controlled Trial Comparing Tailoring Methods of Multimedia-Based Fall Prevention Education for Community-Dwelling Older Adults

PubMed Central

Schepens, Stacey L.; Panzer, Victoria; Goldberg, Allon

2012-01-01

OBJECTIVE We attempted to determine whether multimedia fall prevention education using different instructional strategies increases older adults’ knowledge of fall threats and their fall prevention behaviors. METHOD Fifty-three community-dwelling older adults were randomized to two educational groups or a control group. Multimedia-based educational interventions to increase fall threats knowledge and encourage fall prevention behaviors had two tailoring strategies: (1) improve content realism for individual learners (authenticity group) and (2) highlight program goals and benefits while using participants’ content selections (motivation group). Knowledge was measured at baseline and 1-mo follow-up. Participants recorded prevention behaviors for 1 mo. RESULTS Intervention group participants showed greater knowledge gains and posttest knowledge than did control group participants. The motivation group engaged in more prevention behaviors over 1 mo than did the other groups. CONCLUSION Tailoring fall prevention education by addressing authenticity and motivation successfully improved fall threats knowledge. Combining motivational strategies with multimedia education increased the effectiveness of the intervention in encouraging fall prevention behaviors. PMID:22214115

Information retrieval, critical appraisal and knowledge of evidence-based dentistry among Finnish dental students.

PubMed

Nieminen, P; Virtanen, J I

2017-11-01

One of the core skills of competent dentist is the ability to search and analyse high-quality evidence. Problems in understanding the basic aspects of knowledge-based information may impede its implementation into clinical practice. We examined how Finnish dental students acquire scientific information and how familiar they are with methods for evaluating scientific evidence related to clinical questions. All fifth-year dental students (n = 120) at the three universities in Finland received a self-administered questionnaire. The three most commonly used sources of information were colleagues, the commercial Health Gate Portal for dental practitioners and personal lecture notes. Although students rarely read scientific journals, they did find that they possess at least passable or even good skills in literature retrieval. Three questions related to the appraisal of evidence in dentistry revealed that students' knowledge of evidence-based dentistry was inadequate to critically evaluate clinical research findings. Most students seem to lack knowledge of key methodological evidence-based terms. The present curricula in dental schools fail to encourage the students to search and acquire knowledge wider than their patients themselves do. Universities have the responsibility to teach dentists various methods of critical appraisal to cope with scientific information. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Irrigation scheduling as affected by field capacity and wilting point water content from different data sources

USDA-ARS?s Scientific Manuscript database

Soil water content at field capacity and wilting point water content is critical information for irrigation scheduling, regardless of soil water sensor-based method (SM) or evapotranspiration (ET)-based method. Both methods require knowledge on site-specific and soil-specific Management Allowable De...

Integration of a knowledge-based system and a clinical documentation system via a data dictionary.

PubMed

Eich, H P; Ohmann, C; Keim, E; Lang, K

1997-01-01

This paper describes the design and realisation of a knowledge-based system and a clinical documentation system linked via a data dictionary. The software was developed as a shell with object oriented methods and C++ for IBM-compatible PC's and WINDOWS 3.1/95. The data dictionary covers terminology and document objects with relations to external classifications. It controls the terminology in the documentation program with form-based entry of clinical documents and in the knowledge-based system with scores and rules. The software was applied to the clinical field of acute abdominal pain by implementing a data dictionary with 580 terminology objects, 501 document objects, and 2136 links; a documentation module with 8 clinical documents and a knowledge-based system with 10 scores and 7 sets of rules.

Improving ECG Classification Accuracy Using an Ensemble of Neural Network Modules

PubMed Central

Javadi, Mehrdad; Ebrahimpour, Reza; Sajedin, Atena; Faridi, Soheil; Zakernejad, Shokoufeh

2011-01-01

This paper illustrates the use of a combined neural network model based on Stacked Generalization method for classification of electrocardiogram (ECG) beats. In conventional Stacked Generalization method, the combiner learns to map the base classifiers' outputs to the target data. We claim adding the input pattern to the base classifiers' outputs helps the combiner to obtain knowledge about the input space and as the result, performs better on the same task. Experimental results support our claim that the additional knowledge according to the input space, improves the performance of the proposed method which is called Modified Stacked Generalization. In particular, for classification of 14966 ECG beats that were not previously seen during training phase, the Modified Stacked Generalization method reduced the error rate for 12.41% in comparison with the best of ten popular classifier fusion methods including Max, Min, Average, Product, Majority Voting, Borda Count, Decision Templates, Weighted Averaging based on Particle Swarm Optimization and Stacked Generalization. PMID:22046232

What Do We Know about Knowledge Brokers in Paediatric Rehabilitation? A Systematic Search and Narrative Summary

PubMed Central

Verrier, Molly C.; Landry, Michel D.

2014-01-01

ABSTRACT Purpose: To conduct a systematic review of the literature related to the use of knowledge brokers within paediatric rehabilitation, and specifically to determine (1) how knowledge brokers are defined and used in paediatric rehabilitation and (2) whether knowledge brokers in paediatric rehabilitation have demonstrably improved the performance of health care providers or organizations. Methods: The MEDLINE, CINAHL, EMBASE, and AMED databases were systematically searched to identify studies relating to knowledge brokers or knowledge brokering within paediatric rehabilitation, with no restriction on the study design or primary aim. Following review of titles and abstracts, those studies identified as potentially relevant were assessed based on the inclusion criteria that they: (1) examined some aspect of knowledge brokers/brokering in paediatric rehabilitation; (2) included sufficient descriptive detail on how knowledge brokers/brokering were used; and(3) were peer-reviewed and published in English. Results: Of 1513 articles retrieved, 4 met the inclusion criteria, 3 of which referenced the same knowledge broker initiative. Two papers used mixed methods, one qualitative methodology, and one case presentation. Because of the different methods used in the included studies, the findings are presented in a narrative summary. Conclusions: This study provides an overview of the limited understanding of knowledge brokers within paediatric rehabilitation. Knowledge broker initiatives introduced within paediatric rehabilitation have been anchored in different theoretical frameworks, and no conclusions can be drawn as to the optimum combination of knowledge brokering activities and methods, nor about optimal duration, for sustained results. PMID:24799751

School-Based Speech-Language Pathologists' Knowledge and Perceptions of Autism Spectrum Disorder and Bullying

ERIC Educational Resources Information Center

Ofe, Erin E.; Plumb, Allison M.; Plexico, Laura W.; Haak, Nancy J.

2016-01-01

Purpose: The purpose of the current investigation was to examine speech-language pathologists' (SLPs') knowledge and perceptions of bullying, with an emphasis on autism spectrum disorder (ASD). Method: A 46-item, web-based survey was used to address the purposes of this investigation. Participants were recruited through e-mail and electronic…

Students and Teacher Academic Evaluation Perceptions: Methodology to Construct a Representation Based on Actionable Knowledge Discovery Framework

ERIC Educational Resources Information Center

Molina, Otilia Alejandro; Ratté, Sylvie

2017-01-01

This research introduces a method to construct a unified representation of teachers and students perspectives based on the actionable knowledge discovery (AKD) and delivery framework. The representation is constructed using two models: one obtained from student evaluations and the other obtained from teachers' reflections about their teaching…

Problem-Based Learning--Buginese Cultural Knowledge Model--Case Study: Teaching Mathematics at Junior High School

ERIC Educational Resources Information Center

Cheriani, Cheriani; Mahmud, Alimuddin; Tahmir, Suradi; Manda, Darman; Dirawan, Gufran Darma

2015-01-01

This study aims to determine the differences in learning output by using Problem Based Model combines with the "Buginese" Local Cultural Knowledge (PBL-Culture). It is also explores the students activities in learning mathematics subject by using PBL-Culture Models. This research is using Mixed Methods approach that combined quantitative…

Secondary Mathematics Teachers' Beliefs, Attitudes, Knowledge Base, and Practices in Meeting the Needs of English Language Learners

ERIC Educational Resources Information Center

Gann, Linda

2013-01-01

The research centered on secondary mathematics teachers' beliefs, attitudes, knowledge base, and practices in meeting the academic and language needs of English language learners. Using socio-cultural theory and social practice theory to frame the study, the research design employed a mixed methods approach incorporating self-reported surveys,…

Ontology-Based Adaptive Dynamic e-Learning Map Planning Method for Conceptual Knowledge Learning

ERIC Educational Resources Information Center

Chen, Tsung-Yi; Chu, Hui-Chuan; Chen, Yuh-Min; Su, Kuan-Chun

2016-01-01

E-learning improves the shareability and reusability of knowledge, and surpasses the constraints of time and space to achieve remote asynchronous learning. Since the depth of learning content often varies, it is thus often difficult to adjust materials based on the individual levels of learners. Therefore, this study develops an ontology-based…

Sequential Probability Ratio Test for Collision Avoidance Maneuver Decisions

NASA Technical Reports Server (NTRS)

Carpenter, J. Russell; Markley, F. Landis

2010-01-01

When facing a conjunction between space objects, decision makers must chose whether to maneuver for collision avoidance or not. We apply a well-known decision procedure, the sequential probability ratio test, to this problem. We propose two approaches to the problem solution, one based on a frequentist method, and the other on a Bayesian method. The frequentist method does not require any prior knowledge concerning the conjunction, while the Bayesian method assumes knowledge of prior probability densities. Our results show that both methods achieve desired missed detection rates, but the frequentist method's false alarm performance is inferior to the Bayesian method's

Objected-oriented remote sensing image classification method based on geographic ontology model

NASA Astrophysics Data System (ADS)

Chu, Z.; Liu, Z. J.; Gu, H. Y.

2016-11-01

Nowadays, with the development of high resolution remote sensing image and the wide application of laser point cloud data, proceeding objected-oriented remote sensing classification based on the characteristic knowledge of multi-source spatial data has been an important trend on the field of remote sensing image classification, which gradually replaced the traditional method through improving algorithm to optimize image classification results. For this purpose, the paper puts forward a remote sensing image classification method that uses the he characteristic knowledge of multi-source spatial data to build the geographic ontology semantic network model, and carries out the objected-oriented classification experiment to implement urban features classification, the experiment uses protégé software which is developed by Stanford University in the United States, and intelligent image analysis software—eCognition software as the experiment platform, uses hyperspectral image and Lidar data that is obtained through flight in DaFeng City of JiangSu as the main data source, first of all, the experiment uses hyperspectral image to obtain feature knowledge of remote sensing image and related special index, the second, the experiment uses Lidar data to generate nDSM(Normalized DSM, Normalized Digital Surface Model),obtaining elevation information, the last, the experiment bases image feature knowledge, special index and elevation information to build the geographic ontology semantic network model that implement urban features classification, the experiment results show that, this method is significantly higher than the traditional classification algorithm on classification accuracy, especially it performs more evidently on the respect of building classification. The method not only considers the advantage of multi-source spatial data, for example, remote sensing image, Lidar data and so on, but also realizes multi-source spatial data knowledge integration and application of the knowledge to the field of remote sensing image classification, which provides an effective way for objected-oriented remote sensing image classification in the future.

A reinforcement learning-based architecture for fuzzy logic control

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1992-01-01

This paper introduces a new method for learning to refine a rule-based fuzzy logic controller. A reinforcement learning technique is used in conjunction with a multilayer neural network model of a fuzzy controller. The approximate reasoning based intelligent control (ARIC) architecture proposed here learns by updating its prediction of the physical system's behavior and fine tunes a control knowledge base. Its theory is related to Sutton's temporal difference (TD) method. Because ARIC has the advantage of using the control knowledge of an experienced operator and fine tuning it through the process of learning, it learns faster than systems that train networks from scratch. The approach is applied to a cart-pole balancing system.

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.

History Teachers' Knowledge of Inquiry Methods: An Analysis of Cognitive Processes Used During a Historical Inquiry

ERIC Educational Resources Information Center

Voet, Michiel; De Wever, Bram

2017-01-01

The present study explores secondary school history teachers' knowledge of inquiry methods. To do so, a process model, outlining five core cognitive processes of inquiry in the history classroom, was developed based on a review of the literature. This process model was then used to analyze think-aloud protocols of 20 teachers' reasoning during an…

Reasoning Mind Genie 2: An Intelligent Tutoring System as a Vehicle for International Transfer of Instructional Methods in Mathematics

ERIC Educational Resources Information Center

Khachatryan, George A.; Romashov, Andrey V.; Khachatryan, Alexander R.; Gaudino, Steven J.; Khachatryan, Julia M.; Guarian, Konstantin R.; Yufa, Nataliya V.

2014-01-01

Effective mathematics teachers have a large body of professional knowledge, which is largely undocumented and shared by teachers working in a given country's education system. The volume and cultural nature of this knowledge make it particularly challenging to share curricula and instructional methods between countries. Thus, approaches based on…

Knowing the ABCs: A Comparative Effectiveness Study of Two Methods of Diabetes Education

PubMed Central

Naik, Aanand D.; Teal, Cayla R.; Rodriguez, Elisa; Haidet, Paul

2011-01-01

Objective To test an active-learning, empowerment approach to teaching patients about the “diabetes ABCs” (hemoglobin A1C, systolic blood pressure, and low density lipoprotein cholesterol). Methods 84 (97%) diabetic patients who participated in a randomized effectiveness trial of two clinic-based group educational methods and completed a post-intervention assessment. The empowerment arm participated in a group session that incorporated two educational innovations (a conceptual metaphor to foster understanding, and team-based learning methods to foster active learning). The traditional diabetes education arm received a didactic group session focused on self-management and educational materials about the diabetes ABCs. Participants in both arms received individual review of their current ABC values. Results A questionnaire evaluated knowledge, understanding, and recall of the diabetes ABCs was administered three months after enrollment in the study. At three months, participants in the empowerment group demonstrated greater understanding of the diabetes ABCs (P<.0001), greater knowledge of their own values (P<.0001), and greater knowledge of guideline-derived target goals for the ABCs compared with participants in the traditional arm (P<.0001). Conclusion An active-learning, empowerment-based approach applied to diabetes education can lead to greater understanding and knowledge retention. Practice Implications An empowerment approach to education can facilitate informed, activated patients and increase performance of self-management behaviors. PMID:21300516

Towards a Semantic Web of Things: A Hybrid Semantic Annotation, Extraction, and Reasoning Framework for Cyber-Physical System

PubMed Central

Wu, Zhenyu; Xu, Yuan; Yang, Yunong; Zhang, Chunhong; Zhu, Xinning; Ji, Yang

2017-01-01

Web of Things (WoT) facilitates the discovery and interoperability of Internet of Things (IoT) devices in a cyber-physical system (CPS). Moreover, a uniform knowledge representation of physical resources is quite necessary for further composition, collaboration, and decision-making process in CPS. Though several efforts have integrated semantics with WoT, such as knowledge engineering methods based on semantic sensor networks (SSN), it still could not represent the complex relationships between devices when dynamic composition and collaboration occur, and it totally depends on manual construction of a knowledge base with low scalability. In this paper, to addresses these limitations, we propose the semantic Web of Things (SWoT) framework for CPS (SWoT4CPS). SWoT4CPS provides a hybrid solution with both ontological engineering methods by extending SSN and machine learning methods based on an entity linking (EL) model. To testify to the feasibility and performance, we demonstrate the framework by implementing a temperature anomaly diagnosis and automatic control use case in a building automation system. Evaluation results on the EL method show that linking domain knowledge to DBpedia has a relative high accuracy and the time complexity is at a tolerant level. Advantages and disadvantages of SWoT4CPS with future work are also discussed. PMID:28230725

A Computer Simulation of Community Pharmacy Practice for Educational Use.

PubMed

Bindoff, Ivan; Ling, Tristan; Bereznicki, Luke; Westbury, Juanita; Chalmers, Leanne; Peterson, Gregory; Ollington, Robert

2014-11-15

To provide a computer-based learning method for pharmacy practice that is as effective as paper-based scenarios, but more engaging and less labor-intensive. We developed a flexible and customizable computer simulation of community pharmacy. Using it, the students would be able to work through scenarios which encapsulate the entirety of a patient presentation. We compared the traditional paper-based teaching method to our computer-based approach using equivalent scenarios. The paper-based group had 2 tutors while the computer group had none. Both groups were given a prescenario and postscenario clinical knowledge quiz and survey. Students in the computer-based group had generally greater improvements in their clinical knowledge score, and third-year students using the computer-based method also showed more improvements in history taking and counseling competencies. Third-year students also found the simulation fun and engaging. Our simulation of community pharmacy provided an educational experience as effective as the paper-based alternative, despite the lack of a human tutor.

Learning Physics-based Models in Hydrology under the Framework of Generative Adversarial Networks

NASA Astrophysics Data System (ADS)

Karpatne, A.; Kumar, V.

2017-12-01

Generative adversarial networks (GANs), that have been highly successful in a number of applications involving large volumes of labeled and unlabeled data such as computer vision, offer huge potential for modeling the dynamics of physical processes that have been traditionally studied using simulations of physics-based models. While conventional physics-based models use labeled samples of input/output variables for model calibration (estimating the right parametric forms of relationships between variables) or data assimilation (identifying the most likely sequence of system states in dynamical systems), there is a greater opportunity to explore the full power of machine learning (ML) methods (e.g, GANs) for studying physical processes currently suffering from large knowledge gaps, e.g. ground-water flow. However, success in this endeavor requires a principled way of combining the strengths of ML methods with physics-based numerical models that are founded on a wealth of scientific knowledge. This is especially important in scientific domains like hydrology where the number of data samples is small (relative to Internet-scale applications such as image recognition where machine learning methods has found great success), and the physical relationships are complex (high-dimensional) and non-stationary. We will present a series of methods for guiding the learning of GANs using physics-based models, e.g., by using the outputs of physics-based models as input data to the generator-learner framework, and by using physics-based models as generators trained using validation data in the adversarial learning framework. These methods are being developed under the broad paradigm of theory-guided data science that we are developing to integrate scientific knowledge with data science methods for accelerating scientific discovery.

Patient safety, quality of care, and knowledge translation in the intensive care unit.

PubMed

Needham, Dale M

2010-07-01

A large gap exists between the completion of clinical research demonstrating the benefit of new treatment interventions and improved patient outcomes resulting from implementation of these interventions as part of routine clinical practice. This gap clearly affects patient safety and quality of care. Knowledge translation is important for addressing this gap, but evaluation of the most appropriate and effective knowledge translation methods is still ongoing. Through describing one model for knowledge translation and an example of its implementation, insights can be gained into systematic methods for advancing the implementation of evidence-based interventions to improve safety, quality, and patient outcomes.

A Model for Indexing Medical Documents Combining Statistical and Symbolic Knowledge.

PubMed Central

Avillach, Paul; Joubert, Michel; Fieschi, Marius

2007-01-01

OBJECTIVES: To develop and evaluate an information processing method based on terminologies, in order to index medical documents in any given documentary context. METHODS: We designed a model using both symbolic general knowledge extracted from the Unified Medical Language System (UMLS) and statistical knowledge extracted from a domain of application. Using statistical knowledge allowed us to contextualize the general knowledge for every particular situation. For each document studied, the extracted terms are ranked to highlight the most significant ones. The model was tested on a set of 17,079 French standardized discharge summaries (SDSs). RESULTS: The most important ICD-10 term of each SDS was ranked 1st or 2nd by the method in nearly 90% of the cases. CONCLUSIONS: The use of several terminologies leads to more precise indexing. The improvement achieved in the model’s implementation performances as a result of using semantic relationships is encouraging. PMID:18693792

Nurses experience of using scientific knowledge in clinical practice: a grounded theory study.

PubMed

Renolen, Åste; Hjälmhult, Esther

2015-12-01

Guidelines recommend the use of evidence-based practice in nursing. Nurses are expected to give patients care and treatment based on the best knowledge available. They may have knowledge and positive attitudes, but this does not mean that they are basing their work on evidence-based practice. Knowledge is still lacking about what is needed to successfully implement evidence-based practice. The aim of this study was to gain more knowledge about what nurses perceive as the most important challenge in implementing evidence-based practice and to explain how they act to face and overcome this challenge. We used classical grounded theory methodology and collected data through four focus groups and one individual interview in different geographical locations in one large hospital trust in Norway. Fourteen registered clinical practice nurses participated. We analysed the data in accordance with grounded theory, using the constant comparative method. Contextual balancing of knowledge emerged as the core category and explains how the nurses dealt with their main concern, how to determine what types of knowledge they could trust. The nurses' main strategies were an inquiring approach, examining knowledge and maintaining control while taking care of patients. They combined their own experienced-based knowledge and the guidelines of evidence-based practice with a sense of control in the actual situation. The grounded theory contextual balancing of knowledge may help us to understand how nurses detect what types of knowledge they can trust in clinical practice. The nurses needed to rely on what they did, and they seemed to rely on their own experience rather than on research. © 2015 Nordic College of Caring Science.

A comparative evaluation of the effect of internet-based CME delivery format on satisfaction, knowledge and confidence

PubMed Central

2010-01-01

Background Internet-based instruction in continuing medical education (CME) has been associated with favorable outcomes. However, more direct comparative studies of different Internet-based interventions, instructional methods, presentation formats, and approaches to implementation are needed. The purpose of this study was to conduct a comparative evaluation of two Internet-based CME delivery formats and the effect on satisfaction, knowledge and confidence outcomes. Methods Evaluative outcomes of two differing formats of an Internet-based CME course with identical subject matter were compared. A Scheduled Group Learning format involved case-based asynchronous discussions with peers and a facilitator over a scheduled 3-week delivery period. An eCME On Demand format did not include facilitated discussion and was not based on a schedule; participants could start and finish at any time. A retrospective, pre-post evaluation study design comparing identical satisfaction, knowledge and confidence outcome measures was conducted. Results Participants in the Scheduled Group Learning format reported significantly higher mean satisfaction ratings in some areas, performed significantly higher on a post-knowledge assessment and reported significantly higher post-confidence scores than participants in the eCME On Demand format that was not scheduled and did not include facilitated discussion activity. Conclusions The findings support the instructional benefits of a scheduled delivery format and facilitated asynchronous discussion in Internet-based CME. PMID:20113493

The Impact of Team-Based Learning on Nervous System Examination Knowledge of Nursing Students.

PubMed

Hemmati Maslakpak, Masomeh; Parizad, Naser; Zareie, Farzad

2015-12-01

Team-based learning is one of the active learning approaches in which independent learning is combined with small group discussion in the class. This study aimed to determine the impact of team-based learning in nervous system examination knowledge of nursing students. This quasi-experimental study was conducted on 3(rd) grade nursing students, including 5th semester (intervention group) and 6(th) semester (control group). The traditional lecture method and the team-based learning method were used for educating the examination of the nervous system for intervention and control groups, respectively. The data were collected by a test covering 40-questions (multiple choice, matching, gap-filling and descriptive questions) before and after intervention in both groups. Individual Readiness Assurance Test (RAT) and Group Readiness Assurance Test (GRAT) used to collect data in the intervention group. In the end, the collected data were analyzed by SPSS ver. 13 using descriptive and inferential statistical tests. In team-based learning group, mean and standard deviation was 13.39 (4.52) before the intervention, which had been increased to 31.07 (3.20) after the intervention and this increase was statistically significant. Also, there was a statistically significant difference between the scores of RAT and GRAT in team-based learning group. Using team-based learning approach resulted in much better improvement and stability in the nervous system examination knowledge of nursing students compared to traditional lecture method; therefore, this method could be efficiently used as an effective educational approach in nursing education.

Uncovering clinical knowledge and caring practices.

PubMed

Feldman, M E

1993-06-01

Narrative storytelling is a means by which knowledge embedded in nursing practice is uncovered and examined. Benner uses this method to study and explore skill acquisition and experience-based knowledge in nursing practice. By sharing these stories, knowledge that is unique to the experienced clinician is preserved and extended. The narrative presented here describes the expert coaching, discretionary judgment, and skilled involvement in the care of a patient in the PACU.

Using diagnostic experiences in experience-based innovative design

NASA Astrophysics Data System (ADS)

Prabhakar, Sattiraju; Goel, Ashok K.

1992-03-01

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

The Effects of Smartphone-based Nebulizer Therapy Education on Parents' Knowledge and Confidence of Performance in Caring for Children with Respiratory Disease.

PubMed

Lee, Jung Min; Kim, Shin-Jeong; Min, Hae Young

This study aimed to identify the effects of smartphone-based nebulizer therapy education on the knowledge and confidence of parents while performing care for their children with respiratory disease. This quasi-experimental study employed a pretest-posttest design using a nonequivalent control group. Data were collected from children's parents who had not used nebulizer therapy for their children previously. Both the groups were given nebulizer therapy education using the same content but different learning methods. The experimental group (n=36) was taught using smartphones, while the control group (n=36) was taught using verbal and paper-based methods. The data were analyzed using the Chi Square test, repeated measures analysis of variance, and t-test. The mean scores on knowledge improvement (F=100.949, p<0.001) and confidence in performing care (t=-6.959, p<0.001) were significantly higher for the experimental group as compared to the control group. Further, the scores on satisfaction with the learning method were significantly higher for the experimental group as compared to the control group (t=-5.819, p<0.001). Our results suggest that smartphone-based education on nebulizer therapy might be effective in improving parents' knowledge and confidence in performing care for their children. This study suggests that smartphone-based education needs to be considered as an effective educational intervention in providing nursing support for parents of children with respiratory disease. Copyright © 2017 Elsevier Inc. All rights reserved.

Enhancing students’ mathematical representation and selfefficacy through situation-based learning assisted by geometer’s sketchpad program

NASA Astrophysics Data System (ADS)

Sowanto; Kusumah, Y. S.

2018-05-01

This research was conducted based on the problem of a lack of students’ mathematical representation ability as well as self-efficacy in accomplishing mathematical tasks. To overcome this problem, this research used situation-based learning (SBL) assisted by geometer’s sketchpad program (GSP). This research investigated students’ improvement of mathematical representation ability who were taught under situation-based learning (SBL) assisted by geometer’s sketchpad program (GSP) and regular method that viewed from the whole students’ prior knowledge (high, average, and low level). In addition, this research investigated the difference of students’ self-efficacy after learning was given. This research belongs to quasi experiment research using non-equivalent control group design with purposive sampling. The result of this research showed that students’ enhancement in their mathematical representation ability taught under SBL assisted by GSP was better than the regular method. Also, there was no interaction between learning methods and students prior knowledge in student’ enhancement of mathematical representation ability. There was significant difference of students’ enhancement of mathematical representation ability taught under SBL assisted by GSP viewed from students’ prior knowledge. Furthermore, there was no significant difference in terms of self-efficacy between those who were taught by SBL assisted by GSP with the regular method.

Forecasting Doctoral-Level Content in Agricultural Education: Viewpoints of Engaged Scholars in the United States

ERIC Educational Resources Information Center

Shinn, Glen C.; Briers, Gary; Baker, Matt

2008-01-01

In this study, the researchers used a classical Delphi method to re-examine the conceptual framework, definition, and knowledge base of the field. Seventeen engaged scholars, each representing the expert agricultural education community, reached consensus on defining the field of study, 10 knowledge domains, and 67 knowledge objects. The Delphi…

Community-Based Individual Knowledge Construction in the Classroom: A Process-Oriented Account

ERIC Educational Resources Information Center

Looi, C.-K.; Chen, W.

2010-01-01

This paper explores the process of knowledge convergence and knowledge sharing in the context of classroom collaboration in which students do a group learning activity mediated by a generic representation tool. In analysing the transcript of the interactions of a group, we adapt the group cognition method of Stahl and the uptake analysis…

An Investigation of Technological Pedagogical Content Knowledge, Self-Confidence, and Perception of Pre-Service Middle School Mathematics Teachers towards Instructional Technologies

ERIC Educational Resources Information Center

Karatas, Ilhan; Tunc, Mutlu Piskin; Yilmaz, Nurbanu; Karaci, Gulzade

2017-01-01

Technology provides new methods and approaches for educational activities. Therefore, teachers should improve their ability and knowledge to integrate technology into instruction. The use of technology-based learning environment which is effectively used to improve the technological pedagogical content knowledge of pre-service teachers has a…

Momentum Concept in the Process of Knowledge Construction

ERIC Educational Resources Information Center

Ergul, N. Remziye

2013-01-01

Abstraction is one of the methods for learning knowledge with using mental processes that cannot be obtained through experiment and observation. RBC model that is based on abstraction in the process of creating knowledge is directly related to mental processes. In this study, the RBC model is used for the high school students' processes of…

New Method for Knowledge Management Focused on Communication Pattern in Product Development

NASA Astrophysics Data System (ADS)

Noguchi, Takashi; Shiba, Hajime

In the field of manufacturing, the importance of utilizing knowledge and know-how has been growing. To meet this background, there is a need for new methods to efficiently accumulate and extract effective knowledge and know-how. To facilitate the extraction of knowledge and know-how needed by engineers, we first defined business process information which includes schedule/progress information, document data, information about communication among parties concerned, and information which corresponds to these three types of information. Based on our definitions, we proposed an IT system (FlexPIM: Flexible and collaborative Process Information Management) to register and accumulate business process information with the least effort. In order to efficiently extract effective information from huge volumes of accumulated business process information, focusing attention on “actions” and communication patterns, we propose a new extraction method using communication patterns. And the validity of this method has been verified for some communication patterns.

Sentiment classification technology based on Markov logic networks

NASA Astrophysics Data System (ADS)

He, Hui; Li, Zhigang; Yao, Chongchong; Zhang, Weizhe

2016-07-01

With diverse online media emerging, there is a growing concern of sentiment classification problem. At present, text sentiment classification mainly utilizes supervised machine learning methods, which feature certain domain dependency. On the basis of Markov logic networks (MLNs), this study proposed a cross-domain multi-task text sentiment classification method rooted in transfer learning. Through many-to-one knowledge transfer, labeled text sentiment classification, knowledge was successfully transferred into other domains, and the precision of the sentiment classification analysis in the text tendency domain was improved. The experimental results revealed the following: (1) the model based on a MLN demonstrated higher precision than the single individual learning plan model. (2) Multi-task transfer learning based on Markov logical networks could acquire more knowledge than self-domain learning. The cross-domain text sentiment classification model could significantly improve the precision and efficiency of text sentiment classification.

Initial investigation of dietitian perception of plant-based protein quality.

PubMed

Hughes, Glenna J; Kress, Kathleen S; Armbrecht, Eric S; Mukherjea, Ratna; Mattfeldt-Beman, Mildred

2014-07-01

Interest in plant-based diets is increasing, evidenced by scientific and regulatory recommendations, including Dietary Guidelines for Americans. Dietitians provide guidance in dietary protein selection but little is known about how familiar dietitians are with the quality of plant versus animal proteins or methods for measuring protein quality. Likewise, there is a need to explore their beliefs related to dietary recommendations. The aim of this study was to assess dietitians' perceptions of plant-based protein quality and to determine if these are affected by demographic factors such as age and dietary practice group (DPG) membership. This was a cross-sectional design using an online survey. The survey was sent to all members of the Missouri Dietetic Association. All completed surveys (136) were analyzed. The main outcome measures were responses to belief and knowledge questions about the protein quality of plant-based diets, along with demographic information including age and DPG membership. Descriptive statistics and frequencies were determined, and chi-square analysis was used to determine the associations between belief and knowledge responses and demographic characteristics. Responses to belief statements suggested a high level of support for plant-based diets. No associations were found between any of the belief questions and demographic factors. A majority of respondents were not familiar with protein quality determination methods that are currently recognized by global regulatory and advisory agencies. Potential barriers identified in shifting to a more plant-based diet were lack of interest and perceived difficulty. Knowledge among dietitians of plant-based protein quality in general, and methods of protein quality measurement more specifically, needs to be addressed to enhance their knowledge base for making dietary protein recommendations. Two potential avenues for training are university curricula and continuing education opportunities provided to practitioners who provide dietary advice.

The Typicality Ranking Task: A New Method to Derive Typicality Judgments from Children.

PubMed

Djalal, Farah Mutiasari; Ameel, Eef; Storms, Gert

2016-01-01

An alternative method for deriving typicality judgments, applicable in young children that are not familiar with numerical values yet, is introduced, allowing researchers to study gradedness at younger ages in concept development. Contrary to the long tradition of using rating-based procedures to derive typicality judgments, we propose a method that is based on typicality ranking rather than rating, in which items are gradually sorted according to their typicality, and that requires a minimum of linguistic knowledge. The validity of the method is investigated and the method is compared to the traditional typicality rating measurement in a large empirical study with eight different semantic concepts. The results show that the typicality ranking task can be used to assess children's category knowledge and to evaluate how this knowledge evolves over time. Contrary to earlier held assumptions in studies on typicality in young children, our results also show that preference is not so much a confounding variable to be avoided, but that both variables are often significantly correlated in older children and even in adults.

The Typicality Ranking Task: A New Method to Derive Typicality Judgments from Children

PubMed Central

Ameel, Eef; Storms, Gert

2016-01-01

An alternative method for deriving typicality judgments, applicable in young children that are not familiar with numerical values yet, is introduced, allowing researchers to study gradedness at younger ages in concept development. Contrary to the long tradition of using rating-based procedures to derive typicality judgments, we propose a method that is based on typicality ranking rather than rating, in which items are gradually sorted according to their typicality, and that requires a minimum of linguistic knowledge. The validity of the method is investigated and the method is compared to the traditional typicality rating measurement in a large empirical study with eight different semantic concepts. The results show that the typicality ranking task can be used to assess children’s category knowledge and to evaluate how this knowledge evolves over time. Contrary to earlier held assumptions in studies on typicality in young children, our results also show that preference is not so much a confounding variable to be avoided, but that both variables are often significantly correlated in older children and even in adults. PMID:27322371

Creating a Knowledge-Based Economy in the United Arab Emirates: Realising the Unfulfilled Potential of Women in the Science, Technology and Engineering Fields

ERIC Educational Resources Information Center

Aswad, Noor Ghazal; Vidican, Georgeta; Samulewicz, Diana

2011-01-01

As the United Arab Emirates (UAE) moves towards a knowledge-based economy, maximising the participation of the national workforce, especially women, in the transformation process is crucial. Using survey methods and semi-structured interviews, this paper examines the factors that influence women's decisions regarding their degree programme and…

Measuring New Environmental Paradigm Based on Students' Knowledge about Ecosystem and Locus of Control

ERIC Educational Resources Information Center

Putrawan, I. Made

2015-01-01

This research is aimed at obtaining information related to instrument development of Students' New Environmental Paradigm (NEP) based on their knowledge about ecosystem and Locus of Control (LOC). A survey method has been carried out by selecting senior high school students randomly with n = 362 (first stage 2013) and n = 722 (2014). Data analysed…

The Impact of a Community-Based Comprehensive Sex Education Program on Chinese Adolescents' Sex-Related Knowledge and Attitudes

ERIC Educational Resources Information Center

Wang, Bo; Meier, Ann; Shah, Iqbal; Li, Xiaoming

2006-01-01

The purpose of this study was to evaluate a community-based comprehensive sex education program among unmarried youth in China. The impact of the intervention on sexual knowledge, attitudes, and sexual initiation were assessed, using a pre-test post-test quasi-experimental research design. The program used six methods for providing sex-related…

The Influence of Trust on Knowledge Donating and Collecting: An Examination of Malaysian Universities

ERIC Educational Resources Information Center

Goh, See-Kwong; Sandhu, Manjit-Singh

2014-01-01

The purpose of this research is to examine the influence of affect-based trust and cognition-based trust on knowledge sharing behaviour by adopting the theory of planned behaviour in selected universities in Malaysia. The research adopted survey method and a total of 545 participants from 30 universities. Multiple regression was used to assess the…

Main Road Extraction from ZY-3 Grayscale Imagery Based on Directional Mathematical Morphology and VGI Prior Knowledge in Urban Areas

PubMed Central

Liu, Bo; Wu, Huayi; Wang, Yandong; Liu, Wenming

2015-01-01

Main road features extracted from remotely sensed imagery play an important role in many civilian and military applications, such as updating Geographic Information System (GIS) databases, urban structure analysis, spatial data matching and road navigation. Current methods for road feature extraction from high-resolution imagery are typically based on threshold value segmentation. It is difficult however, to completely separate road features from the background. We present a new method for extracting main roads from high-resolution grayscale imagery based on directional mathematical morphology and prior knowledge obtained from the Volunteered Geographic Information found in the OpenStreetMap. The two salient steps in this strategy are: (1) using directional mathematical morphology to enhance the contrast between roads and non-roads; (2) using OpenStreetMap roads as prior knowledge to segment the remotely sensed imagery. Experiments were conducted on two ZiYuan-3 images and one QuickBird high-resolution grayscale image to compare our proposed method to other commonly used techniques for road feature extraction. The results demonstrated the validity and better performance of the proposed method for urban main road feature extraction. PMID:26397832

Dynamic knowledge representation using agent-based modeling: ontology instantiation and verification of conceptual models.

PubMed

An, Gary

2009-01-01

The sheer volume of biomedical research threatens to overwhelm the capacity of individuals to effectively process this information. Adding to this challenge is the multiscale nature of both biological systems and the research community as a whole. Given this volume and rate of generation of biomedical information, the research community must develop methods for robust representation of knowledge in order for individuals, and the community as a whole, to "know what they know." Despite increasing emphasis on "data-driven" research, the fact remains that researchers guide their research using intuitively constructed conceptual models derived from knowledge extracted from publications, knowledge that is generally qualitatively expressed using natural language. Agent-based modeling (ABM) is a computational modeling method that is suited to translating the knowledge expressed in biomedical texts into dynamic representations of the conceptual models generated by researchers. The hierarchical object-class orientation of ABM maps well to biomedical ontological structures, facilitating the translation of ontologies into instantiated models. Furthermore, ABM is suited to producing the nonintuitive behaviors that often "break" conceptual models. Verification in this context is focused at determining the plausibility of a particular conceptual model, and qualitative knowledge representation is often sufficient for this goal. Thus, utilized in this fashion, ABM can provide a powerful adjunct to other computational methods within the research process, as well as providing a metamodeling framework to enhance the evolution of biomedical ontologies.

Comparing the effect of group-based and compact disk-based training on midwives' knowledge and attitude toward domestic violence in women of reproductive age.

PubMed

Vakily, Masoomeh; Noroozi, Mahnaz; Yamani, Nikoo

2017-01-01

Training the health personnel about domestic violence would cause them to investigate and evaluate this issue more than before. Considering the new educational approaches for transferring knowledge, the goal of this research was to compare the effect of group-based and compact disk (CD)-based training on midwives' knowledge and attitude toward domestic violence. In this clinical experiment, seventy midwives working at health centers and hospitals of Isfahan were randomly allocated into two classes of group-based and CD-based trainings and were trained in the fields of recognition, prevention, and management of domestic violence. Data were collected by questionnaires which were completed by the midwives for evaluation of their knowledge and attitude. The mean score of midwives' knowledge and attitude toward domestic violence had a meaningful increase after the training (16.1, 46.9) compared to the score of before the training (12.1, 39.1) in both of the classes (group-based training: 17.7, 45.4) (CD-based training: 11.7, 38.6). No meaningful difference was observed between the two groups regarding midwives' attitude toward domestic violence after the intervention; however, regarding their knowledge level, the difference was statistically meaningful ( P = 0.001), and this knowledge increase was more in the CD-based training group. In spite of the effectiveness of both of the training methods in promoting midwives' knowledge and attitude about domestic violence, training with CD was more effective in increasing their knowledge; as a result, considering the benefits of CD-based training such as cost-effectiveness and possibility of use at any time, it is advised to be used in training programs for the health personnel.

A Case-Based Exploration of Task/Technology Fit in a Knowledge Management Context

DTIC Science & Technology

2008-03-01

have a difficult time articulating to others. Researchers who subscribe to the constructionist perspective view knowledge as an inherently social ...Acceptance Model With Task-Technology Fit Constructs. Information & Management, 36, 9-21. Dooley, D. (2001). Social Research Methods (4th ed.). Upper...L. (2006). Social Research Methods : Qualitative and Quantitative Approaches (6 ed.). Boston: Pearson Education, Inc. Nonaka, I. (1994). A Dynamic

Concept mapping as a method to enhance evidence-based public health.

PubMed

van Bon-Martens, Marja J H; van de Goor, Ien A M; van Oers, Hans A M

2017-02-01

In this paper we explore the suitability of concept mapping as a method for integrating knowledge from science, practice, and policy. In earlier research we described and analysed five cases of concept mapping procedures in the Netherlands, serving different purposes and fields in public health. In the current paper, seven new concept mapping studies of co-produced work are added to extend this analysis. For each of these twelve studies we analysed: (1) how the method was able to integrate knowledge from practice with scientific knowledge by facilitating dialogue and collaboration between different stakeholders in the field of public health, such as academic researchers, practitioners, policy-makers and the public; (2) how the method was able to bring theory development a step further (scientific relevance); and (3) how the method was able to act as a sound basis for practical decision-making (practical relevance). Based on the answers to these research questions, all but one study was considered useful for building more evidence-based public health, even though the extent to which they underpinned actual decision-making varied. The chance of actually being implemented in practice seems strongly related to the extent to which the responsible decision-makers are involved in the way the concept map is prepared and executed. Copyright © 2016 Elsevier Ltd. All rights reserved.

Comparison of lecture and team-based learning in medical ethics education.

PubMed

Ozgonul, Levent; Alimoglu, Mustafa Kemal

2017-01-01

Medical education literature suggests that ethics education should be learner-centered and problem-based rather than theory-based. Team-based learning is an appropriate method for this suggestion. However, its effectiveness was not investigated enough in medical ethics education. Is team-based learning effective in medical ethics education in terms of knowledge retention, in-class learner engagement, and learner reactions? This was a prospective controlled follow-up study. We changed lecture with team-based learning method to teach four topics in a 2-week medical ethics clerkship, while the remaining topics were taught by lectures. For comparison, we formed team-based learning and lecture groups, in which the students and instructor are the same, but the topics and teaching methodologies are different. We determined in-class learner engagement by direct observation and student satisfaction by feedback forms. Student success for team-based learning and lecture topics in the end-of-clerkship exam and two retention tests performed 1 year and 2 years later were compared. Ethical considerations: Ethical approval for the study was granted by Akdeniz University Board of Ethics on Noninvasive Clinical Human Studies Ethics committee. Short-term knowledge retention did not differ; however, team-based learning was found superior to lecture at long-term retention tests. Student satisfaction was high with team-based learning and in-class engagement was better in team-based learning sessions. Our results on learner engagement and satisfaction with team-based learning were similar to those of previous reports. However, knowledge retention results in our study were contrary to literature. The reason might be the fact that students prepared for the end-of-clerkship pass/fail exam (short term) regardless of the teaching method. But, at long-term retention tests, they did not prepare for the exam and answered the questions just using the knowledge retained in their memories. Our findings suggest that team-based learning is a better alternative to lecture to teach ethics in medical education.

Interteaching

ERIC Educational Resources Information Center

Saville, Bryan K.; Zinn, Tracy E.

2011-01-01

In general, people associate college and university teaching with lecture-based methods, in which an expert (the teacher) delivers information to a group of nonexperts (the students), who subsequently show their newfound "knowledge" by answering examination questions. Because of the common notion that knowledge and intelligence are…

Discursive archaeology: constituting knowledge of militant nurses in trade associations.

PubMed

Almeida, Deybson Borba de; Silva, Gilberto Tadeu Reis da; Freitas, Genival Fernandes de; Padilha, Maria Itayra; Almeida, Igor Ferreira Borba de

2018-05-01

To analyze the constituting knowledge of militant nurses in trade associations. Historical research, based on the oral history method, with a qualitative approach carried out with 11 nurses who are/were militants for professional issues since the 1980s in the state of Bahia. The data collected through semi-structured interviews were organized in the software n-vivo 10 and analyzed based on dialectical hermeneutics. We identified pedagogical, administrative, public health, sociological, and trade union background knowledge as constituent of militant individuals. Final considerations: The constituting knowledge of militant nurses are inscribed in the Social Sciences, distanced from biomedical knowledge and power, pointing at ways for structuring nursing curricula. We identified the Brazilian Association of Nursing as a space for political formation.

Improving drivers' knowledge of road rules using digital games.

PubMed

Li, Qing; Tay, Richard

2014-04-01

Although a proficient knowledge of the road rules is important to safe driving, many drivers do not retain the knowledge acquired after they have obtained their licenses. Hence, more innovative and appealing methods are needed to improve drivers' knowledge of the road rules. This study examines the effect of game based learning on drivers' knowledge acquisition and retention. We find that playing an entertaining game that is designed to impart knowledge of the road rules not only improves players' knowledge but also helps them retain such knowledge. Hence, learning by gaming appears to be a promising learning approach for driver education. Copyright © 2013 Elsevier Ltd. All rights reserved.

e-Learning Content Design for Corrective Maintenance of Toshiba BMC 80.5 based on Knowledge Conversion using SECI Method: A Case Study in Aerospace Company

NASA Astrophysics Data System (ADS)

Permata Shabrina, Ayu; Pramuditya Soesanto, Rayinda; Kurniawati, Amelia; Teguh Kurniawan, Mochamad; Andrawina, Luciana

2018-03-01

Knowledge is a combination of experience, value, and information that is based on the intuition that allows an organization to evaluate and combine new information. In an organization, knowledge is not only attached to document but also in routine value creating activities, therefore knowledge is an important asset for the organization. X Corp is a company that focused on manufacturing aerospace components. In carrying out the production process, the company is supported by various machines, one of the machines is Toshiba BMC 80.5. The machine is used occasionally and therefore maintenance activity is needed, especially corrective maintenance. Corrective maintenance is done to make a breakdown machine back to work. Corrective maintenance is done by maintenance operator whose retirement year is close. The long term experience of the maintenance operator needs to be captured by the organization and shared across maintenance division. E-learning is one type of media that can support and assist knowledge sharing. This research purpose is to create the e-learning content for best practice of corrective maintenance activity for Toshiba BMC 80.5 by extracting the knowledge and experience from the operator based on knowledge conversion using SECI method. The knowledge source in this research is a maintenance supervisor and a senior maintenance engineer. From the evaluation of the e-learning content, it is known that the average test score of the respondents who use the e-learning increases from 77.5 to 87.5.

Parasitic Worms: Knowledge, Attitudes, and Practices in Western Côte d’Ivoire with Implications for Integrated Control

PubMed Central

Acka, Cinthia A.; Raso, Giovanna; N'Goran, Eliézer K.; Tschannen, Andres B.; Bogoch, Isaac I.; Séraphin, Essane; Tanner, Marcel; Obrist, Brigit; Utzinger, Jürg

2010-01-01

Background In the developing world where parasitic worm infections are pervasive, preventive chemotherapy is the key strategy for morbidity control. However, local knowledge, attitudes, and practices (KAP) of parasitic worms are poorly understood, although such information is required for prevention and sustainable control. Methods We carried out KAP surveys in two rural communities of Côte d'Ivoire that were subjected to school-based and community-based research and control activities. We used qualitative and quantitative methods. The former included observations, in-depth interviews with key informants, and focus group discussions with school children and adults. Quantitative methods consisted of a structured questionnaire administered to household heads. Principal Findings Access to clean water was lacking in both communities and only a quarter of the households had functioning latrines. There was a better understanding of soil-transmitted helminthiasis than intestinal schistosomiasis, but community-based rather than school-based interventions appeared to improve knowledge of schistosomiasis. In the villages with community-based interventions, three-quarters of household interviewees knew about intestinal schistosomiasis compared to 14% in the village where school-based interventions were implemented (P<0.001). Whereas two-thirds of respondents from the community-based intervention village indicated that the research and control project was the main source of information, only a quarter of the respondents cited the project as the main source. Conclusions/Significance Preventive chemotherapy targeting school-aged children has limitations, as older population segments are neglected, and hence lack knowledge about how to prevent and control parasitic worm infections. Improved access to clean water and sanitation is necessary, along with health education to make a durable impact against helminth infections. PMID:21200423

Induction of belief decision trees from data

NASA Astrophysics Data System (ADS)

AbuDahab, Khalil; Xu, Dong-ling; Keane, John

2012-09-01

In this paper, a method for acquiring belief rule-bases by inductive inference from data is described and evaluated. Existing methods extract traditional rules inductively from data, with consequents that are believed to be either 100% true or 100% false. Belief rules can capture uncertain or incomplete knowledge using uncertain belief degrees in consequents. Instead of using singled-value consequents, each belief rule deals with a set of collectively exhaustive and mutually exclusive consequents. The proposed method extracts belief rules from data which contain uncertain or incomplete knowledge.

[Anatomy of the skull base and the cranial nerves in slice imaging].

PubMed

Bink, A; Berkefeld, J; Zanella, F

2009-07-01

Computed tomography (CT) and magnetic resonance imaging (MRI) are suitable methods for examination of the skull base. Whereas CT is used to evaluate mainly bone destruction e.g. for planning surgical therapy, MRI is used to show pathologies in the soft tissue and bone invasion. High resolution and thin slice thickness are indispensible for both modalities of skull base imaging. Detailed anatomical knowledge is necessary even for correct planning of the examination procedures. This knowledge is a requirement to be able to recognize and interpret pathologies. MRI is the method of choice for examining the cranial nerves. The total path of a cranial nerve can be visualized by choosing different sequences taking into account the tissue surrounding this cranial nerve. This article summarizes examination methods of the skull base in CT and MRI, gives a detailed description of the anatomy and illustrates it with image examples.

Unveiling health attitudes and creating good-for-you foods: the genomics metaphor, consumer innovative web-based technologies.

PubMed

Moskowitz, H R; German, J B; Saguy, I S

2005-01-01

This article presents an integrated analysis of three emerging knowledge bases in the nutrition and consumer products industries, and how they may effect the food industry. These knowledge bases produce new vistas for corporate product development, especially with respect to those foods that are positioned as 'good for you.' Couched within the current thinking of state-of-the-art knowledge and information, this article highlights how today's thinking about accelerated product development can be introduced into the food and health industries to complement these three research areas. The 3 knowledge bases are: the genomics revolution, which has opened new insights into understanding the interactions of personal needs of individual consumers with nutritionally relevant components of the foods; the investigation of food choice by scientific studies; the development of large scale databases (mega-studies) about the consumer mind. These knowledge bases, combined with new methods to understand the consumer through research, make possible a more focused development. The confluence of trends outlined in this article provides the corporation with the beginnings of a new path to a knowledge-based, principles-grounded product-development system. The approaches hold the potential to create foods based upon people's nutritional requirements combined with their individual preferences. Integrating these emerging knowledge areas with new consumer research techniques may well reshape how the food industry develops new products to satisfy consumer needs and wants.

Discovering and Articulating What Is Not yet Known: Using Action Learning and Grounded Theory as a Knowledge Management Strategy

ERIC Educational Resources Information Center

Pauleen, David J.; Corbitt, Brian; Yoong, Pak

2007-01-01

Purpose: To provide a conceptual model for the discovery and articulation of emergent organizational knowledge, particularly knowledge that develops when people work with new technologies. Design/methodology/approach: The model is based on two widely accepted research methods--action learning and grounded theory--and is illustrated using a case…

Some requirements and suggestions for a methodology to develop knowledge based systems.

PubMed

Green, D W; Colbert, M; Long, J

1989-11-01

This paper describes an approach to the creation of a methodology for the development of knowledge based systems. It specifies some requirements and suggests how these requirements might be met. General requirements can be satisfied using a systems approach. More specific ones can be met by viewing an organization as a network of consultations for coordinating expertise. The nature of consultations is described and the form of a possible cognitive model using a blackboard architecture is outlined. The value of the approach is illustrated in terms of certain knowledge elicitation methods.

A knowledge-based design framework for airplane conceptual and preliminary design

NASA Astrophysics Data System (ADS)

Anemaat, Wilhelmus A. J.

The goal of work described herein is to develop the second generation of Advanced Aircraft Analysis (AAA) into an object-oriented structure which can be used in different environments. One such environment is the third generation of AAA with its own user interface, the other environment with the same AAA methods (i.e. the knowledge) is the AAA-AML program. AAA-AML automates the initial airplane design process using current AAA methods in combination with AMRaven methodologies for dependency tracking and knowledge management, using the TechnoSoft Adaptive Modeling Language (AML). This will lead to the following benefits: (1) Reduced design time: computer aided design methods can reduce design and development time and replace tedious hand calculations. (2) Better product through improved design: more alternative designs can be evaluated in the same time span, which can lead to improved quality. (3) Reduced design cost: due to less training and less calculation errors substantial savings in design time and related cost can be obtained. (4) Improved Efficiency: the design engineer can avoid technically correct but irrelevant calculations on incomplete or out of sync information, particularly if the process enables robust geometry earlier. Although numerous advancements in knowledge based design have been developed for detailed design, currently no such integrated knowledge based conceptual and preliminary airplane design system exists. The third generation AAA methods are tested over a ten year period on many different airplane designs. Using AAA methods will demonstrate significant time savings. The AAA-AML system will be exercised and tested using 27 existing airplanes ranging from single engine propeller, business jets, airliners, UAV's to fighters. Data for the varied sizing methods will be compared with AAA results, to validate these methods. One new design, a Light Sport Aircraft (LSA), will be developed as an exercise to use the tool for designing a new airplane. Using these tools will show an improvement in efficiency over using separate programs due to the automatic recalculation with any change of input data. The direct visual feedback of 3D geometry in the AAA-AML, will lead to quicker resolving of problems as opposed to conventional methods.

Validating a Web-based Diabetes Education Program in continuing nursing education: knowledge and competency change and user perceptions on usability and quality

PubMed Central

2014-01-01

Background Nurses as the members of health care professionals need to improve their knowledge and competencies particularly in diabetes mellitus through continuing nursing education programs. E-learning is an indirect method of training that can meet nurses’ educational needs. This study is aimed at validating a web-based diabetes education program through measurement of nurses’ knowledge and clinical competency in diabetes and nurses’ perception about its usability and quality. Methods This Quasi-experimental research was conducted on a single group of 31 nurses employed in hospitals affiliated with Shiraz University of Medical Sciences. We used a 125 MCQ knowledge test and Objective Structured Clinical Exam (OSCE) to measure knowledge and clinical competency of nurses in diabetes before and after intervention. A Learning Management System (LMS) was designed to provide educational content in the form of 12 multimedia electronic modules, interactive tests; a forum and learning activities. Nurses were trained for two months in this system after which the post-test was administered. Each nurse completed two questionnaires for measurement of their perceptions on usability and quality. We used descriptive statistics for demographic and descriptive data analysis. Paired t-test was used to compare pre- and post-data using SPSS. Results The findings showed significant differences in knowledge scores (p < 0.001), total score of clinical competencies (p < 0.001), and all ten assessed clinical competencies. The range of ratings given by participants varied on the six usability variables of Web-based training (2.96-4.23 from 5) and eight quality variables of Web-based training (3.58-4.37 from 5). Conclusion Web-based education increased nurses’ knowledge and competencies in diabetes. They positively evaluated Web-based learning usability and quality. It is hoped that this course will have a positive clinical outcomes. PMID:26086025

The smooth (tractor) operator: insights of knowledge engineering.

PubMed

Cullen, Ralph H; Smarr, Cory-Ann; Serrano-Baquero, Daniel; McBride, Sara E; Beer, Jenay M; Rogers, Wendy A

2012-11-01

The design of and training for complex systems requires in-depth understanding of task demands imposed on users. In this project, we used the knowledge engineering approach (Bowles et al., 2004) to assess the task of mowing in a citrus grove. Knowledge engineering is divided into four phases: (1) Establish goals. We defined specific goals based on the stakeholders involved. The main goal was to identify operator demands to support improvement of the system. (2) Create a working model of the system. We reviewed product literature, analyzed the system, and conducted expert interviews. (3) Extract knowledge. We interviewed tractor operators to understand their knowledge base. (4) Structure knowledge. We analyzed and organized operator knowledge to inform project goals. We categorized the information and developed diagrams to display the knowledge effectively. This project illustrates the benefits of knowledge engineering as a qualitative research method to inform technology design and training. Copyright © 2012 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Knowledge acquisition and rapid protyping of an expert system: Dealing with real world problems

NASA Technical Reports Server (NTRS)

Bailey, Patrick A.; Doehr, Brett B.

1988-01-01

The knowledge engineering and rapid prototyping phases of an expert system that does fault handling for a Solid Amine, Water Desorbed CO2 removal assembly for the Environmental Control and Life Support System for space based platforms are addressed. The knowledge acquisition phase for this project was interesting because it could not follow the textbook examples. As a result of this, a variety of methods were used during the knowledge acquisition task. The use of rapid prototyping and the need for a flexible prototype suggested certain types of knowledge representation. By combining various techniques, a representative subset of faults and a method for handling those faults was achieved. The experiences should prove useful for developing future fault handling expert systems under similar constraints.

Design and Diagnosis Problem Solving with Multifunctional Technical Knowledge Bases

DTIC Science & Technology

1992-09-29

STRUCTURE METHODOLOGY Design problem solving is a complex activity involving a number of subtasks. and a number of alternative methods potentially available...Conference on Artificial Intelligence. London: The British Computer Society, pp. 621-633. Friedland, P. (1979). Knowledge-based experimental design ...Computing Milieuxl: Management of Computing and Information Systems- -ty,*m man- agement General Terms: Design . Methodology Additional Key Words and Phrases

The Effect of Project-Based History and Nature of Science Practices on the Change of Nature of Scientific Knowledge

ERIC Educational Resources Information Center

Çibik, Ayse Sert

2016-01-01

The aim of this study is to compare the change of pre-service science teachers' views about the nature of scientific knowledge through Project-Based History and Nature of Science training and Conventional Method. The sample of the study consists of two groups of 3rd grade undergraduate students attending teacher preparation program of science…

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.

Simulation Study of Effects of the Blind Deconvolution on Ultrasound Image

NASA Astrophysics Data System (ADS)

He, Xingwu; You, Junchen

2018-03-01

Ultrasonic image restoration is an essential subject in Medical Ultrasound Imaging. However, without enough and precise system knowledge, some traditional image restoration methods based on the system prior knowledge often fail to improve the image quality. In this paper, we use the simulated ultrasound image to find the effectiveness of the blind deconvolution method for ultrasound image restoration. Experimental results demonstrate that the blind deconvolution method can be applied to the ultrasound image restoration and achieve the satisfactory restoration results without the precise prior knowledge, compared with the traditional image restoration method. And with the inaccurate small initial PSF, the results shows blind deconvolution could improve the overall image quality of ultrasound images, like much better SNR and image resolution, and also show the time consumption of these methods. it has no significant increasing on GPU platform.

Using multimodal information for the segmentation of fluorescent micrographs with application to virology and microbiology.

PubMed

Held, Christian; Wenzel, Jens; Webel, Rike; Marschall, Manfred; Lang, Roland; Palmisano, Ralf; Wittenberg, Thomas

2011-01-01

In order to improve reproducibility and objectivity of fluorescence microscopy based experiments and to enable the evaluation of large datasets, flexible segmentation methods are required which are able to adapt to different stainings and cell types. This adaption is usually achieved by the manual adjustment of the segmentation methods parameters, which is time consuming and challenging for biologists with no knowledge on image processing. To avoid this, parameters of the presented methods automatically adapt to user generated ground truth to determine the best method and the optimal parameter setup. These settings can then be used for segmentation of the remaining images. As robust segmentation methods form the core of such a system, the currently used watershed transform based segmentation routine is replaced by a fast marching level set based segmentation routine which incorporates knowledge on the cell nuclei. Our evaluations reveal that incorporation of multimodal information improves segmentation quality for the presented fluorescent datasets.

Use of prior knowledge for the analysis of high-throughput transcriptomics and metabolomics data

PubMed Central

2014-01-01

Background High-throughput omics technologies have enabled the measurement of many genes or metabolites simultaneously. The resulting high dimensional experimental data poses significant challenges to transcriptomics and metabolomics data analysis methods, which may lead to spurious instead of biologically relevant results. One strategy to improve the results is the incorporation of prior biological knowledge in the analysis. This strategy is used to reduce the solution space and/or to focus the analysis on biological meaningful regions. In this article, we review a selection of these methods used in transcriptomics and metabolomics. We combine the reviewed methods in three groups based on the underlying mathematical model: exploratory methods, supervised methods and estimation of the covariance matrix. We discuss which prior knowledge has been used, how it is incorporated and how it modifies the mathematical properties of the underlying methods. PMID:25033193

Computerization of guidelines: a knowledge specification method to convert text to detailed decision tree for electronic implementation.

PubMed

Aguirre-Junco, Angel-Ricardo; Colombet, Isabelle; Zunino, Sylvain; Jaulent, Marie-Christine; Leneveut, Laurence; Chatellier, Gilles

2004-01-01

The initial step for the computerization of guidelines is the knowledge specification from the prose text of guidelines. We describe a method of knowledge specification based on a structured and systematic analysis of text allowing detailed specification of a decision tree. We use decision tables to validate the decision algorithm and decision trees to specify and represent this algorithm, along with elementary messages of recommendation. Edition tools are also necessary to facilitate the process of validation and workflow between expert physicians who will validate the specified knowledge and computer scientist who will encode the specified knowledge in a guide-line model. Applied to eleven different guidelines issued by an official agency, the method allows a quick and valid computerization and integration in a larger decision support system called EsPeR (Personalized Estimate of Risks). The quality of the text guidelines is however still to be developed further. The method used for computerization could help to define a framework usable at the initial step of guideline development in order to produce guidelines ready for electronic implementation.

Using Purposefully Created Stories to Teach Academic Vocabulary

ERIC Educational Resources Information Center

Lee, Changnam; Roberts, Carly; Coffey, Debra

2017-01-01

Students' knowledge of vocabulary affects their reading comprehension. Despite abundant research findings in vocabulary learning, practical instructional methods for use in schools are typically underdeveloped. This article proposes a research-based method for teaching the meanings of base academic vocabulary (i.e., Tier 2) words. The method…

Web-Based Training Methods for Behavioral Health Providers: A Systematic Review.

PubMed

Jackson, Carrie B; Quetsch, Lauren B; Brabson, Laurel A; Herschell, Amy D

2018-07-01

There has been an increase in the use of web-based training methods to train behavioral health providers in evidence-based practices. This systematic review focuses solely on the efficacy of web-based training methods for training behavioral health providers. A literature search yielded 45 articles meeting inclusion criteria. Results indicated that the serial instruction training method was the most commonly studied web-based training method. While the current review has several notable limitations, findings indicate that participating in a web-based training may result in greater post-training knowledge and skill, in comparison to baseline scores. Implications and recommendations for future research on web-based training methods are discussed.

Auditing Knowledge toward Leveraging Organizational IQ in Healthcare Organizations.

PubMed

Shahmoradi, Leila; Karami, Mahtab; Farzaneh Nejad, Ahmadreza

2016-04-01

In this study, a knowledge audit was conducted based on organizational intelligence quotient (OIQ) principles of Iran's Ministry of Health and Medical Education (MOHME) to determine levers that can enhance OIQ in healthcare. The mixed method study was conducted within the MOHME. The study population consisted of 15 senior managers and policymakers. A tool based on literature review and panel expert opinions was developed to perform a knowledge audit. The significant results of this auditing revealed the following: lack of defined standard processes for organizing knowledge management (KM), lack of a knowledge map, absence of a trustee to implement KM, absence of specialists to produce a knowledge map, individuals' unwillingness to share knowledge, implicitness of knowledge format, occasional nature of knowledge documentation for repeated use, lack of a mechanism to determine repetitive tasks, lack of a reward system for the formation of communities, groups and networks, non-updatedness of the available knowledge, and absence of commercial knowledge. The analysis of the audit findings revealed that three levers for enhancing OIQ, including structure and process, organizational culture, and information technology must be created or modified.

Learning from Simple Ebooks, Online Cases or Classroom Teaching When Acquiring Complex Knowledge. A Randomized Controlled Trial in Respiratory Physiology and Pulmonology

PubMed Central

Worm, Bjarne Skjødt

2013-01-01

Background and Aims E-learning is developing fast because of the rapid increased use of smartphones, tablets and portable computers. We might not think of it as e-learning, but today many new e-books are in fact very complex electronic teaching platforms. It is generally accepted that e-learning is as effective as classroom teaching methods, but little is known about its value in relaying contents of different levels of complexity to students. We set out to investigate e-learning effects on simple recall and complex problem-solving compared to classroom teaching. Methods 63 nurses specializing in anesthesiology were evenly randomized into three groups. They were given internet-based knowledge tests before and after attending a teaching module about respiratory physiology and pulmonology. The three groups was either an e-learning group with eBook teaching material, an e-learning group with case-based teaching or a group with face-to-face case-based classroom teaching. After the module the students were required to answer a post-test. Time spent and the number of logged into the system was also measured. Results For simple recall, all methods were equally effective. For problem-solving, the eCase group achieved a comparable knowledge level to classroom teaching, while textbook learning was inferior to both (p<0.01). The textbook group also spent the least amount of time on acquiring knowledge (33 minutes, p<0.001), while the eCase group spent significantly more time on the subject (53 minutes, p<0.001) and logged into the system significantly more (2.8 vs 1.6, p<0.001). Conclusions E-learning based cases are an effective tool for teaching complex knowledge and problem-solving ability, but future studies using higher-level e-learning are encouraged.Simple recall skills, however, do not require any particular learning method. PMID:24039917

Obstetric skills drills: evaluation of teaching methods.

PubMed

Birch, L; Jones, N; Doyle, P M; Green, P; McLaughlin, A; Champney, C; Williams, D; Gibbon, K; Taylor, K

2007-11-01

To determine the most effective method of delivering training to staff on the management of an obstetric emergency. The research was conducted in a District General Hospital in the UK, delivering approximately 3500 women per year. Thirty-six staff, comprising of junior and senior medical and midwifery staff were included as research subjects. Each of the staff members were put into one of six multi-professional teams. Effectively, this gave six teams, each comprising of six members. Three teaching methods were employed. Lecture based teaching (LBT), simulation based teaching (SBT) or a combination of these two (LAS). Each team of staff were randomly allocated to undertake a full day of training in the management of Post Partum Haemorrhage utilising one of these three teaching methods. Team knowledge and performance were assessed pre-training, post training and at three months later. In addition to this assessment of knowledge and performance, qualitative semi-structured interviews were carried out with 50% of the original cohort one year after the training, to explore anxiety, confidence, communication, knowledge retention, enjoyment and transferable skills. All teams improved in their performance and knowledge. The teams taught using simulation only (SBT) were the only group to demonstrate sustained improvement in clinical management of the case, confidence, communication skills and knowledge. However, the study did not have enough power to reach statistical significance. The SBT group reported transferable skills and less anxiety in subsequent emergencies. SBT and LAS reported improved multidisciplinary communication. Although tiring, the SBT was enjoyed the most. Obstetrics is a high risk speciality, in which emergencies are to some extent, inevitable. Training staff to manage these emergencies is a fundamental principal of risk management. Traditional risk management strategies based on incident reporting and event analysis are reactive and not always effective. Simulation based training is an appropriate proactive approach to reducing errors and risk in obstetrics, improving teamwork and communication, whilst giving the student a multiplicity of transferable skills to improve their performance.

Inference of Gene Regulatory Networks Incorporating Multi-Source Biological Knowledge via a State Space Model with L1 Regularization

PubMed Central

Hasegawa, Takanori; Yamaguchi, Rui; Nagasaki, Masao; Miyano, Satoru; Imoto, Seiya

2014-01-01

Comprehensive understanding of gene regulatory networks (GRNs) is a major challenge in the field of systems biology. Currently, there are two main approaches in GRN analysis using time-course observation data, namely an ordinary differential equation (ODE)-based approach and a statistical model-based approach. The ODE-based approach can generate complex dynamics of GRNs according to biologically validated nonlinear models. However, it cannot be applied to ten or more genes to simultaneously estimate system dynamics and regulatory relationships due to the computational difficulties. The statistical model-based approach uses highly abstract models to simply describe biological systems and to infer relationships among several hundreds of genes from the data. However, the high abstraction generates false regulations that are not permitted biologically. Thus, when dealing with several tens of genes of which the relationships are partially known, a method that can infer regulatory relationships based on a model with low abstraction and that can emulate the dynamics of ODE-based models while incorporating prior knowledge is urgently required. To accomplish this, we propose a method for inference of GRNs using a state space representation of a vector auto-regressive (VAR) model with L1 regularization. This method can estimate the dynamic behavior of genes based on linear time-series modeling constructed from an ODE-based model and can infer the regulatory structure among several tens of genes maximizing prediction ability for the observational data. Furthermore, the method is capable of incorporating various types of existing biological knowledge, e.g., drug kinetics and literature-recorded pathways. The effectiveness of the proposed method is shown through a comparison of simulation studies with several previous methods. For an application example, we evaluated mRNA expression profiles over time upon corticosteroid stimulation in rats, thus incorporating corticosteroid kinetics/dynamics, literature-recorded pathways and transcription factor (TF) information. PMID:25162401

Aggregating concept map data to investigate the knowledge of beginning CS students

NASA Astrophysics Data System (ADS)

Mühling, Andreas

2016-07-01

Concept maps have a long history in educational settings as a tool for teaching, learning, and assessing. As an assessment tool, they are predominantly used to extract the structural configuration of learners' knowledge. This article presents an investigation of the knowledge structures of a large group of beginning CS students. The investigation is based on a method that collects, aggregates, and automatically analyzes the concept maps of a group of learners as a whole, to identify common structural configurations and differences in the learners' knowledge. It shows that those students who have attended CS education in their secondary school life have, on average, configured their knowledge about typical core CS/OOP concepts differently. Also, artifacts of their particular CS curriculum are visible in their externalized knowledge. The data structures and analysis methods necessary for working with concept landscapes have been implemented as a GNU R package that is freely available.

Structuration and acquisition of medical knowledge. Using UMLS in the conceptual graph formalism.

PubMed Central

Volot, F.; Zweigenbaum, P.; Bachimont, B.; Ben Said, M.; Bouaud, J.; Fieschi, M.; Boisvieux, J. F.

1993-01-01

The use of a taxonomy, such as the concept type lattice (CTL) of Conceptual Graphs, is a central structuring piece in a knowledge-based system. The knowledge it contains is constantly used by the system, and its structure provides a guide for the acquisition of other pieces of knowledge. We show how UMLS can be used as a knowledge resource to build a CTL and how the CTL can help the process of acquisition for other kinds of knowledge. We illustrate this method in the context of the MENELAS natural language understanding project. PMID:8130568

Knowledge-Based Scheduling of Arrival Aircraft in the Terminal Area

NASA Technical Reports Server (NTRS)

Krzeczowski, K. J.; Davis, T.; Erzberger, H.; Lev-Ram, Israel; Bergh, Christopher P.

1995-01-01

A knowledge based method for scheduling arrival aircraft in the terminal area has been implemented and tested in real time simulation. The scheduling system automatically sequences, assigns landing times, and assign runways to arrival aircraft by utilizing continuous updates of aircraft radar data and controller inputs. The scheduling algorithm is driven by a knowledge base which was obtained in over two thousand hours of controller-in-the-loop real time simulation. The knowledge base contains a series of hierarchical 'rules' and decision logic that examines both performance criteria, such as delay reductions, as well as workload reduction criteria, such as conflict avoidance. The objective of the algorithm is to devise an efficient plan to land the aircraft in a manner acceptable to the air traffic controllers. This paper describes the scheduling algorithms, gives examples of their use, and presents data regarding their potential benefits to the air traffic system.

Knowledge-based scheduling of arrival aircraft

NASA Technical Reports Server (NTRS)

Krzeczowski, K.; Davis, T.; Erzberger, H.; Lev-Ram, I.; Bergh, C.

1995-01-01

A knowledge-based method for scheduling arrival aircraft in the terminal area has been implemented and tested in real-time simulation. The scheduling system automatically sequences, assigns landing times, and assigns runways to arrival aircraft by utilizing continuous updates of aircraft radar data and controller inputs. The scheduling algorithms is driven by a knowledge base which was obtained in over two thousand hours of controller-in-the-loop real-time simulation. The knowledge base contains a series of hierarchical 'rules' and decision logic that examines both performance criteria, such as delay reduction, as well as workload reduction criteria, such as conflict avoidance. The objective of the algorithms is to devise an efficient plan to land the aircraft in a manner acceptable to the air traffic controllers. This paper will describe the scheduling algorithms, give examples of their use, and present data regarding their potential benefits to the air traffic system.

Integrating clinicians, knowledge and data: expert-based cooperative analysis in healthcare decision support.

PubMed

Gibert, Karina; García-Alonso, Carlos; Salvador-Carulla, Luis

2010-09-30

Decision support in health systems is a highly difficult task, due to the inherent complexity of the process and structures involved. This paper introduces a new hybrid methodology Expert-based Cooperative Analysis (EbCA), which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge (IK) to improve decision support in healthcare systems. EbCA has been applied to two different case studies, showing its usability and versatility: 1) Bench-marking of small mental health areas based on technical efficiency estimated by EbCA-Data Envelopment Analysis (EbCA-DEA), and 2) Case-mix of schizophrenia based on functional dependency using Clustering Based on Rules (ClBR). In both cases comparisons towards classical procedures using qualitative explicit prior knowledge were made. Bayesian predictive validity measures were used for comparison with expert panels results. Overall agreement was tested by Intraclass Correlation Coefficient in case "1" and kappa in both cases. EbCA is a new methodology composed by 6 steps:. 1) Data collection and data preparation; 2) acquisition of "Prior Expert Knowledge" (PEK) and design of the "Prior Knowledge Base" (PKB); 3) PKB-guided analysis; 4) support-interpretation tools to evaluate results and detect inconsistencies (here Implicit Knowledg -IK- might be elicited); 5) incorporation of elicited IK in PKB and repeat till a satisfactory solution; 6) post-processing results for decision support. EbCA has been useful for incorporating PEK in two different analysis methods (DEA and Clustering), applied respectively to assess technical efficiency of small mental health areas and for case-mix of schizophrenia based on functional dependency. Differences in results obtained with classical approaches were mainly related to the IK which could be elicited by using EbCA and had major implications for the decision making in both cases. This paper presents EbCA and shows the convenience of completing classical data analysis with PEK as a mean to extract relevant knowledge in complex health domains. One of the major benefits of EbCA is iterative elicitation of IK.. Both explicit and tacit or implicit expert knowledge are critical to guide the scientific analysis of very complex decisional problems as those found in health system research.

Knowledge acquisition and learning process description in context of e-learning

NASA Astrophysics Data System (ADS)

Kiselev, B. G.; Yakutenko, V. A.; Yuriev, M. A.

2017-01-01

This paper investigates the problem of design of e-learning and MOOC systems. It describes instructional design-based approaches to e-learning systems design: IMS Learning Design, MISA and TELOS. To solve this problem we present Knowledge Field of Educational Environment with Competence boundary conditions - instructional engineering method for self-learning systems design. It is based on the simplified TELOS approach and enables a user to create their individual learning path by choosing prerequisite and target competencies. The paper provides the ontology model for the described instructional engineering method, real life use cases and the classification of the presented model. Ontology model consists of 13 classes and 15 properties. Some of them are inherited from Knowledge Field of Educational Environment and some are new and describe competence boundary conditions and knowledge validation objects. Ontology model uses logical constraints and is described using OWL 2 standard. To give TELOS users better understanding of our approach we list mapping between TELOS and KFEEC.

Combining Knowledge and Data Driven Insights for Identifying Risk Factors using Electronic Health Records

PubMed Central

Sun, Jimeng; Hu, Jianying; Luo, Dijun; Markatou, Marianthi; Wang, Fei; Edabollahi, Shahram; Steinhubl, Steven E.; Daar, Zahra; Stewart, Walter F.

2012-01-01

Background: The ability to identify the risk factors related to an adverse condition, e.g., heart failures (HF) diagnosis, is very important for improving care quality and reducing cost. Existing approaches for risk factor identification are either knowledge driven (from guidelines or literatures) or data driven (from observational data). No existing method provides a model to effectively combine expert knowledge with data driven insight for risk factor identification. Methods: We present a systematic approach to enhance known knowledge-based risk factors with additional potential risk factors derived from data. The core of our approach is a sparse regression model with regularization terms that correspond to both knowledge and data driven risk factors. Results: The approach is validated using a large dataset containing 4,644 heart failure cases and 45,981 controls. The outpatient electronic health records (EHRs) for these patients include diagnosis, medication, lab results from 2003–2010. We demonstrate that the proposed method can identify complementary risk factors that are not in the existing known factors and can better predict the onset of HF. We quantitatively compare different sets of risk factors in the context of predicting onset of HF using the performance metric, the Area Under the ROC Curve (AUC). The combined risk factors between knowledge and data significantly outperform knowledge-based risk factors alone. Furthermore, those additional risk factors are confirmed to be clinically meaningful by a cardiologist. Conclusion: We present a systematic framework for combining knowledge and data driven insights for risk factor identification. We demonstrate the power of this framework in the context of predicting onset of HF, where our approach can successfully identify intuitive and predictive risk factors beyond a set of known HF risk factors. PMID:23304365

Impact of an online medical internet site on knowledge and practice of health care providers: a mixed methods study of the Spinal Cord Injury Rehabilitation Evidence project.

PubMed

Eng, Janice J; Noonan, Vanessa K; Townson, Andrea F; Higgins, Caroline E; Rogers, Jess; Wolfe, Dalton L

2014-12-23

It is not known whether ongoing access to a broad-based Internet knowledge resource can influence the practice of health care providers. We undertook a study to evaluate the impact of a Web-based knowledge resource on increasing access to evidence and facilitating best practice of health care providers. The objective of this study was to evaluate (1) the impact of the Spinal Cord Injury Rehabilitation Evidence (SCIRE) project on access to information for health care providers and researchers and (2) how SCIRE influenced health care providers' management of clients. A 4-part mixed methods evaluation was undertaken: (1) monitoring website traffic and utilization using Google Analytics, (2) online survey of users who accessed the SCIRE website, (3) online survey of targeted end-users, that is, rehabilitation health care providers known to work with spinal cord injury (SCI) clients, as well as researchers, and (4) focus groups with health care providers who had previously accessed SCIRE. The online format allowed the content for a relatively specialized field to have far reach (eg, 26 countries and over 6500 users per month). The website survey and targeted end-user survey confirmed that health care providers, as well as researchers perceived that the website increased their access to SCI evidence. Access to SCIRE not only improved knowledge of SCI evidence but helped inform changes to the health providers' clinical practice and improved their confidence in treating SCI clients. The SCIRE information directly influenced the health providers' clinical decision making, in terms of choice of intervention, equipment needs, or assessment tool. A Web-based knowledge resource may be a relatively inexpensive method to increase access to evidence-based information, increase knowledge of the evidence, inform changes to the health providers' practice, and influence their clinical decision making.

Improving the Knowledge and Attitude on 'Standard Days Method' of Family Planning Through a Promotional Program Among Indian Postgraduate Students.

PubMed

Menachery, Philby Babu; Noronha, Judith Angelitta; Fernanades, Sweety

2017-08-01

The 'Standard Days Method' is a fertility awareness-based method of family planning that identifies day 8 through day 19 of the menstrual cycle as fertile days during which a woman is likely to conceive with unprotected intercourse. The study was aimed to determine the effectiveness of a promotional program on the 'Standard Days Method' in terms of improving the knowledge scores and attitude scores. A pre-experimental one-group pretest-posttest research design was adopted. The samples included 365 female postgraduate students from selected colleges of Udupi Taluk, Karnataka. The data was collected using self-administered questionnaires. The plan for the promotional program was also established. The findings of the study were analyzed using the descriptive and inferential statistics. The mean pretest and posttest knowledge scores were computed, and it was found that there was an increase in the mean knowledge score from 8.96 ± 3.84 to 32.64 ± 5.59, respectively. It was observed that the promotional program on 'Standard Days Method' was effective in improving the knowledge ( p  < 0.001) and attitude ( p  < 0.001) of the postgraduate students. The promotional program on Standard Days Method of family planning was effective in improving the knowledge and attitude of the postgraduate female students. This will enable the women to adopt this method and plan their pregnancies naturally and reduce the side effects of using oral contraceptives.

Awareness, knowledge, and attitude of dentistry students in Kerman towards evidence-based dentistry

PubMed Central

Sarani, Arezoo; Sarani, Melika; Abdar, Mohammad Esmaeli; Abdar, Zahra Esmaeili

2016-01-01

Introduction Evidence-based care helps dentists provide quality dental services to patients, and such care is based on the use of reliable information about treatment and patient care from a large number of papers, books, and published textbooks. This study aimed to determine the knowledge, awareness, and attitude of dentistry students towards evidence-based dentistry. Methods In this cross-sectional study, all dentistry students who were studying in their sixth semester and higher in the Kerman School of Dentistry (n = 73) were studied. The data were analyzed using SPSS version 17 and the independent-samples t-tests and the ANOVA test. Results The means of the students’ knowledge, awareness, and attitude scores were 29.2 ± 10.8, 29.9 ± 8.12 and 44.5 ± 5.3, respectively. Among demographic variables, only the number of semesters showed a significant difference with knowledge, awareness, and attitude of dentistry students toward evidence-based dentistry (p = 0.001). Conclusion According to the results of this study, knowledge and awareness of dentistry students at Kerman University of Medical Sciences towards evidence-based dentistry were average and have a neutral attitude. Thus, providing necessary training in this regard will cause promoting the knowledge, awareness, and improved attitudes of dentistry students. PMID:27382446

Preparing Students for Flipped or Team-Based Learning Methods

ERIC Educational Resources Information Center

Balan, Peter; Clark, Michele; Restall, Gregory

2015-01-01

Purpose: Teaching methods such as Flipped Learning and Team-Based Learning require students to pre-learn course materials before a teaching session, because classroom exercises rely on students using self-gained knowledge. This is the reverse to "traditional" teaching when course materials are presented during a lecture, and students are…

Grid workflow validation using ontology-based tacit knowledge: A case study for quantitative remote sensing applications

NASA Astrophysics Data System (ADS)

Liu, Jia; Liu, Longli; Xue, Yong; Dong, Jing; Hu, Yingcui; Hill, Richard; Guang, Jie; Li, Chi

2017-01-01

Workflow for remote sensing quantitative retrieval is the ;bridge; between Grid services and Grid-enabled application of remote sensing quantitative retrieval. Workflow averts low-level implementation details of the Grid and hence enables users to focus on higher levels of application. The workflow for remote sensing quantitative retrieval plays an important role in remote sensing Grid and Cloud computing services, which can support the modelling, construction and implementation of large-scale complicated applications of remote sensing science. The validation of workflow is important in order to support the large-scale sophisticated scientific computation processes with enhanced performance and to minimize potential waste of time and resources. To research the semantic correctness of user-defined workflows, in this paper, we propose a workflow validation method based on tacit knowledge research in the remote sensing domain. We first discuss the remote sensing model and metadata. Through detailed analysis, we then discuss the method of extracting the domain tacit knowledge and expressing the knowledge with ontology. Additionally, we construct the domain ontology with Protégé. Through our experimental study, we verify the validity of this method in two ways, namely data source consistency error validation and parameters matching error validation.

COM3/369: Knowledge-based Information Systems: A new approach for the representation and retrieval of medical information

PubMed Central

Mann, G; Birkmann, C; Schmidt, T; Schaeffler, V

1999-01-01

Introduction Present solutions for the representation and retrieval of medical information from online sources are not very satisfying. Either the retrieval process lacks of precision and completeness the representation does not support the update and maintenance of the represented information. Most efforts are currently put into improving the combination of search engines and HTML based documents. However, due to the current shortcomings of methods for natural language understanding there are clear limitations to this approach. Furthermore, this approach does not solve the maintenance problem. At least medical information exceeding a certain complexity seems to afford approaches that rely on structured knowledge representation and corresponding retrieval mechanisms. Methods Knowledge-based information systems are based on the following fundamental ideas. The representation of information is based on ontologies that define the structure of the domain's concepts and their relations. Views on domain models are defined and represented as retrieval schemata. Retrieval schemata can be interpreted as canonical query types focussing on specific aspects of the provided information (e.g. diagnosis or therapy centred views). Based on these retrieval schemata it can be decided which parts of the information in the domain model must be represented explicitly and formalised to support the retrieval process. As representation language propositional logic is used. All other information can be represented in a structured but informal way using text, images etc. Layout schemata are used to assign layout information to retrieved domain concepts. Depending on the target environment HTML or XML can be used. Results Based on this approach two knowledge-based information systems have been developed. The 'Ophthalmologic Knowledge-based Information System for Diabetic Retinopathy' (OKIS-DR) provides information on diagnoses, findings, examinations, guidelines, and reference images related to diabetic retinopathy. OKIS-DR uses combinations of findings to specify the information that must be retrieved. The second system focuses on nutrition related allergies and intolerances. Information on allergies and intolerances of a patient are used to retrieve general information on the specified combination of allergies and intolerances. As a special feature the system generates tables showing food types and products that are tolerated or not tolerated by patients. Evaluation by external experts and user groups showed that the described approach of knowledge-based information systems increases the precision and completeness of knowledge retrieval. Due to the structured and non-redundant representation of information the maintenance and update of the information can be simplified. Both systems are available as WWW based online knowledge bases and CD-ROMs (cf. http://mta.gsf.de topic: products).

Knowledge and Acceptability of Long-Acting Reversible Contraception Among Adolescent Women Receiving School-Based Primary Care Services

PubMed Central

Hoopes, Andrea J.; Ahrens, Kym R.; Gilmore, Kelly; Cady, Janet; Haaland, Wren L.; Amies Oelschlager, Anne-Marie; Prager, Sarah

2016-01-01

Background: A key strategy to reduce unintended adolescent pregnancies is to expand access to long-acting reversible contraceptive (LARC) methods, including intrauterine devices and subdermal contraceptive implants. LARC services can be provided to adolescents in school-based health and other primary care settings, yet limited knowledge and negative attitudes about LARC methods may influence adolescents’ utilization of these methods. This study aimed to evaluate correlates of knowledge and acceptability of LARC methods among adolescent women at a school-based health center (SBHC). Methods: In this cross-sectional study, female patients receiving care at 2 SBHCs in Seattle, Washington completed an electronic survey about sexual and reproductive health. Primary outcomes were (1) LARC knowledge as measured by percentage correct of 10 true-false questions and (2) LARC acceptability as measured by participants reporting either liking the idea of having an intrauterine device (IUD)/subdermal implant or currently using one. Results: A total of 102 students diverse in race/ethnicity and socioeconomic backgrounds completed the survey (mean age 16.2 years, range 14.4-19.1 years). Approximately half reported a lifetime history of vaginal sex. Greater LARC knowledge was associated with white race (regression coefficient [coef] = 26.8; 95% CI 13.3-40.4; P < .001), history of vaginal intercourse (coef = 29.9; 95% CI 17.1-42.7; P < .001), and current/prior LARC use (coef = 22.8; 95% CI 6.5-40.0; P = .007). Older age was associated with lower IUD acceptability (odds ratio = 0.53, 95% CI 0.30-0.94; P = .029) while history of intercourse was associated with greater implant acceptability (odds ratio 5.66, 95% CI 1.46-22.0; P = .012). Discussion: Adolescent women in this SBHC setting had variable knowledge and acceptability of LARC. A history of vaginal intercourse was the strongest predictor of LARC acceptability. Our findings suggest a need for LARC counseling and education strategies, particularly for young women from diverse cultural backgrounds and those with less sexual experience. PMID:27067583

[Bases and methods of suturing].

PubMed

Vogt, P M; Altintas, M A; Radtke, C; Meyer-Marcotty, M

2009-05-01

If pharmaceutic modulation of scar formation does not improve the quality of the healing process over conventional healing, the surgeon must rely on personal skill and experience. Therefore a profound knowledge of wound healing based on experimental and clinical studies supplemented by postsurgical means of scar management and basic techniques of planning incisions, careful tissue handling, and thorough knowledge of suturing remain the most important ways to avoid abnormal scarring. This review summarizes the current experimental and clinical bases of surgical scar management.

Enriching semantic knowledge bases for opinion mining in big data applications.

PubMed

Weichselbraun, A; Gindl, S; Scharl, A

2014-10-01

This paper presents a novel method for contextualizing and enriching large semantic knowledge bases for opinion mining with a focus on Web intelligence platforms and other high-throughput big data applications. The method is not only applicable to traditional sentiment lexicons, but also to more comprehensive, multi-dimensional affective resources such as SenticNet. It comprises the following steps: (i) identify ambiguous sentiment terms, (ii) provide context information extracted from a domain-specific training corpus, and (iii) ground this contextual information to structured background knowledge sources such as ConceptNet and WordNet. A quantitative evaluation shows a significant improvement when using an enriched version of SenticNet for polarity classification. Crowdsourced gold standard data in conjunction with a qualitative evaluation sheds light on the strengths and weaknesses of the concept grounding, and on the quality of the enrichment process.

WebMail versus WebApp: Comparing Problem-Based Learning Methods in a Business Research Methods Course

ERIC Educational Resources Information Center

Williams van Rooij, Shahron

2007-01-01

This study examined the impact of two Problem-Based Learning (PBL) approaches on knowledge transfer, problem-solving self-efficacy, and perceived learning gains among four intact classes of adult learners engaged in a group project in an online undergraduate business research methods course. With two of the classes using a text-only PBL workbook…

Flipped Instruction in English Language Teacher Education: A Design-­Based Study in a Complex, Open-­Ended Learning Environment

ERIC Educational Resources Information Center

Egbert, Joy; Herman, David; Lee, HyunGyung

2015-01-01

Reports of flipped classrooms across areas in the field of ESL are rare, and those that address the complexities of ESL teacher education, particularly the methods course in which procedural knowledge is privileged over declarative knowledge, are even rarer. This paper uses a design-­-based research (DBR) approach to explore the flip of an ESL…

A Method of Sharing Tacit Knowledge by a Bulletin Board Link to Video Scene and an Evaluation in the Field of Nursing Skill

NASA Astrophysics Data System (ADS)

Shimada, Satoshi; Azuma, Shouzou; Teranaka, Sayaka; Kojima, Akira; Majima, Yukie; Maekawa, Yasuko

We developed the system that knowledge could be discovered and shared cooperatively in the organization based on the SECI model of knowledge management. This system realized three processes by the following method. (1)A video that expressed skill is segmented into a number of scenes according to its contents. Tacit knowledge is shared in each scene. (2)Tacit knowledge is extracted by bulletin board linked to each scene. (3)Knowledge is acquired by repeatedly viewing the video scene with the comment that shows the technical content to be practiced. We conducted experiments that the system was used by nurses working for general hospitals. Experimental results show that the nursing practical knack is able to be collected by utilizing bulletin board linked to video scene. Results of this study confirmed the possibility of expressing the tacit knowledge of nurses' empirical nursing skills sensitively with a clue of video images.

Structured product labeling improves detection of drug-intolerance issues.

PubMed

Schadow, Gunther

2009-01-01

This study sought to assess the value of the Health Level 7/U.S. Food and Drug Administration Structured Product Labeling (SPL) drug knowledge representation standard and its associated terminology sources for drug-intolerance (allergy) decision support in computerized provider order entry (CPOE) systems. The Regenstrief Institute CPOE drug-intolerance issue detection system and its knowledge base was compared with a method based on existing SPL label content enriched with knowledge sources used with SPL (NDF-RT/MeSH). Both methods were applied to a large set of drug-intolerance (allergy) records, drug orders, and medication dispensing records covering >50,000 patients over 30 years. The number of drug-intolerance issues detected by both methods was counted, as well as the number of patients with issues, number of distinct drugs, and number of distinct intolerances. The difference between drug-intolerance issues detected or missed by either method was qualitatively analyzed. Although <70% of terms were mapped to SPL, the new approach detected four times as many drug-intolerance issues on twice as many patients. The SPL-based approach is more sensitive and suggests that mapping local dictionaries to SPL, and enhancing the depth and breadth of coverage of SPL content are worth accelerating. The study also highlights specificity problems known to trouble drug-intolerance decision support and suggests how terminology and methods of recording drug intolerances could be improved.

Structured Product Labeling Improves Detection of Drug-intolerance Issues

PubMed Central

Schadow, Gunther

2009-01-01

Objectives This study sought to assess the value of the Health Level 7/U.S. Food and Drug Administration Structured Product Labeling (SPL) drug knowledge representation standard and its associated terminology sources for drug-intolerance (allergy) decision support in computerized provider order entry (CPOE) systems. Design The Regenstrief Institute CPOE drug-intolerance issue detection system and its knowledge base was compared with a method based on existing SPL label content enriched with knowledge sources used with SPL (NDF-RT/MeSH). Both methods were applied to a large set of drug-intolerance (allergy) records, drug orders, and medication dispensing records covering >50,000 patients over 30 years. Measurements The number of drug-intolerance issues detected by both methods was counted, as well as the number of patients with issues, number of distinct drugs, and number of distinct intolerances. The difference between drug-intolerance issues detected or missed by either method was qualitatively analyzed. Results Although <70% of terms were mapped to SPL, the new approach detected four times as many drug-intolerance issues on twice as many patients. Conclusion The SPL-based approach is more sensitive and suggests that mapping local dictionaries to SPL, and enhancing the depth and breadth of coverage of SPL content are worth accelerating. The study also highlights specificity problems known to trouble drug-intolerance decision support and suggests how terminology and methods of recording drug intolerances could be improved. PMID:18952933

[Research & development on computer expert system for forensic bones estimation].

PubMed

Zhao, Jun-ji; Zhang, Jan-zheng; Liu, Nin-guo

2005-08-01

To build an expert system for forensic bones estimation. By using the object oriented method, employing statistical data of forensic anthropology, combining the statistical data frame knowledge representation with productions and also using the fuzzy matching and DS evidence theory method. Software for forensic estimation of sex, age and height with opened knowledge base was designed. This system is reliable and effective, and it would be a good assistant of the forensic technician.

Using "What If.." Questions to Teach Science

ERIC Educational Resources Information Center

Tan, Kok Siang

2007-01-01

With the widening knowledge base students will need to be more flexible in their learning habits. Traditionally, teaching school science often involves teacher-centred methods like lectures, experimental demonstration or guided inquiry. Plain knowledge dissemination will not adequately prepare students to cope with the changing world. Hence,…

The impact of blended teaching on knowledge, satisfaction, and self-directed learning in nursing undergraduates: a randomized, controlled trial.

PubMed

Gagnon, Marie-Pierre; Gagnon, Johanne; Desmartis, Marie; Njoya, Merlin

2013-01-01

This study aimed to assess the effectiveness of a blended-teaching intervention using Internet-based tutorials coupled with traditional lectures in an introduction to research undergraduate nursing course. Effects of the intervention were compared with conventional, face-to-face classroom teaching on three outcomes: knowledge, satisfaction, and self-learning readiness. A two-group, randomized, controlled design was used, involving 112 participants. Descriptive statistics and analysis of covariance (ANCOVA) were performed. The teaching method was found to have no direct impact on knowledge acquisition, satisfaction, and self-learning readiness. However, motivation and teaching method had an interaction effect on knowledge acquisition by students. Among less motivated students, those in the intervention group performed better than those who received traditional training. These findings suggest that this blended-teaching method could better suit some students, depending on their degree of motivation and level of self-directed learning readiness.

Effective data validation of high-frequency data: time-point-, time-interval-, and trend-based methods.

PubMed

Horn, W; Miksch, S; Egghart, G; Popow, C; Paky, F

1997-09-01

Real-time systems for monitoring and therapy planning, which receive their data from on-line monitoring equipment and computer-based patient records, require reliable data. Data validation has to utilize and combine a set of fast methods to detect, eliminate, and repair faulty data, which may lead to life-threatening conclusions. The strength of data validation results from the combination of numerical and knowledge-based methods applied to both continuously-assessed high-frequency data and discontinuously-assessed data. Dealing with high-frequency data, examining single measurements is not sufficient. It is essential to take into account the behavior of parameters over time. We present time-point-, time-interval-, and trend-based methods for validation and repair. These are complemented by time-independent methods for determining an overall reliability of measurements. The data validation benefits from the temporal data-abstraction process, which provides automatically derived qualitative values and patterns. The temporal abstraction is oriented on a context-sensitive and expectation-guided principle. Additional knowledge derived from domain experts forms an essential part for all of these methods. The methods are applied in the field of artificial ventilation of newborn infants. Examples from the real-time monitoring and therapy-planning system VIE-VENT illustrate the usefulness and effectiveness of the methods.

Metal Artifact Reduction in X-ray Computed Tomography Using Computer-Aided Design Data of Implants as Prior Information.

PubMed

Ruth, Veikko; Kolditz, Daniel; Steiding, Christian; Kalender, Willi A

2017-06-01

The performance of metal artifact reduction (MAR) methods in x-ray computed tomography (CT) suffers from incorrect identification of metallic implants in the artifact-affected volumetric images. The aim of this study was to investigate potential improvements of state-of-the-art MAR methods by using prior information on geometry and material of the implant. The influence of a novel prior knowledge-based segmentation (PS) compared with threshold-based segmentation (TS) on 2 MAR methods (linear interpolation [LI] and normalized-MAR [NORMAR]) was investigated. The segmentation is the initial step of both MAR methods. Prior knowledge-based segmentation uses 3-dimensional registered computer-aided design (CAD) data as prior knowledge to estimate the correct position and orientation of the metallic objects. Threshold-based segmentation uses an adaptive threshold to identify metal. Subsequently, for LI and NORMAR, the selected voxels are projected into the raw data domain to mark metal areas. Attenuation values in these areas are replaced by different interpolation schemes followed by a second reconstruction. Finally, the previously selected metal voxels are replaced by the metal voxels determined by PS or TS in the initial reconstruction. First, we investigated in an elaborate phantom study if the knowledge of the exact implant shape extracted from the CAD data provided by the manufacturer of the implant can improve the MAR result. Second, the leg of a human cadaver was scanned using a clinical CT system before and after the implantation of an artificial knee joint. The results were compared regarding segmentation accuracy, CT number accuracy, and the restoration of distorted structures. The use of PS improved the efficacy of LI and NORMAR compared with TS. Artifacts caused by insufficient segmentation were reduced, and additional information was made available within the projection data. The estimation of the implant shape was more exact and not dependent on a threshold value. Consequently, the visibility of structures was improved when comparing the new approach to the standard method. This was further confirmed by improved CT value accuracy and reduced image noise. The PS approach based on prior implant information provides image quality which is superior to TS-based MAR, especially when the shape of the metallic implant is complex. The new approach can be useful for improving MAR methods and dose calculations within radiation therapy based on the MAR corrected CT images.

On the integration of reinforcement learning and approximate reasoning for control

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1991-01-01

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

Calculating semantic relatedness for biomedical use in a knowledge-poor environment.

PubMed

Rybinski, Maciej; Aldana-Montes, José

2014-01-01

Computing semantic relatedness between textual labels representing biological and medical concepts is a crucial task in many automated knowledge extraction and processing applications relevant to the biomedical domain, specifically due to the huge amount of new findings being published each year. Most methods benefit from making use of highly specific resources, thus reducing their usability in many real world scenarios that differ from the original assumptions. In this paper we present a simple resource-efficient method for calculating semantic relatedness in a knowledge-poor environment. The method obtains results comparable to state-of-the-art methods, while being more generic and flexible. The solution being presented here was designed to use only a relatively generic and small document corpus and its statistics, without referring to a previously defined knowledge base, thus it does not assume a 'closed' problem. We propose a method in which computation for two input texts is based on the idea of comparing the vocabulary associated with the best-fit documents related to those texts. As keyterm extraction is a costly process, it is done in a preprocessing step on a 'per-document' basis in order to limit the on-line processing. The actual computations are executed in a compact vector space, limited by the most informative extraction results. The method has been evaluated on five direct benchmarks by calculating correlation coefficients w.r.t. average human answers. It also has been used on Gene - Disease and Disease- Disease data pairs to highlight its potential use as a data analysis tool. Apart from comparisons with reported results, some interesting features of the method have been studied, i.e. the relationship between result quality, efficiency and applicable trimming threshold for size reduction. Experimental evaluation shows that the presented method obtains results that are comparable with current state of the art methods, even surpassing them on a majority of the benchmarks. Additionally, a possible usage scenario for the method is showcased with a real-world data experiment. Our method improves flexibility of the existing methods without a notable loss of quality. It is a legitimate alternative to the costly construction of specialized knowledge-rich resources.

Dengue knowledge, attitudes and practices and their impact on community-based vector control in rural Cambodia

PubMed Central

Doum, Dyna; Keo, Vanney; Sokha, Ly; Sam, BunLeng; Chan, Vibol; Alexander, Neal; Bradley, John; Liverani, Marco; Prasetyo, Didot Budi; Rachmat, Agus; Lopes, Sergio; Hii, Jeffrey; Rithea, Leang; Shafique, Muhammad; Hustedt, John

2018-01-01

Background Globally there are an estimated 390 million dengue infections per year, of which 96 million are clinically apparent. In Cambodia, estimates suggest as many as 185,850 cases annually. The World Health Organization global strategy for dengue prevention aims to reduce mortality rates by 50% and morbidity by 25% by 2020. The adoption of integrated vector management approach using community-based methods tailored to the local context is one of the recommended strategies to achieve these objectives. Understanding local knowledge, attitudes and practices is therefore essential to designing suitable strategies to fit each local context. Methods and findings A Knowledge, Attitudes and Practices survey in 600 randomly chosen households was administered in 30 villages in Kampong Cham which is one of the most populated provinces of Cambodia. KAP surveys were administered to a sub-sample of households where an entomology survey was conducted (1200 households), during which Aedes larval/pupae and adult female Aedes mosquito densities were recorded. Participants had high levels of knowledge regarding the transmission of dengue, Aedes breeding, and biting prevention methods; the majority of participants believed they were at risk and that dengue transmission is preventable. However, self-reported vector control practices did not match observed practices recorded in our surveys. No correlation was found between knowledge and observed practices either. Conclusion An education campaign regarding dengue prevention in this setting with high knowledge levels is unlikely to have any significant effect on practices unless it is incorporated in a more comprehensive strategy for behavioural change, such a COMBI method, which includes behavioural models as well as communication and marketing theory and practice. Trial registration ISRCTN85307778. PMID:29451879

MO-DE-BRA-05: Developing Effective Medical Physics Knowledge Structures: Models and Methods

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

Sprawls, P

Purpose: Develop a method and supporting online resources to be used by medical physics educators for teaching medical imaging professionals and trainees so they develop highly-effective physics knowledge structures that can contribute to improved diagnostic image quality on a global basis. Methods: The different types of mental knowledge structures were analyzed and modeled with respect to both the learning and teaching process for their development and the functions or tasks that can be performed with the knowledge. While symbolic verbal and mathematical knowledge structures are very important in medical physics for many purposes, the tasks of applying physics in clinicalmore » imaging--especially to optimize image quality and diagnostic accuracy--requires a sensory conceptual knowledge structure, specifically, an interconnected network of visually based concepts. This type of knowledge supports tasks such as analysis, evaluation, problem solving, interacting, and creating solutions. Traditional educational methods including lectures, online modules, and many texts are serial procedures and limited with respect to developing interconnected conceptual networks. A method consisting of the synergistic combination of on-site medical physics teachers and the online resource, CONET (Concept network developer), has been developed and made available for the topic Radiographic Image Quality. This was selected as the inaugural topic, others to follow, because it can be used by medical physicists teaching the large population of medical imaging professionals, such as radiology residents, who can apply the knowledge. Results: Tutorials for medical physics educators on developing effective knowledge structures are being presented and published and CONET is available with open access for all to use. Conclusion: An adjunct to traditional medical physics educational methods with the added focus on sensory concept development provides opportunities for medical physics teachers to share their knowledge and experience at a higher cognitive level and produce medical professionals with the enhanced ability to apply physics to clinical procedures.« less

Recommendations for Developing Alternative Test Methods for Developmental Neurotoxicity

EPA Science Inventory

There is great interest in developing alternative methods for developmental neurotoxicity testing (DNT) that are cost-efficient, use fewer animals and are based on current scientific knowledge of the developing nervous system. Alternative methods will require demonstration of the...

The impact of internet and simulation-based training on transoesophageal echocardiography learning in anaesthetic trainees: a prospective randomised study.

PubMed

Sharma, V; Chamos, C; Valencia, O; Meineri, M; Fletcher, S N

2013-06-01

With the increasing role of transoesophageal echocardiography in clinical fields other than cardiac surgery, we decided to assess the efficacy of multi-modular echocardiography learning in echo-naïve anaesthetic trainees. Twenty-eight trainees undertook a pre-test to ascertain basic echocardiography knowledge, following which the study subjects were randomly assigned to two groups: learning via traditional methods such as review of guidelines and other literature (non-internet group); and learning via an internet-based echocardiography resource (internet group). After this, subjects in both groups underwent simulation-based echocardiography training. More tests were then conducted after a review of the respective educational resources and simulation sessions. Mean (SD) scores of subjects in the non-internet group were 28 (10)%, 44 (10)% and 63 (5)% in the pre-test, post-intervention test and post-simulation test, respectively, whereas those in the internet group scored 29 (8)%, 59 (10)%, (p = 0.001) and 72 (8)%, p = 0.005, respectively. The use of internet- and simulation-based learning methods led to a significant improvement in knowledge of transoesophageal echocardiography by anaesthetic trainees. The impact of simulation-based training was greater in the group who did not use the internet-based resource. We conclude that internet- and simulation-based learning methods both improve transoesophageal echocardiography knowledge in echo-naïve anaesthetic trainees. Anaesthesia © 2013 The Association of Anaesthetists of Great Britain and Ireland.

Advanced Networks in Dental Rich Online MEDiA (ANDROMEDA)

NASA Astrophysics Data System (ADS)

Elson, Bruce; Reynolds, Patricia; Amini, Ardavan; Burke, Ezra; Chapman, Craig

There is growing demand for dental education and training not only in terms of knowledge but also skills. This demand is driven by continuing professional development requirements in the more developed economies, personnel shortages and skills differences across the European Union (EU) accession states and more generally in the developing world. There is an excellent opportunity for the EU to meet this demand by developing an innovative online flexible learning platform (FLP). Current clinical online systems are restricted to the delivery of general, knowledge-based training with no easy method of personalization or delivery of skill-based training. The PHANTOM project, headed by Kings College London is developing haptic-based virtual reality training systems for clinical dental training. ANDROMEDA seeks to build on this and establish a Flexible Learning Platform that can integrate the haptic and sensor based training with rich media knowledge transfer, whilst using sophisticated technologies such as including service-orientated architecture (SOA), Semantic Web technologies, knowledge-based engineering, business intelligence (BI) and virtual worlds for personalization.

GPs' thoughts on prescribing medication and evidence-based knowledge: the benefit aspect is a strong motivator. A descriptive focus group study.

PubMed

Skoglund, Ingmarie; Segesten, Kerstin; Björkelund, Cecilia

2007-06-01

To describe GPs' thoughts of prescribing medication and evidence-based knowledge (EBM) concerning drug therapy. Tape-recorded focus-group interviews transcribed verbatim and analysed using qualitative methods. GPs from the south-eastern part of Västra Götaland, Sweden. A total of 16 GPs out of 178 from the south-eastern part of the region strategically chosen to represent urban and rural, male and female, long and short GP experience. Transcripts were analysed using a descriptive qualitative method. The categories were: benefits, time and space, and expert knowledge. The benefit was a merge of positive elements, all aspects of the GPs' tasks. Time and space were limitations for GPs' tasks. EBM as a constituent of expert knowledge should be more customer adjusted to be able to be used in practice. Benefit was the most important category, existing in every decision-making situation for the GP. The core category was prompt and pragmatic benefit, which was the utmost benefit. GPs' thoughts on evidence-based medicine and prescribing medication were highly related to reflecting on benefit and results. The interviews indicated that prompt and pragmatic benefit is important for comprehending their thoughts.

A New Educational Method to Acquire and Transfer Experience-based Wisdom for Power Engineers

NASA Astrophysics Data System (ADS)

Kyomoto, Sumie; Doi, Atsushi

Electric power industry faces circumstances where advances in system automation technologies and enhancement of operational reliability make on-the-job training (OJT) opportunities less frequent and consequently it becomes difficult to rely simply on a traditional method based on OJT for successfully passing experimental knowledge and skills from one generation of technicians to another. In addition, the “year 2007 issue” puts companies concerned at risk of losing sophisticated skills or know-how which veterans in their employment have accumulated over many years of service. This paper discusses, in light of the usefulness of “guided experience” under an apprentice system, a training/education scheme designed to realize an inheritance of experienced personnel's know-how, in particular tacit knowledge, and a new educational system which is based on this notion. A system is proposed which involves: 1) making use of a work simulator, 2) accumulating tacit knowledge which experienced personnel use as the way or process to identify, analyze and solve complex problems in specific challenging situations, and 3) realizing “learning by doing” which is supported by the database of tacit knowledge. Trial on a prototype has proved the feasibility of this system.

A knowledge engineering approach to recognizing and extracting sequences of nucleic acids from scientific literature.

PubMed

García-Remesal, Miguel; Maojo, Victor; Crespo, José

2010-01-01

In this paper we present a knowledge engineering approach to automatically recognize and extract genetic sequences from scientific articles. To carry out this task, we use a preliminary recognizer based on a finite state machine to extract all candidate DNA/RNA sequences. The latter are then fed into a knowledge-based system that automatically discards false positives and refines noisy and incorrectly merged sequences. We created the knowledge base by manually analyzing different manuscripts containing genetic sequences. Our approach was evaluated using a test set of 211 full-text articles in PDF format containing 3134 genetic sequences. For such set, we achieved 87.76% precision and 97.70% recall respectively. This method can facilitate different research tasks. These include text mining, information extraction, and information retrieval research dealing with large collections of documents containing genetic sequences.

E-learning and nursing assessment skills and knowledge - An integrative review.

PubMed

McDonald, Ewan W; Boulton, Jessica L; Davis, Jacqueline L

2018-07-01

This review examines the current evidence on the effectiveness of digital technologies or e-based learning for enhancing the skills and knowledge of nursing students in nursing assessment. This integrative review identifies themes emerging from e-learning and 'nursing assessment' literature. Literature reviews have been undertaken in relation to digital learning and nursing education, including clinical skills, clinical case studies and the nurse-educator role. Whilst perceptions of digital learning are well covered, a gap in knowledge persists for understanding the effectiveness of e-learning on nursing assessment skills and knowledge. This is important as comprehensive assessment skills and knowledge are a key competency for newly qualified nurses. The MEDLINE, CINAHL, Cochrane Library and ProQuest Nursing and Allied Health Source electronic databases were searched for the period 2006 to 2016. Hand searching in bibliographies was also undertaken. Selection criteria for this review included: FINDINGS: Twenty articles met the selection criteria for this review, and five major themes for e-based learning were identified (a) students become self-evaluators; (b) blend and scaffold learning; (c) measurement of clinical reasoning; (d) mobile technology and Facebook are effective; and (e) training and preparation is vital. Although e-based learning programs provide a flexible teaching method, evidence suggests e-based learning alone does not exceed face-to-face patient simulation. This is particularly the case where nursing assessment learning is not scaffolded. This review demonstrates that e-based learning and traditional teaching methods used in conjunction with each other create a superior learning style. Copyright © 2018 Elsevier Ltd. All rights reserved.

From the EBM pyramid to the Greek temple: a new conceptual approach to Guidelines as implementation tools in mental health.

PubMed

Salvador-Carulla, L; Lukersmith, S; Sullivan, W

2017-04-01

Guideline methods to develop recommendations dedicate most effort around organising discovery and corroboration knowledge following the evidence-based medicine (EBM) framework. Guidelines typically use a single dimension of information, and generally discard contextual evidence and formal expert knowledge and consumer's experiences in the process. In recognition of the limitations of guidelines in complex cases, complex interventions and systems research, there has been significant effort to develop new tools, guides, resources and structures to use alongside EBM methods of guideline development. In addition to these advances, a new framework based on the philosophy of science is required. Guidelines should be defined as implementation decision support tools for improving the decision-making process in real-world practice and not only as a procedure to optimise the knowledge base of scientific discovery and corroboration. A shift from the model of the EBM pyramid of corroboration of evidence to the use of broader multi-domain perspective graphically depicted as 'Greek temple' could be considered. This model takes into account the different stages of scientific knowledge (discovery, corroboration and implementation), the sources of knowledge relevant to guideline development (experimental, observational, contextual, expert-based and experiential); their underlying inference mechanisms (deduction, induction, abduction, means-end inferences) and a more precise definition of evidence and related terms. The applicability of this broader approach is presented for the development of the Canadian Consensus Guidelines for the Primary Care of People with Developmental Disabilities.

Rule-based simulation models

NASA Technical Reports Server (NTRS)

Nieten, Joseph L.; Seraphine, Kathleen M.

1991-01-01

Procedural modeling systems, rule based modeling systems, and a method for converting a procedural model to a rule based model are described. Simulation models are used to represent real time engineering systems. A real time system can be represented by a set of equations or functions connected so that they perform in the same manner as the actual system. Most modeling system languages are based on FORTRAN or some other procedural language. Therefore, they must be enhanced with a reaction capability. Rule based systems are reactive by definition. Once the engineering system has been decomposed into a set of calculations using only basic algebraic unary operations, a knowledge network of calculations and functions can be constructed. The knowledge network required by a rule based system can be generated by a knowledge acquisition tool or a source level compiler. The compiler would take an existing model source file, a syntax template, and a symbol table and generate the knowledge network. Thus, existing procedural models can be translated and executed by a rule based system. Neural models can be provide the high capacity data manipulation required by the most complex real time models.

An integrated strategy of knowledge application for optimal e-health implementation: A multi-method study protocol

PubMed Central

Gagnon, Marie-Pierre; Légaré, France; Fortin, Jean-Paul; Lamothe, Lise; Labrecque, Michel; Duplantie, Julie

2008-01-01

Background E-health is increasingly valued for supporting: 1) access to quality health care services for all citizens; 2) information flow and exchange; 3) integrated health care services and 4) interprofessional collaboration. Nevertheless, several questions remain on the factors allowing an optimal integration of e-health in health care policies, organisations and practices. An evidence-based integrated strategy would maximise the efficacy and efficiency of e-health implementation. However, decisions regarding e-health applications are usually not evidence-based, which can lead to a sub-optimal use of these technologies. This study aims at understanding factors influencing the application of scientific knowledge for an optimal implementation of e-health in the health care system. Methods A three-year multi-method study is being conducted in the Province of Quebec (Canada). Decision-making at each decisional level (political, organisational and clinical) are analysed based on specific approaches. At the political level, critical incidents analysis is being used. This method will identify how decisions regarding the implementation of e-health could be influenced or not by scientific knowledge. Then, interviews with key-decision-makers will look at how knowledge was actually used to support their decisions, and what factors influenced its use. At the organisational level, e-health projects are being analysed as case studies in order to explore the use of scientific knowledge to support decision-making during the implementation of the technology. Interviews with promoters, managers and clinicians will be carried out in order to identify factors influencing the production and application of scientific knowledge. At the clinical level, questionnaires are being distributed to clinicians involved in e-health projects in order to analyse factors influencing knowledge application in their decision-making. Finally, a triangulation of the results will be done using mixed methodologies to allow a transversal analysis of the results at each of the decisional levels. Results This study will identify factors influencing the use of scientific evidence and other types of knowledge by decision-makers involved in planning, financing, implementing and evaluating e-health projects. Conclusion These results will be highly relevant to inform decision-makers who wish to optimise the implementation of e-health in the Quebec health care system. This study is extremely relevant given the context of major transformations in the health care system where e-health becomes a must. PMID:18435853

The Effects of a Summer Inservice Program on Secondary Science Teachers' Stages of Concerns, Attitudes, and Knowledge of Selected STS Concepts and Its Impact on Students' Knowledge.

ERIC Educational Resources Information Center

Zielinski, Edward J.; Bernardo, John A.

This investigation was conducted to determine the effects of a 10-day summer workshop using the Concerns Based Adoption Model concerning science technology and society (STS) topics and methods of classroom implementation on the knowledge, attitudes, and stages of concerns of the participating secondary inservice teachers, as well as student…

The Structure of Savant Calendrical Knowledge

ERIC Educational Resources Information Center

Heavey, Lisa; Hermelin, Beate; Crane, Laura; Pring, Linda

2012-01-01

Aim: We aimed to explore the organization of the calendar knowledge base underlying date calculation by assessing the ability of savant calendar calculators to free recall a series of date lists. Method: Four experiments are reported that assessed recall of structural and non-structural features of the calendar in eight savant calendar calculators…

Knowledge about Pandemic Influenza in Healthcare and Non-Healthcare Students in London

ERIC Educational Resources Information Center

Purssell, Edward; While, Alison

2011-01-01

Objective: To investigate the knowledge of university students regarding pandemic and seasonal influenza. Design: Online questionnaire-based survey of undergraduate and postgraduate students, including those on nursing, medical, other health and non-health related courses. Method: The sample was recruited using the university email system, and the…

Using Film and Intergenerational Colearning to Enhance Knowledge and Attitudes toward Older Adults

ERIC Educational Resources Information Center

McCleary, Roseanna

2014-01-01

This study evaluated whether two evidence-based methods used collaboratively, intergenerational colearning and use of films/documentaries in an educational context, enhanced knowledge levels and attitudes toward older adults in nursing, social work, and other allied profession students. Students participated in a gerontology film festival where…

Supporting the M-Learning Based Knowledge Transfer in University Education and Corporate Sector

ERIC Educational Resources Information Center

Benedek, András; Molnár, György

2014-01-01

The evolution of today's connective forms of teaching and learning draws attention to expansion of "space" in which teaching and learning moments: engaging the attention, knowledge transfer, acquisition, demonstration, experience, experiment research and practice, conclusions are organized around a more free method. Due to these…

Health Literacy Predicts Cardiac Knowledge Gains in Cardiac Rehabilitation Participants

ERIC Educational Resources Information Center

Mattson, Colleen C.; Rawson, Katherine; Hughes, Joel W.; Waechter, Donna; Rosneck, James

2015-01-01

Objective: Health literacy is increasingly recognised as a potentially important patient characteristic related to patient education efforts. We evaluated whether health literacy would predict gains in knowledge after completion of patient education in cardiac rehabilitation. Method: This was a re-post observational analysis study design based on…

Characteristic and Competency Measurement Instrument Development for Maintenance Staff of Mechanical Expertise with SECI Method: A Case of Manufacturing Company

NASA Astrophysics Data System (ADS)

Mahatmavidya, P. A.; Soesanto, R. P.; Kurniawati, A.; Andrawina, L.

2018-03-01

Human resource is an important factor for a company to gain competitiveness, therefore competencies of each individual in a company is a basic characteristic that is taken into account. The increasing employee’s competency will affect directly to the company's performance. The purpose of this research is to improve the quality of human resources of maintenance staff in manufacturing company by designing competency measurement instrument that aims to assess the competency of employees. The focus of this research is the mechanical expertise of maintenance staff. SECI method is used in this research for managing knowledge that is held by senior employees regarding employee competence of mechanical expertise. The SECI method converts the knowledge of a person's tacit knowledge into an explicit knowledge so that the knowledge can be used by others. The knowledge that is gathered from SECI method is converted into a list of competence and break down into the detailed competency. Based on the results of this research, it is known that 11 general competencies, 17 distinctive competencies, 20 indicators, and 20 item list for assessing the competencies are developed. From the result of competency breakdown, the five-level instrument of measurement is designed which can assist in assessing employee’s competency for mechanical expertise.

Developing and validating a nutrition knowledge questionnaire: key methods and considerations.

PubMed

Trakman, Gina Louise; Forsyth, Adrienne; Hoye, Russell; Belski, Regina

2017-10-01

To outline key statistical considerations and detailed methodologies for the development and evaluation of a valid and reliable nutrition knowledge questionnaire. Literature on questionnaire development in a range of fields was reviewed and a set of evidence-based guidelines specific to the creation of a nutrition knowledge questionnaire have been developed. The recommendations describe key qualitative methods and statistical considerations, and include relevant examples from previous papers and existing nutrition knowledge questionnaires. Where details have been omitted for the sake of brevity, the reader has been directed to suitable references. We recommend an eight-step methodology for nutrition knowledge questionnaire development as follows: (i) definition of the construct and development of a test plan; (ii) generation of the item pool; (iii) choice of the scoring system and response format; (iv) assessment of content validity; (v) assessment of face validity; (vi) purification of the scale using item analysis, including item characteristics, difficulty and discrimination; (vii) evaluation of the scale including its factor structure and internal reliability, or Rasch analysis, including assessment of dimensionality and internal reliability; and (viii) gathering of data to re-examine the questionnaire's properties, assess temporal stability and confirm construct validity. Several of these methods have previously been overlooked. The measurement of nutrition knowledge is an important consideration for individuals working in the nutrition field. Improved methods in the development of nutrition knowledge questionnaires, such as the use of factor analysis or Rasch analysis, will enable more confidence in reported measures of nutrition knowledge.

Knowledge-Based Topic Model for Unsupervised Object Discovery and Localization.

PubMed

Niu, Zhenxing; Hua, Gang; Wang, Le; Gao, Xinbo

Unsupervised object discovery and localization is to discover some dominant object classes and localize all of object instances from a given image collection without any supervision. Previous work has attempted to tackle this problem with vanilla topic models, such as latent Dirichlet allocation (LDA). However, in those methods no prior knowledge for the given image collection is exploited to facilitate object discovery. On the other hand, the topic models used in those methods suffer from the topic coherence issue-some inferred topics do not have clear meaning, which limits the final performance of object discovery. In this paper, prior knowledge in terms of the so-called must-links are exploited from Web images on the Internet. Furthermore, a novel knowledge-based topic model, called LDA with mixture of Dirichlet trees, is proposed to incorporate the must-links into topic modeling for object discovery. In particular, to better deal with the polysemy phenomenon of visual words, the must-link is re-defined as that one must-link only constrains one or some topic(s) instead of all topics, which leads to significantly improved topic coherence. Moreover, the must-links are built and grouped with respect to specific object classes, thus the must-links in our approach are semantic-specific , which allows to more efficiently exploit discriminative prior knowledge from Web images. Extensive experiments validated the efficiency of our proposed approach on several data sets. It is shown that our method significantly improves topic coherence and outperforms the unsupervised methods for object discovery and localization. In addition, compared with discriminative methods, the naturally existing object classes in the given image collection can be subtly discovered, which makes our approach well suited for realistic applications of unsupervised object discovery.Unsupervised object discovery and localization is to discover some dominant object classes and localize all of object instances from a given image collection without any supervision. Previous work has attempted to tackle this problem with vanilla topic models, such as latent Dirichlet allocation (LDA). However, in those methods no prior knowledge for the given image collection is exploited to facilitate object discovery. On the other hand, the topic models used in those methods suffer from the topic coherence issue-some inferred topics do not have clear meaning, which limits the final performance of object discovery. In this paper, prior knowledge in terms of the so-called must-links are exploited from Web images on the Internet. Furthermore, a novel knowledge-based topic model, called LDA with mixture of Dirichlet trees, is proposed to incorporate the must-links into topic modeling for object discovery. In particular, to better deal with the polysemy phenomenon of visual words, the must-link is re-defined as that one must-link only constrains one or some topic(s) instead of all topics, which leads to significantly improved topic coherence. Moreover, the must-links are built and grouped with respect to specific object classes, thus the must-links in our approach are semantic-specific , which allows to more efficiently exploit discriminative prior knowledge from Web images. Extensive experiments validated the efficiency of our proposed approach on several data sets. It is shown that our method significantly improves topic coherence and outperforms the unsupervised methods for object discovery and localization. In addition, compared with discriminative methods, the naturally existing object classes in the given image collection can be subtly discovered, which makes our approach well suited for realistic applications of unsupervised object discovery.

Development of Korean Rare Disease Knowledge Base

PubMed Central

Seo, Heewon; Kim, Dokyoon; Chae, Jong-Hee; Kang, Hee Gyung; Lim, Byung Chan; Cheong, Hae Il

2012-01-01

Objectives Rare disease research requires a broad range of disease-related information for the discovery of causes of genetic disorders that are maladies caused by abnormalities in genes or chromosomes. A rarity in cases makes it difficult for researchers to elucidate definite inception. This knowledge base will be a major resource not only for clinicians, but also for the general public, who are unable to find consistent information on rare diseases in a single location. Methods We design a compact database schema for faster querying; its structure is optimized to store heterogeneous data sources. Then, clinicians at Seoul National University Hospital (SNUH) review and revise those resources. Additionally, we integrated other sources to capture genomic resources and clinical trials in detail on the Korean Rare Disease Knowledge base (KRDK). Results As a result, we have developed a Web-based knowledge base, KRDK, suitable for study of Mendelian diseases that commonly occur among Koreans. This knowledge base is comprised of disease summary and review, causal gene list, laboratory and clinic directory, patient registry, and so on. Furthermore, database for analyzing and giving access to human biological information and the clinical trial management system are integrated on KRDK. Conclusions We expect that KRDK, the first rare disease knowledge base in Korea, may contribute to collaborative research and be a reliable reference for application to clinical trials. Additionally, this knowledge base is ready for querying of drug information so that visitors can search a list of rare diseases that is relative to specific drugs. Visitors can have access to KRDK via http://www.snubi.org/software/raredisease/. PMID:23346478

A population-based tissue probability map-driven level set method for fully automated mammographic density estimations.

PubMed

Kim, Youngwoo; Hong, Byung Woo; Kim, Seung Ja; Kim, Jong Hyo

2014-07-01

A major challenge when distinguishing glandular tissues on mammograms, especially for area-based estimations, lies in determining a boundary on a hazy transition zone from adipose to glandular tissues. This stems from the nature of mammography, which is a projection of superimposed tissues consisting of different structures. In this paper, the authors present a novel segmentation scheme which incorporates the learned prior knowledge of experts into a level set framework for fully automated mammographic density estimations. The authors modeled the learned knowledge as a population-based tissue probability map (PTPM) that was designed to capture the classification of experts' visual systems. The PTPM was constructed using an image database of a selected population consisting of 297 cases. Three mammogram experts extracted regions for dense and fatty tissues on digital mammograms, which was an independent subset used to create a tissue probability map for each ROI based on its local statistics. This tissue class probability was taken as a prior in the Bayesian formulation and was incorporated into a level set framework as an additional term to control the evolution and followed the energy surface designed to reflect experts' knowledge as well as the regional statistics inside and outside of the evolving contour. A subset of 100 digital mammograms, which was not used in constructing the PTPM, was used to validate the performance. The energy was minimized when the initial contour reached the boundary of the dense and fatty tissues, as defined by experts. The correlation coefficient between mammographic density measurements made by experts and measurements by the proposed method was 0.93, while that with the conventional level set was 0.47. The proposed method showed a marked improvement over the conventional level set method in terms of accuracy and reliability. This result suggests that the proposed method successfully incorporated the learned knowledge of the experts' visual systems and has potential to be used as an automated and quantitative tool for estimations of mammographic breast density levels.

Pedagogical Strategies Used by Selected Leading Mixed Methodologists in Mixed Research Courses

ERIC Educational Resources Information Center

Frels, Rebecca K.; Onwuegbuzie, Anthony J.; Leech, Nancy L.; Collins, Kathleen M. T.

2014-01-01

The teaching of research methods is common across multiple fields in the social and educational sciences for establishing evidence-based practices and furthering the knowledge base through scholarship. Yet, specific to mixed methods, scant information exists as to how to approach teaching complex concepts for meaningful learning experiences. Thus,…

Scaffolding Wiki-Supported Collaborative Learning for Small-Group Projects and Whole-Class Collaborative Knowledge Building

ERIC Educational Resources Information Center

Lin, C-Y.; Reigeluth, C. M.

2016-01-01

While educators value wikis' potential, wikis may fail to support collaborative constructive learning without careful scaffolding. This article proposes literature-based instructional methods, revised based on two expert instructors' input, presents the collected empirical evidence on the effects of these methods and proposes directions for future…

A Natural Teaching Method Based on Learning Theory.

ERIC Educational Resources Information Center

Smilkstein, Rita

1991-01-01

The natural teaching method is active and student-centered, based on schema and constructivist theories, and informed by research in neuroplasticity. A schema is a mental picture or understanding of something we have learned. Humans can have knowledge only to the degree to which they have constructed schemas from learning experiences and practice.…

Hybrid forecasting of chaotic processes: Using machine learning in conjunction with a knowledge-based model

NASA Astrophysics Data System (ADS)

Pathak, Jaideep; Wikner, Alexander; Fussell, Rebeckah; Chandra, Sarthak; Hunt, Brian R.; Girvan, Michelle; Ott, Edward

2018-04-01

A model-based approach to forecasting chaotic dynamical systems utilizes knowledge of the mechanistic processes governing the dynamics to build an approximate mathematical model of the system. In contrast, machine learning techniques have demonstrated promising results for forecasting chaotic systems purely from past time series measurements of system state variables (training data), without prior knowledge of the system dynamics. The motivation for this paper is the potential of machine learning for filling in the gaps in our underlying mechanistic knowledge that cause widely-used knowledge-based models to be inaccurate. Thus, we here propose a general method that leverages the advantages of these two approaches by combining a knowledge-based model and a machine learning technique to build a hybrid forecasting scheme. Potential applications for such an approach are numerous (e.g., improving weather forecasting). We demonstrate and test the utility of this approach using a particular illustrative version of a machine learning known as reservoir computing, and we apply the resulting hybrid forecaster to a low-dimensional chaotic system, as well as to a high-dimensional spatiotemporal chaotic system. These tests yield extremely promising results in that our hybrid technique is able to accurately predict for a much longer period of time than either its machine-learning component or its model-based component alone.

Knowledge representation to support reasoning based on multiple models

NASA Technical Reports Server (NTRS)

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

1990-01-01

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

Jointly learning word embeddings using a corpus and a knowledge base

PubMed Central

Bollegala, Danushka; Maehara, Takanori; Kawarabayashi, Ken-ichi

2018-01-01

Methods for representing the meaning of words in vector spaces purely using the information distributed in text corpora have proved to be very valuable in various text mining and natural language processing (NLP) tasks. However, these methods still disregard the valuable semantic relational structure between words in co-occurring contexts. These beneficial semantic relational structures are contained in manually-created knowledge bases (KBs) such as ontologies and semantic lexicons, where the meanings of words are represented by defining the various relationships that exist among those words. We combine the knowledge in both a corpus and a KB to learn better word embeddings. Specifically, we propose a joint word representation learning method that uses the knowledge in the KBs, and simultaneously predicts the co-occurrences of two words in a corpus context. In particular, we use the corpus to define our objective function subject to the relational constrains derived from the KB. We further utilise the corpus co-occurrence statistics to propose two novel approaches, Nearest Neighbour Expansion (NNE) and Hedged Nearest Neighbour Expansion (HNE), that dynamically expand the KB and therefore derive more constraints that guide the optimisation process. Our experimental results over a wide-range of benchmark tasks demonstrate that the proposed method statistically significantly improves the accuracy of the word embeddings learnt. It outperforms a corpus-only baseline and reports an improvement of a number of previously proposed methods that incorporate corpora and KBs in both semantic similarity prediction and word analogy detection tasks. PMID:29529052

Modeling technology innovation: How science, engineering, and industry methods can combine to generate beneficial socioeconomic impacts

PubMed Central

2012-01-01

Background Government-sponsored science, technology, and innovation (STI) programs support the socioeconomic aspects of public policies, in addition to expanding the knowledge base. For example, beneficial healthcare services and devices are expected to result from investments in research and development (R&D) programs, which assume a causal link to commercial innovation. Such programs are increasingly held accountable for evidence of impact—that is, innovative goods and services resulting from R&D activity. However, the absence of comprehensive models and metrics skews evidence gathering toward bibliometrics about research outputs (published discoveries), with less focus on transfer metrics about development outputs (patented prototypes) and almost none on econometrics related to production outputs (commercial innovations). This disparity is particularly problematic for the expressed intent of such programs, as most measurable socioeconomic benefits result from the last category of outputs. Methods This paper proposes a conceptual framework integrating all three knowledge-generating methods into a logic model, useful for planning, obtaining, and measuring the intended beneficial impacts through the implementation of knowledge in practice. Additionally, the integration of the Context-Input-Process-Product (CIPP) model of evaluation proactively builds relevance into STI policies and programs while sustaining rigor. Results The resulting logic model framework explicitly traces the progress of knowledge from inputs, following it through the three knowledge-generating processes and their respective knowledge outputs (discovery, invention, innovation), as it generates the intended socio-beneficial impacts. It is a hybrid model for generating technology-based innovations, where best practices in new product development merge with a widely accepted knowledge-translation approach. Given the emphasis on evidence-based practice in the medical and health fields and “bench to bedside” expectations for knowledge transfer, sponsors and grantees alike should find the model useful for planning, implementing, and evaluating innovation processes. Conclusions High-cost/high-risk industries like healthcare require the market deployment of technology-based innovations to improve domestic society in a global economy. An appropriate balance of relevance and rigor in research, development, and production is crucial to optimize the return on public investment in such programs. The technology-innovation process needs a comprehensive operational model to effectively allocate public funds and thereby deliberately and systematically accomplish socioeconomic benefits. PMID:22591638

A Cross-Cultural Study of the Effect of a Graph-Oriented Computer-Assisted Project-Based Learning Environment on Middle School Students' Science Knowledge and Argumentation Skills

ERIC Educational Resources Information Center

Hsu, P.-S.; Van Dyke, M.; Chen, Y.; Smith, T. J.

2016-01-01

The purpose of this mixed-methods study was to explore how seventh graders in a suburban school in the United States and sixth graders in an urban school in Taiwan developed argumentation skills and science knowledge in a project-based learning environment that incorporated a graph-oriented, computer-assisted application (GOCAA). A total of 42…

A novel probabilistic framework for event-based speech recognition

NASA Astrophysics Data System (ADS)

Juneja, Amit; Espy-Wilson, Carol

2003-10-01

One of the reasons for unsatisfactory performance of the state-of-the-art automatic speech recognition (ASR) systems is the inferior acoustic modeling of low-level acoustic-phonetic information in the speech signal. An acoustic-phonetic approach to ASR, on the other hand, explicitly targets linguistic information in the speech signal, but such a system for continuous speech recognition (CSR) is not known to exist. A probabilistic and statistical framework for CSR based on the idea of the representation of speech sounds by bundles of binary valued articulatory phonetic features is proposed. Multiple probabilistic sequences of linguistically motivated landmarks are obtained using binary classifiers of manner phonetic features-syllabic, sonorant and continuant-and the knowledge-based acoustic parameters (APs) that are acoustic correlates of those features. The landmarks are then used for the extraction of knowledge-based APs for source and place phonetic features and their binary classification. Probabilistic landmark sequences are constrained using manner class language models for isolated or connected word recognition. The proposed method could overcome the disadvantages encountered by the early acoustic-phonetic knowledge-based systems that led the ASR community to switch to systems highly dependent on statistical pattern analysis methods and probabilistic language or grammar models.

Knowledge Engineering as a Component of the Curriculum for Medical Cybernetists.

PubMed

Karas, Sergey; Konev, Arthur

2017-01-01

According to a new state educational standard, students who have chosen medical cybernetics as their major must develop a knowledge engineering competency. Previously, in the course "Clinical cybernetics" while practicing project-based learning students were designing automated workstations for medical personnel using client-server technology. The purpose of the article is to give insight into the project of a new educational module "Knowledge engineering". Students will acquire expert knowledge by holding interviews and conducting surveys, and then they will formalize it. After that, students will form declarative expert knowledge in a network model and analyze the knowledge graph. Expert decision making methods will be applied in software on the basis of a production model of knowledge. Project implementation will result not only in the development of analytical competencies among students, but also creation of a practically useful expert system based on student models to support medical decisions. Nowadays, this module is being tested in the educational process.

Research on Customer Value Based on Extension Data Mining

NASA Astrophysics Data System (ADS)

Chun-Yan, Yang; Wei-Hua, Li

Extenics is a new discipline for dealing with contradiction problems with formulize model. Extension data mining (EDM) is a product combining Extenics with data mining. It explores to acquire the knowledge based on extension transformations, which is called extension knowledge (EK), taking advantage of extension methods and data mining technology. EK includes extensible classification knowledge, conductive knowledge and so on. Extension data mining technology (EDMT) is a new data mining technology that mining EK in databases or data warehouse. Customer value (CV) can weigh the essentiality of customer relationship for an enterprise according to an enterprise as a subject of tasting value and customers as objects of tasting value at the same time. CV varies continually. Mining the changing knowledge of CV in databases using EDMT, including quantitative change knowledge and qualitative change knowledge, can provide a foundation for that an enterprise decides the strategy of customer relationship management (CRM). It can also provide a new idea for studying CV.

Objective estimates based on experimental data and initial and final knowledge

NASA Technical Reports Server (NTRS)

Rosenbaum, B. M.

1972-01-01

An extension of the method of Jaynes, whereby least biased probability estimates are obtained, permits such estimates to be made which account for experimental data on hand as well as prior and posterior knowledge. These estimates can be made for both discrete and continuous sample spaces. The method allows a simple interpretation of Laplace's two rules: the principle of insufficient reason and the rule of succession. Several examples are analyzed by way of illustration.

'Before reaching the last mile'- Knowledge, attitude, practice and perceived barriers related to tuberculosis directly observed therapy among ASHA workers in Central India: A mixed method study.

PubMed

Singh, Akash Ranjan; Pakhare, Abhijit; Kokane, Arun M; Shewade, Hemant Deepak; Chauhan, Ashish; Singh, Abhishek; Gangwar, Arti; Thakur, Prahlad Singh

2017-12-01

Community-based direct observed treatment (DOT) providers are an important bridge for the national tuberculosis programme in India to reach the unreached. The present study has explored the knowledge, attitude, practice and barriers perceived by the community-based DOT providers. Mixed-methods study design was used among 41 community-based DOT providers (Accredited Social Health Activist (ASHAs)) working in 67 villages from a primary health center in Raisen district of Madhya Pradesh, India. The cross-sectional quantitative component assessed the knowledge and practices and three focus-group discussions explored the attitude and perceived barriers related to DOT provision. 'Adequate knowledge' and 'satisfactory practice' related to DOT provision was seen in 14 (34%) and 13 (32%) ASHAs respectively. Only two (5%) received any amount of honorarium for completion of DOT in last 3years. The focus-group discussions revealed unfavourable attitude; inadequate training and supervision, non-payment of honorarium, issues related to assured services after referral and patient related factors as the barriers to satisfactory practice of DOT. Study revealed inadequate knowledge and unsatisfactory practice related to DOT provision among ASHAs. Innovations addressing the perceived barriers to improve practice of DOT provision by ASHAs are urgently required. Copyright © 2017 Ministry of Health, Saudi Arabia. Published by Elsevier Ltd. All rights reserved.

Knowledge discovery about quality of life changes of spinal cord injury patients: clustering based on rules by states.

PubMed

Gibert, Karina; García-Rudolph, Alejandro; Curcoll, Lluïsa; Soler, Dolors; Pla, Laura; Tormos, José María

2009-01-01

In this paper, an integral Knowledge Discovery Methodology, named Clustering based on rules by States, which incorporates artificial intelligence (AI) and statistical methods as well as interpretation-oriented tools, is used for extracting knowledge patterns about the evolution over time of the Quality of Life (QoL) of patients with Spinal Cord Injury. The methodology incorporates the interaction with experts as a crucial element with the clustering methodology to guarantee usefulness of the results. Four typical patterns are discovered by taking into account prior expert knowledge. Several hypotheses are elaborated about the reasons for psychological distress or decreases in QoL of patients over time. The knowledge discovery from data (KDD) approach turns out, once again, to be a suitable formal framework for handling multidimensional complexity of the health domains.

Translating knowledge into practice: An exploratory study of dementia-specific training for community-based service providers.

PubMed

O'Sullivan, Grace; Hocking, Clare; McPherson, Kathryn

2017-08-01

Objective To develop, deliver, and evaluate dementia-specific training designed to inform service delivery by enhancing the knowledge of community-based service providers. Methods This exploratory qualitative study used an interdisciplinary, interuniversity team approach to develop and deliver dementia-specific training. Participants included management, care staff, and clients from three organizations funded to provide services in the community. Data on the acceptability, applicability, and perceived outcomes of the training were gathered through focus group discussions and individual interviews. Transcripts were analyzed to generate open codes which were clustered into themes and sub-themes addressing the content, delivery, and value of the training. Findings Staff valued up-to-date knowledge and "real stories" grounded in practice. Clients welcomed the strengths-based approach. Contractual obligations impact on the application of knowledge in practice. Implications The capacity to implement new knowledge may be limited by the legislative policies which frame service provision, to the detriment of service users.

Mentor-mentee Relationship: A Win-Win Contract In Graduate Medical Education.

PubMed

Toklu, Hale Z; Fuller, Jacklyn C

2017-12-05

Scholarly activities (i.e., the discovery of new knowledge; development of new technologies, methods, materials, or uses; integration of knowledge leading to new understanding) are intended to measure the quality and quantity of dissemination of knowledge. A successful mentorship program is necessary during residency to help residents achieve the six core competencies (patient care, medical knowledge, practice-based learning and improvement, systems-based practice, professionalism, interpersonal and communication skills) required by the Accreditation Council for Graduate Medical Education (ACGME). The role of the mentor in this process is pivotal in the advancement of the residents' knowledge about evidence-based medicine. With this process, while mentees become more self-regulated, exhibit confidence in their performance, and demonstrate more insight and aptitude in their jobs, mentors also achieve elevated higher self-esteem, enhanced leadership skills, and personal gratification. As such, we may conclude that mentoring is a two-sided relationship; i.e., a 'win-win' style of commitment between the mentor and mentee. Hence, both parties will eventually advance academically, as well as professionally.

Reliability and performance evaluation of systems containing embedded rule-based expert systems

NASA Technical Reports Server (NTRS)

Beaton, Robert M.; Adams, Milton B.; Harrison, James V. A.

1989-01-01

A method for evaluating the reliability of real-time systems containing embedded rule-based expert systems is proposed and investigated. It is a three stage technique that addresses the impact of knowledge-base uncertainties on the performance of expert systems. In the first stage, a Markov reliability model of the system is developed which identifies the key performance parameters of the expert system. In the second stage, the evaluation method is used to determine the values of the expert system's key performance parameters. The performance parameters can be evaluated directly by using a probabilistic model of uncertainties in the knowledge-base or by using sensitivity analyses. In the third and final state, the performance parameters of the expert system are combined with performance parameters for other system components and subsystems to evaluate the reliability and performance of the complete system. The evaluation method is demonstrated in the context of a simple expert system used to supervise the performances of an FDI algorithm associated with an aircraft longitudinal flight-control system.

Towards knowledge-based systems in clinical practice: development of an integrated clinical information and knowledge management support system.

PubMed

Kalogeropoulos, Dimitris A; Carson, Ewart R; Collinson, Paul O

2003-09-01

Given that clinicians presented with identical clinical information will act in different ways, there is a need to introduce into routine clinical practice methods and tools to support the scientific homogeneity and accountability of healthcare decisions and actions. The benefits expected from such action include an overall reduction in cost, improved quality of care, patient and public opinion satisfaction. Computer-based medical data processing has yielded methods and tools for managing the task away from the hospital management level and closer to the desired disease and patient management level. To this end, advanced applications of information and disease process modelling technologies have already demonstrated an ability to significantly augment clinical decision making as a by-product. The wide-spread acceptance of evidence-based medicine as the basis of cost-conscious and concurrently quality-wise accountable clinical practice suffices as evidence supporting this claim. Electronic libraries are one-step towards an online status of this key health-care delivery quality control environment. Nonetheless, to date, the underlying information and knowledge management technologies have failed to be integrated into any form of pragmatic or marketable online and real-time clinical decision making tool. One of the main obstacles that needs to be overcome is the development of systems that treat both information and knowledge as clinical objects with same modelling requirements. This paper describes the development of such a system in the form of an intelligent clinical information management system: a system which at the most fundamental level of clinical decision support facilitates both the organised acquisition of clinical information and knowledge and provides a test-bed for the development and evaluation of knowledge-based decision support functions.

Medical Students' Knowledge of Fertility Awareness-Based Methods of Family Planning.

PubMed

Danis, Peter G; Kurz, Sally A; Covert, Laura M

2017-01-01

Traditional medical school curricula have not addressed fertility awareness-based methods (FABMs) of family planning. The objective of this study was to assess (1) 3-year medical students' knowledge of FABMs of family planning, (2) their confidence in utilizing that knowledge in patient care, and (3) to implement focused education on FABMs to improve knowledge and confidence. Third-year medical students at one institution in the United States were given a 10-question assessment at the beginning of their OB-GYN rotation. Two lectures about FABMs and their clinical applications were given during the rotation. Students were given the same questions at the end of the rotation. Each questionnaire consisted of eight questions to assess a student's knowledge of FABMs and two questions to assess the student's confidence in sharing and utilizing that information in a clinical setting. McNemar's test was used to analyze the data. Two hundred seventy-seven students completed a pretest questionnaire and 196 students completed the posttest questionnaire. Medical knowledge improved from an initial test score of 38.99% to final test score of 53.57% ( p  < 0.05). Confidence in sharing FABM information with patients (0 = very uncomfortable; 5 = very comfortable) improved from 1.51 to 3.00 ( p  < 0.05). Confidence in utilizing FABM to diagnose and treat gynecologic/reproductive problems (0 = not very confident and 5 = very confident) improved from 1.01 to 3.15 ( p  < 0.05). Medical schools may not include FABMs in OB-GYN curriculum; however, to patients, these methods remain a sought after and valid form of family planning. This study shows that brief, focused education can increase medical students' knowledge of and confidence with FABMs of family planning.

Vulnerable Women’s Self-Care Needs in Knowledge, Attitude and Practice Concerning Sexually Transmitted Diseases

PubMed Central

Alimohammadi, Nasrollah; Baghersad, Zahra; Boroumandfar, Zahra

2016-01-01

Background: Vulnerable women are prone to sexually transmitted diseases (STD) due to their special conditions and poor knowledge about these diseases in the society. Therefore, the present study aimed to determine the vulnerable women’s self-care needs in knowledge, attitude and practice concerning STD. Methods: This is a cross-sectional-descriptive study conducted in 2014. The data collection was carried out using a self-administered structured questionnaire. 120 vulnerable women referring to centers affiliated to health and well-being center in Isfahan participated in this study. They were selected through proportional rationing sampling and filled out a researcher developed questionnaire containing information on personal characteristics, self-care knowledge, attitude, and practice needs toward the STD. The data were analyzed using statistical methods including Spearman & Pearson correlation co-efficient, independent t-test and ANOVA. All analyses were carried out using SPSS, 20. Results: Based on the results, most of the subjects mentioned that their priorities of self-care needs in domains of knowledge, attitude and practice were “familiarization with the types and contamination ways of sexually transmitted diseases” (57.9%); “diagnosis of STD only makes us anxious” (24.8), and “the method of washing the genital area before and after intercourse” 41.3%), respectively. There was a significant association among marital status, education, history of addiction, and self-care needs in domains of knowledge, attitude and practice (P<0.05). Conclusion: Results showed that vulnerable women not only knew their need about STD, but also paid attention to their attitude and practice needs toward STD. Therefore, educational programs should be designed and administrated by the experts, based on vulnerable women’s self-care needs concerning their knowledge, attitude and practice to prevent and control STD in vulnerable individuals. PMID:27382588

Construction of teacher knowledge in context: Preparing elementary teachers to teach mathematics and science

NASA Astrophysics Data System (ADS)

Lowery, Maye Norene Vail

1998-12-01

The purposes of this study were to further the understanding of how preservice teacher construct teacher knowledge and pedagogical content knowledge of elementary mathematics and science and to determine the extent of that knowledge in a school-based setting. Preservice teachers, university instructors, inservice teachers, and other school personnel were involved in this context-specific study. Evidence of the preservice teachers' knowledge construction (its acquisition, its dimensions, and the social context) was collected through the use of a qualitative methodology. Collected data included individual and group interviews, course documents, artifacts, and preservice teaching portfolios. Innovative aspects of this integrated mathematics and science elementary methods course included standards-based instruction with immediate access to field experiences. Grade-level teams of preservice and inservice teachers planned and implemented lessons in mathematics and science for elementary students. An on-site, portable classroom building served as a mathematics and science teaching and learning laboratory. A four-stage analysis was performed, revealing significant patterns of learning. An ecosystem of learning within a constructivist learning environment was identified to contain three systems: the university system; the school system; and the cohort of learners system. A mega system for the construction of teacher knowledge was revealed in the final analysis. Learning venues were discovered to be the conduits of learning in a situated learning context. Analysis and synthesis of data revealed an extensive acquisition of teacher knowledge and pedagogical content knowledge through identified learning components. Patience, flexibility, and communication were identified as necessities for successful teaching. Learning components included: collaboration with inservice teachers; implementation of discovery learning and hands-on/minds-on learning; small groupwork; lesson planning; classroom management; and application of standards-based instruction. Prolonged, extensive classroom involvement provided familiarity with the ability levels of elementary students. Gains in positive attitudes and confidence in teaching mathematics and science were identified as direct results of this experience. This may be attributed to the immersion in the school-based setting (hands-on) and the standards-based approach (minds-on) methods course. The results are written in case study form using thick description with an emphasis on preservice teachers.

Using Bourdieu’s Theoretical Framework to Examine How the Pharmacy Educator Views Pharmacy Knowledge

PubMed Central

2015-01-01

Objective. To explore how different pharmacy educators view pharmacy knowledge within the United Kingdom MPharm program and to relate these findings to Pierre Bourdieu’s theoretical framework. Methods. Twelve qualitative interviews were conducted with 4 faculty members from 3 different types of schools of pharmacy in the United Kingdom: a newer school, an established teaching-based school, and an established research-intensive school. Selection was based on a representation of both science-based and practice-based disciplines, gender balance, and teaching experience. Results. The interview transcripts indicated how these members of the academic community describe knowledge. There was a polarization between science-based and practice-based educators in terms of Bourdieu’s description of field, species of capital, and habitus. Conclusion. A Bourdieusian perspective on the differences among faculty member responses supports our understanding of curriculum integration and offers some practical implications for the future development of pharmacy programs. PMID:26889065

Using a computer-based simulation with an artificial intelligence component and discovery learning to formulate training needs for a new technology

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

Hillis, D.R.

A computer-based simulation with an artificial intelligence component and discovery learning was investigated as a method to formulate training needs for new or unfamiliar technologies. Specifically, the study examined if this simulation method would provide for the recognition of applications and knowledge/skills which would be the basis for establishing training needs. The study also examined the effect of field-dependence/independence on recognition of applications and knowledge/skills. A pretest-posttest control group experimental design involving fifty-eight college students from an industrial technology program was used. The study concluded that the simulation was effective in developing recognition of applications and the knowledge/skills for amore » new or unfamiliar technology. And, the simulation's effectiveness for providing this recognition was not limited by an individual's field-dependence/independence.« less

Enriching semantic knowledge bases for opinion mining in big data applications

PubMed Central

Weichselbraun, A.; Gindl, S.; Scharl, A.

2014-01-01

This paper presents a novel method for contextualizing and enriching large semantic knowledge bases for opinion mining with a focus on Web intelligence platforms and other high-throughput big data applications. The method is not only applicable to traditional sentiment lexicons, but also to more comprehensive, multi-dimensional affective resources such as SenticNet. It comprises the following steps: (i) identify ambiguous sentiment terms, (ii) provide context information extracted from a domain-specific training corpus, and (iii) ground this contextual information to structured background knowledge sources such as ConceptNet and WordNet. A quantitative evaluation shows a significant improvement when using an enriched version of SenticNet for polarity classification. Crowdsourced gold standard data in conjunction with a qualitative evaluation sheds light on the strengths and weaknesses of the concept grounding, and on the quality of the enrichment process. PMID:25431524

A model for indexing medical documents combining statistical and symbolic knowledge.

PubMed

Avillach, Paul; Joubert, Michel; Fieschi, Marius

2007-10-11

To develop and evaluate an information processing method based on terminologies, in order to index medical documents in any given documentary context. We designed a model using both symbolic general knowledge extracted from the Unified Medical Language System (UMLS) and statistical knowledge extracted from a domain of application. Using statistical knowledge allowed us to contextualize the general knowledge for every particular situation. For each document studied, the extracted terms are ranked to highlight the most significant ones. The model was tested on a set of 17,079 French standardized discharge summaries (SDSs). The most important ICD-10 term of each SDS was ranked 1st or 2nd by the method in nearly 90% of the cases. The use of several terminologies leads to more precise indexing. The improvement achieved in the models implementation performances as a result of using semantic relationships is encouraging.

Max-margin weight learning for medical knowledge network.

PubMed

Jiang, Jingchi; Xie, Jing; Zhao, Chao; Su, Jia; Guan, Yi; Yu, Qiubin

2018-03-01

The application of medical knowledge strongly affects the performance of intelligent diagnosis, and method of learning the weights of medical knowledge plays a substantial role in probabilistic graphical models (PGMs). The purpose of this study is to investigate a discriminative weight-learning method based on a medical knowledge network (MKN). We propose a training model called the maximum margin medical knowledge network (M 3 KN), which is strictly derived for calculating the weight of medical knowledge. Using the definition of a reasonable margin, the weight learning can be transformed into a margin optimization problem. To solve the optimization problem, we adopt a sequential minimal optimization (SMO) algorithm and the clique property of a Markov network. Ultimately, M 3 KN not only incorporates the inference ability of PGMs but also deals with high-dimensional logic knowledge. The experimental results indicate that M 3 KN obtains a higher F-measure score than the maximum likelihood learning algorithm of MKN for both Chinese Electronic Medical Records (CEMRs) and Blood Examination Records (BERs). Furthermore, the proposed approach is obviously superior to some classical machine learning algorithms for medical diagnosis. To adequately manifest the importance of domain knowledge, we numerically verify that the diagnostic accuracy of M 3 KN is gradually improved as the number of learned CEMRs increase, which contain important medical knowledge. Our experimental results show that the proposed method performs reliably for learning the weights of medical knowledge. M 3 KN outperforms other existing methods by achieving an F-measure of 0.731 for CEMRs and 0.4538 for BERs. This further illustrates that M 3 KN can facilitate the investigations of intelligent healthcare. Copyright © 2018 Elsevier B.V. All rights reserved.

a Study on Satellite Diagnostic Expert Systems Using Case-Based Approach

NASA Astrophysics Data System (ADS)

Park, Young-Tack; Kim, Jae-Hoon; Park, Hyun-Soo

1997-06-01

Many research works are on going to monitor and diagnose diverse malfunctions of satellite systems as the complexity and number of satellites increase. Currently, many works on monitoring and diagnosis are carried out by human experts but there are needs to automate much of the routine works of them. Hence, it is necessary to study on using expert systems which can assist human experts routine work by doing automatically, thereby allow human experts devote their expertise more critical and important areas of monitoring and diagnosis. In this paper, we are employing artificial intelligence techniques to model human experts' knowledge and inference the constructed knowledge. Especially, case-based approaches are used to construct a knowledge base to model human expert capabilities which use previous typical exemplars. We have designed and implemented a prototype case-based system for diagnosing satellite malfunctions using cases. Our system remembers typical failure cases and diagnoses a current malfunction by indexing the case base. Diverse methods are used to build a more user friendly interface which allows human experts can build a knowledge base in as easy way.

Use of Case-Based or Hands-On Laboratory Exercises with Physiology Lectures Improves Knowledge Retention, but Veterinary Medicine Students Prefer Case-Based Activities

ERIC Educational Resources Information Center

McFee, Renee M.; Cupp, Andrea S.; Wood, Jennifer R.

2018-01-01

Didactic lectures are prevalent in physiology courses within veterinary medicine programs, but more active learning methods have also been utilized. Our goal was to identify the most appropriate learning method to augment the lecture component of our physiology course. We hypothesized that case-based learning would be well received by students and…

Sustaining clinician penetration, attitudes and knowledge in cognitive-behavioral therapy for youth anxiety

PubMed Central

2014-01-01

Background Questions remain regarding the sustainment of evidence-based practices following implementation. The present study examined the sustainment of community clinicians’ implementation (i.e., penetration) of cognitive-behavioral therapy, attitudes toward evidence-based practices, and knowledge of cognitive-behavioral therapy for youth anxiety two years following training and consultation in cognitive-behavioral therapy for youth anxiety. Methods Of the original 115 participants, 50 individuals (43%) participated in the two-year follow-up. A t- test examined sustainment in penetration over time. Hierarchical linear modeling examined sustainment in knowledge and attitudes over time. Time spent in consultation sessions was examined as a potential moderator of the change in knowledge and attitudes. Results Findings indicated sustained self-reported penetration of cognitive-behavioral therapy for anxious youth, with low fidelity to some key CBT components (i.e., exposure tasks). Follow-up knowledge was higher than at baseline but lower than it had been immediately following the consultation phase of the study. Belief in the utility of evidence-based practices was sustained. Willingness to implement an evidence-based practice if required to do so, appeal of evidence-based practices, and openness toward evidence-based practices were not sustained. Participation in consultation positively moderated changes in knowledge and some attitudes. Conclusions Sustainment varied depending on the outcome examined. Generally, greater participation in consultation predicted greater sustainment. Implications for future training include higher dosages of consultation. PMID:25030651

Uncertainty management by relaxation of conflicting constraints in production process scheduling

NASA Technical Reports Server (NTRS)

Dorn, Juergen; Slany, Wolfgang; Stary, Christian

1992-01-01

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

Conjecturing via analogical reasoning constructs ordinary students into like gifted student

NASA Astrophysics Data System (ADS)

Supratman; Ratnaningsih, N.; Ryane, S.

2017-12-01

The purpose of this study is to reveal the development of knowledge of ordinary students to be like gifted students in the classroom based on Piaget's theory. In exposing it, students are given an open problem of classical analogy. Researchers explore students who conjecture via analogical reasoning in problem solving. Of the 32 students, through the method of think out loud and the interview was completed: 25 students conjecture via analogical reasoning. Of the 25 students, all of them have almost the same character in problem solving/knowledge construction. For that, a student is taken to analyze the thinking process while solving the problem/construction of knowledge based on Piaget's theory. Based on Piaget's theory in the development of the same knowledge, gifted students and ordinary students have similar structures in final equilibrium. They begin processing: assimilation and accommodation of problem, strategies, and relationships.

Development of knowledge base of intellectual system for support of formal and informal training of IT staff

NASA Astrophysics Data System (ADS)

Kurvaeva, L. V.; Gavrilova, I. V.; Mahmutova, M. V.; Chichilanova, S. A.; Povituhin, S. A.

2018-05-01

The choice of educational digital content, according to education goals (descriptors which are formed by competences, labor functions, etc.), becomes an important practical task because of the variety of existing educational online systems that is available to persons within formal, informal IT education formats. Ontologies can form a basis for working out knowledge bases, which are center of intellectual system support in IT specialist training. The paper describes a technology of ontological model creation; analyzes the structure and the content of basic data. The structure of knowledge interrelation of the considered subject and IT education is considered. This knowledge base is applied for solving tasks of educational and methodical supplementation of educational programs of the higher and additional professional education, corporate training; for creating systems of certification and testing for students and practicing experts; for forming individual trajectories of training and career development.

Automating the design of scientific computing software

NASA Technical Reports Server (NTRS)

Kant, Elaine

1992-01-01

SINAPSE is a domain-specific software design system that generates code from specifications of equations and algorithm methods. This paper describes the system's design techniques (planning in a space of knowledge-based refinement and optimization rules), user interaction style (user has option to control decision making), and representation of knowledge (rules and objects). It also summarizes how the system knowledge has evolved over time and suggests some issues in building software design systems to facilitate reuse.

Ambulatory Morning Report: A Case-Based Method of Teaching EBM Through Experiential Learning.

PubMed

Luciano, Gina L; Visintainer, Paul F; Kleppel, Reva; Rothberg, Michael B

2016-02-01

Evidence-based medicine (EBM) skills are important to daily practice, but residents generally feel unskilled incorporating EBM into practice. The Kolb experiential learning theory, as applied to curricular planning, offers a unique methodology to help learners build an EBM skill set based on clinical experiences. We sought to blend the learner-centered, case-based merits of the morning report with an experientially based EBM curriculum. We describe and evaluate a patient-centered ambulatory morning report combining the User's Guides to the Medical Literature approach to EBM and experiential learning theory in the internal medicine department at Baystate Medical Center. The Kolb experiential learning theory postulates that experience transforms knowledge; within that premise we designed a curriculum to build EBM skills incorporating residents' patient encounters. By developing structured clinical questions based on recent clinical problems, residents activate prior knowledge. Residents acquire new knowledge through selection and evaluation of an article that addresses the structured clinical questions. Residents then apply and use new knowledge in future patient encounters. To assess the curriculum, we designed an 18-question EBM test, which addressed applied knowledge and EBM skills based on the User's Guides approach. Of the 66 residents who could participate in the curriculum, 61 (92%) completed the test. There was a modest improvement in EBM knowledge, primarily during the first year of training. Our experiential curriculum teaches EBM skills essential to clinical practice. The curriculum differs from traditional EBM curricula in that ours blends experiential learning with an EBM skill set; learners use new knowledge in real time.

Knowledge-based zonal grid generation for computational fluid dynamics

NASA Technical Reports Server (NTRS)

Andrews, Alison E.

1988-01-01

Automation of flow field zoning in two dimensions is an important step towards reducing the difficulty of three-dimensional grid generation in computational fluid dynamics. Using a knowledge-based approach makes sense, but problems arise which are caused by aspects of zoning involving perception, lack of expert consensus, and design processes. These obstacles are overcome by means of a simple shape and configuration language, a tunable zoning archetype, and a method of assembling plans from selected, predefined subplans. A demonstration system for knowledge-based two-dimensional flow field zoning has been successfully implemented and tested on representative aerodynamic configurations. The results show that this approach can produce flow field zonings that are acceptable to experts with differing evaluation criteria.

Assessing pre-service science teachers' technological pedagogical content knowledge (TPACK) through observations and lesson plans

NASA Astrophysics Data System (ADS)

Canbazoglu Bilici, Sedef; Selcen Guzey, S.; Yamak, Havva

2016-05-01

Background: Technological pedagogical content knowledge (TPACK) is critical for effective teaching with technology. However, generally science teacher education programs do not help pre-service teachers develop TPACK. Purpose: The purpose of this study was to assess pre-service science teachers' TPACK over a semester-long Science Methods. Sample: Twenty-seven pre-service science teachers took the course toward the end of their four-year teacher education program. Design and method: The study employed the case study methodology. Lesson plans and microteaching observations were used as data collection tools. Technological Pedagogical Content Knowledge-based lesson plan assessment instrument (TPACK-LpAI) and Technological Pedagogical Content Knowledge Observation Protocol (TPACK-OP) were used to analyze data obtained from observations and lesson plans. Results: The results showed that the TPACK-focused Science Methods course had an impact on pre-service teachers' TPACK to varying degrees. Most importantly, the course helped teachers gain knowledge of effective usage of educational technology tools. Conclusion: Teacher education programs should provide opportunities to pre-service teachers to develop their TPACK so that they can effectively integrate technology into their teaching.

Introducing the Big Knowledge to Use (BK2U) challenge

PubMed Central

Perl, Yehoshua; Geller, James; Halper, Michael; Ochs, Christopher; Zheng, Ling; Kapusnik-Uner, Joan

2016-01-01

The purpose of the Big Data to Knowledge (BD2K) initiative is to develop methods for discovering new knowledge from large amounts of data. However, if the resulting knowledge is so large that it resists comprehension, referred to here as Big Knowledge (BK), how can it be used properly and creatively? We call this secondary challenge, Big Knowledge to Use (BK2U). Without a high-level mental representation of the kinds of knowledge in a BK knowledgebase, effective or innovative use of the knowledge may be limited. We describe summarization and visualization techniques that capture the big picture of a BK knowledgebase, possibly created from Big Data. In this research, we distinguish between assertion BK and rule-based BK and demonstrate the usefulness of summarization and visualization techniques of assertion BK for clinical phenotyping. As an example, we illustrate how a summary of many intracranial bleeding concepts can improve phenotyping, compared to the traditional approach. We also demonstrate the usefulness of summarization and visualization techniques of rule-based BK for drug–drug interaction discovery. PMID:27750400

Radical Conversations: Part One Social-Constructivist Methods in the ABE Classroom

ERIC Educational Resources Information Center

Muth, Bill

2008-01-01

For the past 40 years adult learning theory has stressed the need for adults to share in the planning of their own learning and socially construct new knowledge by building on their background knowledge and life experiences. Despite growing acceptance of social-constructivist pedagogies in community-based literacy programs and even corporate…

Scholarship of Teaching International Business: Challenges and Opportunities

ERIC Educational Resources Information Center

Aggarwal, Raj; Goodell, John W.

2011-01-01

International business (IB) is an important topic for business schools as business is global, but much business school teaching of IB still seems inadequate. IB education can be challenging but also presents many opportunities. We need to build our knowledge base of effective IB teaching methods and procedures. Such knowledge can not only be used…

Recent Trends in Diabetes Knowledge, Perceptions, and Behaviors: Implications for National Diabetes Education

ERIC Educational Resources Information Center

Piccinino, Linda; Griffey, Susan; Gallivan, Joanne; Lotenberg, Lynne Doner; Tuncer, Diane

2015-01-01

Objectives: Examine trends in diabetes-related knowledge, perceptions, and behavior among U.S. adults with and without a diagnosis of diabetes and among subpopulations at risk. Discuss implications for national diabetes education and for the National Diabetes Education Program (NDEP) in particular. Methods: Three population-based NDEP National…

Medical Students' Knowledge about Alcohol and Drug Problems: Results of the Medical Council of Canada Examination

ERIC Educational Resources Information Center

Kahan, Meldon; Midmer, Deana; Wilson, Lynn; Borsoi, Diane

2006-01-01

Purpose: To determine knowledge of a national sample of medical students about substance withdrawal, screening and early intervention, medical and psychiatric complications of addiction, and treatment options. Methods: Based on learning objectives developed by medical faculty, twenty-two questions on addictions were included in the 1998 Canadian…

Cumulating the Intellectual Gold of Case Study Research.

ERIC Educational Resources Information Center

Rodgers, Robert; Jensen, Jason L.

2001-01-01

Looks at criticisms of public administration research: (1) knowledge in the field is not being accumulated, and (2) the research has low quality. Proposes meta-analysis as a solution to the first problem. Suggests that quality judgments should be based on knowledge cumulation, which acknowledges the value of all research methods. (Contains 48…

Integration of Mathematical and Natural-Science Knowledge in School Students' Project-Based Activity

ERIC Educational Resources Information Center

Luneeva, Olga L.; Zakirova, Venera G.

2017-01-01

New educational standards implementation prioritizes the projective beginning of training in school education. Therefore, consideration of educational activity only as the process of obtaining ready knowledge should be abandoned. Thus the relevance of the studied problem is substantiated by the need to develop methodical works connected with the…

Analysis of Tasks in Pre-Service Elementary Teacher Education Courses

ERIC Educational Resources Information Center

Sierpinska, Anna; Osana, Helena

2012-01-01

This paper presents some results of research aimed at contributing to the development of a professional knowledge base for teachers of elementary mathematics methods courses, called here "teacher educators." We propose that a useful unit of analysis for this knowledge could be the tasks in which teacher-educators engage pre-service…

Using Students' Knowledge to Generate Individual Feedback: Concept for an Intelligent Educational System on Logistics.

ERIC Educational Resources Information Center

Ziems, Dietrich; Neumann, Gaby

1997-01-01

Discusses a methods kit for interactive problem-solving exercises in engineering education as well as a methodology for intelligent evaluation of solutions. The quality of a system teaching logistics thinking can be improved using artificial intelligence. Embedding a rule-based diagnosis module that evaluates the student's knowledge actively…

Work-Based Learning: Valuing Practice as an Educational Event

ERIC Educational Resources Information Center

Raelin, Joseph A.

2010-01-01

The dominant method of providing formal knowledge to students in education in North America is through classroom training. The focus of this effort is on the delivery of a broad range of conceptual knowledge and skills in various liberal and professional fields of endeavor. Besides classroom instruction, the other predominant mode is through…

Balancing Act: How to Capture Knowledge without Killing It.

ERIC Educational Resources Information Center

Brown, John Seely; Duguid, Paul

2000-01-01

Top-down processes for institutionalizing ideas can stifle creativity. Xerox researchers learned how to combine process-based and practice-based methods in order to disseminate best practices from a community of repair technicians. (JOW)

Just-in-Time Teaching, Just-in-Need Learning: Designing towards Optimized Pedagogical Outcomes

ERIC Educational Resources Information Center

Killi, Steinar; Morrison, Andrew

2015-01-01

Teaching methods are constantly being changed, new ones are developed and old methods have undergone a renaissance. Two main approaches to teaching prevail: a) lecture-based and project-based and b) an argumentative approach to known knowledge or learning by exploration. Today, there is a balance between these two approaches, and they are more…

Accurate identification of RNA editing sites from primitive sequence with deep neural networks.

PubMed

Ouyang, Zhangyi; Liu, Feng; Zhao, Chenghui; Ren, Chao; An, Gaole; Mei, Chuan; Bo, Xiaochen; Shu, Wenjie

2018-04-16

RNA editing is a post-transcriptional RNA sequence alteration. Current methods have identified editing sites and facilitated research but require sufficient genomic annotations and prior-knowledge-based filtering steps, resulting in a cumbersome, time-consuming identification process. Moreover, these methods have limited generalizability and applicability in species with insufficient genomic annotations or in conditions of limited prior knowledge. We developed DeepRed, a deep learning-based method that identifies RNA editing from primitive RNA sequences without prior-knowledge-based filtering steps or genomic annotations. DeepRed achieved 98.1% and 97.9% area under the curve (AUC) in training and test sets, respectively. We further validated DeepRed using experimentally verified U87 cell RNA-seq data, achieving 97.9% positive predictive value (PPV). We demonstrated that DeepRed offers better prediction accuracy and computational efficiency than current methods with large-scale, mass RNA-seq data. We used DeepRed to assess the impact of multiple factors on editing identification with RNA-seq data from the Association of Biomolecular Resource Facilities and Sequencing Quality Control projects. We explored developmental RNA editing pattern changes during human early embryogenesis and evolutionary patterns in Drosophila species and the primate lineage using DeepRed. Our work illustrates DeepRed's state-of-the-art performance; it may decipher the hidden principles behind RNA editing, making editing detection convenient and effective.

Knowledge and Acceptability of Long-Acting Reversible Contraception Among Adolescent Women Receiving School-Based Primary Care Services.

PubMed

Hoopes, Andrea J; Ahrens, Kym R; Gilmore, Kelly; Cady, Janet; Haaland, Wren L; Amies Oelschlager, Anne-Marie; Prager, Sarah

2016-07-01

A key strategy to reduce unintended adolescent pregnancies is to expand access to long-acting reversible contraceptive (LARC) methods, including intrauterine devices and subdermal contraceptive implants. LARC services can be provided to adolescents in school-based health and other primary care settings, yet limited knowledge and negative attitudes about LARC methods may influence adolescents' utilization of these methods. This study aimed to evaluate correlates of knowledge and acceptability of LARC methods among adolescent women at a school-based health center (SBHC). In this cross-sectional study, female patients receiving care at 2 SBHCs in Seattle, Washington completed an electronic survey about sexual and reproductive health. Primary outcomes were (1) LARC knowledge as measured by percentage correct of 10 true-false questions and (2) LARC acceptability as measured by participants reporting either liking the idea of having an intrauterine device (IUD)/subdermal implant or currently using one. A total of 102 students diverse in race/ethnicity and socioeconomic backgrounds completed the survey (mean age 16.2 years, range 14.4-19.1 years). Approximately half reported a lifetime history of vaginal sex. Greater LARC knowledge was associated with white race (regression coefficient [coef] = 26.8; 95% CI 13.3-40.4; P < .001), history of vaginal intercourse (coef = 29.9; 95% CI 17.1-42.7; P < .001), and current/prior LARC use (coef = 22.8; 95% CI 6.5-40.0; P = .007). Older age was associated with lower IUD acceptability (odds ratio = 0.53, 95% CI 0.30-0.94; P = .029) while history of intercourse was associated with greater implant acceptability (odds ratio 5.66, 95% CI 1.46-22.0; P = .012). Adolescent women in this SBHC setting had variable knowledge and acceptability of LARC. A history of vaginal intercourse was the strongest predictor of LARC acceptability. Our findings suggest a need for LARC counseling and education strategies, particularly for young women from diverse cultural backgrounds and those with less sexual experience. © The Author(s) 2016.

Integrative vs. Traditional Learning from the Student Perspective

PubMed Central

Kadmon, Guni; Schmidt, Jan; De Cono, Nicola; Kadmon, Martina

2011-01-01

Background: The interdisciplinary surgery block of the reformed undergraduate curriculum HeiCuMed includes daily cycles of interactive case-based seminars, problem-based tutorials, case presentation by students, skills and communication training, and bedside teaching. The teaching doctors receive didactic training. In contrast, the previous traditional course was based on lectures with only two weekly hours of bedside teaching. Didactic training was not available. Objective: The present work aims at analysing the importance of active participation of students and the didactic components of the reformed and traditional curricula, which contribute to successful learning as evaluated by the students. Method: Differentiated student evaluations of the undergraduate surgical courses between 1999 and 2008 were examined by correlation and regression analyses. Results: The evaluation scores for organisation, dedication of the teaching staff, their ability to make lessons interesting and complex topics easily understandable, and the subjective gain of knowledge were significantly better in HeiCuMed than in the traditional curriculum. However, the dependence of knowledge gain on the didactic quality was the same in both curricula. The quality of discussions and the ability of the teaching doctors to promote active student participation were important to the subjective gain of knowledge in both seminars and practical courses of the reformed curriculum as well as for the overall evaluation of the practical courses but not the gain of knowledge in the traditional curriculum. Conclusion: The findings confirm psychological-educational perceptions, that competent implementation of integrative didactical methods is more important to successful teaching and the subjective gain of knowledge than knowledge transfer by traditional classroom teaching. PMID:21818238

Towards transdisciplinarity in Arctic sustainability knowledge co-production: Socially-Oriented Observations as a participatory integrated activity

NASA Astrophysics Data System (ADS)

Vlasova, Tatiana; Volkov, Sergey

2016-09-01

The paper is an attempt to tie together main biogeophysical and social science projects under the auspice of interdisciplinary sustainability science development. Special attention is put to the necessity of the transdisciplinary knowledge co-production based on activities and problem-solutions approaches. It puts attention to the role of monitoring activities in sustainability interdisciplinary science and transdisciplinary knowledge evolution in the Arctic. Socially focused monitoring named Socially-Oriented Observations creating a transdisciplinary space is viewed as one of sources of learning and transformations towards sustainability making possible to shape rapid changes happening in the Arctic based on sustainability knowledge co-production. Continuous Socially-Oriented Observations integrating scientific, education and monitoring methods enables to define adaptation and transformation pathways in the Arctic - the most rapidly changing region of our planet. Socially-Oriented Observations are based on the existing and developing interdisciplinary scientific approaches emerged within natural science and social science projects, sustainable development and resilience concepts putting principle attention to building sustainable and resilient socio-ecological systems. It is argued that the Arctic sustainability science is a valuable component of the whole and broader system of the Arctic Sustainability knowledge co-produced with the help of transdisciplinary approaches integrating science, local/traditional knowledge, entrepreneurship, education, decision-making. Socially-Oriented Observations are designed to be a transdisciplinary interactive continuous participatory process empowering deliberate choices of people that can shape the changes and enable transformation towards sustainability. Approaches of Socially-Oriented Observations and methods of implementation that have been developed since the IPY 2007/2008 and being practiced in different regions of the Arctic are discussed.

Evaluating the Sharing Stories youth theatre program: an interactive theatre and drama-based strategy for sexual health promotion among multicultural youth.

PubMed

Roberts, Meagan; Lobo, Roanna; Sorenson, Anne

2017-03-01

Issue addressed Rates of sexually transmissible infections among young people are high, and there is a need for innovative, youth-focused sexual health promotion programs. This study evaluated the effectiveness of the Sharing Stories youth theatre program, which uses interactive theatre and drama-based strategies to engage and educate multicultural youth on sexual health issues. The effectiveness of using drama-based evaluation methods is also discussed. Methods The youth theatre program participants were 18 multicultural youth from South East Asian, African and Middle Eastern backgrounds aged between 14 and 21 years. Four sexual health drama scenarios and a sexual health questionnaire were used to measure changes in knowledge and attitudes. Results Participants reported being confident talking to and supporting their friends with regards to safe sex messages, improved their sexual health knowledge and demonstrated a positive shift in their attitudes towards sexual health. Drama-based evaluation methods were effective in engaging multicultural youth and worked well across the cultures and age groups. Conclusions Theatre and drama-based sexual health promotion strategies are an effective method for up-skilling young people from multicultural backgrounds to be peer educators and good communicators of sexual health information. Drama-based evaluation methods are engaging for young people and an effective way of collecting data from culturally diverse youth. So what? This study recommends incorporating interactive and arts-based strategies into sexual health promotion programs for multicultural youth. It also provides guidance for health promotion practitioners evaluating an arts-based health promotion program using arts-based data collection methods.

Subject knowledge in the health sciences library: an online survey of Canadian academic health sciences librarians

PubMed Central

Watson, Erin M.

2005-01-01

Objectives: This study investigated whether Canadian academic health sciences librarians found knowledge of the health sciences to be important and, if so, how they acquired and maintained this knowledge. Methods: Data were gathered using a Web-based questionnaire made available to Canadian academic health sciences librarians. Results: Respondents recognized the need for subject knowledge: 93.3% of respondents indicated that subject knowledge was “very important” or “somewhat important” to doing their job. However, few respondents felt that holding a degree in the health sciences was necessary. Respondents reported devoting on average more than 6 hours per week to continuing education through various means. Reading or browsing health sciences journals, visiting Websites, studying independently, and participating in professional associations were identified by the largest number of participants as the best ways to become and stay informed. Conclusions: Although more research needs to be done with a larger sample, subject knowledge continues to be important to Canadian academic health sciences librarians. Continuing education, rather than formal degree studies, is the method of choice for obtaining and maintaining this knowledge. PMID:16239942

Knowledge Discovery from Vibration Measurements

PubMed Central

Li, Jian; Wang, Daoyao

2014-01-01

The framework as well as the particular algorithms of pattern recognition process is widely adopted in structural health monitoring (SHM). However, as a part of the overall process of knowledge discovery from data bases (KDD), the results of pattern recognition are only changes and patterns of changes of data features. In this paper, based on the similarity between KDD and SHM and considering the particularity of SHM problems, a four-step framework of SHM is proposed which extends the final goal of SHM from detecting damages to extracting knowledge to facilitate decision making. The purposes and proper methods of each step of this framework are discussed. To demonstrate the proposed SHM framework, a specific SHM method which is composed by the second order structural parameter identification, statistical control chart analysis, and system reliability analysis is then presented. To examine the performance of this SHM method, real sensor data measured from a lab size steel bridge model structure are used. The developed four-step framework of SHM has the potential to clarify the process of SHM to facilitate the further development of SHM techniques. PMID:24574933

Oral vocabulary training program for Spanish third-graders with low socio-economic status: A randomized controlled trial

PubMed Central

Simpson, Ian Craig; Valle, Araceli; Defior, Sylvia

2017-01-01

Although the importance of vocabulary training in English speaking countries is well recognized and has been extensively studied, the same is not true for Spanish–few evidence based vocabulary studies for Spanish-speaking children have been reported. Here, two rich oral vocabulary training programs (definition and context), based on literature about vocabulary instruction for English-speaking children, were developed and applied in a sample of 100 Spanish elementary school third-graders recruited from areas of predominantly low socio-economic status (SES). Compared to an alternative read-aloud method which served as the control, both explicit methods were more effective in teaching word meanings when assessed immediately after the intervention. Nevertheless, five months later, only the definition group continued to demonstrate significant vocabulary knowledge gains. The definition method was more effective in specifically teaching children word meanings and, more broadly, in helping children organize and express knowledge of words. We recommend the explicit and rich vocabulary instruction as a means to fostering vocabulary knowledge in low SES children. PMID:29186175

Utility of Combining a Simulation-Based Method With a Lecture-Based Method for Fundoscopy Training in Neurology Residency.

PubMed

Gupta, Deepak K; Khandker, Namir; Stacy, Kristin; Tatsuoka, Curtis M; Preston, David C

2017-10-01

Fundoscopic examination is an essential component of the neurologic examination. Competence in its performance is mandated as a required clinical skill for neurology residents by the American Council of Graduate Medical Education. Government and private insurance agencies require its performance and documentation for moderate- and high-level neurologic evaluations. Traditionally, assessment and teaching of this key clinical examination technique have been difficult in neurology residency training. To evaluate the utility of a simulation-based method and the traditional lecture-based method for assessment and teaching of fundoscopy to neurology residents. This study was a prospective, single-blinded, education research study of 48 neurology residents recruited from July 1, 2015, through June 30, 2016, at a large neurology residency training program. Participants were equally divided into control and intervention groups after stratification by training year. Baseline and postintervention assessments were performed using questionnaire, survey, and fundoscopy simulators. After baseline assessment, both groups initially received lecture-based training, which covered fundamental knowledge on the components of fundoscopy and key neurologic findings observed on fundoscopic examination. The intervention group additionally received simulation-based training, which consisted of an instructor-led, hands-on workshop that covered practical skills of performing fundoscopic examination and identifying neurologically relevant findings on another fundoscopy simulator. The primary outcome measures were the postintervention changes in fundoscopy knowledge, skills, and total scores. A total of 30 men and 18 women were equally distributed between the 2 groups. The intervention group had significantly higher mean (SD) increases in skills (2.5 [2.3] vs 0.8 [1.8], P = .01) and total (9.3 [4.3] vs 5.3 [5.8], P = .02) scores compared with the control group. Knowledge scores (6.8 [3.3] vs 4.5 [4.9], P = .11) increased nonsignificantly in both groups. This study supports the use of a simulation-based method as a supplementary tool to the lecture-based method in the assessment and teaching of fundoscopic examination in neurology residency.

Factors Associated with Knowledge of Diabetes in Patients with Type 2 Diabetes Using the Diabetes Knowledge Test Validated with Rasch Analysis

PubMed Central

Fenwick, Eva K.; Xie, Jing; Rees, Gwyn; Finger, Robert P.; Lamoureux, Ecosse L.

2013-01-01

Objective In patients with Type 2 diabetes, to determine the factors associated with diabetes knowledge, derived from Rasch analysis, and compare results with a traditional raw scoring method. Research Design & Methods Participants in this cross-sectional study underwent a comprehensive clinical and biochemical assessment. Diabetes knowledge (main outcome) was assessed using the Diabetes Knowledge Test (DKT) which was psychometrically validated using Rasch analysis. The relationship between diabetes knowledge and risk factors identified during univariate analyses was examined using multivariable linear regression. The results using raw and Rasch-transformed methods were descriptively compared. Results 181 patients (mean age±standard deviation = 66.97±9.17 years; 113 (62%) male) were included. Using Rasch-derived DKT scores, those with greater education (β = 1.14; CI: 0.25,2.04, p = 0.013); had seen an ophthalmologist (β = 1.65; CI: 0.63,2.66, p = 0.002), and spoke English at home (β = 1.37; CI: 0.43,2.31, p = 0.005) had significantly better diabetes knowledge than those with less education, had not seen an ophthalmologist and spoke a language other than English, respectively. Patients who were members of the National Diabetes Service Scheme (NDSS) and had seen a diabetes educator also had better diabetes knowledge than their counterparts. Higher HbA1c level was independently associated with worse diabetes knowledge. Using raw measures, access to an ophthalmologist and NDSS membership were not independently associated with diabetes knowledge. Conclusions Sociodemographic, clinical and service use factors were independently associated with diabetes knowledge based on both raw scores and Rasch-derived scores, which supports the implementation of targeted interventions to improve patients' knowledge. Choice of psychometric analytical method can affect study outcomes and should be considered during intervention development. PMID:24312484

Model-based segmentation of hand radiographs

NASA Astrophysics Data System (ADS)

Weiler, Frank; Vogelsang, Frank

1998-06-01

An important procedure in pediatrics is to determine the skeletal maturity of a patient from radiographs of the hand. There is great interest in the automation of this tedious and time-consuming task. We present a new method for the segmentation of the bones of the hand, which allows the assessment of the skeletal maturity with an appropriate database of reference bones, similar to the atlas based methods. The proposed algorithm uses an extended active contour model for the segmentation of the hand bones, which incorporates a-priori knowledge of shape and topology of the bones in an additional energy term. This `scene knowledge' is integrated in a complex hierarchical image model, that is used for the image analysis task.

Using Knowledge Base for Event-Driven Scheduling of Web Monitoring Systems

NASA Astrophysics Data System (ADS)

Kim, Yang Sok; Kang, Sung Won; Kang, Byeong Ho; Compton, Paul

Web monitoring systems report any changes to their target web pages by revisiting them frequently. As they operate under significant resource constraints, it is essential to minimize revisits while ensuring minimal delay and maximum coverage. Various statistical scheduling methods have been proposed to resolve this problem; however, they are static and cannot easily cope with events in the real world. This paper proposes a new scheduling method that manages unpredictable events. An MCRDR (Multiple Classification Ripple-Down Rules) document classification knowledge base was reused to detect events and to initiate a prompt web monitoring process independent of a static monitoring schedule. Our experiment demonstrates that the approach improves monitoring efficiency significantly.

NASA's online machine aided indexing system

NASA Technical Reports Server (NTRS)

Silvester, June P.; Genuardi, Michael T.; Klingbiel, Paul H.

1993-01-01

This report describes the NASA Lexical Dictionary, a machine aided indexing system used online at the National Aeronautics and Space Administration's Center for Aerospace Information (CASI). This system is comprised of a text processor that is based on the computational, non-syntactic analysis of input text, and an extensive 'knowledge base' that serves to recognize and translate text-extracted concepts. The structure and function of the various NLD system components are described in detail. Methods used for the development of the knowledge base are discussed. Particular attention is given to a statistically-based text analysis program that provides the knowledge base developer with a list of concept-specific phrases extracted from large textual corpora. Production and quality benefits resulting from the integration of machine aided indexing at CASI are discussed along with a number of secondary applications of NLD-derived systems including on-line spell checking and machine aided lexicography.

Sticky knowledge: A possible model for investigating implementation in healthcare contexts

PubMed Central

Elwyn, Glyn; Taubert, Mark; Kowalczuk, Jenny

2007-01-01

Background In health care, a well recognized gap exists between what we know should be done based on accumulated evidence and what we actually do in practice. A body of empirical literature shows organizations, like individuals, are difficult to change. In the business literature, knowledge management and transfer has become an established area of theory and practice, whilst in healthcare it is only starting to establish a firm footing. Knowledge has become a business resource, and knowledge management theorists and practitioners have examined how knowledge moves in organisations, how it is shared, and how the return on knowledge capital can be maximised to create competitive advantage. New models are being considered, and we wanted to explore the applicability of one of these conceptual models to the implementation of evidence-based practice in healthcare systems. Methods The application of a conceptual model called sticky knowledge, based on an integration of communication theory and knowledge transfer milestones, into a scenario of attempting knowledge transfer in primary care. Results We describe Szulanski's model, the empirical work he conducted, and illustrate its potential applicability with a hypothetical healthcare example based on improving palliative care services. We follow a doctor through two different posts and analyse aspects of knowledge transfer in different primary care settings. The factors included in the sticky knowledge model include: causal ambiguity, unproven knowledge, motivation of source, credibility of source, recipient motivation, recipient absorptive capacity, recipient retentive capacity, barren organisational context, and arduous relationship between source and recipient. We found that we could apply all these factors to the difficulty of implementing new knowledge into practice in primary care settings. Discussion Szulanski argues that knowledge factors play a greater role in the success or failure of a knowledge transfer than has been suspected, and we consider that this conjecture requires further empirical work in healthcare settings. PMID:18096040

A feature dictionary supporting a multi-domain medical knowledge base.

PubMed

Naeymi-Rad, F

1989-01-01

Because different terminology is used by physicians of different specialties in different locations to refer to the same feature (signs, symptoms, test results), it is essential that our knowledge development tools provide a means to access a common pool of terms. This paper discusses the design of an online medical dictionary that provides a solution to this problem for developers of multi-domain knowledge bases for MEDAS (Medical Emergency Decision Assistance System). Our Feature Dictionary supports phrase equivalents for features, feature interactions, feature classifications, and translations to the binary features generated by the expert during knowledge creation. It is also used in the conversion of a domain knowledge to the database used by the MEDAS inference diagnostic sessions. The Feature Dictionary also provides capabilities for complex queries across multiple domains using the supported relations. The Feature Dictionary supports three methods for feature representation: (1) for binary features, (2) for continuous valued features, and (3) for derived features.

Learning from simple ebooks, online cases or classroom teaching when acquiring complex knowledge. A randomized controlled trial in respiratory physiology and pulmonology.

PubMed

Worm, Bjarne Skjødt

2013-01-01

E-learning is developing fast because of the rapid increased use of smartphones, tablets and portable computers. We might not think of it as e-learning, but today many new e-books are in fact very complex electronic teaching platforms. It is generally accepted that e-learning is as effective as classroom teaching methods, but little is known about its value in relaying contents of different levels of complexity to students. We set out to investigate e-learning effects on simple recall and complex problem-solving compared to classroom teaching. 63 nurses specializing in anesthesiology were evenly randomized into three groups. They were given internet-based knowledge tests before and after attending a teaching module about respiratory physiology and pulmonology. The three groups was either an e-learning group with eBook teaching material, an e-learning group with case-based teaching or a group with face-to-face case-based classroom teaching. After the module the students were required to answer a post-test. Time spent and the number of logged into the system was also measured. For simple recall, all methods were equally effective. For problem-solving, the eCase group achieved a comparable knowledge level to classroom teaching, while textbook learning was inferior to both (p<0.01). The textbook group also spent the least amount of time on acquiring knowledge (33 minutes, p<0.001), while the eCase group spent significantly more time on the subject (53 minutes, p<0.001) and logged into the system significantly more (2.8 vs 1.6, p<0.001). E-learning based cases are an effective tool for teaching complex knowledge and problem-solving ability, but future studies using higher-level e-learning are encouraged.Simple recall skills, however, do not require any particular learning method.

The Effectiveness of TBL with Real Patients in Neurology Education in Terms of Knowledge Retention, In-Class Engagement, and Learner Reactions

ERIC Educational Resources Information Center

Alimoglu, Mustafa Kemal; Yardim, Selda; Uysal, Hilmi

2017-01-01

In our medical school, we changed from a lecture-based method to a team-based learning (TBL) method to teach "polyneuropathies" in the neurology clerkship starting from the 2014 to 2015 academic year. Real patients were used instead of written scenarios in TBL sessions. This study aimed to compare former lecture-based and the current TBL…

EMR-based medical knowledge representation and inference via Markov random fields and distributed representation learning.

PubMed

Zhao, Chao; Jiang, Jingchi; Guan, Yi; Guo, Xitong; He, Bin

2018-05-01

Electronic medical records (EMRs) contain medical knowledge that can be used for clinical decision support (CDS). Our objective is to develop a general system that can extract and represent knowledge contained in EMRs to support three CDS tasks-test recommendation, initial diagnosis, and treatment plan recommendation-given the condition of a patient. We extracted four kinds of medical entities from records and constructed an EMR-based medical knowledge network (EMKN), in which nodes are entities and edges reflect their co-occurrence in a record. Three bipartite subgraphs (bigraphs) were extracted from the EMKN, one to support each task. One part of the bigraph was the given condition (e.g., symptoms), and the other was the condition to be inferred (e.g., diseases). Each bigraph was regarded as a Markov random field (MRF) to support the inference. We proposed three graph-based energy functions and three likelihood-based energy functions. Two of these functions are based on knowledge representation learning and can provide distributed representations of medical entities. Two EMR datasets and three metrics were utilized to evaluate the performance. As a whole, the evaluation results indicate that the proposed system outperformed the baseline methods. The distributed representation of medical entities does reflect similarity relationships with respect to knowledge level. Combining EMKN and MRF is an effective approach for general medical knowledge representation and inference. Different tasks, however, require individually designed energy functions. Copyright © 2018 Elsevier B.V. All rights reserved.

MMKG: An approach to generate metallic materials knowledge graph based on DBpedia and Wikipedia

NASA Astrophysics Data System (ADS)

Zhang, Xiaoming; Liu, Xin; Li, Xin; Pan, Dongyu

2017-02-01

The research and development of metallic materials are playing an important role in today's society, and in the meanwhile lots of metallic materials knowledge is generated and available on the Web (e.g., Wikipedia) for materials experts. However, due to the diversity and complexity of metallic materials knowledge, the knowledge utilization may encounter much inconvenience. The idea of knowledge graph (e.g., DBpedia) provides a good way to organize the knowledge into a comprehensive entity network. Therefore, the motivation of our work is to generate a metallic materials knowledge graph (MMKG) using available knowledge on the Web. In this paper, an approach is proposed to build MMKG based on DBpedia and Wikipedia. First, we use an algorithm based on directly linked sub-graph semantic distance (DLSSD) to preliminarily extract metallic materials entities from DBpedia according to some predefined seed entities; then based on the results of the preliminary extraction, we use an algorithm, which considers both semantic distance and string similarity (SDSS), to achieve the further extraction. Second, due to the absence of materials properties in DBpedia, we use an ontology-based method to extract properties knowledge from the HTML tables of corresponding Wikipedia Web pages for enriching MMKG. Materials ontology is used to locate materials properties tables as well as to identify the structure of the tables. The proposed approach is evaluated by precision, recall, F1 and time performance, and meanwhile the appropriate thresholds for the algorithms in our approach are determined through experiments. The experimental results show that our approach returns expected performance. A tool prototype is also designed to facilitate the process of building the MMKG as well as to demonstrate the effectiveness of our approach.

Knowledge-based grouping of modeled HLA peptide complexes.

PubMed

Kangueane, P; Sakharkar, M K; Lim, K S; Hao, H; Lin, K; Chee, R E; Kolatkar, P R

2000-05-01

Human leukocyte antigens are the most polymorphic of human genes and multiple sequence alignment shows that such polymorphisms are clustered in the functional peptide binding domains. Because of such polymorphism among the peptide binding residues, the prediction of peptides that bind to specific HLA molecules is very difficult. In recent years two different types of computer based prediction methods have been developed and both the methods have their own advantages and disadvantages. The nonavailability of allele specific binding data restricts the use of knowledge-based prediction methods for a wide range of HLA alleles. Alternatively, the modeling scheme appears to be a promising predictive tool for the selection of peptides that bind to specific HLA molecules. The scoring of the modeled HLA-peptide complexes is a major concern. The use of knowledge based rules (van der Waals clashes and solvent exposed hydrophobic residues) to distinguish binders from nonbinders is applied in the present study. The rules based on (1) number of observed atomic clashes between the modeled peptide and the HLA structure, and (2) number of solvent exposed hydrophobic residues on the modeled peptide effectively discriminate experimentally known binders from poor/nonbinders. Solved crystal complexes show no vdW Clash (vdWC) in 95% cases and no solvent exposed hydrophobic peptide residues (SEHPR) were seen in 86% cases. In our attempt to compare experimental binding data with the predicted scores by this scoring scheme, 77% of the peptides are correctly grouped as good binders with a sensitivity of 71%.

An avatar based education application to improve patients' knowledge of and response to heart attack symptoms: a pragmatic randomized controlled trial protocol.

PubMed

Tongpeth, Jintana; Du, Huiyun; Clark, Robyn

2018-06-19

To evaluate the effectiveness of an interactive, avatar based education application to improve knowledge of and response to heart attack symptoms in people who are at risk of a heart attack. Poor knowledge of heart attack symptoms is recognised as a significant barrier to timely medical treatment. Numerous studies have demonstrated that technology can assist in patient education to improve knowledge and self-care. A single-center, non-blinded, two parallel groups, pragmatic randomized controlled trial. Seventy patients will be recruited from the coronary care unit of a public hospital. Eligible participants will be randomised to either the usual care or the intervention group (usual care plus avatar-based heart attack education app). The primary outcome of this study is knowledge. Secondary outcomes include response to heart attack symptoms, health service use and satisfaction. Study participants will be followed-up for six months. This study will evaluate the avatar based education app as a method to deliver vital information to patients. Participants' knowledge of and response to heart attack symptoms, as well as their health service use, will be assessed to evaluate the intervention effectiveness. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Practice-Based Evidence: Delivering What Works

ERIC Educational Resources Information Center

Brendtro, Larry K.; Mitchell, Martin L.

2012-01-01

Many methods claim to be Evidence-Based Practices. Yet success comes not from a particular practice, but principles that underlie all effective helping. This article uses the principle of consilience to tap knowledge from science, values, and practical experience.

Randomized controlled trial comparing tailoring methods of multimedia-based fall prevention education for community-dwelling older adults.

PubMed

Schepens, Stacey L; Panzer, Victoria; Goldberg, Allon

2011-01-01

We attempted to determine whether multimedia fall prevention education using different instructional strategies increases older adults' knowledge of fall threats and their fall prevention behaviors. Fifty-three community-dwelling older adults were randomized to iwo educational groups or a control group. Multimedia-based educational interventions to increase fall threats knowledge and encourage fall prevention behaviors had two tailoring strategies: (1) improve content realism for individual learners (authenticity group) and (2) highlight program goals and benefits while using participants' content selections (motivation group). Knowledge was measured at baseline and 1-mo follow-up. Participants recorded prevention behaviors for 1 mo. Intervention group participants showed greater knowledge gains and posttest knowledge than did control group participants. The motivation group engaged in more prevention behaviors over 1 mo than did the other groups. Tailoring fall prevention education by addressing authenticity and motivation successfully improved fall threats knowledge. Combining motivational strategies with multimedia education increased the effectiveness of the intervention in encouraging fall prevention behaviors.

Detection of cyst using image segmentation and building knowledge-based intelligent decision support system as an aid to telemedicine

NASA Astrophysics Data System (ADS)

Janet, J.; Natesan, T. R.; Santhosh, Ramamurthy; Ibramsha, Mohideen

2005-02-01

An intelligent decision support tool to the Radiologist in telemedicine is described. Medical prescriptions are given based on the images of cyst that has been transmitted over computer networks to the remote medical center. The digital image, acquired by sonography, is converted into an intensity image. This image is then subjected to image preprocessing which involves correction methods to eliminate specific artifacts. The image is resized into a 256 x 256 matrix by using bilinear interpolation method. The background area is detected using distinct block operation. The area of the cyst is calculated by removing the background area from the original image. Boundary enhancement and morphological operations are done to remove unrelated pixels. This gives us the cyst volume. This segmented image of the cyst is sent to the remote medical center for analysis by Knowledge based artificial Intelligent Decision Support System (KIDSS). The type of cyst is detected and reported to the control mechanism of KIDSS. Then the inference engine compares this with the knowledge base and gives appropriate medical prescriptions or treatment recommendations by applying reasoning mechanisms at the remote medical center.

Multi-frame knowledge based text enhancement for mobile phone captured videos

NASA Astrophysics Data System (ADS)

Ozarslan, Suleyman; Eren, P. Erhan

2014-02-01

In this study, we explore automated text recognition and enhancement using mobile phone captured videos of store receipts. We propose a method which includes Optical Character Resolution (OCR) enhanced by our proposed Row Based Multiple Frame Integration (RB-MFI), and Knowledge Based Correction (KBC) algorithms. In this method, first, the trained OCR engine is used for recognition; then, the RB-MFI algorithm is applied to the output of the OCR. The RB-MFI algorithm determines and combines the most accurate rows of the text outputs extracted by using OCR from multiple frames of the video. After RB-MFI, KBC algorithm is applied to these rows to correct erroneous characters. Results of the experiments show that the proposed video-based approach which includes the RB-MFI and the KBC algorithm increases the word character recognition rate to 95%, and the character recognition rate to 98%.

Towards an Age-Phenome Knowledge-base

PubMed Central

2011-01-01

Background Currently, data about age-phenotype associations are not systematically organized and cannot be studied methodically. Searching for scientific articles describing phenotypic changes reported as occurring at a given age is not possible for most ages. Results Here we present the Age-Phenome Knowledge-base (APK), in which knowledge about age-related phenotypic patterns and events can be modeled and stored for retrieval. The APK contains evidence connecting specific ages or age groups with phenotypes, such as disease and clinical traits. Using a simple text mining tool developed for this purpose, we extracted instances of age-phenotype associations from journal abstracts related to non-insulin-dependent Diabetes Mellitus. In addition, links between age and phenotype were extracted from clinical data obtained from the NHANES III survey. The knowledge stored in the APK is made available for the relevant research community in the form of 'Age-Cards', each card holds the collection of all the information stored in the APK about a particular age. These Age-Cards are presented in a wiki, allowing community review, amendment and contribution of additional information. In addition to the wiki interaction, complex searches can also be conducted which require the user to have some knowledge of database query construction. Conclusions The combination of a knowledge model based repository with community participation in the evolution and refinement of the knowledge-base makes the APK a useful and valuable environment for collecting and curating existing knowledge of the connections between age and phenotypes. PMID:21651792

Pressure area care: an exploration of Greek nurses' knowledge and practice.

PubMed

Panagiotopoulou, Kalliopi; Kerr, Susan M

2002-11-01

Despite a plethora of information on the prevention of pressure sores, they remain a significant problem in both hospital and community settings. The need to reduce the incidence of pressure sores has been well documented; unfortunately there is little evidence to suggest improvement. The reasons for this lack of improvement have been explored, but the picture remains unclear. While some studies have suggested that nurses have the appropriate knowledge to prevent pressure sores developing (but do not use their knowledge), others suggest that nurses' knowledge of preventive strategies is deficient. In Greece, similarly to the United Kingdom (UK), the incidence of pressure sores is high. There is currently no evidence on Greek nurses' knowledge and practice and therefore no baseline on which to build, in terms of improving practice. The purpose of this study was to explore Greek nurses' knowledge of 'risk factors', 'areas at risk' and 'recommended preventive strategies' in relation to pressure area care. In addition, information was sought on nurses' 'current preventive practice' and any barriers to 'good practice'. The study was exploratory and descriptive, adopting a cross-sectional survey approach. The sample was drawn from the population of nurses working in a military hospital near Athens. The data were collected over a 4-week period in June 2000, using a self-completed questionnaire. Although the knowledge-base of many of the nurses was good in relation to 'risk factors' and 'areas at risk', a significant proportion were unaware that methods such as 'massage' and 'donuts' are no longer recommended. This lack of knowledge influenced practice with these methods commonly being used. In relation to barriers to good practice, a significant proportion of nurses reported that they could not access, read or understand research findings. This has obvious implications for the implementation of evidence-based practice. The results of this study suggest that the knowledge and practice of participants could be improved. It is of particular concern that methods known to be detrimental were in common use. Finally, there is a need to improve the research skills of Greek nurses in order to provide them with the appropriate knowledge to use research findings.

Team knowledge research: emerging trends and critical needs.

PubMed

Wildman, Jessica L; Thayer, Amanda L; Pavlas, Davin; Salas, Eduardo; Stewart, John E; Howse, William R

2012-02-01

This article provides a systematic review of the team knowledge literature and guidance for further research. Recent research has called attention to the need for the improved study and understanding of team knowledge. Team knowledge refers to the higher level knowledge structures that emerge from the interactions of individual team members. We conducted a systematic review of the team knowledge literature, focusing on empirical work that involves the measurement of team knowledge constructs. For each study, we extracted author degree area, study design type, study setting, participant type, task type, construct type, elicitation method, aggregation method, measurement timeline, and criterion domain. Our analyses demonstrate that many of the methodological characteristics of team knowledge research can be linked back to the academic training of the primary author and that there are considerable gaps in our knowledge with regard to the relationships between team knowledge constructs, the mediating mechanisms between team knowledge and performance, and relationships with criteria outside of team performance, among others. We also identify categories of team knowledge not yet examined based on an organizing framework derived from a synthesis of the literature. There are clear opportunities for expansion in the study of team knowledge; the science of team knowledge would benefit from a more holistic theoretical approach. Human factors researchers are increasingly involved in the study of teams. This review and the resulting organizing framework provide researchers with a summary of team knowledge research over the past 10 years and directions for improving further research.

Focus-on-form instructional methods promote deaf college students' improvement in English grammar.

PubMed

Berent, Gerald P; Kelly, Ronald R; Aldersley, Stephen; Schmitz, Kathryn L; Khalsa, Baldev Kaur; Panara, John; Keenan, Susan

2007-01-01

Focus-on-form English teaching methods are designed to facilitate second-language learners' noticing of target language input, where "noticing" is an acquisitional prerequisite for the comprehension, processing, and eventual integration of new grammatical knowledge. While primarily designed for teaching hearing second-language learners, many focus-on-form methods lend themselves to visual presentation. This article reports the results of classroom research on the visually based implementation of focus-on-form methods with deaf college students learning English. Two of 3 groups of deaf students received focus-on-form instruction during a 10-week remedial grammar course; a third control group received grammatical instruction that did not involve focus-on-form methods. The 2 experimental groups exhibited significantly greater improvement in English grammatical knowledge relative to the control group. These results validate the efficacy of visually based focus-on-form English instruction for deaf students of English and set the stage for the continual search for innovative and effective English teaching methodologies.

A Web-Based Program to Increase Knowledge and Reduce Cigarette and Nargila Smoking Among Arab University Students in Israel: Mixed-Methods Study to Test Acceptability

PubMed Central

Linn, Shai; Rafaeli, Sheizaf

2015-01-01

Background Among Arab citizens in Israel, cigarette and nargila (hookah, waterpipe) smoking is a serious public health problem, particularly among the young adult population. With the dramatic increase of Internet and computer use among Arab college and university students, a Web-based program may provide an easy, accessible tool to reduce smoking rates without heavy resource demands required by traditional methods. Objective The purpose of this research was to examine the acceptability and feasibility of a pilot Web-based program that provides tailored feedback to increase smoking knowledge and reduce cigarette and nargila smoking behaviors among Arab college/university students in Israel. Methods A pilot Web-based program was developed, consisting of a self-administered questionnaire and feedback system on cigarette and nargila smoking. Arab university students were recruited to participate in a mixed-methods study, using both quantitative (pre-/posttest study design) and qualitative tools. A posttest was implemented at 1 month following participation in the intervention to assess any changes in smoking knowledge and behaviors. Focus group sessions were implemented to assess acceptability and preferences related to the Web-based program. Results A total of 225 participants—response rate of 63.2% (225/356)—completed the intervention at baseline and at 1-month poststudy, and were used for the comparative analysis. Statistically significant reductions in nargila smoking among participants (P=.001) were found. The intervention did not result in reductions in cigarette smoking. However, the tailored Web intervention resulted in statistically significant increases in the intention to quit smoking (P=.021). No statistically significant increases in knowledge were seen at 1-month poststudy. Participants expressed high satisfaction with the intervention and 93.8% (211/225) of those who completed the intervention at both time intervals reported that they would recommend the program to their friends, indicating excellent acceptability and feasibility of the intervention. This was further emphasized in the focus group sessions. Conclusions A tailored Web-based program may be a promising tool to reduce nargila smoking among Arab university students in Israel. The tailored Web intervention was not successful at significantly reducing cigarette smoking or increasing knowledge. However, the intervention did increase participants’ intention to quit smoking. Participants considered the Web-based tool to be an interesting, feasible, and highly acceptable strategy. Trial Registration Trial Registration: ISRCTN registry ISRCTN59207794; http://www.isrctn.com/ISRCTN59207794 (Archived by WebCite at http://www.webcitation.org/6VkYOBNOJ). PMID:25707034

Uncertainty Quantification Techniques for Population Density Estimates Derived from Sparse Open Source Data

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

Stewart, Robert N; White, Devin A; Urban, Marie L

2013-01-01

The Population Density Tables (PDT) project at the Oak Ridge National Laboratory (www.ornl.gov) is developing population density estimates for specific human activities under normal patterns of life based largely on information available in open source. Currently, activity based density estimates are based on simple summary data statistics such as range and mean. Researchers are interested in improving activity estimation and uncertainty quantification by adopting a Bayesian framework that considers both data and sociocultural knowledge. Under a Bayesian approach knowledge about population density may be encoded through the process of expert elicitation. Due to the scale of the PDT effort whichmore » considers over 250 countries, spans 40 human activity categories, and includes numerous contributors, an elicitation tool is required that can be operationalized within an enterprise data collection and reporting system. Such a method would ideally require that the contributor have minimal statistical knowledge, require minimal input by a statistician or facilitator, consider human difficulties in expressing qualitative knowledge in a quantitative setting, and provide methods by which the contributor can appraise whether their understanding and associated uncertainty was well captured. This paper introduces an algorithm that transforms answers to simple, non-statistical questions into a bivariate Gaussian distribution as the prior for the Beta distribution. Based on geometric properties of the Beta distribution parameter feasibility space and the bivariate Gaussian distribution, an automated method for encoding is developed that responds to these challenging enterprise requirements. Though created within the context of population density, this approach may be applicable to a wide array of problem domains requiring informative priors for the Beta distribution.« less

A knowledgebase system to enhance scientific discovery: Telemakus

PubMed Central

Fuller, Sherrilynne S; Revere, Debra; Bugni, Paul F; Martin, George M

2004-01-01

Background With the rapid expansion of scientific research, the ability to effectively find or integrate new domain knowledge in the sciences is proving increasingly difficult. Efforts to improve and speed up scientific discovery are being explored on a number of fronts. However, much of this work is based on traditional search and retrieval approaches and the bibliographic citation presentation format remains unchanged. Methods Case study. Results The Telemakus KnowledgeBase System provides flexible new tools for creating knowledgebases to facilitate retrieval and review of scientific research reports. In formalizing the representation of the research methods and results of scientific reports, Telemakus offers a potential strategy to enhance the scientific discovery process. While other research has demonstrated that aggregating and analyzing research findings across domains augments knowledge discovery, the Telemakus system is unique in combining document surrogates with interactive concept maps of linked relationships across groups of research reports. Conclusion Based on how scientists conduct research and read the literature, the Telemakus KnowledgeBase System brings together three innovations in analyzing, displaying and summarizing research reports across a domain: (1) research report schema, a document surrogate of extracted research methods and findings presented in a consistent and structured schema format which mimics the research process itself and provides a high-level surrogate to facilitate searching and rapid review of retrieved documents; (2) research findings, used to index the documents, allowing searchers to request, for example, research studies which have studied the relationship between neoplasms and vitamin E; and (3) visual exploration interface of linked relationships for interactive querying of research findings across the knowledgebase and graphical displays of what is known as well as, through gaps in the map, what is yet to be tested. The rationale and system architecture are described and plans for the future are discussed. PMID:15507158

Fifth Conference on Artificial Intelligence for Space Applications

NASA Technical Reports Server (NTRS)

Odell, Steve L. (Compiler)

1990-01-01

The Fifth Conference on Artificial Intelligence for Space Applications brings together diverse technical and scientific work in order to help those who employ AI methods in space applications to identify common goals and to address issues of general interest in the AI community. Topics include the following: automation for Space Station; intelligent control, testing, and fault diagnosis; robotics and vision; planning and scheduling; simulation, modeling, and tutoring; development tools and automatic programming; knowledge representation and acquisition; and knowledge base/data base integration.

Knowledge-based simulation for aerospace systems

NASA Technical Reports Server (NTRS)

Will, Ralph W.; Sliwa, Nancy E.; Harrison, F. Wallace, Jr.

1988-01-01

Knowledge-based techniques, which offer many features that are desirable in the simulation and development of aerospace vehicle operations, exhibit many similarities to traditional simulation packages. The eventual solution of these systems' current symbolic processing/numeric processing interface problem will lead to continuous and discrete-event simulation capabilities in a single language, such as TS-PROLOG. Qualitative, totally-symbolic simulation methods are noted to possess several intrinsic characteristics that are especially revelatory of the system being simulated, and capable of insuring that all possible behaviors are considered.

Accreditation Council for Graduate Medical Education Core Competencies at a Community Teaching Hospital: Is There a Gap in Awareness?

PubMed

Al-Temimi, Mohammed; Kidon, Michael; Johna, Samir

2016-01-01

Reports evaluating faculty knowledge of the Accreditation Council for Graduate Medical Education (ACGME) core competencies in community hospitals without a dedicated residency program are uncommon. Faculty evaluation regarding knowledge of ACGME core competencies before a residency program is started. Physicians at the Kaiser Permanente Fontana Medical Center (N = 480) were surveyed for their knowledge of ACGME core competencies before starting new residency programs. Knowledge of ACGME core competencies. Fifty percent of physicians responded to the survey, and 172 (71%) of respondents were involved in teaching residents. Of physicians who taught residents and had complete responses (N = 164), 65 (39.7%) were unsure of their knowledge of the core competencies. However, most stated that they provided direct teaching to residents related to the knowledge, skills, and attitudes stated in each of the 6 competencies as follows: medical knowledge (96.3%), patient care (95.7%), professionalism (90.7%), interpersonal and communication skills (86.3%), practice-based learning (85.9%), and system-based practice (79.6%). Physician specialty, years in practice (1-10 vs > 10), and number of rotations taught per year (1-6 vs 7-12) were not associated with knowledge of the competencies (p > 0.05); however, full-time faculty (teaching 10-12 rotations per year) were more likely to provide competency-based teaching. Objective assessment of faculty awareness of ACGME core competencies is essential when starting a residency program. Discrepancy between knowledge of the competencies and acclaimed provision of competency-based teaching emphasizes the need for standardized teaching methods that incorporate the values of these competencies.

Comparison of computer-assisted instruction (CAI) versus traditional textbook methods for training in abdominal examination (Japanese experience).

PubMed

Qayumi, A K; Kurihara, Y; Imai, M; Pachev, G; Seo, H; Hoshino, Y; Cheifetz, R; Matsuura, K; Momoi, M; Saleem, M; Lara-Guerra, H; Miki, Y; Kariya, Y

2004-10-01

This study aimed to compare the effects of computer-assisted, text-based and computer-and-text learning conditions on the performances of 3 groups of medical students in the pre-clinical years of their programme, taking into account their academic achievement to date. A fourth group of students served as a control (no-study) group. Participants were recruited from the pre-clinical years of the training programmes in 2 medical schools in Japan, Jichi Medical School near Tokyo and Kochi Medical School near Osaka. Participants were randomly assigned to 4 learning conditions and tested before and after the study on their knowledge of and skill in performing an abdominal examination, in a multiple-choice test and an objective structured clinical examination (OSCE), respectively. Information about performance in the programme was collected from school records and students were classified as average, good or excellent. Student and faculty evaluations of their experience in the study were explored by means of a short evaluation survey. Compared to the control group, all 3 study groups exhibited significant gains in performance on knowledge and performance measures. For the knowledge measure, the gains of the computer-assisted and computer-assisted plus text-based learning groups were significantly greater than the gains of the text-based learning group. The performances of the 3 groups did not differ on the OSCE measure. Analyses of gains by performance level revealed that high achieving students' learning was independent of study method. Lower achieving students performed better after using computer-based learning methods. The results suggest that computer-assisted learning methods will be of greater help to students who do not find the traditional methods effective. Explorations of the factors behind this are a matter for future research.

Investigating Knowledge Management Status among Faculty Members of Kerman University of Medical Sciences based on the Nonaka Model in 2015

PubMed Central

Vali, Leila; Izadi, Azar; Jahani, Yunes; Okhovati, Maryam

2016-01-01

Introduction Education and research are two major functions of universities, which require proper and systematic exploitation of available knowledge and information. Therefore, it is necessary to investigate the knowledge management status in an education system by considering the function of faculty members in creation and dissemination of knowledge. This study was conducted to investigate the knowledge management status among faculty members of the Kerman University of Medical Sciences based on the Nonaka and Takeuchi models in 2015. Methods This was a descriptive-analytical and cross-sectional study. It was conducted on 165 faculty members at the Kerman University of Medical Sciences, who were selected from seven faculties as weighted using a random stratified sampling method. The Nonaka and Takeuchi knowledge management questionnaire consists of 26 questions in four dimensions of socialization, externalization, internalization, and combination. Scoring of questions was conducted using the five-point Likert scale. To analyze data, independent t-test, one-way ANOVA, Pearson correlation coefficients, and the Kruskal-Wallis test were employed. Results The four dimensions in the Nonaka and Takeuchi model are based on optimal indicators (3.5), dimensions of combination, and externalization with an average of 3.3 were found in higher ranks and internalization and socialization had averages of 3.1 and 3. According to the findings of this study, the average knowledge management among faculty members of the Kerman University of Medical Sciences was estimated to be 3.1, with a bit difference compared to the average. According to the results of t-tests, there was no significant relationship between gender and various dimensions of knowledge management (p>0.05). The findings of Kruskal-Wallis showed that there is no significant relationship between variables of age, academic rank, and type of faculty with regard to dimensions of knowledge management (p>0.05). In addition, according to the results of Pearson tests, there is no significant relation between employment history and dimensions of knowledge management (p>0.05). Conclusion Considering the function and importance of knowledge management in education and research organizations including universities, it is recommended to pay comprehensive attention to establishment of knowledge management and knowledge sharing in universities and provide the required background to from research teams and communication networks inside and outside universities. PMID:27757183

Level of confidence in venepuncture and knowledge in determining causes of blood sample haemolysis among clinical staff and phlebotomists.

PubMed

Makhumula-Nkhoma, Nellie; Whittaker, Vicki; McSherry, Robert

2015-02-01

To investigate the association between confidence level in venepuncture and knowledge in determining causes of blood sample haemolysis among clinical staff and phlebotomists. Various collection methods are used to perform venepuncture, also called phlebotomy, the act of drawing blood from a patient using a needle. The collection method used has an impact on preanalytical blood sample haemolysis. Haemolysis is the breakdown of red blood cells, which makes the sample unsuitable. Despite available evidence on the common causes, extensive literature search showed a lack of published evidence on the association of haemolysis with staff confidence and knowledge. A quantitative primary research design using survey method. A purposive sample of 290 clinical staff and phlebotomists conducting venepuncture in one North England hospital participated in this quantitative survey. A three-section web-based questionnaire comprising demographic profile, confidence and competence levels, and knowledge sections was used to collect data in 2012. The chi-squared test for independence was used to compare the distribution of responses for categorical data. anova was used to determine mean difference in the knowledge scores of staff with different confidence levels. Almost 25% clinical staff and phlebotomists participated in the survey. There was an increase in confidence at the last venepuncture among staff of all categories. While doctors' scores were higher compared with healthcare assistants', p ≤ 0·001, nurses' were of wide range and lowest. There was no statistically significant difference (at the 5% level) in the total knowledge scores and confidence level at the last venepuncture F(2,4·690) = 1·67, p = 0·31 among staff of all categories. Evidence-based measures are required to boost staff knowledge base of preanalytical blood sample haemolysis for standardised and quality service. Monitoring and evaluation of the training, conducting and monitoring haemolysis rate are equally crucial. Although the hospital is succeeding in providing regular training in venepuncture, this is only one aspect of quality. The process and outcome also need interventions. © 2014 John Wiley & Sons Ltd.

Adult Bronchoscopy Training

PubMed Central

Wahidi, Momen M.; Read, Charles A.; Buckley, John D.; Addrizzo-Harris, Doreen J.; Shah, Pallav L.; Herth, Felix J. F.; de Hoyos Parra, Alberto; Ornelas, Joseph; Yarmus, Lonny; Silvestri, Gerard A.

2015-01-01

BACKGROUND: The determination of competency of trainees in programs performing bronchoscopy is quite variable. Some programs provide didactic lectures with hands-on supervision, other programs incorporate advanced simulation centers, whereas others have a checklist approach. Although no single method has been proven best, the variability alone suggests that outcomes are variable. Program directors and certifying bodies need guidance to create standards for training programs. Little well-developed literature on the topic exists. METHODS: To provide credible and trustworthy guidance, rigorous methodology has been applied to create this bronchoscopy consensus training statement. All panelists were vetted and approved by the CHEST Guidelines Oversight Committee. Each topic group drafted questions in a PICO (population, intervention, comparator, outcome) format. MEDLINE data through PubMed and the Cochrane Library were systematically searched. Manual searches also supplemented the searches. All gathered references were screened for consideration based on inclusion criteria, and all statements were designated as an Ungraded Consensus-Based Statement. RESULTS: We suggest that professional societies move from a volume-based certification system to skill acquisition and knowledge-based competency assessment for trainees. Bronchoscopy training programs should incorporate multiple tools, including simulation. We suggest that ongoing quality and process improvement systems be introduced and that certifying agencies move from a volume-based certification system to skill acquisition and knowledge-based competency assessment for trainees. We also suggest that assessment of skill maintenance and improvement in practice be evaluated regularly with ongoing quality and process improvement systems after initial skill acquisition. CONCLUSIONS: The current methods used for bronchoscopy competency in training programs are variable. We suggest that professional societies and certifying agencies move from a volume- based certification system to a standardized skill acquisition and knowledge-based competency assessment for pulmonary and thoracic surgery trainees. PMID:25674901

Carnegie Knowledge Network Concluding Recommendations. What We Know Series

ERIC Educational Resources Information Center

Goldhaber, Dan; Harris Douglas N.; Loeb, Susanna; McCaffrey, Daniel F.; Raudenbush, Stephen W.

2015-01-01

It is common knowledge that teacher quality is a key in-school factor affecting student achievement. While the quality of teaching clearly matters for how much students learn, this quality is challenging to measure. Evaluating teacher quality based on the level of their students' end-of-year test scores has been one method of assessing…

Team- and Case-Based Learning to Activate Participants and Enhance Knowledge: An Evaluation of Seminars in Germany

ERIC Educational Resources Information Center

Kuhne-Eversmann, Lisa; Eversmann, Thomas; Fischer, Martin R.

2008-01-01

Introduction: There is a strong need for high-quality continuing medical education (CME) in Germany. To maintain a medical license, physicians are required to participate in regular training. Although evidence suggests that compared to lectures interactive methods can impart sustainable knowledge and a high degree of satisfaction, few interactive…

Knowledge of Mental Capacity Issues in Community Teams for Adults with Learning Disabilities

ERIC Educational Resources Information Center

Willner, Paul; Jenkins, Rosemary; Rees, Paul; Griffiths, Vanessa J.; John, Elinor

2011-01-01

Background: The aim of this study was to evaluate the state of knowledge of mental capacity issues among health and social services professionals working in community teams supporting people with learning disabilities. Methods A structured interview was constructed around three scenarios, based on actual cases, concerning a financial/legal issue,…

Prevention of Child Sexual Abuse in China: Knowledge, Attitudes, and Communication Practices of Parents of Elementary School Children

ERIC Educational Resources Information Center

Chen, JingQi; Dunne, Michael P.; Han, Ping

2007-01-01

Objective: Active involvement by parents may contribute substantially to the success of school-based programs to prevent child sexual abuse (CSA). In China, little is known about parental understanding of CSA. This study investigated Chinese parents' knowledge, attitudes, and communication practices with their children about CSA. Method: Six…

Doctors Online: Learning Using an Internet Based Content Management System

ERIC Educational Resources Information Center

Pullen, Darren

2013-01-01

The past century has seen spectacular gains in the breadth and depth of medical knowledge, but the potential of these gains has been hampered by a slow system of disseminating knowledge. Over the course of medical education numerous technologies and methods have been used to deliver continuing medical education (CME) to health care professionals…

Promoting Uptake of the HPV Vaccine: The Knowledge and Views of School Staff

ERIC Educational Resources Information Center

Rose, Sally B.; Lanumata, Tolotea; Lawton, Beverley A.

2011-01-01

Background: School-based human papillomavirus (HPV)/cervical cancer vaccination programs have been implemented widely, but few studies have investigated the knowledge and views of school staff about this new vaccine. Methods: Prior to the introduction of the HPV vaccine in 2009, we surveyed staff at 14 socioeconomically diverse schools to assess…

Advantages of Thesaurus Representation Using the Simple Knowledge Organization System (SKOS) Compared with Proposed Alternatives

ERIC Educational Resources Information Center

Pastor-Sanchez, Juan-Antonio; Martinez Mendez, Francisco Javier; Rodriguez-Munoz, Jose Vicente

2009-01-01

Introduction: This paper presents an analysis of the Simple Knowledge Organization System (SKOS) compared with other alternatives for thesaurus representation in the Semantic Web. Method: Based on functional and structural changes of thesauri, provides an overview of the current context in which lexical paradigm is abandoned in favour of the…

Rural Indonesian health care workers' constructs of infection prevention and control knowledge.

PubMed

Marjadi, Brahmaputra; McLaws, Mary-Louise

2010-06-01

Understanding the constructs of knowledge behind clinical practices in low-resource rural health care settings with limited laboratory facilities and surveillance programs may help in designing resource-appropriate infection prevention and control education. Multiple qualitative methods of direct observations, individual and group focus discussions, and document analysis were used to examine health care workers' knowledge of infection prevention and control practices in intravenous therapy, antibiotic therapy, instrument reprocessing, and hand hygiene in 10 rural Indonesian health care facilities. Awareness of health care-associated infections was low. Protocols were in the main based on verbal instructions handed down through the ranks of health care workers. The evidence-based knowledge gained across professional training was overridden by empiricism, nonscientific modifications, and organizational and societal cultures when resources were restricted or patients demanded inappropriate therapies. This phenomenon remained undetected by accreditation systems and clinical educators. Rural Indonesian health care workers would benefit from a formal introduction to evidence-based practice that would deconstruct individual protocols that include nonscientific knowledge. To achieve levels of acceptable patient safety, protocols would have to be both evidence-based and resource-appropriate. Copyright 2010 Association for Professionals in Infection Control and Epidemiology, Inc. All rights reserved.

Attitude toward, acceptance of and knowledge about female sterilization as a method of contraception.

PubMed

Erlenwein, J; Kundu, S; Schippert, C; Soergel, P; Hillemanns, P; Staboulidou, I

2015-02-01

Surgical sterilization via tubal ligation or the disconnection of the tubes is a method of permanent contraception. The aim of this study was to evaluate the attitude, acceptance and knowledge of women about female sterilization as a method of contraception in terms of the social and cultural backgrounds of those women. Prospective study based on an anonymous questionnaire that analyzed background knowledge, attitude, influence factors and motivation regarding sterilization, as well as the reasons for declining. The questionnaire also attempted to evaluate the effects on the self-esteem of the women, as well as the impact of religious dogma and the related beliefs. One thousand, eight hundred questionnaires were distributed, and 1247 women completed the questionnaire—a response rate of 69.3%. There were mainly positive attitudes toward sterilization as a contraceptive method. Cultural background, including religion and faith; the mother's experiences and point of view; knowledge; family planning and the actual life situation have an influence on the attitudes toward and acceptance of sterilization as a contraceptive method and on the final choice of a contraceptive method. Cultural background and present life situation have a great impact on the attitude toward and acceptance of sterilization as a method of contraception, thus influencing the final choice of a contraceptive method. Detailed counselling about this topic is essential and should be improved. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Novel joint TOA/RSSI-based WCE location tracking method without prior knowledge of biological human body tissues.

PubMed

Ito, Takahiro; Anzai, Daisuke; Jianqing Wang

2014-01-01

This paper proposes a novel joint time of arrival (TOA)/received signal strength indicator (RSSI)-based wireless capsule endoscope (WCE) location tracking method without prior knowledge of biological human tissues. Generally, TOA-based localization can achieve much higher localization accuracy than other radio frequency-based localization techniques, whereas wireless signals transmitted from a WCE pass through various kinds of human body tissues, as a result, the propagation velocity inside a human body should be different from one in free space. Because the variation of propagation velocity is mainly affected by the relative permittivity of human body tissues, instead of pre-measurement for the relative permittivity in advance, we simultaneously estimate not only the WCE location but also the relative permittivity information. For this purpose, this paper first derives the relative permittivity estimation model with measured RSSI information. Then, we pay attention to a particle filter algorithm with the TOA-based localization and the RSSI-based relative permittivity estimation. Our computer simulation results demonstrates that the proposed tracking methods with the particle filter can accomplish an excellent localization accuracy of around 2 mm without prior information of the relative permittivity of the human body tissues.

Problem-Based Learning: Exploiting Knowledge of How People Learn to Promote Effective Learning

ERIC Educational Resources Information Center

Wood, E. J.

2004-01-01

There is much information from educational psychology studies on how people learn. The thesis of this paper is that we should use this information to guide the ways in which we teach rather than blindly using our traditional methods. In this context, problem-based learning (PBL), as a method of teaching widely used in medical schools but…

Introduction and Evaluation of Case-Based Learning in the First Foundational Course of an Undergraduate Medical Curriculum

ERIC Educational Resources Information Center

Fortun, Jenny; Morales, Ana Cecilia; Tempest, Helen Ghislaine

2017-01-01

Case-based learning (CBL) has been proposed as an effective method to promote student knowledge and motivation. The timing and methods for implementation have varied among schools, and data regarding the effectiveness of this pedagogy compared to other learning modalities are inconclusive. We introduced five different cases in the first course of…

Gradient-based reliability maps for ACM-based segmentation of hippocampus.

PubMed

Zarpalas, Dimitrios; Gkontra, Polyxeni; Daras, Petros; Maglaveras, Nicos

2014-04-01

Automatic segmentation of deep brain structures, such as the hippocampus (HC), in MR images has attracted considerable scientific attention due to the widespread use of MRI and to the principal role of some structures in various mental disorders. In this literature, there exists a substantial amount of work relying on deformable models incorporating prior knowledge about structures' anatomy and shape information. However, shape priors capture global shape characteristics and thus fail to model boundaries of varying properties; HC boundaries present rich, poor, and missing gradient regions. On top of that, shape prior knowledge is blended with image information in the evolution process, through global weighting of the two terms, again neglecting the spatially varying boundary properties, causing segmentation faults. An innovative method is hereby presented that aims to achieve highly accurate HC segmentation in MR images, based on the modeling of boundary properties at each anatomical location and the inclusion of appropriate image information for each of those, within an active contour model framework. Hence, blending of image information and prior knowledge is based on a local weighting map, which mixes gradient information, regional and whole brain statistical information with a multi-atlas-based spatial distribution map of the structure's labels. Experimental results on three different datasets demonstrate the efficacy and accuracy of the proposed method.

Translational systems biology using an agent-based approach for dynamic knowledge representation: An evolutionary paradigm for biomedical research.

PubMed

An, Gary C

2010-01-01

The greatest challenge facing the biomedical research community is the effective translation of basic mechanistic knowledge into clinically effective therapeutics. This challenge is most evident in attempts to understand and modulate "systems" processes/disorders, such as sepsis, cancer, and wound healing. Formulating an investigatory strategy for these issues requires the recognition that these are dynamic processes. Representation of the dynamic behavior of biological systems can aid in the investigation of complex pathophysiological processes by augmenting existing discovery procedures by integrating disparate information sources and knowledge. This approach is termed Translational Systems Biology. Focusing on the development of computational models capturing the behavior of mechanistic hypotheses provides a tool that bridges gaps in the understanding of a disease process by visualizing "thought experiments" to fill those gaps. Agent-based modeling is a computational method particularly well suited to the translation of mechanistic knowledge into a computational framework. Utilizing agent-based models as a means of dynamic hypothesis representation will be a vital means of describing, communicating, and integrating community-wide knowledge. The transparent representation of hypotheses in this dynamic fashion can form the basis of "knowledge ecologies," where selection between competing hypotheses will apply an evolutionary paradigm to the development of community knowledge.

Numeric and symbolic knowledge representation of cerebral cortex anatomy: methods and preliminary results.

PubMed

Dameron, O; Gibaud, B; Morandi, X

2004-06-01

The human cerebral cortex anatomy describes the brain organization at the scale of gyri and sulci. It is used as landmarks for neurosurgery as well as localization support for functional data analysis or inter-subject data comparison. Existing models of the cortex anatomy either rely on image labeling but fail to represent variability and structural properties or rely on a conceptual model but miss the inner 3D nature and relations of anatomical structures. This study was therefore conducted to propose a model of sulco-gyral anatomy for the healthy human brain. We hypothesized that both numeric knowledge (i.e., image-based) and symbolic knowledge (i.e., concept-based) have to be represented and coordinated. In addition, the representation of this knowledge should be application-independent in order to be usable in various contexts. Therefore, we devised a symbolic model describing specialization, composition and spatial organization of cortical anatomical structures. We also collected numeric knowledge such as 3D models of shape and shape variation about cortical anatomical structures. For each numeric piece of knowledge, a companion file describes the concept it refers to and the nature of the relationship. Demonstration software performs a mapping between the numeric and the symbolic aspects for browsing the knowledge base.

Dengue knowledge, attitudes and practices and their impact on community-based vector control in rural Cambodia.

PubMed

Kumaran, Emmanuelle; Doum, Dyna; Keo, Vanney; Sokha, Ly; Sam, BunLeng; Chan, Vibol; Alexander, Neal; Bradley, John; Liverani, Marco; Prasetyo, Didot Budi; Rachmat, Agus; Lopes, Sergio; Hii, Jeffrey; Rithea, Leang; Shafique, Muhammad; Hustedt, John

2018-02-01

Globally there are an estimated 390 million dengue infections per year, of which 96 million are clinically apparent. In Cambodia, estimates suggest as many as 185,850 cases annually. The World Health Organization global strategy for dengue prevention aims to reduce mortality rates by 50% and morbidity by 25% by 2020. The adoption of integrated vector management approach using community-based methods tailored to the local context is one of the recommended strategies to achieve these objectives. Understanding local knowledge, attitudes and practices is therefore essential to designing suitable strategies to fit each local context. A Knowledge, Attitudes and Practices survey in 600 randomly chosen households was administered in 30 villages in Kampong Cham which is one of the most populated provinces of Cambodia. KAP surveys were administered to a sub-sample of households where an entomology survey was conducted (1200 households), during which Aedes larval/pupae and adult female Aedes mosquito densities were recorded. Participants had high levels of knowledge regarding the transmission of dengue, Aedes breeding, and biting prevention methods; the majority of participants believed they were at risk and that dengue transmission is preventable. However, self-reported vector control practices did not match observed practices recorded in our surveys. No correlation was found between knowledge and observed practices either. An education campaign regarding dengue prevention in this setting with high knowledge levels is unlikely to have any significant effect on practices unless it is incorporated in a more comprehensive strategy for behavioural change, such a COMBI method, which includes behavioural models as well as communication and marketing theory and practice. ISRCTN85307778.

Implementing case-based teaching strategies in a decentralised nursing management programme in South Africa.

PubMed

Nkosi, Zethu; Pillay, Padmini; Nokes, Kathleen M

2013-01-01

Case-based education has a long history in the disciplines of education, business, law and the health professions. Research suggests that students who learn via a case-based method have advanced critical thinking skills and a greater ability for application of knowledge in practice. In medical education, case-based methodology is widely used to facilitate knowledge transfer from theoretical knowledge to application in patient care. Nursing education has also adopted case-based methodology to enhance learner outcomes and critical thinking. The objectives of the study was to describe a decentralised nursing management education programme located in Durban, South Africa and describe the perceptions of nursing faculty facilitators regarding implementation of this teaching method. Data was collected through the use of one-on-one interviews and also focus groups amongst the fifteen facilitators who were using a case-based curriculum to teach the programme content. The average facilitator was female, between 41 and 50 years of age, working part-time, educated with a baccalaureate degree, working as a professional nurse for between 11 and 20 years; slightly more than half had worked as a facilitator for three or more years. The facilitators identified themes related to the student learners, the learning environment, and strengths and challenges of using facilitation to teach the content through cases. Decentralised nursing management educational programmes can meet the needs of nurses who are located in remote areas which are characterised by poor transportation patterns and limited resources and have great need for quality healthcare services. Nursing faculty facilitators need knowledgeable and accessible contact with centrally based full-time nursing faculty in order to promote high quality educational programmes.

Assessment of phase based dose modulation for improved dose efficiency in cardiac CT on an anthropomorphic motion phantom

NASA Astrophysics Data System (ADS)

Budde, Adam; Nilsen, Roy; Nett, Brian

2014-03-01

State of the art automatic exposure control modulates the tube current across view angle and Z based on patient anatomy for use in axial full scan reconstructions. Cardiac CT, however, uses a fundamentally different image reconstruction that applies a temporal weighting to reduce motion artifacts. This paper describes a phase based mA modulation that goes beyond axial and ECG modulation; it uses knowledge of the temporal view weighting applied within the reconstruction algorithm to improve dose efficiency in cardiac CT scanning. Using physical phantoms and synthetic noise emulation, we measure how knowledge of sinogram temporal weighting and the prescribed cardiac phase can be used to improve dose efficiency. First, we validated that a synthetic CT noise emulation method produced realistic image noise. Next, we used the CT noise emulation method to simulate mA modulation on scans of a physical anthropomorphic phantom where a motion profile corresponding to a heart rate of 60 beats per minute was used. The CT noise emulation method matched noise to lower dose scans across the image within 1.5% relative error. Using this noise emulation method to simulate modulating the mA while keeping the total dose constant, the image variance was reduced by an average of 11.9% on a scan with 50 msec padding, demonstrating improved dose efficiency. Radiation dose reduction in cardiac CT can be achieved while maintaining the same level of image noise through phase based dose modulation that incorporates knowledge of the cardiac reconstruction algorithm.

Resource-Based Capability on Development Knowledge Management Capabilities of Coastal Community

NASA Astrophysics Data System (ADS)

Teniwut, Roberto M. K.; Hasyim, Cawalinya L.; Teniwut, Wellem A.

2017-10-01

Building sustainable knowledge management capabilities in the coastal area might face a whole new challenge since there are many intangible factors involved from openness on new knowledge, access and ability to use the latest technology to the various local wisdom that still in place. The aimed of this study was to identify and analyze the resource-based condition of coastal community in this area to have an empirical condition of tangible and intangible infrastructure on developing knowledge management capability coastal community in Southeast Maluku, Indonesia. We used qualitative and quantitative analysis by depth interview and questionnaire for collecting the data with multiple linear regression as our analysis method. The result provided the information on current state of resource-based capability of a coastal community in this Southeast Maluku to build a sustainability model of knowledge management capabilities especially on utilization marine and fisheries resources. The implication of this study can provide an empirical information for government, NGO and research institution to dictate on how they conducted their policy and program on developing coastal community region.

Mentor-mentee Relationship: A Win-Win Contract In Graduate Medical Education

PubMed Central

Fuller, Jacklyn C

2017-01-01

Scholarly activities (i.e., the discovery of new knowledge; development of new technologies, methods, materials, or uses; integration of knowledge leading to new understanding) are intended to measure the quality and quantity of dissemination of knowledge. A successful mentorship program is necessary during residency to help residents achieve the six core competencies (patient care, medical knowledge, practice-based learning and improvement, systems-based practice, professionalism, interpersonal and communication skills) required by the Accreditation Council for Graduate Medical Education (ACGME). The role of the mentor in this process is pivotal in the advancement of the residents’ knowledge about evidence-based medicine. With this process, while mentees become more self-regulated, exhibit confidence in their performance, and demonstrate more insight and aptitude in their jobs, mentors also achieve elevated higher self-esteem, enhanced leadership skills, and personal gratification. As such, we may conclude that mentoring is a two-sided relationship; i.e., a 'win-win' style of commitment between the mentor and mentee. Hence, both parties will eventually advance academically, as well as professionally. PMID:29435394

The Sydney West Knowledge Portal: Evaluating the Growth of a Knowledge Portal to Support Translational Research

PubMed Central

2016-01-01

Background The Sydney West Translational Cancer Research Centre is an organization funded to build capacity for translational research in cancer. Translational research is essential for ensuring the integration of best available evidence into practice and for improving patient outcomes. However, there is a low level of awareness regarding what it is and how to conduct it optimally. One solution to addressing this gap is the design and deployment of web-based knowledge portals to disseminate new knowledge and engage with and connect dispersed networks of researchers. A knowledge portal is an web-based platform for increasing knowledge dissemination and management in a specialized area. Objective To measure the design and growth of an web-based knowledge portal for increasing individual awareness of translational research and to build organizational capacity for the delivery of translational research projects in cancer. Methods An adaptive methodology was used to capture the design and growth of an web-based knowledge portal in cancer. This involved stakeholder consultations to inform initial design of the portal. Once the portal was live, site analytics were reviewed to evaluate member usage of the portal and to measure growth in membership. Results Knowledge portal membership grew consistently for the first 18 months after deployment, before leveling out. Analysis of site metrics revealed members were most likely to visit portal pages with community-generated content, particularly pages with a focus on translational research. This was closely followed by pages that disseminated educational material about translational research. Conclusions Preliminary data from this study suggest that knowledge portals may be beneficial tools for translating new evidence and fostering an environment of communication and collaboration. PMID:27357641

The effect of concept mapping on preservice elementary teachers' knowledge of science inquiry teaching

NASA Astrophysics Data System (ADS)

Jackson, Diann Carol

This study examined the effect of concept mapping as a method of stimulating reflection on preservice elementary teachers' knowledge of science inquiry instruction methods. Three intact classes of science education preservice teachers participated in a non-randomized comparison group with a pretest and posttest design to measure the influence of mapping on participants' knowledge of inquiry science instruction. All groups followed the same course syllabus, in class activities, readings, assignments and assessment tasks. The manner in which they presented their ideas about inquiry science teaching varied. Groups constructed pre-lesson, post-lesson, and homework lists or maps across three inquiry based instruction modules (ecosystems, food chains, and electricity). Equivalent forms of the Teaching Science Inventory (TSI) were used to investigate changes in preservice teachers' propositional knowledge about how to teach using inquiry science instruction methods. Equivalent forms of the Science Lesson Planning (SLP) test were used to investigate changes in preservice teachers' application knowledge about how to teach using inquiry science instruction methods. Data analysis included intrarater reliability, ANOVAs, ANCOVAs, and correlations between lists and maps and examination responses. SLP and TSI scores improved from the pretest to the posttest in each of the three study groups. The results indicate that, in general, there were basically no relationships between the treatment and outcome measures. In addition, there were no significant differences between the three groups in their knowledge about how to teach science. Conclusions drawn from this study include, first, the learners did learn how to teach science using inquiry. Second, in this study there is little evidence to support that concept mapping was more successful than the listing strategy in improving preservice elementary teachers' knowledge of teaching science using inquiry science instruction methods.

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.

Building distributed rule-based systems using the AI Bus

NASA Technical Reports Server (NTRS)

Schultz, Roger D.; Stobie, Iain C.

1990-01-01

The AI Bus software architecture was designed to support the construction of large-scale, production-quality applications in areas of high technology flux, running heterogeneous distributed environments, utilizing a mix of knowledge-based and conventional components. These goals led to its current development as a layered, object-oriented library for cooperative systems. This paper describes the concepts and design of the AI Bus and its implementation status as a library of reusable and customizable objects, structured by layers from operating system interfaces up to high-level knowledge-based agents. Each agent is a semi-autonomous process with specialized expertise, and consists of a number of knowledge sources (a knowledge base and inference engine). Inter-agent communication mechanisms are based on blackboards and Actors-style acquaintances. As a conservative first implementation, we used C++ on top of Unix, and wrapped an embedded Clips with methods for the knowledge source class. This involved designing standard protocols for communication and functions which use these protocols in rules. Embedding several CLIPS objects within a single process was an unexpected problem because of global variables, whose solution involved constructing and recompiling a C++ version of CLIPS. We are currently working on a more radical approach to incorporating CLIPS, by separating out its pattern matcher, rule and fact representations and other components as true object oriented modules.

Power and knowledge in psychiatry and the troubling case of Dr Osheroff.

PubMed

Robertson, Michael

2005-12-01

To consider the state of knowledge in psychiatry with reference to the 'Osheroff debate' about the treatment of depression. A review of the key philosophical issues regarding the nature of knowledge applied to the Osheroff case. There is an apparent dichotomy between knowledge derived from a reductionist scientific method, as manifest in evidence-based medicine, and that of a narrative form of knowledge derived from clinical experience. The Focauldian notion of knowledge/power and knowledge as discourse suggests that scientific knowledge dominates over narrative knowledge in psychiatry. The implication of this applied to the Osheroff case is the potential annihilation of all forms of knowledge other than science. Knowledge in psychiatry is a pluralist, rather than singularly scientific enterprise. In the Osheroff case, the potential for scientific knowledge to abolish other forms of knowledge posed a serious threat of weakening the profession. In the light of the current debate about best practice, there is a need for reconsideration of the implications of Osheroff.

Knowledge Management Framework for Emerging Infectious Diseases Preparedness and Response: Design and Development of Public Health Document Ontology

PubMed Central

Zhang, Zhizun; Gonzalez, Mila C; Morse, Stephen S

2017-01-01

Background There are increasing concerns about our preparedness and timely coordinated response across the globe to cope with emerging infectious diseases (EIDs). This poses practical challenges that require exploiting novel knowledge management approaches effectively. Objective This work aims to develop an ontology-driven knowledge management framework that addresses the existing challenges in sharing and reusing public health knowledge. Methods We propose a systems engineering-inspired ontology-driven knowledge management approach. It decomposes public health knowledge into concepts and relations and organizes the elements of knowledge based on the teleological functions. Both knowledge and semantic rules are stored in an ontology and retrieved to answer queries regarding EID preparedness and response. Results A hybrid concept extraction was implemented in this work. The quality of the ontology was evaluated using the formal evaluation method Ontology Quality Evaluation Framework. Conclusions Our approach is a potentially effective methodology for managing public health knowledge. Accuracy and comprehensiveness of the ontology can be improved as more knowledge is stored. In the future, a survey will be conducted to collect queries from public health practitioners. The reasoning capacity of the ontology will be evaluated using the queries and hypothetical outbreaks. We suggest the importance of developing a knowledge sharing standard like the Gene Ontology for the public health domain. PMID:29021130

Semantic representation of CDC-PHIN vocabulary using Simple Knowledge Organization System.

PubMed

Zhu, Min; Mirhaji, Parsa

2008-11-06

PHIN Vocabulary Access and Distribution System (VADS) promotes the use of standards based vocabulary within CDC information systems. However, the current PHIN vocabulary representation hinders its wide adoption. Simple Knowledge Organization System (SKOS) is a W3C draft specification to support the formal representation of Knowledge Organization Systems (KOS) within the framework of the Semantic Web. We present a method of adopting SKOS to represent PHIN vocabulary in order to enable automated information sharing and integration.

The Diffusion of Evidence-Based Practice: Reviewing the Evidence-Based Practice Networks in the United States and German-Speaking Countries.

PubMed

Ghanem, Christian; Lawson, Thomas R; Pankofer, Sabine; Maragkos, Markos; Kollar, Ingo

2017-01-01

Evidence-based practice (EBP) has had a major influence on U.S. social work while it has rarely been adapted in German-speaking countries. This study investigates how knowledge about EBP is diffused within and across geographical contexts. Network analysis methods reveals different diffusion patterns and provide reasons for these differences. For example, the U.S. discourse is self-contained and based on a more homogeneous knowledge base, while the German discourse is more heterogeneous and focuses on a notion of reflexive professionalism. The different conceptual influences within the U.S. and German discourses are discussed in light of future directions of disciplinary social work.

A research-based didactic model for education to promote culturally competent nursing care in Sweden.

PubMed

Gebru, Kerstin; Willman, Ania

2003-01-01

As Sweden changes toward a multicultural society, scientific knowledge of transcultural nursing care becomes increasingly important. Earlier studies in Swedish nursing education have demonstrated a lack of knowledge base in transcultural nursing. Through an extensive review of the literature, a didactic model was developed to help facilitate the establishment of this body of knowledge in transcultural nursing. The article demonstrates how the model applies the content and structure of Leininger's theory of culture care diversity and universality and ethnonursing method in a 3-year nursing program in theory as well as clinical education. The model includes a written guide for faculty members, with references to scientific articles and documents to be used.

Knowledge network model of the energy consumption in discrete manufacturing system

NASA Astrophysics Data System (ADS)

Xu, Binzi; Wang, Yan; Ji, Zhicheng

2017-07-01

Discrete manufacturing system generates a large amount of data and information because of the development of information technology. Hence, a management mechanism is urgently required. In order to incorporate knowledge generated from manufacturing data and production experience, a knowledge network model of the energy consumption in the discrete manufacturing system was put forward based on knowledge network theory and multi-granularity modular ontology technology. This model could provide a standard representation for concepts, terms and their relationships, which could be understood by both human and computer. Besides, the formal description of energy consumption knowledge elements (ECKEs) in the knowledge network was also given. Finally, an application example was used to verify the feasibility of the proposed method.

Improving performance with knowledge management

NASA Astrophysics Data System (ADS)

Kim, Sangchul

2018-06-01

People and organization are unable to easily locate their experience and knowledge, so meaningful data is usually fragmented, unstructured, not up-to-date and largely incomplete. Poor knowledge management (KM) leaves a company weak to their knowledge-base - or intellectual capital - walking out of the door each year, that is minimum estimated at 10%. Knowledge management (KM) can be defined as an emerging set of organizational design and operational principles, processes, organizational structures, applications and technologies that helps knowledge workers dramatically leverage their creativity and ability to deliver business value and to reap finally a competitive advantage. Then, this paper proposed various method and software starting with an understanding of the enterprise aspect, and gave inspiration to those who wanted to use KM.

Extracting rate changes in transcriptional regulation from MEDLINE abstracts.

PubMed

Liu, Wenting; Miao, Kui; Li, Guangxia; Chang, Kuiyu; Zheng, Jie; Rajapakse, Jagath C

2014-01-01

Time delays are important factors that are often neglected in gene regulatory network (GRN) inference models. Validating time delays from knowledge bases is a challenge since the vast majority of biological databases do not record temporal information of gene regulations. Biological knowledge and facts on gene regulations are typically extracted from bio-literature with specialized methods that depend on the regulation task. In this paper, we mine evidences for time delays related to the transcriptional regulation of yeast from the PubMed abstracts. Since the vast majority of abstracts lack quantitative time information, we can only collect qualitative evidences of time delays. Specifically, the speed-up or delay in transcriptional regulation rate can provide evidences for time delays (shorter or longer) in GRN. Thus, we focus on deriving events related to rate changes in transcriptional regulation. A corpus of yeast regulation related abstracts was manually labeled with such events. In order to capture these events automatically, we create an ontology of sub-processes that are likely to result in transcription rate changes by combining textual patterns and biological knowledge. We also propose effective feature extraction methods based on the created ontology to identify the direct evidences with specific details of these events. Our ontologies outperform existing state-of-the-art gene regulation ontologies in the automatic rule learning method applied to our corpus. The proposed deterministic ontology rule-based method can achieve comparable performance to the automatic rule learning method based on decision trees. This demonstrates the effectiveness of our ontology in identifying rate-changing events. We also tested the effectiveness of the proposed feature mining methods on detecting direct evidence of events. Experimental results show that the machine learning method on these features achieves an F1-score of 71.43%. The manually labeled corpus of events relating to rate changes in transcriptional regulation for yeast is available in https://sites.google.com/site/wentingntu/data. The created ontologies summarized both biological causes of rate changes in transcriptional regulation and corresponding positive and negative textual patterns from the corpus. They are demonstrated to be effective in identifying rate-changing events, which shows the benefits of combining textual patterns and biological knowledge on extracting complex biological events.

A deep learning method for lincRNA detection using auto-encoder algorithm.

PubMed

Yu, Ning; Yu, Zeng; Pan, Yi

2017-12-06

RNA sequencing technique (RNA-seq) enables scientists to develop novel data-driven methods for discovering more unidentified lincRNAs. Meantime, knowledge-based technologies are experiencing a potential revolution ignited by the new deep learning methods. By scanning the newly found data set from RNA-seq, scientists have found that: (1) the expression of lincRNAs appears to be regulated, that is, the relevance exists along the DNA sequences; (2) lincRNAs contain some conversed patterns/motifs tethered together by non-conserved regions. The two evidences give the reasoning for adopting knowledge-based deep learning methods in lincRNA detection. Similar to coding region transcription, non-coding regions are split at transcriptional sites. However, regulatory RNAs rather than message RNAs are generated. That is, the transcribed RNAs participate the biological process as regulatory units instead of generating proteins. Identifying these transcriptional regions from non-coding regions is the first step towards lincRNA recognition. The auto-encoder method achieves 100% and 92.4% prediction accuracy on transcription sites over the putative data sets. The experimental results also show the excellent performance of predictive deep neural network on the lincRNA data sets compared with support vector machine and traditional neural network. In addition, it is validated through the newly discovered lincRNA data set and one unreported transcription site is found by feeding the whole annotated sequences through the deep learning machine, which indicates that deep learning method has the extensive ability for lincRNA prediction. The transcriptional sequences of lincRNAs are collected from the annotated human DNA genome data. Subsequently, a two-layer deep neural network is developed for the lincRNA detection, which adopts the auto-encoder algorithm and utilizes different encoding schemes to obtain the best performance over intergenic DNA sequence data. Driven by those newly annotated lincRNA data, deep learning methods based on auto-encoder algorithm can exert their capability in knowledge learning in order to capture the useful features and the information correlation along DNA genome sequences for lincRNA detection. As our knowledge, this is the first application to adopt the deep learning techniques for identifying lincRNA transcription sequences.

Knowledge translation to fitness trainers: A systematic review

PubMed Central

2010-01-01

Background This study investigates approaches for translating evidence-based knowledge for use by fitness trainers. Specific questions were: Where do fitness trainers get their evidence-based information? What types of interventions are effective for translating evidence-based knowledge for use by fitness trainers? What are the barriers and facilitators to the use of evidence-based information by fitness trainers in their practice? Methods We describe a systematic review of studies about knowledge translation interventions targeting fitness trainers. Fitness trainers were defined as individuals who provide exercise program design and supervision services to the public. Nurses, physicians, physiotherapists, school teachers, athletic trainers, and sport team strength coaches were excluded. Results Of 634 citations, two studies were eligible for inclusion: a survey of 325 registered health fitness professionals (66% response rate) and a qualitative study of 10 fitness instructors. Both studies identified that fitness trainers obtain information from textbooks, networking with colleagues, scientific journals, seminars, and mass media. Fitness trainers holding higher levels of education are reported to use evidence-based information sources such as scientific journals compared to those with lower education levels, who were reported to use mass media sources. The studies identified did not evaluate interventions to translate evidence-based knowledge for fitness trainers and did not explore factors influencing uptake of evidence in their practice. Conclusion Little is known about how fitness trainers obtain and incorporate new evidence-based knowledge into their practice. Further exploration and specific research is needed to better understand how emerging health-fitness evidence can be translated to maximize its use by fitness trainers providing services to the general public. PMID:20398317

STRUTEX: A prototype knowledge-based system for initially configuring a structure to support point loads in two dimensions

NASA Technical Reports Server (NTRS)

Robers, James L.; Sobieszczanski-Sobieski, Jaroslaw

1989-01-01

Only recently have engineers begun making use of Artificial Intelligence (AI) tools in the area of conceptual design. To continue filling this void in the design process, a prototype knowledge-based system, called STRUTEX has been developed to initially configure a structure to support point loads in two dimensions. This prototype was developed for testing the application of AI tools to conceptual design as opposed to being a testbed for new methods for improving structural analysis and optimization. This system combines numerical and symbolic processing by the computer with interactive problem solving aided by the vision of the user. How the system is constructed to interact with the user is described. Of special interest is the information flow between the knowledge base and the data base under control of the algorithmic main program. Examples of computed and refined structures are presented during the explanation of the system.

Common Criteria Related Security Design Patterns for Intelligent Sensors—Knowledge Engineering-Based Implementation

PubMed Central

Bialas, Andrzej

2011-01-01

Intelligent sensors experience security problems very similar to those inherent to other kinds of IT products or systems. The assurance for these products or systems creation methodologies, like Common Criteria (ISO/IEC 15408) can be used to improve the robustness of the sensor systems in high risk environments. The paper presents the background and results of the previous research on patterns-based security specifications and introduces a new ontological approach. The elaborated ontology and knowledge base were validated on the IT security development process dealing with the sensor example. The contribution of the paper concerns the application of the knowledge engineering methodology to the previously developed Common Criteria compliant and pattern-based method for intelligent sensor security development. The issue presented in the paper has a broader significance in terms that it can solve information security problems in many application domains. PMID:22164064

Common criteria related security design patterns for intelligent sensors--knowledge engineering-based implementation.

PubMed

Bialas, Andrzej

2011-01-01

Intelligent sensors experience security problems very similar to those inherent to other kinds of IT products or systems. The assurance for these products or systems creation methodologies, like Common Criteria (ISO/IEC 15408) can be used to improve the robustness of the sensor systems in high risk environments. The paper presents the background and results of the previous research on patterns-based security specifications and introduces a new ontological approach. The elaborated ontology and knowledge base were validated on the IT security development process dealing with the sensor example. The contribution of the paper concerns the application of the knowledge engineering methodology to the previously developed Common Criteria compliant and pattern-based method for intelligent sensor security development. The issue presented in the paper has a broader significance in terms that it can solve information security problems in many application domains.

A comparative evaluation of the effect of Internet-based CME delivery format on satisfaction, knowledge and confidence.

PubMed

Curran, Vernon R; Fleet, Lisa J; Kirby, Fran

2010-01-29

Internet-based instruction in continuing medical education (CME) has been associated with favorable outcomes. However, more direct comparative studies of different Internet-based interventions, instructional methods, presentation formats, and approaches to implementation are needed. The purpose of this study was to conduct a comparative evaluation of two Internet-based CME delivery formats and the effect on satisfaction, knowledge and confidence outcomes. Evaluative outcomes of two differing formats of an Internet-based CME course with identical subject matter were compared. A Scheduled Group Learning format involved case-based asynchronous discussions with peers and a facilitator over a scheduled 3-week delivery period. An eCME On Demand format did not include facilitated discussion and was not based on a schedule; participants could start and finish at any time. A retrospective, pre-post evaluation study design comparing identical satisfaction, knowledge and confidence outcome measures was conducted. Participants in the Scheduled Group Learning format reported significantly higher mean satisfaction ratings in some areas, performed significantly higher on a post-knowledge assessment and reported significantly higher post-confidence scores than participants in the eCME On Demand format that was not scheduled and did not include facilitated discussion activity. The findings support the instructional benefits of a scheduled delivery format and facilitated asynchronous discussion in Internet-based CME.

Increasing postpartum contraception in rural India: evaluation of a community-based behavior change communication intervention.

PubMed

Sebastian, Mary Philip; Khan, Mohammed Ejazduin; Kumari, Kaushal; Idnani, Rukma

2012-06-01

The Indian family planning program, though successful in increasing contraceptive use among couples who have achieved their desired family size, has not been equally successful in educating couples about the use of contraceptive methods for birth spacing. An evaluation was conducted of a behavior change communication intervention integrated into the existing government program to increase knowledge and use of the lactational amenorrhea method and postpartum contraception through counseling by community workers. The intervention, which ran between September 2006 and January 2007, was conducted among 959 pregnant women aged 15-24 who lived in Uttar Pradesh, India. The evaluation used logistic regression analyses to measure differences in knowledge and contraceptive use between baseline and the four- and nine-month postpartum follow-up surveys within and between the intervention and comparison groups. The follow-up data show increases in knowledge of the lactational amenorrhea method and spacing methods and in use of spacing methods. At four months postpartum, women in the intervention group were more likely to know the healthy spacing messages than those in the comparison group (odds ratio, 2.1). At nine months postpartum, women in the intervention group, those with higher knowledge of healthy spacing practices and those with correct knowledge of two or more spacing methods were more likely than others to be using a contraceptive method (1.5-3.5). Use of modern contraceptives for spacing at nine months postpartum was 57% in the intervention group versus 30% in the comparison group. Targeted behavior change communication using community workers is an effective and feasible strategy for promoting postpartum contraception.

Exploring arts-based knowledge translation: sharing research findings through performing the patterns, rehearsing the results, staging the synthesis.

PubMed

Rieger, Kendra; Schultz, Annette S H

2014-04-01

Cultivation of knowledge translation (KT) strategies that actively engage health professionals in critical reflection of their practice and research-based evidence are imperative to address the research-practice gap. While research-based evidence is exponentially growing, our ability to facilitate uptake by nurses and other health professionals has not kept pace. Innovative approaches that extend epistemological bias beyond a singular standpoint of postpositivism, such as the utilization of arts-based methods, expand the possibility to address the complexities of context, engage audience members, promote dissemination within communities of practice, and foster new audiences interested in research findings. In this paper, we address the importance of adopting a social constructivist epistemological stance to facilitate knowledge translation to diverse audiences, explore various arts-based knowledge translation (ABKT) strategies, and open a dialogue concerning evaluative tenets of ABKT. ABKT utilizes various art forms to disseminate research knowledge to diverse audiences and promote evidence-informed practice. ABKT initiatives translate knowledge not based upon a linear model, which views knowledge as an objective entity, but rather operate from the premise that knowledge is socially situated, which demands acknowledging and engaging the learner within their context. Theatre, dance, photography, and poetry are art forms that are commonly used to communicate research findings to diverse audiences. Given the emerging interest and importance of utilizing this KT strategy situated within a social constructivist epistemology, potential challenges and plausible evaluative criteria specific to ABKT are presented. ABKT is an emerging KT strategy that is grounded in social constructivist epistemological tenets, and holds potential for meaningfully sharing new research knowledge with diverse audiences. ABKT is an innovative and synergistic approach to traditional dissemination strategies. This creative KT approach is emerging as potent transformational learning tools that are congruent with the relational nature of nursing practice. ABKT facilitates learning about new research findings in an engaging and critical reflective manner that promotes learning within communities of practice. © 2014 Sigma Theta Tau International.

An empirical Bayes approach to network recovery using external knowledge.

PubMed

Kpogbezan, Gino B; van der Vaart, Aad W; van Wieringen, Wessel N; Leday, Gwenaël G R; van de Wiel, Mark A

2017-09-01

Reconstruction of a high-dimensional network may benefit substantially from the inclusion of prior knowledge on the network topology. In the case of gene interaction networks such knowledge may come for instance from pathway repositories like KEGG, or be inferred from data of a pilot study. The Bayesian framework provides a natural means of including such prior knowledge. Based on a Bayesian Simultaneous Equation Model, we develop an appealing Empirical Bayes (EB) procedure that automatically assesses the agreement of the used prior knowledge with the data at hand. We use variational Bayes method for posterior densities approximation and compare its accuracy with that of Gibbs sampling strategy. Our method is computationally fast, and can outperform known competitors. In a simulation study, we show that accurate prior data can greatly improve the reconstruction of the network, but need not harm the reconstruction if wrong. We demonstrate the benefits of the method in an analysis of gene expression data from GEO. In particular, the edges of the recovered network have superior reproducibility (compared to that of competitors) over resampled versions of the data. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Comparative analysis of machine learning methods in ligand-based virtual screening of large compound libraries.

PubMed

Ma, Xiao H; Jia, Jia; Zhu, Feng; Xue, Ying; Li, Ze R; Chen, Yu Z

2009-05-01

Machine learning methods have been explored as ligand-based virtual screening tools for facilitating drug lead discovery. These methods predict compounds of specific pharmacodynamic, pharmacokinetic or toxicological properties based on their structure-derived structural and physicochemical properties. Increasing attention has been directed at these methods because of their capability in predicting compounds of diverse structures and complex structure-activity relationships without requiring the knowledge of target 3D structure. This article reviews current progresses in using machine learning methods for virtual screening of pharmacodynamically active compounds from large compound libraries, and analyzes and compares the reported performances of machine learning tools with those of structure-based and other ligand-based (such as pharmacophore and clustering) virtual screening methods. The feasibility to improve the performance of machine learning methods in screening large libraries is discussed.

Development and Assessment of a Geographic Knowledge-Based Model for Mapping Suitable Areas for Rift Valley Fever Transmission in Eastern Africa

PubMed Central

Tran, Annelise; Trevennec, Carlène; Lutwama, Julius; Sserugga, Joseph; Gély, Marie; Pittiglio, Claudia; Pinto, Julio; Chevalier, Véronique

2016-01-01

Rift Valley fever (RVF), a mosquito-borne disease affecting ruminants and humans, is one of the most important viral zoonoses in Africa. The objective of the present study was to develop a geographic knowledge-based method to map the areas suitable for RVF amplification and RVF spread in four East African countries, namely, Kenya, Tanzania, Uganda and Ethiopia, and to assess the predictive accuracy of the model using livestock outbreak data from Kenya and Tanzania. Risk factors and their relative importance regarding RVF amplification and spread were identified from a literature review. A numerical weight was calculated for each risk factor using an analytical hierarchy process. The corresponding geographic data were collected, standardized and combined based on a weighted linear combination to produce maps of the suitability for RVF transmission. The accuracy of the resulting maps was assessed using RVF outbreak locations in livestock reported in Kenya and Tanzania between 1998 and 2012 and the ROC curve analysis. Our results confirmed the capacity of the geographic information system-based multi-criteria evaluation method to synthesize available scientific knowledge and to accurately map (AUC = 0.786; 95% CI [0.730–0.842]) the spatial heterogeneity of RVF suitability in East Africa. This approach provides users with a straightforward and easy update of the maps according to data availability or the further development of scientific knowledge. PMID:27631374

Rethinking the Elementary Science Methods Course: A Case for Content, Pedagogy, and Informal Science Education.

ERIC Educational Resources Information Center

Kelly, Janet

2000-01-01

Indicates the importance of preparing prospective teachers who will be elementary science teachers with different methods. Presents the theoretical and practical rationale for developing a constructivist-based elementary science methods course. Discusses the impact student knowledge and understanding of science and student attitudes has on…

Eliciting candidate anatomical routes for protein interactions: a scenario from endocrine physiology

PubMed Central

2013-01-01

Background In this paper, we use: i) formalised anatomical knowledge of connectivity between body structures and ii) a formal theory of physiological transport between fluid compartments in order to define and make explicit the routes followed by proteins to a site of interaction. The underlying processes are the objects of mathematical models of physiology and, therefore, the motivation for the approach can be understood as using knowledge representation and reasoning methods to propose concrete candidate routes corresponding to correlations between variables in mathematical models of physiology. In so doing, the approach projects physiology models onto a representation of the anatomical and physiological reality which underpins them. Results The paper presents a method based on knowledge representation and reasoning for eliciting physiological communication routes. In doing so, the paper presents the core knowledge representation and algorithms using it in the application of the method. These are illustrated through the description of a prototype implementation and the treatment of a simple endocrine scenario whereby a candidate route of communication between ANP and its receptors on the external membrane of smooth muscle cells in renal arterioles is elicited. The potential of further development of the approach is illustrated through the informal discussion of a more complex scenario. Conclusions The work presented in this paper supports research in intercellular communication by enabling knowledge‐based inference on physiologically‐related biomedical data and models. PMID:23590598

Incorporating Problem-Based Learning in Physical Education Teacher Education

ERIC Educational Resources Information Center

Hushman, Glenn; Napper-Owen, Gloria

2011-01-01

Problem-based learning (PBL) is an educational method that identifies a problem as a context for student learning. Critical-thinking skills, deductive reasoning, knowledge, and behaviors are developed as students learn how theory can be applied to practical settings. Problem-based learning encourages self-direction, lifelong learning, and sharing…

A Loud Silence: Working with Research-Based Theatre and A/R/Tography

ERIC Educational Resources Information Center

Lea, Graham W.; Belliveau, George; Wager, Amanda; Beck, Jaime L.

2011-01-01

Arts-based approaches to research have emerged as an integral component of current scholarship in the social sciences, education, health research, and humanities. Integrating arts-based methods and methodologies with research generates possibilities for fresh approaches for creating, translating, and exchanging knowledge (Barone & Eisner, 1997;…

DNA-Based Methods in the Immunohematology Reference Laboratory

PubMed Central

Denomme, Gregory A

2010-01-01

Although hemagglutination serves the immunohematology reference laboratory well, when used alone, it has limited capability to resolve complex problems. This overview discusses how molecular approaches can be used in the immunohematology reference laboratory. In order to apply molecular approaches to immunohematology, knowledge of genes, DNA-based methods, and the molecular bases of blood groups are required. When applied correctly, DNA-based methods can predict blood groups to resolve ABO/Rh discrepancies, identify variant alleles, and screen donors for antigen-negative units. DNA-based testing in immunohematology is a valuable tool used to resolve blood group incompatibilities and to support patients in their transfusion needs. PMID:21257350

Biology Factual Knowledge at Eleventh Grade of Senior High School Students in Pacitan based on Favorite Schools

NASA Astrophysics Data System (ADS)

Yustiana, I. A.; Paidi; Mercuriani, I. S.

2018-03-01

This study aimed to determine the Biology factual knowledge at eleventh grade of senior high school students in Pacitan based on favorite schools. This research was a descriptive research by using survey method. The population in this study was all of senior high school students in Pacitan. The sampling technique used purposive sampling technique and obtained 3 favorite schools and 3 non-favorite schools. The technique of collecting data used test form which was as the instrument of the research. Data analysis technique used Mann-Whitney U test. Based on the test, it was obtained p = 0,000 (p <0,05) so there was a significant difference between the factual knowledge of the students in the favorite schools and non-favorite schools in Pacitan. The factual knowledge of students in favorite schools was higher with an average of 5.32 while non-favorite schools were obtained an average of 4.36.

Problem-based Learning Using the Online Medicare Part D Plan Finder Tool

PubMed Central

Stebbins, Marilyn R.; Lai, Eric; Smith, Amanda R.; Lipton, Helene Levens

2008-01-01

Objectives To implement didactic and problem-based learning curricular innovations aimed at increasing students' knowledge of Medicare Part D, improving their ability to apply the online Medicare Prescription Drug Plan Finder tool to a patient case, and improving their attitudes toward patient advocacy for Medicare beneficiaries. Methods A survey instrument and a case-based online Medicare Prescription Drug Plan Finder tool exercise were administered to a single group (n = 120) of second-year pharmacy graduate students prior to and following completion of a course on health policy. Three domains (knowledge, skill mastery and attitudes) were measured before and after two 90-minute lectures on Medicare Part D. Results The online Medicare Prescription Drug Plan Finder exercise and Medicare Part D didactic lectures had positive effects on students' knowledge of Part D, attitudes toward patient advocacy, and ability to accurately use the Medicare Prescription Drug Plan Finder tool. Conclusions The success of these didactic and problem-based curricular innovations in improving pharmacy students' knowledge, skills, and attitudes regarding Part D warrants further evaluation to determine their portability to clinical settings and other pharmacy schools. PMID:18698399

Is risk analysis scientific?

PubMed

Hansson, Sven Ove; Aven, Terje

2014-07-01

This article discusses to what extent risk analysis is scientific in view of a set of commonly used definitions and criteria. We consider scientific knowledge to be characterized by its subject matter, its success in developing the best available knowledge in its fields of study, and the epistemic norms and values that guide scientific investigations. We proceed to assess the field of risk analysis according to these criteria. For this purpose, we use a model for risk analysis in which science is used as a base for decision making on risks, which covers the five elements evidence, knowledge base, broad risk evaluation, managerial review and judgment, and the decision; and that relates these elements to the domains experts and decisionmakers, and to the domains fact-based or value-based. We conclude that risk analysis is a scientific field of study, when understood as consisting primarily of (i) knowledge about risk-related phenomena, processes, events, etc., and (ii) concepts, theories, frameworks, approaches, principles, methods and models to understand, assess, characterize, communicate, and manage risk, in general and for specific applications (the instrumental part). © 2014 Society for Risk Analysis.

A prototype system for perinatal knowledge engineering using an artificial intelligence tool.

PubMed

Sokol, R J; Chik, L

1988-01-01

Though several perinatal expert systems are extant, the use of artificial intelligence has, as yet, had minimal impact in medical computing. In this evaluation of the potential of AI techniques in the development of a computer based "Perinatal Consultant," a "top down" approach to the development of a perinatal knowledge base was taken, using as a source for such a knowledge base a 30-page manuscript of a chapter concerning high risk pregnancy. The UNIX utility "style" was used to parse sentences and obtain key words and phrases, both as part of a natural language interface and to identify key perinatal concepts. Compared with the "gold standard" of sentences containing key facts as chosen by the experts, a semiautomated method using a nonmedical speller to identify key words and phrases in context functioned with a sensitivity of 79%, i.e., approximately 8 in 10 key sentences were detected as the basis for PROLOG, rules and facts for the knowledge base. These encouraging results suggest that functional perinatal expert systems may well be expedited by using programming utilities in conjunction with AI tools and published literature.

Knowledge base and sensor bus messaging service architecture for critical tsunami warning and decision-support

NASA Astrophysics Data System (ADS)

Sabeur, Z. A.; Wächter, J.; Middleton, S. E.; Zlatev, Z.; Häner, R.; Hammitzsch, M.; Loewe, P.

2012-04-01

The intelligent management of large volumes of environmental monitoring data for early tsunami warning requires the deployment of robust and scalable service oriented infrastructure that is supported by an agile knowledge-base for critical decision-support In the TRIDEC project (TRIDEC 2010-2013), a sensor observation service bus of the TRIDEC system is being developed for the advancement of complex tsunami event processing and management. Further, a dedicated TRIDEC system knowledge-base is being implemented to enable on-demand access to semantically rich OGC SWE compliant hydrodynamic observations and operationally oriented meta-information to multiple subscribers. TRIDEC decision support requires a scalable and agile real-time processing architecture which enables fast response to evolving subscribers requirements as the tsunami crisis develops. This is also achieved with the support of intelligent processing services which specialise in multi-level fusion methods with relevance feedback and deep learning. The TRIDEC knowledge base development work coupled with that of the generic sensor bus platform shall be presented to demonstrate advanced decision-support with situation awareness in context of tsunami early warning and crisis management.

Efficacy of Adolescent Suicide Prevention E-Learning Modules for Gatekeepers: A Randomized Controlled Trial

PubMed Central

Gould, Madelyn S; Twisk, Jos WR; Kerkhof, Ad JFM; Koot, Hans M

2016-01-01

Background Face-to-face gatekeeper training can be an effective strategy in the enhancement of gatekeepers’ knowledge and self-efficacy in adolescent suicide prevention. However, barriers related to access (eg, time, resources) may hamper participation in face-to-face training sessions. The transition to a Web-based setting could address obstacles associated with face-to-face gatekeeper training. Although Web-based suicide prevention training targeting adolescents exists, so far no randomized controlled trials (RCTs) have been conducted to investigate their efficacy. Objective This RCT study investigated the efficacy of a Web-based adolescent suicide prevention program entitled Mental Health Online, which aimed to improve the knowledge and self-confidence of gatekeepers working with adolescents (12-20 years old). The program consisted of 8 short e-learning modules each capturing an important aspect of the process of early recognition, guidance, and referral of suicidal adolescents, alongside additional information on the topic of (adolescent) suicide prevention. Methods A total of 190 gatekeepers (ages 21 to 62 years) participated in this study and were randomized to either the experimental group or waitlist control group. The intervention was not masked. Participants from both groups completed 3 Web-based assessments (pretest, posttest, and 3-month follow-up). The outcome measures of this study were actual knowledge, and participants’ ratings of perceived knowledge and perceived self-confidence using questionnaires developed specifically for this study. Results The actual knowledge, perceived knowledge, and perceived self-confidence of gatekeepers in the experimental group improved significantly compared to those in the waitlist control group at posttest, and the effects remained significant at 3-month follow-up. The overall effect sizes were 0.76, 1.20, and 1.02, respectively, across assessments. Conclusions The findings of this study indicate that Web-based suicide prevention e-learning modules can be an effective educational method to enhance knowledge and self-confidence of gatekeepers with regard to adolescent suicide prevention. Gatekeepers with limited time and resources can benefit from the accessibility, simplicity, and flexibility of Web-based training. Trial Registration Netherlands Trial Register NTR3625; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=3625 (Archived by WebCite at http://www.webcitation.org/6eHvyRh6M) PMID:26825006

The Impact of Farmer Field Schools on Human and Social Capital: A Case Study from Ghana

ERIC Educational Resources Information Center

David, Soniia; Asamoah, Christopher

2011-01-01

Based on a case study of Ghanaian cocoa farmers who attended farmer field schools (FFS), this paper explores the impact of the FFS methodology on farmers' technical knowledge, experimentation, knowledge diffusion, group formation and social skills as a way of assessing whether the relatively high costs associated with the method is justified. We…

Semi-Automated Methods for Refining a Domain-Specific Terminology Base

DTIC Science & Technology

2011-02-01

only as a resource for written and oral translation, but also for Natural Language Processing ( NLP ) applications, text retrieval, document indexing...Natural Language Processing ( NLP ) applications, text retrieval, document indexing, and other knowledge management tasks. The objective of this...also for Natural Language Processing ( NLP ) applications, text retrieval (1), document indexing, and other knowledge management tasks. The National

A Symbolic Approach Using Feature Construction Capable of Acquiring Information/Knowledge for Building Expert Systems.

ERIC Educational Resources Information Center

Major, Raymond L.

1998-01-01

Presents a technique for developing a knowledge-base of information to use in an expert system. Proposed approach employs a popular machine-learning algorithm along with a method for forming a finite number of features or conjuncts of at most n primitive attributes. Illustrates this procedure by examining qualitative information represented in a…

The Knowledge Base of Subject Matter Experts in Teaching: A Case Study of a Professional Scientist as a Beginning Teacher

ERIC Educational Resources Information Center

Diezmann, Carmel M.; Watters, James J.

2015-01-01

One method of addressing the shortage of science and mathematics teachers is to train scientists and other science-related professionals to become teachers. Advocates argue that as discipline experts these career changers can relate the subject matter knowledge to various contexts and applications in teaching. In this paper, through interviews and…

Knowledge of Human Papillomavirus and Perceived Barriers to Vaccination in a Sample of US Female College Students

ERIC Educational Resources Information Center

Dillard, James Price; Spear, Margaret E.

2010-01-01

Objective: To assess knowledge of human papillomavirus (HPV) and perceived barriers to being vaccinated against the virus. Participants: Three hundred ninety-six undergraduate women enrolled at Penn State University in Fall 2008. Methods: A random sample of students were invited to participate in a Web-based survey. Results: Awareness of HPV and…

Computer Model of the Empirical Knowledge of Physics Formation: Coordination with Testing Results

ERIC Educational Resources Information Center

Mayer, Robert V.

2016-01-01

The use of method of imitational modeling to study forming the empirical knowledge in pupil's consciousness is discussed. The offered model is based on division of the physical facts into three categories: 1) the facts established in everyday life; 2) the facts, which the pupil can experimentally establish at a physics lesson; 3) the facts which…

Development of an Educational Video to Improve HIV-Related Knowledge, Attitudes and Prevention among Company Workers in Ecuador

ERIC Educational Resources Information Center

del Carmen Cabezas, María; Fornasini, Marco; Barmettler, David; Ortuño, Diego; Borja, Teresa; Albert, Adelin

2015-01-01

Objective: To develop and assess an innovative educational video package for improving HIV knowledge, attitudes and practices among company workers in Ecuador. Methods: The design and development of the HIV prevention educational video was based on the results of a large-scale survey conducted in 115 companies (commerce, manufacturing and real…

Improving the Understanding of Schistosomiasis among Adolescents in Endemic Areas in Brazil: a Comparison of Educational Methods

PubMed Central

Gazzinelli, Maria Flávia; Lobato, Lucas; Andrade, Gisele; Matoso, Leonardo Ferreira; Diemert, David J.; Gazzinelli, Andréa

2016-01-01

Objective To evaluate the effectiveness of two teaching strategies, both guided by the concept of dialogicity, on adolescents’ knowledge about schistosomiasis and adherence to diagnostic fecal testing. Methods Two teaching strategies related to schistosomiasis were developed, an educational video and group conversation, which were tested in two groups of students aged 10–15 years old. Before and after the intervention, a questionnaire was applied to assess participants' knowledge about schistosomiasis and, after the intervention, two fecal samples were requested from each participant. Comparisons were performed by paired t- and McNemar tests. Results Both strategies resulted in statistically significant improvements in knowledge between the pre- and post-tests. Students who watched the video had a higher return rate of fecal samples and percentage of correct questionnaire answers, mainly on questions about schistosomiasis infection. Conclusion teaching strategies based on dialogue favored the construction of concepts about schistosomiasis that can influence the adoption of positives attitudes related to health. Practical Implications Using teaching strategies based on the concept of dialogicity can favor the increase of knowledge of school age children about schistosomiasis and can influence behavioral change related to health. PMID:27180618

Knowledge flow and exchange in interdisciplinary primary health care teams (PHCTs): an exploratory study

PubMed Central

Sibbald, Shannon L.; Wathen, C. Nadine; Kothari, Anita; Day, Adam M. B.

2013-01-01

Objective: Improving the process of evidence-based practice in primary health care requires an understanding of information exchange among colleagues. This study explored how clinically oriented research knowledge flows through multidisciplinary primary health care teams (PHCTs) and influences clinical decisions. Methods: This was an exploratory mixed-methods study with members of six PHCTs in Ontario, Canada. Quantitative data were collected using a questionnaire and analyzed with social network analysis (SNA) using UCINet. Qualitative data were collected using semi-structured interviews and analyzed with content analysis procedures using NVivo8. Results: It was found that obtaining research knowledge was perceived to be a shared responsibility among team members, whereas its application in patient care was seen as the responsibility of the team leader, usually the senior physician. PHCT members acknowledged the need for resources for information access, synthesis, interpretation, or management. Conclusion: Information sharing in interdisciplinary teams is a complex and multifaceted process. Specific interventions need to be improved such as formalizing modes of communication, better organizing knowledge-sharing activities, and improving the active use of allied health professionals. Despite movement toward team-based models, senior physicians are often gatekeepers of uptake of new evidence and changes in practice. PMID:23646028

Simulation Training: Evaluating the Instructor’s Contribution to a Wizard of Oz Simulator in Obstetrics and Gynecology Ultrasound Training

PubMed Central

Tepper, Ronnie

2017-01-01

Background Workplaces today demand graduates who are prepared with field-specific knowledge, advanced social skills, problem-solving skills, and integration capabilities. Meeting these goals with didactic learning (DL) is becoming increasingly difficult. Enhanced training methods that would better prepare tomorrow’s graduates must be more engaging and game-like, such as feedback based e-learning or simulation-based training, while saving time. Empirical evidence regarding the effectiveness of advanced learning methods is lacking. Objective quantitative research comparing advanced training methods with DL is sparse. Objectives This quantitative study assessed the effectiveness of a computerized interactive simulator coupled with an instructor who monitored students’ progress and provided Web-based immediate feedback. Methods A low-cost, globally accessible, telemedicine simulator, developed at the Technion—Israel Institute of Technology, Haifa, Israel—was used. A previous study in the field of interventional cardiology, evaluating the efficacy of the simulator to enhanced learning via knowledge exams, presented promising results of average scores varying from 94% after training and 54% before training (n=20) with P<.001. Two independent experiments involving obstetrics and gynecology (Ob-Gyn) physicians and senior ultrasound sonographers, with 32 subjects, were conducted using a new interactive concept of the WOZ (Wizard of OZ) simulator platform. The contribution of an instructor to learning outcomes was evaluated by comparing students’ knowledge before and after each interactive instructor-led session as well as after fully automated e-learning in the field of Ob-Gyn. Results from objective knowledge tests were analyzed using hypothesis testing and model fitting. Results A significant advantage (P=.01) was found in favor of the WOZ training approach. Content type and training audience were not significant. Conclusions This study evaluated the contribution of an integrated teaching environment using a computerized interactive simulator, with an instructor providing immediate Web-based immediate feedback to trainees. Involvement of an instructor in the simulation-based training process provided better learning outcomes that varied training content and trainee populations did not affect the overall learning gains. PMID:28432039

Determination of optimal imaging settings for urolithiasis CT using filtered back projection (FBP), statistical iterative reconstruction (IR) and knowledge-based iterative model reconstruction (IMR): a physical human phantom study

PubMed Central

Choi, Se Y; Ahn, Seung H; Choi, Jae D; Kim, Jung H; Lee, Byoung-Il; Kim, Jeong-In

2016-01-01

Objective: The purpose of this study was to compare CT image quality for evaluating urolithiasis using filtered back projection (FBP), statistical iterative reconstruction (IR) and knowledge-based iterative model reconstruction (IMR) according to various scan parameters and radiation doses. Methods: A 5 × 5 × 5 mm3 uric acid stone was placed in a physical human phantom at the level of the pelvis. 3 tube voltages (120, 100 and 80 kV) and 4 current–time products (100, 70, 30 and 15 mAs) were implemented in 12 scans. Each scan was reconstructed with FBP, statistical IR (Levels 5–7) and knowledge-based IMR (soft-tissue Levels 1–3). The radiation dose, objective image quality and signal-to-noise ratio (SNR) were evaluated, and subjective assessments were performed. Results: The effective doses ranged from 0.095 to 2.621 mSv. Knowledge-based IMR showed better objective image noise and SNR than did FBP and statistical IR. The subjective image noise of FBP was worse than that of statistical IR and knowledge-based IMR. The subjective assessment scores deteriorated after a break point of 100 kV and 30 mAs. Conclusion: At the setting of 100 kV and 30 mAs, the radiation dose can be decreased by approximately 84% while keeping the subjective image assessment. Advances in knowledge: Patients with urolithiasis can be evaluated with ultralow-dose non-enhanced CT using a knowledge-based IMR algorithm at a substantially reduced radiation dose with the imaging quality preserved, thereby minimizing the risks of radiation exposure while providing clinically relevant diagnostic benefits for patients. PMID:26577542

How to help intelligent systems with different uncertainty representations cooperate with each other

NASA Technical Reports Server (NTRS)

Kreinovich, Vladik YA.; Kumar, Sundeep

1991-01-01

In order to solve a complicated problem one must use the knowledge from different domains. Therefore, if one wants to automatize the solution of these problems, one has to help the knowledge-based systems that correspond to these domains cooperate, that is, communicate facts and conclusions to each other in the process of decision making. One of the main obstacles to such cooperation is the fact that different intelligent systems use different methods of knowledge acquisition and different methods and formalisms for uncertainty representation. So an interface f is needed, 'translating' the values x, y, which represent uncertainty of the experts' knowledge in one system, into the values f(x), f(y) appropriate for another one. The problem of designing such an interface as a mathematical problem is formulated and solved. It is shown that the interface must be fractionally linear: f(x) = (ax + b)/(cx + d).

Neurologist knowledge about interactions between antiepileptic drugs and contraceptive methods.

PubMed

Suto, Hilda S; Braga, Giordana C; Scarpellini, Giuliano R; Takeuchi, Leandro I; Martins, Ana P; Leite, João P; Vieira, Carolina S

2016-09-01

To evaluate neurologists' knowledge of contraceptive counseling for women receiving antiepileptic drugs (AEDs). An interview-based survey was conducted from February 2 to June 30, 2015, among neurologists working in Ribeirão Preto, Brazil. Direct interviews were conducted using a questionnaire that assessed knowledge of the pharmacological interactions between various contraceptive methods and six AEDs (carbamazepine, phenobarbital, topiramate, phenytoin, lamotrigine, and valproate) on the basis of WHO medical eligibility criteria for contraceptive use. Among 42 neurologists who participated, 32 (76%) stated that they treated women with epilepsy and provided them with counseling for family planning. Overall, 34 (81%) recommended the use of a copper intrauterine device irrespective of the AED used, and 26 (60%) stated that they co-prescribed AEDs and hormonal contraceptives. Although 39 (93%) neurologists had knowledge that AEDs might contraindicate the use of some contraceptives, their knowledge regarding the specific drug interactions was lacking. Furthermore, 34 (81%) had no knowledge of WHO medical eligibility criteria for contraceptive use. Although most neurologists interviewed had knowledge of interactions between AEDs and hormonal contraceptives, they did not know which specific AEDs interacted with these agents. Copyright © 2016 International Federation of Gynecology and Obstetrics. Published by Elsevier Ireland Ltd. All rights reserved.

Development of a Moodle Course for Schoolchildren's Table Tennis Learning Based on Competence Motivation Theory: Its Effectiveness in Comparison to Traditional Training Method

ERIC Educational Resources Information Center

Zou, Junhua; Liu, Qingtang; Yang, Zongkai

2012-01-01

Based on Competence Motivation Theory (CMT), a Moodle course for schoolchildren's table tennis learning was developed (The URL is http://www.bssepp.com, and this course allows guest access). The effects of the course on students' knowledge, perceived competence and interest were evaluated through quantitative methods. The sample of the study…

Right ventricular volumes assessed by echocardiographic three-dimensional knowledge-based reconstruction compared with magnetic resonance imaging in a clinical setting.

PubMed

Neukamm, Christian; Try, Kirsti; Norgård, Gunnar; Brun, Henrik

2014-01-01

A technique that uses two-dimensional images to create a knowledge-based, three-dimensional model was tested and compared to magnetic resonance imaging. Measurement of right ventricular volumes and function is important in the follow-up of patients after pulmonary valve replacement. Magnetic resonance imaging is the gold standard for volumetric assessment. Echocardiographic methods have been validated and are attractive alternatives. Thirty patients with tetralogy of Fallot (25 ± 14 years) after pulmonary valve replacement were examined. Magnetic resonance imaging volumetric measurements and echocardiography-based three-dimensional reconstruction were performed. End-diastolic volume, end-systolic volume, and ejection fraction were measured, and the results were compared. Magnetic resonance imaging measurements gave coefficient of variation in the intraobserver study of 3.5, 4.6, and 5.3 and in the interobserver study of 3.6, 5.9, and 6.7 for end-diastolic volume, end-systolic volume, and ejection fraction, respectively. Echocardiographic three-dimensional reconstruction was highly feasible (97%). In the intraobserver study, the corresponding values were 6.0, 7.0, and 8.9 and in the interobserver study 7.4, 10.8, and 13.4. In comparison of the methods, correlations with magnetic resonance imaging were r = 0.91, 0.91, and 0.38, and the corresponding coefficient of variations were 9.4, 10.8, and 14.7. Echocardiography derived volumes (mL/m(2)) were significantly higher than magnetic resonance imaging volumes in end-diastolic volume 13.7 ± 25.6 and in end-systolic volume 9.1 ± 17.0 (both P < .05). The knowledge-based three-dimensional right ventricular volume method was highly feasible. Intra and interobserver variabilities were satisfactory. Agreement with magnetic resonance imaging measurements for volumes was reasonable but unsatisfactory for ejection fraction. Knowledge-based reconstruction may replace magnetic resonance imaging measurements for serial follow-up, whereas magnetic resonance imaging should be used for surgical decision making.

The effects of computer-supported inquiry-based learning methods and peer interaction on learning stellar parallax

NASA Astrophysics Data System (ADS)

Ruzhitskaya, Lanika

The presented research study investigated the effects of computer-supported inquiry-based learning and peer interaction methods on effectiveness of learning a scientific concept. The stellar parallax concept was selected as a basic, and yet important in astronomy, scientific construct, which is based on a straightforward relationship of several components presented in a simple mathematical equation: d = 1/p. The simplicity of the concept allowed the researchers to explore how the learners construct their conceptual knowledge, build mathematical skills and transfer their knowledge beyond the learning settings. A computer-based tutorial Stellar Parallax Interactive Restricted and Unrestricted Tutorial (SPIRUT) was developed for this study, and was designed to aid students' knowledge construction of the concept either in a learner-controlled or a program-controlled mode. The first investigated method in the study was enhancing engagement by the means of scaffolding for inquiry, which included scripted prompts and called for students' predictions and reflections while working in the learner-controlled or the computer-controlled version of SPIRUT. A second form of enhancing engagement was through peers working cooperatively during the learning activities. The students' level of understanding of the concept was measured by (1) the number of correct answers on a conceptual test with (2) several questions that require knowledge transfer to unfamiliar situations and (3) their ability to calculate the stellar parallax and find distances to stars. The study was conducted in the University of Missouri among 199 non-science major students enrolled in an introductory astronomy course in the fall semester 2010. The participants were divided into two main groups: one was working with SPIRUT and another group was a control group and utilized a paper-based tutorial. The SPIRUT group was further divided into the learner-controlled and the program-controlled subgroups. Students' learning achievements were measured by two post- tests and compared to the students' results on a pre-test. The first post-test was administered right after the treatment with aim to measure the immediate effect of the treatment. The second post-test was administered eight weeks later and was aimed to elicit how much of the constructed knowledge students retained after the treatment. Results of the study revealed that students who learned the concept with SPIRUT constructed greater conceptual knowledge and were able to better transfer it to another situation while their mathematical skills were equally improved as those students who worked with the paper-based tutorial. It was also evident that there was no difference between students' performances after their engagement with the learner-controlled or with the program-controlled version of SPIRUT. It was also found that students who worked independently constructed slightly greater knowledge than students who worked with peers. Albeit, there was no significant difference found of retention of knowledge after any type of treatment.

SAFOD Brittle Microstructure and Mechanics Knowledge Base (SAFOD BM2KB)

NASA Astrophysics Data System (ADS)

Babaie, H. A.; Hadizadeh, J.; di Toro, G.; Mair, K.; Kumar, A.

2008-12-01

We have developed a knowledge base to store and present the data collected by a group of investigators studying the microstructures and mechanics of brittle faulting using core samples from the SAFOD (San Andreas Fault Observatory at Depth) project. The investigations are carried out with a variety of analytical and experimental methods primarily to better understand the physics of strain localization in fault gouge. The knowledge base instantiates an specially-designed brittle rock deformation ontology developed at Georgia State University. The inference rules embedded in the semantic web languages, such as OWL, RDF, and RDFS, which are used in our ontology, allow the Pellet reasoner used in this application to derive additional truths about the ontology and knowledge of this domain. Access to the knowledge base is via a public website, which is designed to provide the knowledge acquired by all the investigators involved in the project. The stored data will be products of studies such as: experiments (e.g., high-velocity friction experiment), analyses (e.g., microstructural, chemical, mass transfer, mineralogical, surface, image, texture), microscopy (optical, HRSEM, FESEM, HRTEM]), tomography, porosity measurement, microprobe, and cathodoluminesence. Data about laboratories, experimental conditions, methods, assumptions, equipments, and mechanical properties and lithology of the studied samples will also be presented on the website per investigation. The ontology was modeled applying the UML (Unified Modeling Language) in Rational Rose, and implemented in OWL-DL (Ontology Web Language) using the Protégé ontology editor. The UML model was converted to OWL-DL by first mapping it to Ecore (.ecore) and Generator model (.genmodel) with the help of the EMF (Eclipse Modeling Framework) plugin in Eclipse. The Ecore model was then mapped to a .uml file, which later was converted into an .owl file and subsequently imported into the Protégé ontology editing environment. The web-interface was developed in java using eclipse as the IDE. The web interfaces to query and submit data were implemented applying JSP, servlets, javascript, and AJAX. The Jena API, a Java framework for building Semantic Web applications, was used to develop the web-interface. Jena provided a programmatic environment for RDF, RDFS, OWL, and SPARQL query engine. Building web applications with AJAX helps retrieving data from the server asynchronously in the background without interfering with the display and behavior of the existing page. The application was deployed on an apache tomcat server at GSU. The SAFOD BM2KB website provides user-friendly search, submit, feedback, and other services. The General Search option allows users to search the knowledge base by selecting the classes (e.g., Experiment, Surface Analysis), their respective attributes (e.g., apparatus, date performed), and the relationships to other classes (e.g., Sample, Laboratory). The Search by Sample option allows users to search the knowledge base based on sample number. The Search by Investigator lets users to search the knowledge base by choosing an investigator who is involved in this project. The website also allows users to submit new data. The Submit Data option opens a page where users can submit the SAFOD data to our knowledge base by selecting specific classes and attributes. The submitted data then become available for query as part of the knowledge base. The SAFOD BM2KB can be accessed from the main SAFOD website.

Pathway-based analyses.

PubMed

Kent, Jack W

2016-02-03

New technologies for acquisition of genomic data, while offering unprecedented opportunities for genetic discovery, also impose severe burdens of interpretation and penalties for multiple testing. The Pathway-based Analyses Group of the Genetic Analysis Workshop 19 (GAW19) sought reduction of multiple-testing burden through various approaches to aggregation of highdimensional data in pathways informed by prior biological knowledge. Experimental methods testedincluded the use of "synthetic pathways" (random sets of genes) to estimate power and false-positive error rate of methods applied to simulated data; data reduction via independent components analysis, single-nucleotide polymorphism (SNP)-SNP interaction, and use of gene sets to estimate genetic similarity; and general assessment of the efficacy of prior biological knowledge to reduce the dimensionality of complex genomic data. The work of this group explored several promising approaches to managing high-dimensional data, with the caveat that these methods are necessarily constrained by the quality of external bioinformatic annotation.

Computer-Assisted Learning Applications in Health Educational Informatics: A Review.

PubMed

Shaikh, Faiq; Inayat, Faisal; Awan, Omer; Santos, Marlise D; Choudhry, Adnan M; Waheed, Abdul; Kajal, Dilkash; Tuli, Sagun

2017-08-10

Computer-assisted learning (CAL) as a health informatics application is a useful tool for medical students in the era of expansive knowledge bases and the increasing need for and the consumption of automated and interactive systems. As the scope and breadth of medical knowledge expand, the need for additional learning outside of lecture hours is becoming increasingly important. CAL can be an impactful adjunct to conventional methods that currently exist in the halls of learning. There is an increasing body of literature that suggests that CAL should be a commonplace and the recommended method of learning for medical students. Factors such as technical issues that hinder the performance of CAL are also evaluated. We conclude by encouraging the use of CAL by medical students as a highly beneficial method of learning that complements and enhances lectures and provides intuitive, interactive modulation of a self-paced curriculum based on the individual's academic abilities.

Accreditation Council for Graduate Medical Education Core Competencies at a Community Teaching Hospital: Is There a Gap in Awareness?

PubMed Central

Al-Temimi, Mohammed; Kidon, Michael; Johna, Samir

2016-01-01

Context Reports evaluating faculty knowledge of the Accreditation Council for Graduate Medical Education (ACGME) core competencies in community hospitals without a dedicated residency program are uncommon. Objective Faculty evaluation regarding knowledge of ACGME core competencies before a residency program is started. Design Physicians at the Kaiser Permanente Fontana Medical Center (N = 480) were surveyed for their knowledge of ACGME core competencies before starting new residency programs. Main Outcome Measures Knowledge of ACGME core competencies. Results Fifty percent of physicians responded to the survey, and 172 (71%) of respondents were involved in teaching residents. Of physicians who taught residents and had complete responses (N = 164), 65 (39.7%) were unsure of their knowledge of the core competencies. However, most stated that they provided direct teaching to residents related to the knowledge, skills, and attitudes stated in each of the 6 competencies as follows: medical knowledge (96.3%), patient care (95.7%), professionalism (90.7%), interpersonal and communication skills (86.3%), practice-based learning (85.9%), and system-based practice (79.6%). Physician specialty, years in practice (1–10 vs > 10), and number of rotations taught per year (1–6 vs 7–12) were not associated with knowledge of the competencies (p > 0.05); however, full-time faculty (teaching 10–12 rotations per year) were more likely to provide competency-based teaching. Conclusion Objective assessment of faculty awareness of ACGME core competencies is essential when starting a residency program. Discrepancy between knowledge of the competencies and acclaimed provision of competency-based teaching emphasizes the need for standardized teaching methods that incorporate the values of these competencies. PMID:27768565

A Knowledge-Based System For Analysis, Intervention Planning and Prevention of Defects in Immovable Cultural Heritage Objects and Monuments

NASA Astrophysics Data System (ADS)

Valach, J.; Cacciotti, R.; Kuneš, P.; ČerÅanský, M.; Bláha, J.

2012-04-01

The paper presents a project aiming to develop a knowledge-based system for documentation and analysis of defects of cultural heritage objects and monuments. The MONDIS information system concentrates knowledge on damage of immovable structures due to various causes, and preventive/remedial actions performed to protect/repair them, where possible. The currently built system is to provide for understanding of causal relationships between a defect, materials, external load, and environment of built object. Foundation for the knowledge-based system will be the systemized and formalized knowledge on defects and their mitigation acquired in the process of analysis of a representative set of cases documented in the past. On the basis of design comparability, used technologies, materials and the nature of the external forces and surroundings, the developed software system has the capacity to indicate the most likely risks of new defect occurrence or the extension of the existing ones. The system will also allow for a comparison of the actual failure with similar cases documented and will propose a suitable technical intervention plan. The system will provide conservationists, administrators and owners of historical objects with a toolkit for defect documentation for their objects. Also, advanced artificial intelligence methods will offer accumulated knowledge to users and will also enable them to get oriented in relevant techniques of preventive interventions and reconstructions based on similarity with their case.

Learning gait of quadruped robot without prior knowledge of the environment

NASA Astrophysics Data System (ADS)

Xu, Tao; Chen, Qijun

2012-09-01

Walking is the basic skill of a legged robot, and one of the promising ways to improve the walking performance and its adaptation to environment changes is to let the robot learn its walking by itself. Currently, most of the walking learning methods are based on robot vision system or some external sensing equipment to estimate the walking performance of certain walking parameters, and therefore are usually only applicable under laboratory condition, where environment can be pre-defined. Inspired by the rhythmic swing movement during walking of legged animals and the behavior of their adjusting their walking gait on different walking surfaces, a concept of walking rhythmic pattern(WRP) is proposed to evaluate the walking specialty of legged robot, which is just based on the walking dynamics of the robot. Based on the onboard acceleration sensor data, a method to calculate WRP using power spectrum in frequency domain and diverse smooth filters is also presented. Since the evaluation of WRP is only based on the walking dynamics data of the robot's body, the proposed method doesn't require prior knowledge of environment and thus can be applied in unknown environment. A gait learning approach of legged robots based on WRP and evolution algorithm(EA) is introduced. By using the proposed approach, a quadruped robot can learn its locomotion by its onboard sensing in an unknown environment, where the robot has no prior knowledge about this place. The experimental result proves proportional relationship exits between WRP match score and walking performance of legged robot, which can be used to evaluate the walking performance in walking optimization under unknown environment.

Methodology for the specification of communication activities within the framework of a multi-layered architecture: Toward the definition of a knowledge base

NASA Astrophysics Data System (ADS)

Amyay, Omar

A method defined in terms of synthesis and verification steps is presented. The specification of the services and protocols of communication within a multilayered architecture of the Open Systems Interconnection (OSI) type is an essential issue for the design of computer networks. The aim is to obtain an operational specification of the protocol service couple of a given layer. Planning synthesis and verification steps constitute a specification trajectory. The latter is based on the progressive integration of the 'initial data' constraints and verification of the specification originating from each synthesis step, through validity constraints that characterize an admissible solution. Two types of trajectories are proposed according to the style of the initial specification of the service protocol couple: operational type and service supplier viewpoint; knowledge property oriented type and service viewpoint. Synthesis and verification activities were developed and formalized in terms of labeled transition systems, temporal logic and epistemic logic. The originality of the second specification trajectory and the use of the epistemic logic are shown. An 'artificial intelligence' approach enables a conceptual model to be defined for a knowledge base system for implementing the method proposed. It is structured in three levels of representation of the knowledge relating to the domain, the reasoning characterizing synthesis and verification activities and the planning of the steps of a specification trajectory.

Energetics of protein-DNA interactions.

PubMed

Donald, Jason E; Chen, William W; Shakhnovich, Eugene I

2007-01-01

Protein-DNA interactions are vital for many processes in living cells, especially transcriptional regulation and DNA modification. To further our understanding of these important processes on the microscopic level, it is necessary that theoretical models describe the macromolecular interaction energetics accurately. While several methods have been proposed, there has not been a careful comparison of how well the different methods are able to predict biologically important quantities such as the correct DNA binding sequence, total binding free energy and free energy changes caused by DNA mutation. In addition to carrying out the comparison, we present two important theoretical models developed initially in protein folding that have not yet been tried on protein-DNA interactions. In the process, we find that the results of these knowledge-based potentials show a strong dependence on the interaction distance and the derivation method. Finally, we present a knowledge-based potential that gives comparable or superior results to the best of the other methods, including the molecular mechanics force field AMBER99.

Knowledge-based segmentation and feature analysis of hand and wrist radiographs

NASA Astrophysics Data System (ADS)

Efford, Nicholas D.

1993-07-01

The segmentation of hand and wrist radiographs for applications such as skeletal maturity assessment is best achieved by model-driven approaches incorporating anatomical knowledge. The reasons for this are discussed, and a particular frame-based or 'blackboard' strategy for the simultaneous segmentation of the hand and estimation of bone age via the TW2 method is described. The new approach is structured for optimum robustness and computational efficiency: features of interest are detected and analyzes in order of their size and prominence in the image, the largest and most distinctive being dealt with first, and the evidence generated by feature analysis is used to update a model of hand anatomy and hence guide later stages of the segmentation. Closed bone boundaries are formed by a hybrid technique combining knowledge-based, one-dimensional edge detection with model-assisted heuristic tree searching.