Building validation tools for knowledge-based systems

NASA Technical Reports Server (NTRS)

Stachowitz, R. A.; Chang, C. L.; Stock, T. S.; Combs, J. B.

1987-01-01

The Expert Systems Validation Associate (EVA), a validation system under development at the Lockheed Artificial Intelligence Center for more than a year, provides a wide range of validation tools to check the correctness, consistency and completeness of a knowledge-based system. A declarative meta-language (higher-order language), is used to create a generic version of EVA to validate applications written in arbitrary expert system shells. The architecture and functionality of EVA are presented. The functionality includes Structure Check, Logic Check, Extended Structure Check (using semantic information), Extended Logic Check, Semantic Check, Omission Check, Rule Refinement, Control Check, Test Case Generation, Error Localization, and Behavior Verification.

Use of the self-organising map network (SOMNet) as a decision support system for regional mental health planning.

PubMed

Chung, Younjin; Salvador-Carulla, Luis; Salinas-Pérez, José A; Uriarte-Uriarte, Jose J; Iruin-Sanz, Alvaro; García-Alonso, Carlos R

2018-04-25

Decision-making in mental health systems should be supported by the evidence-informed knowledge transfer of data. Since mental health systems are inherently complex, involving interactions between its structures, processes and outcomes, decision support systems (DSS) need to be developed using advanced computational methods and visual tools to allow full system analysis, whilst incorporating domain experts in the analysis process. In this study, we use a DSS model developed for interactive data mining and domain expert collaboration in the analysis of complex mental health systems to improve system knowledge and evidence-informed policy planning. We combine an interactive visual data mining approach, the self-organising map network (SOMNet), with an operational expert knowledge approach, expert-based collaborative analysis (EbCA), to develop a DSS model. The SOMNet was applied to the analysis of healthcare patterns and indicators of three different regional mental health systems in Spain, comprising 106 small catchment areas and providing healthcare for over 9 million inhabitants. Based on the EbCA, the domain experts in the development team guided and evaluated the analytical processes and results. Another group of 13 domain experts in mental health systems planning and research evaluated the model based on the analytical information of the SOMNet approach for processing information and discovering knowledge in a real-world context. Through the evaluation, the domain experts assessed the feasibility and technology readiness level (TRL) of the DSS model. The SOMNet, combined with the EbCA, effectively processed evidence-based information when analysing system outliers, explaining global and local patterns, and refining key performance indicators with their analytical interpretations. The evaluation results showed that the DSS model was feasible by the domain experts and reached level 7 of the TRL (system prototype demonstration in operational environment). This study supports the benefits of combining health systems engineering (SOMNet) and expert knowledge (EbCA) to analyse the complexity of health systems research. The use of the SOMNet approach contributes to the demonstration of DSS for mental health planning in practice.

Does Joint Fact-finding work for Water-energy-food Nexus Issues? A Role of Scientific Evidence in Policy Process

NASA Astrophysics Data System (ADS)

Baba, K.

2014-12-01

A quite famous phrase in risk management "How safe is enough safe?" implies there exists a framing gap among experts, the general public and stakeholders. Scientific evidence that experts provide usually contains uncertainty, while the public tends to have the other type of qualitative local knowledge. As there is no zero-risk society, we have to build consensus on acceptable level of risk and trade-offs of risks based on expert knowledge and local knowledge. Therefore having a dialogue among them in the early stage of the policy process such as problem definition and agenda setting is essential to cultivate trust and to integrate their knowledge. To this end, we especially pay attention to Joint Fact-finding (JFF). The tentative definition of JFF is that a promising strategy for experts, decision makers, and key public rights-holders and stakeholders from opposing sides of an issue to work together to resolve or narrow factual disputes over public policy issues. JFF process usually begins with identifying stakeholders and holding interviews with them to determine their interests. We call this step stakeholder analysis. Then we define the scope of the study including the required scientific evidence and the preliminary list of experts. After that, stakeholders jointly select experts to participate in the study, then they work together on what they would like to clear about scientific evidence. They finally get the common understanding and findings through these collaboration. We applied the stakeholder analysis to the issue of groundwater in Obama City and the issues of hot spring water and geothermal power in Beppu City in Japan. We drew conclusions from these case studies to some extent but at the same time we found that the analysis method has a limitation in applying it to multiple nexus issues because the method based on stakeholders' cognition. For example, in Obama case, we identified a lack of cooperation among stakeholders that especially agricultural sector who should have positive relationship with groundwater in nature is not involved in groundwater issue thoroughly. However, we could not enough furnish stakeholders with the framing of trade-offs between resources. Accordingly we need to raise awareness of stakeholders with scientific evidence of experts on the way of the stakeholder analysis.

Diversity, local knowledge and use of stingless bees (Apidae: Meliponini) in the municipality of Nocupétaro, Michoacan, Mexico

PubMed Central

2014-01-01

Background Stingless bees were significant resources managed by Mesoamerican peoples during pre-Columbian times and remain important in particular areas. Our study aimed at inventorying stingless bees’ species, traditional knowledge and forms of use and management of them at the municipality of Nocupetaro, Michoacán, Mexico, a region of the Balsas River Basin. Methods We inventoried the stingless bees of the municipality of Nocupétaro, Michoacán, México, through extensive collecting of bee specimens in different vegetation types. We then conducted semi-structured interviews to local experts in order to document their knowledge and management techniques of stingless bees’ species. Results We identified a total of eight stingless bees’ species in the study area as well as three additional unidentified taxa recognized by people through the local names. Our inventory included one new record of species for the region (Lestrimelitta chamelensis Ayala, 1999). The taxa identified are all used by local people. Scaptotrigona hellwegeri Friese, 1900; Melipona fasciata Latreille, 1811; Frieseomelitta nigra Cresson, 1878 and Geotrigona acapulconis Strand, 1919 are particularly valued as food (honey), medicinal (honey and pollen), and material for handcrafts (wax). All species recorded are wild and their products are obtained through gathering. On average, local experts were able to collect 4 nests of stingless bees per year obtaining on average 6 L of honey and 4 Kg of wax but some came to collect up 10–12 hives per year (18 L of honey and 24 Kg of wax). Conclusions Local knowledge about use, management and ecological issues on stingless bees is persistent and deep in the study area. Information about this group of bees is progressively scarcer in Mexico and significant effort should be done from ethnobiological and ecological perspectives in order to complement the national inventory of bee resources and traditional knowledge and management of them. PMID:24903644

Diversity, local knowledge and use of stingless bees (Apidae: Meliponini) in the municipality of Nocupétaro, Michoacan, Mexico.

PubMed

Reyes-González, Alejandro; Camou-Guerrero, Andrés; Reyes-Salas, Octavio; Argueta, Arturo; Casas, Alejandro

2014-06-05

Stingless bees were significant resources managed by Mesoamerican peoples during pre-Columbian times and remain important in particular areas. Our study aimed at inventorying stingless bees' species, traditional knowledge and forms of use and management of them at the municipality of Nocupetaro, Michoacán, Mexico, a region of the Balsas River Basin. We inventoried the stingless bees of the municipality of Nocupétaro, Michoacán, México, through extensive collecting of bee specimens in different vegetation types. We then conducted semi-structured interviews to local experts in order to document their knowledge and management techniques of stingless bees' species. We identified a total of eight stingless bees' species in the study area as well as three additional unidentified taxa recognized by people through the local names. Our inventory included one new record of species for the region (Lestrimelitta chamelensis Ayala, 1999). The taxa identified are all used by local people. Scaptotrigona hellwegeri Friese, 1900; Melipona fasciata Latreille, 1811; Frieseomelitta nigra Cresson, 1878 and Geotrigona acapulconis Strand, 1919 are particularly valued as food (honey), medicinal (honey and pollen), and material for handcrafts (wax). All species recorded are wild and their products are obtained through gathering. On average, local experts were able to collect 4 nests of stingless bees per year obtaining on average 6 L of honey and 4 Kg of wax but some came to collect up 10-12 hives per year (18 L of honey and 24 Kg of wax). Local knowledge about use, management and ecological issues on stingless bees is persistent and deep in the study area. Information about this group of bees is progressively scarcer in Mexico and significant effort should be done from ethnobiological and ecological perspectives in order to complement the national inventory of bee resources and traditional knowledge and management of them.

Air quality as respiratory health indicator: a critical review.

PubMed

Moshammer, Hanns; Wallner, Peter

2011-09-01

As part of the European Public Health project IMCA II validity and practicability of "air pollution" as a respiratory health indicator were analyzed. The definitions of air quality as an indicator proposed by the WHO project ECOEHIS and by IMCA I were compared. The public availability of the necessary data was checked through access to web-based data-bases. Practicability and interpretation of the indicator were discussed with project partners and external experts. Air quality serves as a kind of benchmark for the good health-related environmental policy. In this sense, it is a relevant health indicator. Although air quality is not directly in the responsibility of health policy, its vital importance for the population's health should not be neglected. In principle, data is available to calculate this IMCA indicator for any chosen area in Europe. The indicator is relevant and informative, but calculation and interpretation need input from local expert knowledge. The European health policy is well advised to take air quality into account. To that end, an interdisciplinary approach is warranted. The proposed definition of air quality as a (respiratory) health indicator is workable, but correct interpretation depends on expert and local knowledge.

Establishment of a hydrological monitoring network in a tropical African catchment: An integrated participatory approach

NASA Astrophysics Data System (ADS)

Gomani, M. C.; Dietrich, O.; Lischeid, G.; Mahoo, H.; Mahay, F.; Mbilinyi, B.; Sarmett, J.

Sound decision making for water resources management has to be based on good knowledge of the dominant hydrological processes of a catchment. This information can only be obtained through establishing suitable hydrological monitoring networks. Research catchments are typically established without involving the key stakeholders, which results in instruments being installed at inappropriate places as well as at high risk of theft and vandalism. This paper presents an integrated participatory approach for establishing a hydrological monitoring network. We propose a framework with six steps beginning with (i) inception of idea; (ii) stakeholder identification; (iii) defining the scope of the network; (iv) installation; (v) monitoring; and (vi) feedback mechanism integrated within the participatory framework. The approach is illustrated using an example of the Ngerengere catchment in Tanzania. In applying the approach, the concept of establishing the Ngerengere catchment monitoring network was initiated in 2008 within the Resilient Agro-landscapes to Climate Change in Tanzania (ReACCT) research program. The main stakeholders included: local communities; Sokoine University of Agriculture; Wami Ruvu Basin Water Office and the ReACCT Research team. The scope of the network was based on expert experience in similar projects and lessons learnt from literature review of similar projects from elsewhere integrated with local expert knowledge. The installations involved reconnaissance surveys, detailed surveys, and expert consultations to identify best sites. First, a Digital Elevation Model, land use, and soil maps were used to identify potential monitoring sites. Local and expert knowledge was collected on flow regimes, indicators of shallow groundwater plant species, precipitation pattern, vegetation, and soil types. This information was integrated and used to select sites for installation of an automatic weather station, automatic rain gauges, river flow gauging stations, flow measurement sites and shallow groundwater wells. The network is now used to monitor hydro-meteorological parameters in collaboration with key stakeholders in the catchment. Preliminary results indicate that the network is working well. The benefits of this approach compared to conventional narrow scientific/technical approaches have been shown by gaining rapid insight into the hydrology of the catchment, identifying best sites for the instruments; and voluntary participation of stakeholders in installation, monitoring and safeguarding the installations. This approach has proved simple yet effective and yielded good results. Based on this experience gained in applying the approach in establishing the Ngerengere catchment monitoring network, we conclude that the integrated participatory approach helps to assimilate local and expert knowledge in catchments monitoring which consequently results in: (i) identifying best sites for the hydrologic monitoring; (ii) instilling the sense of ownership; (iii) providing security of the installed network; and (iv) minimizing costs for installation and monitoring.

User Directed Tools for Exploiting Expert Knowledge in an Immersive Segmentation and Visualization Environment

NASA Technical Reports Server (NTRS)

Senger, Steven O.

1998-01-01

Volumetric data sets have become common in medicine and many sciences through technologies such as computed x-ray tomography (CT), magnetic resonance (MR), positron emission tomography (PET), confocal microscopy and 3D ultrasound. When presented with 2D images humans immediately and unconsciously begin a visual analysis of the scene. The viewer surveys the scene identifying significant landmarks and building an internal mental model of presented information. The identification of features is strongly influenced by the viewers expectations based upon their expert knowledge of what the image should contain. While not a conscious activity, the viewer makes a series of choices about how to interpret the scene. These choices occur in parallel with viewing the scene and effectively change the way the viewer sees the image. It is this interaction of viewing and choice which is the basis of many familiar visual illusions. This is especially important in the interpretation of medical images where it is the expert knowledge of the radiologist which interprets the image. For 3D data sets this interaction of view and choice is frustrated because choices must precede the visualization of the data set. It is not possible to visualize the data set with out making some initial choices which determine how the volume of data is presented to the eye. These choices include, view point orientation, region identification, color and opacity assignments. Further compounding the problem is the fact that these visualization choices are defined in terms of computer graphics as opposed to language of the experts knowledge. The long term goal of this project is to develop an environment where the user can interact with volumetric data sets using tools which promote the utilization of expert knowledge by incorporating visualization and choice into a tight computational loop. The tools will support activities involving the segmentation of structures, construction of surface meshes and local filtering of the data set. To conform to this environment tools should have several key attributes. First, they should be only rely on computations over a local neighborhood of the probe position. Second, they should operate iteratively over time converging towards a limit behavior. Third, they should adapt to user input modifying they operational parameters with time.

Capturing farm diversity with hypothesis-based typologies: An innovative methodological framework for farming system typology development

PubMed Central

Alvarez, Stéphanie; Timler, Carl J.; Michalscheck, Mirja; Paas, Wim; Descheemaeker, Katrien; Tittonell, Pablo; Andersson, Jens A.; Groot, Jeroen C. J.

2018-01-01

Creating typologies is a way to summarize the large heterogeneity of smallholder farming systems into a few farm types. Various methods exist, commonly using statistical analysis, to create these typologies. We demonstrate that the methodological decisions on data collection, variable selection, data-reduction and clustering techniques can bear a large impact on the typology results. We illustrate the effects of analysing the diversity from different angles, using different typology objectives and different hypotheses, on typology creation by using an example from Zambia’s Eastern Province. Five separate typologies were created with principal component analysis (PCA) and hierarchical clustering analysis (HCA), based on three different expert-informed hypotheses. The greatest overlap between typologies was observed for the larger, wealthier farm types but for the remainder of the farms there were no clear overlaps between typologies. Based on these results, we argue that the typology development should be guided by a hypothesis on the local agriculture features and the drivers and mechanisms of differentiation among farming systems, such as biophysical and socio-economic conditions. That hypothesis is based both on the typology objective and on prior expert knowledge and theories of the farm diversity in the study area. We present a methodological framework that aims to integrate participatory and statistical methods for hypothesis-based typology construction. This is an iterative process whereby the results of the statistical analysis are compared with the reality of the target population as hypothesized by the local experts. Using a well-defined hypothesis and the presented methodological framework, which consolidates the hypothesis through local expert knowledge for the creation of typologies, warrants development of less subjective and more contextualized quantitative farm typologies. PMID:29763422

Capturing farm diversity with hypothesis-based typologies: An innovative methodological framework for farming system typology development.

PubMed

Alvarez, Stéphanie; Timler, Carl J; Michalscheck, Mirja; Paas, Wim; Descheemaeker, Katrien; Tittonell, Pablo; Andersson, Jens A; Groot, Jeroen C J

2018-01-01

Creating typologies is a way to summarize the large heterogeneity of smallholder farming systems into a few farm types. Various methods exist, commonly using statistical analysis, to create these typologies. We demonstrate that the methodological decisions on data collection, variable selection, data-reduction and clustering techniques can bear a large impact on the typology results. We illustrate the effects of analysing the diversity from different angles, using different typology objectives and different hypotheses, on typology creation by using an example from Zambia's Eastern Province. Five separate typologies were created with principal component analysis (PCA) and hierarchical clustering analysis (HCA), based on three different expert-informed hypotheses. The greatest overlap between typologies was observed for the larger, wealthier farm types but for the remainder of the farms there were no clear overlaps between typologies. Based on these results, we argue that the typology development should be guided by a hypothesis on the local agriculture features and the drivers and mechanisms of differentiation among farming systems, such as biophysical and socio-economic conditions. That hypothesis is based both on the typology objective and on prior expert knowledge and theories of the farm diversity in the study area. We present a methodological framework that aims to integrate participatory and statistical methods for hypothesis-based typology construction. This is an iterative process whereby the results of the statistical analysis are compared with the reality of the target population as hypothesized by the local experts. Using a well-defined hypothesis and the presented methodological framework, which consolidates the hypothesis through local expert knowledge for the creation of typologies, warrants development of less subjective and more contextualized quantitative farm typologies.

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.

Semantic Mappings and Locality of Nursing Diagnostic Concepts in UMLS

PubMed Central

Kim, Tae Youn; Coenen, Amy; Hardiker, Nicholas

2011-01-01

One solution for enhancing the interoperability between nursing information systems, given the availability of multiple nursing terminologies, is to cross-map existing nursing concepts. The Unified Medical Language System (UMLS) developed and distributed by the National Library of Medicine (NLM) is a knowledge resource containing cross-mappings of various terminologies in a unified framework. While the knowledge resource has been available for the last two decades, little research on the representation of nursing terminologies in UMLS has been conducted. As a first step, UMLS semantic mappings and concept locality were examined for nursing diagnostic concepts or problems selected from three terminologies (i.e., CCC, ICNP, and NANDA-I) along with corresponding SNOMED CT concepts. The evaluation of UMLS semantic mappings was conducted by measuring the proportion of concordance between UMLS and human expert mappings. The semantic locality of nursing diagnostic concepts was assessed by examining the associations of select concepts and the placement of the nursing concepts on the Semantic Network and Group. The study found that the UMLS mappings of CCC and NANDA-I concepts to SNOMED CT were highly concordant to expert mappings. The level of concordance in mappings of ICNP to SNOMED CT, CCC and NANDA-I within UMLS was relatively low, indicating the need for further research and development. Likewise, the semantic locality of ICNP concepts could be further improved. Various stakeholders need to collaborate to enhance the NLM knowledge resource and the interoperability of nursing data within the discipline as well as across health-related disciplines. PMID:21951759

Indigenous Knowledge and Sea Ice Science: What Can We Learn from Indigenous Ice Users?

NASA Astrophysics Data System (ADS)

Eicken, H.

2010-12-01

Drawing on examples mostly from Iñupiaq and Yup’ik sea-ice expertise in coastal Alaska, this contribution examines how local, indigenous knowledge (LIK) can inform and guide geophysical and biological sea-ice research. Part of the relevance of LIK derives from its linkage to sea-ice use and the services coastal communities derive from the ice cover. As a result, indigenous experts keep track of a broad range of sea-ice variables at a particular location. These observations are embedded into a broader worldview that speaks to both long-term variability or change and to the system of values associated with ice use. The contribution examines eight different contexts in which LIK in study site selection and assessment of a sampling campaign in the context of inter annual variability, the identification of rare or inconspicuous phenomena or events, the contribution by indigenous experts to hazard assessment and emergency response, the record of past and present climate embedded in LIK, and the value of holistic sea-ice knowledge in detecting subtle, intertwined patterns of environmental change. The relevance of local, indigenous sea-ice expertise in helping advance adaptation and responses to climate change as well as its potential role in guiding research questions and hypotheses are also examined. The challenges that may have to be overcome in creating an interface for exchange between indigenous experts and seaice researchers are considered. Promising approaches to overcome these challenges include cross-cultural, interdisciplinary education, and the fostering of Communities of Practice.

Autonomously acquiring declarative and procedural knowledge for ICAT systems

NASA Technical Reports Server (NTRS)

Kovarik, Vincent J., Jr.

1993-01-01

The construction of Intelligent Computer Aided Training (ICAT) systems is critically dependent on the ability to define and encode knowledge. This knowledge engineering effort can be broadly divided into two categories: domain knowledge and expert or task knowledge. Domain knowledge refers to the physical environment or system with which the expert interacts. Expert knowledge consists of the set of procedures and heuristics employed by the expert in performing their task. Both these areas are a significant bottleneck in the acquisition of knowledge for ICAT systems. This paper presents a research project in the area of autonomous knowledge acquisition using a passive observation concept. The system observes an expert and then generalizes the observations into production rules representing the domain expert's knowledge.

Making intersections safer : a toolbox of engineering countermeasures to reduce red-light running : an informational report

DOT National Transportation Integrated Search

2003-01-01

The Institute of Transportation Engineers (ITE) formed a panel of experts from federal, state and local governments, as well as academia and the private sector, to share knowledge and experiences in addressing red-light running using engineering coun...

Working with local nurses to promote hospital-nursing care during humanitarian assignments overseas: experiences from the perspectives of nurses.

PubMed

Tjoflåt, Ingrid; Karlsen, Bjørg; Saetre Hansen, Britt

2016-06-01

To describe how Norwegian expatriate nurses engaged in humanitarian assignments overseas experience working with the local nurses promoting nursing care in the hospital ward. Western countries have a long tradition of providing nurses with expert knowledge in nursing care for humanitarian projects and international work overseas. Studies from humanitarian mission revealed that health workers rarely acknowledge or use the local knowledge. However, there is a lack of studies highlighting expatriate nurses' experiences working with local nurses to promote nursing care in the hospital ward. This study applies a descriptive explorative qualitative design. The data were collected in 2013 by means of seven semi-structured interviews and analysed using qualitative content analysis. The data analyses revealed three themes related to the expatriate nurses' experiences of working with the local nurses to promote nursing care in the hospital ward: (1) Breaking the code, (2) Colliding worlds and (3) Challenges in sharing knowledge. The findings reflect different challenges when working with the local nurses. Findings indicate valuable knowledge gained about local nursing care and the local health and educational system. They also demonstrate challenges for the expatriate nurses related to the local nursing standard in the wards and using the local nurses' experiences and knowledge when working together. The findings can inform nurses, humanitarian organisations and institutions working overseas regarding the recruitment and the preparation of nurses who want to work cross- culturally or in humanitarian missions overseas. © 2016 John Wiley & Sons Ltd.

Expert and non-expert knowledge in medical practice.

PubMed

Nordin, I

2000-01-01

One problematic aspect of the rationality of medical practice concerns the relation between expert knowledge and non-expert knowledge. In medical practice it is important to match medical knowledge with the self-knowledge of the individual patient. This paper tries to study the problem of such matching by describing a model for technological paradigms and comparing it with an ideal of technological rationality. The professionalised experts tend to base their decisions and actions mostly on medical knowledge while the rationality of medicine also involves just as important elements of the personal evaluation and knowledge of the patients. Since both types of knowledge are necessary for rational decisions, the gap between the expert and the non-expert has to be bridged in some way. A solution to the problem is suggested in terms of pluralism, with the patient as ultimate decision-maker.

Alaska shorefast ice: Interfacing geophysics with local sea ice knowledge and use

NASA Astrophysics Data System (ADS)

Druckenmiller, Matthew L.

This thesis interfaces geophysical techniques with local and traditional knowledge (LTK) of indigenous ice experts to track and evaluate coastal sea ice conditions over annual and inter-annual timescales. A novel approach is presented for consulting LTK alongside a systematic study of where, when, and how the community of Barrow, Alaska uses the ice cover. The goal of this research is to improve our understanding of and abilities to monitor the processes that govern the state and dynamics of shorefast sea ice in the Chukchi Sea and use of ice by the community. Shorefast ice stability and community strategies for safe hunting provide a framework for data collection and knowledge sharing that reveals how nuanced observations by Inupiat ice experts relate to identifying hazards. In particular, shorefast ice break-out events represent a significant threat to the lives of hunters. Fault tree analysis (FTA) is used to combine local and time-specific observations of ice conditions by both geophysical instruments and local experts, and to evaluate how ice features, atmospheric and oceanic forces, and local to regional processes interact to cause break-out events. Each year, the Barrow community builds trails across shorefast ice for use during the spring whaling season. In collaboration with hunters, a systematic multi-year survey (2007--2011) was performed to map these trails and measure ice thickness along them. Relationships between ice conditions and hunter strategies that guide trail placement and risk assessment are explored. In addition, trail surveys provide a meaningful and consistent approach to monitoring the thickness distribution of shorefast ice, while establishing a baseline for assessing future environmental change and potential impacts to the community. Coastal communities in the region have proven highly adaptive in their ability to safely and successfully hunt from sea ice over the last 30 years as significant changes have been observed in the ice zone north of Alaska. This research further illustrates how Barrow's whaling community copes with year-to-year variability and significant intra-seasonal changes in ice conditions. Hence, arctic communities that have coped with such short-term variability may be more adaptive to future environmental change than communities located in less dynamic environments.

Smoke Sense - A crowd sourced study of health impacts of wildland fire smoke exposures &&

EPA Science Inventory

11/21/2017 Alaska Native Tribal Health Consortium (ANTHC) will host a webinar and teleconference for LEO Network Participants (LEO is a network of local observers and topic experts who share knowledge about unusual animal, environment and weather events). With LEO you can connect...

Evolution of a research prototype expert system for endemic populations of mountain pine beetle in lodgepole pine forests

Treesearch

Dale L. Bartos; Kent B. Downing

1989-01-01

A knowledge acquisition program was written to aid in obtaining knowledge from the experts concerning endemic populations of mountain pine beetle in lodgepole pine forest. An application expert system is then automatically generated by the knowledge acquisition program that contains the codified base of expert knowledge. Data can then be entered into the expert system...

Design of CIAO, a research program to support the development of an integrated approach to prevent overweight and obesity in the Netherlands.

PubMed

van Koperen, Marije Tm; van der Kleij, Rianne Mjj; Renders, Carry Cm; Crone, Matty Mr; Hendriks, Anna-Marie Am; Jansen, Maria M; van de Gaar, Vivian Vm; Raat, Hein Jh; Ruiter, Emilie Elm; Molleman, Gerard Grm; Schuit, Jantine Aj; Seidell, Jacob Jc

2014-01-01

The aim of this paper is to describe the research aims, concepts and methods of the research Consortium Integrated Approach of Overweight (CIAO). CIAO is a concerted action of five Academic Collaborative Centres, local collaborations between academic institutions, regional public health services, local authorities and other relevant sectors in the Netherlands. Prior research revealed lacunas in knowledge of and skills related to five elements of the integrated approach of overweight prevention in children (based upon the French EPODE approach), namely political support, parental education, implementation, social marketing and evaluation. CIAO aims to gain theoretical and practical insight of these elements through five sub-studies and to develop, based on these data, a framework for monitoring and evaluation. For this research program, mixed methods are used in all the five sub-studies. First, problem specification through literature research and consultation of stakeholders, experts, health promotion specialists, parents and policy makers will be carried out. Based on this information, models, theoretical frameworks and practical instruments will be developed, tested and evaluated in the communities that implement the integrated approach to prevent overweight in children. Knowledge obtained from these studies and insights from experts and stakeholders will be combined to create an evaluation framework to evaluate the integrated approach at central, local and individual levels that will be applicable to daily practice. This innovative research program stimulates sub-studies to collaborate with local stakeholders and to share and integrate their knowledge, methodology and results. Therefore, the output of this program (both knowledge and practical tools) will be matched and form building blocks of a blueprint for a local evidence- and practice-based integrated approach towards prevention of overweight in children. The output will then support various communities to further optimize the implementation and subsequently the effects of this approach.

Psychological tools for knowledge acquisition

NASA Technical Reports Server (NTRS)

Rueter, Henry H.; Olson, Judith Reitman

1988-01-01

Knowledge acquisition is said to be the biggest bottleneck in the development of expert systems. The problem is getting the knowledge out of the expert's head and into a computer. In cognitive psychology, characterizing metal structures and why experts are good at what they do is an important research area. Is there some way that the tools that psychologists have developed to uncover mental structure can be used to benefit knowledge engineers? We think that the way to find out is to browse through the psychologist's toolbox to see what there is in it that might be of use to knowledge engineers. Expert system developers have relied on two standard methods for extracting knowledge from the expert: (1) the knowledge engineer engages in an intense bout of interviews with the expert or experts, or (2) the knowledge engineer becomes an expert himself, relying on introspection to uncover the basis of his own expertise. Unfortunately, these techniques have the difficulty that often the expert himself isn't consciously aware of the basis of his expertise. If the expert himself isn't conscious of how he solves problems, introspection is useless. Cognitive psychology has faced similar problems for many years and has developed exploratory methods that can be used to discover cognitive structure from simple data.

Mapping High Dimensional Sparse Customer Requirements into Product Configurations

NASA Astrophysics Data System (ADS)

Jiao, Yao; Yang, Yu; Zhang, Hongshan

2017-10-01

Mapping customer requirements into product configurations is a crucial step for product design, while, customers express their needs ambiguously and locally due to the lack of domain knowledge. Thus the data mining process of customer requirements might result in fragmental information with high dimensional sparsity, leading the mapping procedure risk uncertainty and complexity. The Expert Judgment is widely applied against that background since there is no formal requirements for systematic or structural data. However, there are concerns on the repeatability and bias for Expert Judgment. In this study, an integrated method by adjusted Local Linear Embedding (LLE) and Naïve Bayes (NB) classifier is proposed to map high dimensional sparse customer requirements to product configurations. The integrated method adjusts classical LLE to preprocess high dimensional sparse dataset to satisfy the prerequisite of NB for classifying different customer requirements to corresponding product configurations. Compared with Expert Judgment, the adjusted LLE with NB performs much better in a real-world Tablet PC design case both in accuracy and robustness.

Expert consensus on best evaluative practices in community-based rehabilitation.

PubMed

Grandisson, Marie; Thibeault, Rachel; Hébert, Michèle; Cameron, Debra

2016-01-01

The objective of this study was to generate expert consensus on best evaluative practices for community-based rehabilitation (CBR). This consensus includes key features of the evaluation process and methods, and discussion of whether a shared framework should be used to report findings and, if so, which framework should play this role. A Delphi study with two predefined rounds was conducted. Experts in CBR from a wide range of geographical areas and disciplinary backgrounds were recruited to complete the questionnaires. Both quantitative and qualitative analyses were performed to generate the recommendations for best practices in CBR evaluation. A panel of 42 experts reached consensus on 13 recommendations for best evaluative practices in CBR. In regard to the critical qualities of sound CBR evaluation processes, panellists emphasized that these processes should be inclusive, participatory, empowering and respectful of local cultures and languages. The group agreed that evaluators should consider the use of mixed methods and participatory tools, and should combine indicators from a universal list of CBR indicators with locally generated ones. The group also agreed that a common framework should guide CBR evaluations, and that this framework should be a flexible combination between the CBR Matrix and the CBR Principles. An expert panel reached consensus on key features of best evaluative practices in CBR. Knowledge transfer initiatives are now required to develop guidelines, tools and training opportunities to facilitate CBR program evaluations. CBR evaluation processes should strive to be inclusive, participatory, empowering and respectful of local cultures and languages. CBR evaluators should strongly consider using mixed methods, participatory tools, a combination of indicators generated with the local community and with others from a bank of CBR indicators. CBR evaluations should be situated within a shared, but flexible, framework. This shared framework could combine the CBR Matrix and the CBR Principles.

A scale self-adapting segmentation approach and knowledge transfer for automatically updating land use/cover change databases using high spatial resolution images

NASA Astrophysics Data System (ADS)

Wang, Zhihua; Yang, Xiaomei; Lu, Chen; Yang, Fengshuo

2018-07-01

Automatic updating of land use/cover change (LUCC) databases using high spatial resolution images (HSRI) is important for environmental monitoring and policy making, especially for coastal areas that connect the land and coast and that tend to change frequently. Many object-based change detection methods are proposed, especially those combining historical LUCC with HSRI. However, the scale parameter(s) segmenting the serial temporal images, which directly determines the average object size, is hard to choose without experts' intervention. And the samples transferred from historical LUCC also need experts' intervention to avoid insufficient or wrong samples. With respect to the scale parameter(s) choosing, a Scale Self-Adapting Segmentation (SSAS) approach based on the exponential sampling of a scale parameter and location of the local maximum of a weighted local variance was proposed to determine the scale selection problem when segmenting images constrained by LUCC for detecting changes. With respect to the samples transferring, Knowledge Transfer (KT), a classifier trained on historical images with LUCC and applied in the classification of updated images, was also proposed. Comparison experiments were conducted in a coastal area of Zhujiang, China, using SPOT 5 images acquired in 2005 and 2010. The results reveal that (1) SSAS can segment images more effectively without intervention of experts. (2) KT can also reach the maximum accuracy of samples transfer without experts' intervention. Strategy SSAS + KT would be a good choice if the temporal historical image and LUCC match, and the historical image and updated image are obtained from the same resource.

Dengue Disease Risk Mental Models in the City of Dhaka, Bangladesh: Juxtapositions and Gaps Between the Public and Experts.

PubMed

Dhar-Chowdhury, Parnali; Haque, C Emdad; Driedger, S Michelle

2016-05-01

Worldwide, more than 50 million cases of dengue fever are reported every year in at least 124 countries, and it is estimated that approximately 2.5 billion people are at risk for dengue infection. In Bangladesh, the recurrence of dengue has become a growing public health threat. Notably, knowledge and perceptions of dengue disease risk, particularly among the public, are not well understood. Recognizing the importance of assessing risk perception, we adopted a comparative approach to examine a generic methodology to assess diverse sets of beliefs related to dengue disease risk. Our study mapped existing knowledge structures regarding the risk associated with dengue virus, its vector (Aedes mosquitoes), water container use, and human activities in the city of Dhaka, Bangladesh. "Public mental models" were developed from interviews and focus group discussions with diverse community groups; "expert mental models" were formulated based on open-ended discussions with experts in the pertinent fields. A comparative assessment of the public's and experts' knowledge and perception of dengue disease risk has revealed significant gaps in the perception of: (a) disease risk indicators and measurements; (b) disease severity; (c) control of disease spread; and (d) the institutions responsible for intervention. This assessment further identifies misconceptions in public perception regarding: (a) causes of dengue disease; (b) dengue disease symptoms; (c) dengue disease severity; (d) dengue vector ecology; and (e) dengue disease transmission. Based on these results, recommendations are put forward for improving communication of dengue risk and practicing local community engagement and knowledge enhancement in Bangladesh. © 2015 Society for Risk Analysis.

Tidal Wetlands of the Yaquina and Alsea River Estuaries in Oregon: GIS layer development and recommendations for National Wetlands Inventory revisions

EPA Science Inventory

Geographic Information Systems (GIS) layers of current and likely former tidal wetlands in two Oregon estuaries were generated by enhancing the 2010 National Wetlands Inventory (NWI) data with expert local field knowledge, LiDAR-derived elevations, and 2009 aerial orthophotos. Th...

Understanding the Sea Ice Zone: Scientists and Communities Partnering to Archive, Analyze and Disseminate Local Ice Observations

NASA Astrophysics Data System (ADS)

Collins, J. A.; Oldenburg, J.; Liu, M.; Pulsifer, P. L.; Kaufman, M.; Eicken, H.; Parsons, M. A.

2012-12-01

Knowledge of sea ice is critical to the hunting, whaling, and cultural activities of many Indigenous communities in Northern and Western Alaska. Experienced hunters have monitored seasonal changes of the sea ice over many years, giving them a unique expertise in assessing the current state of the sea ice as well as any anomalies in seasonal sea ice conditions. The Seasonal Ice Zone Observing Network (SIZONet), in collaboration with the Exchange for Local Observations and Knowledge of the Arctic (ELOKA), has developed an online application for collecting, storing, and analyzing sea ice observations contributed by local experts from coastal Alaskan communities. Here we present the current iteration of the application, outline future plans and discuss how the development process and resulting system have improved our collective understanding of sea ice processes and changes. The SIZONet application design is based on the needs of the research scientists responsible for entering observation data into the database, the needs of local sea ice experts contributing their observations and knowledge, and the information needs of Alaska coastal communities. Entry forms provide a variety of input methods, including menus, check boxes, and free text input. Input options strive to balance flexibility in capturing concepts and details with the need for analytical consistency. Currently, research staff at the University of Alaska Fairbanks use the application to enter observations received via written or electronic communications from local sea ice experts. Observation data include current weather conditions, snow and ice quantity and quality, and wildlife sighted or taken. Future plans call for direct use of the SIZONet interface by local sea ice experts as well as students, both as contributors to the data collection and as users seeking meaning in the data. This functionality is currently available to a limited number of community members as we extend the application to support specific roles for particular users (or groups of users); this role-based access will be necessary to support a diverse user population while maintaining the integrity of the data and protecting personal information, or the location of sensitive sites, captured in the data records. Additionally, future improvements to the interface will include the ability to upload photos and videos to capture visual records of the environment. The SIZONet application was developed to provide a robust interface for working with observational data. The contributed nature of the data, however, presents a unique set of collaborative benefits and challenges as we work towards the final implementation of the application. The successful partnership supporting the observation network is a direct function of the long-term relationships established between university-based researchers and community members.

Knowledge-based control for robot self-localization

NASA Technical Reports Server (NTRS)

Bennett, Bonnie Kathleen Holte

1993-01-01

Autonomous robot systems are being proposed for a variety of missions including the Mars rover/sample return mission. Prior to any other mission objectives being met, an autonomous robot must be able to determine its own location. This will be especially challenging because location sensors like GPS, which are available on Earth, will not be useful, nor will INS sensors because their drift is too large. Another approach to self-localization is required. In this paper, we describe a novel approach to localization by applying a problem solving methodology. The term 'problem solving' implies a computational technique based on logical representational and control steps. In this research, these steps are derived from observing experts solving localization problems. The objective is not specifically to simulate human expertise but rather to apply its techniques where appropriate for computational systems. In doing this, we describe a model for solving the problem and a system built on that model, called localization control and logic expert (LOCALE), which is a demonstration of concept for the approach and the model. The results of this work represent the first successful solution to high-level control aspects of the localization problem.

Development of a knowledge acquisition tool for an expert system flight status monitor

NASA Technical Reports Server (NTRS)

Disbrow, J. D.; Duke, E. L.; Regenie, V. A.

1986-01-01

Two of the main issues in artificial intelligence today are knowledge acquisition dion and knowledge representation. The Dryden Flight Research Facility of NASA's Ames Research Center is presently involved in the design and implementation of an expert system flight status monitor that will provide expertise and knowledge to aid the flight systems engineer in monitoring today's advanced high-performance aircraft. The flight status monitor can be divided into two sections: the expert system itself and the knowledge acquisition tool. The knowledge acquisition tool, the means it uses to extract knowledge from the domain expert, and how that knowledge is represented for computer use is discussed. An actual aircraft system has been codified by this tool with great success. Future real-time use of the expert system has been facilitated by using the knowledge acquisition tool to easily generate a logically consistent and complete knowledge base.

Development of a knowledge acquisition tool for an expert system flight status monitor

NASA Technical Reports Server (NTRS)

Disbrow, J. D.; Duke, E. L.; Regenie, V. A.

1986-01-01

Two of the main issues in artificial intelligence today are knowledge acquisition and knowledge representation. The Dryden Flight Research Facility of NASA's Ames Research Center is presently involved in the design and implementation of an expert system flight status monitor that will provide expertise and knowledge to aid the flight systems engineer in monitoring today's advanced high-performance aircraft. The flight status monitor can be divided into two sections: the expert system itself and the knowledge acquisition tool. This paper discusses the knowledge acquisition tool, the means it uses to extract knowledge from the domain expert, and how that knowledge is represented for computer use. An actual aircraft system has been codified by this tool with great success. Future real-time use of the expert system has been facilitated by using the knowledge acquisition tool to easily generate a logically consistent and complete knowledge base.

A Framework for Bridging Scientists, Knowledge Brokers and Local Decision Makers in State-level Climate Assessments

NASA Astrophysics Data System (ADS)

Galford, G. L.; Nash, J. L.

2016-12-01

Large-scale analyses like the National Climate Assessment (NCA) contain a wealth of information critical to national and regional responses to climate change but tend to be insufficiently detailed for action at state or local levels. Many states now develop assessments (SCAs) to provide relevant, actionable information to state and local authorities. These assessments generate new or additional primary information, build networks and inform stakeholders. Based on our experience in the Vermont Climate Assessment (VCA), we present a SCA framework to engage local decision makers, using a fluid network of scientific experts and knowledge brokers to conduct subject area prioritization, data analysis, and writing. Knowledge brokers bridged the scientific and stakeholder communities, providing a two-way flow of information by capitalizing on their existing networks. Rich citizen records of climate and climate change impacts associated a human voice, a memorable story, or personal observation with a climate record, improving climate information salience. This engagement process that created salient climate information perceived as credible and legitimate by local and state decision makers. We present this framework as an effective structure for SCAs to foster interaction among scientists, knowledge brokers and stakeholders. We include a qualitative impact evaluation and lessons learned for future SCAs.

Development of an expert system prototype for determining software functional requirements for command management activities at NASA Goddard

NASA Technical Reports Server (NTRS)

Liebowitz, J.

1986-01-01

The development of an expert system prototype for software functional requirement determination for NASA Goddard's Command Management System, as part of its process of transforming general requests into specific near-earth satellite commands, is described. The present knowledge base was formulated through interactions with domain experts, and was then linked to the existing Knowledge Engineering Systems (KES) expert system application generator. Steps in the knowledge-base development include problem-oriented attribute hierarchy development, knowledge management approach determination, and knowledge base encoding. The KES Parser and Inspector, in addition to backcasting and analogical mapping, were used to validate the expert system-derived requirements for one of the major functions of a spacecraft, the solar Maximum Mission. Knowledge refinement, evaluation, and implementation procedures of the expert system were then accomplished.

An e-learning application on electrochemotherapy

PubMed Central

Corovic, Selma; Bester, Janez; Miklavcic, Damijan

2009-01-01

Background Electrochemotherapy is an effective approach in local tumour treatment employing locally applied high-voltage electric pulses in combination with chemotherapeutic drugs. In planning and performing electrochemotherapy a multidisciplinary expertise is required and collaboration, knowledge and experience exchange among the experts from different scientific fields such as medicine, biology and biomedical engineering is needed. The objective of this study was to develop an e-learning application in order to provide the educational content on electrochemotherapy and its underlying principles and to support collaboration, knowledge and experience exchange among the experts involved in the research and clinics. Methods The educational content on electrochemotherapy and cell and tissue electroporation was based on previously published studies from molecular dynamics, lipid bilayers, single cell level and simplified tissue models to complex biological tissues and research and clinical results of electrochemotherapy treatment. We used computer graphics such as model-based visualization (i.e. 3D numerical modelling using finite element method) and 3D computer animations and graphical illustrations to facilitate the representation of complex biological and physical aspects in electrochemotherapy. The e-learning application is integrated into an interactive e-learning environment developed at our institution, enabling collaboration and knowledge exchange among the users. We evaluated the designed e-learning application at the International Scientific workshop and postgraduate course (Electroporation Based Technologies and Treatments). The evaluation was carried out by testing the pedagogical efficiency of the presented educational content and by performing the usability study of the application. Results The e-learning content presents three different levels of knowledge on cell and tissue electroporation. In the first part of the e-learning application we explain basic principles of electroporation process. The second part provides educational content about importance of modelling and visualization of local electric field in electroporation-based treatments. In the third part we developed an interactive module for visualization of local electric field distribution in 3D tissue models of cutaneous tumors for different parameters such as voltage applied, distance between electrodes, electrode dimension and shape, tissue geometry and electric conductivity. The pedagogical efficiency assessment showed that the participants improved their level of knowledge. The results of usability evaluation revealed that participants found the application simple to learn, use and navigate. The participants also found the information provided by the application easy to understand. Conclusion The e-learning application we present in this article provides educational material on electrochemotherapy and its underlying principles such as cell and tissue electroporation. The e-learning application is developed to provide an interactive educational content in order to simulate the "hands-on" learning approach about the parameters being important for successful therapy. The e-learning application together with the interactive e-learning environment is available to the users to provide collaborative and flexible learning in order to facilitate knowledge exchange among the experts from different scientific fields that are involved in electrochemotherapy. The modular structure of the application allows for upgrade with new educational content collected from the clinics and research, and can be easily adapted to serve as a collaborative e-learning tool also in other electroporation-based treatments such as gene electrotransfer, gene vaccination, irreversible tissue ablation and transdermal gene and drug delivery. The presented e-learning application provides an easy and rapid approach for information, knowledge and experience exchange among the experts from different scientific fields, which can facilitate development and optimisation of electroporation-based treatments. PMID:19843322

An e-learning application on electrochemotherapy.

PubMed

Corovic, Selma; Bester, Janez; Miklavcic, Damijan

2009-10-20

Electrochemotherapy is an effective approach in local tumour treatment employing locally applied high-voltage electric pulses in combination with chemotherapeutic drugs. In planning and performing electrochemotherapy a multidisciplinary expertise is required and collaboration, knowledge and experience exchange among the experts from different scientific fields such as medicine, biology and biomedical engineering is needed. The objective of this study was to develop an e-learning application in order to provide the educational content on electrochemotherapy and its underlying principles and to support collaboration, knowledge and experience exchange among the experts involved in the research and clinics. The educational content on electrochemotherapy and cell and tissue electroporation was based on previously published studies from molecular dynamics, lipid bilayers, single cell level and simplified tissue models to complex biological tissues and research and clinical results of electrochemotherapy treatment. We used computer graphics such as model-based visualization (i.e. 3D numerical modelling using finite element method) and 3D computer animations and graphical illustrations to facilitate the representation of complex biological and physical aspects in electrochemotherapy. The e-learning application is integrated into an interactive e-learning environment developed at our institution, enabling collaboration and knowledge exchange among the users. We evaluated the designed e-learning application at the International Scientific workshop and postgraduate course (Electroporation Based Technologies and Treatments). The evaluation was carried out by testing the pedagogical efficiency of the presented educational content and by performing the usability study of the application. The e-learning content presents three different levels of knowledge on cell and tissue electroporation. In the first part of the e-learning application we explain basic principles of electroporation process. The second part provides educational content about importance of modelling and visualization of local electric field in electroporation-based treatments. In the third part we developed an interactive module for visualization of local electric field distribution in 3D tissue models of cutaneous tumors for different parameters such as voltage applied, distance between electrodes, electrode dimension and shape, tissue geometry and electric conductivity. The pedagogical efficiency assessment showed that the participants improved their level of knowledge. The results of usability evaluation revealed that participants found the application simple to learn, use and navigate. The participants also found the information provided by the application easy to understand. The e-learning application we present in this article provides educational material on electrochemotherapy and its underlying principles such as cell and tissue electroporation. The e-learning application is developed to provide an interactive educational content in order to simulate the "hands-on" learning approach about the parameters being important for successful therapy. The e-learning application together with the interactive e-learning environment is available to the users to provide collaborative and flexible learning in order to facilitate knowledge exchange among the experts from different scientific fields that are involved in electrochemotherapy. The modular structure of the application allows for upgrade with new educational content collected from the clinics and research, and can be easily adapted to serve as a collaborative e-learning tool also in other electroporation-based treatments such as gene electrotransfer, gene vaccination, irreversible tissue ablation and transdermal gene and drug delivery. The presented e-learning application provides an easy and rapid approach for information, knowledge and experience exchange among the experts from different scientific fields, which can facilitate development and optimisation of electroporation-based treatments.

Information About a Layperson's Knowledge Supports Experts in Giving Effective and Efficient Online Advice to Laypersons

ERIC Educational Resources Information Center

Nuckles, Matthias; Wittwer, Jorg; Renkl, Alexander

2005-01-01

To give effective and efficient advice to laypersons, experts should adapt their explanations to the layperson's knowledge. However, experts often fail to consider the limited domain knowledge of laypersons. To support adaptation in asynchronous help desk communication, researchers provided computer experts with information about a layperson's…

An expert system for the design of heating, ventilating, and air-conditioning systems

NASA Astrophysics Data System (ADS)

Camejo, Pedro Jose

1989-12-01

Expert systems are computer programs that seek to mimic human reason. An expert system shelf, a software program commonly used for developing expert systems in a relatively short time, was used to develop a prototypical expert system for the design of heating, ventilating, and air-conditioning (HVAC) systems in buildings. Because HVAC design involves several related knowledge domains, developing an expert system for HVAC design requires the integration of several smaller expert systems known as knowledge bases. A menu program and several auxiliary programs for gathering data, completing calculations, printing project reports, and passing data between the knowledge bases are needed and have been developed to join the separate knowledge bases into one simple-to-use program unit.

A demonstration of expert systems applications in transportation engineering : volume I, transportation engineers and expert systems.

DOT National Transportation Integrated Search

1987-01-01

Expert systems, a branch of artificial-intelligence studies, is introduced with a view to its relevance in transportation engineering. Knowledge engineering, the process of building expert systems or transferring knowledge from human experts to compu...

A knowledge creation info-structure to acquire and crystallize the tacit knowledge of health-care experts.

PubMed

Abidi, Syed Sibte Raza; Cheah, Yu-N; Curran, Janet

2005-06-01

Tacit knowledge of health-care experts is an important source of experiential know-how, yet due to various operational and technical reasons, such health-care knowledge is not entirely harnessed and put into professional practice. Emerging knowledge-management (KM) solutions suggest strategies to acquire the seemingly intractable and nonarticulated tacit knowledge of health-care experts. This paper presents a KM methodology, together with its computational implementation, to 1) acquire the tacit knowledge possessed by health-care experts; 2) represent the acquired tacit health-care knowledge in a computational formalism--i.e., clinical scenarios--that allows the reuse of stored knowledge to acquire tacit knowledge; and 3) crystallize the acquired tacit knowledge so that it is validated for health-care decision-support and medical education systems.

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.

Fire Effects, Education, and Expert Systems

Treesearch

Robert E. Martin

1987-01-01

Predicting the effects of fires in the year 2000 and beyond will be enhanced by the use of expert systems. Although our predictions may have broad confidence limits, expert systems should help us to improve the predictions and to focus on the areas where improved knowledge is most needed. The knowledge of experts can be incorporated into previously existing knowledge...

The use of cognitive task analysis to reveal the instructional limitations of experts in the teaching of procedural skills.

PubMed

Sullivan, Maura E; Yates, Kenneth A; Inaba, Kenji; Lam, Lydia; Clark, Richard E

2014-05-01

Because of the automated nature of knowledge, experts tend to omit information when describing a task. A potential solution is cognitive task analysis (CTA). The authors investigated the percentage of knowledge experts omitted when teaching a cricothyrotomy to determine the percentage of additional knowledge gained during a CTA interview. Three experts were videotaped teaching a cricothyrotomy in 2010 at the University of Southern California. After transcription, they participated in CTA interviews for the same procedure. Three additional surgeons were recruited to perform a CTA for the procedure, and a "gold standard" task list was created. Transcriptions from the teaching sessions were compared with the task list to identify omitted steps (both "what" and "how" to do). Transcripts from the CTA interviews were compared against the task list to determine the percentage of knowledge articulated by each expert during the initial "free recall" (unprompted) phase of the CTA interview versus the amount of knowledge gained by using CTA elicitation techniques (prompted). Experts omitted an average of 71% (10/14) of clinical knowledge steps, 51% (14/27) of action steps, and 73% (3.6/5) of decision steps. For action steps, experts described "how to do it" only 13% (3.6/27) of the time. The average number of steps that were described increased from 44% (20/46) when unprompted to 66% (31/46) when prompted. This study supports previous research that experts unintentionally omit knowledge when describing a procedure. CTA is a useful method to extract automated knowledge and augment expert knowledge recall during teaching.

Understanding the role of knowledge in the practice of expert nephrology nurses in Australia.

PubMed

Bonner, Ann

2007-09-01

This paper, which is abstracted from a larger study into the acquisition and exercise of nephrology nursing expertise, aims to explore the role of knowledge in expert practice. Using grounded theory methodology, the study involved 17 registered nurses who were practicing in a metropolitan renal unit in New South Wales, Australia. Concurrent data collection and analysis was undertaken, incorporating participants' observations and interviews. Having extensive nephrology nursing knowledge was a striking characteristic of a nursing expert. Expert nurses clearly relied on and utilized extensive nephrology nursing knowledge to practice. Of importance for nursing, the results of this study indicate that domain-specific knowledge is a crucial feature of expert practice.

Expert system for the design of heating, ventilating, and air-conditioning systems. Master's thesis

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

Camejo, P.J.

1989-12-01

Expert systems are computer programs that seek to mimic human reason. An expert system shelf, a software program commonly used for developing expert systems in a relatively short time, was used to develop a prototypical expert system for the design of heating, ventilating, and air-conditioning (HVAC) systems in buildings. Because HVAC design involves several related knowledge domains, developing an expert system for HVAC design requires the integration of several smaller expert systems known as knowledge bases. A menu program and several auxiliary programs for gathering data, completing calculations, printing project reports, and passing data between the knowledge bases are neededmore » and have been developed to join the separate knowledge bases into one simple-to-use program unit.« less

Expert knowledge maps for knowledge management: a case study in Traditional Chinese Medicine research.

PubMed

Cui, Meng; Yang, Shuo; Yu, Tong; Yang, Ce; Gao, Yonghong; Zhu, Haiyan

2013-10-01

To design a model to capture information on the state and trends of knowledge creation, at both an individual and an organizational level, in order to enhance knowledge management. We designed a graph-theoretic knowledge model, the expert knowledge map (EKM), based on literature-based annotation. A case study in the domain of Traditional Chinese Medicine research was used to illustrate the usefulness of the model. The EKM successfully captured various aspects of knowledge and enhanced knowledge management within the case-study organization through the provision of knowledge graphs, expert graphs, and expert-knowledge biography. Our model could help to reveal the hot topics, trends, and products of the research done by an organization. It can potentially be used to facilitate knowledge learning, sharing and decision-making among researchers, academicians, students, and administrators of organizations.

Core curriculum for medical physicists in radiology. Recommendations from an EFOMP/ESR working group.

PubMed

Geleijns, Jacob; Breatnach, Eamann; Cantera, Alfonso Calzado; Damilakis, John; Dendy, Philip; Evans, Anthony; Faulkner, Keith; Padovani, Renato; Van Der Putten, Wil; Schad, Lothar; Wirestam, Ronnie; Eudaldo, Teresa

2012-06-01

Some years ago it was decided that a European curriculum should be developed for medical physicists professionally engaged in the support of clinical diagnostic imaging departments. With this in mind, EFOMP (European Federation of Organisations for Medical Physics) in association with ESR (European Society of Radiology) nominated an expert working group. This curriculum is now to hand. The curriculum is intended to promote best patient care in radiology departments through the harmonization of education and training of medical physicists to a high standard in diagnostic radiology. It is recommended that a medical physicist working in a radiology department should have an advanced level of professional expertise in X-ray imaging, and additionally, depending on local availability, should acquire knowledge and competencies in overseeing ultrasound imaging, nuclear medicine, and MRI technology. By demonstrating training to a standardized curriculum, medical physicists throughout Europe will enhance their mobility, while maintaining local high standards of medical physics expertise. This document also provides the basis for improved implementation of articles in the European medical exposure directives related to the medical physics expert. The curriculum is divided into three main sections: The first deals with general competencies in the principles of medical physics. The second section describes specific knowledge and skills required for a medical physicist (medical physics expert) to operate clinically in a department of diagnostic radiology. The final section outlines research skills that are also considered to be necessary and appropriate competencies in a career as medical physicist.

Comprehensive Case Analysis on Participatory Approaches, from Nexus Perspectives

NASA Astrophysics Data System (ADS)

Masuhara, N.; Baba, K.

2014-12-01

According to Messages from the Bonn2011 Conference, involving local communities fully and effectively in the planning and implementation processes related to water, energy and food nexus for local ownership and commitment should be strongly needed. The participatory approaches such as deliberative polling, "joint fact-finding" and so on have been applied so far to resolve various environmental disputes, however the drivers and barriers in such processes have not been necessarily enough analyzed in a comprehensive manner, especially in Japan. Our research aims to explore solutions for conflicts in the context of water-energy-food nexus in local communities. To achieve it, we clarify drivers and barriers of each approaches applied so far in water, energy and food policy, focusing on how to deal with scientific facts. We generate hypotheses primarily that multi-issue solutions through policy integration will be more effective for conflicts in the context of water-energy-food nexus than single issue solutions for each policy. One of the key factors to formulate effective solutions is to integrate "scientific fact (expert knowledge)" and "local knowledge". Given this primary hypothesis, more specifically, we assume that it is effective for building consensus to provide opportunities to resolve the disagreement of "framing" that stakeholders can offer experts the points for providing scientific facts and that experts can get common understanding of scientific facts in the early stage of the process. To verify the hypotheses, we develop a database of the cases which such participatory approaches have been applied so far to resolve various environmental disputes based on literature survey of journal articles and public documents of Japanese cases. At present, our database is constructing. But it's estimated that conditions of framing and providing scientific information are important driving factors for problem solving and consensus building. And it's important to refine the driving factors, evaluating if components of database are enough to present each process or not.

Knowledge-based image data management - An expert front-end for the BROWSE facility

NASA Technical Reports Server (NTRS)

Stoms, David M.; Star, Jeffrey L.; Estes, John E.

1988-01-01

An intelligent user interface being added to the NASA-sponsored BROWSE testbed facility is described. BROWSE is a prototype system designed to explore issues involved in locating image data in distributed archives and displaying low-resolution versions of that imagery at a local terminal. For prototyping, the initial application is the remote sensing of forest and range land.

Using expert informed GIS to locate important marine social-ecological hotspots.

PubMed

Mahboubi, Pouyan; Parkes, Margot; Stephen, Craig; Chan, Hing Man

2015-09-01

The marine environment provides significant benefits to many local communities. Pressure to develop coastal waterways worldwide creates an urgent need for tools to locate marine spaces that have important social or ecological values, and to quantify their relative importance. The primary objective of this study was to develop, apply and critically assess a tool to identify important social-ecological hotspots in the marine environment. The study was conducted in a typical coastal community in northern British Columbia, Canada. This expert-informed GIS, or xGIS, tool used a survey instrument to draw on the knowledge of local experts from a range of backgrounds with respect to a series of 12 social-ecological value attributes, such as biodiversity, cultural and economic values. We identified approximately 1500 polygons on marine maps and assigned relative values to them using a token distribution exercise. A series of spatial statistical analyses were performed to locate and quantify the relative social-ecological importance of marine spaces and the results were ultimately summarized in a single hotspot map of the entire study area. This study demonstrates the utility of xGIS as a useful tool for stakeholders and environmental managers engaged in the planning and management of marine resources at the local and regional levels. Copyright © 2015 Elsevier Ltd. All rights reserved.

Students' Refinement of Knowledge during the Development of Knowledge Bases for Expert Systems.

ERIC Educational Resources Information Center

Lippert, Renate; Finley, Fred

The refinement of the cognitive knowledge base was studied through exploration of the transition from novice to expert and the use of an instructional strategy called novice knowledge engineering. Six college freshmen, who were enrolled in an honors physics course, used an expert system to create questions, decisions, rules, and explanations…

Expert systems in civil engineering

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

Kostem, C.N.; Maher, M.L.

1986-01-01

This book presents the papers given at a symposium on expert systems in civil engineering. Topics considered at the symposium included problem solving using expert system techniques, construction schedule analysis, decision making and risk analysis, seismic risk analysis systems, an expert system for inactive hazardous waste site characterization, an expert system for site selection, knowledge engineering, and knowledge-based expert systems in seismic analysis.

Techniques for capturing expert knowledge - An expert systems/hypertext approach

NASA Technical Reports Server (NTRS)

Lafferty, Larry; Taylor, Greg; Schumann, Robin; Evans, Randy; Koller, Albert M., Jr.

1990-01-01

The knowledge-acquisition strategy developed for the Explosive Hazards Classification (EHC) Expert System is described in which expert systems and hypertext are combined, and broad applications are proposed. The EHC expert system is based on rapid prototyping in which primary knowledge acquisition from experts is not emphasized; the explosive hazards technical bulletin, technical guidance, and minimal interviewing are used to develop the knowledge-based system. Hypertext is used to capture the technical information with respect to four issues including procedural, materials, test, and classification issues. The hypertext display allows the integration of multiple knowlege representations such as clarifications or opinions, and thereby allows the performance of a broad range of tasks on a single machine. Among other recommendations, it is suggested that the integration of hypertext and expert systems makes the resulting synergistic system highly efficient.

Novice and expert teachers' conceptions of learners' prior knowledge

NASA Astrophysics Data System (ADS)

Meyer, Helen

2004-11-01

This study presents comparative case studies of preservice and first-year teachers' and expert teachers' conceptions of the concept of prior knowledge. Kelly's (The Psychology of Personal Construct, New York: W.W. Norton, 1955) theory of personal constructs as discussed by Akerson, Flick, and Lederman (Journal of Research in Science Teaching, 2000, 37, 363-385) in relationship to prior knowledge underpins the study. Six teachers were selected to participate in the case studies based upon their level experience teaching science and their willingness to take part. The comparative case studies of the novice and expert teachers provide insights into (a) how novice and expert teachers understand the concept of prior knowledge and (b) how they use this knowledge to make instructional decisions. Data collection consisted of interviews, classroom observations, and document analysis. Findings suggest that novice teachers hold insufficient conceptions of prior knowledge and its role in instruction to effectively implement constructivist teaching practices. While expert teachers hold a complex conception of prior knowledge and make use of their students' prior knowledge in significant ways during instruction. A second finding was an apparent mismatch between the novice teachers' beliefs about their urban students' life experiences and prior knowledge and the wealth of knowledge the expert teachers found to draw upon.

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

PubMed

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

2013-06-01

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

Map Reading beyond Information Given: The Expert Orienteers' Internal Knowledge about Terrain.

ERIC Educational Resources Information Center

Murakoshi, Shin

1990-01-01

Compares novice and expert orienteers' map interpretation skills. Subjects asked to judge terrain from maps, including conditions inferable without corresponding map symbols. Experts' interpretation of identical symbols implies use of experiential knowledge. Internal knowledge characteristics discussed in terms of episodic-semantic memory…

Expert and Knowledge Based Systems.

ERIC Educational Resources Information Center

Demaid, Adrian; Edwards, Lyndon

1987-01-01

Discusses the nature and current state of knowledge-based systems and expert systems. Describes an expert system from the viewpoints of a computer programmer and an applications expert. Addresses concerns related to materials selection and forecasts future developments in the teaching of materials engineering. (ML)

Framing of scientific knowledge as a new category of health care research.

PubMed

Salvador-Carulla, Luis; Fernandez, Ana; Madden, Rosamond; Lukersmith, Sue; Colagiuri, Ruth; Torkfar, Ghazal; Sturmberg, Joachim

2014-12-01

The new area of health system research requires a revision of the taxonomy of scientific knowledge that may facilitate a better understanding and representation of complex health phenomena in research discovery, corroboration and implementation. A position paper by an expert group following and iterative approach. 'Scientific evidence' should be differentiated from 'elicited knowledge' of experts and users, and this latter typology should be described beyond the traditional qualitative framework. Within this context 'framing of scientific knowledge' (FSK) is defined as a group of studies of prior expert knowledge specifically aimed at generating formal scientific frames. To be distinguished from other unstructured frames, FSK must be explicit, standardized, based on the available evidence, agreed by a group of experts and subdued to the principles of commensurability, transparency for corroboration and transferability that characterize scientific research. A preliminary typology of scientific framing studies is presented. This typology includes, among others, health declarations, position papers, expert-based clinical guides, conceptual maps, classifications, expert-driven health atlases and expert-driven studies of costs and burden of illness. This grouping of expert-based studies constitutes a different kind of scientific knowledge and should be clearly differentiated from 'evidence' gathered from experimental and observational studies in health system research. © 2014 John Wiley & Sons, Ltd.

Development of a Spacecraft Materials Selector Expert System

NASA Technical Reports Server (NTRS)

Pippin, G.; Kauffman, W. (Technical Monitor)

2002-01-01

This report contains a description of the knowledge base tool and examples of its use. A downloadable version of the Spacecraft Materials Selector (SMS) knowledge base is available through the NASA Space Environments and Effects Program. The "Spacecraft Materials Selector" knowledge base is part of an electronic expert system. The expert system consists of an inference engine that contains the "decision-making" code and the knowledge base that contains the selected body of information. The inference engine is a software package previously developed at Boeing, called the Boeing Expert System Tool (BEST) kit.

Global Dynamic Exposure and the OpenBuildingMap

NASA Astrophysics Data System (ADS)

Schorlemmer, D.; Beutin, T.; Hirata, N.; Hao, K. X.; Wyss, M.; Cotton, F.; Prehn, K.

2015-12-01

Detailed understanding of local risk factors regarding natural catastrophes requires in-depth characterization of the local exposure. Current exposure capture techniques have to find the balance between resolution and coverage. We aim at bridging this gap by employing a crowd-sourced approach to exposure capturing focusing on risk related to earthquake hazard. OpenStreetMap (OSM), the rich and constantly growing geographical database, is an ideal foundation for us. More than 2.5 billion geographical nodes, more than 150 million building footprints (growing by ~100'000 per day), and a plethora of information about school, hospital, and other critical facility locations allow us to exploit this dataset for risk-related computations. We will harvest this dataset by collecting exposure and vulnerability indicators from explicitly provided data (e.g. hospital locations), implicitly provided data (e.g. building shapes and positions), and semantically derived data, i.e. interpretation applying expert knowledge. With this approach, we can increase the resolution of existing exposure models from fragility classes distribution via block-by-block specifications to building-by-building vulnerability. To increase coverage, we will provide a framework for collecting building data by any person or community. We will implement a double crowd-sourced approach to bring together the interest and enthusiasm of communities with the knowledge of earthquake and engineering experts. The first crowd-sourced approach aims at collecting building properties in a community by local people and activists. This will be supported by tailored building capture tools for mobile devices for simple and fast building property capturing. The second crowd-sourced approach involves local experts in estimating building vulnerability that will provide building classification rules that translate building properties into vulnerability and exposure indicators as defined in the Building Taxonomy 2.0 developed by the Global Earthquake Model (GEM). These indicators will then be combined with a hazard model using the GEM OpenQuake engine to compute a risk model. The free/open framework we will provide can be used on commodity hardware for local to regional exposure capturing and for communities to understand their earthquake risk.

Intelligent systems for human resources.

PubMed

Kline, K B

1988-11-01

An intelligent system contains knowledge about some domain; it has sophisticated decision-making processes and the ability to explain its actions. The most important aspect of an intelligent system is its ability to effectively interact with humans to teach or assist complex information processing. Two intelligent systems are Intelligent Tutoring Systems (ITs) and Expert Systems. The ITSs provide instruction to a student similar to a human tutor. The ITSs capture individual performance and tutor deficiencies. These systems consist of an expert module, which contains the knowledge or material to be taught; the student module, which contains a representation of the knowledge the student knows and does not know about the domain; and the instructional or teaching module, which selects specific knowledge to teach, the instructional strategy, and provides assistance to the student to tutor deficiencies. Expert systems contain an expert's knowledge about some domain and perform specialized tasks or aid a novice in the performance of certain tasks. The most important part of an expert system is the knowledge base. This knowledge base contains all the specialized and technical knowledge an expert possesses. For an expert system to interact effectively with humans, it must have the ability to explain its actions. Use of intelligent systems can have a profound effect on human resources. The ITSs can provide better training by tutoring on an individual basis, and the expert systems can make better use of human resources through job aiding and performing complex tasks. With increasing training requirements and "doing more with less," intelligent systems can have a positive effect on human resources.

Using Pathfinder networks to discover alignment between expert and consumer conceptual knowledge from online vaccine content.

PubMed

Amith, Muhammad; Cunningham, Rachel; Savas, Lara S; Boom, Julie; Schvaneveldt, Roger; Tao, Cui; Cohen, Trevor

2017-10-01

This study demonstrates the use of distributed vector representations and Pathfinder Network Scaling (PFNETS) to represent online vaccine content created by health experts and by laypeople. By analyzing a target audience's conceptualization of a topic, domain experts can develop targeted interventions to improve the basic health knowledge of consumers. The underlying assumption is that the content created by different groups reflects the mental organization of their knowledge. Applying automated text analysis to this content may elucidate differences between the knowledge structures of laypeople (heath consumers) and professionals (health experts). This paper utilizes vaccine information generated by laypeople and health experts to investigate the utility of this approach. We used an established technique from cognitive psychology, Pathfinder Network Scaling to infer the structure of the associational networks between concepts learned from online content using methods of distributional semantics. In doing so, we extend the original application of PFNETS to infer knowledge structures from individual participants, to infer the prevailing knowledge structures within communities of content authors. The resulting graphs reveal opportunities for public health and vaccination education experts to improve communication and intervention efforts directed towards health consumers. Our efforts demonstrate the feasibility of using an automated procedure to examine the manifestation of conceptual models within large bodies of free text, revealing evidence of conflicting understanding of vaccine concepts among health consumers as compared with health experts. Additionally, this study provides insight into the differences between consumer and expert abstraction of domain knowledge, revealing vaccine-related knowledge gaps that suggest opportunities to improve provider-patient communication. Copyright © 2017 Elsevier Inc. All rights reserved.

Shared Knowledge among Graphic Designers, Instructional Designers and Subject Matter Experts in Designing Multimedia-Based Instructional Media

ERIC Educational Resources Information Center

Razak, Rafiza Abdul

2013-01-01

The research identified and explored the shared knowledge among the instructional multimedia design and development experts comprising of subject matter expert, graphic designer and instructional designer. The knowledge shared by the team was categorized into three groups of multimedia design principles encompasses of basic principles, authoring…

Strategic conservation planning for the Eastern North Carolina/Southeastern Virginia Strategic Habitat Conservation Team

USGS Publications Warehouse

Alexander-Vaughn, Louise B.; Collazo, Jaime A.; Drew, C. Ashton

2014-01-01

The Eastern North Carolina/Southeastern Virginia Strategic Habitat Conservation Team (ENCSEVA) is a partnership among local federal agencies and programs with a mission to apply Strategic Habitat Conservation to accomplish priority landscape-level conservation within its geographic region. ENCSEVA seeks to further landscape-scale conservation through collaboration with local partners. To accomplish this mission, ENCSEVA is developing a comprehensive Strategic Habitat Conservation Plan (Plan) to provide guidance for its members, partners, and collaborators by establishing mutual conservation goals, objectives, strategies, and metrics to gauge the success of conservation efforts. Identifying common goals allows the ENCSEVA team to develop strategies that leverage joint resources and are more likely to achieve desired impacts across the landscape. The Plan will also provide an approach for ENCSEVA to meet applied research needs (identify knowledge gaps), foster adaptive management principles, identify conservation priorities, prioritize threats (including potential impacts of climate change), and identify the required capacity to implement strategies to create more resilient landscapes. ENCSEVA seeks to support the overarching goals of the South Atlantic Landscape Conservation Cooperative (SALCC) and to provide scientific and technical support for conservation at landscape scales as well as inform the management of natural resources in response to shifts in climate, habitat fragmentation and loss, and other landscape-level challenges (South Atlantic LCC 2012). The ENCSEVA ecoregion encompasses the northern third of the SALCC geography and offers a unique opportunity to apply landscape conservation at multiple scales through the guidance of local conservation and natural resource management efforts and by reporting metrics that reflect the effectiveness of those efforts (Figure 1). The Environmental Decision Analysis Team, housed within the North Carolina Cooperative Fish and Wildlife Research Unit at North Carolina State University, is assisting the ENCSEVA team in developing a scientifically sound basis for the Plan though the elicitation of expert knowledge and the organization of that knowledge using the Open Standards for the Practice of Conservation. The Open Standards for the Practice of Conservation is a framework that is well suited to incorporating decision-making tools such as Structured Decision Making and provides a multi-step process to conceptually organize conservation projects in a manner that enhances the rigor and transparency of expert and knowledge-based plans. It helps define explicit pathways from 2 planned conservation activities and ultimate impact, as well as indicators to measure success (Stem et al. 2005). Specifically, the framework identifies conservation targets, key ecological attributes, threats, and associated indicators to monitor responses given the implementation of a conservation action (Conservation Measures Partnership 2007). This report serves to provide a scientific foundation for the Plan by summarizing the expert opinion of wildlife biologists, ecologists, hydrologists, researchers, natural resource managers, and conservation practitioners regarding five environments (wetlands, riverine systems, estuaries, uplands, and barrier islands) within the ENCSEVA geography. Specifically, this report describes (1) the approach to elicit expert knowledge meant to support the strategic plan, (2) how this knowledge can inform collaborative conservation planning, and (3) a summary of opportunities available for the ENCSEVA team to address threats and impacts associated with climate change within the ecoregion.

PVDaCS - A prototype knowledge-based expert system for certification of spacecraft data

NASA Technical Reports Server (NTRS)

Wharton, Cathleen; Shiroma, Patricia J.; Simmons, Karen E.

1989-01-01

On-line data management techniques to certify spacecraft information are mandated by increasing telemetry rates. Knowledge-based expert systems offer the ability to certify data electronically without the need for time-consuming human interaction. Issues of automatic certification are explored by designing a knowledge-based expert system to certify data from a scientific instrument, the Orbiter Ultraviolet Spectrometer, on an operating NASA planetary spacecraft, Pioneer Venus. The resulting rule-based system, called PVDaCS (Pioneer Venus Data Certification System), is a functional prototype demonstrating the concepts of a larger system design. A key element of the system design is the representation of an expert's knowledge through the usage of well ordered sequences. PVDaCS produces a certification value derived from expert knowledge and an analysis of the instrument's operation. Results of system performance are presented.

Photolithography diagnostic expert systems: a systematic approach to problem solving in a wafer fabrication facility

NASA Astrophysics Data System (ADS)

Weatherwax Scott, Caroline; Tsareff, Christopher R.

1990-06-01

One of the main goals of process engineering in the semiconductor industry is to improve wafer fabrication productivity and throughput. Engineers must work continuously toward this goal in addition to performing sustaining and development tasks. To accomplish these objectives, managers must make efficient use of engineering resources. One of the tools being used to improve efficiency is the diagnostic expert system. Expert systems are knowledge based computer programs designed to lead the user through the analysis and solution of a problem. Several photolithography diagnostic expert systems have been implemented at the Hughes Technology Center to provide a systematic approach to process problem solving. This systematic approach was achieved by documenting cause and effect analyses for a wide variety of processing problems. This knowledge was organized in the form of IF-THEN rules, a common structure for knowledge representation in expert system technology. These rules form the knowledge base of the expert system which is stored in the computer. The systems also include the problem solving methodology used by the expert when addressing a problem in his area of expertise. Operators now use the expert systems to solve many process problems without engineering assistance. The systems also facilitate the collection of appropriate data to assist engineering in solving unanticipated problems. Currently, several expert systems have been implemented to cover all aspects of the photolithography process. The systems, which have been in use for over a year, include wafer surface preparation (HMDS), photoresist coat and softbake, align and expose on a wafer stepper, and develop inspection. These systems are part of a plan to implement an expert system diagnostic environment throughout the wafer fabrication facility. In this paper, the systems' construction is described, including knowledge acquisition, rule construction, knowledge refinement, testing, and evaluation. The roles played by the process engineering expert and the knowledge engineer are discussed. The features of the systems are shown, particularly the interactive quality of the consultations and the ease of system use.

The Case for Creative Abrasion: Experts Speak Out on Knowledge Management.

ERIC Educational Resources Information Center

Cowley-Durst, Barbara; Christensen, Hal D.; Degler, Duane; Weidner, Douglas; Feldstein, Michael

2001-01-01

Five knowledge management (KM) experts discuss answers to six fundamental issues of KM that address: a definition of knowledge and KM; relationship between business and KM; whether technology has helped the knowledge worker; relationship between learning, performance, knowledge, and community; the promise of knowledge ecology or ecosystem and…

Toward the integration of expert knowledge and instrumental data to control food processes: application to Camembert-type cheese ripening.

PubMed

Sicard, M; Perrot, N; Leclercq-Perlat, M-N; Baudrit, C; Corrieu, G

2011-01-01

Modeling the cheese ripening process remains a challenge because of its complexity. We still lack the knowledge necessary to understand the interactions that take place at different levels of scale during the process. However, information may be gathered from expert knowledge. Combining this expertise with knowledge extracted from experimental databases may allow a better understanding of the entire ripening process. The aim of this study was to elicit expert knowledge and to check its validity to assess the evolution of organoleptic quality during a dynamic food process: Camembert cheese ripening. Experiments on a pilot scale were carried out at different temperatures and relative humidities to obtain contrasting ripening kinetics. During these experiments, macroscopic evolution was evaluated from an expert's point of view and instrumental measurements were carried out to simultaneously monitor microbiological, physicochemical, and biochemical kinetics. A correlation of 76% was established between the microbiological, physicochemical, and biochemical data and the sensory phases measured according to expert knowledge, highlighting the validity of the experts' measurements. In the future, it is hoped that this expert knowledge may be integrated into food process models to build better decision-aid systems that will make it possible to preserve organoleptic qualities by linking them to other phenomena at the microscopic level. Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

An expert system prototype for aiding in the development of software functional requirements for NASA Goddard's command management system: A case study and lessons learned

NASA Technical Reports Server (NTRS)

Liebowitz, Jay

1986-01-01

At NASA Goddard, the role of the command management system (CMS) is to transform general requests for spacecraft opeerations into detailed operational plans to be uplinked to the spacecraft. The CMS is part of the NASA Data System which entails the downlink of science and engineering data from NASA near-earth satellites to the user, and the uplink of command and control data to the spacecraft. Presently, it takes one to three years, with meetings once or twice a week, to determine functional requirements for CMS software design. As an alternative approach to the present technique of developing CMS software functional requirements, an expert system prototype was developed to aid in this function. Specifically, the knowledge base was formulated through interactions with domain experts, and was then linked to an existing expert system application generator called 'Knowledge Engineering System (Version 1.3).' Knowledge base development focused on four major steps: (1) develop the problem-oriented attribute hierachy; (2) determine the knowledge management approach; (3) encode the knowledge base; and (4) validate, test, certify, and evaluate the knowledge base and the expert system prototype as a whole. Backcasting was accomplished for validating and testing the expert system prototype. Knowledge refinement, evaluation, and implementation procedures of the expert system prototype were then transacted.

SWAN: An expert system with natural language interface for tactical air capability assessment

NASA Technical Reports Server (NTRS)

Simmons, Robert M.

1987-01-01

SWAN is an expert system and natural language interface for assessing the war fighting capability of Air Force units in Europe. The expert system is an object oriented knowledge based simulation with an alternate worlds facility for performing what-if excursions. Responses from the system take the form of generated text, tables, or graphs. The natural language interface is an expert system in its own right, with a knowledge base and rules which understand how to access external databases, models, or expert systems. The distinguishing feature of the Air Force expert system is its use of meta-knowledge to generate explanations in the frame and procedure based environment.

[Locally advanced head and neck cancers: recommendations of an expert panel and perspectives for the use of TPF regimen (docetaxel, cisplatin and fluoro-uracil) as induction therapy].

PubMed

Bardet, E; Bourhis, J; Cals, L; Fayette, J; Guigay, J; Hans, S; Saint-Guily, J Lacau; Lagarde, F; Lallemant, B; Milano, G; Rolland, F; Lefebvre, J-L

2009-10-01

The purpose of the present article was to evaluate indications, regimens, treatment modalities, and predictive factors of response to treatment in locally advanced squamous cell carcinoma of the head and neck (SCCHN). An expert panel including otolaryngology and head and neck surgery specialists, oncologists, radiotherapists and biologists analyzed the literature providing a synthesis and giving some recommendations. Findings from the main randomized phase III trials highlight that the TPF regimen (docetaxel, cisplatin, fluorouracil) represent a preferential option when induction chemotherapy is indicated in either operable or non-operable patients. Given the potential fragility of patients presenting with SCCHN, treatment modalities in routine use require applying preventive measures and tailored follow-up according to each patient's profile. As regards predictive factors of response to TPF regimen, no factor is currently validated, but ongoing trials should provide better knowledge. Progresses in induction chemotherapy have allowed improving the prognosis of patients with locally advanced SCCHN. The TPF regimen represents a major improvement in this indication, and ongoing strategic clinical trials should refine its indications.

Ontology-Based Empirical Knowledge Verification for Professional Virtual Community

ERIC Educational Resources Information Center

Chen, Yuh-Jen

2011-01-01

A professional virtual community provides an interactive platform for enterprise experts to create and share their empirical knowledge cooperatively, and the platform contains a tremendous amount of hidden empirical knowledge that knowledge experts have preserved in the discussion process. Therefore, enterprise knowledge management highly…

Pedagogical Content Knowledge in Action: Its Impromptu Development by an Expert Practitioner

ERIC Educational Resources Information Center

Saito, Eisuke; Atencio, Matthew

2016-01-01

Research into pedagogical content knowledge (PCK) has advanced over the years. Yet, since most research has developed within specific subject areas, this paper aims to investigate how an expert teacher generates PCK by using various forms of knowledge. This study draws upon the case of an expert Japanese teacher, Mr. T, an educational consultant…

Model-based vision system for automatic recognition of structures in dental radiographs

NASA Astrophysics Data System (ADS)

Acharya, Raj S.; Samarabandu, Jagath K.; Hausmann, E.; Allen, K. A.

1991-07-01

X-ray diagnosis of destructive periodontal disease requires assessing serial radiographs by an expert to determine the change in the distance between cemento-enamel junction (CEJ) and the bone crest. To achieve this without the subjectivity of a human expert, a knowledge based system is proposed to automatically locate the two landmarks which are the CEJ and the level of alveolar crest at its junction with the periodontal ligament space. This work is a part of an ongoing project to automatically measure the distance between CEJ and the bone crest along a line parallel to the axis of the tooth. The approach presented in this paper is based on identifying a prominent feature such as the tooth boundary using local edge detection and edge thresholding to establish a reference and then using model knowledge to process sub-regions in locating the landmarks. Segmentation techniques invoked around these regions consists of a neural-network like hierarchical refinement scheme together with local gradient extraction, multilevel thresholding and ridge tracking. Recognition accuracy is further improved by first locating the easily identifiable parts of the bone surface and the interface between the enamel and the dentine and then extending these boundaries towards the periodontal ligament space and the tooth boundary respectively. The system is realized as a collection of tools (or knowledge sources) for pre-processing, segmentation, primary and secondary feature detection and a control structure based on the blackboard model to coordinate the activities of these tools.

Introducing quality improvement methods into local public health departments: structured evaluation of a statewide pilot project.

PubMed

Riley, William; Parsons, Helen; McCoy, Kim; Burns, Debra; Anderson, Donna; Lee, Suhna; Sainfort, François

2009-10-01

To test the feasibility and assess the preliminary impact of a unique statewide quality improvement (QI) training program designed for public health departments. One hundred and ninety-five public health employees/managers from 38 local health departments throughout Minnesota were selected to participate in a newly developed QI training program and 65 of those engaged in and completed eight expert-supported QI projects over a period of 10 months from June 2007 through March 2008. As part of the Minnesota Quality Improvement Initiative, a structured distance education QI training program was designed and deployed in a first large-scale pilot. To evaluate the preliminary impact of the program, a mixed-method evaluation design was used based on four dimensions: learner reaction, knowledge, intention to apply, and preliminary outcomes. Subjective ratings of three dimensions of training quality were collected from participants after each of the scheduled learning sessions. Pre- and post-QI project surveys were administered to collect participant reactions, knowledge, future intention to apply learning, and perceived outcomes. Monthly and final QI project reports were collected to further inform success and preliminary outcomes of the projects. The participants reported (1) high levels of satisfaction with the training sessions, (2) increased perception of the relevance of the QI techniques, (3) increased perceived knowledge of all specific QI methods and techniques, (4) increased confidence in applying QI techniques on future projects, (5) increased intention to apply techniques on future QI projects, and (6) high perceived success of, and satisfaction with, the projects. Finally, preliminary outcomes data show moderate to large improvements in quality and/or efficiency for six out of eight projects. QI methods and techniques can be successfully implemented in local public health agencies on a statewide basis using the collaborative model through distance training and expert facilitation. This unique training can improve both core and support processes and lead to favorable staff reactions, increased knowledge, and improved health outcomes. The program can be further improved and deployed and holds great promise to facilitate the successful dissemination of proven QI methods throughout local public health departments.

Small Knowledge-Based Systems in Education and Training: Something New Under the Sun.

ERIC Educational Resources Information Center

Wilson, Brent G.; Welsh, Jack R.

1986-01-01

Discusses artificial intelligence, robotics, natural language processing, and expert or knowledge-based systems research; examines two large expert systems, MYCIN and XCON; and reviews the resources required to build large expert systems and affordable smaller systems (intelligent job aids) for training. Expert system vendors and products are…

Expert Systems: A Challenge for the Reading Profession.

ERIC Educational Resources Information Center

Balajthy, Ernest

The expert systems are designed to imitate the reasoning of a human expert in a content area field. Designed to be advisors, these software systems combine the content area knowledge and decision-making ability of an expert with the user's understanding and knowledge of particular circumstances. The reading diagnosis system, the RD2P System…

Expert-Novice Differences in the Understanding and Explanation of Complex Political Conflicts

ERIC Educational Resources Information Center

Jones, David K.; Read, Stephen J.

2005-01-01

We compare the structure and content of political experts' knowledge with that of novices. We were particularly interested in whether experts would show more causal and historical reasoning in explaining political events, as well as whether their knowledge was structured in the form of a narrative. Eight relative political experts (advanced…

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.

Community Data Management and the Exchange for Local Observations and Knowledge of the Arctic

NASA Astrophysics Data System (ADS)

Duerr, R.; Pulsifer, P. L.; Strawhacker, C.; Mccann, H. S.

2016-12-01

The mission of the Exchange for Local Observations and Knowledge of the Arctic (ELOKA) is to facilitate the collection, preservation, exchange, and use of local observations and knowledge by Indigenous communities in the Arctic by providing data management services and user support, and by fostering collaboration between resident Arctic experts and visiting researchers. ELOKA's overarching philosophy is that Local and Traditional Knowledge (LTK) and scientific data and expertise are complementary and reinforcing ways of understanding the Arctic system. Collecting, documenting, preserving, and sharing knowledge is a cooperative endeavor, and ELOKA is dedicated to fostering ethical knowledge sharing among Arctic residents and communities, scientists, educators, policy makers, and the general public. But what does that mean in practice and what are the next steps for ELOKA in the coming years? In this presentation, we discuss the ethical issues involved with data management for LTK and community-based projects, some of the tools ELOKA has developed for interacting with communities and researchers and for managing LTK data, and our plans for the future. These include a discussion of the considerations local and community-based projects should make when planning and conducting research. It is clear, for example, that research projects should either include Indigenous voices at the outset of the project or have a prominent Indigenous voice so that appropriate methods or approaches can be adopted. Discussion of data access and funder obligations will be included. The data management tools that ELOKA employs and is developing for the future that can manage the wide range of data types typical of a community or LTK project will also be described, as will ELOKA's program for transferring long-term data management skills to communities that wish to take that on. Finally, ELOKA's plans for the future will be described.

Preliminary Design of a Consultation Knowledge-Based System for the Minimization of Distortion in Welded Structures

DTIC Science & Technology

1989-02-01

which capture the knowledge of such experts. These Expert Systems, or Knowledge-Based Systems’, differ from the usual computer programming techniques...their applications in the fields of structural design and welding is reviewed. 5.1 Introduction Expert Systems, or KBES, are computer programs using Al...procedurally constructed as conventional computer programs usually are; * The knowledge base of such systems is executable, unlike databases 3 "Ill

Expertise and category-based induction.

PubMed

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

2000-07-01

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

A middle man approach to knowledge acquisition in expert systems

NASA Technical Reports Server (NTRS)

Jordan, Janice A.; Lin, Min-Jin; Mayer, Richard J.; Sterle, Mark E.

1990-01-01

The Weed Control Advisor (WCA) is a robust expert system that has been successfully implemented on an IBM AT class microcomputer in CLIPS. The goal of the WCA was to demonstrate the feasibility of providing an economical, efficient, user friendly system through which Texas rice producers could obtain expert level knowledge regarding herbicide application for weed control. During the development phase of the WCA, an improved knowledge acquisition method which we call the Middle Man Approach (MMA) was applied to facilitate the communication process between the domain experts and the knowledge engineer. The MMA served to circumvent the problems associated with the more traditional forms of knowledge acquisition by placing the Middle Man, a semi-expert in the problem domain with some computer expertise, at the site of system development. The middle man was able to contribute to system development in two major ways. First, the Middle Man had experience working in rice production and could assume many of the responsibilities normally performed by the domain experts such as explaining the background of the problem domain and determining the important relations. Second, the Middle Man was familiar with computers and worked closely with the system developers to update the rules after the domain experts reviewed the prototype, contribute to the help menus and explanation portions of the expert system, conduct the testing that is required to insure that the expert system gives the expected results answer questions in a timely way, help the knowledge engineer structure the domain knowledge into a useable form, and provide insight into the end user's profile which helped in the development of the simple user friendly interface. The final results were not only that both time expended and costs were greatly reduced by using the MMA, but the quality of the system was improved. This papa will introduce the WCA system and then discuss traditional knowledge acquisition along with some of the problems often associated with it, the MMA methodology, and its application to the WCA development.

Expert System for Automated Design Synthesis

NASA Technical Reports Server (NTRS)

Rogers, James L., Jr.; Barthelemy, Jean-Francois M.

1987-01-01

Expert-system computer program EXADS developed to aid users of Automated Design Synthesis (ADS) general-purpose optimization program. EXADS aids engineer in determining best combination based on knowledge of specific problem and expert knowledge stored in knowledge base. Available in two interactive machine versions. IBM PC version (LAR-13687) written in IQ-LISP. DEC VAX version (LAR-13688) written in Franz-LISP.

Hazard perception, risk perception, and the need for decontamination by residents exposed to soil pollution: the role of sustainability and the limits of expert knowledge.

PubMed

Vandermoere, Frédéric

2008-04-01

This case study examines the hazard and risk perception and the need for decontamination according to people exposed to soil pollution. Using an ecological-symbolic approach (ESA), a multidisciplinary model is developed that draws upon psychological and sociological perspectives on risk perception and includes ecological variables by using data from experts' risk assessments. The results show that hazard perception is best predicted by objective knowledge, subjective knowledge, estimated knowledge of experts, and the assessed risks. However, experts' risk assessments induce an increase in hazard perception only when residents know the urgency of decontamination. Risk perception is best predicted by trust in the risk management. Additionally, need for decontamination relates to hazard perception, risk perception, estimated knowledge of experts, and thoughts about sustainability. In contrast to the knowledge deficit model, objective and subjective knowledge did not significantly relate to risk perception and need for decontamination. The results suggest that residents can make a distinction between hazards in terms of the seriousness of contamination on the one hand, and human health risks on the other hand. Moreover, next to the importance of social determinants of environmental risk perception, this study shows that the output of experts' risk assessments-or the objective risks-can create a hazard awareness rather than an alarming risk consciousness, despite residents' distrust of scientific knowledge.

How much expert knowledge is it worth to put in conceptual hydrological models?

NASA Astrophysics Data System (ADS)

Antonetti, Manuel; Zappa, Massimiliano

2017-04-01

Both modellers and experimentalists agree on using expert knowledge to improve our conceptual hydrological simulations on ungauged basins. However, they use expert knowledge differently for both hydrologically mapping the landscape and parameterising a given hydrological model. Modellers use generally very simplified (e.g. topography-based) mapping approaches and put most of the knowledge for constraining the model by defining parameter and process relational rules. In contrast, experimentalists tend to invest all their detailed and qualitative knowledge about processes to obtain a spatial distribution of areas with different dominant runoff generation processes (DRPs) as realistic as possible, and for defining plausible narrow value ranges for each model parameter. Since, most of the times, the modelling goal is exclusively to simulate runoff at a specific site, even strongly simplified hydrological classifications can lead to satisfying results due to equifinality of hydrological models, overfitting problems and the numerous uncertainty sources affecting runoff simulations. Therefore, to test to which extent expert knowledge can improve simulation results under uncertainty, we applied a typical modellers' modelling framework relying on parameter and process constraints defined based on expert knowledge to several catchments on the Swiss Plateau. To map the spatial distribution of the DRPs, mapping approaches with increasing involvement of expert knowledge were used. Simulation results highlighted the potential added value of using all the expert knowledge available on a catchment. Also, combinations of event types and landscapes, where even a simplified mapping approach can lead to satisfying results, were identified. Finally, the uncertainty originated by the different mapping approaches was compared with the one linked to meteorological input data and catchment initial conditions.

Identifying and Prioritizing Information Needs and Research Priorities of Public Health Emergency Preparedness and Response Practitioners.

PubMed

Siegfried, Alexa L; Carbone, Eric G; Meit, Michael B; Kennedy, Mallory J; Yusuf, Hussain; Kahn, Emily B

2017-10-01

This study describes findings from an assessment conducted to identify perceived knowledge gaps, information needs, and research priorities among state, territorial, and local public health preparedness directors and coordinators related to public health emergency preparedness and response (PHPR). The goal of the study was to gather information that would be useful for ensuring that future funding for research and evaluation targets areas most critical for advancing public health practice. We implemented a mixed-methods approach to identify and prioritize PHPR research questions. A web survey was sent to all state, city, and territorial health agencies funded through the Public Health Emergency Preparedness (PHEP) Cooperative Agreement program and a sample of local health departments (LHDs). Three focus groups of state and local practitioners and subject matter experts from the Centers for Disease Control and Prevention (CDC) were subsequently conducted, followed by 3 meetings of an expert panel of PHPR practitioners and CDC experts to prioritize and refine the research questions. We identified a final list of 44 research questions that were deemed by study participants as priority topics where future research can inform PHPR programs and practice. We identified differences in perceived research priorities between PHEP awardees and LHD survey respondents; the number of research questions rated as important was greater among LHDs than among PHEP awardees (75%, n=33, compared to 24%, n=15). The research questions identified provide insight into public health practitioners' perceived knowledge gaps and the types of information that would be most useful for informing and advancing PHPR practice. The study also points to a higher level of information need among LHDs than among PHEP awardees. These findings are important for CDC and the PHPR research community to ensure that future research studies are responsive to practitioners' needs and provide the information required to enhance their capacity to meet the needs of the communities and jurisdictions they serve. (Disaster Med Public Health Preparedness. 2017;11:552-561).

Risk perception of tsunami in the community of Arauco, Chile - a contribution of risk perception to disaster risk management at local level

NASA Astrophysics Data System (ADS)

Kubisch, M. Sc. Susanne; Edilia Jaque Castillo, Dra.; Braun, JProf. Andreas Ch., ,, Dr.

2017-04-01

The research was carried out in the city center of the coastal community of Arauco, Central Chile. The community of Arauco was one of the most affected communities of the tsunami in Chile, the 27th of February 2010. For the data evaluation, the affected inhabitants of the community have been surveyed via standardized questionnaires. Furthermore experts of different fields, amongst others, Disaster Risk Management (DRM), risk education, urban and regional planning, as well as geology have been consulted in form of expert interviews. The results revealed a high risk perception part of the affected community and a weakness of DRM especially at local level, which opens a gap between the evaluation and treatment of risk by experts and risk perception of the affected community. The risk perception of the affected community, here, is predominantly determined by ecological vulnerability, expressed in direct and indirect experience of a tsunami and by institutional vulnerability, expressed among others by a weakness of DRM at local level and a mistrust in responsible institutions for DRM. Due to the institutional vulnerability and the mistrust in responsible institutions we recommend a Community Based Approach (CBA) to strengthen DRM at local level and to take advantage of the high risk perception and knowledge of the affected community. Involving the community in DRM, we assume to close the gap between risk evaluation of experts and risk perception of the inhabitants and to come up with the unique necessities and conditions at local level. Especially in centralized countries, DRM is less effective, because at the one hand, decisions are made distant from the affected communities, so that measures often do not come up with the unique conditions and necessities at local level, and on the other hand measures often do not find acceptance by the affected community. Furthermore centralized DRM is often not effective and quick in response in case of emergency. Another obstacle for an effective DRM, often forms the general mistrust in governmental institutions. In these cases the participation of the affected communities in form of CBAs are assumed to overcome these problems.

Knowing for Nursing Practice: Patterns of Knowledge and Their Emulation in Expert Systems

PubMed Central

Abraham, Ivo L.; Fitzpatrick, Joyce J.

1987-01-01

This paper addresses the issue of clinical knowledge in nursing, and the feasibility of emulating this knowledge into expert system technology. The perspective on patterns of knowing for nursing practice, advanced by Carper (1978), serves as point of departure. The four patterns of knowing -- empirics, esthetics, ethics, personal knowledge -- are evaluated as to the extent to which they can be emulated in clinical expert systems, given constraints imposed by the current technology of these systems.

Expert elicitation of population-level effects of disturbance

USGS Publications Warehouse

Fleishman, Erica; Burgman, Mark; Runge, Michael C.; Schick, Robert S; Krauss, Scott; Popper, Arthur N.; Hawkins, Anthony

2016-01-01

Expert elicitation is a rigorous method for synthesizing expert knowledge to inform decision making and is reliable and practical when field data are limited. We evaluated the feasibility of applying expert elicitation to estimate population-level effects of disturbance on marine mammals. Diverse experts estimated parameters related to mortality and sublethal injury of North Atlantic right whales (Eubalaena glacialis). We are now eliciting expert knowledge on the movement of right whales among geographic regions to parameterize a spatial model of health. Expert elicitation complements methods such as simulation models or extrapolations from other species, sometimes with greater accuracy and less uncertainty.

An Expert System for Environmental Data Management.

ERIC Educational Resources Information Center

Berka, Petr; Jirku, Petr

1995-01-01

Examines the possibility of using expert system tools for environmental data management. Describes the domain-independent expert system shell SAK and Knowledge EXplorer, a system that learns rules from data. Demonstrates the functionality of Knowledge EXplorer on an example of water quality evaluation. (LZ)

Hidden Expert Knowledge: The Knowledge That Counts for the Small School-District Superintendent

ERIC Educational Resources Information Center

Hyle, Adrienne E.; Ivory, Gary; McClellan, Rhonda L.

2010-01-01

Using Bereiter and Scardamalia's (1993) hidden expert knowledge, we explored what knowledge counts from the perspectives of working small school-district superintendents and the ways in which they gain that knowledge. This qualitative study used focus groups as its primary data collection method. Participants were 37 superintendents of districts…

Scientific practices and social behaviors in managing landslide risks: comparing experiences between developing and developed countries

NASA Astrophysics Data System (ADS)

Devoli, G.

2012-04-01

A successful landslide risk reduction program requires that the society is aware and understand the landslide problems within the geographic area involved. Central organizations that manage national landslide risks should: a) create and systematically applied natural hazard laws/national landslide strategies, where roles and limits of responsibilities of federal, state, provincial, municipal and private entities are well defined; c) establish fruitful multidisciplinary and interinstitutional collaboration among scientists; d) provide good risk assessments in which landslide experts report transparently what is really known and the limitations of methods and tools used; e) share and systematically communicate their knowledge more effectively with all private and public stakeholders involved, paying attention to providing balanced information about risks and addressing inevitable uncertainties; f) support the mass-media in spreading correct scientific information; g) perform serious risk and cost-benefit analyses before mitigation measures are realized; h) assist local authorities in the application of land-use planning policies and g) built trust and confidence by means of a continuous contact and communication with the public and local authorities. However, this is not yet achieved, not even in developed countries where, in theory, more economical resources are available and people are better educated then in developing countries. Herein I make some observations on how national landslide prevention efforts are being organized in two countries (Nicaragua and Norway), where I have been worked at governmental agencies as landslide expert in the last 10 years. I start describing similarities and differences between the countries and try to compare practices and experiences. The analysis was motivated by the following questions: Why after so many years of landslide mapping and investigations, landslide prevention is not good and effective as it should be? Is this because of wrong or inadequate scientific practices, unethical landslide experts, complex bureaucracy and hierarchy at governmental level, presence of non-scientific public officials and politicians with lack of long-term landslide risk management knowledge, often interposed between landslide experts and public, or, because of others human behaviors, or social or political aspects that make this difficult? Are there any differences or similarities in landslide prevention between developed and developing countries? Where is better achieved a good communication between landslide experts and public? Where the multidisciplinary and interstitutional cooperation among specialists gives the most fruitful results? Is it possible and how we can exchange knowledge and experiences learned in developing countries?

Localized neuropathic pain: an expert consensus on local treatments

PubMed Central

Pickering, Gisèle; Martin, Elodie; Tiberghien, Florence; Delorme, Claire; Mick, Gérard

2017-01-01

Background Pain localization is one of the hallmarks for the choice of first-line treatment in neuropathic pain. This literature review has been conducted to provide an overview of the current knowledge regarding the etiology and pathophysiology of localized neuropathic pain (LNP), its assessment and the existing topical pharmacological treatments. Materials and methods Literature review was performed using Medline from 2010 to December 2016, and all studies involving LNP and treatments were examined. A multidisciplinary expert panel of five pain specialists in this article reports a consensus on topical approaches that may be recommended to alleviate LNP and on their advantages in clinical practice. Results Successive international recommendations have included topical 5% lidocaine and 8% capsaicin for LNP treatment. The expert panel considers that these compounds can be a first-line treatment for LNP, especially in elderly patients and patients with comorbidities and polypharmacy. Regulatory LNP indications should cover the whole range of LNP and not be restricted to specific etiologies or sites. Precautions for the use of plasters must be followed cautiously. Conclusion Although there is a real need for more randomized controlled trials for both drugs, publications clearly demonstrate excellent risk/benefit ratios, safety, tolerance and continued efficacy throughout long-term treatment. A major advantage of both plasters is that they have proven efficacy and may reduce the risk of adverse events such as cognitive impairment, confusion, somnolence, dizziness and constipation that are often associated with systemic neuropathic pain treatment and reduce the quality of life. Topical modalities also may be used in combination with other drugs and analgesics with limited drug–drug interactions. PMID:29066862

Expert systems applied to spacecraft fire safety

NASA Technical Reports Server (NTRS)

Smith, Richard L.; Kashiwagi, Takashi

1989-01-01

Expert systems are problem-solving programs that combine a knowledge base and a reasoning mechanism to simulate a human expert. The development of an expert system to manage fire safety in spacecraft, in particular the NASA Space Station Freedom, is difficult but clearly advantageous in the long-term. Some needs in low-gravity flammability characteristics, ventilating-flow effects, fire detection, fire extinguishment, and decision models, all necessary to establish the knowledge base for an expert system, are discussed.

Knowledge discovery from data and Monte-Carlo DEA to evaluate technical efficiency of mental health care in small health areas

PubMed Central

García-Alonso, Carlos; Pérez-Naranjo, Leonor

2009-01-01

Introduction Knowledge management, based on information transfer between experts and analysts, is crucial for the validity and usability of data envelopment analysis (DEA). Aim To design and develop a methodology: i) to assess technical efficiency of small health areas (SHA) in an uncertainty environment, and ii) to transfer information between experts and operational models, in both directions, for improving expert’s knowledge. Method A procedure derived from knowledge discovery from data (KDD) is used to select, interpret and weigh DEA inputs and outputs. Based on KDD results, an expert-driven Monte-Carlo DEA model has been designed to assess the technical efficiency of SHA in Andalusia. Results In terms of probability, SHA 29 is the most efficient being, on the contrary, SHA 22 very inefficient. 73% of analysed SHA have a probability of being efficient (Pe) >0.9 and 18% <0.5. Conclusions Expert knowledge is necessary to design and validate any operational model. KDD techniques make the transfer of information from experts to any operational model easy and results obtained from the latter improve expert’s knowledge.

Kees: a Practical Ict Solution for Rural Areas

NASA Astrophysics Data System (ADS)

Dai, Xiaoye; Tabirca, Sabin; Lenihan, Eamon

This paper introduces a practical e-learning system, identified as Knowledge Exchange E-learning System (abbr. KEES), for knowledge distribution in rural areas. Particularly, this paper is about providing a virtual teaching and learning environment for small holders in agriculture in those rural areas. E-learning is increasingly influencing the agricultural education (information and knowledge learning) in all forms and the current e-learning in agricultural education appears in informal and formal methods in many developed countries and some developing areas such as Asian Pacific regions. KEES is a solution to provide education services including other services of information distribution and knowledge sharing to local farmers, local institutes or local collection of farmers. The design of KEES is made to meet the needs of knowledge capacity building, experience sharing, skill upgrading, and information exchanging in agriculture for different conditions in rural areas. The system allows the online lecture/training materials to be distributed simultaneously with all multimedia resources through different file formats across different platforms. The teaching/training content can be contextless and broad, allowing for greater participation by more small holders, commercial farmers, extension workers, agriculturists, educators, and other agriculture-related experts. The relative inconsistency in content gives farmers more localised and useful knowledge. The framework of KEES has been designed to be a three-tier architecture logic workflow, which can configure the progressive approach for KEES to pass on and respond to different requests/communications between the client side and the server.

Eight habitats, 38 threats and 55 experts: Assessing ecological risk in a multi-use marine region

PubMed Central

Jones, Alice R.; Deveney, Marty R.; Ward, Tim M.; Gillanders, Bronwyn M.

2017-01-01

Identifying the relative risk human activities pose to a habitat, and the ecosystem services they provide, can guide management prioritisation and resource allocation. Using a combination of expert elicitation to assess the probable effect of a threat and existing data to assess the level of threat exposure, we conducted a risk assessment for 38 human-mediated threats to eight marine habitats (totalling 304 threat-habitat combinations) in Spencer Gulf, Australia. We developed a score-based survey to collate expert opinion and assess the relative effect of each threat to each habitat, as well as a novel and independent measure of knowledge-based uncertainty. Fifty-five experts representing multiple sectors and institutions participated in the study, with 6 to 15 survey responses per habitat (n = 81 surveys). We identified key threats specific to each habitat; overall, climate change threats received the highest risk rankings, with nutrient discharge identified as a key local-scale stressor. Invasive species and most fishing-related threats, which are commonly identified as major threats to the marine environment, were ranked as low-tier threats to Spencer Gulf, emphasising the importance of regionally-relevant assessments. Further, we identified critical knowledge gaps and quantified uncertainty scores for each risk. Our approach will facilitate prioritisation of resource allocation in a region of increasing social, economic and environmental importance, and can be applied to marine regions where empirical data are lacking. PMID:28489912

Automatic Overset Grid Generation with Heuristic Feedback Control

NASA Technical Reports Server (NTRS)

Robinson, Peter I.

2001-01-01

An advancing front grid generation system for structured Overset grids is presented which automatically modifies Overset structured surface grids and control lines until user-specified grid qualities are achieved. The system is demonstrated on two examples: the first refines a space shuttle fuselage control line until global truncation error is achieved; the second advances, from control lines, the space shuttle orbiter fuselage top and fuselage side surface grids until proper overlap is achieved. Surface grids are generated in minutes for complex geometries. The system is implemented as a heuristic feedback control (HFC) expert system which iteratively modifies the input specifications for Overset control line and surface grids. It is developed as an extension of modern control theory, production rules systems and subsumption architectures. The methodology provides benefits over the full knowledge lifecycle of an expert system for knowledge acquisition, knowledge representation, and knowledge execution. The vector/matrix framework of modern control theory systematically acquires and represents expert system knowledge. Missing matrix elements imply missing expert knowledge. The execution of the expert system knowledge is performed through symbolic execution of the matrix algebra equations of modern control theory. The dot product operation of matrix algebra is generalized for heuristic symbolic terms. Constant time execution is guaranteed.

A Knowledge-Based System Developer for aerospace applications

NASA Technical Reports Server (NTRS)

Shi, George Z.; Wu, Kewei; Fensky, Connie S.; Lo, Ching F.

1993-01-01

A prototype Knowledge-Based System Developer (KBSD) has been developed for aerospace applications by utilizing artificial intelligence technology. The KBSD directly acquires knowledge from domain experts through a graphical interface then builds expert systems from that knowledge. This raises the state of the art of knowledge acquisition/expert system technology to a new level by lessening the need for skilled knowledge engineers. The feasibility, applicability , and efficiency of the proposed concept was established, making a continuation which would develop the prototype to a full-scale general-purpose knowledge-based system developer justifiable. The KBSD has great commercial potential. It will provide a marketable software shell which alleviates the need for knowledge engineers and increase productivity in the workplace. The KBSD will therefore make knowledge-based systems available to a large portion of industry.

Research and development for Onboard Navigation (ONAV) ground based expert/trainer system: Preliminary ascent knowledge requirements

NASA Technical Reports Server (NTRS)

Bochsler, Daniel C.

1988-01-01

The preliminary version of expert knowledge for the Onboard Navigation (ONAV) Ground Based Expert Trainer Ascent system for the space shuttle is presented. Included is some brief background information along with the information describing the knowledge the system will contain. Information is given on rules and heuristics, telemetry status, landing sites, inertial measurement units, and a high speed trajectory determinator (HSTD) state vector.

A Semiautomated Framework for Integrating Expert Knowledge into Disease Marker Identification

PubMed Central

Wang, Jing; Webb-Robertson, Bobbie-Jo M.; Matzke, Melissa M.; Varnum, Susan M.; Brown, Joseph N.; Riensche, Roderick M.; Adkins, Joshua N.; Jacobs, Jon M.; Hoidal, John R.; Scholand, Mary Beth; Pounds, Joel G.; Blackburn, Michael R.; Rodland, Karin D.; McDermott, Jason E.

2013-01-01

Background. The availability of large complex data sets generated by high throughput technologies has enabled the recent proliferation of disease biomarker studies. However, a recurring problem in deriving biological information from large data sets is how to best incorporate expert knowledge into the biomarker selection process. Objective. To develop a generalizable framework that can incorporate expert knowledge into data-driven processes in a semiautomated way while providing a metric for optimization in a biomarker selection scheme. Methods. The framework was implemented as a pipeline consisting of five components for the identification of signatures from integrated clustering (ISIC). Expert knowledge was integrated into the biomarker identification process using the combination of two distinct approaches; a distance-based clustering approach and an expert knowledge-driven functional selection. Results. The utility of the developed framework ISIC was demonstrated on proteomics data from a study of chronic obstructive pulmonary disease (COPD). Biomarker candidates were identified in a mouse model using ISIC and validated in a study of a human cohort. Conclusions. Expert knowledge can be introduced into a biomarker discovery process in different ways to enhance the robustness of selected marker candidates. Developing strategies for extracting orthogonal and robust features from large data sets increases the chances of success in biomarker identification. PMID:24223463

A Semiautomated Framework for Integrating Expert Knowledge into Disease Marker Identification

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

Wang, Jing; Webb-Robertson, Bobbie-Jo M.; Matzke, Melissa M.

2013-10-01

Background. The availability of large complex data sets generated by high throughput technologies has enabled the recent proliferation of disease biomarker studies. However, a recurring problem in deriving biological information from large data sets is how to best incorporate expert knowledge into the biomarker selection process. Objective. To develop a generalizable framework that can incorporate expert knowledge into data-driven processes in a semiautomated way while providing a metric for optimization in a biomarker selection scheme. Methods. The framework was implemented as a pipeline consisting of five components for the identification of signatures from integrated clustering (ISIC). Expert knowledge was integratedmore » into the biomarker identification process using the combination of two distinct approaches; a distance-based clustering approach and an expert knowledge-driven functional selection. Results. The utility of the developed framework ISIC was demonstrated on proteomics data from a study of chronic obstructive pulmonary disease (COPD). Biomarker candidates were identified in a mouse model using ISIC and validated in a study of a human cohort. Conclusions. Expert knowledge can be introduced into a biomarker discovery process in different ways to enhance the robustness of selected marker candidates. Developing strategies for extracting orthogonal and robust features from large data sets increases the chances of success in biomarker identification.« less

Relation of Knowledge and Performance in Boys' Tennis: Age and Expertise.

ERIC Educational Resources Information Center

McPherson, Sue L.; Thomas, Jerry R.

1989-01-01

Examined 10- to 13-year-old boys' development of knowledge structure and sport performance in tennis by comparing skills and knowledge of experts and novices. Experts focused on higher concepts and exhibited greater decision-making ability because of their more highly developed knowledge structure. (SAK)

Artificial intelligence within the chemical laboratory.

PubMed

Winkel, P

1994-01-01

Various techniques within the area of artificial intelligence such as expert systems and neural networks may play a role during the problem-solving processes within the clinical biochemical laboratory. Neural network analysis provides a non-algorithmic approach to information processing, which results in the ability of the computer to form associations and to recognize patterns or classes among data. It belongs to the machine learning techniques which also include probabilistic techniques such as discriminant function analysis and logistic regression and information theoretical techniques. These techniques may be used to extract knowledge from example patients to optimize decision limits and identify clinically important laboratory quantities. An expert system may be defined as a computer program that can give advice in a well-defined area of expertise and is able to explain its reasoning. Declarative knowledge consists of statements about logical or empirical relationships between things. Expert systems typically separate declarative knowledge residing in a knowledge base from the inference engine: an algorithm that dynamically directs and controls the system when it searches its knowledge base. A tool is an expert system without a knowledge base. The developer of an expert system uses a tool by entering knowledge into the system. Many, if not the majority of problems encountered at the laboratory level are procedural. A problem is procedural if it is possible to write up a step-by-step description of the expert's work or if it can be represented by a decision tree. To solve problems of this type only small expert system tools and/or conventional programming are required.(ABSTRACT TRUNCATED AT 250 WORDS)

Deep nets vs expert designed features in medical physics: An IMRT QA case study.

PubMed

Interian, Yannet; Rideout, Vincent; Kearney, Vasant P; Gennatas, Efstathios; Morin, Olivier; Cheung, Joey; Solberg, Timothy; Valdes, Gilmer

2018-03-30

The purpose of this study was to compare the performance of Deep Neural Networks against a technique designed by domain experts in the prediction of gamma passing rates for Intensity Modulated Radiation Therapy Quality Assurance (IMRT QA). A total of 498 IMRT plans across all treatment sites were planned in Eclipse version 11 and delivered using a dynamic sliding window technique on Clinac iX or TrueBeam Linacs. Measurements were performed using a commercial 2D diode array, and passing rates for 3%/3 mm local dose/distance-to-agreement (DTA) were recorded. Separately, fluence maps calculated for each plan were used as inputs to a convolution neural network (CNN). The CNNs were trained to predict IMRT QA gamma passing rates using TensorFlow and Keras. A set of model architectures, inspired by the convolutional blocks of the VGG-16 ImageNet model, were constructed and implemented. Synthetic data, created by rotating and translating the fluence maps during training, was created to boost the performance of the CNNs. Dropout, batch normalization, and data augmentation were utilized to help train the model. The performance of the CNNs was compared to a generalized Poisson regression model, previously developed for this application, which used 78 expert designed features. Deep Neural Networks without domain knowledge achieved comparable performance to a baseline system designed by domain experts in the prediction of 3%/3 mm Local gamma passing rates. An ensemble of neural nets resulted in a mean absolute error (MAE) of 0.70 ± 0.05 and the domain expert model resulted in a 0.74 ± 0.06. Convolutional neural networks (CNNs) with transfer learning can predict IMRT QA passing rates by automatically designing features from the fluence maps without human expert supervision. Predictions from CNNs are comparable to a system carefully designed by physicist experts. © 2018 American Association of Physicists in Medicine.

Intelligent manipulation technique for multi-branch robotic systems

NASA Technical Reports Server (NTRS)

Chen, Alexander Y. K.; Chen, Eugene Y. S.

1990-01-01

New analytical development in kinematics planning is reported. The INtelligent KInematics Planner (INKIP) consists of the kinematics spline theory and the adaptive logic annealing process. Also, a novel framework of robot learning mechanism is introduced. The FUzzy LOgic Self Organized Neural Networks (FULOSONN) integrates fuzzy logic in commands, control, searching, and reasoning, the embedded expert system for nominal robotics knowledge implementation, and the self organized neural networks for the dynamic knowledge evolutionary process. Progress on the mechanical construction of SRA Advanced Robotic System (SRAARS) and the real time robot vision system is also reported. A decision was made to incorporate the Local Area Network (LAN) technology in the overall communication system.

An engineering approach to the use of expert systems technology in avionics applications

NASA Technical Reports Server (NTRS)

Duke, E. L.; Regenie, V. A.; Brazee, M.; Brumbaugh, R. W.

1986-01-01

The concept of using a knowledge compiler to transform the knowledge base and inference mechanism of an expert system into a conventional program is presented. The need to accommodate real-time systems requirements in applications such as embedded avionics is outlined. Expert systems and a brief comparison of expert systems and conventional programs are reviewed. Avionics applications of expert systems are discussed before the discussions of applying the proposed concept to example systems using forward and backward chaining.

Expert systems and simulation models; Proceedings of the Seminar, Tucson, AZ, November 18, 19, 1985

NASA Technical Reports Server (NTRS)

1986-01-01

The seminar presents papers on modeling and simulation methodology, artificial intelligence and expert systems, environments for simulation/expert system development, and methodology for simulation/expert system development. Particular attention is given to simulation modeling concepts and their representation, modular hierarchical model specification, knowledge representation, and rule-based diagnostic expert system development. Other topics include the combination of symbolic and discrete event simulation, real time inferencing, and the management of large knowledge-based simulation projects.

Perspectives on knowledge in engineering design

NASA Technical Reports Server (NTRS)

Rasdorf, W. J.

1985-01-01

Various perspectives are given of the knowledge currently used in engineering design, specifically dealing with knowledge-based expert systems (KBES). Constructing an expert system often reveals inconsistencies in domain knowledge while formalizing it. The types of domain knowledge (facts, procedures, judgments, and control) differ from the classes of that knowledge (creative, innovative, and routine). The feasible tasks for expert systems can be determined based on these types and classes of knowledge. Interpretive tasks require reasoning about a task in light of the knowledge available, where generative tasks create potential solutions to be tested against constraints. Only after classifying the domain by type and level can the engineer select a knowledge-engineering tool for the domain being considered. The critical features to be weighed after classification are knowledge representation techniques, control strategies, interface requirements, compatibility with traditional systems, and economic considerations.

Computer-assisted knowledge acquisition for hypermedia systems

NASA Technical Reports Server (NTRS)

Steuck, Kurt

1990-01-01

The usage of procedural and declarative knowledge to set up the structure or 'web' of a hypermedia environment is described. An automated knowledge acquisition tool was developed that helps a knowledge engineer elicit and represent an expert's knowledge involved in performing procedural tasks. The tool represents both procedural and prerequisite, declarative knowledge that supports each activity performed by the expert. This knowledge is output and subsequently read by a hypertext scripting language to generate the link between blank, but labeled cards. Each step of the expert's activity and each piece of supporting declarative knowledge is set up as an empty node. An instructional developer can then enter detailed instructional material concerning each step and declarative knowledge into these empty nodes. Other research is also described that facilitates the translation of knowledge from one form into a form more readily useable by computerized systems.

A reusable knowledge acquisition shell: KASH

NASA Technical Reports Server (NTRS)

Westphal, Christopher; Williams, Stephen; Keech, Virginia

1991-01-01

KASH (Knowledge Acquisition SHell) is proposed to assist a knowledge engineer by providing a set of utilities for constructing knowledge acquisition sessions based on interviewing techniques. The information elicited from domain experts during the sessions is guided by a question dependency graph (QDG). The QDG defined by the knowledge engineer, consists of a series of control questions about the domain that are used to organize the knowledge of an expert. The content information supplies by the expert, in response to the questions, is represented in the form of a concept map. These maps can be constructed in a top-down or bottom-up manner by the QDG and used by KASH to generate the rules for a large class of expert system domains. Additionally, the concept maps can support the representation of temporal knowledge. The high degree of reusability encountered in the QDG and concept maps can vastly reduce the development times and costs associated with producing intelligent decision aids, training programs, and process control functions.

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.

Processes in construction of failure management expert systems from device design information

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Lance, Nick

1987-01-01

This paper analyzes the tasks and problem solving methods used by an engineer in constructing a failure management expert system from design information about the device to te diagnosed. An expert test engineer developed a trouble-shooting expert system based on device design information and experience with similar devices, rather than on specific expert knowledge gained from operating the device or troubleshooting its failures. The construction of the expert system was intensively observed and analyzed. This paper characterizes the knowledge, tasks, methods, and design decisions involved in constructing this type of expert system, and makes recommendations concerning tools for aiding and automating construction of such systems.

Does expert knowledge improve automatic probabilistic classification of gait joint motion patterns in children with cerebral palsy?

PubMed Central

Papageorgiou, Eirini; Nieuwenhuys, Angela; Desloovere, Kaat

2017-01-01

Background This study aimed to improve the automatic probabilistic classification of joint motion gait patterns in children with cerebral palsy by using the expert knowledge available via a recently developed Delphi-consensus study. To this end, this study applied both Naïve Bayes and Logistic Regression classification with varying degrees of usage of the expert knowledge (expert-defined and discretized features). A database of 356 patients and 1719 gait trials was used to validate the classification performance of eleven joint motions. Hypotheses Two main hypotheses stated that: (1) Joint motion patterns in children with CP, obtained through a Delphi-consensus study, can be automatically classified following a probabilistic approach, with an accuracy similar to clinical expert classification, and (2) The inclusion of clinical expert knowledge in the selection of relevant gait features and the discretization of continuous features increases the performance of automatic probabilistic joint motion classification. Findings This study provided objective evidence supporting the first hypothesis. Automatic probabilistic gait classification using the expert knowledge available from the Delphi-consensus study resulted in accuracy (91%) similar to that obtained with two expert raters (90%), and higher accuracy than that obtained with non-expert raters (78%). Regarding the second hypothesis, this study demonstrated that the use of more advanced machine learning techniques such as automatic feature selection and discretization instead of expert-defined and discretized features can result in slightly higher joint motion classification performance. However, the increase in performance is limited and does not outweigh the additional computational cost and the higher risk of loss of clinical interpretability, which threatens the clinical acceptance and applicability. PMID:28570616

Building legitimacy by criticising the pharmaceutical industry: a qualitative study among prescribers and local opinion leaders.

PubMed

Pittet, Anne-Laure; Saraga, Michael; Stiefel, Friedrich

2015-01-01

The literature has described opinion leaders not only as marketing tools of the pharmaceutical industry, but also as educators promoting good clinical practice. This qualitative study addresses the distinction between the opinion-leader-as-marketing-tool and the opinion-leader-as-educator, as it is revealed in the discourses of physicians and experts, focusing on the prescription of antidepressants. We explore the relational dynamic between physicians, opinion leaders and the pharmaceutical industry in an area of French-speaking Switzerland. Qualitative content analysis of 24 semistructured interviews with physicians and local experts in psychopharmacology, complemented by direct observation of educational events led by the experts, which were all sponsored by various pharmaceutical companies. Both physicians and experts were critical of the pharmaceutical industry and its use of opinion leaders. Local experts, in contrast, were perceived by the physicians as critical of the industry and, therefore, as a legitimate source of information. Local experts did not consider themselves opinion leaders and argued that they remained intellectually independent from the industry. Field observations confirmed that local experts criticised the industry at continuing medical education events. Local experts were vocal critics of the industry, which nevertheless sponsor their continuing education. This critical attitude enhanced their credibility in the eyes of the prescribing physicians. We discuss how the experts, despite their critical attitude, might still be beneficial to the industry's interests.

TARGET: Rapid Capture of Process Knowledge

NASA Technical Reports Server (NTRS)

Ortiz, C. J.; Ly, H. V.; Saito, T.; Loftin, R. B.

1993-01-01

TARGET (Task Analysis/Rule Generation Tool) represents a new breed of tool that blends graphical process flow modeling capabilities with the function of a top-down reporting facility. Since NASA personnel frequently perform tasks that are primarily procedural in nature, TARGET models mission or task procedures and generates hierarchical reports as part of the process capture and analysis effort. Historically, capturing knowledge has proven to be one of the greatest barriers to the development of intelligent systems. Current practice generally requires lengthy interactions between the expert whose knowledge is to be captured and the knowledge engineer whose responsibility is to acquire and represent the expert's knowledge in a useful form. Although much research has been devoted to the development of methodologies and computer software to aid in the capture and representation of some types of knowledge, procedural knowledge has received relatively little attention. In essence, TARGET is one of the first tools of its kind, commercial or institutional, that is designed to support this type of knowledge capture undertaking. This paper will describe the design and development of TARGET for the acquisition and representation of procedural knowledge. The strategies employed by TARGET to support use by knowledge engineers, subject matter experts, programmers and managers will be discussed. This discussion includes the method by which the tool employs its graphical user interface to generate a task hierarchy report. Next, the approach to generate production rules for incorporation in and development of a CLIPS based expert system will be elaborated. TARGET also permits experts to visually describe procedural tasks as a common medium for knowledge refinement by the expert community and knowledge engineer making knowledge consensus possible. The paper briefly touches on the verification and validation issues facing the CLIPS rule generation aspects of TARGET. A description of efforts to support TARGET's interoperability issues on PCs, Macintoshes and UNIX workstations concludes the paper.

The KnowRISK project - Know your city, Reduce seISmic risK through non-structural elements

NASA Astrophysics Data System (ADS)

Sousa Oliveria, Carlos; Amaral Ferreira, Mónica; Lopez, Mário; Sousa Silva, Delta; Musacchio, Gemma; Rupakhety, Rajesh; Falsaperla, Susanna; Meroni, Fabrizio; Langer, Horst

2016-04-01

Historically, there is a tendency to focus on seismic structural performance of buildings, neglecting the potential for damage of non-structural elements. In particular, non-structural elements of buildings are their architectural parts (i.e. partitions, ceilings, cladding), electrical and mechanical components (i.e., distribution panels, piping, plumbing), and contents (e.g., furniture, bookcases, computers and desktop equipment). Damage of these elements often contributes significantly to earthquake impacts. In the 1999 Izmit Earthquake, Turkey, 50% of the injuries and 3% of human losses were caused by non-structural failures. In the 2010-2011 Christchurch Earthquakes (New Zealand), 40% of building damage was induced by non-structural malfunctions. Around 70%-85% of construction cost goes into these elements, and their damage can strongly influence the ability of communities to cope with and recover from earthquakes. The project Know your city, Reduce seISmic risK through non-structural elements (KnowRISK) aims at facilitating local communities' access to expert knowledge on non-structural seismic protection solutions. The project will study seismic scenarios critical for non-structural damage, produce a portfolio of non-structural protection measures and investigate the level of awareness in specific communities. We will implement risk communication strategies that will take into account the social and cultural background and a participatory approach to raise awareness in local communities. The paradox between the progress of scientific knowledge and the ongoing increase of losses from natural disasters worldwide is a well-identified gap in the UN Hyogo Framework for Action 2005-2015, in which one of the main priorities is the investment on "knowledge use, innovation and education to build a culture of safety and resilience". The KnowRISK is well aligned with these priorities and will contribute to participatory action aimed at: i) transferring expert knowledge on seismic risk and non-structural protective solutions into practical knowledge and ii) communication tools designed to engage communities in disaster risk reduction

Automatic two- and three-dimensional mesh generation based on fuzzy knowledge processing

NASA Astrophysics Data System (ADS)

Yagawa, G.; Yoshimura, S.; Soneda, N.; Nakao, K.

1992-09-01

This paper describes the development of a novel automatic FEM mesh generation algorithm based on the fuzzy knowledge processing technique. A number of local nodal patterns are stored in a nodal pattern database of the mesh generation system. These nodal patterns are determined a priori based on certain theories or past experience of experts of FEM analyses. For example, such human experts can determine certain nodal patterns suitable for stress concentration analyses of cracks, corners, holes and so on. Each nodal pattern possesses a membership function and a procedure of node placement according to this function. In the cases of the nodal patterns for stress concentration regions, the membership function which is utilized in the fuzzy knowledge processing has two meanings, i.e. the “closeness” of nodal location to each stress concentration field as well as “nodal density”. This is attributed to the fact that a denser nodal pattern is required near a stress concentration field. What a user has to do in a practical mesh generation process are to choose several local nodal patterns properly and to designate the maximum nodal density of each pattern. After those simple operations by the user, the system places the chosen nodal patterns automatically in an analysis domain and on its boundary, and connects them smoothly by the fuzzy knowledge processing technique. Then triangular or tetrahedral elements are generated by means of the advancing front method. The key issue of the present algorithm is an easy control of complex two- or three-dimensional nodal density distribution by means of the fuzzy knowledge processing technique. To demonstrate fundamental performances of the present algorithm, a prototype system was constructed with one of object-oriented languages, Smalltalk-80 on a 32-bit microcomputer, Macintosh II. The mesh generation of several two- and three-dimensional domains with cracks, holes and junctions was presented as examples.

A LISP-Ada connection

NASA Technical Reports Server (NTRS)

Jaworski, Allan; Lavallee, David; Zoch, David

1987-01-01

The prototype demonstrates the feasibility of using Ada for expert systems and the implementation of an expert-friendly interface which supports knowledge entry. In the Ford LISP-Ada Connection (FLAC) system LISP and Ada are used in ways which complement their respective capabilities. Future investigation will concentrate on the enhancement of the expert knowledge entry/debugging interface and on the issues associated with multitasking and real-time expert systems implementation in Ada.

MOORE: A prototype expert system for diagnosing spacecraft problems

NASA Technical Reports Server (NTRS)

Howlin, Katherine; Weissert, Jerry; Krantz, Kerry

1988-01-01

MOORE is a rule-based, prototype expert system that assists in diagnosing operational Tracking and Data Relay Satellite (TDRS) problems. It is intended to assist spacecraft engineers at the TDRS ground terminal in trouble shooting problems that are not readily solved with routine procedures, and without expert counsel. An additional goal of the prototype system is to develop in-house expert system and knowledge engineering skills. The prototype system diagnoses antenna pointing and earth pointing problems that may occur within the TDRS Attitude Control System (ACS). Plans include expansion to fault isolation of problems in the most critical subsystems of the TDRS spacecraft. Long term benefits are anticipated with use of an expert system during future TDRS programs with increased mission support time, reduced problem solving time, and retained expert knowledge and experience. Phase 2 of the project is intended to provide NASA the necessary expertise and capability to define requirements, evaluate proposals, and monitor the development progress of a highly competent expert system for NASA's Tracking Data Relay Satellite. Phase 2 also envisions addressing two unexplored applications for expert systems, spacecraft integration and tests (I and T) and support to launch activities. The concept, goals, domain, tools, knowledge acquisition, developmental approach, and design of the expert system. It will explain how NASA obtained the knowledge and capability to develop the system in-house without assistance from outside consultants. Future plans will also be presented.

Pedagogical Content Knowledge of Experts and Novices--What Knowledge Do They Activate When Analyzing Science Lessons?

ERIC Educational Resources Information Center

Krepf, Matthias; Plöger, Wilfried; Scholl, Daniel; Seifert, Andreas

2018-01-01

In the current debate on pedagogical content knowledge (PCK), the term is used to refer to the context-specific knowledge that teachers activate when reflecting on practice. Against the background of this debate, we conducted an empirical study and sought to answer the question of which knowledge experts and novices activated in assessing a…

Global Dynamic Exposure and the OpenBuildingMap - Communicating Risk and Involving Communities

NASA Astrophysics Data System (ADS)

Schorlemmer, Danijel; Beutin, Thomas; Hirata, Naoshi; Hao, Ken; Wyss, Max; Cotton, Fabrice; Prehn, Karsten

2017-04-01

Detailed understanding of local risk factors regarding natural catastrophes requires in-depth characterization of the local exposure. Current exposure capture techniques have to find the balance between resolution and coverage. We aim at bridging this gap by employing a crowd-sourced approach to exposure capturing, focusing on risk related to earthquake hazard. OpenStreetMap (OSM), the rich and constantly growing geographical database, is an ideal foundation for this task. More than 3.5 billion geographical nodes, more than 200 million building footprints (growing by 100'000 per day), and a plethora of information about school, hospital, and other critical facilities allows us to exploit this dataset for risk-related computations. We are combining the strengths of crowd-sourced data collection with the knowledge of experts in extracting the most information from these data. Besides relying on the very active OpenStreetMap community and the Humanitarian OpenStreetMap Team, which are collecting building information at high pace, we are providing a tailored building capture tool for mobile devices. This tool is facilitating simple and fast building property capturing for OpenStreetMap by any person or interested community. With our OpenBuildingMap system, we are harvesting this dataset by processing every building in near-realtime. We are collecting exposure and vulnerability indicators from explicitly provided data (e.g. hospital locations), implicitly provided data (e.g. building shapes and positions), and semantically derived data, i.e. interpretation applying expert knowledge. The expert knowledge is needed to translate the simple building properties as captured by OpenStreetMap users into vulnerability and exposure indicators and subsequently into building classifications as defined in the Building Taxonomy 2.0 developed by the Global Earthquake Model (GEM) and the European Macroseismic Scale (EMS98). With this approach, we increase the resolution of existing exposure models from aggregated exposure information to building-by-building vulnerability. We report on our method, on the software development for the mobile application and the server-side analysis system, and on the OpenBuildingMap (www.openbuildingmap.org), our global Tile Map Service focusing on building properties. The free/open framework we provide can be used on commodity hardware for local to regional exposure capturing, for stakeholders in disaster management and mitigation for communicating risk, and for communities to understand their risk.

Strategies for adding adaptive learning mechanisms to rule-based diagnostic expert systems

NASA Technical Reports Server (NTRS)

Stclair, D. C.; Sabharwal, C. L.; Bond, W. E.; Hacke, Keith

1988-01-01

Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output. The primary objective of such expert systems is to provide accurate and comprehensive advice which can be used to help return the space system in question to nominal operation. The development and maintenance of diagnostic expert systems is time and labor intensive since the services of both knowledge engineer(s) and domain expert(s) are required. The use of adaptive learning mechanisms to increment evaluate and refine rules promises to reduce both time and labor costs associated with such systems. This paper describes the basic adaptive learning mechanisms of strengthening, weakening, generalization, discrimination, and discovery. Next basic strategies are discussed for adding these learning mechanisms to rule-based diagnostic expert systems. These strategies support the incremental evaluation and refinement of rules in the knowledge base by comparing the set of advice given by the expert system (A) with the correct diagnosis (C). Techniques are described for selecting those rules in the in the knowledge base which should participate in adaptive learning. The strategies presented may be used with a wide variety of learning algorithms. Further, these strategies are applicable to a large number of rule-based diagnostic expert systems. They may be used to provide either immediate or deferred updating of the knowledge base.

Narratives of change and reform processes: global and local transactions in French psychiatric hospital reform after the Second World War.

PubMed

Henckes, Nicolas

2009-02-01

As with the rest of biomedicine, psychiatry has, since the Second World War, developed under the strong influence of the transnational accumulation of a whole series of practices and knowledge. Anthropology has taught us to pay attention to the transactions between local-level actors and those operating at the global level in the construction of this new world of medicine. This article examines the role played by the recommendations of the WHO Expert Committee of Mental Health in the reform of the French mental health system during the 1950s. Rooted in the experience of practitioners and administrators participating in the process of reforming local psychiatric systems, the recommendations of the WHO Expert Committee developed a new vision of regulating psychiatry, based on professionalism and an idea of a normativity of the doctor-patient relation. This article shows how, by mobilizing the WHO reports' recommendations, French administrators and doctors succeeded in creating a typically French object: "the psychiatric sector", founded on elaborating a new mandate for the psychiatric profession. The article thus questions the deinstitutionalization model as an explanation of transformations of the structure of the French psychiatry system in the post-war period.

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.

Research and development for Onboard Navigation (ONAV) ground based expert/trainer system: ONAV entry knowledge requirements specification update

NASA Technical Reports Server (NTRS)

Bochsler, Daniel C.

1988-01-01

A revised version of expert knowledge for the onboard navigation (ONAV) entry system is given. Included is some brief background information together with information describing the knowledge that the system does contain.

Bridging Research and Environmental Regulatory Processes: The Role of Knowledge Brokers

PubMed Central

Pennell, Kelly G.; Thompson, Marcella; Rice, James W.; Senier, Laura; Brown, Phil; Suuberg, Eric

2013-01-01

Federal funding agencies increasingly require research investigators to ensure that federally-sponsored research demonstrates broader societal impact. Specifically, the National Institutes of Environmental Health Sciences (NIEHS) Superfund Research Program (SRP) requires research centers to include research translation and community engagement cores to achieve broader impacts, with special emphasis on improving environmental health policies through better scientific understanding. This paper draws on theoretical insights from the social sciences to show how incorporating knowledge brokers in research centers can facilitate translation of scientific expertise to influence regulatory processes and thus promote public health. Knowledge brokers connect academic researchers with decision-makers, to facilitate the translation of research findings into policies and programs. In this article, we describe the stages of the regulatory process and highlight the role of the knowledge broker and scientific expert at each stage. We illustrate the cooperation of knowledge brokers, scientific experts and policymakers using a case from the Brown University (Brown) SRP. We show how the Brown SRP incorporated knowledge brokers to engage scientific experts with regulatory officials around the emerging public health problem of vapor intrusion. In the Brown SRP, the knowledge broker brought regulatory officials into the research process, to help scientific experts understand the critical nature of this emerging public health threat, and helped scientific experts develop a research agenda that would inform the development of timely measures to protect public health. Our experience shows that knowledge brokers can enhance the impact of environmental research on public health by connecting policy decision-makers with scientific experts at critical points throughout the regulatory process. PMID:24083557

Harnessing expert knowledge: Defining a Bayesian network decision model with limited data-Model structure for the vibration qualification problem

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

Rizzo, Davinia B.; Blackburn, Mark R.

As systems become more complex, systems engineers rely on experts to inform decisions. There are few experts and limited data in many complex new technologies. This challenges systems engineers as they strive to plan activities such as qualification in an environment where technical constraints are coupled with the traditional cost, risk, and schedule constraints. Bayesian network (BN) models provide a framework to aid systems engineers in planning qualification efforts with complex constraints by harnessing expert knowledge and incorporating technical factors. By quantifying causal factors, a BN model can provide data about the risk of implementing a decision supplemented with informationmore » on driving factors. This allows a systems engineer to make informed decisions and examine “what-if” scenarios. This paper discusses a novel process developed to define a BN model structure based primarily on expert knowledge supplemented with extremely limited data (25 data sets or less). The model was developed to aid qualification decisions—specifically to predict the suitability of six degrees of freedom (6DOF) vibration testing for qualification. The process defined the model structure with expert knowledge in an unbiased manner. Finally, validation during the process execution and of the model provided evidence the process may be an effective tool in harnessing expert knowledge for a BN model.« less

Harnessing expert knowledge: Defining a Bayesian network decision model with limited data-Model structure for the vibration qualification problem

DOE PAGES

Rizzo, Davinia B.; Blackburn, Mark R.

2018-03-30

As systems become more complex, systems engineers rely on experts to inform decisions. There are few experts and limited data in many complex new technologies. This challenges systems engineers as they strive to plan activities such as qualification in an environment where technical constraints are coupled with the traditional cost, risk, and schedule constraints. Bayesian network (BN) models provide a framework to aid systems engineers in planning qualification efforts with complex constraints by harnessing expert knowledge and incorporating technical factors. By quantifying causal factors, a BN model can provide data about the risk of implementing a decision supplemented with informationmore » on driving factors. This allows a systems engineer to make informed decisions and examine “what-if” scenarios. This paper discusses a novel process developed to define a BN model structure based primarily on expert knowledge supplemented with extremely limited data (25 data sets or less). The model was developed to aid qualification decisions—specifically to predict the suitability of six degrees of freedom (6DOF) vibration testing for qualification. The process defined the model structure with expert knowledge in an unbiased manner. Finally, validation during the process execution and of the model provided evidence the process may be an effective tool in harnessing expert knowledge for a BN model.« less

A knowledge authoring tool for clinical decision support.

PubMed

Dunsmuir, Dustin; Daniels, Jeremy; Brouse, Christopher; Ford, Simon; Ansermino, J Mark

2008-06-01

Anesthesiologists in the operating room are unable to constantly monitor all data generated by physiological monitors. They are further distracted by clinical and educational tasks. An expert system would ideally provide assistance to the anesthesiologist in this data-rich environment. Clinical monitoring expert systems have not been widely adopted, as traditional methods of knowledge encoding require both expert medical and programming skills, making knowledge acquisition difficult. A software application was developed for use as a knowledge authoring tool for physiological monitoring. This application enables clinicians to create knowledge rules without the need of a knowledge engineer or programmer. These rules are designed to provide clinical diagnosis, explanations and treatment advice for optimal patient care to the clinician in real time. By intelligently combining data from physiological monitors and demographical data sources the expert system can use these rules to assist in monitoring the patient. The knowledge authoring process is simplified by limiting connective relationships between rules. The application is designed to allow open collaboration between communities of clinicians to build a library of rules for clinical use. This design provides clinicians with a system for parameter surveillance and expert advice with a transparent pathway of reasoning. A usability evaluation demonstrated that anesthesiologists can rapidly develop useful rules for use in a predefined clinical scenario.

Knowledge acquisition for a simple expert controller

NASA Technical Reports Server (NTRS)

Bieker, B.

1987-01-01

A method is presented for process control which has the properties of being incremental, cyclic and top-down. It is described on the basis of the development of an expert controller for a simple, but nonlinear control route. A quality comparison between expert controller and process operator shows the ability of the method for knowledge acquisition.

An Expert System for Designing Fire Prescriptions

Treesearch

Elizabeth Reinhardt

1987-01-01

Managers use prescribed fire to accomplish a variety of resource objectives. The knowledge needed to design successful prescriptions is both quantitative and qualitative. Some of it is available through publications and computer programs, but much of the knowledge of expert practitioners has never been collected or published. An expert system being developed at the,...

Public engagement with CCS: barriers, key issues and ways forward

NASA Astrophysics Data System (ADS)

Xenias, Dimitrios

2017-04-01

Although Carbon Capture and Storage (CCS) is recognised as a crucial transition technology to a low-carbon world, it has not been popular with the public or some governments (e.g. the UK). Also, despite its use in industrial processes for decades, CCS remains and unfamiliar technology for most publics. It is therefore important to foster top-down and bottom-up acceptance of large scale CCS. In an exploratory round of interviews we canvassed the views of British, Dutch, German and Norwegian experts (N=13) with previous experience in public engagement with CCS. They identified barriers and drivers for CCS deployment and public engagement with CCS. Thematic analysis revealed a small number of recurrent issues, including: (a) lack of political leadership on CCS; (b) lack of public knowledge on relevant technologies and (c) difficulty communicating why CCS is necessary. Emphasis on these barriers varied with the level of experts' engagement with the public. More interestingly, although most experts agreed on the importance of public engagement, their views divided between 'why' engage and 'how' best to do this. In a subsequent expert survey (N=99) interview findings were reinforced: public support was seen as important for CCS roll-out (72%), though lower than political support and funding. The survey also showed that local public was expected to experience most risks, while global public will experience most benefits; whereas local business is seen to benefit more than global. Experts were overwhelmingly positive about CCS - risks outweigh benefits, and are confident that CCS will play a major role in climate change mitigation (along with reduced energy demand and renewables). These findings will be expanded on and triangulated in a follow-up public survey which will benefit those involved with public engagement with CCS.

Learning processes in the professional development of mental health counselors: knowledge restructuring and illness script formation.

PubMed

Strasser, Josef; Gruber, Hans

2015-05-01

An important part of learning processes in the professional development of counselors is the integration of declarative knowledge and professional experience. It was investigated in-how-far mental health counselors at different levels of expertise (experts, intermediates, novices) differ in their availability of experience-based knowledge structures. Participants were prompted with 20 client problems. They had to explain those problems, the explanations were analyzed using think-aloud protocols. The results show that experts' knowledge is organized in script-like structures that integrate declarative knowledge and professional experience and help experts in accessing relevant information about cases. Novices revealed less integrated knowledge structures. It is concluded that knowledge restructuring and illness script formation are crucial parts of the professional learning of counselors.

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.

PCLIPS

NASA Technical Reports Server (NTRS)

Krolak, Patrick D.

1990-01-01

CLIPS is an expert system, created specifically to allow rapid implementation of an expert system. CLIPS is written in C, and thus needs a very small amount of memory to run. Parallel CLIPS (PCLIPS) is an extension to CLIPS which is intended to be used in situations where a group of expert systems are expected to run simultaneously and occasionally communicate with each other on an integrated network. PCLIPS is a coarse-grained data distribution system. Its main goal is to take information in one knowledge base and distribute it to other knowledge bases so that all the executing expert systems are able to use that knowledge to solve their disparate problems.

Eyes on the prize: reflections on the impact of the evolving digital ecology on the librarian as expert intermediary and knowledge coach, 1969-2009.

PubMed

Homan, J Michael

2010-01-01

The 2009 Janet Doe Lecture reflects on the continuing value and increasing return on investment of librarian-mediated services in the constantly evolving digital ecology and complex knowledge environment of the health sciences. The interrelationship of knowledge, decision making based on knowledge, technology used to access and retrieve knowledge, and the important linkage roles of expert librarian intermediaries is examined. Professional experiences from 1969 to 2009, occurring during a time of unprecedented changes in the digital ecology of librarianship, are the base on which the evolving role and value of librarians as knowledge coaches and expert intermediaries are examined. Librarian-mediated services linking knowledge and critical decision making in health care have become more valuable than ever as technology continues to reshape an increasingly complex knowledge environment.

An Approach for Externalization of Expert Tacit Knowledge Using a Query Management System in an E-Learning Environment

ERIC Educational Resources Information Center

Khan, Abdul Azeez; Khader, Sheik Abdul

2014-01-01

E-learning or electronic learning platforms facilitate delivery of the knowledge spectrum to the learning community through information and communication technologies. The transfer of knowledge takes place from experts to learners, and externalization of the knowledge transfer is significant. In the e-learning environment, the learners seek…

An application of object-oriented knowledge representation to engineering expert systems

NASA Technical Reports Server (NTRS)

Logie, D. S.; Kamil, H.; Umaretiya, J. R.

1990-01-01

The paper describes an object-oriented knowledge representation and its application to engineering expert systems. The object-oriented approach promotes efficient handling of the problem data by allowing knowledge to be encapsulated in objects and organized by defining relationships between the objects. An Object Representation Language (ORL) was implemented as a tool for building and manipulating the object base. Rule-based knowledge representation is then used to simulate engineering design reasoning. Using a common object base, very large expert systems can be developed, comprised of small, individually processed, rule sets. The integration of these two schemes makes it easier to develop practical engineering expert systems. The general approach to applying this technology to the domain of the finite element analysis, design, and optimization of aerospace structures is discussed.

Interactive knowledge discovery with the doctor-in-the-loop: a practical example of cerebral aneurysms research.

PubMed

Girardi, Dominic; Küng, Josef; Kleiser, Raimund; Sonnberger, Michael; Csillag, Doris; Trenkler, Johannes; Holzinger, Andreas

2016-09-01

Established process models for knowledge discovery find the domain-expert in a customer-like and supervising role. In the field of biomedical research, it is necessary to move the domain-experts into the center of this process with far-reaching consequences for both their research output and the process itself. In this paper, we revise the established process models for knowledge discovery and propose a new process model for domain-expert-driven interactive knowledge discovery. Furthermore, we present a research infrastructure which is adapted to this new process model and demonstrate how the domain-expert can be deeply integrated even into the highly complex data-mining process and data-exploration tasks. We evaluated this approach in the medical domain for the case of cerebral aneurysms research.

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.

Creating a quality-improvement dialogue: utilizing knowledge from frontline staff, managers, and experts to foster health care quality improvement.

PubMed

Parker, Louise E; Kirchner, JoAnn E; Bonner, Laura M; Fickel, Jacqueline J; Ritchie, Mona J; Simons, Carol E; Yano, Elizabeth M

2009-02-01

There is a growing consensus that a hybrid of two common approaches to quality improvement (QI), local participatory QI and expert QI, might be the best method for achieving quality care. Achieving such a hybrid requires that content experts establish an ongoing dialogue with both frontline staff members and managers. In this study we examined frontline staff members' and managers' preferences regarding how to conduct such a dialogue, and we provide practical suggestions for implementation. The two groups shared a number of preferences (e.g., verbal face-to-face exchanges, discussions focused on quality of care). There were also some differences. For example, although managers were interested in discussions of business aspects (e.g., costs), frontline staff members were concerned with workload issues. Finally, although informants acknowledged that engaging in a QI dialogue was time consuming, they also believed it was essential if health care organizations are to improve the quality of care they provide.

TARGET's role in knowledge acquisition, engineering, validation, and documentation

NASA Technical Reports Server (NTRS)

Levi, Keith R.

1994-01-01

We investigate the use of the TARGET task analysis tool for use in the development of rule-based expert systems. We found TARGET to be very helpful in the knowledge acquisition process. It enabled us to perform knowledge acquisition with one knowledge engineer rather than two. In addition, it improved communication between the domain expert and knowledge engineer. We also found it to be useful for both the rule development and refinement phases of the knowledge engineering process. Using the network in these phases required us to develop guidelines that enabled us to easily translate the network into production rules. A significant requirement for TARGET remaining useful throughout the knowledge engineering process was the need to carefully maintain consistency between the network and the rule representations. Maintaining consistency not only benefited the knowledge engineering process, but also has significant payoffs in the areas of validation of the expert system and documentation of the knowledge in the system.

Knowledge Engineering (Or, Catching Black Cats in Dark Rooms).

ERIC Educational Resources Information Center

Ruyle, Kim E.

1993-01-01

Discusses knowledge engineering, its relationship to artificial intelligence, and possible applications to developing expert systems, job aids, and technical training. The educational background of knowledge engineers is considered; the role of subject matter experts is described; and examples of flow charts, lists, and pictorial representations…

Artificial Intelligence, Expert Systems, Natural Language Interfaces, Knowledge Engineering and the Librarian.

ERIC Educational Resources Information Center

Davies, Jim

This paper begins by examining concepts of artificial intelligence (AI) and discusses various definitions of the concept that have been suggested in the literature. The nesting relationship of expert systems within the broader framework of AI is described, and expert systems are characterized as knowledge-based systems (KBS) which attempt to solve…

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.

Intrusion Detection Systems with Live Knowledge System

DTIC Science & Technology

2016-05-31

Ripple -down Rule (RDR) to maintain the knowledge from human experts with knowledge base generated by the Induct RDR, which is a machine-learning based RDR...propose novel approach that uses Ripple -down Rule (RDR) to maintain the knowledge from human experts with knowledge base generated by the Induct RDR...detection model by applying Induct RDR approach. The proposed induct RDR ( Ripple Down Rules) approach allows to acquire the phishing detection

Elicitation of neurological knowledge with argument-based machine learning.

PubMed

Groznik, Vida; Guid, Matej; Sadikov, Aleksander; Možina, Martin; Georgiev, Dejan; Kragelj, Veronika; Ribarič, Samo; Pirtošek, Zvezdan; Bratko, Ivan

2013-02-01

The paper describes the use of expert's knowledge in practice and the efficiency of a recently developed technique called argument-based machine learning (ABML) in the knowledge elicitation process. We are developing a neurological decision support system to help the neurologists differentiate between three types of tremors: Parkinsonian, essential, and mixed tremor (comorbidity). The system is intended to act as a second opinion for the neurologists, and most importantly to help them reduce the number of patients in the "gray area" that require a very costly further examination (DaTSCAN). We strive to elicit comprehensible and medically meaningful knowledge in such a way that it does not come at the cost of diagnostic accuracy. To alleviate the difficult problem of knowledge elicitation from data and domain experts, we used ABML. ABML guides the expert to explain critical special cases which cannot be handled automatically by machine learning. This very efficiently reduces the expert's workload, and combines expert's knowledge with learning data. 122 patients were enrolled into the study. The classification accuracy of the final model was 91%. Equally important, the initial and the final models were also evaluated for their comprehensibility by the neurologists. All 13 rules of the final model were deemed as appropriate to be able to support its decisions with good explanations. The paper demonstrates ABML's advantage in combining machine learning and expert knowledge. The accuracy of the system is very high with respect to the current state-of-the-art in clinical practice, and the system's knowledge base is assessed to be very consistent from a medical point of view. This opens up the possibility to use the system also as a teaching tool. Copyright © 2012 Elsevier B.V. All rights reserved.

Accessing local knowledge to identify where species of conservation concern occur in a tropical forest landscape.

PubMed

Padmanaba, Michael; Sheil, Douglas; Basuki, Imam; Liswanti, Nining

2013-08-01

Conventional biodiversity surveys play an important role in ensuring good conservation friendly management in tropical forest regions but are demanding in terms of expertise, time, and budget. Can local people help? Here, we illustrate how local knowledge can support low cost conservation surveys. We worked in the Malinau watershed, East Kalimantan, Indonesia, an area currently at risk of extensive forest loss. We selected eight species of regional conservation interest: rafflesia (Rafflesia spp.), black orchid (Coelogyne pandurata), sun bear (Helarctos malayanus), tarsier (Tarsius bancanus), slow loris (Nycticebus coucang), proboscis monkey (Nasalis larvatus), clouded leopard (Neofelis diardi/N. nebulosa), and orang-utan (Pongo pygmaeus). We asked 52 informants in seven villages if, where and when they had observed these species. We used maps, based on both geo-referenced and sketched features, to record these observations. Verification concerns and related issues are discussed. Evaluations suggest our local information is reliable. Our study took 6 weeks and cost about USD 5000. Extensive expert based field surveys across the same region would cost one or two orders of magnitude more. The records extend the known distribution for sun bear, tarsier, slow loris, and clouded leopard. Reports of rafflesia, proboscis monkey, and orang-utan are of immediate conservation significance. While quality concerns should never be abandoned, we conclude that local people can help expand our knowledge of large areas in an effective, reliable, and low cost manner and thus contribute to improved management.

Hemispheric Activation Differences in Novice and Expert Clinicians during Clinical Decision Making

ERIC Educational Resources Information Center

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

2016-01-01

Clinical decision making requires knowledge, experience and analytical/non-analytical types of decision processes. As clinicians progress from novice to expert, research indicates decision-making becomes less reliant on foundational biomedical knowledge and more on previous experience. In this study, we investigated how knowledge and experience…

A Logical Framework for Service Migration Based Survivability

DTIC Science & Technology

2016-06-24

platforms; Service Migration Strategy Fuzzy Inference System Knowledge Base Fuzzy rules representing domain expert knowledge about implications of...service migration strategy. Our approach uses expert knowledge as linguistic reasoning rules and takes service programs damage assessment, service...programs complexity, and available network capability as input. The fuzzy inference system includes four components as shown in Figure 5: (1) a knowledge

The Advantages of Abstract Control Knowledge in Expert System Design. Technical Report #7.

ERIC Educational Resources Information Center

Clancey, William J.

This paper argues that an important design principle for building expert systems is to represent all control knowledge abstractly and separately from the domain knowledge upon which it operates. Abstract control knowledge is defined as the specifications of when and how a program is to carry out its operations, such as pursuing a goal, focusing,…

Supplemental knowledge acquisition through external product interface for CLIPS

NASA Technical Reports Server (NTRS)

Saito, Tim; Ebaud, Stephen; Loftin, Bowen R.

1990-01-01

Traditionally, the acquisition of knowledge for expert systems consisted of the interview process with the domain or subject matter expert (SME), observation of domain environment, and information gathering and research which constituted a direct form of knowledge acquisition (KA). The knowledge engineer would be responsible for accumulating pertinent information and/or knowledge from the SME(s) for input into the appropriate expert system development tool. The direct KA process may (or may not) have included forms of data or documentation to incorporate from the SME's surroundings. The differentiation between direct KA and supplemental KA (indirect) would be the difference in the use of data. In acquiring supplemental knowledge, the knowledge engineer would access other types of evidence (manuals, documents, data files, spreadsheets, etc.) that would support the reasoning or premises of the SME. When an expert makes a decision in a particular task, one tool that may have been used to justify a recommendation, would have been a spreadsheet total or column figure. Locating specific decision points from that data within the SME's framework would constitute supplemental KA. Data used for a specific purpose in one system or environment would be used as supplemental knowledge for another, specifically a CLIPS project.

Eyes on the prize: reflections on the impact of the evolving digital ecology on the librarian as expert intermediary and knowledge coach, 1969–2009*

PubMed Central

Homan, J. Michael

2010-01-01

Objective: The 2009 Janet Doe Lecture reflects on the continuing value and increasing return on investment of librarian-mediated services in the constantly evolving digital ecology and complex knowledge environment of the health sciences. Setting: The interrelationship of knowledge, decision making based on knowledge, technology used to access and retrieve knowledge, and the important linkage roles of expert librarian intermediaries is examined. Methodology: Professional experiences from 1969 to 2009, occurring during a time of unprecedented changes in the digital ecology of librarianship, are the base on which the evolving role and value of librarians as knowledge coaches and expert intermediaries are examined. Conclusion: Librarian-mediated services linking knowledge and critical decision making in health care have become more valuable than ever as technology continues to reshape an increasingly complex knowledge environment. PMID:20098655

Examing nursing students' understanding of the cardiovascular system in a BSN program

NASA Astrophysics Data System (ADS)

Stuart, Parker Emerson

This study investigated the alignment of important cardiovascular system (CVS) concepts identified by expert nurses with nursing student's knowledge. Specifically, it focused on the prevalence of nursing students' alternative conceptions for these important concepts as a potential reason for a theory-practice gap in nursing (Corlett, 2000; Jordan, 1994). This is the first study to target nursing student alternative conceptions exclusively whereas other studies focused on diverse groups of undergraduates' CVS knowledge (Michael et al., 2002). The study was divided into two phases and used a case study approach with each phase of the study representing a single case. The first phase of the study sought to understand what CVS concepts expert nurses deemed relevant to their daily practice and how these experts used these concepts. The second phase identified nursing student alternative conceptions through the use of open-ended scenarios based on the results of phase I. For the first phase of the study involved four CVS expert nurses practicing in emergency rooms and cardiac intensive care units at two local hospitals. Interviews were used to elicit important CVS concepts. The expert nurses identified five broad concepts as important to their practice. These concepts were a) cardiovascular anatomical concepts; b) cardiovascular physiological concepts; c) homeostasis and diseases of the CVS; d) the interdependence and interaction of the CVS with other organ systems and e) the intersection of the CVS and technology in patient diagnosis and treatment. These finding reinforce concepts already being taught to nursing students but also suggest that instruction should focus more on how the CVS interacts with other organ systems and how technology and the CVS interact. The presence of alternative conceptions in the nursing students was examined through the use of open-ended questions. A total of 17 students fully completed the scenario questions. Results indicate that this group of nursing students hold some CVS alternative conceptions. Overall, the alternative conceptions can be grouped into four categories: a) CVS anatomy, b) blood flow and pressure, c) anthropomorphic views and d) miscellaneous alternative conceptions. These findings suggest there is indeed a misalignment between expert nurses' and nursing students' knowledge of the CVS with this misalignment potentially contributing to the theory-practice gap.

Knowledge acquisition and representation for the Systems Test and Operations Language (STOL) Intelligent Tutoring System (ITS)

NASA Technical Reports Server (NTRS)

Seamster, Thomas L.; Eike, David R.; Ames, Troy J.

1990-01-01

This presentation concentrates on knowledge acquisition and its application to the development of an expert module and a user interface for an Intelligent Tutoring System (ITS). The Systems Test and Operations Language (STOL) ITS is being developed to assist NASA control center personnel in learning a command and control language as it is used in mission operations rooms. The objective of the tutor is to impart knowledge and skills that will permit the trainee to solve command and control problems in the same way that the STOL expert solves those problems. The STOL ITS will achieve this object by representing the solution space in such a way that the trainee can visualize the intermediate steps, and by having the expert module production rules parallel the STOL expert's knowledge structures.

An expert system for choosing the best combination of options in a general purpose program for automated design synthesis

NASA Technical Reports Server (NTRS)

Rogers, J. L.; Barthelemy, J.-F. M.

1986-01-01

An expert system called EXADS has been developed to aid users of the Automated Design Synthesis (ADS) general purpose optimization program. ADS has approximately 100 combinations of strategy, optimizer, and one-dimensional search options from which to choose. It is difficult for a nonexpert to make this choice. This expert system aids the user in choosing the best combination of options based on the users knowledge of the problem and the expert knowledge stored in the knowledge base. The knowledge base is divided into three categories; constrained problems, unconstrained problems, and constrained problems being treated as unconstrained problems. The inference engine and rules are written in LISP, contains about 200 rules, and executes on DEC-VAX (with Franz-LISP) and IBM PC (with IQ-LISP) computers.

Desiderata for product labeling of medical expert systems.

PubMed

Geissbühler, A; Miller, R A

1997-12-01

The proliferation and increasing complexity of medical expert systems raise ethical and legal concerns about the ability of practitioners to protect their patients from defective or misused software. Appropriate product labeling of expert systems can help clinical users to understand software indications and limitations. Mechanisms of action and knowledge representation schema should be explained in layperson's terminology. User qualifications and resources available for acquiring the skills necessary to understand and critique the system output should be listed. The processes used for building and maintaining the system's knowledge base are key determinants of the product's quality, and should be carefully documented. To meet these desiderata, a printed label is insufficient. The authors suggest a new, more active, model of product labeling for medical expert systems that involves embedding 'knowledge of the knowledge base', creating user-specific data, and sharing global information using the Internet.

A Semiautomated Framework for Integrating Expert Knowledge into Disease Marker Identification

DOE PAGES

Wang, Jing; Webb-Robertson, Bobbie-Jo M.; Matzke, Melissa M.; ...

2013-01-01

Background . The availability of large complex data sets generated by high throughput technologies has enabled the recent proliferation of disease biomarker studies. However, a recurring problem in deriving biological information from large data sets is how to best incorporate expert knowledge into the biomarker selection process. Objective . To develop a generalizable framework that can incorporate expert knowledge into data-driven processes in a semiautomated way while providing a metric for optimization in a biomarker selection scheme. Methods . The framework was implemented as a pipeline consisting of five components for the identification of signatures from integrated clustering (ISIC). Expertmore » knowledge was integrated into the biomarker identification process using the combination of two distinct approaches; a distance-based clustering approach and an expert knowledge-driven functional selection. Results . The utility of the developed framework ISIC was demonstrated on proteomics data from a study of chronic obstructive pulmonary disease (COPD). Biomarker candidates were identified in a mouse model using ISIC and validated in a study of a human cohort. Conclusions . Expert knowledge can be introduced into a biomarker discovery process in different ways to enhance the robustness of selected marker candidates. Developing strategies for extracting orthogonal and robust features from large data sets increases the chances of success in biomarker identification.« less

Local ecological knowledge and its relationship with biodiversity conservation among two Quilombola groups living in the Atlantic Rainforest, Brazil

PubMed Central

Ticktin, Tamara; Fonseca, Amanda Surerus; Macedo, Arthur Ladeira; Orsi, Timothy Ongaro; Chedier, Luciana Moreira; Rodrigues, Eliana; Pimenta, Daniel Sales

2017-01-01

Information on the knowledge, uses, and abundance of natural resources in local communities can provide insight on conservation status and conservation strategies in these locations. The aim of this research was to evaluate the uses, knowledge and conservation status of plants in two Quilombolas (descendants of slaves of African origin) communities in the Atlantic rainforest of Brazil, São Sebastião da Boa Vista (SSBV) and São Bento (SB). We used a combination of ethnobotanical and ecological survey methods to ask: 1) What ethnobotanical knowledge do the communities hold? 2) What native species are most valuable to them? 3) What is the conservation status of the native species used? Thirteen local experts described the names and uses of 212 species in SSBV (105 native species) and 221 in SB (96 native species). Shannon Wiener diversity and Pielou’s Equitability indices of ethnobotanical knowledge of species were very high (5.27/0.96 and 5.28/0.96, respectively). Species with the highest cultural significance and use-value indexes in SSBV were Dalbergia hortensis (26/2.14), Eremanthus erythropappus (6.88/1), and Tibouchina granulosa (6.02/1); while Piptadenia gonoacantha (3.32/1), Sparattosperma leucanthum (3.32/1) and Cecropia glaziovii (3.32/0.67) were the highest in SB. Thirty-three native species ranked in the highest conservation priority category at SSBV and 31 at SB. D. hortensis was noteworthy because of its extremely high cultural importance at SSBV, and its categorization as a conservation priority in both communities. This information can be used towards generating sustainable use and conservation plans that are appropriate for the local communities. PMID:29182637

Local ecological knowledge and its relationship with biodiversity conservation among two Quilombola groups living in the Atlantic Rainforest, Brazil.

PubMed

Conde, Bruno Esteves; Ticktin, Tamara; Fonseca, Amanda Surerus; Macedo, Arthur Ladeira; Orsi, Timothy Ongaro; Chedier, Luciana Moreira; Rodrigues, Eliana; Pimenta, Daniel Sales

2017-01-01

Information on the knowledge, uses, and abundance of natural resources in local communities can provide insight on conservation status and conservation strategies in these locations. The aim of this research was to evaluate the uses, knowledge and conservation status of plants in two Quilombolas (descendants of slaves of African origin) communities in the Atlantic rainforest of Brazil, São Sebastião da Boa Vista (SSBV) and São Bento (SB). We used a combination of ethnobotanical and ecological survey methods to ask: 1) What ethnobotanical knowledge do the communities hold? 2) What native species are most valuable to them? 3) What is the conservation status of the native species used? Thirteen local experts described the names and uses of 212 species in SSBV (105 native species) and 221 in SB (96 native species). Shannon Wiener diversity and Pielou's Equitability indices of ethnobotanical knowledge of species were very high (5.27/0.96 and 5.28/0.96, respectively). Species with the highest cultural significance and use-value indexes in SSBV were Dalbergia hortensis (26/2.14), Eremanthus erythropappus (6.88/1), and Tibouchina granulosa (6.02/1); while Piptadenia gonoacantha (3.32/1), Sparattosperma leucanthum (3.32/1) and Cecropia glaziovii (3.32/0.67) were the highest in SB. Thirty-three native species ranked in the highest conservation priority category at SSBV and 31 at SB. D. hortensis was noteworthy because of its extremely high cultural importance at SSBV, and its categorization as a conservation priority in both communities. This information can be used towards generating sustainable use and conservation plans that are appropriate for the local communities.

[Pitfalls in 'orthodox knowledge'].

PubMed

Taneda, Hiroyuki

2003-03-01

Within contemporary society both 'pseudoscience' and 'pseudomedicine' can be found. Such knowledge is seen as incorrect, wrong or irrational. I call them 'unorthodox (uncertain) knowledge'. Conversely, 'orthodox knowledge'--for example, science, medicine, etc.--is seen as correct, right or rational. Some people believe 'unorthodox (uncertain) knowledge'. Experts castigate such people from the standpoint that they lack the basic understanding of 'orthodox knowledge'. That is, experts see the ordinary lay person as subjective, ignorant or irrational (whereas they see themselves as objective, analytical, prudent or rational). But are people ignorant or irrational? The aim of this paper is to examine this question in terms of analyzing the interplay among the characteristics of 'orthodox knowledge', 'unorthodox (uncertain) knowledge' and the nature of people's concerns. Thus, this paper explains that people develop certain situated understandings of 'orthodox knowledge' and/or 'unorthodox (uncertain) knowledge' through their intensive experiences. Also, this paper suggests that people need to rethink or reflect on the good institutions which mediate between people and experts.

Engineering monitoring expert system's developer

NASA Technical Reports Server (NTRS)

Lo, Ching F.

1991-01-01

This research project is designed to apply artificial intelligence technology including expert systems, dynamic interface of neural networks, and hypertext to construct an expert system developer. The developer environment is specifically suited to building expert systems which monitor the performance of ground support equipment for propulsion systems and testing facilities. The expert system developer, through the use of a graphics interface and a rule network, will be transparent to the user during rule constructing and data scanning of the knowledge base. The project will result in a software system that allows its user to build specific monitoring type expert systems which monitor various equipments used for propulsion systems or ground testing facilities and accrues system performance information in a dynamic knowledge base.

Workshop on Measurement Needs for Local-Structure Determination in Inorganic Materials

PubMed Central

Levin, Igor; Vanderah, Terrell

2008-01-01

The functional responses (e.g., dielectric, magnetic, catalytic, etc.) of many industrially-relevant materials are controlled by their local structure—a term that refers to the atomic arrangements on a scale ranging from atomic (sub-nanometer) to several nanometers. Thus, accurate knowledge of local structure is central to understanding the properties of nanostructured materials, thereby placing the problem of determining atomic positions on the nanoscale—the so-called “nanostructure problem”—at the center of modern materials development. Today, multiple experimental techniques exist for probing local atomic arrangements; nonetheless, finding accurate comprehensive, and robust structural solutions for the nanostructured materials still remains a formidable challenge because any one of these methods yields only a partial view of the local structure. The primary goal of this 2-day NIST-sponsored workshop was to bring together experts in the key experimental and theoretical areas relevant to local-structure determination to devise a strategy for the collaborative effort required to develop a comprehensive measurement solution on the local scale. The participants unanimously agreed that solving the nanostructure problem—an ultimate frontier in materials characterization—necessitates a coordinated interdisciplinary effort that transcends the existing capabilities of any single institution, including national laboratories, centers, and user facilities. The discussions converged on an institute dedicated to local structure determination as the most viable organizational platform for successfully addressing the nanostructure problem. The proposed “institute” would provide an intellectual infrastructure for local structure determination by (1) developing and maintaining relevant computer software integrated in an open-source global optimization framework (Fig. 2), (2) connecting industrial and academic users with experts in measurement techniques, (3) developing and maintaining pertinent databases, and (4) providing necessary education and training. PMID:27096131

Rationales of a Shift towards Knowledge Economy in Jordan from the Viewpoint of Educational Experts and Relationship with Some Variables

ERIC Educational Resources Information Center

Al Zboon, Mohammad Saleem; Al Ahmad, Suliman Diab Ali; Al Zboon, Saleem Odeh

2009-01-01

The purpose of the present study was to identify rationales underlying a shift towards knowledge economy in education as perceived by the educational experts in Jordan and relationship with some variables. The random stratum sample (n = 90) consisted of educational experts representing faculty members in the Jordanian universities and top leaders…

Using expert knowledge to incorporate uncertainty in cause-of-death assignments for modeling of cause-specific mortality

USGS Publications Warehouse

Walsh, Daniel P.; Norton, Andrew S.; Storm, Daniel J.; Van Deelen, Timothy R.; Heisy, Dennis M.

2018-01-01

Implicit and explicit use of expert knowledge to inform ecological analyses is becoming increasingly common because it often represents the sole source of information in many circumstances. Thus, there is a need to develop statistical methods that explicitly incorporate expert knowledge, and can successfully leverage this information while properly accounting for associated uncertainty during analysis. Studies of cause-specific mortality provide an example of implicit use of expert knowledge when causes-of-death are uncertain and assigned based on the observer's knowledge of the most likely cause. To explicitly incorporate this use of expert knowledge and the associated uncertainty, we developed a statistical model for estimating cause-specific mortality using a data augmentation approach within a Bayesian hierarchical framework. Specifically, for each mortality event, we elicited the observer's belief of cause-of-death by having them specify the probability that the death was due to each potential cause. These probabilities were then used as prior predictive values within our framework. This hierarchical framework permitted a simple and rigorous estimation method that was easily modified to include covariate effects and regularizing terms. Although applied to survival analysis, this method can be extended to any event-time analysis with multiple event types, for which there is uncertainty regarding the true outcome. We conducted simulations to determine how our framework compared to traditional approaches that use expert knowledge implicitly and assume that cause-of-death is specified accurately. Simulation results supported the inclusion of observer uncertainty in cause-of-death assignment in modeling of cause-specific mortality to improve model performance and inference. Finally, we applied the statistical model we developed and a traditional method to cause-specific survival data for white-tailed deer, and compared results. We demonstrate that model selection results changed between the two approaches, and incorporating observer knowledge in cause-of-death increased the variability associated with parameter estimates when compared to the traditional approach. These differences between the two approaches can impact reported results, and therefore, it is critical to explicitly incorporate expert knowledge in statistical methods to ensure rigorous inference.

The effect of expert knowledge on medical search: medical experts have specialized abilities for detecting serious lesions.

PubMed

Nakashima, Ryoichi; Watanabe, Chisaki; Maeda, Eriko; Yoshikawa, Takeharu; Matsuda, Izuru; Miki, Soichiro; Yokosawa, Kazuhiko

2015-09-01

How does domain-specific knowledge influence the experts' performance in their domain of expertise? Specifically, can visual search experts find, with uniform efficiency, any type of target in their domain of expertise? We examined whether acquired knowledge of target importance influences an expert's visual search performance. In some professional searches (e.g., medical screenings), certain targets are rare; one aim of this study was to examine the extent to which experts miss such targets in their searches. In one experiment, radiologists (medical experts) engaged in a medical lesion search task in which both the importance (i.e., seriousness/gravity) and the prevalence of targets varied. Results showed decreased target detection rates in the low prevalence conditions (i.e., the prevalence effect). Also, experts were better at detecting important (versus unimportant) lesions. Results of an experiment using novices ruled out the possibility that decreased performance with unimportant targets was due to low target noticeability/visibility. Overall, the findings suggest that radiologists do not have a generalized ability to detect any type of lesion; instead, they have acquired a specialized ability to detect only those important lesions relevant for effective medical practices.

Knowledge representation issues for explaining plans

NASA Technical Reports Server (NTRS)

Prince, Mary Ellen; Johannes, James D.

1988-01-01

Explanations are recognized as an important facet of intelligent behavior. Unfortunately, expert systems are currently limited in their ability to provide useful, intelligent justifications of their results. We are currently investigating the issues involved in providing explanation facilities for expert planning systems. This investigation addresses three issues: knowledge content, knowledge representation, and explanation structure.

A Methodology for Multiple Rule System Integration and Resolution Within a Singular Knowledge Base

NASA Technical Reports Server (NTRS)

Kautzmann, Frank N., III

1988-01-01

Expert Systems which support knowledge representation by qualitative modeling techniques experience problems, when called upon to support integrated views embodying description and explanation, especially when other factors such as multiple causality, competing rule model resolution, and multiple uses of knowledge representation are included. A series of prototypes are being developed to demonstrate the feasibility of automating the process of systems engineering, design and configuration, and diagnosis and fault management. A study involves not only a generic knowledge representation; it must also support multiple views at varying levels of description and interaction between physical elements, systems, and subsystems. Moreover, it will involve models of description and explanation for each level. This multiple model feature requires the development of control methods between rule systems and heuristics on a meta-level for each expert system involved in an integrated and larger class of expert system. The broadest possible category of interacting expert systems is described along with a general methodology for the knowledge representation and control of mutually exclusive rule systems.

Use (and abuse) of expert elicitation in support of decision making for public policy

PubMed Central

Morgan, M. Granger

2014-01-01

The elicitation of scientific and technical judgments from experts, in the form of subjective probability distributions, can be a valuable addition to other forms of evidence in support of public policy decision making. This paper explores when it is sensible to perform such elicitation and how that can best be done. A number of key issues are discussed, including topics on which there are, and are not, experts who have knowledge that provides a basis for making informed predictive judgments; the inadequacy of only using qualitative uncertainty language; the role of cognitive heuristics and of overconfidence; the choice of experts; the development, refinement, and iterative testing of elicitation protocols that are designed to help experts to consider systematically all relevant knowledge when they make their judgments; the treatment of uncertainty about model functional form; diversity of expert opinion; and when it does or does not make sense to combine judgments from different experts. Although it may be tempting to view expert elicitation as a low-cost, low-effort alternative to conducting serious research and analysis, it is neither. Rather, expert elicitation should build on and use the best available research and analysis and be undertaken only when, given those, the state of knowledge will remain insufficient to support timely informed assessment and decision making. PMID:24821779

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 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.

Alternative Ultrasound Gel for a Sustainable Ultrasound Program: Application of Human Centered Design.

PubMed

Salmon, Margaret; Salmon, Christian; Bissinger, Alexa; Muller, Mundenga Mutendi; Gebreyesus, Alegnta; Geremew, Haimanot; Wendel, Sarah K; Wendell, Sarah; Azaza, Aklilu; Salumu, Maurice; Benfield, Nerys

2015-01-01

This paper describes design of a low cost, ultrasound gel from local products applying aspects of Human Centered Design methodology. A multidisciplinary team worked with clinicians who use ultrasound where commercial gel is cost prohibitive and scarce. The team followed the format outlined in the Ideo Took Kit. Research began by defining the challenge "how to create locally available alternative ultrasound gel for a low-resourced environment? The "End-Users," were identified as clinicians who use ultrasound in Democratic Republic of the Congo and Ethiopia. An expert group was identified and queried for possible alternatives to commercial gel. Responses included shampoo, oils, water and cornstarch. Cornstarch, while a reasonable solution, was either not available or too expensive. We then sought deeper knowledge of locally sources materials from local experts, market vendors, to develop a similar product. Suggested solutions gleaned from these interviews were collected and used to create ultrasound gel accounting for cost, image quality, manufacturing capability. Initial prototypes used cassava root flour from Great Lakes Region (DRC, Rwanda, Uganda, Tanzania) and West Africa, and bula from Ethiopia. Prototypes were tested in the field and resulting images evaluated by our user group. A final prototype was then selected. Cassava and bula at a 32 part water, 8 part flour and 4 part salt, heated, mixed then cooled was the product design of choice.

Attentional advantages in video-game experts are not related to perceptual tendencies.

PubMed

Wong, Nicole H L; Chang, Dorita H F

2018-04-03

Previous studies have suggested that extensive action video gaming may enhance perceptual and attentional capacities. Here, we probed whether attentional differences between video-game experts and non-experts hold when attention is selectively directed at global or local structures. We measured performance on a modified attentional-blink task using hierarchically structured stimuli that consisted of global and local elements. Stimuli carried congruent or incongruent information. In two experiments, we asked observers to direct their attention globally (Experiment 1) or locally (Experiment 2). In each RSVP trial, observers were asked to identify the identity of an initial target (T1), and detect the presence or absence of a second target (T2). Experts showed a markedly attenuated attentional blink, as quantified by higher T2 detection sensitivity, relative to non-experts, in both global and local tasks. Notably, experts and non-experts were comparably affected by stimulus congruency. We speculate that the observed visuo-attentional advantage is unlikely to be related to mere differences perceptual tendencies (i.e., greater global precedence), which has been previously associated with diminished attentional blink.

Test and Evaluation for Enhanced Security: A Quantitative Method to Incorporate Expert Knowledge into Test Planning Decisions.

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

Rizzo, Davinia; Blackburn, Mark

Complex systems are comprised of technical, social, political and environmental factors as well as the programmatic factors of cost, schedule and risk. Testing these systems for enhanced security requires expert knowledge in many different fields. It is important to test these systems to ensure effectiveness, but testing is limited to due cost, schedule, safety, feasibility and a myriad of other reasons. Without an effective decision framework for Test and Evaluation (T&E) planning that can take into consideration technical as well as programmatic factors and leverage expert knowledge, security in complex systems may not be assessed effectively. Therefore, this paper coversmore » the identification of the current T&E planning problem and an approach to include the full variety of factors and leverage expert knowledge in T&E planning through the use of Bayesian Networks (BN).« less

Knowing Who Knows: Laypersons' Capabilities to Judge Experts' Pertinence for Science Topics.

PubMed

Bromme, Rainer; Thomm, Eva

2016-01-01

Because modern societies are built on elaborate divisions of cognitive labor, individuals remain laypersons in most knowledge domains. Hence, they have to rely on others' expertise when deciding on many science-related issues in private and public life. Even children already locate and discern expertise in the minds of others (e.g., Danovitch & Keil, 2004). This study examines how far university students accurately judge experts' pertinence for science topics even when they lack proficient knowledge of the domain. Participants judged the pertinence of experts from diverse disciplines based on the experts' assumed contributions to texts adapted from original articles from Science and Nature. Subjective pertinence judgments were calibrated by comparing them with bibliometrics of the original articles. Furthermore, participants' general science knowledge was controlled. Results showed that participants made well-calibrated pertinence judgments regardless of their level of general science knowledge. Copyright © 2015 Cognitive Science Society, Inc.

Marketing practitioner’s tacit knowledge acquisition using Repertory Grid Technique (RTG)

NASA Astrophysics Data System (ADS)

Azmi, Afdhal; Adriman, Ramzi

2018-05-01

The tacit knowledge of Marketing practitioner’s experts is excellent resources and priceless. It takes into account their experiential, skill, ideas, belief systems, insight and speculation into management decision-making. This expertise is an individual intuitive judgment and personal shortcuts to complete the work efficiently. Tacit knowledge of Marketing practitioner’s experts is one of best problem solutions in marketing strategy, environmental analysis, product management and partner’s relationship. This paper proposes the acquisition method of tacit knowledge from Marketing practitioner’s using Repertory Grid Technique (RGT). The RGT is a software application for tacit acquisition knowledge to provide a systematic approach to capture and acquire the constructs from an individual. The result shows the understanding of RGT could make TKE and MPE get a good result in capturing and acquiring tacit knowledge of Marketing practitioner’s experts.

Patient engagement in the process of planning and designing outpatient care improvements at the Veterans Administration Health-care System: findings from an online expert panel.

PubMed

Khodyakov, Dmitry; Stockdale, Susan E; Smith, Nina; Booth, Marika; Altman, Lisa; Rubenstein, Lisa V

2017-02-01

There is a strong interest in the Veterans Administration (VA) Health-care System in promoting patient engagement to improve patient care. We solicited expert opinion using an online expert panel system with a modified Delphi structure called ExpertLens ™ . Experts reviewed, rated and discussed eight scenarios, representing four patient engagement roles in designing and improving VA outpatient care (consultant, implementation advisor, equal stakeholder and lead stakeholder) and two VA levels (local and regional). Rating criteria included desirability, feasibility, patient ability, physician/staff acceptance and impact on patient-centredness and care quality. Data were analysed using the RAND/UCLA Appropriateness Method for determining consensus. Experts rated consulting with patients at the local level as the most desirable and feasible patient engagement approach. Engagement at the local level was considered more desirable than engagement at the regional level. Being an equal stakeholder at the local level received the highest ratings on the patient-centredness and health-care quality criteria. Our findings illustrate expert opinion about different approaches to patient engagement and highlight the benefits and challenges posed by each. Although experts rated local consultations with patients on an as-needed basis as most desirable and feasible, they rated being an equal stakeholder at the local level as having the highest potential impact on patient-centredness and care quality. This result highlights a perceived discrepancy between what is most desirable and what is potentially most effective, but suggests that routine local engagement of patients as equal stakeholders may be a desirable first step for promoting high-quality, patient-centred care. © 2016 The Authors. Health Expectations Published by John Wiley & Sons Ltd.

Developing and using expert systems and neural networks in medicine: a review on benefits and challenges.

PubMed

Sheikhtaheri, Abbas; Sadoughi, Farahnaz; Hashemi Dehaghi, Zahra

2014-09-01

Complicacy of clinical decisions justifies utilization of information systems such as artificial intelligence (e.g. expert systems and neural networks) to achieve better decisions, however, application of these systems in the medical domain faces some challenges. We aimed at to review the applications of these systems in the medical domain and discuss about such challenges. Following a brief introduction of expert systems and neural networks by representing few examples, the challenges of these systems in the medical domain are discussed. We found that the applications of expert systems and artificial neural networks have been increased in the medical domain. These systems have shown many advantages such as utilization of experts' knowledge, gaining rare knowledge, more time for assessment of the decision, more consistent decisions, and shorter decision-making process. In spite of all these advantages, there are challenges ahead of developing and using such systems including maintenance, required experts, inputting patients' data into the system, problems for knowledge acquisition, problems in modeling medical knowledge, evaluation and validation of system performance, wrong recommendations and responsibility, limited domains of such systems and necessity of integrating such systems into the routine work flows. We concluded that expert systems and neural networks can be successfully used in medicine; however, there are many concerns and questions to be answered through future studies and discussions.

Knowledge as an Aspect of Scientific Competence for Citizenship: Results of a Delphi Study in Spain

ERIC Educational Resources Information Center

España-Ramos, Enrique; González-García, Francisco José; Blanco-López, Ángel; Franco-Mariscal, Antonio Joaquín

2016-01-01

This article focuses on scientific knowledge as one aspect of the scientific competencies that citizens should ideally possess. The analysis is based on a Delphi study we conducted with Spanish experts from different science-related fields. The results showed that although the experts proposed several examples of scientific knowledge, the degree…

Artificial Intelligence In Computational Fluid Dynamics

NASA Technical Reports Server (NTRS)

Vogel, Alison Andrews

1991-01-01

Paper compares four first-generation artificial-intelligence (Al) software systems for computational fluid dynamics. Includes: Expert Cooling Fan Design System (EXFAN), PAN AIR Knowledge System (PAKS), grid-adaptation program MITOSIS, and Expert Zonal Grid Generation (EZGrid). Focuses on knowledge-based ("expert") software systems. Analyzes intended tasks, kinds of knowledge possessed, magnitude of effort required to codify knowledge, how quickly constructed, performances, and return on investment. On basis of comparison, concludes Al most successful when applied to well-formulated problems solved by classifying or selecting preenumerated solutions. In contrast, application of Al to poorly understood or poorly formulated problems generally results in long development time and large investment of effort, with no guarantee of success.

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

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.

Best practice strategies to safeguard drug prescribing and drug administration: an anthology of expert views and opinions.

PubMed

Seidling, Hanna M; Stützle, Marion; Hoppe-Tichy, Torsten; Allenet, Benoît; Bedouch, Pierrick; Bonnabry, Pascal; Coleman, Jamie J; Fernandez-Llimos, Fernando; Lovis, Christian; Rei, Maria Jose; Störzinger, Dominic; Taylor, Lenka A; Pontefract, Sarah K; van den Bemt, Patricia M L A; van der Sijs, Heleen; Haefeli, Walter E

2016-04-01

While evidence on implementation of medication safety strategies is increasing, reasons for selecting and relinquishing distinct strategies and details on implementation are typically not shared in published literature. We aimed to collect and structure expert information resulting from implementing medication safety strategies to provide advice for decision-makers. Medication safety experts with clinical expertise from thirteen hospitals throughout twelve European and North American countries shared their experience in workshop meetings, on-site-visits and remote structured interviews. We performed an expert-based, in-depth assessment of implementation of best-practice strategies to improve drug prescribing and drug administration. Workflow, variability and recommended medication safety strategies in drug prescribing and drug administration processes. According to the experts, institutions chose strategies that targeted process steps known to be particularly error-prone in the respective setting. Often, the selection was channeled by local constraints such as the e-health equipment and critically modulated by national context factors. In our study, the experts favored electronic prescribing with clinical decision support and medication reconciliation as most promising interventions. They agreed that self-assessment and introduction of medication safety boards were crucial to satisfy the setting-specific differences and foster successful implementation. While general evidence for implementation of strategies to improve medication safety exists, successful selection and adaptation of a distinct strategy requires a thorough knowledge of the institute-specific constraints and an ongoing monitoring and adjustment of the implemented measures.

Exploration of Teaching Skills of Pre-Service High School Teachers' through Self-Regulated Learning Based on Learning Style

ERIC Educational Resources Information Center

Habibi; Kuswanto, Heru; Yanti, Fitri April

2017-01-01

An expert in the field of science is often difficult to teach his knowledge to students. Conversely someone who is expert in the field of education is certainly more expert in transferring knowledge. The purpose of this research is to explore the skill of teaching skill preservice of physics teacher of High School. Samples were taken randomly as…

Developing Expert System for Tuberculosis Diagnose to Support Knowledge Sharing in the Era of National Health Insurance System

NASA Astrophysics Data System (ADS)

Lidya, L.

2017-03-01

National Health Insurance has been implemented since 1st January 2014. A number of new policies have been established including multilevel referral system. The multilevel referral system classified health care center into three levels, it determined that the flow of patient treatment should be started from first level health care center. There are 144 kind of diseases that must be treat in the first level which mainly consists of general physicians. Unfortunately, competence of the physician in the first level may not fulfil the standard competence yet. To improved the physisians knowledge, government has created many events to accelerate knowledge sharing. However, it still needs times and many resources to give significan results. Expert system is kind of software that provide consulting services to non-expert users in accordance with the area of its expertise. It can improved effectivity and efficiency of knowledge sharing and learning. This research was developed a model of TB diagnose expert system which comply with the standard procedure of TB diagnosis and regulation. The proposed expert system has characteristics as follows provide facility to manage multimedia clinical data, supporting the complexity of TB diagnosis (combine rule-based and case-based expert system), interactive interface, good usability, multi-platform, evolutionary.

Expert Seeker

NASA Technical Reports Server (NTRS)

Fernandez, Becerra

2003-01-01

Expert Seeker is a computer program of the knowledge-management-system (KMS) type that falls within the category of expertise-locator systems. The main goal of the KMS system implemented by Expert Seeker is to organize and distribute knowledge of who are the domain experts within and without a given institution, company, or other organization. The intent in developing this KMS was to enable the re-use of organizational knowledge and provide a methodology for querying existing information (including structured, semistructured, and unstructured information) in a way that could help identify organizational experts. More specifically, Expert Seeker was developed to make it possible, by use of an intranet, to do any or all of the following: Assist an employee in identifying who has the skills needed for specific projects and to determine whether the experts so identified are available. Assist managers in identifying employees who may need training opportunities. Assist managers in determining what expertise is lost when employees retire or otherwise leave. Facilitate the development of new ways of identifying opportunities for innovation and minimization of duplicated efforts. Assist employees in achieving competitive advantages through the application of knowledge-management concepts and related systems. Assist external organizations in requesting speakers for specific engagements or determining from whom they might be able to request help via electronic mail. Help foster an environment of collaboration for rapid development in today's environment, in which it is increasingly necessary to assemble teams of experts from government, universities, research laboratories, and industries, to quickly solve problems anytime, anywhere. Make experts more visible. Provide a central repository of information about employees, including information that, heretofore, has typically not been captured by the human-resources systems (e.g., information about past projects, patents, or hobbies). Unify myriad collections of data into Web-enabled repository that could easily be searched for relevant data.

Restoring Consistency In Subjective Information For Groundwater Driven Health Risk Assessment

NASA Astrophysics Data System (ADS)

Ozbek, M. M.; Pinder, G. F.

2004-12-01

In an earlier work (Ozbek and Pinder, 2003), we constructed a fuzzy rule-based knowledge base that uses subjective expert opinion to calculate risk-based design constraints (i.e., dose and pattern of exposure) to sustain the groundwater-driven individual health risk at a desired level. Ideally, our system must be capable to produce for any individual a meaningful risk result or for any given risk a meaningful design constraint, in the sense that the result is neither the empty set nor the whole domain of the variable of interest. Otherwise we consider our system as inconsistent. We present a method based on fuzzy similarity relations to restore consistency in our implicative fuzzy rule based system used for the risk-based groundwater remediation design problem. Both a global and a local approach are considered. Even though straightforward and computationally less demanding, the global approach can affect pieces of knowledge negatively by inducing unwarranted imprecision into the knowledge base. On the other hand, the local approach, given a family of parameterized similarity relations, determines a parameter for each inference such that consistent results are computed which may not be feasible in real time applications of our knowledge base. Several scenarios are considered for comparing the two approaches that suggest that for specific applications one or several approaches ranging from a completely global to a completely local one will be more suitable than others while calculating the design constraints.

Expert systems as applied to bridges : knowledge acquisition phase : final report.

DOT National Transportation Integrated Search

1987-01-01

Presented in this report is a detailed description of the procedure to be followed to develop a knowledge-based computerized expert system for determining whether to rehabilitate, improve, replace, abandon, or just to routinely maintain an old highwa...

Space shuttle main engine anomaly data and inductive knowledge based systems: Automated corporate expertise

NASA Technical Reports Server (NTRS)

Modesitt, Kenneth L.

1987-01-01

Progress is reported on the development of SCOTTY, an expert knowledge-based system to automate the analysis procedure following test firings of the Space Shuttle Main Engine (SSME). The integration of a large-scale relational data base system, a computer graphics interface for experts and end-user engineers, potential extension of the system to flight engines, application of the system for training of newly-hired engineers, technology transfer to other engines, and the essential qualities of good software engineering practices for building expert knowledge-based systems are among the topics discussed.

Towards a Collaborative Research: A Case Study on Linking Science to Farmers’ Perceptions and Knowledge on Arabica Coffee Pests and Diseases and Its Management

PubMed Central

Liebig, Theresa; Läderach, Peter; Poehling, Hans-Michael; Kucel, Patrick; Van Asten, Piet; Avelino, Jacques

2016-01-01

The scientific community has recognized the importance of integrating farmer’s perceptions and knowledge (FPK) for the development of sustainable pest and disease management strategies. However, the knowledge gap between indigenous and scientific knowledge still contributes to misidentification of plant health constraints and poor adoption of management solutions. This is particularly the case in the context of smallholder farming in developing countries. In this paper, we present a case study on coffee production in Uganda, a sector depending mostly on smallholder farming facing a simultaneous and increasing number of socio-ecological pressures. The objectives of this study were (i) to examine and relate FPK on Arabica Coffee Pests and Diseases (CPaD) to altitude and the vegetation structure of the production systems; (ii) to contrast results with perceptions from experts and (iii) to compare results with field observations, in order to identify constraints for improving the information flow between scientists and farmers. Data were acquired by means of interviews and workshops. One hundred and fifty farmer households managing coffee either at sun exposure, under shade trees or inter-cropped with bananas and spread across an altitudinal gradient were selected. Field sampling of the two most important CPaD was conducted on a subset of 34 plots. The study revealed the following findings: (i) Perceptions on CPaD with respect to their distribution across altitudes and perceived impact are partially concordant among farmers, experts and field observations (ii) There are discrepancies among farmers and experts regarding management practices and the development of CPaD issues of the previous years. (iii) Field observations comparing CPaD in different altitudes and production systems indicate ambiguity of the role of shade trees. According to the locality-specific variability in CPaD pressure as well as in FPK, the importance of developing spatially variable and relevant CPaD control practices is proposed. PMID:27504826

Towards a Collaborative Research: A Case Study on Linking Science to Farmers' Perceptions and Knowledge on Arabica Coffee Pests and Diseases and Its Management.

PubMed

Liebig, Theresa; Jassogne, Laurence; Rahn, Eric; Läderach, Peter; Poehling, Hans-Michael; Kucel, Patrick; Van Asten, Piet; Avelino, Jacques

2016-01-01

The scientific community has recognized the importance of integrating farmer's perceptions and knowledge (FPK) for the development of sustainable pest and disease management strategies. However, the knowledge gap between indigenous and scientific knowledge still contributes to misidentification of plant health constraints and poor adoption of management solutions. This is particularly the case in the context of smallholder farming in developing countries. In this paper, we present a case study on coffee production in Uganda, a sector depending mostly on smallholder farming facing a simultaneous and increasing number of socio-ecological pressures. The objectives of this study were (i) to examine and relate FPK on Arabica Coffee Pests and Diseases (CPaD) to altitude and the vegetation structure of the production systems; (ii) to contrast results with perceptions from experts and (iii) to compare results with field observations, in order to identify constraints for improving the information flow between scientists and farmers. Data were acquired by means of interviews and workshops. One hundred and fifty farmer households managing coffee either at sun exposure, under shade trees or inter-cropped with bananas and spread across an altitudinal gradient were selected. Field sampling of the two most important CPaD was conducted on a subset of 34 plots. The study revealed the following findings: (i) Perceptions on CPaD with respect to their distribution across altitudes and perceived impact are partially concordant among farmers, experts and field observations (ii) There are discrepancies among farmers and experts regarding management practices and the development of CPaD issues of the previous years. (iii) Field observations comparing CPaD in different altitudes and production systems indicate ambiguity of the role of shade trees. According to the locality-specific variability in CPaD pressure as well as in FPK, the importance of developing spatially variable and relevant CPaD control practices is proposed.

From Data to Knowledge through Concept-oriented Terminologies

PubMed Central

Cimino, James J.

2000-01-01

Knowledge representation involves enumeration of conceptual symbols and arrangement of these symbols into some meaningful structure. Medical knowledge representation has traditionally focused more on the structure than the symbols. Several significant efforts are under way, at local, national, and international levels, to address the representation of the symbols though the creation of high-quality terminologies that are themselves knowledge based. This paper reviews these efforts, including the Medical Entities Dictionary (MED) in use at Columbia University and the New York Presbyterian Hospital. A decade's experience with the MED is summarized to serve as a proof-of-concept that knowledge-based terminologies can support the use of coded patient data for a variety of knowledge-based activities, including the improved understanding of patient data, the access of information sources relevant to specific patient care problems, the application of expert systems directly to the care of patients, and the discovery of new medical knowledge. The terminological knowledge in the MED has also been used successfully to support clinical application development and maintenance, including that of the MED itself. On the basis of this experience, current efforts to create standard knowledge-based terminologies appear to be justified. PMID:10833166

From data to knowledge through concept-oriented terminologies: experience with the Medical Entities Dictionary.

PubMed

Cimino, J J

2000-01-01

Knowledge representation involves enumeration of conceptual symbols and arrangement of these symbols into some meaningful structure. Medical knowledge representation has traditionally focused more on the structure than the symbols. Several significant efforts are under way, at local, national, and international levels, to address the representation of the symbols though the creation of high-quality terminologies that are themselves knowledge based. This paper reviews these efforts, including the Medical Entities Dictionary (MED) in use at Columbia University and the New York Presbyterian Hospital. A decade's experience with the MED is summarized to serve as a proof-of-concept that knowledge-based terminologies can support the use of coded patient data for a variety of knowledge-based activities, including the improved understanding of patient data, the access of information sources relevant to specific patient care problems, the application of expert systems directly to the care of patients, and the discovery of new medical knowledge. The terminological knowledge in the MED has also been used successfully to support clinical application development and maintenance, including that of the MED itself. On the basis of this experience, current efforts to create standard knowledge-based terminologies appear to be justified.

The adversarial court system and the expert medical witness: 'The truth the whole truth and nothing but the truth?'.

PubMed

Ryan, Matthew

2003-06-01

This discussion aims to provide the occasional medical expert witness with background knowledge of the adversarial court system and the role of the medical expert witness within it. The parallel evolution of the adversarial and inquisitorial legal systems has been more out of tradition rather than any systematic review of the effectiveness of one system or the other. Both legal systems have their merits and limitations. Witnesses within the adversarial system are required to present evidence in a structured and highly stylized format consisting of 'evidence in chief' followed by 'cross-examination'. This format is an attempt to exclude unreliable evidence. The medical witness is an 'expert' by means of specialized knowledge not possessed by the general public. This distinction allows the expert medical witness to offer his or her opinion as evidence. There remain several limitations to the expert's evidence and these relate to common knowledge, field of expertise and the 'ultimate issue'. The current practice of selection of expert medical witnesses is seriously flawed with several pressures operating to maximise bias and inaccurate testimony. Doctors should not only anticipate change in this area they should lead reform in this area.

Development of an expert system for assessing trumpeter swan breeding habitat in the Northern Rocky Mountains.

USGS Publications Warehouse

Sojda, Richard S.; Cornely, John E.; Howe, Adele E.

2002-01-01

A decision support system for the management of the Rocky Mountain Population of Trumpeter Swans (Cygnus buccinators) is being developed. As part of this, three expert systems are also in development: one for assessing the quality of Trumpeter Swan breeding habitat; one for making water level recommendations in montane, palustrine wetlands; and one for assessing the contribution a particular site can make towards meeting objectives from as flyway perspective. The focus of this paper is the development of the breeding habitat expert system, which currently consists of 157 rules. Out purpose is to provide decision support for issues that appear to be beyond the capability of a single persons to conceptualize and solve. We propose that by involving multiple experts in the development and use of the systems, management will be significantly improved. The knowledge base for the expert system has been developed using standard knowledge engineering techniques with a small team of ecological experts. Knowledge was then coded using production rules organized in decision trees using a commercial expert system development shell. The final system has been deployed on the world wide web.

Use of cccupancy models to evaluate expert knowledge-based species-habitat relationships

USGS Publications Warehouse

Iglecia, Monica N.; Collazo, Jaime A.; McKerrow, Alexa

2012-01-01

Expert knowledge-based species-habitat relationships are used extensively to guide conservation planning, particularly when data are scarce. Purported relationships describe the initial state of knowledge, but are rarely tested. We assessed support in the data for suitability rankings of vegetation types based on expert knowledge for three terrestrial avian species in the South Atlantic Coastal Plain of the United States. Experts used published studies, natural history, survey data, and field experience to rank vegetation types as optimal, suitable, and marginal. We used single-season occupancy models, coupled with land cover and Breeding Bird Survey data, to examine the hypothesis that patterns of occupancy conformed to species-habitat suitability rankings purported by experts. Purported habitat suitability was validated for two of three species. As predicted for the Eastern Wood-Pewee (Contopus virens) and Brown-headed Nuthatch (Sitta pusilla), occupancy was strongly influenced by vegetation types classified as “optimal habitat” by the species suitability rankings for nuthatches and wood-pewees. Contrary to predictions, Red-headed Woodpecker (Melanerpes erythrocephalus) models that included vegetation types as covariates received similar support by the data as models without vegetation types. For all three species, occupancy was also related to sampling latitude. Our results suggest that covariates representing other habitat requirements might be necessary to model occurrence of generalist species like the woodpecker. The modeling approach described herein provides a means to test expert knowledge-based species-habitat relationships, and hence, help guide conservation planning.

40 CFR 194.26 - Expert judgment.

Code of Federal Regulations, 2010 CFR

2010-07-01

... judgment elicitation processes and the reasoning behind those results. Documentation of interviews used to elicit judgments from experts, the questions or issues presented for elicitation of expert judgment... expert judgment elicitation comports with the level of knowledge required by the questions or issues...

40 CFR 194.26 - Expert judgment.

Code of Federal Regulations, 2011 CFR

2011-07-01

... judgment elicitation processes and the reasoning behind those results. Documentation of interviews used to elicit judgments from experts, the questions or issues presented for elicitation of expert judgment... expert judgment elicitation comports with the level of knowledge required by the questions or issues...

An Alternative Expert Knowledge Transfer Model: A Case Study of an Indigenous Storytelling Approach

ERIC Educational Resources Information Center

Spaulding, Roderick Jay

2010-01-01

The increasing complexity of technical work, the demand for highly skilled workers, and the vital challenges facing the world at large have combined to create a need for better ways to transfer knowledge, especially expert knowledge. In this dissertation, I attempted to see if an approach to this process that is more holistic than is typical in…

Experiential knowledge of expert coaches can help identify informational constraints on performance of dynamic interceptive actions.

PubMed

Greenwood, Daniel; Davids, Keith; Renshaw, Ian

2014-01-01

Coordination of dynamic interceptive movements is predicated on cyclical relations between an individual's actions and information sources from the performance environment. To identify dynamic informational constraints, which are interwoven with individual and task constraints, coaches' experiential knowledge provides a complementary source to support empirical understanding of performance in sport. In this study, 15 expert coaches from 3 sports (track and field, gymnastics and cricket) participated in a semi-structured interview process to identify potential informational constraints which they perceived to regulate action during run-up performance. Expert coaches' experiential knowledge revealed multiple information sources which may constrain performance adaptations in such locomotor pointing tasks. In addition to the locomotor pointing target, coaches' knowledge highlighted two other key informational constraints: vertical reference points located near the locomotor pointing target and a check mark located prior to the locomotor pointing target. This study highlights opportunities for broadening the understanding of perception and action coupling processes, and the identified information sources warrant further empirical investigation as potential constraints on athletic performance. Integration of experiential knowledge of expert coaches with theoretically driven empirical knowledge represents a promising avenue to drive future applied science research and pedagogical practice.

Best Practices for Reduction of Uncertainty in CFD Results

NASA Technical Reports Server (NTRS)

Mendenhall, Michael R.; Childs, Robert E.; Morrison, Joseph H.

2003-01-01

This paper describes a proposed best-practices system that will present expert knowledge in the use of CFD. The best-practices system will include specific guidelines to assist the user in problem definition, input preparation, grid generation, code selection, parameter specification, and results interpretation. The goal of the system is to assist all CFD users in obtaining high quality CFD solutions with reduced uncertainty and at lower cost for a wide range of flow problems. The best-practices system will be implemented as a software product which includes an expert system made up of knowledge databases of expert information with specific guidelines for individual codes and algorithms. The process of acquiring expert knowledge is discussed, and help from the CFD community is solicited. Benefits and challenges associated with this project are examined.

[Multicenter evaluation of the Nutri-Expert Telematic System in diabetic patients].

PubMed

Turnin, M C; Bolzonella-Pene, C; Dumoulin, S; Cerf, I; Charpentier, G; Sandre-Banon, D; Valensi, P; Grenier, J L; Cathelineau, G; Mattei, C

1995-02-01

Nutri-Expert is a system for self-monitoring and dietetic education, accessible through Minitel. A preliminary randomised evaluation of one hundred diabetic patients in the Midi-Pyrénées region showed that Nutri-Expert improved dietetic knowledge, dietary habits and metabolic balance. The aim of the present study was to show that the system can be successfully prescribed to patients by physicians outside the center which originated it, indicating the benefit of a wider use of Nutri-Expert, among the diabetic population. One hundred and fifty-five patients, recruited by six French centres of diabetology, used Nutri-Expert from their homes for six months. Clinical examination, tests of dietetic knowledge and biological tests, including lipid fractions, were carried out before and after six months of use. After six months, there was a significant improvement in the patients' dietetic knowledge and in some biological parameters. Nutri-Expert is thus useful even when prescribed by a centre other than the hospital which devised the system. It is an additional beneficial tool in the ambulatory management of diabetic patients.

Toward a theory of distributed word expert natural language parsing

NASA Technical Reports Server (NTRS)

Rieger, C.; Small, S.

1981-01-01

An approach to natural language meaning-based parsing in which the unit of linguistic knowledge is the word rather than the rewrite rule is described. In the word expert parser, knowledge about language is distributed across a population of procedural experts, each representing a word of the language, and each an expert at diagnosing that word's intended usage in context. The parser is structured around a coroutine control environment in which the generator-like word experts ask questions and exchange information in coming to collective agreement on sentence meaning. The word expert theory is advanced as a better cognitive model of human language expertise than the traditional rule-based approach. The technical discussion is organized around examples taken from the prototype LISP system which implements parts of the theory.

Computers Simulate Human Experts.

ERIC Educational Resources Information Center

Roberts, Steven K.

1983-01-01

Discusses recent progress in artificial intelligence in such narrowly defined areas as medical and electronic diagnosis. Also discusses use of expert systems, man-machine communication problems, novel programing environments (including comments on LISP and LISP machines), and types of knowledge used (factual, heuristic, and meta-knowledge). (JN)

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

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.

Exploring experts' views and perspectives on the enhancement of Strategic Environmental Assessment in European small islands

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

Polido, Alexandra, E-mail: a.polido@campus.fct.unl.pt; João, Elsa, E-mail: elsa.joao@strath.ac.uk; Ramos, Tomás B., E-mail: tabr@fct.unl.pt

Small islands have the attention of the international community because they are territories with unique features, and a pressing need for the enhancement of sustainability. Strategic Environmental Assessment (SEA) has characteristics that may promote the development and improvement of sustainability in these territories: (i) changing the mind-set, and the decision-making and institutional paradigm, (ii) facilitating cooperation and coordination between different stakeholders, and (iii) providing a framework for good governance and community empowerment. The scientific literature suggests that there may be a need for context-specific SEA in these territories. However, SEA studies often do not incorporate local contextual information, including intuitivemore » knowledge and sense of place. Therefore, there is a possible gap between what is found in the literature and what local communities think, including different stakeholders and experts. Hence, the main goal of this research was to gain an insight into the views and perspectives of small islands SEA experts about issues related to SEA in European small islands, including context-specific approaches, as well as the contribution of SEA for sustainability in these territories. To achieve the research aim, exploratory research using a questionnaire-based survey was designed, aimed at experts on SEA in European small islands. Findings showed regional cooperation networks may have a fundamental role when developing SEA-specific approaches in these territories. This is because SEA-specific approaches encourage a joint effort among islands within one region to improve SEA capacity-building, develop and share a baseline information system, and to share and exchange resources, overall. Also, guidelines are preferred among experts over more legal frameworks and regulations. Finally, the research showed that experts view SEA as a way to enhance sustainability in small islands. This study highlights the importance of integrating stakeholders, such as territorial experts, to learn and promote the use and improvement of environmental and sustainability tools such as SEA. - Highlights: • Explored the views and perspectives of European small island experts • Showed the need for cooperation networks while developing SEA in these territories • Encouraged the development of specific guidelines as opposed to more legal frameworks • Highlighted SEA capability for the enhancement of small island sustainability.« less

Model of critical diagnostic reasoning: achieving expert clinician performance.

PubMed

Harjai, Prashant Kumar; Tiwari, Ruby

2009-01-01

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

ESKAPE/CF: A Knowledge Acquisition Tool for Expert Systems Using Cognitive Feedback

DTIC Science & Technology

1991-03-01

NAVAL POSTGRADUATE SCHOOL Monterey, California AD-A241 815i!1! lit 1i iill 1111 !! I 1111 ST E * ODTIC OCT22 z 99I; THESIS ESKAPE /CF: A KNOWLEDGE...11. TITLE (include Security Classification) ESKAPE /CF: A KNOWLEDGE ACQUISITION TOOL FOR EXPERT SYSTEMS USING COGNITIVE FEEDBACK (U) e PERSOIAL AUTVR(Yl...tool using Cognitive Feedback ( ESKAPE /CF), based on Lens model techniques which have demonstrated effectiveness in cap- turing policy knowledge. The

An overview of expert systems. [artificial intelligence

NASA Technical Reports Server (NTRS)

Gevarter, W. B.

1982-01-01

An expert system is defined and its basic structure is discussed. The knowledge base, the inference engine, and uses of expert systems are discussed. Architecture is considered, including choice of solution direction, reasoning in the presence of uncertainty, searching small and large search spaces, handling large search spaces by transforming them and by developing alternative or additional spaces, and dealing with time. Existing expert systems are reviewed. Tools for building such systems, construction, and knowledge acquisition and learning are discussed. Centers of research and funding sources are listed. The state-of-the-art, current problems, required research, and future trends are summarized.

Combining factual and heuristic knowledge in knowledge acquisition

NASA Technical Reports Server (NTRS)

Gomez, Fernando; Hull, Richard; Karr, Clark; Hosken, Bruce; Verhagen, William

1992-01-01

A knowledge acquisition technique that combines heuristic and factual knowledge represented as two hierarchies is described. These ideas were applied to the construction of a knowledge acquisition interface to the Expert System Analyst (OPERA). The goal of OPERA is to improve the operations support of the computer network in the space shuttle launch processing system. The knowledge acquisition bottleneck lies in gathering knowledge from human experts and transferring it to OPERA. OPERA's knowledge acquisition problem is approached as a classification problem-solving task, combining this approach with the use of factual knowledge about the domain. The interface was implemented in a Symbolics workstation making heavy use of windows, pull-down menus, and other user-friendly devices.

Fuzzy Expert System for Heart Attack Diagnosis

NASA Astrophysics Data System (ADS)

Hassan, Norlida; Arbaiy, Nureize; Shah, Noor Aziyan Ahmad; Afizah Afif@Afip, Zehan

2017-08-01

Heart attack is one of the serious illnesses and reported as the main killer disease. Early prevention is significant to reduce the risk of having the disease. The prevention efforts can be strengthen through awareness and education about risk factor and healthy lifestyle. Therefore the knowledge dissemination is needed to play role in order to distribute and educate public in health care management and disease prevention. Since the knowledge dissemination in medical is important, there is a need to develop a knowledge based system that can emulate human intelligence to assist decision making process. Thereby, this study utilized hybrid artificial intelligence (AI) techniques to develop a Fuzzy Expert System for Diagnosing Heart Attack Disease (HAD). This system integrates fuzzy logic with expert system, which helps the medical practitioner and people to predict the risk and as well as diagnosing heart attack based on given symptom. The development of HAD is expected not only providing expert knowledge but potentially become one of learning resources to help citizens to develop awareness about heart-healthy lifestyle.

Proceedings of the Lunar Materials Technology Symposium

NASA Technical Reports Server (NTRS)

1992-01-01

The meeting was organized around a possible lunar outpost scenario, featuring industrial technologies, systems, and components applicable to the extraction, processing, and fabrication of local materials. Acknowledged space resources experts as well as investigators from outside the field whose knowledge could be applied to space development activities were brought together. Presentations came from a variety of specialists in fields such as minerals processing, environmental control, and communications. The sessions of the symposium were divided into the following areas: resource characterization, energy management, materials processing, environment control, and automation and communications.

Knowledge engineering for PACES, the particle accelerator control expert system

NASA Astrophysics Data System (ADS)

Lind, P. C.; Poehlman, W. F. S.; Stark, J. W.; Cousins, T.

1992-04-01

The KN-3000 used at Defense Research Establishment Ottawa is a Van de Graaff particle accelerator employed primarily to produce monoenergetic neutrons for calibrating radiation detectors. To provide training and assistance for new operators, it was decided to develop an expert system for accelerator operation. Knowledge engineering aspects of the expert system are reviewed. Two important issues are involved: the need to encapsulate expert knowledge into the system in a form that facilitates automatic accelerator operation and to partition the system so that time-consuming inferencing is minimized in favor of faster, more algorithmic control. It is seen that accelerator control will require fast, narrowminded decision making for rapid fine tuning, but slower and broader reasoning for machine startup, shutdown, fault diagnosis, and correction. It is also important to render the knowledge base in a form conducive to operator training. A promising form of the expert system involves a hybrid system in which high level reasoning is performed on the host machine that interacts with the user, while an embedded controller employs neural networks for fast but limited adjustment of accelerator performance. This partitioning of duty facilitates a hierarchical chain of command yielding an effective mixture of speed and reasoning ability.

Human motion tracking by temporal-spatial local gaussian process experts.

PubMed

Zhao, Xu; Fu, Yun; Liu, Yuncai

2011-04-01

Human pose estimation via motion tracking systems can be considered as a regression problem within a discriminative framework. It is always a challenging task to model the mapping from observation space to state space because of the high-dimensional characteristic in the multimodal conditional distribution. In order to build the mapping, existing techniques usually involve a large set of training samples in the learning process which are limited in their capability to deal with multimodality. We propose, in this work, a novel online sparse Gaussian Process (GP) regression model to recover 3-D human motion in monocular videos. Particularly, we investigate the fact that for a given test input, its output is mainly determined by the training samples potentially residing in its local neighborhood and defined in the unified input-output space. This leads to a local mixture GP experts system composed of different local GP experts, each of which dominates a mapping behavior with the specific covariance function adapting to a local region. To handle the multimodality, we combine both temporal and spatial information therefore to obtain two categories of local experts. The temporal and spatial experts are integrated into a seamless hybrid system, which is automatically self-initialized and robust for visual tracking of nonlinear human motion. Learning and inference are extremely efficient as all the local experts are defined online within very small neighborhoods. Extensive experiments on two real-world databases, HumanEva and PEAR, demonstrate the effectiveness of our proposed model, which significantly improve the performance of existing models.

Using Ada to implement the operations management system in a community of experts

NASA Technical Reports Server (NTRS)

Frank, M. S.

1986-01-01

An architecture is described for the Space Station Operations Management System (OMS), consisting of a distributed expert system framework implemented in Ada. The motivation for such a scheme is based on the desire to integrate the very diverse elements of the OMS while taking maximum advantage of knowledge based systems technology. Part of the foundation of an Ada based distributed expert system was accomplished in the form of a proof of concept prototype for the KNOMES project (Knowledge-based Maintenance Expert System). This prototype successfully used concurrently active experts to accomplish monitoring and diagnosis for the Remote Manipulator System. The basic concept of this software architecture is named ACTORS for Ada Cognitive Task ORganization Scheme. It is when one considers the overall problem of integrating all of the OMS elements into a cooperative system that the AI solution stands out. By utilizing a distributed knowledge based system as the framework for OMS, it is possible to integrate those components which need to share information in an intelligent manner.

Evolving Expert Knowledge Bases: Applications of Crowdsourcing and Serious Gaming to Advance Knowledge Development for Intelligent Tutoring Systems

ERIC Educational Resources Information Center

Floryan, Mark

2013-01-01

This dissertation presents a novel effort to develop ITS technologies that adapt by observing student behavior. In particular, we define an evolving expert knowledge base (EEKB) that structures a domain's information as a set of nodes and the relationships that exist between those nodes. The structure of this model is not the particularly novel…

Teacher leadership in mathematics and science: Subject content knowledge and the improvement of instruction

NASA Astrophysics Data System (ADS)

Manno, Christopher M.

This study explores the role of teacher leader subject content knowledge in the promotion of professional development and instructional reform. Consistent with a distributed leadership perspective, many have asserted that the promotion of school effectiveness can be enhanced through the application of teacher leadership (Frost & Durrant, 2003; Harris, 2002a; Sherrill, 1999; Silva, Gimbert, & Nolan, 2000; York-Barr & Duke, 2004). There has been much discussion in the research about the significance of teachers' subject content knowledge in teaching and learning which has generally asserted a positive relationship with instructional practice and student achievement (Darling-Hammond, 2000; Newton & Newton, 2001; Parker & Heywood, 2000). The role of content knowledge in teacher leader work has been less researched. This study focused on deepening understanding of perceptions regarding teacher leaders' roles in improving instructional practice. Based on a framework of common teacher leader tasks, qualitative methods were used to investigate the relationship between teacher leader subject content knowledge and perceptions of effectiveness in promoting professional development and instructional reform. The study indicates that content experts behave differently than their non-expert counterparts. Content experts recognize deficiencies in colleagues' content knowledge as a primary problem in the implementation of math or science reform. Content experts view their work as advocacy for improved curriculum and instruction for all children, and work within a small set of task categories to promote discussions about teaching, learning, and content. Content experts develop trust and rapport with colleagues by demonstrating expertise, and are respected for their deep knowledge and efforts to help teachers learn the content. They also differ from non-content experts in the professional growth experiences in which they engage. The consideration of content expertise as an influence to teacher leader work helps to refine our conception of teacher leadership. A task-focused model of content expert teacher leadership is presented, and provides guidance for recruitment, selection, and development of future teacher leaders. Content expertise is presented as a form of human capital that promotes task-focused distributed leadership. Practical recommendations for future teacher leadership initiatives and suggestions for future research are presented.

On the acquisition and representation of procedural knowledge

NASA Technical Reports Server (NTRS)

Saito, T.; Ortiz, C.; Loftin, R. B.

1992-01-01

Historically knowledge acquisition has proven to be one of the greatest barriers to the development of intelligent systems. Current practice generally requires lengthy interactions between the expert whose knowledge is to be captured and the knowledge engineer whose responsibility is to acquire and represent knowledge in a useful form. Although much research has been devoted to the development of methodologies and computer software to aid in the capture and representation of some of some types of knowledge, little attention has been devoted to procedural knowledge. NASA personnel frequently perform tasks that are primarily procedural in nature. Previous work is reviewed in the field of knowledge acquisition and then focus on knowledge acquisition for procedural tasks with special attention devoted to the Navy's VISTA tool. The design and development is described of a system for the acquisition and representation of procedural knowledge-TARGET (Task Analysis and Rule Generation Tool). TARGET is intended as a tool that permits experts to visually describe procedural tasks and as a common medium for knowledge refinement by the expert and knowledge engineer. The system is designed to represent the acquired knowledge in the form of production rules. Systems such as TARGET have the potential to profoundly reduce the time, difficulties, and costs of developing knowledge-based systems for the performance of procedural tasks.

Sex work and the claim for grassroots legislation.

PubMed

Fassi, Marisa N

2015-01-01

The aim of this paper is to contribute to understanding of legal models that aim to control sex work, and the policy implications of these, by discussing the experience of developing a grassroots legislation bill proposal by organised sex workers in Córdoba, Argentina. The term 'grassroots legislation' here refers to a legal response that derives from the active involvement of local social movements and thus incorporates the experiential knowledge and claims of these particular social groupings in the proposal. The experience described in this paper excludes approaches that render sex workers as passive victims or as deviant perpetrators; instead, it conceives of sex workers in terms of their political subjectivity and of political subjectivity in its capacity to speak, to decide, to act and to propose. This means challenging current patterns of knowledge/power that give superiority to 'expert knowledge' above and beyond the claims, experiences, knowledge and needs of sex workers themselves as meaningful sources for law making.

Knowledge management strategies: Enhancing knowledge transfer to clinicians and patients.

PubMed

Roemer, Lorrie K; Rocha, Roberto A; Del Fiol, Guilherme; Bradshaw, Richard L; Hanna, Timothy P; Hulse, Nathan C

2006-01-01

At Intermountain Healthcare (Intermountain), executive clinical content experts are responsible for disseminating consistent evidence-based clinical content throughout the enterprise at the point-of-care. With a paper-based system it was difficult to ensure that current information was received and was being used in practice. With electronic information systems multiple applications were supplying similar, but different, vendor-licensed and locally-developed content. These issues influenced the consistency of clinical practice within the enterprise, jeopardized patient and clinician safety, and exposed the enterprise and its employees to potential financial penalties. In response to these issues Intermountain is developing a knowledge management infrastructure providing tools and services to support clinical content development, deployment, maintenance, and communication. The Intermountain knowledge management philosophy includes strategies guiding clinicians and consumers of health information to relevant best practice information with the intention of changing behaviors. This paper presents three case studies describing different information management problems identified within Intermountain, methods used to solve the problems, implementation challenges, and the current status of each project.

Knowledge Brokers in the Making: Opportunities to Connect Researchers and Stakeholders

NASA Astrophysics Data System (ADS)

Pennell, K. G.; Pennell, M. C.

2014-12-01

Environmental science and engineering graduate students often lack training on how to communicate with policy decision makers who are grappling with questions to which research is responding. They communicate directly with mutual experts, but are many times unable to engage with non-experts about their research, thereby limiting the reach and impact of their findings. This presentation highlights opportunities within environmental science and engineering research to create opportunities for researchers to hone skills as knowledge brokers, so they learn ways to meaningfully engage with a range of stakeholders. A knowledge broker is an individual who connects scientific experts and relevant stakeholders with meaningful and useable information. Recognizing that information must flow in multiple directions, the knowledge broker must quickly and effectively translate needs and questions using established relationships. It is these relationships, as well as the synthesis of scientific knowledge into useable information, on which the success of the knowledge broker lies. Using lessons learned, as well as communication science theory related to knowledge brokering, this presentation highlights training opportunities for knowledge brokers who are primarily educated in science and engineering fields, yet seek to engage with societally relevant stakeholders. We present case study examples of knowledge brokering within two large multi-disciplinary research centers. These centers provide unique experiences for researchers to build relationships with stakeholders, so that the scientific experts not only create novel research within their specific discipline, but also inform policy decision makers, community members and regulatory officials.

Personalized Knowledge Transfer for Caregiving Relatives.

PubMed

Wolff, Dominik; Behrends, Marianne; Gerlach, Mario; Kupka, Thomas; Marschollek, Michael

2018-01-01

Caregiving relatives have to manage very diverse tasks and need a lot of care-relevant knowledge. For most of them it is not easy to find the knowledge required. Thus, a personalized knowledge transfer for caregiving relatives is necessary. Against this background, methods to determine the personal relevance and importance of knowledge resources for caregiving relatives are developed. To evaluate these methods, an exemplary fictitious person is created by experts in Nursing Science. In this evaluation, the approach's results are compared with an expert opinion. The approach indicates that a personalized knowledge transfer is possible, providing caregiving relatives with necessary care knowledge according to their personal life situation.

An evaluation of selected (Q)SARs/expert systems for predicting skin sensitisation potential.

PubMed

Fitzpatrick, J M; Roberts, D W; Patlewicz, G

2018-06-01

Predictive testing to characterise substances for their skin sensitisation potential has historically been based on animal models such as the Local Lymph Node Assay (LLNA) and the Guinea Pig Maximisation Test (GPMT). In recent years, EU regulations, have provided a strong incentive to develop non-animal alternatives, such as expert systems software. Here we selected three different types of expert systems: VEGA (statistical), Derek Nexus (knowledge-based) and TIMES-SS (hybrid), and evaluated their performance using two large sets of animal data: one set of 1249 substances from eChemportal and a second set of 515 substances from NICEATM. A model was considered successful at predicting skin sensitisation potential if it had at least the same balanced accuracy as the LLNA and the GPMT had in predicting the other outcomes, which ranged from 79% to 86%. We found that the highest balanced accuracy of any of the expert systems evaluated was 65% when making global predictions. For substances within the domain of TIMES-SS, however, balanced accuracies for the two datasets were found to be 79% and 82%. In those cases where a chemical was within the TIMES-SS domain, the TIMES-SS skin sensitisation hazard prediction had the same confidence as the result from LLNA or GPMT.

Research on an expert system for database operation of simulation-emulation math models. Volume 1, Phase 1: Results

NASA Technical Reports Server (NTRS)

Kawamura, K.; Beale, G. O.; Schaffer, J. D.; Hsieh, B. J.; Padalkar, S.; Rodriguez-Moscoso, J. J.

1985-01-01

The results of the first phase of Research on an Expert System for Database Operation of Simulation/Emulation Math Models, is described. Techniques from artificial intelligence (AI) were to bear on task domains of interest to NASA Marshall Space Flight Center. One such domain is simulation of spacecraft attitude control systems. Two related software systems were developed to and delivered to NASA. One was a generic simulation model for spacecraft attitude control, written in FORTRAN. The second was an expert system which understands the usage of a class of spacecraft attitude control simulation software and can assist the user in running the software. This NASA Expert Simulation System (NESS), written in LISP, contains general knowledge about digital simulation, specific knowledge about the simulation software, and self knowledge.

Object-oriented knowledge representation for expert systems

NASA Technical Reports Server (NTRS)

Scott, Stephen L.

1991-01-01

Object oriented techniques have generated considerable interest in the Artificial Intelligence (AI) community in recent years. This paper discusses an approach for representing expert system knowledge using classes, objects, and message passing. The implementation is in version 4.3 of NASA's C Language Integrated Production System (CLIPS), an expert system tool that does not provide direct support for object oriented design. The method uses programmer imposed conventions and keywords to structure facts, and rules to provide object oriented capabilities.

Using the Internet to Collaborate with Consumers in Redefining a Psychosocial Agenda for Families with Hereditary Breast Cancer

DTIC Science & Technology

2007-06-01

expert patient and has broad relevance in terms of people developing the knowledge to maintain their health and manage illness, thereby having...growing controversy concerning the expert patient [32] revolves around whether it is possible for lay persons to actually renegotiate a more balanced...participating in this thread seem to fulfill the more empowering view of the expert patient by integrat- ing personal and medical knowledge to renegotiate

The nutrition advisor expert system

NASA Technical Reports Server (NTRS)

Huse, Scott M.; Shyne, Scott S.

1991-01-01

The Nutrition Advisor Expert System (NAES) is an expert system written in the C Language Integrated Production System (CLIPS). NAES provides expert knowledge and guidance into the complex world of nutrition management by capturing the knowledge of an expert and placing it at the user's fingertips. Specifically, NAES enables the user to: (1) obtain precise nutrition information for food items; (2) perform nutritional analysis of meal(s), flagging deficiencies based upon the U.S. Recommended Daily Allowances; (3) predict possible ailments based upon observed nutritional deficiency trends; (4) obtain a top ten listing of food items for a given nutrient; and (5) conveniently upgrade the data base. An explanation facility for the ailment prediction feature is also provided to document the reasoning process.

International education is a broken field: Can ubuntu education bring solutions?

NASA Astrophysics Data System (ADS)

Piper, Benjamin

2016-02-01

Ubuntu is an African philosophy of human kindness; applying it in the Global South would fundamentally alter the design of the education sector. This essay argues, however, that the field of international educational development is not, in fact, structured to support an education influenced by ubuntu ideals. Specifically, the educational development milieu includes donors, implementers and academicians who do not sufficiently question the power dynamics which underpin education development. This creates a field where the power imbalances between donors and host governments are not interrogated, where development workers place too much faith in their own knowledge rather than that of local education experts, and where development practitioners rarely appreciate the privilege of working in countries which are not their own. An ubuntu education would alter the educational development field in myriad critical ways, a few of which are suggested in this essay. Educational development programmes in universities and intake programmes for implementers and donors should teach officers humility, appreciating existing local talent and expertise. Donor programmes should incentivise reflective practice which formally embeds appreciation for local culture and expertise, thereby supporting structures which help educational development experts to review their metacognitive processes. The field should also dramatically increase the numbers of local, minority and female educational development practitioners and provide more avenues for advancement for those groups. These are activities which are critical to supporting the education development field, but require a fundamental change of attitude by practitioners to ensure the right kind of relationships between the West and the Global South.

A knowledge-based support system for mechanical ventilation of the lungs. The KUSIVAR concept and prototype.

PubMed

Rudowski, R; Frostell, C; Gill, H

1989-09-01

The KUSIVAR is an expert system for mechanical ventilation of adult patients suffering from respiratory insufficiency. Its main objective is to provide guidance in respirator management. The knowledge base includes both qualitative, rule-based knowledge and quantitative knowledge expressed in the form of mathematical models (expert control) which is used for prediction of arterial gas tensions and optimization purposes. The system is data driven and uses a forward chaining mechanism for rule invocation. The interaction with the user will be performed in advisory, critiquing, semi-automatic and automatic modes. The system is at present in an advanced prototype stage. Prototyping is performed using KEE (Knowledge Engineering Environment) on a Sperry Explorer workstation. For further development and clinical use the expert system will be downloaded to an advanced PC. The system is intended to support therapy with a Siemens-Elema Servoventilator 900 C.

Expert system technology

NASA Technical Reports Server (NTRS)

Prince, Mary Ellen

1987-01-01

The expert system is a computer program which attempts to reproduce the problem-solving behavior of an expert, who is able to view problems from a broad perspective and arrive at conclusions rapidly, using intuition, shortcuts, and analogies to previous situations. Expert systems are a departure from the usual artificial intelligence approach to problem solving. Researchers have traditionally tried to develop general modes of human intelligence that could be applied to many different situations. Expert systems, on the other hand, tend to rely on large quantities of domain specific knowledge, much of it heuristic. The reasoning component of the system is relatively simple and straightforward. For this reason, expert systems are often called knowledge based systems. The report expands on the foregoing. Section 1 discusses the architecture of a typical expert system. Section 2 deals with the characteristics that make a problem a suitable candidate for expert system solution. Section 3 surveys current technology, describing some of the software aids available for expert system development. Section 4 discusses the limitations of the latter. The concluding section makes predictions of future trends.

The development of a knowledge test of depression and its treatment for patients suffering from non-psychotic depression: a psychometric assessment

PubMed Central

Gabriel, Adel; Violato, Claudio

2009-01-01

Background To develop and psychometrically assess a multiple choice question (MCQ) instrument to test knowledge of depression and its treatments in patients suffering from depression. Methods A total of 63 depressed patients and twelve psychiatric experts participated. Based on empirical evidence from an extensive review, theoretical knowledge and in consultations with experts, 27-item MCQ knowledge of depression and its treatment test was constructed. Data collected from the psychiatry experts were used to assess evidence of content validity for the instrument. Results Cronbach's alpha of the instrument was 0.68, and there was an overall 87.8% agreement (items are highly relevant) between experts about the relevance of the MCQs to test patient knowledge on depression and its treatments. There was an overall satisfactory patients' performance on the MCQs with 78.7% correct answers. Results of an item analysis indicated that most items had adequate difficulties and discriminations. Conclusion There was adequate reliability and evidence for content and convergent validity for the instrument. Future research should employ a lager and more heterogeneous sample from both psychiatrist and community samples, than did the present study. Meanwhile, the present study has resulted in psychometrically tested instruments for measuring knowledge of depression and its treatment of depressed patients. PMID:19754944

A time-responsive tool for informing policy making: rapid realist review.

PubMed

Saul, Jessie E; Willis, Cameron D; Bitz, Jennifer; Best, Allan

2013-09-05

A realist synthesis attempts to provide policy makers with a transferable theory that suggests a certain program is more or less likely to work in certain respects, for particular subjects, in specific kinds of situations. Yet realist reviews can require considerable and sustained investment over time, which does not always suit the time-sensitive demands of many policy decisions. 'Rapid Realist Review' methodology (RRR) has been developed as a tool for applying a realist approach to a knowledge synthesis process in order to produce a product that is useful to policy makers in responding to time-sensitive and/or emerging issues, while preserving the core elements of realist methodology. Using examples from completed RRRs, we describe key features of the RRR methodology, the resources required, and the strengths and limitations of the process. All aspects of an RRR are guided by both a local reference group, and a group of content experts. Involvement of knowledge users and external experts ensures both the usability of the review products, as well as their links to current practice. RRRs have proven useful in providing evidence for and making explicit what is known on a given topic, as well as articulating where knowledge gaps may exist. From the RRRs completed to date, findings broadly adhere to four (often overlapping) classifications: guiding rules for policy-making; knowledge quantification (i.e., the amount of literature available that identifies context, mechanisms, and outcomes for a given topic); understanding tensions/paradoxes in the evidence base; and, reinforcing or refuting beliefs and decisions taken. 'Traditional' realist reviews and RRRs have some key differences, which allow policy makers to apply each type of methodology strategically to maximize its utility within a particular local constellation of history, goals, resources, politics and environment. In particular, the RRR methodology is explicitly designed to engage knowledge users and review stakeholders to define the research questions, and to streamline the review process. In addition, results are presented with a focus on context-specific explanations for what works within a particular set of parameters rather than producing explanations that are potentially transferrable across contexts and populations. For policy makers faced with making difficult decisions in short time frames for which there is sufficient (if limited) published/research and practice-based evidence available, RRR provides a practical, outcomes-focused knowledge synthesis method.

Development of a short course on management of critically ill patients with acute respiratory infection and impact on clinician knowledge in resource-limited ICUs.

PubMed

Diaz, Janet V; Ortiz, Justin R; Lister, Paula; Shindo, Nahoko; Adhikari, Neill K J

2018-05-04

The 2009 influenza A (H1N1) pandemic caused surges of patients in intensive care units (ICUs) in resource-limited settings. Several Ministries of Health requested clinical management guidance from the World Health Organization (WHO), which had not previously developed guidance regarding critically ill patients. To assess the acceptability and impact on knowledge of a short course about the management of critically ill patients with acute respiratory infections complicated by sepsis or acute respiratory distress syndrome delivered to clinicians in resource-limited ICUs. Over four years (2009-2013), WHO led the development, piloting, implementation, and preliminary evaluation of a three-day course that emphasized patient management based on evidence-based guidelines and used interactive adult-learner teaching methodology. International content experts (n=35) and instructional designers contributed to development. We assessed participants' satisfaction and content knowledge before and after the course. The course was piloted among clinicians in Trinidad and Tobago (n=29), Indonesia (n=38), and Vietnam (n=86); feedback from these courses contributed to the final version. In 2013, inaugural national courses were delivered in Tajikistan (n=28), Uzbekistan (n=39), and Azerbaijan (n=30). Participants rated the course highly and demonstrated increased immediate content knowledge after (vs. before) course completion (p<0.001). We found that it was feasible to create and deliver a focused critical care short course to clinicians in low- and middle-income countries. Collaboration between WHO, clinical experts, instructional designers, Ministries of Health, and local clinician-leaders facilitated course delivery. Future work should assess its impact on longer-term knowledge retention and on processes and outcomes of care. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Automatic recognition of surface landmarks of anatomical structures of back and posture

NASA Astrophysics Data System (ADS)

Michoński, Jakub; Glinkowski, Wojciech; Witkowski, Marcin; Sitnik, Robert

2012-05-01

Faulty postures, scoliosis and sagittal plane deformities should be detected as early as possible to apply preventive and treatment measures against major clinical consequences. To support documentation of the severity of deformity and diminish x-ray exposures, several solutions utilizing analysis of back surface topography data were introduced. A novel approach to automatic recognition and localization of anatomical landmarks of the human back is presented that may provide more repeatable results and speed up the whole procedure. The algorithm was designed as a two-step process involving a statistical model built upon expert knowledge and analysis of three-dimensional back surface shape data. Voronoi diagram is used to connect mean geometric relations, which provide a first approximation of the positions, with surface curvature distribution, which further guides the recognition process and gives final locations of landmarks. Positions obtained using the developed algorithms are validated with respect to accuracy of manual landmark indication by experts. Preliminary validation proved that the landmarks were localized correctly, with accuracy depending mostly on the characteristics of a given structure. It was concluded that recognition should mainly take into account the shape of the back surface, putting as little emphasis on the statistical approximation as possible.

In the public interest: assessing expert and stakeholder influence in public deliberation about biobanks.

PubMed

MacLean, Samantha; Burgess, Michael M

2010-07-01

Providing technical and experiential information without overwhelming participants' perspectives presents a major challenge to public involvement in policy decisions. This article reports the design and analysis of a case study on incorporating expert and stakeholder knowledge without including them as deliberators, while supporting deliberative participants' ability to introduce and critically assess different perspectives. Analysis of audio-recorded deliberations illustrates how expert and stakeholder knowledge was cited, criticized and incorporated into deliberations. In conclusion, separating experts and stakeholders from deliberations may be an important prima facie principle when the goal is to enhance citizen representation on technical issues and related policy.

Teacher Knowledge for Active-Learning Instruction: Expert-Novice Comparison Reveals Differences.

PubMed

Auerbach, A J; Higgins, M; Brickman, P; Andrews, T C

2018-01-01

Active-learning strategies can improve science, technology, engineering, and mathematics (STEM) undergraduates' abilities to learn fundamental concepts and skills. However, the results instructors achieve vary substantially. One explanation for this is that instructors commonly implement active learning differently than intended. An important factor affecting how instructors implement active learning is knowledge of teaching and learning. We aimed to discover knowledge that is important to effective active learning in large undergraduate courses. We developed a lesson-analysis instrument to elicit teacher knowledge, drawing on the theoretical construct of teacher noticing. We compared the knowledge used by expert ( n = 14) and novice ( n = 29) active-learning instructors as they analyzed lessons. Experts and novices differed in what they noticed, with experts more commonly considering how instructors hold students accountable, topic-specific student difficulties, whether the instructor elicited and responded to student thinking, and opportunities students had to generate their own ideas and work. Experts were also better able to support their lesson analyses with reasoning. This work provides foundational knowledge for the future design of preparation and support for instructors adopting active learning. Improving teacher knowledge will improve the implementation of active learning, which will be necessary to widely realize the potential benefits of active learning in undergraduate STEM. © 2018 A. J. Auerbach et al. CBE—Life Sciences Education © 2018 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Expert Knowledge Influences Decision-Making for Couples Receiving Positive Prenatal Chromosomal Microarray Testing Results.

PubMed

Rubel, M A; Werner-Lin, A; Barg, F K; Bernhardt, B A

2017-09-01

To assess how participants receiving abnormal prenatal genetic testing results seek information and understand the implications of results, 27 US female patients and 12 of their male partners receiving positive prenatal microarray testing results completed semi-structured phone interviews. These interviews documented participant experiences with chromosomal microarray testing, understanding of and emotional response to receiving results, factors affecting decision-making about testing and pregnancy termination, and psychosocial needs throughout the testing process. Interview data were analyzed using a modified grounded theory approach. In the absence of certainty about the implications of results, understanding of results is shaped by biomedical expert knowledge (BEK) and cultural expert knowledge (CEK). When there is a dearth of BEK, as in the case of receiving results of uncertain significance, participants rely on CEK, including religious/spiritual beliefs, "gut instinct," embodied knowledge, and social network informants. CEK is a powerful platform to guide understanding of prenatal genetic testing results. The utility of culturally situated expert knowledge during testing uncertainty emphasizes that decision-making occurs within discourses beyond the biomedical domain. These forms of "knowing" may be integrated into clinical consideration of efficacious patient assessment and counseling.

An Ada Based Expert System for the Ada Version of SAtool II. Volume 1 and 2

DTIC Science & Technology

1991-06-06

Integrated Computer-Aided Manufacturing (ICAM) (20). In fact, IDEF 0 stands for ICAM Definition Method Zero . IDEF0 defines a subset of SA that omits...reasoning that has been programmed). An expert’s knowledge is specific to one problem domain as opposed to knowledge about general problem-solving...techniques. General problem domains are medicine, finance, science or engineering and so forth in which an expert can solve specific problems very well

The development of children's ability to fill the gaps in their knowledge by consulting experts.

PubMed

Aguiar, Naomi R; Stoess, Caryn J; Taylor, Marjorie

2012-01-01

This research investigated children's ability to recognize gaps in their knowledge and seek missing information from appropriate informants. In Experiment 1, forty-five 4- and 5-year-olds were adept in assigning questions from 3 domains (medicine, firefighting, and farming) to corresponding experts (doctor, firefighter, or farmer). However, when given the options of answering the same questions themselves or assigning them to an expert (Experiment 2), only 6-year-olds were consistently able to recognize when they did not know answers and then assign test questions correctly. Four- and 5-year-olds tended to overestimate their own knowledge or assign questions to the wrong expert. This result was replicated in Experiment 3, in which 5-year-olds were given incentives for correct answers. © 2012 The Authors. Child Development © 2012 Society for Research in Child Development, Inc.

Energy literacy of Indiana high school practical arts and vocational teachers

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

Emshousen, F.W. Jr.

The purpose of the study was to develop an energy knowledge examination, investigate the extent high school teachers of home economics, agriculture, and industrial arts differ in their knowledge of energy, and to ascertain the extent their knowledge of energy differs with personal, educational, and geographic characteristics. Based upon literature review, a subject model was structured according to Bloom's (1956) taxonomy category of Knowledge and Hauenstein's (1972) procedure for classifying knowledges. Energy experts critically evaluated this model, which after refinement, was used to develop an Energy Knowledge Examination. The model consisted of six primary elements: sources, uses, costs, conservation, conversion,more » and policy issues. Energy experts reviewed items for accuracy, relevance, reading level, and clarity. The final instrument (65 multiple choice questions), was administered to a stratified random sample of Indiana public high school (IPHS) teachers from selected disciplines. Findings revealed significant biases among energy experts regarding relevance of specific subject content to the needs of teachers and students. Significant differences in the energy knowledge of IPHS teachers existed only in specific areas of the subject.« less

A brief history and technical review of the expert system research

NASA Astrophysics Data System (ADS)

Tan, Haocheng

2017-09-01

The expert system is a computer system that emulates the decision-making ability of a human expert, which aims to solve complex problems by reasoning knowledge. It is an important branch of artificial intelligence. In this paper, firstly, we briefly introduce the development and basic structure of the expert system. Then, from the perspective of the enabling technology, we classify the current expert systems and elaborate four expert systems: The Rule-Based Expert System, the Framework-Based Expert System, the Fuzzy Logic-Based Expert System and the Expert System Based on Neural Network.

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.

Development of a component centered fault monitoring and diagnosis knowledge based system for space power system

NASA Technical Reports Server (NTRS)

Lee, S. C.; Lollar, Louis F.

1988-01-01

The overall approach currently being taken in the development of AMPERES (Autonomously Managed Power System Extendable Real-time Expert System), a knowledge-based expert system for fault monitoring and diagnosis of space power systems, is discussed. The system architecture, knowledge representation, and fault monitoring and diagnosis strategy are examined. A 'component-centered' approach developed in this project is described. Critical issues requiring further study are identified.

[Translation, cultural adaptation and validation of the Salt Knowledge Questionnaire to the Spanish language].

PubMed

Quinteros-Reyes, C; Marcionelli-Sandhaus, T; Mayta-Tristán, P

2017-11-03

In order to reduce salt consumption in Spanish speaking countries it is necessary to know the level of salt knowledge in the population. However, there are no tools in Spanish to measure salt knowledge, but the only valid tool of measurement is the 'Salt Knowledge Questionnaire' (SKQ) developed in Australia, in English. A validation study was conducted in three phases: (Phase1) Translation of the original Australian version into Spanish; (Phase2) Cultural adaptation based on a Spanish-speaking population such as Peru and following criteria used in the development of the original questionnaire which was evaluated by a panel of experts; (Phase3) Construct validity by comparing the scores of three groups (experts, medical students and non-experts) and reliability by performing a test retest. The translation of the SKQ into Spanish maintained a semantic equivalence with the original questionnaire and a panel of experts accepted the cultural adaptation. The SKQ enables discrimination between those who know and those who do not because differences of scores were found between the group of experts, students and non-experts (P<.001). A good overall internal consistency of the instrument was found (KR20=0.69) and a good overall intraclass correlation (0.79) and no test variations in test-retest (P>.05). The SKQ questionnaire in Spanish is valid, reliable and is a suitable first tool to measure knowledge about salt in the Spanish language. It is considered possible to adapt it culturally to the Spanish-speaking country that wishes to use it. Copyright © 2017 SEH-LELHA. Publicado por Elsevier España, S.L.U. All rights reserved.

Predicting landscape connectivity for the Asian elephant in its largest remaining subpopulation

Treesearch

J.-P. Puyravaud; Samuel Cushman; P. Davidar; D. Madappa

2016-01-01

Landscape connectivity between protected areas is crucial for the conservation of megafauna. But often, corridor identification relies on expert knowledge that is subjective and not spatially synoptic. Landscape analysis allows generalization of expert knowledge when satellite tracking or genetic data are not available. The Nilgiri Biosphere Reserve in southern India...

The Instructional Developer, Expert Systems, and the Front End Process.

ERIC Educational Resources Information Center

Dills, Charles R.; Romiszowski, Alexander

This paper is intended to provide the instructional technologist already possessing some understanding of expert systems with some insight into two of the many steps involved in the design and production of such systems: knowledge acquisition and knowledge structuring or representation. It is also intended to help technologists to see how they…

How Instructional Design Experts Use Knowledge and Experience to Solve Ill-Structured Problems

ERIC Educational Resources Information Center

Ertmer, Peggy A.; Stepich, Donald A.; York, Cindy S.; Stickman, Ann; Wu, Xuemei (Lily); Zurek, Stacey; Goktas, Yuksel

2008-01-01

This study examined how instructional design (ID) experts used their prior knowledge and previous experiences to solve an ill-structured instructional design problem. Seven experienced designers used a think-aloud procedure to articulate their problem-solving processes while reading a case narrative. Results, presented in the form of four…

Concepts of Teacher Knowledge as Social Strategies

ERIC Educational Resources Information Center

Johannesson, Ingolfur Asgeir

2006-01-01

This article reviews didactical and psychologically based research on teachers' work and teacher thinking, narrative educational inquiry and studies of change in teachers' work and places them in the context of sociological theory about expert work and symbolic capital. The work of Abbott on the structure of expert work and knowledge, and Bourdieu…

"Let Your Data Tell a Story:" Climate Change Experts and Students Navigating Disciplinary Argumentation in the Classroom

ERIC Educational Resources Information Center

Walsh, Elizabeth Mary; McGowan, Veronica Cassone

2017-01-01

Science education trends promote student engagement in authentic knowledge in practice to tackle personally consequential problems. This study explored how partnering scientists and students on a social media platform supported students' development of disciplinary practice knowledge through practice-based learning with experts during two pilot…

Influence of Domain Knowledge on Monitoring Performance across the Life Span

ERIC Educational Resources Information Center

Löffler, Elisabeth; von der Linden, Nicole; Schneider, Wolfgang

2016-01-01

Two studies were conducted to investigate effects of domain knowledge on metacognitive monitoring across the life span in materials of different complexity. Participants from 4 age groups (3rd-grade children, adolescents, younger and older adults) were compared using an expert-novice paradigm. In Study 1, soccer experts' and novices'…

The Significance of Practical Training in Linking Theoretical Studies with Practice

ERIC Educational Resources Information Center

Katajavuori, Nina; Lindblom-Ylanne, Sari; Hirvonen, Jouni

2006-01-01

Today's experts must continuously reconstruct their expertise and be able to apply their theoretical knowledge in actual work. The development of expertise is a long process, during which theoretical, practical and metacognitive elements of expert knowledge are integrated into a coherent whole. It is important to foster student's learning and…

Decision support system for nursing management control

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

Ernst, C.J.

A knowledge representation approach for expert systems supporting decision processes in business is proposed. A description of a knowledge representation schema using a logic programming metalanguage is described, then the role of such a schema in a management expert system is demonstrated through the problem of nursing management control in hospitals. 18 references.

Information/Knowledge Acquisition Methods for Decision Support Systems and Expert Systems.

ERIC Educational Resources Information Center

Yang, Heng-Li

1995-01-01

Compares information requirement-elicitation (IRE) methods for decision support systems (DSS) with knowledge acquisition (KA) methods for expert systems (ES) development. The definition and architectures of ES and DSS are compared and the systems' development cycles and IRE/KA methods are discussed. Differences are noted between ES and DSS…

Renewable energy education and industrial arts: linking knowledge producers with knowledge

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

Foley, R.L.

This study introduces renewable energy technology into the industrial arts programs in the State of New Hampshire by providing the following information for decision making: (1) a broad-based perspective on renewable energy technology; (2) the selection of an educational change model; (3) data from a needs analysis; (4) an initial screening of potential teacher-trainers. The Wolf-Welsh Linkage Model was selected as the knowledge production/utilization model for bridging the knowledge gap between renewable energy experts and industrial arts teachers. Ninety-six renewable energy experts were identified by a three-step peer nomination process (92% response rate). The experts stressed the conceptual foundations, economicmore » justifications, and the scientific and quantitative basics of renewable energy technology. The teachers focused on wood-burning technology, educational strategies, and the more popular alternative energy sources such as windpower, hydropower, photovoltaics, and biomass. The most emphatic contribution of the needs analysis was the experts' and teachers' shared perception that residential/commercial building design, retrofitting, and construction is the single most important practical, technical area for the application of renewable energy technology.« less

What Is An Expert System? ERIC Digest.

ERIC Educational Resources Information Center

Boss, Richard W.

This digest describes and defines the various components of an expert system, e.g., a computerized tool designed to enhance the quality and availability of knowledge required by decision makers. It is noted that expert systems differ from conventional applications software in the following areas: (1) the existence of the expert systems shell, or…

RAMBOT: A Connectionist Expert System That Learns by Example.

ERIC Educational Resources Information Center

Mozer, Michael C.

One solution to the problem of getting expert knowledge into expert systems would be to endow the systems with powerful learning procedures that could discover appropriate behaviors by observing an expert in action. A promising source of such learning procedures can be found in recent work on connectionist networks, which are massively parallel…

Expert Systems: Implications for the Diagnosis and Treatment of Learning Disabilities.

ERIC Educational Resources Information Center

Hofmeister, Alan M.; Lubke, Margaret M.

1988-01-01

The article examines characteristics and present or potential applications of expert systems technology for diagnosis and treatment of learning disabilities. Preliminary findings indicate that expert systems can perform as well as humans in specific areas, and that the process of organizing knowledge bases for expert systems helps clarify existing…

An Analysis of the Working Memories of Expert Sport Instructors

ERIC Educational Resources Information Center

McCullick, Bryan; Schempp, Paul; Hsu, Shan-Hui; Jung, Jin Hong; Vickers, Brad; Schuknecht, Greg

2006-01-01

A distinguishing characteristic of expert teachers appears to be an excellent memory (Berliner, 1986; Tan, 1997). Possessing an excellent memory aids experts in building a substantial knowledge base relative to teaching and learning. Despite its importance, the memory skills of expert teachers have yet to be investigated. Therefore, the purpose of…

Knowledge-based expert systems and a proof-of-concept case study for multiple sequence alignment construction and analysis.

PubMed

Aniba, Mohamed Radhouene; Siguenza, Sophie; Friedrich, Anne; Plewniak, Frédéric; Poch, Olivier; Marchler-Bauer, Aron; Thompson, Julie Dawn

2009-01-01

The traditional approach to bioinformatics analyses relies on independent task-specific services and applications, using different input and output formats, often idiosyncratic, and frequently not designed to inter-operate. In general, such analyses were performed by experts who manually verified the results obtained at each step in the process. Today, the amount of bioinformatics information continuously being produced means that handling the various applications used to study this information presents a major data management and analysis challenge to researchers. It is now impossible to manually analyse all this information and new approaches are needed that are capable of processing the large-scale heterogeneous data in order to extract the pertinent information. We review the recent use of integrated expert systems aimed at providing more efficient knowledge extraction for bioinformatics research. A general methodology for building knowledge-based expert systems is described, focusing on the unstructured information management architecture, UIMA, which provides facilities for both data and process management. A case study involving a multiple alignment expert system prototype called AlexSys is also presented.

Knowledge-based expert systems and a proof-of-concept case study for multiple sequence alignment construction and analysis

PubMed Central

Aniba, Mohamed Radhouene; Siguenza, Sophie; Friedrich, Anne; Plewniak, Frédéric; Poch, Olivier; Marchler-Bauer, Aron

2009-01-01

The traditional approach to bioinformatics analyses relies on independent task-specific services and applications, using different input and output formats, often idiosyncratic, and frequently not designed to inter-operate. In general, such analyses were performed by experts who manually verified the results obtained at each step in the process. Today, the amount of bioinformatics information continuously being produced means that handling the various applications used to study this information presents a major data management and analysis challenge to researchers. It is now impossible to manually analyse all this information and new approaches are needed that are capable of processing the large-scale heterogeneous data in order to extract the pertinent information. We review the recent use of integrated expert systems aimed at providing more efficient knowledge extraction for bioinformatics research. A general methodology for building knowledge-based expert systems is described, focusing on the unstructured information management architecture, UIMA, which provides facilities for both data and process management. A case study involving a multiple alignment expert system prototype called AlexSys is also presented. PMID:18971242

Computer Based Expert Systems.

ERIC Educational Resources Information Center

Parry, James D.; Ferrara, Joseph M.

1985-01-01

Claims knowledge-based expert computer systems can meet needs of rural schools for affordable expert advice and support and will play an important role in the future of rural education. Describes potential applications in prediction, interpretation, diagnosis, remediation, planning, monitoring, and instruction. (NEC)

Machine learning research 1989-90

NASA Technical Reports Server (NTRS)

Porter, Bruce W.; Souther, Arthur

1990-01-01

Multifunctional knowledge bases offer a significant advance in artificial intelligence because they can support numerous expert tasks within a domain. As a result they amortize the costs of building a knowledge base over multiple expert systems and they reduce the brittleness of each system. Due to the inevitable size and complexity of multifunctional knowledge bases, their construction and maintenance require knowledge engineering and acquisition tools that can automatically identify interactions between new and existing knowledge. Furthermore, their use requires software for accessing those portions of the knowledge base that coherently answer questions. Considerable progress was made in developing software for building and accessing multifunctional knowledge bases. A language was developed for representing knowledge, along with software tools for editing and displaying knowledge, a machine learning program for integrating new information into existing knowledge, and a question answering system for accessing the knowledge base.

A machine independent expert system for diagnosing environmentally induced spacecraft anomalies

NASA Technical Reports Server (NTRS)

Rolincik, Mark J.

1991-01-01

A new rule-based, machine independent analytical tool for diagnosing spacecraft anomalies, the EnviroNET expert system, was developed. Expert systems provide an effective method for storing knowledge, allow computers to sift through large amounts of data pinpointing significant parts, and most importantly, use heuristics in addition to algorithms which allow approximate reasoning and inference, and the ability to attack problems not rigidly defines. The EviroNET expert system knowledge base currently contains over two hundred rules, and links to databases which include past environmental data, satellite data, and previous known anomalies. The environmental causes considered are bulk charging, single event upsets (SEU), surface charging, and total radiation dose.

Passive acquisition of CLIPS rules

NASA Technical Reports Server (NTRS)

Kovarik, Vincent J., Jr.

1991-01-01

The automated acquisition of knowledge by machine has not lived up to expectations, and knowledge engineering remains a human intensive task. Part of the reason for the lack of success is the difference in the cognitive focus of the expert. The expert must shift his or her focus from the subject domain to that of the representation environment. In doing so this cognitive shift introduces opportunity for errors and omissions. Presented here is work that observes the expert interact with a simulation of the domain. The system logs changes in the simulation objects and the expert's actions in response to those changes. This is followed by the application of inductive reasoning to move the domain specific rules observed to general domain rules.

Second CLIPS Conference Proceedings, volume 1

NASA Technical Reports Server (NTRS)

Giarratano, Joseph (Editor); Culbert, Christopher J. (Editor)

1991-01-01

Topics covered at the 2nd CLIPS Conference held at the Johnson Space Center, September 23-25, 1991 are given. Topics include rule groupings, fault detection using expert systems, decision making using expert systems, knowledge representation, computer aided design and debugging expert systems.

Psychology of developing and designing expert systems

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

Tonn, B.; MacGregor, D.

This paper discusses psychological problems relevant to developing and designing expert systems. With respect to the former, the psychological literature suggests that several cognitive biases may affect the elicitation of a valid knowledge base from the expert. The literature also suggests that common expert system inference engines may be quite inconsistent with reasoning heuristics employed by experts. With respect to expert system user interfaces, care should be taken when eliciting uncertainty estimates from users, presenting system conclusions, and ordering questions.

Progress and challenges in the application of artificial intelligence to computational fluid dynamics

NASA Technical Reports Server (NTRS)

Andrews, Alison E.

1987-01-01

An approach to analyzing CFD knowledge-based systems is proposed which is based, in part, on the concept of knowledge-level analysis. Consideration is given to the expert cooling fan design system, the PAN AIR knowledge system, grid adaptation, and expert zonal grid generation. These AI/CFD systems demonstrate that current AI technology can be successfully applied to well-formulated problems that are solved by means of classification or selection of preenumerated solutions.

A multi-method approach to curriculum development for in-service training in China's newly established health emergency response offices.

PubMed

Wang, Yadong; Li, Xiangrui; Yuan, Yiwen; Patel, Mahomed S

2014-01-01

To describe an innovative approach for developing and implementing an in-service curriculum in China for staff of the newly established health emergency response offices (HEROs), and that is generalisable to other settings. The multi-method training needs assessment included reviews of the competency domains needed to implement the International Health Regulations (2005) as well as China's policies and emergency regulations. The review, iterative interviews and workshops with experts in government, academia, the military, and with HERO staff were reviewed critically by an expert technical advisory panel. Over 1600 participants contributed to curriculum development. Of the 18 competency domains identified as essential for HERO staff, nine were developed into priority in-service training modules to be conducted over 2.5 weeks. Experts from academia and experienced practitioners prepared and delivered each module through lectures followed by interactive problem-solving exercises and desktop simulations to help trainees apply, experiment with, and consolidate newly acquired knowledge and skills. This study adds to the emerging literature on China's enduring efforts to strengthen its emergency response capabilities since the outbreak of SARS in 2003. The multi-method approach to curriculum development in partnership with senior policy-makers, researchers, and experienced practitioners can be applied in other settings to ensure training is responsive and customized to local needs, resources and priorities. Ongoing curriculum development should reflect international standards and be coupled with the development of appropriate performance support systems at the workplace for motivating staff to apply their newly acquired knowledge and skills effectively and creatively.

Family Planning Policy Environment in the Democratic Republic of the Congo: Levers of Positive Change and Prospects for Sustainability.

PubMed

Mukaba, Thibaut; Binanga, Arsene; Fohl, Sarah; Bertrand, Jane T

2015-06-17

Building on expressed support from the Prime Minister to the Ministries of Health and Planning, the country's new family planning commitment grew out of: (1) recognition of the impact of family planning on maternal mortality and economic development; (2) knowledge sharing of best practices from other African countries; (3) participatory development of a national strategic plan; (4) strong collaboration between stakeholders; (5) effective advocacy by champions including country and international experts; and (6) increased donor support. The question becomes: Will the favorable policy environment translate into effective local programming?

Are Places Concepts? Familarity and Expertise Effects in Neighborhood Cognition

NASA Astrophysics Data System (ADS)

Davies, Clare

Named urban neighborhoods (localities) are often examples of vague place extents. These are compared with current knowledge of vagueness in concepts and categories within semantic memory, implying graded membership and typicality. If places are mentally constructed and used like concepts, this might account for their cognitive variability, and help us choose suitable geospatial (GIS) data models. An initial within-subjects study with expert geographic surveyors tested specific predictions about the role of central tendency, ideals, context specificity, familiarity and expertise in location judgements - theoretically equivalent to categorization. Implications for spatial data models and a further research agenda are suggested.

A Description of the Strategic Knowledge of Experts Solving Transmission Genetics Problems.

ERIC Educational Resources Information Center

Collins, Angelo

Descriptions of the problem-solving strategies of experts solving realistic, computer-generated transmission genetics problems are presented in this paper and implications for instruction are discussed. Seven experts were involved in the study. All of the experts had a doctoral degree and experience in both teaching and doing research in genetics.…

The Potential of Computer-Based Expert Systems for Special Educators in Rural Settings.

ERIC Educational Resources Information Center

Parry, James D.; Ferrara, Joseph M.

Knowledge-based expert computer systems are addressing issues relevant to all special educators, but are particularly relevant in rural settings where human experts are less available because of distance and cost. An expert system is an application of artificial intelligence (AI) that typically engages the user in a dialogue resembling the…

Expert system for skin problem consultation in Thai traditional medicine.

PubMed

Nopparatkiat, Pornchai; na Nagara, Byaporn; Chansa-ngavej, Chuvej

2014-01-01

This paper aimed to demonstrate the research and development of a rule-based expert system for skin problem consulting in the areas of acne, melasma, freckle, wrinkle, and uneven skin tone, with recommended treatments from Thai traditional medicine knowledge. The tool selected for developing the expert system is a software program written in the PHP language. MySQL database is used to work together with PHP for building database of the expert system. The system is web-based and can be reached from anywhere with Internet access. The developed expert system gave recommendations on the skin problem treatment with Thai herbal recipes and Thai herbal cosmetics based on 416 rules derived from primary and secondary sources. The system had been tested by 50 users consisting of dermatologists, Thai traditional medicine doctors, and general users. The developed system was considered good for learning and consultation. The present work showed how such a scattered body of traditional knowledge as Thai traditional medicine and herbal recipes could be collected, organised and made accessible to users and interested parties. The expert system developed herein should contribute in a meaningful way towards preserving the knowledge and helping promote the use of Thai traditional medicine as a practical alternative medicine for the treatment of illnesses.

Impact of Secondary Students' Content Knowledge on Their Communication Skills in Science

ERIC Educational Resources Information Center

Kulgemeyer, Christoph

2018-01-01

The "expert blind spot" (EBS) hypothesis implies that even some experts with a high content knowledge might have problems in science communication because they are using the structure of the content rather than their addressee's prerequisites as an orientation. But is that also true for students? Explaining science to peers is a crucial…

Using Historical Knowledge to Reason about Contemporary Political Issues: An Expert-Novice Study

ERIC Educational Resources Information Center

Shreiner, Tamara L.

2014-01-01

People often justify history's place in the curriculum by its relationship to citizenship, yet there is little research to help educators picture how people use historical knowledge for civic purposes. This expert-novice study used the think-aloud method to examine how eight political scientists and eight high school students employed…

Relative Expertise in an Everyday Reasoning Task: Epistemic Understanding, Problem Representation, and Reasoning Competence

ERIC Educational Resources Information Center

Weinstock, Michael

2009-01-01

Experts in cognitive domains differ from non-experts in how they represent problems and knowledge, and in their epistemic understandings of tasks in their domain of expertise. This study investigates whether task-specific epistemic understanding also underlies the representation of knowledge on an everyday reasoning task on which the competent…

Development and Validation of Pre-Service Teachers' Personal Epistemologies of Teaching Scale (PT-PETS)

ERIC Educational Resources Information Center

Yu, Ji Hyun

2013-01-01

The Internet has changed not only how we conceptualize knowledge, but also how we learn in classroom. Knowledge is not any longer transmitted from experts to non-experts, but is constructed through communication, collaboration, and integration among a network of people. In this context, teachers are expected to facilitate student-centered learning…

The Development of Children's Ability to Fill the Gaps in Their Knowledge by Consulting Experts

ERIC Educational Resources Information Center

Aguiar, Naomi R.; Stoess, Caryn J.; Taylor, Marjorie

2012-01-01

This research investigated children's ability to recognize gaps in their knowledge and seek missing information from appropriate informants. In Experiment 1, forty-five 4- and 5-year-olds were adept in assigning questions from 3 domains (medicine, firefighting, and farming) to corresponding experts (doctor, firefighter, or farmer). However, when…

Cognitive Task Analysis for Instruction in Single-Injection Ultrasound Guided-Regional Anesthesia

ERIC Educational Resources Information Center

Gucev, Gligor V.

2012-01-01

Cognitive task analysis (CTA) is methodology for eliciting knowledge from subject matter experts. CTA has been used to capture the cognitive processes, decision-making, and judgments that underlie expert behaviors. A review of the literature revealed that CTA has not yet been used to capture the knowledge required to perform ultrasound guided…

Experiments in Knowledge Refinement for a Large Rule-Based System

DTIC Science & Technology

1993-08-01

empirical analysis to refine expert system knowledge bases. Aritificial Intelligence , 22:23-48, 1984. *! ...The Addison- Weslev series in artificial intelligence . Addison-Weslev. Reading, Massachusetts. 1981. Cooke, 1991: ttoger M. Cooke. Experts in...ment for classification systems. Artificial Intelligence , 35:197-226, 1988. 14 Overall, we believe that it will be possible to build a heuristic system

A Novice-Expert Study of Modeling Skills and Knowledge Structures about Air Quality

ERIC Educational Resources Information Center

Hsu, Ying-Shao; Lin, Li-Fen; Wu, Hsin-Kai; Lee, Dai-Ying; Hwang, Fu-Kwun

2012-01-01

This study compared modeling skills and knowledge structures of four groups as seen in their understanding of air quality. The four groups were: experts (atmospheric scientists), intermediates (upper-level graduate students in a different field), advanced novices (talented 11th and 12th graders), and novices (10th graders). It was found that when…

A True Delphi Approach: Developing a Tailored Curriculum in Response to Local Agriscience Need

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

Rubenstein, Eric; Thoron, Andrew; Burleson, Sarah

2012-02-07

The Delphi approach is a structured communication technique, developed as a systematic, interactive forecasting method which relies on a panel of experts. In this specific case experts from Industry, Education and Extension fields addressed needs for educational programs in a traditional agriculturally-based community, environmentally conscious practices in order to restore environmental integrity and multi-disciplinary approach to solve sustainability problems facing the agricultural industry. The experts were divided into two main groups, (A) Secondary and (B) Post-secondary, and answered questionnaires in three rounds: • 1st Round – Participants generated a list of knowledge, skills, and competencies followed • 2nd Round –more » Panelists rated each item • 3rd Round – Panelists were given the opportunity to combine and add additional items As a result, top six items from both groups were not found similar, secondary panelists centralized around employment skills and post-secondary panelists focused on content areas. Implications include a need for content-based curriculum for post-secondary graduates, utilization of true-Delphi technique for future curriculum development research and further examination of students that complete secondary and post-secondary programs in biofuels/sustainable agriculture.« less

Expert knowledge in palliative care on the World Wide Web: palliativedrugs.org.

PubMed

Gavrin, Jonathan

2009-01-01

In my last Internet-related article, I speculated that social networking would be the coming wave in the effort to share knowledge among experts in various disciplines. At the time I did not know that a palliative care site on the World Wide Web (WWW), palliativedrugs.com, already provided the infrastructure for sharing expert knowledge in the field. The Web site is an excellent traditional formulary but it is primarily devoted to "unlicensed" ("off-label") use of medications in palliative care, something we in the specialty often do with little to support our interventions except shared knowledge and experience. There is nothing fancy about this Web site. In a good way, its format is a throwback to Web sites of the 1990s. In only the loosest sense can one describe it as "multimedia." Yet, it provides the perfect forum for expert knowledge and is a "must see" resource. Its existing content is voluminous and reliable, filtered and reviewed by renowned clinicians and educators in the field. Although its origin and structure were not specifically designed for social or professional networking, the Web site's format makes it a natural way for practitioners around the world to contribute to an ever-growing body of expertise in palliative care.

Cognitive task analysis for instruction in single-injection ultrasound guided-regional anesthesia

NASA Astrophysics Data System (ADS)

Gucev, Gligor V.

Cognitive task analysis (CTA) is methodology for eliciting knowledge from subject matter experts. CTA has been used to capture the cognitive processes, decision-making, and judgments that underlie expert behaviors. A review of the literature revealed that CTA has not yet been used to capture the knowledge required to perform ultrasound guided regional anesthesia (UGRA). The purpose of this study was to utilize CTA to extract knowledge from UGRA experts and to determine whether instruction based on CTA of UGRA will produce results superior to the results of traditional training. This study adds to the knowledge base of CTA in being the first one to effectively capture the expert knowledge of UGRA. The derived protocol was used in a randomized, double blinded experiment involving UGRA instruction to 39 novice learners. The results of this study strongly support the hypothesis that CTA-based instruction in UGRA is more effective than conventional clinical instruction, as measured by conceptual pre- and post-tests, performance of a simulated UGRA procedure, and time necessary for the task performance. This study adds to the number of studies that have proven the superiority of CTA-informed instruction. Finally, it produced several validated instruments that can be used in instructing and evaluating UGRA.

EDNA: Expert fault digraph analysis using CLIPS

NASA Technical Reports Server (NTRS)

Dixit, Vishweshwar V.

1990-01-01

Traditionally fault models are represented by trees. Recently, digraph models have been proposed (Sack). Digraph models closely imitate the real system dependencies and hence are easy to develop, validate and maintain. However, they can also contain directed cycles and analysis algorithms are hard to find. Available algorithms tend to be complicated and slow. On the other hand, the tree analysis (VGRH, Tayl) is well understood and rooted in vast research effort and analytical techniques. The tree analysis algorithms are sophisticated and orders of magnitude faster. Transformation of a digraph (cyclic) into trees (CLP, LP) is a viable approach to blend the advantages of the representations. Neither the digraphs nor the trees provide the ability to handle heuristic knowledge. An expert system, to capture the engineering knowledge, is essential. We propose an approach here, namely, expert network analysis. We combine the digraph representation and tree algorithms. The models are augmented by probabilistic and heuristic knowledge. CLIPS, an expert system shell from NASA-JSC will be used to develop a tool. The technique provides the ability to handle probabilities and heuristic knowledge. Mixed analysis, some nodes with probabilities, is possible. The tool provides graphics interface for input, query, and update. With the combined approach it is expected to be a valuable tool in the design process as well in the capture of final design knowledge.

Recommended practices for computerized clinical decision support and knowledge management in community settings: a qualitative study

PubMed Central

2012-01-01

Background The purpose of this study was to identify recommended practices for computerized clinical decision support (CDS) development and implementation and for knowledge management (KM) processes in ambulatory clinics and community hospitals using commercial or locally developed systems in the U.S. Methods Guided by the Multiple Perspectives Framework, the authors conducted ethnographic field studies at two community hospitals and five ambulatory clinic organizations across the U.S. Using a Rapid Assessment Process, a multidisciplinary research team: gathered preliminary assessment data; conducted on-site interviews, observations, and field surveys; analyzed data using both template and grounded methods; and developed universal themes. A panel of experts produced recommended practices. Results The team identified ten themes related to CDS and KM. These include: 1) workflow; 2) knowledge management; 3) data as a foundation for CDS; 4) user computer interaction; 5) measurement and metrics; 6) governance; 7) translation for collaboration; 8) the meaning of CDS; 9) roles of special, essential people; and 10) communication, training, and support. Experts developed recommendations about each theme. The original Multiple Perspectives framework was modified to make explicit a new theoretical construct, that of Translational Interaction. Conclusions These ten themes represent areas that need attention if a clinic or community hospital plans to implement and successfully utilize CDS. In addition, they have implications for workforce education, research, and national-level policy development. The Translational Interaction construct could guide future applied informatics research endeavors. PMID:22333210

Investigating Public trust in Expert Knowledge: Narrative, Ethics, and Engagement.

PubMed

Camporesi, Silvia; Vaccarella, Maria; Davis, Mark

2017-03-01

"Public Trust in Expert Knowledge: Narrative, Ethics, and Engagement" examines the social, cultural, and ethical ramifications of changing public trust in the expert biomedical knowledge systems of emergent and complex global societies. This symposium was conceived as an interdisciplinary project, drawing on bioethics, the social sciences, and the medical humanities. We settled on public trust as a topic for our work together because its problematization cuts across our fields and substantive research interests. For us, trust is simultaneously a matter of ethics, social relations, and the cultural organization of meaning. We share a commitment to narrative inquiry across our fields of expertise in the bioethics of transformative health technologies, public communications on health threats, and narrative medicine. The contributions to this symposium have applied, in different ways and with different effects, this interdisciplinary mode of inquiry, supplying new reflections on public trust, expertise, and biomedical knowledge.

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

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

Expert Systems in Reference Services.

ERIC Educational Resources Information Center

Roysdon, Christine, Ed.; White, Howard D., Ed.

1989-01-01

Eleven articles introduce expert systems applications in library and information science, and present design and implementation issues of system development for reference services. Topics covered include knowledge based systems, prototype development, the use of artificial intelligence to remedy current system inadequacies, and an expert system to…

Let's Talk About Water: Using Film Screenings to Engage Students and the Public in Water Science and Policy

NASA Astrophysics Data System (ADS)

Saleem Arrigo, J. A.; Berry, K.; Hooper, R. P.; Lilienfeld, L.

2013-12-01

"Let's Talk about Water" is a film symposium designed to bring together experts and the public to talk about the complex water issues facing society. The format of the event is quite simple: a panel of experts and the audience view a water documentary (such as "FLOW", "Liquid Assets", or "Gasland") together and there is an extended moderated discussion period following the film between the panel and the audience. Over the course of several events, we have developed best practices that make this simple format very effective. A film creates a context of subject and language for the discussion--it gets the audience and the panel on the same page. The moderators must actively manage the discussion, both challenging the panelists with follow up questions, asking questions to simplify the language the expert is using, and passing a question among panelists to bring out different points of view. The panelists are provided with the film in advance to view and, most importantly, meet the day before the event to discuss the film. This makes for a much more convivial discussion at the event. We have found that these discussions can easily be sustained for 90 to 120 minutes with active audience participation. We have found key element of the event is local relevance. Films should be carefully chosen to resonate with the audience, and the local host is critical in defining the audience, goals and identified panel members. Having local experts from universities and representatives from local water authorities and environmental groups bring a sense of community and a confidence in the audience that the panel members have local knowledge that is important for sustaining discussion. The discussion begins with points raised by the movie (are these issues real? Do they apply here? What are the scientific, engineering, and policy solutions to these problems?) and then segues into a discussion about career opportunities in the water sector, volunteer opportunities in the community or other ways for the audience to get involved. This format has been applied at college campuses with a target audience of lower-level undergraduates, in several universities in the United States and Canada. Additionally, we have held public events (at the NY Public Library, concurrent with World Water Week) and have documented experiences for other educators and researchers who want to employ this format. CUAHSI has created best practice "tips," hosting guides documenting our experiences with individual films, and other information on our website.

Understanding the local public health workforce: labels versus substance.

PubMed

Merrill, Jacqueline A; Keeling, Jonathan W

2014-11-01

The workforce is a key component of the nation's public health (PH) infrastructure, but little is known about the skills of local health department (LHD) workers to guide policy and planning. To profile a sample of LHD workers using classification schemes for PH work (the substance of what is done) and PH job titles (the labeling of what is done) to determine if work content is consistent with job classifications. A secondary analysis was conducted on data collected from 2,734 employees from 19 LHDs using a taxonomy of 151 essential tasks performed, knowledge possessed, and resources available. Each employee was classified by job title using a schema developed by PH experts. The inter-rater agreement was calculated within job classes and congruence on tasks, knowledge, and resources for five exemplar classes was examined. The average response rate was 89%. Overall, workers exhibited moderate agreement on tasks and poor agreement on knowledge and resources. Job classes with higher agreement included agency directors and community workers; those with lower agreement were mid-level managers such as program directors. Findings suggest that local PH workers within a job class perform similar tasks but vary in training and access to resources. Job classes that are specific and focused have higher agreement whereas job classes that perform in many roles show less agreement. The PH worker classification may not match employees' skill sets or how LHDs allocate resources, which may be a contributor to unexplained fluctuation in public health system performance. Copyright © 2014. Published by Elsevier Inc.

Arctic sea-ice syntheses: Charting across scope, scale, and knowledge systems

NASA Astrophysics Data System (ADS)

Druckenmiller, M. L.; Perovich, D. K.; Francis, J. A.

2017-12-01

Arctic sea ice supports and intersects a multitude of societal benefit areas, including regulating regional and global climates, structuring marine food webs, providing for traditional food provisioning by indigenous peoples, and constraining marine shipping and access. At the same time, sea ice is one of the most rapidly changing elements of the Arctic environment and serves as a source of key physical indicators for monitoring Arctic change. Before the present scientific interest in Arctic sea ice for climate research, it has long been, and remains, a focus of applied research for industry and national security. For generations, the icy coastal seas of the North have also provided a basis for the sharing of local and indigenous knowledge between Arctic residents and researchers, including anthropologists, biologists, and geoscientists. This presentation will summarize an ongoing review of existing synthesis studies of Arctic sea ice. We will chart efforts to achieve system-level understanding across geography, temporal scales, and the ecosystem services that Arctic sea ice supports. In doing so, we aim to illuminate the role of interdisciplinary science, together with local and indigenous experts, in advancing knowledge of the roles of sea ice in the Arctic system and beyond, reveal the historical and scientific evolution of sea-ice research, and assess current gaps in system-scale understanding.

Assessing land degradation and acknowledging adaptive policy options to face with changes: an integrated approach applied to a semiarid agropastoral system

NASA Astrophysics Data System (ADS)

Tarrasón, D.; Ravera, F.; Reed, M.; Dougill, A.

2009-04-01

The complexity of assessing land degradation on semiarid systems deals with challenges that have rarely been addressed. Land degradation is a human-induced and permanent reduction of key ecosystem functions and services at different temporal and spatial scale. Initial attempts to assess land degradation at a broader scale were based on expert opinion, however the empirical bases to sustain these estimations are weak and the ecological data are still scarce. In addition, such approaches are essentially subjective and they reflect the objectives and assumptions of those making the assessment, who are rarely land users themselves. Currently, the concept of "land degradation" is debated, and in the last years have emerged a growing number of efforts to develop land degradation participatory assessment methods that could capture a more complex understanding of human-environment interactions. This study proposes an interdisciplinary and hybrid methodology, combining local and scientific knowledge, to assess land degradation in mixed farming systems. Specifically, i) it describes and analyses the mixed farming system and it explores how historically political, social and institutional local factors have interacted with ecological process, ii) it identifies key ecosystem processes and services needed to support the agropastoral systems that are perceived to be under threat from land degradation; iii) it assesses the status and trends of these key ecosystem services; and iv) it identifies and evaluates potential management alternatives to prevent land degradation and cope with changes (e.g. climate change). We show how to achieve, through a co-construction of hybrid knowledge between scientific and farmers, a more accurate and reliable appraisal of land degradation, since farmer's perception is contextualized, dynamic and complex and involves simultaneously multiple temporal and spatial scales and multiple dimensions of analysis that could help the scientific exploration. The study reveals that the ecosystem services' exploration with local actors is a good method to reveal the multiple and sometimes conflictive local strategies and interests at stake. Ecosystem services assessment has also been used as an entry to discuss with local land users about adaptive management strategies to improve soil functions involved in the maintenance of the provision and regulation processes and land productivity that support local livelihoods face to changes. The integrated methodological framework adopted has a positive impact to empower local users, enlarging the access to adequate information and channels of communication between experts/local users, and improving their capacity to use the co-constructed hybrid knowledge. We argue that engaging the relevant and interested actors in the process is key to understand margin of flexibility for dialogue between local users, scientific and policy makers and it is a base for ownership of local actors in decision making processes that facilitates effective soil-land governance. Finally, we discuss how wide institutional changes at different levels are needed to support agro-environmental policies for communities, small and medium farmers and to undertake new adaptive management strategies to cope with uncertainties of future changes.

The implementation of knowledge dissemination in the prevention of occupational skin diseases.

PubMed

Wilke, A; Bollmann, U; Cazzaniga, S; Hübner, A; John, S M; Karadzinska-Bislimovska, J; Mijakoski, D; Šimić, D; Simon, D; Sonsmann, F; Stoleski, S; Weinert, P; Wulfhorst, B

2018-03-01

Occupational skin diseases (OSD) have a high medical, social, economic and political impact. Knowledge dissemination from research activities to key stakeholders involved in health care is a prerequisite to make prevention effective. To study and prioritize different activity fields and stakeholders that are involved in the prevention of OSD, to reflect on their inter-relationships, to develop a strategic approach for knowledge dissemination and to develop a hands-on tool for OSD prevention projects METHODS: Seven different activity fields that are relevant in the prevention of OSD have been stepwise identified. This was followed by an impact analysis. Fifty-five international OSD experts rated the impact and the influence of the activity fields for the prevention of OSD with a standardized questionnaire. Activity fields identified to have a high impact in OSD prevention are the political system, mass media and industry. The political system has a strong but more indirect effect on the general population via the educational system, local public health services or the industry. The educational system, mass media, industry and local public health services have a strong direct impact on the OSD 'at risk' worker. Finally, a hands-on tool for future OSD prevention projects has been developed that addresses knowledge dissemination and different stakeholder needs. Systematic knowledge dissemination is important to make OSD prevention more effective and to close the gap between research and practice. This study provides guidance to identify stakeholders, strategies and dissemination channels for systematic knowledge dissemination which need to be adapted to country-specific structures, for example the social security system and healthcare systems. A key for successful knowledge dissemination is building linkages among different stakeholders, building strategic partnerships and gaining their support right from the inception phase of a project. © 2017 European Academy of Dermatology and Venereology.

An Expert System for Automating Nuclear Strike Aircraft Replacement, Aircraft Beddown, and Logistics Movement for the Theater Warfare Exercise.

DTIC Science & Technology

1989-12-01

that can be easily understood. (9) Parallelism. Several system components may need to execute in parallel. For example, the processing of sensor data...knowledge base are not accessible for processing by the database. Also in the likely case that the expert system poses a series of related queries, the...hiharken nxpfilcs’Iog - Knowledge base for the automation of loCgistics rr-ovenet T’he Ii rectorY containing the strike aircraft replacement knowledge base

Management of complex knowledge in planning for sustainable development: The use of multi-criteria decision aids

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

Kain, Jaan-Henrik; Soederberg, Henriette

2008-01-15

The vision of sustainable development entails new and complex planning situations, confronting local policy makers with changing political conditions, different content in decision making and planning and new working methods. Moreover, the call for sustainable development has been a major driving force towards an increasingly multi-stakeholder planning system. This situation requires competence in working in, and managing, groups of actors, including not only experts and project owners but also other categories of stakeholders. Among other qualities, such competence requires a working strategy aimed at integrating various, and sometimes incommensurable, forms of knowledge to construct a relevant and valid knowledge basemore » prior to decision making. Consequently, there lies great potential in methods that facilitate the evaluation of strategies for infrastructural development across multiple knowledge areas, so-called multi-criteria decision aids (MCDAs). In the present article, observations from six case studies are discussed, where the common denominators are infrastructural planning, multi-stakeholder participation and the use of MCDAs as interactive decision support. Three MCDAs are discussed - NAIADE, SCA and STRAD - with an emphasis on how they function in their procedural context. Accordingly, this is not an analysis of MCDA algorithms, of software programming aspects or of MCDAs as context-independent 'decision machines'-the focus is on MCDAs as actor systems, not as expert systems. The analysis is carried out across four main themes: (a) symmetrical management of different forms of knowledge; (b) management of heterogeneity, pluralism and conflict; (c) functionality and ease of use; and (d) transparency and trust. It shows that STRAD, by far, seems to be the most useful MCDA in interactive settings. NAIADE and SCA are roughly equivalent but have their strengths and weaknesses in different areas. Moreover, it was found that some MCDA issues require further attention, i.e., regarding transparency and understandability; qualitative/quantitative knowledge input; switching between different modes of weighting; software flexibility; as well as graphic and user interfaces.« less

Improving Medical Students' Application of Knowledge and Clinical Decision-Making Through a Porcine-Based Integrated Cardiac Basic Science Program.

PubMed

Stott, Martyn Charles; Gooseman, Michael Richard; Briffa, Norman Paul

2016-01-01

Despite the concerted effort of modern undergraduate curriculum designers, the ability to integrate basic sciences in clinical rotations is an ongoing problem in medical education. Students and newly qualified doctors themselves report worry about the effect this has on their clinical performance. There are examples in the literature to support development of attempts at integrating such aspects, but this "vertical integration" has proven to be difficult. We designed an expert-led integrated program using dissection of porcine hearts to improve the use of cardiac basic sciences in clinical medical students' decision-making processes. To our knowledge, this is the first time in the United Kingdom that an animal model has been used to teach undergraduate clinical anatomy to medical students to direct wider application of knowledge. Action research methodology was used to evaluate the local curriculum and assess learners needs, and the agreed teaching outcomes, methods, and delivery outline were established. A total of 18 students in the clinical years of their degree program attended, completing precourse and postcourse multichoice questions examinations and questionnaires to assess learners' development. Student's knowledge scores improved by 17.5% (p = 0.01; students t-test). Students also felt more confident at applying underlying knowledge to decision-making and diagnosis in clinical medicine. An expert teacher (consultant surgeon) was seen as beneficial to students' understanding and appreciation. This study outlines how the development of a teaching intervention using porcine-based methods successfully improved both student's knowledge and application of cardiac basic sciences. We recommend that clinicians fully engage with integrating previously learnt underlying sciences to aid students in developing decision-making and diagnostic skills as well as a deeper approach to learning. Copyright © 2016 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

The Shrinkage Model And Expert System Of Plastic Lens Formation

NASA Astrophysics Data System (ADS)

Chang, Rong-Seng

1988-06-01

Shrinkage causes both the appearance & dimension defects of the injected plastic lens. We have built up a model of state equations with the help of finite element analysis program to estimate the volume change (shrinkage and swelling) under the combinations of injection variables such as pressure and temperature etc., then the personal computer expert system has been build up to make that knowledge conveniently available to the user in the model design, process planning, process operation and some other work. The domain knowledge is represented by a R-graph (Relationship-graph) model which states the relationships of variables & equations. This model could be compare with other models in the expert system. If the user has better model to solve the shrinkage problem, the program will evaluate it automatically and a learning file will be trigger by the expert system to teach the user to update their knowledge base and modify the old model by this better model. The Rubin's model and Gilmore's model have been input to the expert system. The conflict has been solved both from the user and the deeper knowledge base. A cube prism and the convex lens examples have been shown in this paper. This program is written by MULISP language in IBM PC-AT. The natural language provides English Explaination of know why and know how and the automatic English translation for the equation rules and the production rules.

The NSF-RCN Urban Heat Island Network

NASA Astrophysics Data System (ADS)

Snyder, P. K.; Twine, T. E.; Hamilton, P.; Shepherd, M.; Stone, B., Jr.

2016-12-01

In much of the world cities are warming at twice the rate of outlying rural areas. The frequency of urban heat waves is projected to increase with climate change through the 21st century. Addressing the economic, environmental, and human costs of urban heat islands requires a better understanding of their behavior from many disciplinary perspectives. The goal of this four-year Urban Heat Island Network is to (1) bring together scientists studying the causes and impacts of urban warming, (2) advance multidisciplinary understanding of urban heat islands, (3) examine how they can be ameliorated through engineering and design practices, and (4) share these new insights with a wide array of stakeholders responsible for managing urban warming to reduce their health, economic, and environmental impacts. The NSF-RCN Urban Heat Island Network involves atmospheric scientists, engineers, architects, landscape designers, urban planners, public health experts, and education and outreach experts, who will share knowledge, evaluate research directions, and communicate knowledge and research recommendations to the larger research community as well as stakeholders engaged in developing strategies to adapt to and mitigate urban warming. The first Urban Climate Institute was held in Saint Paul, MN in July 2013 and focused on the characteristics of urban heat islands. Scientists engaged with local practitioners to improve communication pathways surrounding issues of understanding, adapting to, and mitigating urban warming. The second Urban Climate Institute was held in Atlanta, Georgia in July 2014 and focused on urban warming and public health. The third Urban Climate Institute was held in Athens, GA in July 2015 and focused on urban warming and the role of the built environment. Scientists and practitioners discussed strategies for mitigation and adaptation. The fourth Institute was held in Saint Paul, MN in July 2016 and focused on putting research to practice. Evaluation experts at the Science Museum of Minnesota have extensively evaluated the Institutes to inform other research coordination networks and to identify effective ways that researchers and practitioners can share knowledge and communicate more effectively.

Real Time Data System (RTDS)

NASA Technical Reports Server (NTRS)

Muratore, John F.

1991-01-01

Lessons learned from operational real time expert systems are examined. The basic system architecture is discussed. An expert system is any software that performs tasks to a standard that would normally require a human expert. An expert system implies knowledge contained in data rather than code. And an expert system implies the use of heuristics as well as algorithms. The 15 top lessons learned by the operation of a real time data system are presented.

A hierarchically distributed architecture for fault isolation expert systems on the space station

NASA Technical Reports Server (NTRS)

Miksell, Steve; Coffer, Sue

1987-01-01

The Space Station Axiomatic Fault Isolating Expert Systems (SAFTIES) system deals with the hierarchical distribution of control and knowledge among independent expert systems doing fault isolation and scheduling of Space Station subsystems. On its lower level, fault isolation is performed on individual subsystems. These fault isolation expert systems contain knowledge about the performance requirements of their particular subsystem and corrective procedures which may be involved in repsonse to certain performance errors. They can control the functions of equipment in their system and coordinate system task schedules. On a higher level, the Executive contains knowledge of all resources, task schedules for all systems, and the relative priority of all resources and tasks. The executive can override any subsystem task schedule in order to resolve use conflicts or resolve errors that require resources from multiple subsystems. Interprocessor communication is implemented using the SAFTIES Communications Interface (SCI). The SCI is an application layer protocol which supports the SAFTIES distributed multi-level architecture.

Sherlock Holmes: an expert's view of expertise.

PubMed

André, Didierjean; Fernand, Gobet

2008-02-01

In recent years, there has been an intense research effort to understand the cognitive processes and structures underlying expert behaviour. Work in different fields, including scientific domains, sports, games and mnemonics, has shown that there are vast differences in perceptual abilities between experts and novices, and that these differences may underpin other cognitive differences in learning, memory and problem solving. In this article, we evaluate the progress made in the last years through the eyes of an outstanding, albeit fictional, expert: Sherlock Holmes. We first use the Sherlock Holmes character to illustrate expert processes as described by current research and theories. In particular, the role of perception, as well as the nature and influence of expert knowledge, are all present in the description of Conan Doyle's hero. In the second part of the article, we discuss a number of issues that current research on expertise has barely addressed. These gaps include, for example, several forms of reasoning, the influence of emotions on cognition, and the effect of age on experts' knowledge and cognitive processes. Thus, although nearly 120-year-old, Conan Doyle's books show remarkable illustrations of expert behaviour, including the coverage of themes that have mostly been overlooked by current research.

Real-time diagnostics for a reusable rocket engine

NASA Technical Reports Server (NTRS)

Guo, T. H.; Merrill, W.; Duyar, A.

1992-01-01

A hierarchical, decentralized diagnostic system is proposed for the Real-Time Diagnostic System component of the Intelligent Control System (ICS) for reusable rocket engines. The proposed diagnostic system has three layers of information processing: condition monitoring, fault mode detection, and expert system diagnostics. The condition monitoring layer is the first level of signal processing. Here, important features of the sensor data are extracted. These processed data are then used by the higher level fault mode detection layer to do preliminary diagnosis on potential faults at the component level. Because of the closely coupled nature of the rocket engine propulsion system components, it is expected that a given engine condition may trigger more than one fault mode detector. Expert knowledge is needed to resolve the conflicting reports from the various failure mode detectors. This is the function of the diagnostic expert layer. Here, the heuristic nature of this decision process makes it desirable to use an expert system approach. Implementation of the real-time diagnostic system described above requires a wide spectrum of information processing capability. Generally, in the condition monitoring layer, fast data processing is often needed for feature extraction and signal conditioning. This is usually followed by some detection logic to determine the selected faults on the component level. Three different techniques are used to attack different fault detection problems in the NASA LeRC ICS testbed simulation. The first technique employed is the neural network application for real-time sensor validation which includes failure detection, isolation, and accommodation. The second approach demonstrated is the model-based fault diagnosis system using on-line parameter identification. Besides these model based diagnostic schemes, there are still many failure modes which need to be diagnosed by the heuristic expert knowledge. The heuristic expert knowledge is implemented using a real-time expert system tool called G2 by Gensym Corp. Finally, the distributed diagnostic system requires another level of intelligence to oversee the fault mode reports generated by component fault detectors. The decision making at this level can best be done using a rule-based expert system. This level of expert knowledge is also implemented using G2.

Health Disparities and Toxicant Exposure of Akwesasne Mohawk Young Adults: A Partnership Approach to Research

PubMed Central

Schell, Lawrence M.; Ravenscroft, Julia; Cole, Maxine; Jacobs, Agnes; Newman, Joan

2005-01-01

In this article we describe a research partnership between the Akwesasne Mohawk Nation and scientists at the University at Albany, State University of New York, initiated to address community and scientific concerns regarding environmental contamination and its health consequences (thyroid hormone function, social adjustment, and school functioning). The investigation focuses on cultural inputs into health disparities. It employs a risk-focusing model of biocultural interaction: behaviors expressing cultural identity and values allocate or focus risk, in this instance the risk of toxicant exposure, which alters health status through the effects of toxicants. As culturally based behaviors and activities fulfill a key role in the model, accurate assessment of subtle cultural and behavioral variables is required and best accomplished through integration of local expert knowledge from the community. As a partnership project, the investigation recognizes the cultural and socioeconomic impacts of research in small communities beyond the production of scientific knowledge. The components of sustainable partnerships are discussed, including strategies that helped promote equity between the partners such as hiring community members as key personnel, integrating local expertise into research design, and developing a local Community Outreach and Education Program. Although challenges arose during the design and implementation of the research project, a collaborative approach has benefited the community and facilitated research. PMID:16330372

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…

Using expert knowledge in landscape ecology [Book review

Treesearch

Eric J. Gustafson

2013-01-01

This volume perfectly illustrates the truism—"we don't know what it is that we don't know." I have been a landscape ecologist for over 20 years, and have even used expert knowledge many times in my own research. Yet I learned something profoundly new in almost every chapter of this collection of primers and case studies focused on the use...

DETERMINATION OF RELATIVE IMPORTANCE OF NONPROLIFERATION FACTORS

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

Richard Metcalf

2009-07-01

Methodologies to determine the proliferation resistance (PR) of nuclear facilities often rely on either expert elicitation, a resource-intensive approach without easily reproducible results, or numeric evaluations, which can fail to take into account the institutional knowledge and expert experience of the nonproliferation community. In an attempt to bridge the gap and bring the institutional knowledge into numeric evaluations of PR, a survey was conducted of 33 individuals to find the relative importance of a set of 62 nonproliferation factors, subsectioned into groups under the headings of Diversion, Transportation, Transformation, and Weaponization. One third of the respondents were self-described nonproliferation professionals,more » and the remaining two thirds were from secondary professions related to nonproliferation, such as industrial engineers or policy analysts. The factors were taken from previous work which used multi-attribute utility analysis with uniform weighting of attributes and did not include institutional knowledge. In both expert and non-expert groups, all four headings and the majority of factors had different relative importance at a confidence of 95% (p=0.05). This analysis and survey demonstrates that institutional knowledge can be brought into numeric evaluations of PR, if there is a sufficient investment of resources made prior to the evaluation.« less

How to Fully Represent Expert Information about Imprecise Properties in a Computer System – Random Sets, Fuzzy Sets, and Beyond: An Overview

PubMed Central

Nguyen, Hung T.; Kreinovich, Vladik

2014-01-01

To help computers make better decisions, it is desirable to describe all our knowledge in computer-understandable terms. This is easy for knowledge described in terms on numerical values: we simply store the corresponding numbers in the computer. This is also easy for knowledge about precise (well-defined) properties which are either true or false for each object: we simply store the corresponding “true” and “false” values in the computer. The challenge is how to store information about imprecise properties. In this paper, we overview different ways to fully store the expert information about imprecise properties. We show that in the simplest case, when the only source of imprecision is disagreement between different experts, a natural way to store all the expert information is to use random sets; we also show how fuzzy sets naturally appear in such random-set representation. We then show how the random-set representation can be extended to the general (“fuzzy”) case when, in addition to disagreements, experts are also unsure whether some objects satisfy certain properties or not. PMID:25386045

Industrial knowledge design: an approach for designing information artifacts

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

Schatz, Sae; Berking, Peter; Raybourn, Elaine M.

In this study, the authors define a new approach that addresses the challenge of efficiently designing informational artefacts for optimal knowledge acquisition, an important issue in cognitive ergonomics. Termed Industrial Knowledge Design (or InK'D), it draws from information-related (e.g. informatics) and neurosciences-related (e.g. neuroergonomics) disciplines. Although it can be used for a broad scope of communication-driven business functions, our focus as learning professionals is on conveying knowledge for purposes of training, education, and performance support. This paper discusses preliminary principles of InK'D practice that can be employed to maximise the quality and quantity of transferred knowledge through interaction design. Themore » paper codifies tacit knowledge into explicit concepts that can be leveraged by expert and non-expert knowledge designers alike.« less

Industrial knowledge design: an approach for designing information artifacts

DOE PAGES

Schatz, Sae; Berking, Peter; Raybourn, Elaine M.

2017-01-19

In this study, the authors define a new approach that addresses the challenge of efficiently designing informational artefacts for optimal knowledge acquisition, an important issue in cognitive ergonomics. Termed Industrial Knowledge Design (or InK'D), it draws from information-related (e.g. informatics) and neurosciences-related (e.g. neuroergonomics) disciplines. Although it can be used for a broad scope of communication-driven business functions, our focus as learning professionals is on conveying knowledge for purposes of training, education, and performance support. This paper discusses preliminary principles of InK'D practice that can be employed to maximise the quality and quantity of transferred knowledge through interaction design. Themore » paper codifies tacit knowledge into explicit concepts that can be leveraged by expert and non-expert knowledge designers alike.« less

Pesticide risk perceptions and the differences between farmers and extensionists: Towards a knowledge-in-context model

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

Ríos-González, Adriana, E-mail: adrianariosg@hotmail.com; The Africa and Latin America Research Groups Network; Jansen, Kees, E-mail: Kees.Jansen@wur.nl

A growing body of literature analyzes farmer perceptions of pesticide risk, but much less attention has been given to differences in risk perception between farmers and technical experts. Furthermore, inconsistencies in knowledge have too easily been explained in terms of lack of knowledge rather than exploring the underlying reasons for particular forms of thinking about pesticide risks. By doing this, the division between expert and lay knowledge has been deepened rather than transcended. Objective: This study aims to understand differences and similarities among the perceptions of pesticide risks of farmers, farm workers, and technical experts such as extensionists, by applyingmore » a social science approach towards knowledge and risk attitudes. Methods: Semi-structured interviews and field observations were conducted to smallholders, farm workers, extensionists, health professionals and scientists involved in the use and handling of pesticides. Subsequently, a survey was carried out to quantify the farmers and extensionists' acceptance or rejection of typical assertions expressed previously in the semi-structured interviews. Results: Smallholders showed to gain knowledge from their own experiences and to adapt pesticides practices, which is a potential basis for transforming notions of pesticide safety and risk reduction strategies. Though extensionists have received formal education, they sometimes develop ideas deviating from the technical perspective. The risk perception of the studied actors appeared to vary according to their role in the agricultural labor process; they varied much less than expected according to their schooling level. Conclusions: Commitment to the technical perspective is not dramatically different for extensionists on the one hand and farmers as well as farm workers on the other hand. Ideas about a supposed lack of knowledge by farmers and the need of formal training are too much driven by a deficit model of knowledge. Further research on risk perceptions of pesticides and training of rural people will benefit from the development of a knowledge-in-context model. -- Highlights: • Researching perceptions of farmers' extensionists and other professionals. • Experts as well as farmers deviate from the technical perspective. • Blaming who is responsible for pesticide problems creates expert-lay division. • Qualitative and quantitative methods, not as complementary but integrated. • Knowledge-in-context model as an alternative to the knowledge-deficit model.« less

Features of effective medical knowledge resources to support point of care learning: a focus group study.

PubMed

Cook, David A; Sorensen, Kristi J; Hersh, William; Berger, Richard A; Wilkinson, John M

2013-01-01

Health care professionals access various information sources to quickly answer questions that arise in clinical practice. The features that favorably influence the selection and use of knowledge resources remain unclear. We sought to better understand how clinicians select among the various knowledge resources available to them, and from this to derive a model for an effective knowledge resource. We conducted 11 focus groups at an academic medical center and outlying community sites. We included a purposive sample of 50 primary care and subspecialist internal medicine and family medicine physicians. We transcribed focus group discussions and analyzed these using a constant comparative approach to inductively identify features that influence the selection of knowledge resources. We identified nine features that influence users' selection of knowledge resources, namely efficiency (with sub-features of comprehensiveness, searchability, and brevity), integration with clinical workflow, credibility, user familiarity, capacity to identify a human expert, reflection of local care processes, optimization for the clinical question (e.g., diagnosis, treatment options, drug side effect), currency, and ability to support patient education. No single existing resource exemplifies all of these features. The influential features identified in this study will inform the development of knowledge resources, and could serve as a framework for future research in this field.

Features of Effective Medical Knowledge Resources to Support Point of Care Learning: A Focus Group Study

PubMed Central

Cook, David A.; Sorensen, Kristi J.; Hersh, William; Berger, Richard A.; Wilkinson, John M.

2013-01-01

Objective Health care professionals access various information sources to quickly answer questions that arise in clinical practice. The features that favorably influence the selection and use of knowledge resources remain unclear. We sought to better understand how clinicians select among the various knowledge resources available to them, and from this to derive a model for an effective knowledge resource. Methods We conducted 11 focus groups at an academic medical center and outlying community sites. We included a purposive sample of 50 primary care and subspecialist internal medicine and family medicine physicians. We transcribed focus group discussions and analyzed these using a constant comparative approach to inductively identify features that influence the selection of knowledge resources. Results We identified nine features that influence users' selection of knowledge resources, namely efficiency (with sub-features of comprehensiveness, searchability, and brevity), integration with clinical workflow, credibility, user familiarity, capacity to identify a human expert, reflection of local care processes, optimization for the clinical question (e.g., diagnosis, treatment options, drug side effect), currency, and ability to support patient education. No single existing resource exemplifies all of these features. Conclusion The influential features identified in this study will inform the development of knowledge resources, and could serve as a framework for future research in this field. PMID:24282535

System diagnostic builder: a rule-generation tool for expert systems that do intelligent data evaluation

NASA Astrophysics Data System (ADS)

Nieten, Joseph L.; Burke, Roger

1993-03-01

The system diagnostic builder (SDB) is an automated knowledge acquisition tool using state- of-the-art artificial intelligence (AI) technologies. The SDB uses an inductive machine learning technique to generate rules from data sets that are classified by a subject matter expert (SME). Thus, data is captured from the subject system, classified by an expert, and used to drive the rule generation process. These rule-bases are used to represent the observable behavior of the subject system, and to represent knowledge about this system. The rule-bases can be used in any knowledge based system which monitors or controls a physical system or simulation. The SDB has demonstrated the utility of using inductive machine learning technology to generate reliable knowledge bases. In fact, we have discovered that the knowledge captured by the SDB can be used in any number of applications. For example, the knowledge bases captured from the SMS can be used as black box simulations by intelligent computer aided training devices. We can also use the SDB to construct knowledge bases for the process control industry, such as chemical production, or oil and gas production. These knowledge bases can be used in automated advisory systems to ensure safety, productivity, and consistency.

A New Perspective on Modeling Groundwater-Driven Health Risk With Subjective Information

NASA Astrophysics Data System (ADS)

Ozbek, M. M.

2003-12-01

Fuzzy rule-based systems provide an efficient environment for the modeling of expert information in the context of risk management for groundwater contamination problems. In general, their use in the form of conditional pieces of knowledge, has been either as a tool for synthesizing control laws from data (i.e., conjunction-based models), or in a knowledge representation and reasoning perspective in Artificial Intelligence (i.e., implication-based models), where only the latter may lead to coherence problems (e.g., input data that leads to logical inconsistency when added to the knowledge base). We implement a two-fold extension to an implication-based groundwater risk model (Ozbek and Pinder, 2002) including: 1) the implementation of sufficient conditions for a coherent knowledge base, and 2) the interpolation of expert statements to supplement gaps in knowledge. The original model assumes statements of public health professionals for the characterization of the exposed individual and the relation of dose and pattern of exposure to its carcinogenic effects. We demonstrate the utility of the extended model in that it: 1)identifies inconsistent statements and establishes coherence in the knowledge base, and 2) minimizes the burden of knowledge elicitation from the experts for utilizing existing knowledge in an optimal fashion.ÿÿ

Experts' views regarding Australian school-leavers' knowledge of nutrition and food systems.

PubMed

Sadegholvad, Sanaz; Yeatman, Heather; Parrish, Anne-Maree; Worsley, Anthony

2017-10-01

To explore Australian experts' views regarding strengths and gaps in school-leavers' knowledge of nutrition and food systems ( N&FS) and factors that influence that knowledge. Semi-structured interviews were conducted with 21 highly experienced food-related experts in Australia. Qualitative data were analysed thematically using Attride-Stirling's thematic network framework. Two global themes and several organising themes were identified. The first global theme, 'structural curriculum-based problems', emerged from three organising themes of: inconsistencies in provided food education programs at schools in Australia; insufficient coverage of food-related skills and food systems topics in school curricula; and the lack of trained school teachers. The second global theme, 'insufficient levels of school-leavers knowledge of N&FS ', was generated from four organising themes, which together described Australian school-leavers' poor knowledge of N&FS more broadly and knowledge translation problem for everyday practices. Study findings identified key problems relating to current school-based N&FS education programs in Australia and reported knowledge gaps in relation to N&FS among Australian school-leavers. These findings provide important guidance for N&FS curriculum development, to clearly articulate broadly-based N&FS knowledge acquisition in curriculum policy and education documents for Australian schools. © 2017 The Authors.

Trends and priorities in occupational health research and knowledge transfer in Italy.

PubMed

Rondinone, Bruna Maria; Boccuni, Fabio; Iavicoli, Sergio

2010-06-01

In 2000-2001, the Italian National Institute for Occupational Safety and Prevention (ISPESL) carried out a survey to identify the research priorities in the field of occupational safety and health (OSH). The present study, carried out in 2007-2008, was a follow-up designed to (i) review the themes identified earlier, (ii) detect emerging issues linked to new risks and forms of work, and (iii) look for any shifts in focus. The survey was extended to cover not only research but also the concept of knowledge transfer. In the first round, ISPESL distributed questionnaires to the heads of both university occupational medicine departments and prevention departments in local national health units (known as ASL in Italy) asking respondents to identify OSH priority themes. In the latest survey covering both research and the need for knowledge transfer, the same experts were asked to rank the importance of the earlier-identified topics and list any emerging issues in the OSH field. The two most important themes identified were "work accidents" and "occupational carcinogenesis". In the overall sample and among ASL experts, they received the 1st and 2nd highest mean scores. The university respondents also prioritized them but in reverse order. Some of the new priority topics included: risks associated with nanotechnologies; assessment of psychosocial and organizational risks; migration and work; and cost-benefit analysis of prevention. In light of the findings, efforts are urgently needed to identify research and knowledge transfer priorities related to workers' health and safety on an international scale using a standardized method in order to obtain comparable results, avoid wasteful duplication of resources, and reduce occupational accidents and illness.

Artificial Intelligence in Education.

ERIC Educational Resources Information Center

Ruyle, Kim E.

Expert systems have made remarkable progress in areas where the knowledge of an expert can be codified and represented, and these systems have many potentially useful applications in education. Expert systems seem "intelligent" because they do not simply repeat a set of predetermined questions during a consultation session, but will have…

Organization of Programming Knowledge of Novices and Experts.

ERIC Educational Resources Information Center

Wiedenbeck, Susan

1986-01-01

Reports on an experiment where novice and expert programmers made decisions about Fortran code segments. The results show that, although expert programmers are better able to extract and use functional information, they don't differ significantly from novices in their ability to use syntactic concepts. (Author/EM)

What people know about electronic devices: A descriptive study

NASA Astrophysics Data System (ADS)

Kieras, D. E.

1982-10-01

Informal descriptive results on the nature of people's natural knowledge of electronic devices are presented. Expert and nonexpert subjects were given an electronic device to examine and describe orally. The devices ranged from familiar everyday devices, to those familiar only to the expert, to unusual devices unfamiliar even to an expert. College students were asked to describe everyday devices from memory. The results suggest that device knowledge consists of the major categories of what the device is for, how it is used, its structure in terms of subdevices, its physical layout, how it works, and its behavior. A preliminary theoretical framework for device knowledge is that it consists of a hierarchy of schemas, corresponding to a hierarchial decomposition of the device into subdevices, with each level containing the major categories of information.

A flight expert system for on-board fault monitoring and diagnosis

NASA Technical Reports Server (NTRS)

Ali, Moonis

1990-01-01

An architecture for a flight expert system (FLES) to assist pilots in monitoring, diagnosing, and recovering from inflight faults is described. A prototype was implemented and an attempt was made to automate the knowledge acquisition process by employing a learning by being told methodology. The scope of acquired knowledge ranges from domain knowledge, including the information about objects and their relationships, to the procedural knowledge associated with the functionality of the mechanisms. AKAS (automatic knowledge acquisition system) is the constructed prototype for demonstration proof of concept, in which the expert directly interfaces with the knowledge acquisition system to ultimately construct the knowledge base for the particular application. The expert talks directly to the system using a natural language restricted only by the extent of the definitions in an analyzer dictionary, i.e., the interface understands a subset of concepts related to a given domain. In this case, the domain is the electrical system of the Boeing 737. Efforts were made to define and employ heuristics as well as algorithmic rules to conceptualize data produced by normal and faulty jet engine behavior examples. These rules were employed in developing the machine learning system (MLS). The input to MLS is examples which contain data of normal and faulty engine behavior and which are obtained from an engine simulation program. MLS first transforms the data into discrete selectors. Partial descriptions formed by those selectors are then generalized or specialized to generate concept descriptions about faults. The concepts are represented in the form of characteristic and discriminant descriptions, which are stored in the knowledge base and are employed to diagnose faults. MLS was successfully tested on jet engine examples.

Analysis of nasopharyngeal carcinoma risk factors with Bayesian networks.

PubMed

Aussem, Alex; de Morais, Sérgio Rodrigues; Corbex, Marilys

2012-01-01

We propose a new graphical framework for extracting the relevant dietary, social and environmental risk factors that are associated with an increased risk of nasopharyngeal carcinoma (NPC) on a case-control epidemiologic study that consists of 1289 subjects and 150 risk factors. This framework builds on the use of Bayesian networks (BNs) for representing statistical dependencies between the random variables. We discuss a novel constraint-based procedure, called Hybrid Parents and Children (HPC), that builds recursively a local graph that includes all the relevant features statistically associated to the NPC, without having to find the whole BN first. The local graph is afterwards directed by the domain expert according to his knowledge. It provides a statistical profile of the recruited population, and meanwhile helps identify the risk factors associated to NPC. Extensive experiments on synthetic data sampled from known BNs show that the HPC outperforms state-of-the-art algorithms that appeared in the recent literature. From a biological perspective, the present study confirms that chemical products, pesticides and domestic fume intake from incomplete combustion of coal and wood are significantly associated with NPC risk. These results suggest that industrial workers are often exposed to noxious chemicals and poisonous substances that are used in the course of manufacturing. This study also supports previous findings that the consumption of a number of preserved food items, like house made proteins and sheep fat, are a major risk factor for NPC. BNs are valuable data mining tools for the analysis of epidemiologic data. They can explicitly combine both expert knowledge from the field and information inferred from the data. These techniques therefore merit consideration as valuable alternatives to traditional multivariate regression techniques in epidemiologic studies. Copyright © 2011 Elsevier B.V. All rights reserved.

An expert system that performs a satellite station keepimg maneuver

NASA Technical Reports Server (NTRS)

Linesbrowning, M. Kate; Stone, John L., Jr.

1987-01-01

The development and characteristics of a prototype expert system, Expert System for Satellite Orbit Control (ESSOC), capable of providing real-time spacecraft system analysis and command generation for a geostationary satellite are described. The ESSOC recommends appropriate commands that reflect both the changing spacecraft condition and previous procedural action. An internal knowledge base stores satellite status information and is updated with processed spacecraft telemetry. Procedural structure data are encoded in production rules. Structural methods of knowledge acquisition and the design and performance-enhancing techniques that enable ESSOC to operate in real time are also considered.

Improved knowledge diffusion model based on the collaboration hypernetwork

NASA Astrophysics Data System (ADS)

Wang, Jiang-Pan; Guo, Qiang; Yang, Guang-Yong; Liu, Jian-Guo

2015-06-01

The process for absorbing knowledge becomes an essential element for innovation in firms and in adapting to changes in the competitive environment. In this paper, we present an improved knowledge diffusion hypernetwork (IKDH) model based on the idea that knowledge will spread from the target node to all its neighbors in terms of the hyperedge and knowledge stock. We apply the average knowledge stock V(t) , the variable σ2(t) , and the variance coefficient c(t) to evaluate the performance of knowledge diffusion. By analyzing different knowledge diffusion ways, selection ways of the highly knowledgeable nodes, hypernetwork sizes and hypernetwork structures for the performance of knowledge diffusion, results show that the diffusion speed of IKDH model is 3.64 times faster than that of traditional knowledge diffusion (TKDH) model. Besides, it is three times faster to diffuse knowledge by randomly selecting "expert" nodes than that by selecting large-hyperdegree nodes as "expert" nodes. Furthermore, either the closer network structure or smaller network size results in the faster knowledge diffusion.

A community-engaged infection prevention and control approach to Ebola.

PubMed

Marais, Frederick; Minkler, Meredith; Gibson, Nancy; Mwau, Baraka; Mehtar, Shaheen; Ogunsola, Folasade; Banya, Sama S; Corburn, Jason

2016-06-01

The real missing link in Ebola control efforts to date may lie in the failure to apply core principles of health promotion: the early, active and sustained engagement of affected communities, their trusted leaders, networks and lay knowledge, to help inform what local control teams do, and how they may better do it, in partnership with communities. The predominant focus on viral transmission has inadvertently stigmatized and created fear-driven responses among affected individuals, families and communities. While rigorous adherence to standard infection prevention and control (IPC) precautions and safety standards for Ebola is critical, we may be more successful if we validate and combine local community knowledge and experiences with that of IPC medical teams. In an environment of trust, community partners can help us learn of modest adjustments that would not compromise safety but could improve community understanding of, and responses to, disease control protocol, so that it better reflects their 'community protocol' (local customs, beliefs, knowledge and practices) and concerns. Drawing on the experience of local experts in several African nations and of community-engaged health promotion leaders in the USA, Canada and WHO, we present an eight step model, from entering communities with cultural humility, though reciprocal learning and trust, multi-method communication, development of the joint protocol, to assessing progress and outcomes and building for sustainability. Using examples of changes that are culturally relevant yet maintain safety, we illustrate how often minor adjustments can help prevent and treat the most serious emerging infectious disease since HIV/AIDS. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A comparison study of atlas-based 3D cardiac MRI segmentation: global versus global and local transformations

NASA Astrophysics Data System (ADS)

Daryanani, Aditya; Dangi, Shusil; Ben-Zikri, Yehuda Kfir; Linte, Cristian A.

2016-03-01

Magnetic Resonance Imaging (MRI) is a standard-of-care imaging modality for cardiac function assessment and guidance of cardiac interventions thanks to its high image quality and lack of exposure to ionizing radiation. Cardiac health parameters such as left ventricular volume, ejection fraction, myocardial mass, thickness, and strain can be assessed by segmenting the heart from cardiac MRI images. Furthermore, the segmented pre-operative anatomical heart models can be used to precisely identify regions of interest to be treated during minimally invasive therapy. Hence, the use of accurate and computationally efficient segmentation techniques is critical, especially for intra-procedural guidance applications that rely on the peri-operative segmentation of subject-specific datasets without delaying the procedure workflow. Atlas-based segmentation incorporates prior knowledge of the anatomy of interest from expertly annotated image datasets. Typically, the ground truth atlas label is propagated to a test image using a combination of global and local registration. The high computational cost of non-rigid registration motivated us to obtain an initial segmentation using global transformations based on an atlas of the left ventricle from a population of patient MRI images and refine it using well developed technique based on graph cuts. Here we quantitatively compare the segmentations obtained from the global and global plus local atlases and refined using graph cut-based techniques with the expert segmentations according to several similarity metrics, including Dice correlation coefficient, Jaccard coefficient, Hausdorff distance, and Mean absolute distance error.

The Roles of Knowledge Professionals for Knowledge Management.

ERIC Educational Resources Information Center

Kim, Seonghee

This paper starts by exploring the definition of knowledge and knowledge management; examples of acquisition, creation, packaging, application, and reuse of knowledge are provided. It then considers the partnership for knowledge management and especially how librarians as knowledge professionals, users, and technology experts can contribute to…

A demonstration of expert systems applications in transportation engineering : volume II, TRANZ, a prototype expert system for traffic control in highway work zones.

DOT National Transportation Integrated Search

1988-01-01

The development of a prototype knowledge-based expert system (KBES) for selecting appropriate traffic control strategies and management techniques around highway work zones was initiated. This process was encompassed by the steps that formulate the p...

CORMIX1: AN EXPERT SYSTEM FOR MIXING ZONE ANALYSIS OF TOXIC AND CONVENTIONAL, SINGLE PORT AQUATIC DISCHARGES

EPA Science Inventory

An expert system, CORMIX1, was developed to predict the dilution and trajectory of a single buoyant discharge into an unstratified aquatic environment with and without crossflow. The system uses knowledge and inference rules obtained from hydrodynamic experts to classify and pred...

'Imagining ourselves' as participating publics: An example from biodiversity conservation.

PubMed

Castro, Paula; Mouro, Carla

2016-10-01

This article examines how residents in Natura 2000 sites in Southern Portugal 'imagine themselves' as publics participating in biodiversity conservation. Through nine focus groups (n = 49) it seeks to understand whether and how these self-imaginations reproduce and/or resist experts' highly shared, hegemonic, representations across two dimensions: the epistemic and the normative. Analysis of the groups' discussions shows that (1) reproduction is clearer in the normative dimension, conveyed through discursive formats that place 'people' as its actor and exempt the Ego from it; (2) resistance is clearer in the epistemic dimension, relying on vibrant claims of local knowledge, yet it can be maintained as hidden discourse; (3) the forms of reproduction or resistance that emerged were hybrid ones; and (4) self-imaginations are more fragmented and negative in normative matters and more unified and positive in epistemic matters. We discuss how these findings help understand how hegemonic representations are maintained/resisted in enduring public-expert relations. © The Author(s) 2015.

Governing by Testing: Circulation, Psychometric Knowledge, Experts and the "Alliance for Progress" in Latin America during the 1960s and 1970s

ERIC Educational Resources Information Center

Alarcón, Cristina

2015-01-01

This paper analyzes the activities, members, and effects of an inter-American expert network for the diffusion of psychometric knowledge, specifically of standardized aptitude testing for university admission in Latin America during the 1960s and 1970s. Within the framework of educational transfer studies, the role of international,…

Young Adults' Knowledge and Understanding of Personal Finance in Germany: Interviews with Experts and Test-Takers

ERIC Educational Resources Information Center

Happ, Roland; Förster, Manuel; Rüspeler, Ann-Katrin; Rothweiler, Jasmin

2018-01-01

In recent years, the financial education of young adults has gained importance in Germany; however, very few valid test instruments to assess the knowledge and understanding of personal finance are suitable for use in Germany. In this article, we describe results of a survey in which experts in Germany in areas related to personal finance judged…

Constructivist learning at the science-policy interface: tsunami science informing disaster policy in West Sumatra

NASA Astrophysics Data System (ADS)

McCaughey, J.; Dewi, P. R.; Natawidjaja, D. H.; Sieh, K. E.

2012-12-01

Science communication often falls short when it is based on the blank-slate assumption that if we can just get the message right, then the information will be received and understood as intended. In contrast, constructivist learning theory and practice suggest that we all actively construct our knowledge from a variety of information sources and through particular, novel associations with our prior knowledge. This constructed knowledge can be quite different from any of its original sources, such as a particular science communication. Successful communication requires carefully examining how people construct their knowledge of the topic of interest. Examples from our outreach work to connect hazard-science research with disaster-risk reduction practice in West Sumatra illustrate the mismatch between expert and stakeholder/public mental models of the characteristics of tsunamigenic earthquakes. There are incorrect conceptions that seawater always withdraws before a tsunami, and that a tsunami can be produced by an earthquake only if the epicenter is located at the ocean trench. These incorrect conceptions arise from generalizations based on recent, local earthquake experiences, as well as from unintended consequences of science outreach, science education, and, in one case, the way that tsunami modelling is graphically presented in scientific journals. We directly address these incorrect conceptions in our discussions with government officials and others; as a result, the local disaster-management agency has changed its policies to reflect an increased understanding of the hazard. This outreach success would not have been possible without eliciting the prior knowledge of our audiences through dialogue.

Scientific Cluster Deployment and Recovery - Using puppet to simplify cluster management

NASA Astrophysics Data System (ADS)

Hendrix, Val; Benjamin, Doug; Yao, Yushu

2012-12-01

Deployment, maintenance and recovery of a scientific cluster, which has complex, specialized services, can be a time consuming task requiring the assistance of Linux system administrators, network engineers as well as domain experts. Universities and small institutions that have a part-time FTE with limited time for and knowledge of the administration of such clusters can be strained by such maintenance tasks. This current work is the result of an effort to maintain a data analysis cluster (DAC) with minimal effort by a local system administrator. The realized benefit is the scientist, who is the local system administrator, is able to focus on the data analysis instead of the intricacies of managing a cluster. Our work provides a cluster deployment and recovery process (CDRP) based on the puppet configuration engine allowing a part-time FTE to easily deploy and recover entire clusters with minimal effort. Puppet is a configuration management system (CMS) used widely in computing centers for the automatic management of resources. Domain experts use Puppet's declarative language to define reusable modules for service configuration and deployment. Our CDRP has three actors: domain experts, a cluster designer and a cluster manager. The domain experts first write the puppet modules for the cluster services. A cluster designer would then define a cluster. This includes the creation of cluster roles, mapping the services to those roles and determining the relationships between the services. Finally, a cluster manager would acquire the resources (machines, networking), enter the cluster input parameters (hostnames, IP addresses) and automatically generate deployment scripts used by puppet to configure it to act as a designated role. In the event of a machine failure, the originally generated deployment scripts along with puppet can be used to easily reconfigure a new machine. The cluster definition produced in our CDRP is an integral part of automating cluster deployment in a cloud environment. Our future cloud efforts will further build on this work.

Essential Nutrition and Food Systems Components for School Curricula: Views from Experts in Iran

PubMed Central

SADEGHOLVAD, Sanaz; YEATMAN, Heather; OMIDVAR, Nasrin; PARRISH, Anne-Maree; WORSLEY, Anthony

2017-01-01

Background: This study aimed to investigate food experts’ views on important nutrition and food systems knowledge issues for education purposes at schools in Iran. Methods: In 2012, semi-structured, face-to-face or telephone interviews were conducted with twenty-eight acknowledged Iranian experts in food and nutrition fields. Participants were selected from four major provinces in Iran (Tehran, Isfahan, Fars and Gilan). Open-ended interview questions were used to identify nutrition and food systems knowledge issues, which experts considered as important to be included in school education programs. Qualitative interviews were analyzed thematically using NVivo. Results: A framework of knowledge that would assist Iranian students and school-leavers to make informed decisions in food-related areas was developed, comprising five major clusters and several sub-clusters. Major knowledge clusters included nutrition basics; food production; every day food-related practices; prevalent nutritional health problems in Iran and improvement of students’ ethical attitudes in the food domain. Conclusion: These findings provide a guide to curriculum developers and policy makers to assess current education curricula in order to optimize students’ knowledge of nutrition and food systems. PMID:28845405

Virtual reality training improves students' knowledge structures of medical concepts.

PubMed

Stevens, Susan M; Goldsmith, Timothy E; Summers, Kenneth L; Sherstyuk, Andrei; Kihmm, Kathleen; Holten, James R; Davis, Christopher; Speitel, Daniel; Maris, Christina; Stewart, Randall; Wilks, David; Saland, Linda; Wax, Diane; Panaiotis; Saiki, Stanley; Alverson, Dale; Caudell, Thomas P

2005-01-01

Virtual environments can provide training that is difficult to achieve under normal circumstances. Medical students can work on high-risk cases in a realistic, time-critical environment, where students practice skills in a cognitively demanding and emotionally compelling situation. Research from cognitive science has shown that as students acquire domain expertise, their semantic organization of core domain concepts become more similar to those of an expert's. In the current study, we hypothesized that students' knowledge structures would become more expert-like as a result of their diagnosing and treating a patient experiencing a hematoma within a virtual environment. Forty-eight medical students diagnosed and treated a hematoma case within a fully immersed virtual environment. Student's semantic organization of 25 case-related concepts was assessed prior to and after training. Students' knowledge structures became more integrated and similar to an expert knowledge structure of the concepts as a result of the learning experience. The methods used here for eliciting, representing, and evaluating knowledge structures offer a sensitive and objective means for evaluating student learning in virtual environments and medical simulations.

A spectral-knowledge-based approach for urban land-cover discrimination

NASA Technical Reports Server (NTRS)

Wharton, Stephen W.

1987-01-01

A prototype expert system was developed to demonstrate the feasibility of classifying multispectral remotely sensed data on the basis of spectral knowledge. The spectral expert was developed and tested with Thematic Mapper Simulator (TMS) data having eight spectral bands and a spatial resolution of 5 m. A knowledge base was developed that describes the target categories in terms of characteristic spectral relationships. The knowledge base was developed under the following assumptions: the data are calibrated to ground reflectance, the area is well illuminated, the pixels are dominated by a single category, and the target categories can be recognized without the use of spatial knowledge. Classification decisions are made on the basis of convergent evidence as derived from applying the spectral rules to a multiple spatial resolution representation of the image. The spectral expert achieved an accuracy of 80-percent correct or higher in recognizing 11 spectral categories in TMS data for the washington, DC, area. Classification performance can be expected to decrease for data that do not satisfy the above assumptions as illustrated by the 63-percent accuracy for 30-m resolution Thematic Mapper data.

Breakfast barriers and opportunities for children living in a Dutch disadvantaged neighbourhood.

PubMed

van Kleef, Ellen; Vingerhoeds, Monique H; Vrijhof, Milou; van Trijp, Hans C M

2016-12-01

The objective of this study was to explore parents', children's, and experts' beliefs and experiences about breakfast motivation, opportunity, and ability and elicit their thoughts on effective interventions to encourage healthy breakfast consumption. The setting was a disadvantaged neighbourhood in Rotterdam, the Netherlands. Focus groups with mothers and children and semi-structured individual interviews with experts were conducted. Interview guides were developed based on the motivation, opportunity, and ability consumer psychology model. Thirty-two mothers of primary school children participated in five group discussions, eight focus groups were conducted with 44 children, and nine experts participated in interviews. Data from expert interviews and group discussions were coded and thematically analysed. The following themes emerged from the focus groups: (1) generally high motivation to have breakfast, (2) improved performance at school is key motivator, (3) limited time hinders breakfast, and (4) lack of nutritional knowledge about high quality breakfast. Experts mentioned lack of effort, knowledge, and time; financial constraints; and environmental issues (food availability) as barriers to breakfasting healthily. Several ways to encourage healthy breakfasting habits were identified: (1) involvement of both children and parents, (2) role models inspiring change, and (3) interactive educational approaches. Experts perceived more problems and challenges in achieving healthy breakfast habits than did mothers and children. Lack of opportunity (according to the children and experts) and ability (according to the experts) were identified, although the motivation to eat a healthy breakfast was present. Predominant barriers are lack of time and nutritional knowledge. Overall, findings suggest educational and social marketing approaches as interventions to encourage healthy breakfast consumption. Copyright © 2016 Elsevier Ltd. All rights reserved.

Using XML and XSLT for flexible elicitation of mental-health risk knowledge.

PubMed

Buckingham, C D; Ahmed, A; Adams, A E

2007-03-01

Current tools for assessing risks associated with mental-health problems require assessors to make high-level judgements based on clinical experience. This paper describes how new technologies can enhance qualitative research methods to identify lower-level cues underlying these judgements, which can be collected by people without a specialist mental-health background. Content analysis of interviews with 46 multidisciplinary mental-health experts exposed the cues and their interrelationships, which were represented by a mind map using software that stores maps as XML. All 46 mind maps were integrated into a single XML knowledge structure and analysed by a Lisp program to generate quantitative information about the numbers of experts associated with each part of it. The knowledge was refined by the experts, using software developed in Flash to record their collective views within the XML itself. These views specified how the XML should be transformed by XSLT, a technology for rendering XML, which resulted in a validated hierarchical knowledge structure associating patient cues with risks. Changing knowledge elicitation requirements were accommodated by flexible transformations of XML data using XSLT, which also facilitated generation of multiple data-gathering tools suiting different assessment circumstances and levels of mental-health knowledge.

12 CFR 390.91 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-01-01

...: (1) The representation of another person at any adjudicatory, investigatory, removal or rulemaking... licensed expert which is filed with or submitted to the FDIC, with such expert's consent or knowledge in...

Expert operator's associate: A knowledge based system for spacecraft control

NASA Technical Reports Server (NTRS)

Nielsen, Mogens; Grue, Klaus; Lecouat, Francois

1991-01-01

The Expert Operator's Associate (EOA) project is presented which studies the applicability of expert systems for day-to-day space operations. A prototype expert system is developed, which operates on-line with an existing spacecraft control system at the European Space Operations Centre, and functions as an 'operator's assistant' in controlling satellites. The prototype is demonstrated using an existing real-time simulation model of the MARECS-B2 telecommunication satellite. By developing a prototype system, the extent to which reliability and effectivens of operations can be enhanced by AI based support is examined. In addition the study examines the questions of acquisition and representation of the 'knowledge' for such systems, and the feasibility of 'migration' of some (currently) ground-based functions into future spaceborne autonomous systems.

Expert Recommender: Designing for a Network Organization

NASA Astrophysics Data System (ADS)

Reichling, Tim; Veith, Michael; Wulf, Volker

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

Characterizing Forest Change Using Community-Based Monitoring Data and Landsat Time Series

PubMed Central

DeVries, Ben; Pratihast, Arun Kumar; Verbesselt, Jan; Kooistra, Lammert; Herold, Martin

2016-01-01

Increasing awareness of the issue of deforestation and degradation in the tropics has resulted in efforts to monitor forest resources in tropical countries. Advances in satellite-based remote sensing and ground-based technologies have allowed for monitoring of forests with high spatial, temporal and thematic detail. Despite these advances, there is a need to engage communities in monitoring activities and include these stakeholders in national forest monitoring systems. In this study, we analyzed activity data (deforestation and forest degradation) collected by local forest experts over a 3-year period in an Afro-montane forest area in southwestern Ethiopia and corresponding Landsat Time Series (LTS). Local expert data included forest change attributes, geo-location and photo evidence recorded using mobile phones with integrated GPS and photo capabilities. We also assembled LTS using all available data from all spectral bands and a suite of additional indices and temporal metrics based on time series trajectory analysis. We predicted deforestation, degradation or stable forests using random forest models trained with data from local experts and LTS spectral-temporal metrics as model covariates. Resulting models predicted deforestation and degradation with an out of bag (OOB) error estimate of 29% overall, and 26% and 31% for the deforestation and degradation classes, respectively. By dividing the local expert data into training and operational phases corresponding to local monitoring activities, we found that forest change models improved as more local expert data were used. Finally, we produced maps of deforestation and degradation using the most important spectral bands. The results in this study represent some of the first to combine local expert based forest change data and dense LTS, demonstrating the complementary value of both continuous data streams. Our results underpin the utility of both datasets and provide a useful foundation for integrated forest monitoring systems relying on data streams from diverse sources. PMID:27018852

Integrating observations and models to help understanding how flooding impacts upon catchments as a basis for decision making.

NASA Astrophysics Data System (ADS)

Owen, Gareth; Quinn, Paul; O'Donnell, Greg

2014-05-01

This paper explains how flood management projects might be better informed in the future by using more observations and a novel impact modelling tool in a simple transparent framework. The understanding of how local scale impacts propagate downstream to impact on the downstream hydrograph is difficult to determine using traditional rainfall runoff and hydraulic routing methods. The traditional approach to modelling essentially comprises selecting a fixed model structure and then calibrating to an observational hydrograph, which make those model predictions highly uncertain. Here, a novel approach is used in which the structure of the runoff generation is not specified a priori and incorporates expert knowledge. Rather than using externally for calibration, the observed outlet hydrographs are used directly within the model. Essentially the approach involves the disaggregation of the outlet hydrograph by making assumptions about the spatial distribution of runoff generated. The channel network is parameterised through a comparison of the timing of observed hydrographs at a number of nested locations within the catchment. The user is then encouraged to use their expert knowledge to define how runoff is generated locally and what the likely impact of any local mitigation is. Therefore the user can specify any hydrological model or flow estimation method that captures their expertise. Equally, the user is encouraged to install as many instruments as they can afford to cover the catchment network. A Decision Support Matrix (DSM) is used to encapsulate knowledge of the runoff dynamics gained from simulation in a simple visual way and hence to convey the likely impacts that arise from a given flood management scenario. This tool has been designed primarily to inform and educate landowners, catchment managers and decision makers. The DSM outlines scenarios that are likely to increase or decrease runoff rates and allows the user to contemplate the implications and uncertainty of their decisions. The tool can also be used to map the likely changes in flood peak due to land use management options. An example case study will be shown for a 35km2 catchment in Northern England which is prone to flooding. The method encourages end users to instrument and quantify their own catchment network and to make informed, evidence based decisions appropriate to their own flooding problems.

Expert Seeker: A People-Finder Knowledge Management System

NASA Technical Reports Server (NTRS)

Becerra-Fernandez, Irma

2000-01-01

The first objective for this report was to perform a comprehensive research of industry models currently being used for similar purposes, in order to provide the Center with ideas of what is being done in area by private companies and government agencies. The second objective was to evaluate the use of taxonomies or ontologies to describe and catalog the areas of expertise at GSFC. The creation of a knowledge taxonomy is necessary for information extraction in order for The Expert Seeker to adequately search and find experts in a particular area of expertise. The requirements to develop a taxonomy are: provide minimal descriptive text; have the appropriate level of abstration; facilitate browsing; ease of use and speed of data entry are critical for success; customized to the organization and its culture; extent of knowledge areas; expandable, so new skills could be develop; could be complemented with free text fields to allow users the option to describe their knowledge in detail.

The effect of food label cues on perceptions of quality and purchase intentions among high-involvement consumers with varying levels of nutrition knowledge.

PubMed

Walters, Amber; Long, Marilee

2012-01-01

To determine whether differences in nutrition knowledge affected how women (a high-involvement group) interpreted intrinsic cues (ingredient list) and extrinsic cues ("all natural" label) on food labels. A 2 (intrinsic cue) × 2 (extrinsic cue) × 2 (nutrition knowledge expert vs novice) within-subject factorial design was used. Participants were 106 female college students (61 experts, 45 novices). Dependent variables were perception of product quality and purchase intention. As predicted by the elaboration likelihood model, experts used central route processing to scrutinize intrinsic cues and make judgments about food products. Novices used peripheral route processing to make simple inferences about the extrinsic cues in labels. Consumers' levels of nutrition knowledge influenced their ability to process food labels. The United States Food and Drug Administration should regulate the "all natural" food label, because this claim is likely to mislead most consumers. Copyright © 2012 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

Ontology-based classification of remote sensing images using spectral rules

NASA Astrophysics Data System (ADS)

Andrés, Samuel; Arvor, Damien; Mougenot, Isabelle; Libourel, Thérèse; Durieux, Laurent

2017-05-01

Earth Observation data is of great interest for a wide spectrum of scientific domain applications. An enhanced access to remote sensing images for "domain" experts thus represents a great advance since it allows users to interpret remote sensing images based on their domain expert knowledge. However, such an advantage can also turn into a major limitation if this knowledge is not formalized, and thus is difficult for it to be shared with and understood by other users. In this context, knowledge representation techniques such as ontologies should play a major role in the future of remote sensing applications. We implemented an ontology-based prototype to automatically classify Landsat images based on explicit spectral rules. The ontology is designed in a very modular way in order to achieve a generic and versatile representation of concepts we think of utmost importance in remote sensing. The prototype was tested on four subsets of Landsat images and the results confirmed the potential of ontologies to formalize expert knowledge and classify remote sensing images.

A theory of expert leadership (TEL) in psychiatry.

PubMed

Goodall, Amanda H

2016-06-01

Leaders' technical competence - 'expert knowledge' - has been shown in many settings to be associated with better organizational performance. In universities, for example, there is longitudinal evidence that research-focused scholars make the best leaders; results from a hospital study show that doctors instead of professional managers are most closely associated with the best performing institutions. To explain these patterns, and raise hypotheses, a theory of expert leadership (TEL) has been developed that might explain these patterns. In this paper the framework for expert leadership is applied to psychiatry. The TEL proposes that psychiatric leaders, as opposed to non-expert managers, improve organizational performance through several channels. First, experts' knowledge influences organizational strategy. Second, having been 'one of them', a psychiatrist understands how to create the optimal work environment for psychiatric teams, through appropriate goal-setting, evaluation and support. These factors are positively associated with workers' wellbeing and performance. Third, exceptional psychiatrist-leaders are likely to set high standards for hiring. Fourth, leaders' credibility extends their influence among core workers, and also signals organizational priorities to stakeholders. Finally, a necessary prerequisite of TEL is that expert leaders have direct executive power inclusive of budgetary and strategic oversight. © The Royal Australian and New Zealand College of Psychiatrists 2015.

Key attributes of expert NRL referees.

PubMed

Morris, Gavin; O'Connor, Donna

2017-05-01

Experiential knowledge of elite National Rugby League (NRL) referees was investigated to determine the key attributes contributing to expert officiating performance. Fourteen current first-grade NRL referees were asked to identify the key attributes they believed contributed to their expert refereeing performance. The modified Delphi method involved a 3-round process of an initial semi-structured interview followed by 2 questionnaires to reach consensus of opinion. The data revealed 25 attributes that were rated as most important that underpin expert NRL refereeing performance. Results illustrate the significance of the cognitive category, with the top 6 ranked attributes all cognitive skills. Of these, the referees ranked decision-making accuracy as the most important attribute, followed by reading the game, communication, game understanding, game management and knowledge of the rules. Player rapport, positioning and teamwork were the top ranked game skill attributes underpinning performance excellence. Expert referees also highlighted a number of psychological attributes (e.g., concentration, composure and mental toughness) that were significant to performance. There were only 2 physiological attributes (fitness, aerobic endurance) that were identified as significant to elite officiating performance. In summary, expert consensus was attained which successfully provided a hierarchy of the most significant attributes of expert NRL refereeing performance.

Methods for optimizing solutions when considering group arguments by team of experts

NASA Astrophysics Data System (ADS)

Chernyi, Sergei; Budnik, Vlad

2017-11-01

The article is devoted to methods of expert evaluation. The technology of expert evaluation is presented from the standpoint of precedent structures. In this paper, an aspect of the mathematical basis for constructing a component of decision analysis is considered. In fact, this approach leaves out any identification of their knowledge and skills of simulating organizational and manufacturing situations and taking efficient managerial decisions; it doesn't enable any identification and assessment of their knowledge on the basis of multi-informational and least loss-making methods and information technologies. Hence the problem is to research and develop a methodology for systemic identification of professional problem-focused knowledge acquired by employees operating adaptive automated systems of training management (AASTM operators), which shall also further the theory and practice of the intelligence-related aspects thereof.

SIRE: A Simple Interactive Rule Editor for NICBES

NASA Technical Reports Server (NTRS)

Bykat, Alex

1988-01-01

To support evolution of domain expertise, and its representation in an expert system knowledge base, a user-friendly rule base editor is mandatory. The Nickel Cadmium Battery Expert System (NICBES), a prototype of an expert system for the Hubble Space Telescope power storage management system, does not provide such an editor. In the following, a description of a Simple Interactive Rule Base Editor (SIRE) for NICBES is described. The SIRE provides a consistent internal representation of the NICBES knowledge base. It supports knowledge presentation and provides a user-friendly and code language independent medium for rule addition and modification. The SIRE is integrated with NICBES via an interface module. This module provides translation of the internal representation to Prolog-type rules (Horn clauses), latter rule assertion, and a simple mechanism for rule selection for its Prolog inference engine.

When science becomes too easy: Science popularization inclines laypeople to underrate their dependence on experts.

PubMed

Scharrer, Lisa; Rupieper, Yvonne; Stadtler, Marc; Bromme, Rainer

2017-11-01

Science popularization fulfills the important task of making scientific knowledge understandable and accessible for the lay public. However, the simplification of information required to achieve this accessibility may lead to the risk of audiences relying overly strongly on their own epistemic capabilities when making judgments about scientific claims. Moreover, they may underestimate how the division of cognitive labor makes them dependent on experts. This article reports an empirical study demonstrating that this "easiness effect of science popularization" occurs when laypeople read authentic popularized science depictions. After reading popularized articles addressed to a lay audience, laypeople agreed more with the knowledge claims they contained and were more confident in their claim judgments than after reading articles addressed to expert audiences. Implications for communicating scientific knowledge to the general public are discussed.

Design and implementation of a status at a glance user interface for a power distribution expert system

NASA Technical Reports Server (NTRS)

Liberman, Eugene M.; Manner, David B.; Dolce, James L.; Mellor, Pamela A.

1993-01-01

Expert systems are widely used in health monitoring and fault detection applications. One of the key features of an expert system is that it possesses a large body of knowledge about the application for which it was designed. When the user consults this knowledge base, it is essential that the expert system's reasoning process and its conclusions be as concise as possible. If, in addition, an expert system is part of a process monitoring system, the expert system's conclusions must be combined with current events of the process. Under these circumstances, it is difficult for a user to absorb and respond to all the available information. For example, a user can become distracted and confused if two or more unrelated devices in different parts of the system require attention. A human interface designed to integrate expert system diagnoses with process data and to focus the user's attention to the important matters provides a solution to the 'information overload' problem. This paper will discuss a user interface to the power distribution expert system for Space Station Freedom. The importance of features which simplify assessing system status and which minimize navigating through layers of information will be discussed. Design rationale and implementation choices will also be presented.

Shifting public health practice to advance health equity: recommendations from experts and community leaders.

PubMed

Knight, Erin K

2014-01-01

While the evidence base regarding the social determinants of health and their relationship to health inequities grows, the field of public health is challenged to translate this knowledge into practice changes that advance health equity. Drawing on the knowledge, beliefs, and experiences of public health experts and community leaders working to advance health equity, our objective was to develop and disseminate recommendations for changing public health practice to better address this problem. We conducted semistructured, qualitative telephone interviews (n = 25) with key informants. Interviews were recorded and transcribed, and data were coded and analyzed using both inductive and deductive methods. Member checks were used to enhance quality. A purposeful sample of key informants was selected from content experts and community leaders involved with the development of the Unnatural Causes public impact campaign. Participants represented state and local health departments, community-based organizations, national research/advocacy organizations, and academic institutions across the country. Participants distinguished between social determinants of health and their structural precursors in social and political institutions. They believed that the field of public health has an obligation to address health inequities and shifts in practice are needed that focus more attention on societal factors that underlie such inequities. According to participants, specific practice changes are difficult to identify because actions should be community specific and community driven. Recommended approaches that may be adapted to community-based needs and assets include building nontraditional partnerships, engaging in political advocacy, promoting community leadership, collecting better data on social conditions and institutional factors, and enhancing communication for health equity. Recommended shifts in practice may be facilitated by revisiting our understanding of the 3 core functions of public health-assessment, assurance, and policy development.

Bridging the Gap between Experts in Designing Multimedia-Based Instructional Media for Learning

ERIC Educational Resources Information Center

Razak, Rafiza Abdul

2013-01-01

The research identified and explored the cognitive knowledge among the instructional multimedia design and development experts comprising of multimedia designer, graphic designer, subject-matter expert and instructional designer. A critical need exists for a solid understanding of the factors that influence team decision making and performance in…

When Do Children Trust the Expert? Benevolence Information Influences Children's Trust More than Expertise

ERIC Educational Resources Information Center

Landrum, Asheley R.; Mills, Candice M.; Johnston, Angie M.

2013-01-01

How do children use informant niceness, meanness, and expertise when choosing between informant claims and crediting informants with knowledge? In Experiment 1, preschoolers met two experts providing conflicting claims for which only one had relevant expertise. Five-year-olds endorsed the relevant expert's claim and credited him with knowledge…

Knowledge-driven institutional change: an empirical study on combating desertification in northern China from 1949 to 2004.

PubMed

Yang, Lihua; Wu, Jianguo

2012-11-15

Understanding institutional changes is crucial for environmental management. Here we investigated how institutional changes influenced the process and result of desertification control in northern China between 1949 and 2004. Our analysis was based on a case study of 21 field sites and a meta-analysis of additional 29 sites reported in the literature. Our results show that imposed knowledge-driven institutional change was often perceived as a more progressive, scientific, and rational type of institutional change by entrepreneurs, scholars, experts, and technicians, while voluntary, knowledge-driven institutional change based on indigenous knowledge and experiences of local populations was discouraged. Our findings also demonstrate that eight working rules of imposed knowledge-driven institutional change can be applied to control desertification effectively. These rules address the issues of perception of potential gains, entrepreneurs' appeals and support, coordination of multiple goals, collaboration among multiple organizations, interest distribution and conflict resolution, incremental institutional change, external intervention, and coordination among the myriad institutions involved. Imposed knowledge-driven institutional change tended to be more successful when these rules were thoroughly implemented. These findings provide an outline for implementing future institutional changes and policy making to combat desertification and other types of ecological and environmental management. Copyright © 2012 Elsevier Ltd. All rights reserved.

Are Clinicians Better Than Lay Judges at Recalling Case Details? An Evaluation of Expert Memory.

PubMed

Webb, Christopher A; Keeley, Jared W; Eakin, Deborah K

2016-04-01

This study examined the role of expertise in clinicians' memory for case details. Clinicians' diagnostic formulations may afford mechanisms for retaining and retrieving information. Experts (N = 41; 47.6% males, 23.8% females; 28.6% did not report gender; age: mean [M] = 54.69) were members of the American Board of Professional Psychologists. Lay judges (N = 156; 25.4% males, 74.1% females; age: M = 18.85) were undergraduates enrolled in general psychology. Three vignettes were presented to each group, creating a 2 (group: expert, lay judge) x 3 (vignettes: simple, complex-coherent, complex-incoherent) mixed factorial design. Recall accuracy for vignette details was the dependent variable. Data analyses used multivariate analyses of variance to detect group differences among multiple continuous variables. Experts recalled more information than lay judges, overall. However, experts also exhibited more false memories for the complex-incoherent case because of their schema-based knowledge. This study supported clinical expertise as beneficial. Nonetheless, negative influences from experts' schema-based knowledge, as exhibited, could adversely affect clinical practices. © 2016 Wiley Periodicals, Inc.

Users manual for an expert system (HSPEXP) for calibration of the hydrological simulation program; Fortran

USGS Publications Warehouse

Lumb, A.M.; McCammon, R.B.; Kittle, J.L.

1994-01-01

Expert system software was developed to assist less experienced modelers with calibration of a watershed model and to facilitate the interaction between the modeler and the modeling process not provided by mathematical optimization. A prototype was developed with artificial intelligence software tools, a knowledge engineer, and two domain experts. The manual procedures used by the domain experts were identified and the prototype was then coded by the knowledge engineer. The expert system consists of a set of hierarchical rules designed to guide the calibration of the model through a systematic evaluation of model parameters. When the prototype was completed and tested, it was rewritten for portability and operational use and was named HSPEXP. The watershed model Hydrological Simulation Program--Fortran (HSPF) is used in the expert system. This report is the users manual for HSPEXP and contains a discussion of the concepts and detailed steps and examples for using the software. The system has been tested on watersheds in the States of Washington and Maryland, and the system correctly identified the model parameters to be adjusted and the adjustments led to improved calibration.

The knowledge of expert nurses and the practical-reflective rationality.

PubMed

Pina Queirós, Paulo Joaquim

2015-01-01

To identify the characteristics of an expert nurse. A group of 49 nurses starting their Master's degree was asked to answer the following question: ''Which characteristics and skills distinguish a novice from an expert nurse?'' The answers were analyzed and classified based on Bardin's content analysis. Through a three-stage classification process, the competences and skills assigned to expert nurses were divided into 17 categories. These nurses showed wide-ranging skills and acquired meta-competencies. Expert nurses are characterized by their leadership, supervision and ability to manage change, as well as their communication and relational skills. They have the ability to act reflectively, plan, systematize and consistently assess; they also show more dexterity. They have more adaptive skills, confidence and achieve a broader view. They are competent while managing conflicts and stress, as well as articulating theory and practice; they create knowledge, make use of research, respond to complex situations and are capable of making decisions. Expert nurses have anticipation skills, insight, use detailed observation, take immediate action and are able to define priorities; they keep context in mind and have a tendency for specialization.

Collective intelligence in medical diagnosis systems: A case study.

PubMed

Hernández-Chan, Gandhi S; Ceh-Varela, Edgar Eduardo; Sanchez-Cervantes, Jose L; Villanueva-Escalante, Marisol; Rodríguez-González, Alejandro; Pérez-Gallardo, Yuliana

2016-07-01

Diagnosing a patient's condition is one of the most important and challenging tasks in medicine. We present a study of the application of collective intelligence in medical diagnosis by applying consensus methods. We compared the accuracy obtained with this method against the diagnostics accuracy reached through the knowledge of a single expert. We used the ontological structures of ten diseases. Two knowledge bases were created by placing five diseases into each knowledge base. We conducted two experiments, one with an empty knowledge base and the other with a populated knowledge base. For both experiments, five experts added and/or eliminated signs/symptoms and diagnostic tests for each disease. After this process, the individual knowledge bases were built based on the output of the consensus methods. In order to perform the evaluation, we compared the number of items for each disease in the agreed knowledge bases against the number of items in the GS (Gold Standard). We identified that, while the number of items in each knowledge base is higher, the consensus level is lower. In all cases, the lowest level of agreement (20%) exceeded the number of signs that are in the GS. In addition, when all experts agreed, the number of items decreased. The use of collective intelligence can be used to increase the consensus of physicians. This is because, by using consensus, physicians can gather more information and knowledge than when obtaining information and knowledge from knowledge bases fed or populated from the knowledge found in the literature, and, at the same time, they can keep updated and collaborate dynamically. Copyright © 2016 Elsevier Ltd. All rights reserved.

ECLSS advanced automation preliminary requirements

NASA Technical Reports Server (NTRS)

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

1989-01-01

A description of the total Environmental Control and Life Support System (ECLSS) is presented. The description of the hardware is given in a top down format, the lowest level of which is a functional description of each candidate implementation. For each candidate implementation, both its advantages and disadvantages are presented. From this knowledge, it was suggested where expert systems could be used in the diagnosis and control of specific portions of the ECLSS. A process to determine if expert systems are applicable and how to select the expert system is also presented. The consideration of possible problems or inconsistencies in the knowledge or workings in the subsystems is described.

Temporal and contextual knowledge in model-based expert systems

NASA Technical Reports Server (NTRS)

Toth-Fejel, Tihamer; Heher, Dennis

1987-01-01

A basic paradigm that allows representation of physical systems with a focus on context and time is presented. Paragon provides the capability to quickly capture an expert's knowledge in a cognitively resonant manner. From that description, Paragon creates a simulation model in LISP, which when executed, verifies that the domain expert did not make any mistakes. The Achille's heel of rule-based systems has been the lack of a systematic methodology for testing, and Paragon's developers are certain that the model-based approach overcomes that problem. The reason this testing is now possible is that software, which is very difficult to test, has in essence been transformed into hardware.

Will You Miss Me when I'm Gone? A Study of the Potential Loss of Company Knowledge and Expertise as Employees Retire

ERIC Educational Resources Information Center

McQuade, Eamonn; Sjoer, Ellen; Fabian, Peter; Nascimento, Jose Carlos; Schroeder, Sanaz

2007-01-01

Purpose--The purpose of this paper is to report on a research project, the aim of which was to identify the potential loss of company knowledge and expertise as experienced and expert employees retire. Design/methodology/approach--The methodology used in this research was based on interviewing experienced and expert people who had retired or were…

Cirrus: Inducing Subject Models from Protocol Data

DTIC Science & Technology

1988-08-16

Protocol analysis is used routinely by psychologists and other behavior scientists, and more recently, by knowledge engineers who wish to embed the...knowledge of human experts in an expert system. However, protocol analysis is notoriously difficult and time comsuming . Several systems have been developed to...formal trace of it (a problem behavior graph). The system, however, did not produce an abstract model of the subject. Bhaskar and Simon (1977) avoided the

Cirrus: Inducing Subject Models from Protocol Data

DTIC Science & Technology

1988-08-16

behavior scientists, and more recently, by knowledge engineers who wish to embed the knowledge of human experts in an expert system. However, protocol...analysis is notoriously difficult and time comsuming . Several systems have been developed to aid in protocol analysis. Waterman and Newell (1971, 1973...developed a system that could read the natural langauge of the protocol and produce a formal trace of it (a problem behavior graph). The system, however

Empirical Analysis and Refinement of Expert System Knowledge Bases

DTIC Science & Technology

1988-08-31

refinement. Both a simulated case generation program, and a random rule basher were developed to enhance rule refinement experimentation. *Substantial...the second fiscal year 88 objective was fully met. Rule Refinement System Simulated Rule Basher Case Generator Stored Cases Expert System Knowledge...generated until the rule is satisfied. Cases may be randomly generated for a given rule or hypothesis. Rule Basher Given that one has a correct

Knowledge-Acquisition Tool For Expert System

NASA Technical Reports Server (NTRS)

Disbrow, James D.; Duke, Eugene L.; Regenie, Victoria A.

1988-01-01

Digital flight-control systems monitored by computer program that evaluates and recommends. Flight-systems engineers for advanced, high-performance aircraft use knowlege-acquisition tool for expert-system flight-status monitor suppling interpretative data. Interpretative function especially important in time-critical, high-stress situations because it facilitates problem identification and corrective strategy. Conditions evaluated and recommendations made by ground-based engineers having essential knowledge for analysis and monitoring of performances of advanced aircraft systems.

Knowledge Requirements and Management in Expert Decision Support Systems for (Military) Situation Assessment

DTIC Science & Technology

1983-08-01

constitutes a fundamental problem in many decision making processes. In business management we face this problem when determining the status of an...Tehiical Report 576 ( 1 ) 4 KNOWLEDGE REQUIREMENTS AND MANAGEMENT IN EXPERT DECISION SUPPORT SYSTEMS FOR (MILITARY) SITUATION ASSESSMENT MOOM sen...accomplished under contract for the Department of the Army The Israel Institute of Business Research Technical review by Robert H. Sasmor Joseph M

A Cognitive Architecture for Human Performance Process Model Research

DTIC Science & Technology

1992-11-01

individually defined, updatable world representation which is a description of the world as the operator knows it. It contains rules for decisions, an...operate it), and rules of engagement (knowledge about the operator’s expected behavior). The HPP model works in the following way. Information enters...based models depict the problem-solving processes of experts. The experts’ knowledge is represented in symbol structures, along with rules for

Knowledge Acquisition for Expert Systems in Construction

DTIC Science & Technology

1988-12-01

following scientific personnel have been closely involved in the execution of this research : Dr R J Allwood Mr A E Bryman Mr C N Cooper Dr J Cullen Mr...alternative methods and should use them flexibly as the position unfolds. This approach has been advocated by other researchers (eg Cordingley - see Diaper...currently engaged in research into methods of knowledge acquisition for expert systems. Although their original focus was on construction industry

Determining Coastal Hazards Risk Perception to Enhance Local Mitigation Planning through a Participatory Mapping Approach

NASA Astrophysics Data System (ADS)

Bethel, M.; Braud, D.; Lambeth, T.; Biber, P.; Wu, W.

2017-12-01

Coastal community leaders, government officials, and natural resource managers must be able to accurately assess and predict a given coastal landscape's sustainability and/or vulnerability as coastal habitat continues to undergo rapid and dramatic changes associated with natural and anthropogenic activities such as accelerated relative sea level rise (SLR). To help address this information need, a multi-disciplinary project team conducted Sea Grant sponsored research in Louisiana and Mississippi with traditional ecosystem users and natural resource managers to determine a method for producing localized vulnerability and sustainability maps for projected SLR and storm surge impacts, and determine how and whether the results of such an approach can provide more useful information to enhance hazard mitigation planning. The goals of the project are to develop and refine SLR visualization tools for local implementation in areas experiencing subsidence and erosion, and discover the different ways stakeholder groups evaluate risk and plan mitigation strategies associated with projected SLR and storm surge. Results from physical information derived from data and modeling of subsidence, erosion, engineered restoration and coastal protection features, historical land loss, and future land projections under SLR are integrated with complimentary traditional ecological knowledge (TEK) offered by the collaborating local ecosystem users for these assessments. The data analysis involves interviewing stakeholders, coding the interviews for themes, and then converting the themes into vulnerability and sustainability factors. Each factor is weighted according to emphasis by the TEK experts and number of experts who mention it to determine which factors are the highest priority. The priority factors are then mapped with emphasis on the perception of contributing to local community vulnerability or sustainability to SLR and storm surge. The maps are used by the collaborators to benefit local hazard mitigation and adaptation planning. The results to date in achieving the project objectives will be presented that include: analyses of scientific field data collected related to marsh vegetation biomass characteristics, analyses of TEK data collected, and mapping products developed.

We’re only in it for the knowledge? A problem solving turn in environment and health expert elicitation

PubMed Central

2012-01-01

Background The FP6 EU HENVINET project aimed at synthesizing the scientific information available on a number of topics of high relevance to policy makers in environment and health. The goal of the current paper is to reflect on the methodology that was used in the project, in view of exploring the usefulness of this and similar methodologies to the policy process. The topics investigated included health impacts of the brominated flame retardants decabrominated diphenylether (decaBDE) and hexabromocyclododecane (HBCD), phthalates highlighting di(2-ethylhexyl)phthalate (DEHP), the pesticide chlorpyrifos (CPF), nanoparticles, the impacts of climate change on asthma and other respiratory disorders, and the influence of environment health stressors on cancer induction. Methods Initially the focus was on identifying knowledge gaps in the state of the art in scientific knowledge. Literature reviews covered all elements that compose the causal chain of the different environmental health issues from emissions to exposures, to effects and to health impacts. Through expert elicitation, knowledge gaps were highlighted by assessing expert confidence using calibrated confidence scales. During this work a complementary focus to that on knowledge gaps was developed through interdisciplinary reflections. By extending the scope of the endeavour from only a scientific perspective, to also include the more problem solving oriented policy perspective, the question of which kind of policy action experts consider justifiable was addressed. This was addressed by means of a questionnaire. In an expert workshop the results of both questionnaires were discussed as a basis for policy briefs. Results The expert elicitation, the application of the calibrated confidence levels and the problem solving approach were all experienced as being quite challenging for the experts involved, as these approaches did not easily relate to mainstream environment and health scientific practices. Even so, most experts were quite positive about it. In particular, the opportunity to widen one’s own horizon and to interactively exchange knowledge and debate with a diversity of experts seemed to be well appreciated in this approach. Different parts of the approach also helped in focussing on specific relevant aspects of scientific knowledge, and as such can be considered of reflective value. Conclusions The approach developed by HENVINET was part of a practice of learning by doing and of interdisciplinary cooperation and negotiation. Ambitions were challenged by unforeseen complexities and difference of opinion and as no Holy Grail approach was at hand to copy or follow, it was quite an interesting but also complicated endeavour. Perfection, if this could be defined, seemed out of reach all the time. Nevertheless, many involved were quite positive about it. It seems that many felt that it fitted some important needs in current science when addressing the needs of policy making on such important issues, without anyone really having a clue on how to actually do this. Challenging questions remain on the quality of such approach and its product. Practice tells us that there probably is no best method and that the best we can do is dependent on contextual negotiation and learning from experiences that we think are relevant. PMID:22759503

Do short courses in evidence based medicine improve knowledge and skills? Validation of Berlin questionnaire and before and after study of courses in evidence based medicine

PubMed Central

Fritsche, L; Greenhalgh, T; Falck-Ytter, Y; Neumayer, H-H; Kunz, R

2002-01-01

Objective To develop and validate an instrument for measuring knowledge and skills in evidence based medicine and to investigate whether short courses in evidence based medicine lead to a meaningful increase in knowledge and skills. Design Development and validation of an assessment instrument and before and after study. Setting Various postgraduate short courses in evidence based medicine in Germany. Participants The instrument was validated with experts in evidence based medicine, postgraduate doctors, and medical students. The effect of courses was assessed by postgraduate doctors from medical and surgical backgrounds. Intervention Intensive 3 day courses in evidence based medicine delivered through tutor facilitated small groups. Main outcome measure Increase in knowledge and skills. Results The questionnaire distinguished reliably between groups with different expertise in evidence based medicine. Experts attained a threefold higher average score than students. Postgraduates who had not attended a course performed better than students but significantly worse than experts. Knowledge and skills in evidence based medicine increased after the course by 57% (mean score before course 6.3 (SD 2.9) v 9.9 (SD 2.8), P<0.001). No difference was found among experts or students in absence of an intervention. Conclusions The instrument reliably assessed knowledge and skills in evidence based medicine. An intensive 3 day course in evidence based medicine led to a significant increase in knowledge and skills. What is already known on this topicNumerous observational studies have investigated the impact of teaching evidence based medicine to healthcare professionals, with conflicting resultsMost of the studies were of poor methodological qualityWhat this study addsAn instrument assessing basic knowledge and skills required for practising evidence based medicine was developed and validatedAn intensive 3 day course on evidence based medicine for doctors from various backgrounds and training level led to a clinically meaningful improvement of knowledge and skills PMID:12468485

Knowledge Preservation for Design of Rocket Systems

NASA Technical Reports Server (NTRS)

Moreman, Douglas

2002-01-01

An engineer at NASA Lewis RC presented a challenge to us at Southern University. Our response to that challenge, stated circa 1993, has evolved into the Knowledge Preservation Project which is here reported. The stated problem was to capture some of the knowledge of retiring NASA engineers and make it useful to younger engineers via computers. We evolved that initial challenge to this - design a system of tools such that, with this system, people might efficiently capture and make available via commonplace computers, deep knowledge of retiring NASA engineers. In the process of proving some of the concepts of this system, we would (and did) capture knowledge from some specific engineers and, so, meet the original challenge along the way to meeting the new. Some of the specific knowledge acquired, particularly that on the RL- 10 engine, was directly relevant to design of rocket engines. We considered and rejected some of the techniques popular in the days we began - specifically "expert systems" and "oral histories". We judged that these old methods had too high a cost per sentence preserved. That cost could be measured in hours of labor of a "knowledge professional". We did spend, particularly in the grant preceding this one, some time creating a couple of "concept maps", one of the latest ideas of the day, but judged this also to be costly in time of a specially trained knowledge-professional. We reasoned that the cost in specialized labor could be lowered if less time were spent being selective about sentences from the engineers and in crafting replacements for those sentences. The trade-off would seem to be that our set of sentences would be less dense in information, but we found a computer-based way around this seeming defect. Our plan, details of which we have been carrying out, was to find methods of extracting information from experts which would be capable of gaining cooperation, and interest, of senior engineers and using their time in a way they would find worthy (and, so, they would give more of their time and recruit time of other engineers as well). We studied these four ways of creating text: 1) the old way, via interviews and discussions - one of our team working with one expert, 2) a group-discussion led by one of the experts themselves and on a topic which inspires interaction of the experts, 3) a spoken dissertation by one expert practiced in giving talks, 4) expropriating, and modifying for our system, some existing reports (such as "oral histories" from the Smithsonian Institution).

Nurses collaborating with cross disciplinary networks: starting to integrate genomics into practice.

PubMed

Adegbola, Maxine

2010-07-01

Nurses and other health-care providers are poised to include genetic discoveries into practice settings and to translate such knowledge for consumer benefit within culturally appropriate contexts. Nurses must seek collaboration with multi-disciplinary networks both locally and internationally. They must also capitalize on the expertise of other seasoned researchers in order to gain national and international exposure, recognition, and funding. Scholarly tailgating is using network relationships to achieve one's professional goals, and capitalizing on expert knowledge from seasoned researchers, educators, and practitioners from diverse international groups. By using scholarly tailgating principles, nurses can become important agents of change for multi-disciplinary networks, and thereby assist in decreasing health disparities. The purpose of this document is to encourage and inspire nurses to seek collaborative multi-disciplinary networks to enable genomic integration into health-care practice and education. Strategies for integrating genomics into practice settings are discussed.

An expert system for diagnostics and estimation of steam turbine components condition

NASA Astrophysics Data System (ADS)

Murmansky, B. E.; Aronson, K. E.; Brodov, Yu. M.

2017-11-01

The report describes an expert system of probability type for diagnostics and state estimation of steam turbine technological subsystems components. The expert system is based on Bayes’ theorem and permits to troubleshoot the equipment components, using expert experience, when there is a lack of baseline information on the indicators of turbine operation. Within a unified approach the expert system solves the problems of diagnosing the flow steam path of the turbine, bearings, thermal expansion system, regulatory system, condensing unit, the systems of regenerative feed-water and hot water heating. The knowledge base of the expert system for turbine unit rotors and bearings contains a description of 34 defects and of 104 related diagnostic features that cause a change in its vibration state. The knowledge base for the condensing unit contains 12 hypotheses and 15 evidence (indications); the procedures are also designated for 20 state parameters estimation. Similar knowledge base containing the diagnostic features and faults hypotheses are formulated for other technological subsystems of turbine unit. With the necessary initial information available a number of problems can be solved within the expert system for various technological subsystems of steam turbine unit: for steam flow path it is the correlation and regression analysis of multifactor relationship between the vibration parameters variations and the regime parameters; for system of thermal expansions it is the evaluation of force acting on the longitudinal keys depending on the temperature state of the turbine cylinder; for condensing unit it is the evaluation of separate effect of the heat exchange surface contamination and of the presence of air in condenser steam space on condenser thermal efficiency performance, as well as the evaluation of term for condenser cleaning and for tube system replacement and so forth. With a lack of initial information the expert system enables to formulate a diagnosis, calculating the probability of faults hypotheses, given the degree of the expert confidence in estimation of turbine components operation parameters.

Imaging work-up for screening of paraganglioma and pheochromocytoma in SDHx mutation carriers: a multicenter prospective study from the PGL.EVA Investigators.

PubMed

Gimenez-Roqueplo, Anne-Paule; Caumont-Prim, Aurore; Houzard, Claire; Hignette, Chantal; Hernigou, Anne; Halimi, Philippe; Niccoli, Patricia; Leboulleux, Sophie; Amar, Laurence; Borson-Chazot, Françoise; Cardot-Bauters, Catherine; Delemer, Brigitte; Chabolle, Frédéric; Coupier, Isabelle; Libé, Rossella; Peitzsch, Mirko; Peyrard, Séverine; Tenenbaum, Florence; Plouin, Pierre-François; Chatellier, Gilles; Rohmer, Vincent

2013-01-01

Recommendations have not been established concerning imaging to screen SDHx mutation carriers for paraganglioma and pheochromocytoma. Our objective was to compare the performance of gadolinium-enhanced magnetic resonance angiography, contrast-enhanced computed tomography, and [(123)I]metaiodo-benzylguanidine and somatostatin receptor scintigraphies for detecting head and neck and thoracic-abdominal-pelvic paragangliomas in SDHx mutation carriers. We conducted a prospective, multicenter study from June 2005 to December 2009 at 23 French medical centers. A total of 238 index cases or relatives carrying mutations in SDHD, SDHB, or SDHC genes were included. Images obtained by each technique were analyzed blind, without knowledge of results from other tests, first in each local center and then centrally. We evaluated sensitivity, specificity, and likelihood ratios for individual and combinations of tests, the gold standard being the consensus of an expert committee. Two hundred two tumors were diagnosed in 96 subjects. At local assessment, the sensitivity of anatomical imaging for detecting all tumors was higher (85.7%) than that of both scintigraphic techniques (42.7% for [(123)I]metaiodo-benzylguanidine and 69.5% for somatostatin receptor scintigraphy), except for thoracic localizations where somatostatin receptor scintigraphy was more sensitive (61.5 vs. 46.2% for anatomical imaging and 30.8% for [(123)I]metaiodo-benzylguanidine scintigraphy). The best diagnostic performance during local assessment was obtained by combining anatomical imaging tests and somatostatin receptor scintigraphy (sensitivity 91.7%). Central assessment significantly increased the sensitivity (98.6%) of tests in combination. In routine practice, the imaging work-up for screening SDHx mutation carriers should include thoraco-abdomino-pelvic computed tomography, head and neck magnetic angiography, and somatostatin receptor scintigraphy. Expert centralized image assessment is recommended.

Bottom-up responses to environmental and social impact assessments: A case study from Guatemala

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

Aguilar-Støen, Mariel, E-mail: mariel.stoen@sum.uio.no; Hirsch, Cecilie; Department of International Environment and Development, Norwegian University of Life Sciences

In this article we take a closer look at resistance to the practice of Environmental Impact Assessment (EIA) in mining and energy projects in Guatemala. Collectivities resisting mining and hydropower projects in Guatemala are increasingly using the evaluations of EIAs conducted by international independent professionals. Reaching out to international experts is facilitated by local communities' engagements in transnational networks bringing together activists, NGOs, scientists, journalists and others. We argue that resistance movements resort to international professionals to challenge the limits imposed on them by the national legislation and institutional arrangements as well as by the way in which EIAs aremore » performed in the country. Further, the engagements in networks that facilitate access to knowledge contribute to strengthen the legitimacy of communities' claims. Challenges to and complaints about EIAs are ways in which affected communities try to reclaim their right to participate in decision-making related to their local environment and the development of their communities. Both complaints about EIAs and the use of transnational networks to attain better participation in decision making processes at local levels, illustrated in this study for Guatemala, are common responses to the advancement of extractive industries and hydropower development across Latin America. The widespread of initiatives to challenge EIAs involving international experts in the region show that EIAs have become a sort of a transnational battleground. - Highlights: • Communities’ opposition to extractive projects is rooted in lack of participation in decision-making, including EIAs • Experts’ evaluations of approved EIAs confirm communities’ claims of poor practices in the public sector • Research presented here shows that local communities linked to transnational networks are able to scale up their demands.« less

Social vulnerability of rural households to flood hazards in western mountainous regions of Henan province, China

NASA Astrophysics Data System (ADS)

Liu, Delin; Li, Yue

2016-05-01

Evaluating social vulnerability is a crucial issue in risk and disaster management. In this study, a household social vulnerability index (HSVI) to flood hazards was developed and used to assess the social vulnerability of rural households in western mountainous regions of Henan province, China. Eight key indicators were identified using existing literature and discussions with experts from multiple disciplines and local farmers, and their weights were determined using principle component analysis (PCA) and an expert scoring method. The results showed that (1) the ratio of perennial work in other places, hazard-related training and illiteracy ratio (15+) were the most dominant factors of social vulnerability. (2) The numbers of high, moderate and low vulnerability households were 14, 64 and 16, respectively, which accounted for 14.9, 68.1 and 17.0 % of the total interviewed rural households, respectively. (3) The correlation coefficient between household social vulnerability scores and casualties in a storm flood in July 2010 was significant at 0.05 significance level (r = 0.748), which indicated that the selected indicators and their weights were valid. (4) Some mitigation strategies to reduce household social vulnerability to flood hazards were proposed, which included (1) improving the local residents' income and their disaster-related knowledge and evacuation skills, (2) developing emergency plans and carrying out emergency drills and training, (3) enhancing the accuracy of disaster monitoring and warning systems and (4) establishing a specific emergency management department and comprehensive rescue systems. These results can provide useful information for rural households and local governments to prepare, mitigate and respond to flood hazards, and the corresponding strategies can help local households to reduce their social vulnerability and improve their ability to resist flood hazard.

Integrating Evidence From Systematic Reviews, Qualitative Research, and Expert Knowledge Using Co-Design Techniques to Develop a Web-Based Intervention for People in the Retirement Transition

PubMed Central

O'Brien, Nicola; Heaven, Ben; Teal, Gemma; Evans, Elizabeth H; Cleland, Claire; Moffatt, Suzanne; Sniehotta, Falko F; White, Martin; Mathers, John C

2016-01-01

Background Integrating stakeholder involvement in complex health intervention design maximizes acceptability and potential effectiveness. However, there is little methodological guidance about how to integrate evidence systematically from various sources in this process. Scientific evidence derived from different approaches can be difficult to integrate and the problem is compounded when attempting to include diverse, subjective input from stakeholders. Objective The intent of the study was to describe and appraise a systematic, sequential approach to integrate scientific evidence, expert knowledge and experience, and stakeholder involvement in the co-design and development of a complex health intervention. The development of a Web-based lifestyle intervention for people in retirement is used as an example. Methods Evidence from three systematic reviews, qualitative research findings, and expert knowledge was compiled to produce evidence statements (stage 1). Face validity of these statements was assessed by key stakeholders in a co-design workshop resulting in a set of intervention principles (stage 2). These principles were assessed for face validity in a second workshop, resulting in core intervention concepts and hand-drawn prototypes (stage 3). The outputs from stages 1-3 were translated into a design brief and specification (stage 4), which guided the building of a functioning prototype, Web-based intervention (stage 5). This prototype was de-risked resulting in an optimized functioning prototype (stage 6), which was subject to iterative testing and optimization (stage 7), prior to formal pilot evaluation. Results The evidence statements (stage 1) highlighted the effectiveness of physical activity, dietary and social role interventions in retirement; the idiosyncratic nature of retirement and well-being; the value of using specific behavior change techniques including those derived from the Health Action Process Approach; and the need for signposting to local resources. The intervention principles (stage 2) included the need to facilitate self-reflection on available resources, personalization, and promotion of links between key lifestyle behaviors. The core concepts and hand-drawn prototypes (stage 3) had embedded in them the importance of time use and work exit planning, personalized goal setting, and acceptance of a Web-based intervention. The design brief detailed the features and modules required (stage 4), guiding the development of wireframes, module content and functionality, virtual mentors, and intervention branding (stage 5). Following an iterative process of intervention testing and optimization (stage 6), the final Web-based intervention prototype of LEAP (Living, Eating, Activity, and Planning in retirement) was produced (stage 7). The approach was resource intensive and required a multidisciplinary team. The design expert made an invaluable contribution throughout the process. Conclusions Our sequential approach fills an important methodological gap in the literature, describing the stages and techniques useful in developing an evidence-based complex health intervention. The systematic and rigorous integration of scientific evidence, expert knowledge and experience, and stakeholder input has resulted in an intervention likely to be acceptable and feasible. PMID:27489143

Integrating Evidence From Systematic Reviews, Qualitative Research, and Expert Knowledge Using Co-Design Techniques to Develop a Web-Based Intervention for People in the Retirement Transition.

PubMed

O'Brien, Nicola; Heaven, Ben; Teal, Gemma; Evans, Elizabeth H; Cleland, Claire; Moffatt, Suzanne; Sniehotta, Falko F; White, Martin; Mathers, John C; Moynihan, Paula

2016-08-03

Integrating stakeholder involvement in complex health intervention design maximizes acceptability and potential effectiveness. However, there is little methodological guidance about how to integrate evidence systematically from various sources in this process. Scientific evidence derived from different approaches can be difficult to integrate and the problem is compounded when attempting to include diverse, subjective input from stakeholders. The intent of the study was to describe and appraise a systematic, sequential approach to integrate scientific evidence, expert knowledge and experience, and stakeholder involvement in the co-design and development of a complex health intervention. The development of a Web-based lifestyle intervention for people in retirement is used as an example. Evidence from three systematic reviews, qualitative research findings, and expert knowledge was compiled to produce evidence statements (stage 1). Face validity of these statements was assessed by key stakeholders in a co-design workshop resulting in a set of intervention principles (stage 2). These principles were assessed for face validity in a second workshop, resulting in core intervention concepts and hand-drawn prototypes (stage 3). The outputs from stages 1-3 were translated into a design brief and specification (stage 4), which guided the building of a functioning prototype, Web-based intervention (stage 5). This prototype was de-risked resulting in an optimized functioning prototype (stage 6), which was subject to iterative testing and optimization (stage 7), prior to formal pilot evaluation. The evidence statements (stage 1) highlighted the effectiveness of physical activity, dietary and social role interventions in retirement; the idiosyncratic nature of retirement and well-being; the value of using specific behavior change techniques including those derived from the Health Action Process Approach; and the need for signposting to local resources. The intervention principles (stage 2) included the need to facilitate self-reflection on available resources, personalization, and promotion of links between key lifestyle behaviors. The core concepts and hand-drawn prototypes (stage 3) had embedded in them the importance of time use and work exit planning, personalized goal setting, and acceptance of a Web-based intervention. The design brief detailed the features and modules required (stage 4), guiding the development of wireframes, module content and functionality, virtual mentors, and intervention branding (stage 5). Following an iterative process of intervention testing and optimization (stage 6), the final Web-based intervention prototype of LEAP (Living, Eating, Activity, and Planning in retirement) was produced (stage 7). The approach was resource intensive and required a multidisciplinary team. The design expert made an invaluable contribution throughout the process. Our sequential approach fills an important methodological gap in the literature, describing the stages and techniques useful in developing an evidence-based complex health intervention. The systematic and rigorous integration of scientific evidence, expert knowledge and experience, and stakeholder input has resulted in an intervention likely to be acceptable and feasible.

An expert systems approach to automated fault management in a regenerative life support subsystem

NASA Technical Reports Server (NTRS)

Malin, J. T.; Lance, N., Jr.

1986-01-01

This paper describes FIXER, a prototype expert system for automated fault management in a regenerative life support subsystem typical of Space Station applications. The development project provided an evaluation of the use of expert systems technology to enhance controller functions in space subsystems. The software development approach permitted evaluation of the effectiveness of direct involvement of the expert in design and development. The approach also permitted intensive observation of the knowledge and methods of the expert. This paper describes the development of the prototype expert system and presents results of the evaluation.

Breast carcinoma during pregnancy. International recommendations from an expert meeting.

PubMed

Loibl, Sibylle; von Minckwitz, Gunter; Gwyn, Karin; Ellis, Paul; Blohmer, Jens U; Schlegelberger, Brigitte; Keller, Monika; Harder, Sebastian; Theriault, Richard L; Crivellari, Diana; Klingebiel, Thomas; Louwen, Frank; Kaufmann, Manfred

2006-01-15

Breast carcinoma during pregnancy (BCP) is a difficult clinical situation, as it appears to put the health of the mother in conflict with that of the fetus. An international expert meeting was conducted to form guidelines on how to diagnose and treat women with BCP. The goal for treatment of the pregnant woman with breast carcinoma is the same as that of the nonpregnant breast carcinoma patient: local control of disease and prevention of systemic metastases. However, certain treatment modalities need to be modified because of the potential for adverse effects on the fetus. There is evidence to support the safety of anthracycline-based chemotherapy during the second and third trimesters of pregnancy (Oxford Level of Evidence [LOE] 2b). Because of the lack of evidence, the expert opinion was not to recommend the routine use of newer cytotoxic drugs like the taxanes during pregnancy (LOE 5). The recommendations provided should help to reach informed decision making by the patient. The ongoing prospective collection of data on BCP, such as that at the University of Texas M.D. Anderson Cancer Center (UTMDACC) and that of the German Breast Group/Breast International Group (GBG/BIG), is necessary to further our knowledge regarding the treatment of this unique group of breast carcinoma patients.

Anti-HER2 Therapy Beyond Second-Line for HER2-Positive Metastatic Breast Cancer: A Short Review and Recommendations for Several Clinical Scenarios from a Spanish Expert Panel

PubMed Central

Martínez-Jañez, Noelia; Chacón, Ignacio; de Juan, Ana; Cruz-Merino, Luis; del Barco, Sònia; Fernández, Isaura; García-Teijido, Paula; Gómez-Bernal, Amalia; Plazaola, Arrate; Ponce, José; Servitja, Sonia; Zamora, Pilar

2016-01-01

Summary Background The aim of this project was to provide an expert opinion regarding anti-human epidermal growth factor receptor 2 (HER2) therapy beyond second-line treatment of metastatic breast cancer (mBC). Methods A group of experts discussed specific issues concerning anti-HER2 therapy in late-line settings in mBC. Results Trastuzumab emtansine (T-DM1) or dual HER2 blockade appeared to be good options for HER2-positive mBC after ≥ 2 HER2-targeted therapies. Once an objective response has been achieved with anti-HER2-containing therapy, the anti-HER2 agent can be continued until progression of the disease, unacceptable toxicity or patient decision. mBC treated with ≥ 3 consecutive lines of anti-HER therapy, ≥ 1 being a dual HER2 blockade and with early progression of disease during a fourth or later-line treatment, are clinically resistant to anti-HER therapy. For progression of metastasis in the brain after anti-HER2 therapy, lapatinib and chemotherapy appear to be a good alternative after best local treatment. Conclusions Further clinical trials are needed to provide valuable knowledge about the best treatment options in the later settings of mBC. PMID:27239176

Matrix Failure Modes and Effects Analysis as a Knowledge Base for a Real Time Automated Diagnosis Expert System

NASA Technical Reports Server (NTRS)

Herrin, Stephanie; Iverson, David; Spukovska, Lilly; Souza, Kenneth A. (Technical Monitor)

1994-01-01

Failure Modes and Effects Analysis contain a wealth of information that can be used to create the knowledge base required for building automated diagnostic Expert systems. A real time monitoring and diagnosis expert system based on an actual NASA project's matrix failure modes and effects analysis was developed. This Expert system Was developed at NASA Ames Research Center. This system was first used as a case study to monitor the Research Animal Holding Facility (RAHF), a Space Shuttle payload that is used to house and monitor animals in orbit so the effects of space flight and microgravity can be studied. The techniques developed for the RAHF monitoring and diagnosis Expert system are general enough to be used for monitoring and diagnosis of a variety of other systems that undergo a Matrix FMEA. This automated diagnosis system was successfully used on-line and validated on the Space Shuttle flight STS-58, mission SLS-2 in October 1993.

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

PubMed Central

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

1992-01-01

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

Back-and-Forth Methodology for Objective Voice Quality Assessment: From/to Expert Knowledge to/from Automatic Classification of Dysphonia

NASA Astrophysics Data System (ADS)

Fredouille, Corinne; Pouchoulin, Gilles; Ghio, Alain; Revis, Joana; Bonastre, Jean-François; Giovanni, Antoine

2009-12-01

This paper addresses voice disorder assessment. It proposes an original back-and-forth methodology involving an automatic classification system as well as knowledge of the human experts (machine learning experts, phoneticians, and pathologists). The goal of this methodology is to bring a better understanding of acoustic phenomena related to dysphonia. The automatic system was validated on a dysphonic corpus (80 female voices), rated according to the GRBAS perceptual scale by an expert jury. Firstly, focused on the frequency domain, the classification system showed the interest of 0-3000 Hz frequency band for the classification task based on the GRBAS scale. Later, an automatic phonemic analysis underlined the significance of consonants and more surprisingly of unvoiced consonants for the same classification task. Submitted to the human experts, these observations led to a manual analysis of unvoiced plosives, which highlighted a lengthening of VOT according to the dysphonia severity validated by a preliminary statistical analysis.

Determining rules for closing customer service centers: A public utility company's fuzzy decision

NASA Technical Reports Server (NTRS)

Dekorvin, Andre; Shipley, Margaret F.; Lea, Robert N.

1992-01-01

In the present work, we consider the general problem of knowledge acquisition under uncertainty. Simply stated, the problem reduces to the following: how can we capture the knowledge of an expert when the expert is unable to clearly formulate how he or she arrives at a decision? A commonly used method is to learn by examples. We observe how the expert solves specific cases and from this infer some rules by which the decision may have been made. Unique to our work is the fuzzy set representation of the conditions or attributes upon which the expert may possibly base his fuzzy decision. From our examples, we infer certain and possible fuzzy rules for closing a customer service center and illustrate the importance of having the decision closely relate to the conditions under consideration.

Building an adaptive agent to monitor and repair the electrical power system of an orbital satellite

NASA Technical Reports Server (NTRS)

Tecuci, Gheorghe; Hieb, Michael R.; Dybala, Tomasz

1995-01-01

Over several years we have developed a multistrategy apprenticeship learning methodology for building knowledge-based systems. Recently we have developed and applied our methodology to building intelligent agents. This methodology allows a subject matter expert to build an agent in the same way in which the expert would teach a human apprentice. The expert will give the agent specific examples of problems and solutions, explanations of these solutions, or supervise the agent as it solves new problems. During such interactions, the agent learns general rules and concepts, continuously extending and improving its knowledge base. In this paper we present initial results on applying this methodology to build an intelligent adaptive agent for monitoring and repair of the electrical power system of an orbital satellite, stressing the interaction with the expert during apprenticeship learning.

Application of artificial intelligence to pharmacy and medicine.

PubMed

Dasta, J F

1992-04-01

Artificial intelligence (AI) is a branch of computer science dealing with solving problems using symbolic programming. It has evolved into a problem solving science with applications in business, engineering, and health care. One application of AI is expert system development. An expert system consists of a knowledge base and inference engine, coupled with a user interface. A crucial aspect of expert system development is knowledge acquisition and implementing computable ways to solve problems. There have been several expert systems developed in medicine to assist physicians with medical diagnosis. Recently, several programs focusing on drug therapy have been described. They provide guidance on drug interactions, drug therapy monitoring, and drug formulary selection. There are many aspects of pharmacy that AI can have an impact on and the reader is challenged to consider these possibilities because they may some day become a reality in pharmacy.

Computational aerodynamics and artificial intelligence

NASA Technical Reports Server (NTRS)

Mehta, U. B.; Kutler, P.

1984-01-01

The general principles of artificial intelligence are reviewed and speculations are made concerning how knowledge based systems can accelerate the process of acquiring new knowledge in aerodynamics, how computational fluid dynamics may use expert systems, and how expert systems may speed the design and development process. In addition, the anatomy of an idealized expert system called AERODYNAMICIST is discussed. Resource requirements for using artificial intelligence in computational fluid dynamics and aerodynamics are examined. Three main conclusions are presented. First, there are two related aspects of computational aerodynamics: reasoning and calculating. Second, a substantial portion of reasoning can be achieved with artificial intelligence. It offers the opportunity of using computers as reasoning machines to set the stage for efficient calculating. Third, expert systems are likely to be new assets of institutions involved in aeronautics for various tasks of computational aerodynamics.

Place in Pacific Islands Climate Education

NASA Astrophysics Data System (ADS)

Barros, C.; Koh, M. W.

2015-12-01

Understanding place, including both the environment and its people, is essential to understanding our climate, climate change, and its impacts. For us to develop a sense of our place, we need to engage in multiple ways of learning: observation, experimentation, and opportunities to apply new knowledge (Orr, 1992). This approach allows us to access different sources of knowledge and then create local solutions for local issues. It is especially powerful when we rely on experts and elders in our own community along with information from the global community.The Pacific islands Climate Education Partnership (PCEP) is a collaboration of partners—school systems, nongovernmental organizations, and government agencies—working to support learning and teaching about climate in the Pacific. Since 2009, PCEP partners have been working together to develop and implement classroom resources, curriculum standards, and teacher professional learning opportunities in which learners approach climate change and its impacts first through the lens of their own place. Such an approach to putting place central to teaching and learning about climate requires partnership and opportunities for learners to explore solutions for and with their communities. In this presentation, we will share the work unfolding in the Republic of the Marshall Islands (RMI) as one example of PCEP's approach to place-based climate education. Three weeklong K-12 teacher professional learning workshops took place during June-July 2015 in Majuro, RMI on learning gardens, climate science, and project-based learning. Each workshop was co-taught with local partners and supports educators in teaching climate-related curriculum standards through tasks that can foster sense of place through observation, experimentation, and application of new knowledge. Additionally, we will also share PCEP's next steps in place-based climate education, specifically around emerging conversations about the importance of highlighting stories of place to generate local solutions for local issues, as well as further global awareness about climate change impacts in the Pacific.

Knowledge Base Editor (SharpKBE)

NASA Technical Reports Server (NTRS)

Tikidjian, Raffi; James, Mark; Mackey, Ryan

2007-01-01

The SharpKBE software provides a graphical user interface environment for domain experts to build and manage knowledge base systems. Knowledge bases can be exported/translated to various target languages automatically, including customizable target languages.

Developing expectations regarding the boundaries of expertise.

PubMed

Landrum, Asheley R; Mills, Candice M

2015-01-01

Three experiments examined elementary school-aged children's and adults' expectations regarding what specialists (i.e., those with narrow domains of expertise) and generalists (i.e., those with broad domains of expertise) are likely to know. Experiment 1 demonstrated developmental differences in the ability to differentiate between generalists and specialists, with younger children believing generalists have more specific trivia knowledge than older children and adults believed. Experiment 2 demonstrated that children and adults expected generalists to have more underlying principles knowledge than specific trivia knowledge about unfamiliar animals. However, they believed that generalists would have more of both types of knowledge than themselves. Finally, Experiment 3 demonstrated that children and adults recognized that underlying principles knowledge can be generalized between topics closely related to the specialists' domains of expertise. However, they did not recognize when this knowledge was generalizable to topics slightly less related, expecting generalists to know only as much as they would. Importantly, this work contributes to the literature by showing how much of and what kinds of knowledge different types of experts are expected to have. In sum, this work provides insight into some of the ways children's notions of expertise change over development. The current research demonstrates that between the ages of 5 and 10, children are developing the ability to recognize how experts' knowledge is likely to be limited. That said, even older children at times struggle to determine the breadth of an experts' knowledge. Copyright © 2014 Elsevier B.V. All rights reserved.

Process evaluation of knowledge transfer across industries: Leveraging Coca-Cola's supply chain expertise for medicine availability in Tanzania.

PubMed

Linnander, Erika; Yuan, Christina T; Ahmed, Shirin; Cherlin, Emily; Talbert-Slagle, Kristina; Curry, Leslie A

2017-01-01

Persistent gaps in the availability of essential medicines have slowed the achievement of global health targets. Despite the supply chain knowledge and expertise that ministries of health might glean from other industries, limited empirical research has examined the process of knowledge transfer from other industries into global public health. We examined a partnership designed to improve the availability of medical supplies in Tanzania by transferring knowledge from The Coca-Cola system to Tanzania's Medical Stores Department (MSD). We conducted a process evaluation including in-depth interviews with 70 participants between July 2011 and May 2014, corresponding to each phase of the partnership, with focus on challenges and strategies to address them, as well as benefits perceived by partners. Partners faced challenges in (1) identifying relevant knowledge to transfer, (2) translating operational solutions from Coca-Cola to MSD, and (3) maintaining momentum between project phases. Strategies to respond to these challenges emerged through real-time problem solving and included (1) leveraging the receptivity of MSD leadership, (2) engaging a boundary spanner to identify knowledge to transfer, (3) promoting local recognition of commonalities across industries, (4) engaging external technical experts to manage translation activities, (5) developing tools with visible benefits for MSD, (6) investing in local relationships, and (7) providing time and space for the partnership model to evolve. Benefits of the partnership perceived by MSD staff included enhanced collaboration and communication, more proactive orientations in managing operations, and greater attention to performance management. Benefits perceived by Coca-Cola staff included strengthened knowledge transfer capability and enhanced job satisfaction. Linking theoretical constructs with practical experiences from the field, we highlight the challenges, emergent strategies, and perceived benefits of a partnership across industry boundaries that may be useful to others seeking to promote the transfer of knowledge to improve global health.

Process evaluation of knowledge transfer across industries: Leveraging Coca-Cola’s supply chain expertise for medicine availability in Tanzania

PubMed Central

Yuan, Christina T.; Ahmed, Shirin; Cherlin, Emily; Talbert-Slagle, Kristina; Curry, Leslie A.

2017-01-01

Persistent gaps in the availability of essential medicines have slowed the achievement of global health targets. Despite the supply chain knowledge and expertise that ministries of health might glean from other industries, limited empirical research has examined the process of knowledge transfer from other industries into global public health. We examined a partnership designed to improve the availability of medical supplies in Tanzania by transferring knowledge from The Coca-Cola system to Tanzania’s Medical Stores Department (MSD). We conducted a process evaluation including in-depth interviews with 70 participants between July 2011 and May 2014, corresponding to each phase of the partnership, with focus on challenges and strategies to address them, as well as benefits perceived by partners. Partners faced challenges in (1) identifying relevant knowledge to transfer, (2) translating operational solutions from Coca-Cola to MSD, and (3) maintaining momentum between project phases. Strategies to respond to these challenges emerged through real-time problem solving and included (1) leveraging the receptivity of MSD leadership, (2) engaging a boundary spanner to identify knowledge to transfer, (3) promoting local recognition of commonalities across industries, (4) engaging external technical experts to manage translation activities, (5) developing tools with visible benefits for MSD, (6) investing in local relationships, and (7) providing time and space for the partnership model to evolve. Benefits of the partnership perceived by MSD staff included enhanced collaboration and communication, more proactive orientations in managing operations, and greater attention to performance management. Benefits perceived by Coca-Cola staff included strengthened knowledge transfer capability and enhanced job satisfaction. Linking theoretical constructs with practical experiences from the field, we highlight the challenges, emergent strategies, and perceived benefits of a partnership across industry boundaries that may be useful to others seeking to promote the transfer of knowledge to improve global health. PMID:29121051

Section-constrained local geological interface dynamic updating method based on the HRBF surface

NASA Astrophysics Data System (ADS)

Guo, Jiateng; Wu, Lixin; Zhou, Wenhui; Li, Chaoling; Li, Fengdan

2018-02-01

Boundaries, attitudes and sections are the most common data acquired from regional field geological surveys, and they are used for three-dimensional (3D) geological modelling. However, constructing topologically consistent 3D geological models from rapid and automatic regional modelling with convenient local modifications remains unresolved. In previous works, the Hermite radial basis function (HRBF) surface was introduced for the simulation of geological interfaces from geological boundaries and attitudes, which allows 3D geological models to be automatically extracted from the modelling area by the interfaces. However, the reasonability and accuracy of non-supervised subsurface modelling is limited without further modifications generated through explanations and analyses performed by geology experts. In this paper, we provide flexible and convenient manual interactive manipulation tools for geologists to sketch constraint lines, and these tools may help geologists transform and apply their expert knowledge to the models. In the modified modelling workflow, the geological sections were treated as auxiliary constraints to construct more reasonable 3D geological models. The geometric characteristics of section lines were abstracted to coordinates and normal vectors, and along with the transformed coordinates and vectors from boundaries and attitudes, these characteristics were adopted to co-calculate the implicit geological surface function parameters of the HRBF equations and form constrained geological interfaces from topographic (boundaries and attitudes) and subsurface data (sketched sections). Based on this new modelling method, a prototype system was developed, in which the section lines could be imported from databases or interactively sketched, and the models could be immediately updated after the new constraints were added. Experimental comparisons showed that all boundary, attitude and section data are well represented in the constrained models, which are consistent with expert explanations and help improve the quality of the models.

What Do Geoscience Experts and Novices Look At and What Do They See When Viewing and Interpreting Data Visualizations?

NASA Astrophysics Data System (ADS)

Kastens, K. A.; Shipley, T. F.; Boone, A.

2012-12-01

When geoscience experts look at data visualizations, they can "see" structures, and processes and traces of Earth history. When students look at those same visualizations, they may see only blotches of color, dots or squiggles. What are those experts doing, and how can students learn to do the same? We report on a study in which experts (>10 years of geoscience research experience) and novices (undergrad psychology students) examine shaded-relief/color-coded images of topography/bathymetry, while answering questions aloud and being eye-tracked. Images were a global map, two high-res images of continental terrain and two of oceanic terrain, with hi-res localities chosen to display distinctive traces of important earth processes. The differences in what they look at as recorded by eye-tracking are relatively subtle. On the global image, novices tend to focus on continents, whereas experts distribute their attention more evenly across continents and oceans. Experts universally access the available scale information (distance scale, lat/long axes), whereas most students do not. Novices do attend substantially and spontaneously to the salient geomorphological features in the high-res images: seamounts, mid-ocean ridge/transform intersection, erosional river channels, and compressional ridges and valley system. The more marked differences come in what respondents see, as captured in video recordings of their words and gestures in response to experimenter's questions. When their attention is directed to a small and distinctive part of a high-res image and they are asked to "….describe what you see…", experts typically produce richly detailed descriptions that may include the regional depth/altitude, local relief, shape and spatial distribution of major features, symmetry or lack thereof, cross-cutting relationships, presence of lineations and their orientations, and similar geomorphological details. Following or interwoven with these rich descriptions, some experts also offer interpretations of causal Earth processes. We identified four types of novice answers: (a) "flat" answers, in which the student describes the patches of color on the screen with no mention of shape or relief; (b) "thing" answers, in which the student mentions an inappropriate object, such as "the Great Wall of China," (c) geomorphology answers, in which the student talks about depth/altitude, relief, or shapes of landforms, and (d) process answers, in which student talks about earth processes, such as earthquakes, erosion, or plate tectonics. Novice "geomorphology" (c) answers resemble expert responses, but lack the rich descriptive detail. The "process" (d) category includes many interpretations that lack any grounding in the evidentiary base available in the viewed data. These findings suggest that instruction around earth data should include an emphasis on thoroughly and accurately describing the features that are present in the data--a skill that our experts display and our novices mostly lack. It is unclear, though, how best to sequence the teaching of descriptive and interpretive skills, since the experts' attention to empirical features in the data is steered by their knowledge of which features have causal significance.

Expert Systems for Libraries at SCIL [Small Computers in Libraries]'88.

ERIC Educational Resources Information Center

Kochtanek, Thomas R.; And Others

1988-01-01

Six brief papers on expert systems for libraries cover (1) a knowledge-based approach to database design; (2) getting started in expert systems; (3) using public domain software to develop a business reference system; (4) a music cataloging inquiry system; (5) linguistic analysis of reference transactions; and (6) a model of a reference librarian.…

Perspective on intelligent avionics

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

Jones, H.L.

1987-01-01

Technical issues which could potentially limit the capability and acceptibility of expert systems decision-making for avionics applications are addressed. These issues are: real-time AI, mission-critical software, conventional algorithms, pilot interface, knowledge acquisition, and distributed expert systems. Examples from on-going expert system development programs are presented to illustrate likely architectures and applications of future intelligent avionic systems. 13 references.

Adaptation and validation of the REGEN expert system for the Central Appalachians

Treesearch

Lance A. Vickers; Thomas R. Fox; David L. Loftis; David A. Boucugnani

2011-01-01

REGEN is an expert system that predicts future species composition at the onset of stem exclusion using preharvest stand conditions. To extend coverage into hardwood stands of the Central Appalachians, we developed REGEN knowledge bases for four site qualities (xeric, subxeric, submesic, mesic) based on relevant literature and expert opinion. Data were collected from...

What Matters Most: A Comparison of Expert and Novice Teachers' Noticing of Mathematics Classroom Events

ERIC Educational Resources Information Center

Huang, Rongjin; Li, Yeping

2012-01-01

In this study, we examined 10 expert and 10 novice teachers' noticing of classroom events in China. It was found that both expert and novice teachers, who were selected from two cities in China, highly attended to developing students' mathematics knowledge coherently and developing students' mathematical thinking and ability; they also paid…

Multi-viewpoint clustering analysis

NASA Technical Reports Server (NTRS)

Mehrotra, Mala; Wild, Chris

1993-01-01

In this paper, we address the feasibility of partitioning rule-based systems into a number of meaningful units to enhance the comprehensibility, maintainability and reliability of expert systems software. Preliminary results have shown that no single structuring principle or abstraction hierarchy is sufficient to understand complex knowledge bases. We therefore propose the Multi View Point - Clustering Analysis (MVP-CA) methodology to provide multiple views of the same expert system. We present the results of using this approach to partition a deployed knowledge-based system that navigates the Space Shuttle's entry. We also discuss the impact of this approach on verification and validation of knowledge-based systems.

Representation and matching of knowledge to design digital systems

NASA Technical Reports Server (NTRS)

Jones, J. U.; Shiva, S. G.

1988-01-01

A knowledge-based expert system is described that provides an approach to solve a problem requiring an expert with considerable domain expertise and facts about available digital hardware building blocks. To design digital hardware systems from their high level VHDL (Very High Speed Integrated Circuit Hardware Description Language) representation to their finished form, a special data representation is required. This data representation as well as the functioning of the overall system is described.

[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.

Expert database system for quality control

NASA Astrophysics Data System (ADS)

Wang, Anne J.; Li, Zhi-Cheng

1993-09-01

There are more competitors today. Markets are not homogeneous they are fragmented into increasingly focused niches requiring greater flexibility in the product mix shorter manufacturing production runs and above allhigher quality. In this paper the author identified a real-time expert system as a way to improve plantwide quality management. The quality control expert database system (QCEDS) by integrating knowledge of experts in operations quality management and computer systems use all information relevant to quality managementfacts as well as rulesto determine if a product meets quality standards. Keywords: expert system quality control data base

Planning bioinformatics workflows using an expert system.

PubMed

Chen, Xiaoling; Chang, Jeffrey T

2017-04-15

Bioinformatic analyses are becoming formidably more complex due to the increasing number of steps required to process the data, as well as the proliferation of methods that can be used in each step. To alleviate this difficulty, pipelines are commonly employed. However, pipelines are typically implemented to automate a specific analysis, and thus are difficult to use for exploratory analyses requiring systematic changes to the software or parameters used. To automate the development of pipelines, we have investigated expert systems. We created the Bioinformatics ExperT SYstem (BETSY) that includes a knowledge base where the capabilities of bioinformatics software is explicitly and formally encoded. BETSY is a backwards-chaining rule-based expert system comprised of a data model that can capture the richness of biological data, and an inference engine that reasons on the knowledge base to produce workflows. Currently, the knowledge base is populated with rules to analyze microarray and next generation sequencing data. We evaluated BETSY and found that it could generate workflows that reproduce and go beyond previously published bioinformatics results. Finally, a meta-investigation of the workflows generated from the knowledge base produced a quantitative measure of the technical burden imposed by each step of bioinformatics analyses, revealing the large number of steps devoted to the pre-processing of data. In sum, an expert system approach can facilitate exploratory bioinformatic analysis by automating the development of workflows, a task that requires significant domain expertise. https://github.com/jefftc/changlab. jeffrey.t.chang@uth.tmc.edu. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Planning bioinformatics workflows using an expert system

PubMed Central

Chen, Xiaoling; Chang, Jeffrey T.

2017-01-01

Abstract Motivation: Bioinformatic analyses are becoming formidably more complex due to the increasing number of steps required to process the data, as well as the proliferation of methods that can be used in each step. To alleviate this difficulty, pipelines are commonly employed. However, pipelines are typically implemented to automate a specific analysis, and thus are difficult to use for exploratory analyses requiring systematic changes to the software or parameters used. Results: To automate the development of pipelines, we have investigated expert systems. We created the Bioinformatics ExperT SYstem (BETSY) that includes a knowledge base where the capabilities of bioinformatics software is explicitly and formally encoded. BETSY is a backwards-chaining rule-based expert system comprised of a data model that can capture the richness of biological data, and an inference engine that reasons on the knowledge base to produce workflows. Currently, the knowledge base is populated with rules to analyze microarray and next generation sequencing data. We evaluated BETSY and found that it could generate workflows that reproduce and go beyond previously published bioinformatics results. Finally, a meta-investigation of the workflows generated from the knowledge base produced a quantitative measure of the technical burden imposed by each step of bioinformatics analyses, revealing the large number of steps devoted to the pre-processing of data. In sum, an expert system approach can facilitate exploratory bioinformatic analysis by automating the development of workflows, a task that requires significant domain expertise. Availability and Implementation: https://github.com/jefftc/changlab Contact: jeffrey.t.chang@uth.tmc.edu PMID:28052928

Knowledge structures and the acquisition of a complex skill.

PubMed

Day, E A; Arthur, W; Gettman, D

2001-10-01

The purpose of this study was to examine the viability of knowledge structures as an operationalization of learning in the context of a task that required a high degree of skill. Over the course of 3 days, 86 men participated in 9 training sessions and learned a complex video game. At the end of acquisition, participants' knowledge structures were assessed. After a 4-day nonpractice interval, trainees completed tests of skill retention and skill transfer. Findings indicated that the similarity of trainees' knowledge structures to an expert structure was correlated with skill acquisition and was predictive of skill retention and skill transfer. However, the magnitude of these effects was dependent on the method used to derive the expert referent structure. Moreover, knowledge structures mediated the relationship between general cognitive ability and skill-based performance.

A simple scaling approach to produce climate scenarios of local precipitation extremes for the Netherlands

NASA Astrophysics Data System (ADS)

Lenderink, Geert; Attema, Jisk

2015-08-01

Scenarios of future changes in small scale precipitation extremes for the Netherlands are presented. These scenarios are based on a new approach whereby changes in precipitation extremes are set proportional to the change in water vapor amount near the surface as measured by the 2m dew point temperature. This simple scaling framework allows the integration of information derived from: (i) observations, (ii) a new unprecedentedly large 16 member ensemble of simulations with the regional climate model RACMO2 driven by EC-Earth, and (iii) short term integrations with a non-hydrostatic model Harmonie. Scaling constants are based on subjective weighting (expert judgement) of the three different information sources taking also into account previously published work. In all scenarios local precipitation extremes increase with warming, yet with broad uncertainty ranges expressing incomplete knowledge of how convective clouds and the atmospheric mesoscale circulation will react to climate change.

Marking out the clinical expert/clinical leader/clinical scholar: perspectives from nurses in the clinical arena.

PubMed

Mannix, Judy; Wilkes, Lesley; Jackson, Debra

2013-01-01

Clinical scholarship has been conceptualised and theorised in the nursing literature for over 30 years but no research has captured nurses' clinicians' views on how it differs or is the same as clinical expertise and clinical leadership. The aim of this study was to determine clinical nurses' understanding of the differences and similarities between the clinical expert, clinical leader and clinical scholar. A descriptive interpretative qualitative approach using semi-structured interviews with 18 practising nurses from Australia, Canada and England. The audio-taped interviews were transcribed and the text coded for emerging themes. The themes were sorted into categories of clinical expert, clinical leader and clinical scholarship as described by the participants. These themes were then compared and contrasted and the essential elements that characterise the nursing roles of the clinical expert, clinical leader and clinical scholar were identified. Clinical experts were seen as linking knowledge to practice with some displaying clinical leadership and scholarship. Clinical leadership is seen as a positional construct with a management emphasis. For the clinical scholar they linked theory and practice and encouraged research and dissemination of knowledge. There are distinct markers for the roles of clinical expert, clinical leader and clinical scholar. Nurses working in one or more of these roles need to work together to improve patient care. An 'ideal nurse' may be a blending of all three constructs. As nursing is a practice discipline its scholarship should be predominantly based on clinical scholarship. Nurses need to be encouraged to go beyond their roles as clinical leaders and experts to use their position to challenge and change through the propagation of knowledge to their community.

Marking out the clinical expert/clinical leader/clinical scholar: perspectives from nurses in the clinical arena

PubMed Central

2013-01-01

Background Clinical scholarship has been conceptualised and theorised in the nursing literature for over 30 years but no research has captured nurses’ clinicians’ views on how it differs or is the same as clinical expertise and clinical leadership. The aim of this study was to determine clinical nurses’ understanding of the differences and similarities between the clinical expert, clinical leader and clinical scholar. Methods A descriptive interpretative qualitative approach using semi-structured interviews with 18 practising nurses from Australia, Canada and England. The audio-taped interviews were transcribed and the text coded for emerging themes. The themes were sorted into categories of clinical expert, clinical leader and clinical scholarship as described by the participants. These themes were then compared and contrasted and the essential elements that characterise the nursing roles of the clinical expert, clinical leader and clinical scholar were identified. Results Clinical experts were seen as linking knowledge to practice with some displaying clinical leadership and scholarship. Clinical leadership is seen as a positional construct with a management emphasis. For the clinical scholar they linked theory and practice and encouraged research and dissemination of knowledge. Conclusion There are distinct markers for the roles of clinical expert, clinical leader and clinical scholar. Nurses working in one or more of these roles need to work together to improve patient care. An ‘ideal nurse’ may be a blending of all three constructs. As nursing is a practice discipline its scholarship should be predominantly based on clinical scholarship. Nurses need to be encouraged to go beyond their roles as clinical leaders and experts to use their position to challenge and change through the propagation of knowledge to their community. PMID:23587282

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.

Autonomous power expert fault diagnostic system for Space Station Freedom electrical power system testbed

NASA Technical Reports Server (NTRS)

Truong, Long V.; Walters, Jerry L.; Roth, Mary Ellen; Quinn, Todd M.; Krawczonek, Walter M.

1990-01-01

The goal of the Autonomous Power System (APS) program is to develop and apply intelligent problem solving and control to the Space Station Freedom Electrical Power System (SSF/EPS) testbed being developed and demonstrated at NASA Lewis Research Center. The objectives of the program are to establish artificial intelligence technology paths, to craft knowledge-based tools with advanced human-operator interfaces for power systems, and to interface and integrate knowledge-based systems with conventional controllers. The Autonomous Power EXpert (APEX) portion of the APS program will integrate a knowledge-based fault diagnostic system and a power resource planner-scheduler. Then APEX will interface on-line with the SSF/EPS testbed and its Power Management Controller (PMC). The key tasks include establishing knowledge bases for system diagnostics, fault detection and isolation analysis, on-line information accessing through PMC, enhanced data management, and multiple-level, object-oriented operator displays. The first prototype of the diagnostic expert system for fault detection and isolation has been developed. The knowledge bases and the rule-based model that were developed for the Power Distribution Control Unit subsystem of the SSF/EPS testbed are described. A corresponding troubleshooting technique is also described.

Cartilage segmentation of 3D MRI scans of the osteoarthritic knee combining user knowledge and active contours

NASA Astrophysics Data System (ADS)

Lynch, John A.; Zaim, Souhil; Zhao, Jenny; Stork, Alexander; Peterfy, Charles G.; Genant, Harry K.

2000-06-01

A technique for segmentation of articular cartilage from 3D MRI scans of the knee has been developed. It overcomes the limitations of the conventionally used region growing techniques, which are prone to inter- and intra-observer variability, and which can require much manual intervention. We describe a hybrid segmentation method combining expert knowledge with directionally oriented Canny filters, cost functions and cubic splines. After manual initialization, the technique utilized 3 cost functions which aided automated detection of cartilage and its boundaries. Using the sign of the edge strength, and the local direction of the boundary, this technique is more reliable than conventional 'snakes,' and the user had little control over smoothness of boundaries. This means that the automatically detected boundary can conform to the true shape of the real boundary, also allowing reliable detection of subtle local lesions on the normally smooth cartilage surface. Manual corrections, with possible re-optimization were sometimes needed. When compared to the conventionally used region growing techniques, this newly described technique measured local cartilage volume with 3 times better reproducibility, and involved two thirds less human interaction. Combined with the use of 3D image registration, the new technique should also permit unbiased segmentation of followup scans by automated initialization from a baseline segmentation of an earlier scan of the same patient.

An Expert System for Diagnosing Eye Diseases using Forward Chaining Method

NASA Astrophysics Data System (ADS)

Munaiseche, C. P. C.; Kaparang, D. R.; Rompas, P. T. D.

2018-02-01

Expert System is a system that seeks to adopt human knowledge to the computer, so that the computer can solve problems which are usually done by experts. The purpose of medical expert system is to support the diagnosis process of physicians. It considers facts and symptoms to provide diagnosis. This implies that a medical expert system uses knowledge about diseases and facts about the patients to suggest diagnosis. The aim of this research is to design an expert system application for diagnosing eye diseases using forward chaining method and to figure out user acceptance to this application through usability testing. Eye is selected because it is one of the five senses which is very sensitive and important. The scope of the work is extended to 16 types of eye diseases with 41 symptoms of the disease, arranged in 16 rules. The computer programming language employed was the PHP programming language and MySQL as the Relational Database Management System (RDBMS). The results obtained showed that the expert system was able to successfully diagnose eye diseases corresponding to the selected symptoms entered as query and the system evaluation through usability testing showed the expert system for diagnosis eye diseases had very good rate of usability, which includes learnability, efficiency, memorability, errors, and satisfaction so that the system can be received in the operational environment.

Bridging Troubled Waters: Historians, Natural Resource Litigation, and the Expert Witness Phenomenon.

PubMed

Brescia, Michael M

2015-02-01

This special issue of The Public Historian examines the nature and scope of the historian's role as a consultant and expert witness in natural resource litigation. The introductory essay identifies the major issues and challenges that historians face when they bring their knowledge, skills, and professional best standards into law offices and courtrooms, while also positing a conceptual framework for public history practitioners to better understand and appreciate the larger stakes in conducting research for environmental litigation. The author delineates his own experience as an expert in certain water rights cases in the American Southwest where knowledge of the Spanish and Mexican civil law of property is essential.

A center for commercial development of space: Real-time satellite mapping. Remote sensing-based agricultural information expert system

NASA Technical Reports Server (NTRS)

Hadipriono, Fabian C.; Diaz, Carlos F.; Merritt, Earl S.

1989-01-01

The research project results in a powerful yet user friendly CROPCAST expert system for use by a client to determine the crop yield production of a certain crop field. The study is based on the facts that heuristic assessment and decision making in agriculture are significant and dominate much of agribusiness. Transfer of the expert knowledge concerning remote sensing based crop yield production into a specific expert system is the key program in this study. A knowledge base consisting of a root frame, CROP-YIELD-FORECAST, and four subframes, namely, SATELLITE, PLANT-PHYSIOLOGY, GROUND, and MODEL were developed to accommodate the production rules obtained from the domain expert. The expert system shell Personal Consultant Plus version 4.0. was used for this purpose. An external geographic program was integrated to the system. This project is the first part of a completely built expert system. The study reveals that much effort was given to the development of the rules. Such effort is inevitable if workable, efficient, and accurate rules are desired. Furthermore, abundant help statements and graphics were included. Internal and external display routines add to the visual capability of the system. The work results in a useful tool for the client for making decisions on crop yield production.

Managing cows: an ethnography of breeding practices and uses of reproductive technology in contemporary dairy farming in Lombardy (Italy).

PubMed

Grasseni, Cristina

2007-06-01

The aim of this article is to contribute detailed ethnographic material to broaden the scope of what we mean by reproductive technology. Technology can be defined not only by a series of laboratory techniques (such as artificial insemination and embryo transfer) that are drafted into the daily management of the animal body, but also by a range of on-farm management strategies and working routines, as well as the cultural dispositions, social networks and tacit knowledge of the actors involved. RT is communicated to lay operators and disseminated amongst semi-professional figures such as breed experts, herd inspectors and technical consultants. The practical contexts in which reproductive knowledge is popularized and applied provide ample scope for local negotiations, resistance and conflict. Professional knowledge about breed-improvement is personalised and appropriated by operators and plays a role in power relations and the exercise of personal charisma as well as being specific to context, in particular the nuances of pre-existing relationships of trust, friendship, kinship or hierarchy. No wonder then that many ambivalences and compromises coexist in the practice of applying 'reproductive knowledge' to breed selection.

Incorporating priors on expert performance parameters for segmentation validation and label fusion: a maximum a posteriori STAPLE

PubMed Central

Commowick, Olivier; Warfield, Simon K

2010-01-01

In order to evaluate the quality of segmentations of an image and assess intra- and inter-expert variability in segmentation performance, an Expectation Maximization (EM) algorithm for Simultaneous Truth And Performance Level Estimation (STAPLE) was recently developed. This algorithm, originally presented for segmentation validation, has since been used for many applications, such as atlas construction and decision fusion. However, the manual delineation of structures of interest is a very time consuming and burdensome task. Further, as the time required and burden of manual delineation increase, the accuracy of the delineation is decreased. Therefore, it may be desirable to ask the experts to delineate only a reduced number of structures or the segmentation of all structures by all experts may simply not be achieved. Fusion from data with some structures not segmented by each expert should be carried out in a manner that accounts for the missing information. In other applications, locally inconsistent segmentations may drive the STAPLE algorithm into an undesirable local optimum, leading to misclassifications or misleading experts performance parameters. We present a new algorithm that allows fusion with partial delineation and which can avoid convergence to undesirable local optima in the presence of strongly inconsistent segmentations. The algorithm extends STAPLE by incorporating prior probabilities for the expert performance parameters. This is achieved through a Maximum A Posteriori formulation, where the prior probabilities for the performance parameters are modeled by a beta distribution. We demonstrate that this new algorithm enables dramatically improved fusion from data with partial delineation by each expert in comparison to fusion with STAPLE. PMID:20879379

Incorporating priors on expert performance parameters for segmentation validation and label fusion: a maximum a posteriori STAPLE.

PubMed

Commowick, Olivier; Warfield, Simon K

2010-01-01

In order to evaluate the quality of segmentations of an image and assess intra- and inter-expert variability in segmentation performance, an Expectation Maximization (EM) algorithm for Simultaneous Truth And Performance Level Estimation (STAPLE) was recently developed. This algorithm, originally presented for segmentation validation, has since been used for many applications, such as atlas construction and decision fusion. However, the manual delineation of structures of interest is a very time consuming and burdensome task. Further, as the time required and burden of manual delineation increase, the accuracy of the delineation is decreased. Therefore, it may be desirable to ask the experts to delineate only a reduced number of structures or the segmentation of all structures by all experts may simply not be achieved. Fusion from data with some structures not segmented by each expert should be carried out in a manner that accounts for the missing information. In other applications, locally inconsistent segmentations may drive the STAPLE algorithm into an undesirable local optimum, leading to misclassifications or misleading experts performance parameters. We present a new algorithm that allows fusion with partial delineation and which can avoid convergence to undesirable local optima in the presence of strongly inconsistent segmentations. The algorithm extends STAPLE by incorporating prior probabilities for the expert performance parameters. This is achieved through a Maximum A Posteriori formulation, where the prior probabilities for the performance parameters are modeled by a beta distribution. We demonstrate that this new algorithm enables dramatically improved fusion from data with partial delineation by each expert in comparison to fusion with STAPLE.

TARGET - TASK ANALYSIS REPORT GENERATION TOOL, VERSION 1.0

NASA Technical Reports Server (NTRS)

Ortiz, C. J.

1994-01-01

The Task Analysis Report Generation Tool, TARGET, is a graphical interface tool used to capture procedural knowledge and translate that knowledge into a hierarchical report. TARGET is based on VISTA, a knowledge acquisition tool developed by the Naval Systems Training Center. TARGET assists a programmer and/or task expert organize and understand the steps involved in accomplishing a task. The user can label individual steps in the task through a dialogue-box and get immediate graphical feedback for analysis. TARGET users can decompose tasks into basic action kernels or minimal steps to provide a clear picture of all basic actions needed to accomplish a job. This method allows the user to go back and critically examine the overall flow and makeup of the process. The user can switch between graphics (box flow diagrams) and text (task hierarchy) versions to more easily study the process being documented. As the practice of decomposition continues, tasks and their subtasks can be continually modified to more accurately reflect the user's procedures and rationale. This program is designed to help a programmer document an expert's task thus allowing the programmer to build an expert system which can help others perform the task. Flexibility is a key element of the system design and of the knowledge acquisition session. If the expert is not able to find time to work on the knowledge acquisition process with the program developer, the developer and subject matter expert may work in iterative sessions. TARGET is easy to use and is tailored to accommodate users ranging from the novice to the experienced expert systems builder. TARGET is written in C-language for IBM PC series and compatible computers running MS-DOS and Microsoft Windows version 3.0 or 3.1. No source code is supplied. The executable also requires 2Mb of RAM, a Microsoft compatible mouse, a VGA display and an 80286, 386 or 486 processor machine. The standard distribution medium for TARGET is one 5.25 inch 360K MS-DOS format diskette. TARGET was developed in 1991.

A safety incident reporting system for primary care. A systematic literature review and consensus procedure by the LINNEAUS collaboration on patient safety in primary care

PubMed Central

Klemp, Kerstin; Zwart, Dorien; Hansen, Jørgen; Hellebek, Torben; Luettel, Dagmar; Verstappen, Wim; Beyer, Martin; Gerlach, Ferdin M.; Hoffmann, Barbara; Esmail, Aneez

2015-01-01

Background: Incident reporting is widely used in both patient safety improvement programmes, and in research on patient safety. Objective: To identify the key requirements for incident reporting systems in primary care; to develop an Internet-based incident reporting and learning system for primary care. Methods: A literature review looking at the purpose, design and requirements of an incident reporting system (IRS) was used to update an existing incident reporting system, widely used in Germany. Then, an international expert panel with knowledge on IRS developed the criteria for the design of a new web-based incident reporting system for European primary care. A small demonstration project was used to create a web-based reporting system, to be made freely available for practitioners and researchers. The expert group compiled recommendations regarding the desirable features of an incident reporting system for European primary care. These features covered the purpose of reporting, who should be involved in reporting, the mode of reporting, design considerations, feedback mechanisms and preconditions necessary for the implementation of an IRS. Results: A freely available web-based reporting form was developed, based on these criteria. It can be modified for local contexts. Practitioners and researchers can use this system as a means of recording patient safety incidents in their locality and use it as a basis for learning from errors. Conclusion: The LINNEAUS collaboration has provided a freely available incident reporting system that can be modified for a local context and used throughout Europe. PMID:26339835

[Medical expert assessment in criminal processes from the legal viewpoint].

PubMed

Ulsenheimer, K

1996-11-01

In the area of medical professional blunder, the medical expert witness is the one participant in a trial whose statement is practically decisive for the court or the prosecutor. Legally, the responsibility remains naturally in the legal hand as the expert witness is only the assistant of the judge. The most important demands on the expert witness are strict objectiveness including towards the colleague, no independent inquiries or interrogations, comprehensive processing of the expert assessment, readiness to revise a written expert assessment according to better knowledge or new facts, independence from the client, no legal comments, clarity of language and intellectual honesty.

Ethnogeological Cultural Model of Karst Derived from Traditional Knowledge in Puerto Rico and Dominican Republic

NASA Astrophysics Data System (ADS)

Garcia, A.; Semken, S. C.; Brandt, E.

2017-12-01

Ethnogeology is the scientific study of human relationships with and knowledge of the Earth system, and is typically investigated within the context of a specific culture. Many indigenous and local systems of environmental and place knowledge incorporate empirical observations and culturally framed interpretations of geological features and processes. Ethnogeological interpretations may differ from those of conventional mainstream geoscience, but they are validated by their direct relevance to long-term cultural and environmental resilience and sustainability, typically in challenging environments. Ethnogeologic findings can enrich geoscientific knowledge bases for further research, and inform place-based geoscience education that has been shown to engage and enrich students from diverse underrepresented minority backgrounds. Ethnogeological research blends methods from field geology with methods from field ethnography: such as participant observation, free listing, participatory mapping, and cultural consensus analysis among other methods from rapid participatory assessment. We report here on an ongoing field study in Puerto Rico (PR) and the Dominican Republic (DR) on ethnogeological knowledge of karst topography, geology, and hydrogeology among local cultural indigenous communities such as the Boricua jíbaro and the Dominican campesino. Applied focused ethnographic fieldwork results suggest a good fit for the cultural consensus model about geological processes among culturally expert consultants in DR (4.604) and PR (4.669), as well as competence average with values of 0.552 and 0.628 respectively. This suggests the existence of a regional cultural model for the domain of karst that is shared between PR and DR populations that reside in or near karst terrain. Additional data in support of the cultural model include stories, analogies, and family history using participant observation, and participatory mapping.

Environmental Sensing of Expert Knowledge in a Computational Evolution System for Complex Problem Solving in Human Genetics

NASA Astrophysics Data System (ADS)

Greene, Casey S.; Hill, Douglas P.; Moore, Jason H.

The relationship between interindividual variation in our genomes and variation in our susceptibility to common diseases is expected to be complex with multiple interacting genetic factors. A central goal of human genetics is to identify which DNA sequence variations predict disease risk in human populations. Our success in this endeavour will depend critically on the development and implementation of computational intelligence methods that are able to embrace, rather than ignore, the complexity of the genotype to phenotype relationship. To this end, we have developed a computational evolution system (CES) to discover genetic models of disease susceptibility involving complex relationships between DNA sequence variations. The CES approach is hierarchically organized and is capable of evolving operators of any arbitrary complexity. The ability to evolve operators distinguishes this approach from artificial evolution approaches using fixed operators such as mutation and recombination. Our previous studies have shown that a CES that can utilize expert knowledge about the problem in evolved operators significantly outperforms a CES unable to use this knowledge. This environmental sensing of external sources of biological or statistical knowledge is important when the search space is both rugged and large as in the genetic analysis of complex diseases. We show here that the CES is also capable of evolving operators which exploit one of several sources of expert knowledge to solve the problem. This is important for both the discovery of highly fit genetic models and because the particular source of expert knowledge used by evolved operators may provide additional information about the problem itself. This study brings us a step closer to a CES that can solve complex problems in human genetics in addition to discovering genetic models of disease.

Development of a reliable, valid measure to assess parents' and teachers' understanding of postural care for children with physical disabilities: the (UKC PostCarD) questionnaire.

PubMed

Hotham, S; Hutton, E; Hamilton-West, K E

2015-11-01

Previous research has highlighted lack of knowledge, understanding and confidence among parents and teachers responsible for the postural care of children with physical disability. Interventions designed to improve these qualities require a reliable and validated tool to assess pre- and post-intervention levels. Currently, however, no validated measure of postural care confidence (i.e. self-efficacy) exists. Hence, the aim of this research was to develop a reliable and valid questionnaire to assess parents' and teachers' confidence, alongside knowledge and understanding of postural care - the Understanding Knowledge and Confidence in providing POSTural CARe for children with Disabilities (UKC PostCarD) questionnaire. Items were developed by a multidisciplinary team and designed to map onto the content of 'An A-to-Z of Postural Care'. Parents, teachers and therapists assessed items for face validity. Scale reliability was then assessed using Cronbach's alpha and known-group validity was assessed by comparing scores of an 'expert' group (physiotherapists and occupational therapists) with those of a 'non-expert' group (with no formal training in postural care). The total scale and all three subscales (understanding and knowledge, confidence and concerns) demonstrated adequate reliability (α > 0.83) and subscale correlations formed a logical pattern (understanding and knowledge correlated positively with confidence and negatively with concerns). Experts' (n = 111) scores were higher than non-experts' (n = 79) for the total scale and all subscales (P < 0.001). Findings support the reliability and validity of the UKC PostCarD questionnaire as a measure of understanding, knowledge and confidence in providing postural care for children with disabilities. © 2015 John Wiley & Sons Ltd.

Introducing Managers to Expert Systems.

ERIC Educational Resources Information Center

Finlay, Paul N.; And Others

1991-01-01

Describes a short course to expose managers to expert systems, consisting of (1) introductory lecture; (2) supervised computer tutorial; (3) lecture and discussion about knowledge structuring and modeling; and (4) small group work on a case study using computers. (SK)

What Artificial Intelligence Is Doing for Training.

ERIC Educational Resources Information Center

Kirrane, Peter R.; Kirrane, Diane E.

1989-01-01

Discusses the three areas of research and application of artificial intelligence: (1) robotics, (2) natural language processing, and (3) knowledge-based or expert systems. Focuses on what expert systems can do, especially in the area of training. (JOW)

An expert system for the evaluation of reinforced concrete structure durability

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

Berra, M.; Bertolini, L.; Briglia, M.C.

1999-11-01

A user-friendly expert system has been developed to evaluate primarily the durability of reinforced concrete structures, either in the design phase or during service life related to reinforcement corrosion. Besides the durability module, the ES has been provided with three other expert modules in order to support the user during the following activities: inspections, corrosion diagnosis and repair strategy (of concrete and reinforcement). Corrosion induced by carbonation and chlorides penetration and caused by concrete degradation such as sulfate attack, freeze/thaw cycles, alkali silica reaction are considered. The knowledge used for the expert system is based both on open literature andmore » international standards as well as on specific experiences and proprietary databases. The paper describes main features of the system, including the modeling of the knowledge, input data, the algorithms, the rules and the outputs for each module.« less

A real-time navigation monitoring expert system for the Space Shuttle Mission Control Center

NASA Technical Reports Server (NTRS)

Wang, Lui; Fletcher, Malise

1993-01-01

The ONAV (Onboard Navigation) Expert System has been developed as a real time console assistant for use by ONAV flight controllers in the Mission Control Center at the Johnson Space Center. This expert knowledge based system is used to monitor the Space Shuttle onboard navigation system, detect faults, and advise flight operations personnel. This application is the first knowledge-based system to use both telemetry and trajectory data from the Mission Operations Computer (MOC). To arrive at this stage, from a prototype to real world application, the ONAV project has had to deal with not only AI issues but operating environment issues. The AI issues included the maturity of AI languages and the debugging tools, verification, and availability, stability and size of the expert pool. The environmental issues included real time data acquisition, hardware suitability, and how to achieve acceptance by users and management.

Decision Support Systems for Launch and Range Operations Using Jess

NASA Technical Reports Server (NTRS)

Thirumalainambi, Rajkumar

2007-01-01

The virtual test bed for launch and range operations developed at NASA Ames Research Center consists of various independent expert systems advising on weather effects, toxic gas dispersions and human health risk assessment during space-flight operations. An individual dedicated server supports each expert system and the master system gather information from the dedicated servers to support the launch decision-making process. Since the test bed is based on the web system, reducing network traffic and optimizing the knowledge base is critical to its success of real-time or near real-time operations. Jess, a fast rule engine and powerful scripting environment developed at Sandia National Laboratory has been adopted to build the expert systems providing robustness and scalability. Jess also supports XML representation of knowledge base with forward and backward chaining inference mechanism. Facts added - to working memory during run-time operations facilitates analyses of multiple scenarios. Knowledge base can be distributed with one inference engine performing the inference process. This paper discusses details of the knowledge base and inference engine using Jess for a launch and range virtual test bed.

Predicting Mycobacterium tuberculosis Complex Clades Using Knowledge-Based Bayesian Networks

PubMed Central

Bennett, Kristin P.

2014-01-01

We develop a novel approach for incorporating expert rules into Bayesian networks for classification of Mycobacterium tuberculosis complex (MTBC) clades. The proposed knowledge-based Bayesian network (KBBN) treats sets of expert rules as prior distributions on the classes. Unlike prior knowledge-based support vector machine approaches which require rules expressed as polyhedral sets, KBBN directly incorporates the rules without any modification. KBBN uses data to refine rule-based classifiers when the rule set is incomplete or ambiguous. We develop a predictive KBBN model for 69 MTBC clades found in the SITVIT international collection. We validate the approach using two testbeds that model knowledge of the MTBC obtained from two different experts and large DNA fingerprint databases to predict MTBC genetic clades and sublineages. These models represent strains of MTBC using high-throughput biomarkers called spacer oligonucleotide types (spoligotypes), since these are routinely gathered from MTBC isolates of tuberculosis (TB) patients. Results show that incorporating rules into problems can drastically increase classification accuracy if data alone are insufficient. The SITVIT KBBN is publicly available for use on the World Wide Web. PMID:24864238

Expert system training and control based on the fuzzy relation matrix

NASA Technical Reports Server (NTRS)

Ren, Jie; Sheridan, T. B.

1991-01-01

Fuzzy knowledge, that for which the terms of reference are not crisp but overlapped, seems to characterize human expertise. This can be shown from the fact that an experienced human operator can control some complex plants better than a computer can. Proposed here is fuzzy theory to build a fuzzy expert relation matrix (FERM) from given rules or/and examples, either in linguistic terms or in numerical values to mimic human processes of perception and decision making. The knowledge base is codified in terms of many implicit fuzzy rules. Fuzzy knowledge thus codified may also be compared with explicit rules specified by a human expert. It can also provide a basis for modeling the human operator and allow comparison of what a human operator says to what he does in practice. Two experiments were performed. In the first, control of liquid in a tank, demonstrates how the FERM knowledge base is elicited and trained. The other shows how to use a FERM, build up from linguistic rules, and to control an inverted pendulum without a dynamic model.

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.

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

ERIC Educational Resources Information Center

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

2010-01-01

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

Proceedings of the international conference on cybernetics and societ

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

Not Available

1985-01-01

This book presents the papers given at a conference on artificial intelligence, expert systems and knowledge bases. Topics considered at the conference included automating expert system development, modeling expert systems, causal maps, data covariances, robot vision, image processing, multiprocessors, parallel processing, VLSI structures, man-machine systems, human factors engineering, cognitive decision analysis, natural language, computerized control systems, and cybernetics.

Systematic methods for knowledge acquisition and expert system development

NASA Technical Reports Server (NTRS)

Belkin, Brenda L.; Stengel, Robert F.

1991-01-01

Nine cooperating rule-based systems, collectively called AUTOCREW which were designed to automate functions and decisions associated with a combat aircraft's subsystems, are discussed. The organization of tasks within each system is described; performance metrics were developed to evaluate the workload of each rule base and to assess the cooperation between the rule bases. Simulation and comparative workload results for two mission scenarios are given. The scenarios are inbound surface-to-air-missile attack on the aircraft and pilot incapacitation. The methodology used to develop the AUTOCREW knowledge bases is summarized. Issues involved in designing the navigation sensor selection expert in AUTOCREW's NAVIGATOR knowledge base are discussed in detail. The performance of seven navigation systems aiding a medium-accuracy INS was investigated using Kalman filter covariance analyses. A navigation sensor management (NSM) expert system was formulated from covariance simulation data using the analysis of variance (ANOVA) method and the ID3 algorithm. ANOVA results show that statistically different position accuracies are obtained when different navaids are used, the number of navaids aiding the INS is varied, the aircraft's trajectory is varied, and the performance history is varied. The ID3 algorithm determines the NSM expert's classification rules in the form of decision trees. The performance of these decision trees was assessed on two arbitrary trajectories, and the results demonstrate that the NSM expert adapts to new situations and provides reasonable estimates of the expected hybrid performance.

CLIPS: A tool for corn disease diagnostic system and an aid to neural network for automated knowledge acquisition

NASA Technical Reports Server (NTRS)

Wu, Cathy; Taylor, Pam; Whitson, George; Smith, Cathy

1990-01-01

This paper describes the building of a corn disease diagnostic expert system using CLIPS, and the development of a neural expert system using the fact representation method of CLIPS for automated knowledge acquisition. The CLIPS corn expert system diagnoses 21 diseases from 52 symptoms and signs with certainty factors. CLIPS has several unique features. It allows the facts in rules to be broken down to object-attribute-value (OAV) triples, allows rule-grouping, and fires rules based on pattern-matching. These features combined with the chained inference engine result to a natural user query system and speedy execution. In order to develop a method for automated knowledge acquisition, an Artificial Neural Expert System (ANES) is developed by a direct mapping from the CLIPS system. The ANES corn expert system uses the same OAV triples in the CLIPS system for its facts. The LHS and RHS facts of the CLIPS rules are mapped into the input and output layers of the ANES, respectively; and the inference engine of the rules is imbedded in the hidden layer. The fact representation by OAC triples gives a natural grouping of the rules. These features allow the ANES system to automate rule-generation, and make it efficient to execute and easy to expand for a large and complex domain.

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

Pilat, Joseph F

The application of the methodology developed by the GenIV International Forum's (GIF's) Proliferation Resistance and Physical Protection (PR&PP) Working Group is an expert elicitation. Although the framework of the methodology is structured and systematic, it does not by itself constitute or require a formal elicitation. However, formal elicitation can be utilized in the PR&PP context to provide a systematic, credible and transparent qualitative analysis and develop input for quantitative analyses. This section provides an overview of expert elicitations, a discussion of the role formal expert elicitations can play in the PR&PP methodology, an outline of the formal expert elicitation processmore » and a brief practical guide to conducting formal expert elicitations. Expert elicitation is a process utilizing knowledgeable people in cases, for example, when an assessment is needed but physically based data is absent or open to interpretation. More specifically, it can be used to: (1) predict future events; (2) provide estimates on new, rare, complex or poorly understood phenomena; (3) integrate or interpret existing information; or (4) determine what is currently known, how well it is known or what is worth learning in a field. Expert elicitation can be informal or formal. The informal application of expert judgment is frequently used. Although it can produce good results, it often provides demonstrably biased or otherwise flawed answers to problems. This along with the absence of transparency can result in a loss of confidence when experts speak on issues. More formal expert elicitation is a structured process that makes use of people knowledgeable in certain areas to make assessments. The reason for advocating formal use is that the quality and accuracy of expert judgment comes from the completeness of the expert's understanding of the phenomena and the process used to elicit and analyze the data. The use of a more formal process to obtain, lU1derstand and analyze expert judgment has led to an improved acceptance of expert judgment because of the rigor and transparency of the results.« less

Perceiving land-degrading activities from the lay perspective in northern China.

PubMed

Lee, Harry F; Zhang, David D

2005-11-01

Investigation into local peoples' perceptions can produce useful information that could be incorporated into the decision-making process to help resolve environmental problems. Within the arena of land degradation, a number of studies have also been conducted to explore local peoples' views of the problem. However, the perceptions of land-degrading practices of the general public have so far not been actively solicited. This study aimed to contribute to this area of research by adopting the psychometric scaling technique to empirically explore the lay public's ecological risk perceptions of land-degrading activities in Minqin County in Gansu Province, northern China. The primary data were collected via a questionnaire survey (n=1,138) administered between 14 and 31 December 2002. The major findings of the survey were: (1) Respondents perceived the ecological risks posed by different land-degrading activities to be different. (2) There was a considerable incongruence in the way in which mining of groundwater was conceived by experts and laymen, respectively. (3) Respondents were pretty unsure of expert knowledge. (4) Respondents' ecological risk perceptions were significantly affected by their personal attributes. As far as the policy implications of these findings are concerned, this study accentuates that we must be aware of, and involved in, the environmental perceptions of the lay public in order to succeed in guiding any human-environment tensions along more sustainable trajectories and navigating the transition to sustainability.

How to adapt existing evidence-based clinical practice guidelines: a case example with smoking cessation guidelines in Canada

PubMed Central

Selby, Peter; Hunter, Katie; Rogers, Jess; Lang-Robertson, Kelly; Soklaridis, Sophie; Chow, Virginia; Tremblay, Michèle; Koubanioudakis, Denise; Dragonetti, Rosa; Hussain, Sarwar; Zawertailo, Laurie

2017-01-01

Objective To develop and encourage the adoption of clinical practice guidelines (CPGs) for smoking cessation in Canada by engaging stakeholders in the adaptation of existing high-quality CPGs using principles of the ADAPTE framework. Methods An independent expert body in guideline review conducted a review and identified six existing CPGs, which met a priori criteria for quality and potential applicability to the local context. Summary statements were extracted and assigned a grade of recommendation and level of evidence by a second expert panel. Regional knowledge exchange brokers recruited additional stakeholders to build a multidisciplinary network of over 800 clinicians, researchers and decision-makers from across Canada. This interprofessional network and other stakeholders were offered various opportunities to provide input on the guideline both online and in person. We actively encouraged end-user input into the development and adaptation of the guidelines to ensure applicability to various practice settings and to promote adoption. Results The final guideline contained 24 summary statements along with supporting clinical considerations, across six topic area sections. The guideline was adopted by various provincial/territorial and national government and non-governmental organisations. Conclusions This method can be applied in other jurisdictions to adapt existing high-quality smoking cessation CPGs to the local context and to facilitate subsequent adoption by various stakeholders. PMID:29102984

Modelling Chemical Reasoning to Predict and Invent Reactions.

PubMed

Segler, Marwin H S; Waller, Mark P

2017-05-02

The ability to reason beyond established knowledge allows organic chemists to solve synthetic problems and invent novel transformations. Herein, we propose a model that mimics chemical reasoning, and formalises reaction prediction as finding missing links in a knowledge graph. We have constructed a knowledge graph containing 14.4 million molecules and 8.2 million binary reactions, which represents the bulk of all chemical reactions ever published in the scientific literature. Our model outperforms a rule-based expert system in the reaction prediction task for 180 000 randomly selected binary reactions. The data-driven model generalises even beyond known reaction types, and is thus capable of effectively (re-)discovering novel transformations (even including transition metal-catalysed reactions). Our model enables computers to infer hypotheses about reactivity and reactions by only considering the intrinsic local structure of the graph and because each single reaction prediction is typically achieved in a sub-second time frame, the model can be used as a high-throughput generator of reaction hypotheses for reaction discovery. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Plant Distribution Data Show Broader Climatic Limits than Expert-Based Climatic Tolerance Estimates

PubMed Central

Curtis, Caroline A.; Bradley, Bethany A.

2016-01-01

Background Although increasingly sophisticated environmental measures are being applied to species distributions models, the focus remains on using climatic data to provide estimates of habitat suitability. Climatic tolerance estimates based on expert knowledge are available for a wide range of plants via the USDA PLANTS database. We aim to test how climatic tolerance inferred from plant distribution records relates to tolerance estimated by experts. Further, we use this information to identify circumstances when species distributions are more likely to approximate climatic tolerance. Methods We compiled expert knowledge estimates of minimum and maximum precipitation and minimum temperature tolerance for over 1800 conservation plant species from the ‘plant characteristics’ information in the USDA PLANTS database. We derived climatic tolerance from distribution data downloaded from the Global Biodiversity and Information Facility (GBIF) and corresponding climate from WorldClim. We compared expert-derived climatic tolerance to empirical estimates to find the difference between their inferred climate niches (ΔCN), and tested whether ΔCN was influenced by growth form or range size. Results Climate niches calculated from distribution data were significantly broader than expert-based tolerance estimates (Mann-Whitney p values << 0.001). The average plant could tolerate 24 mm lower minimum precipitation, 14 mm higher maximum precipitation, and 7° C lower minimum temperatures based on distribution data relative to expert-based tolerance estimates. Species with larger ranges had greater ΔCN for minimum precipitation and minimum temperature. For maximum precipitation and minimum temperature, forbs and grasses tended to have larger ΔCN while grasses and trees had larger ΔCN for minimum precipitation. Conclusion Our results show that distribution data are consistently broader than USDA PLANTS experts’ knowledge and likely provide more robust estimates of climatic tolerance, especially for widespread forbs and grasses. These findings suggest that widely available expert-based climatic tolerance estimates underrepresent species’ fundamental niche and likely fail to capture the realized niche. PMID:27870859

Development of the Spacecraft Materials Selector Expert System

NASA Technical Reports Server (NTRS)

Pippin, H. G.

2000-01-01

A specific knowledge base to evaluate the on-orbit performance of selected materials on spacecraft is being developed under contract to the NASA SEE program. An artificial intelligence software package, the Boeing Expert System Tool (BEST), contains an inference engine used to operate knowledge bases constructed to selectively recall and distribute information about materials performance in space applications. This same system is used to make estimates of the environmental exposures expected for a given space flight. The performance capabilities of the Spacecraft Materials Selector (SMS) knowledge base are described in this paper. A case history for a planned flight experiment on ISS is shown as an example of the use of the SMS, and capabilities and limitations of the knowledge base are discussed.

Knowledge-based diagnosis for aerospace systems

NASA Technical Reports Server (NTRS)

Atkinson, David J.

1988-01-01

The need for automated diagnosis in aerospace systems and the approach of using knowledge-based systems are examined. Research issues in knowledge-based diagnosis which are important for aerospace applications are treated along with a review of recent relevant research developments in Artificial Intelligence. The design and operation of some existing knowledge-based diagnosis systems are described. The systems described and compared include the LES expert system for liquid oxygen loading at NASA Kennedy Space Center, the FAITH diagnosis system developed at the Jet Propulsion Laboratory, the PES procedural expert system developed at SRI International, the CSRL approach developed at Ohio State University, the StarPlan system developed by Ford Aerospace, the IDM integrated diagnostic model, and the DRAPhys diagnostic system developed at NASA Langley Research Center.

An integrated knowledge system for the Space Shuttle hazardous gas detection system

NASA Technical Reports Server (NTRS)

Lo, Ching F.; Shi, George Z.; Bangasser, Carl; Fensky, Connie; Cegielski, Eric; Overbey, Glenn

1993-01-01

A computer-based integrated Knowledge-Based System, the Intelligent Hypertext Manual (IHM), was developed for the Space Shuttle Hazardous Gas Detection System (HGDS) at NASA Marshall Space Flight Center (MSFC). The IHM stores HGDS related knowledge and presents it in an interactive and intuitive manner. This manual is a combination of hypertext and an expert system which store experts' knowledge and experience in hazardous gas detection and analysis. The IHM's purpose is to provide HGDS personnel with the capabilities of: locating applicable documentation related to procedures, constraints, and previous fault histories; assisting in the training of personnel; enhancing the interpretation of real time data; and recognizing and identifying possible faults in the Space Shuttle sub-systems related to hazardous gas detection.

Integrated Knowledge Based Expert System for Disease Diagnosis System

NASA Astrophysics Data System (ADS)

Arbaiy, Nureize; Sulaiman, Shafiza Eliza; Hassan, Norlida; Afizah Afip, Zehan

2017-08-01

The role and importance of healthcare systems to improve quality of life and social welfare in a society have been well recognized. Attention should be given to raise awareness and implementing appropriate measures to improve health care. Therefore, a computer based system is developed to serve as an alternative for people to self-diagnose their health status based on given symptoms. This strategy should be emphasized so that people can utilize the information correctly as a reference to enjoy healthier life. Hence, a Web-based Community Center for Healthcare Diagnosis system is developed based on expert system technique. Expert system reasoning technique is employed in the system to enable information about treatment and prevention of the diseases based on given symptoms. At present, three diseases are included which are arthritis, thalassemia and pneumococcal. Sets of rule and fact are managed in the knowledge based system. Web based technology is used as a platform to disseminate the information to users in order for them to optimize the information appropriately. This system will benefit people who wish to increase health awareness and seek expert knowledge on the diseases by performing self-diagnosis for early disease detection.

Identifying key conservation threats to Alpine birds through expert knowledge

PubMed Central

Pedrini, Paolo; Brambilla, Mattia; Rolando, Antonio; Girardello, Marco

2016-01-01

Alpine biodiversity is subject to a range of increasing threats, but the scarcity of data for many taxa means that it is difficult to assess the level and likely future impact of a given threat. Expert opinion can be a useful tool to address knowledge gaps in the absence of adequate data. Experts with experience in Alpine ecology were approached to rank threat levels for 69 Alpine bird species over the next 50 years for the whole European Alps in relation to ten categories: land abandonment, climate change, renewable energy, fire, forestry practices, grazing practices, hunting, leisure, mining and urbanization. There was a high degree of concordance in ranking of perceived threats among experts for most threat categories. The major overall perceived threats to Alpine birds identified through expert knowledge were land abandonment, urbanization, leisure and forestry, although other perceived threats were ranked highly for particular species groups (renewable energy and hunting for raptors, hunting for gamebirds). For groups of species defined according to their breeding habitat, open habitat species and treeline species were perceived as the most threatened. A spatial risk assessment tool based on summed scores for the whole community showed threat levels were highest for bird communities of the northern and western Alps. Development of the approaches given in this paper, including addressing biases in the selection of experts and adopting a more detailed ranking procedure, could prove useful in the future in identifying future threats, and in carrying out risk assessments based on levels of threat to the whole bird community. PMID:26966659

Literally experts: expertise and the processing of analogical metaphors in pharmaceutical advertising.

PubMed

Delbaere, Marjorie; Smith, Malcolm C

2014-01-01

This research examined differences between novices and experts in processing analogical metaphors appearing in prescription drug advertisements. In contrast to previous studies on knowledge transfer, no evidence of the superiority of experts in processing metaphors was found. The results from an experiment suggest that expert consumers were more likely to process a metaphor in an ad literally than novices. Our findings point to a condition in which the expertise effect with processing analogies is not the linear relationship assumed in previous studies.

Knowledge-based systems for power management

NASA Technical Reports Server (NTRS)

Lollar, L. F.

1992-01-01

NASA-Marshall's Electrical Power Branch has undertaken the development of expert systems in support of further advancements in electrical power system automation. Attention is given to the features (1) of the Fault Recovery and Management Expert System, (2) a resource scheduler or Master of Automated Expert Scheduling Through Resource Orchestration, and (3) an adaptive load-priority manager, or Load Priority List Management System. The characteristics of an advisory battery manager for the Hubble Space Telescope, designated the 'nickel-hydrogen expert system', are also noted.

How Expert Clinicians Intuitively Recognize a Medical Diagnosis.

PubMed

Brush, John E; Sherbino, Jonathan; Norman, Geoffrey R

2017-06-01

Research has shown that expert clinicians make a medical diagnosis through a process of hypothesis generation and verification. Experts begin the diagnostic process by generating a list of diagnostic hypotheses using intuitive, nonanalytic reasoning. Analytic reasoning then allows the clinician to test and verify or reject each hypothesis, leading to a diagnostic conclusion. In this article, we focus on the initial step of hypothesis generation and review how expert clinicians use experiential knowledge to intuitively recognize a medical diagnosis. Copyright © 2017 Elsevier Inc. All rights reserved.

Projects in an expert system class

NASA Technical Reports Server (NTRS)

Whitson, George M.

1991-01-01

Many universities now teach courses in expert systems. In these courses students study the architecture of an expert system, knowledge acquisition techniques, methods of implementing systems and verification and validation techniques. A major component of any such course is a class project consisting of the design and implementation of an expert system. Discussed here are a number of techniques that we have used at the University of Texas at Tyler to develop meaningful projects that could be completed in a semester course.

Comparing Four Instructional Techniques for Promoting Robust Knowledge

ERIC Educational Resources Information Center

Richey, J. Elizabeth; Nokes-Malach, Timothy J.

2015-01-01

Robust knowledge serves as a common instructional target in academic settings. Past research identifying characteristics of experts' knowledge across many domains can help clarify the features of robust knowledge as well as ways of assessing it. We review the expertise literature and identify three key features of robust knowledge (deep,…

The coexistence of traditional medicine and biomedicine: A study with local health experts in two Brazilian regions.

PubMed

Zank, Sofia; Hanazaki, Natalia

2017-01-01

This study investigated the combined use of traditional medicine and biomedicine by local experts in Chapada do Araripe communities (Ceará State) and maroon communities (Santa Catarina State), Brazil. The objective was to understand the perception of local health specialists regarding the number of healers, demand for healers and use of medicinal plants, and the dependence of different environments to obtain such plants. We also aimed to understand the role of medicinal plants to treat different categories of diseases and if there is a complementary use of medicinal plants and allopathic biomedicine, according to the context of each group. The research was conducted with local health specialists that answered structured interviews, created free lists and participated in guided tours to collect cited plants. Sixty-six local health specialists were identified in the Araripe communities and 22 specialists in the maroon communities. In the maroon communities, a greater number of specialists thought there was a decrease in the number and demand for healers, as well as the use of medicinal plants, due to changes in traditional livelihoods, since they are located in a region where the effects of the modernization were more intense. In the Chapada do Araripe communities the specialists knew more plants extracted from native vegetation, whereas in the maroon communities cultivated plants were better known, which may reflect the environmental conditions and the history of each region. Medicinal plants are preferred to treat simpler health problems that do not require medical care, such as gastrointestinal problems, general pain, flues and colds. The biomedicine is used principally for problems with blood pressure, general pains and endocrine and nutritional diseases. Even with the particularities of each region, in general the use of medicinal plants and biomedicines occurred in a complementary form in both regions; however, this coexistence may result from these different contexts. This study also found that there was knowledge and appreciation for traditional health practices in both regions.

The coexistence of traditional medicine and biomedicine: A study with local health experts in two Brazilian regions

PubMed Central

Zank, Sofia; Hanazaki, Natalia

2017-01-01

This study investigated the combined use of traditional medicine and biomedicine by local experts in Chapada do Araripe communities (Ceará State) and maroon communities (Santa Catarina State), Brazil. The objective was to understand the perception of local health specialists regarding the number of healers, demand for healers and use of medicinal plants, and the dependence of different environments to obtain such plants. We also aimed to understand the role of medicinal plants to treat different categories of diseases and if there is a complementary use of medicinal plants and allopathic biomedicine, according to the context of each group. The research was conducted with local health specialists that answered structured interviews, created free lists and participated in guided tours to collect cited plants. Sixty-six local health specialists were identified in the Araripe communities and 22 specialists in the maroon communities. In the maroon communities, a greater number of specialists thought there was a decrease in the number and demand for healers, as well as the use of medicinal plants, due to changes in traditional livelihoods, since they are located in a region where the effects of the modernization were more intense. In the Chapada do Araripe communities the specialists knew more plants extracted from native vegetation, whereas in the maroon communities cultivated plants were better known, which may reflect the environmental conditions and the history of each region. Medicinal plants are preferred to treat simpler health problems that do not require medical care, such as gastrointestinal problems, general pain, flues and colds. The biomedicine is used principally for problems with blood pressure, general pains and endocrine and nutritional diseases. Even with the particularities of each region, in general the use of medicinal plants and biomedicines occurred in a complementary form in both regions; however, this coexistence may result from these different contexts. This study also found that there was knowledge and appreciation for traditional health practices in both regions. PMID:28414735

Expert Systems: Tutors, Tools, and Tutees.

ERIC Educational Resources Information Center

Lippert, Renate C.

1989-01-01

Discusses the current status, research, and practical implications of artificial intelligence and expert systems in education. Topics discussed include computer-assisted instruction; intelligent computer-assisted instruction; intelligent tutoring systems; instructional strategies involving the creation of knowledge bases; decision aids;…

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.

The NSF-RCN Urban Heat Island Network

NASA Astrophysics Data System (ADS)

Twine, T. E.; Snyder, P. K.; Hamilton, P.; Shepherd, M.; Stone, B., Jr.

2015-12-01

In much of the world cities are warming at twice the rate of outlying rural areas. The frequency of urban heat waves is projected to increase with climate change through the 21st century. Addressing the economic, environmental, and human costs of urban heat islands requires a better understanding of their behavior from many disciplinary perspectives. The goal of this four-year Urban Heat Island Network is to (1) bring together scientists studying the causes and impacts of urban warming, (2) advance multidisciplinary understanding of urban heat islands, (3) examine how they can be ameliorated through engineering and design practices, and (4) share these new insights with a wide array of stakeholders responsible for managing urban warming to reduce their health, economic, and environmental impacts. The NSF-RCN Urban Heat Island Network involves atmospheric scientists, engineers, architects, landscape designers, urban planners, public health experts, and education and outreach experts, who will share knowledge, evaluate research directions, and communicate knowledge and research recommendations to the larger research community as well as stakeholders engaged in developing strategies to adapt to and mitigate urban warming. The first Urban Climate Institute was held in Saint Paul, MN in July 2013 and focused on the characteristics of urban heat islands. Scientists engaged with local practitioners to improve communication pathways surrounding issues of understanding, adapting to, and mitigating urban warming. The second Urban Climate Institute was held in Atlanta, Georgia in July 2014 and focused on urban warming and public health. The third Urban Climate Institute was held in Athens, GA in July 2015 and focused on urban warming and the role of the built environment. Scientists and practitioners discussed strategies for mitigation and adaptation. Evaluation experts at the Science Museum of Minnesota have extensively evaluated the Institutes to inform other research coordination networks and to identify effective ways that researchers and practitioners can share knowledge and communicate more effectively. A final Institute is planned for July of 2016 in Saint Paul, MN. This institute will focus on synthesizing findings from the first three workshops and discuss education and outreach efforts.

Assessing Students' Accounting Knowledge: A Structural Approach.

ERIC Educational Resources Information Center

Boldt, Margaret N.

2001-01-01

Comparisons of students' representations of financial accounting concepts with the knowledge structures of experts were depicted using Pathfinder networks. This structural approach identified the level of students' understanding of concepts and knowledge gaps that need to be addressed. (SK)

Transformation reborn: A new generation expert system for planning HST operations

NASA Technical Reports Server (NTRS)

Gerb, Andrew

1991-01-01

The Transformation expert system (TRANS) converts proposals for astronomical observations with the Hubble Space Telescope (HST) into detailed observing plans. It encodes expert knowledge to solve problems faced in planning and commanding HST observations to enable their processing by the Science Operations Ground System (SOGS). Among these problems are determining an acceptable order of executing observations, grouping of observations to enhance efficiency and schedulability, inserting extra observations when necessary, and providing parameters for commanding HST instruments. TRANS is currently an operational system and plays a critical role in the HST ground system. It was originally designed using forward-chaining provided by the OPS5 expert system language, but has been reimplemented using a procedural knowledge base. This reimplementation was forced by the explosion in the amount of OPS5 code required to specify the increasingly complicated situations requiring expert-level intervention by the TRANS knowledge base. This problem was compounded by the difficulty of avoiding unintended interaction between rules. To support the TRANS knowledge base, XCL, a small but powerful extension to Commom Lisp was implemented. XCL allows a compact syntax for specifying assignments and references to object attributes. XCL also allows the capability to iterate over objects and perform keyed lookup. The reimplementation of TRANS has greatly diminished the effort needed to maintain and enhance it. As a result of this, its functions have been expanded to include warnings about observations that are difficult or impossible to schedule or command, providing data to aid SPIKE, an intelligent planning system used for HST long-term scheduling, and providing information to the Guide Star Selection System (GSSS) to aid in determination of the long range availability of guide stars.

Knowledge base and functionality of concepts of some Filipino biology teachers in five biology topics

NASA Astrophysics Data System (ADS)

Barquilla, Manuel B.

2018-01-01

This mixed research, is a snapshot of some Filipino Biology teachers' knowledge structure and how their concepts of the five topics in Biology (Photosynthesis, Cellular Respiration, human reproductive system, Mendelian genetics and NonMendelian genetics) functions and develops inside a biology classroom. The study focuses on the six biology teachers and a total of 222 students in their respective classes. Of the Six (6) teachers, three (3) are under the Science curriculum and the other three (3) are under regular curriculum in both public and private schools in Iligan city and Lanao del Norte, Philippines. The study utilized classroom discourses, concept maps, interpretative case-study method, bracketing method, and concept analysis for qualitative part; the quantitative part uses a nonparametric statistical tool, Kendall's tau Coefficient for determining relationship and congruency while measures of central tendencies and dispersion (mean, and standard deviation) for concept maps scores interpretation. Knowledge Base of Biology teachers were evaluated by experts in field of specialization having a doctorate program (e.g. PhD in Genetics) and PhD Biology candidates. The data collection entailed seven (7) months immersion: one (1) month for preliminary phase for the researcher to gain teachers' and students' confidence and the succeeding six (6) months for main observation and data collection. The evaluation of teachers' knowledge base by experts indicated that teachers' knowledge of (65%) is lower than the minimum (75%) recommended by ABD-el-Khalick and Boujaoude (1997). Thus, the experts believe that content knowledge of the teachers is hardly adequate for their teaching assignment. Moreover, the teachers in this study do not systematically use reallife situation to apply the concepts they teach. They can identify concepts too abstract for their student; however, they seldom use innovative ways to bring the discussion to their students' level of readiness and capacity to learn. Kendall's Tau Coefficient of agreement indicated that there is an agreement of the rating by experts and PhD (Biology) candidates. As for recommended level for teaching based on the respondent content knowledge structure, the experts and the PhD (Biology) candidates agree that the content knowledge of the teachers is at the borderline (rating of 6) between elementary and high school. These results imply that biology teachers need in-service training to upgrade their content knowledge in the subject. At the same time, the pre-service curriculum for biology teachers needs upgrading.

Flood damage modeling based on expert knowledge: Insights from French damage model for agricultural sector

NASA Astrophysics Data System (ADS)

Grelot, Frédéric; Agenais, Anne-Laurence; Brémond, Pauline

2015-04-01

In France, since 2011, it is mandatory for local communities to conduct cost-benefit analysis (CBA) of their flood management projects, to make them eligible for financial support from the State. Meanwhile, as a support, the French Ministry in charge of Environment proposed a methodology to fulfill CBA. Like for many other countries, this methodology is based on the estimation of flood damage. However, existing models to estimate flood damage were judged not convenient for a national-wide use. As a consequence, the French Ministry in charge of Environment launched studies to develop damage models for different sectors, such as: residential sector, public infrastructures, agricultural sector, and commercial and industrial sector. In this presentation, we aim at presenting and discussing methodological choices of those damage models. They all share the same principle: no sufficient data from past events were available to build damage models on a statistical analysis, so modeling was based on expert knowledge. We will focus on the model built for agricultural activities and more precisely for agricultural lands. This model was based on feedback from 30 agricultural experts who experienced floods in their geographical areas. They were selected to have a representative experience of crops and flood conditions in France. The model is composed of: (i) damaging functions, which reveal physiological vulnerability of crops, (ii) action functions, which correspond to farmers' decision rules for carrying on crops after a flood, and (iii) economic agricultural data, which correspond to featured characteristics of crops in the geographical area where the flood management project studied takes place. The two first components are generic and the third one is specific to the area studied. It is, thus, possible to produce flood damage functions adapted to different agronomic and geographical contexts. In the end, the model was applied to obtain a pool of damage functions giving damage in euros by hectare for 14 agricultural lands categories. As a conclusion, we will discuss the validation step of the model. Although the model was validated by experts, we analyse how it could gain insight from comparison with past events.

Flood damage modeling based on expert knowledge: Insights from French damage model for agricultural sector

NASA Astrophysics Data System (ADS)

Grelot, Frédéric; Agenais, Anne-Laurence; Brémond, Pauline

2014-05-01

In France, since 2011, it is mandatory for local communities to conduct cost-benefit analysis (CBA) of their flood management projects, to make them eligible for financial support from the State. Meanwhile, as a support, the French Ministry in charge of Environment proposed a methodology to fulfill CBA. Like for many other countries, this methodology is based on the estimation of flood damage. Howerver, existing models to estimate flood damage were judged not convenient for a national-wide use. As a consequence, the French Ministry in charge of Environment launched studies to develop damage models for different sectors, such as: residential sector, public infrastructures, agricultural sector, and commercial and industrial sector. In this presentation, we aim at presenting and discussing methodological choices of those damage models. They all share the same principle: no sufficient data from past events were available to build damage models on a statistical analysis, so modeling was based on expert knowledge. We will focus on the model built for agricultural activities and more precisely for agricultural lands. This model was based on feedback from 30 agricultural experts who experienced floods in their geographical areas. They were selected to have a representative experience of crops and flood conditions in France. The model is composed of: (i) damaging functions, which reveal physiological vulnerability of crops, (ii) action functions, which correspond to farmers' decision rules for carrying on crops after a flood, and (iii) economic agricultural data, which correspond to featured characteristics of crops in the geographical area where the flood management project studied takes place. The two first components are generic and the third one is specific to the area studied. It is, thus, possible to produce flood damage functions adapted to different agronomic and geographical contexts. In the end, the model was applied to obtain a pool of damage functions giving damage in euros by hectare for 14 agricultural lands categories. As a conclusion, we will discuss the validation step of the model. Although the model was validated by experts, we analyse how it could gain insight from comparison with past events.

Applications of artificial intelligence V; Proceedings of the Meeting, Orlando, FL, May 18-20, 1987

NASA Technical Reports Server (NTRS)

Gilmore, John F. (Editor)

1987-01-01

The papers contained in this volume focus on current trends in applications of artificial intelligence. Topics discussed include expert systems, image understanding, artificial intelligence tools, knowledge-based systems, heuristic systems, manufacturing applications, and image analysis. Papers are presented on expert system issues in automated, autonomous space vehicle rendezvous; traditional versus rule-based programming techniques; applications to the control of optional flight information; methodology for evaluating knowledge-based systems; and real-time advisory system for airborne early warning.

Measurement and Analysis Infrastructure Diagnostic, Version 1.0: Method Definition Document

DTIC Science & Technology

2010-08-01

to facilitate the conduct of MAID at the client’s site Client SME client M & A subject matter experts ( SMEs ) who are knowledgeable about the M & A...22 | CMU/SEI-2010-TR-035 Key roles, cont. Client SME client M & A subject matter experts ( SMEs ) who are knowledgeable about the M & A...vacation days, days not available, % time available for the MAID evaluation). 1b Client POC Identifies the client SME for each of the areas that

Artificial intelligence, expert systems, computer vision, and natural language processing

NASA Technical Reports Server (NTRS)

Gevarter, W. B.

1984-01-01

An overview of artificial intelligence (AI), its core ingredients, and its applications is presented. The knowledge representation, logic, problem solving approaches, languages, and computers pertaining to AI are examined, and the state of the art in AI is reviewed. The use of AI in expert systems, computer vision, natural language processing, speech recognition and understanding, speech synthesis, problem solving, and planning is examined. Basic AI topics, including automation, search-oriented problem solving, knowledge representation, and computational logic, are discussed.

Proceedings of the 1986 IEEE international conference on systems, man and cybernetics

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

Not Available

1986-01-01

This book presents the papers given at a conference on man-machine systems. Topics considered at the conference included neural model-based cognitive theory and engineering, user interfaces, adaptive and learning systems, human interaction with robotics, decision making, the testing and evaluation of expert systems, software development, international conflict resolution, intelligent interfaces, automation in man-machine system design aiding, knowledge acquisition in expert systems, advanced architectures for artificial intelligence, pattern recognition, knowledge bases, and machine vision.

Expert systems in transmission planning

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

Galiana, F.D.; McGillis, D.T.; Marin, M.A.

1992-05-01

In this paper the state of the field of expert systems and knowledge engineering in transmission planning is reviewed. A detailed analysis of the goals, definition, requirements and methodology of transmission planning is presented. Potential benefits of knowledge-based applications in transmission planning are reviewed. This is followed by a thorough review of the area broken down into subareas or important related topics. The conclusions offer a number of suggestions for possible future research and development. Finally, a detailed bibliography divided into subareas is presented.

Structuring expert input for a knowledge-based approach to watershed condition assessment for the Northwest Forest Plan, USA

Treesearch

Sean N. Gordon; Gallo Kirsten

2011-01-01

Assessments of watershed condition for aquatic and riparian species often have to rely on expert opinion because of the complexity of establishing statistical relationships among the many factors involved. Such expert-based assessments can be difficult to document and apply consistently over time and space. We describe and reflect on the process of developing a...

Mudflow Hazards in the Georgian Caucasus - Using Participatory Methods to Investigate Disaster Risk

NASA Astrophysics Data System (ADS)

Spanu, Valentina; McCall, Michael; Gaprindashvili, George

2014-05-01

The Caucasus form an extremely complex mountainous area of Georgia in terms of geology and the scale and frequency of natural disaster processes. These processes, especially mudflows, frequently result in considerable damage to the settlements, farmlands and infrastructure facilities. The occurrence intervals between mudflows are becoming significantly shorter, therefore the most populated areas and infrastucture need to be included in risk zones. This presentation reviews the case of the mudflow problem in Mleta village in the region of Dusheti where the mudflow risk is critical. The villages of Zemo Mleta (Higher Mleta) and Kvemo Mleta (Lower Mleta) are entirely surrounded by unstable slopes where mudslides, landslides and floods are often generated. These hazards occur at least twice per year and sometimes result in severe events. In 2006 and 2010 in Mleta village a very severe mudflow event occurred creating heavy damage. This paper focuses on the recognition of the importance of cooperating with the local communities affected by these disasters, in order to get useful information and local knowledge to apply to disaster prevention and management. In October 2010, the EU-financed MATRA Project (Institutional Capacity Building in Natural Disaster Risk Reduction) in Georgia included fieldworks in several locations. Particular attention was given to Mleta village in the Caucasus Mountains, where the activities focused on institutional capacity-building in disaster risk reduction, including modern spatial planning approaches and technologies and the development of risk communication strategies. Participatory methods of acquiring local knowledge from local communities reveal many advantages compared to traditional survey approaches for collecting data. In a participatory survey and planning approach, local authorities, experts and local communities are supposed to work together to provide useful information and eventually produce a plan for Disaster Risk Reduction/Management (DRR and DRM). Participatory surveys (and participatory monitoring) elicit local people's knowledge about the specifics of the hazard concerning frequency, timing, warning signals, rates of flow, spatial extent, etc. And significantly, only this local knowledge from informants can reveal essential information about different vulnerabilities of people and places, and about any coping or adjustment mechanisms that local people have. The participatory methods employed in Mleta included historical discussions with key informants, village social transects, participatory mapping with children, semi-structured interviews with inhabitants, and VCA (Vulnerability & Capacity Analysis). The geolomorphological map produced on the base of the local geology has been realized with ArcGIS. This allowed the assessment of the areas at risk and the relative maps. We adapted and tested the software programme CyberTracker as a survey tool, a digital device method of field data collection. Google Earth, OpenStreetMap, Virtual Earth and Ilwis have been used for data processing.

Spanning Knowledge Barriers in E-Learning Content Design

ERIC Educational Resources Information Center

Chu, Tsai-Hsin; Lee, Yi; Lee, Yen-Hsien

2013-01-01

E-learning content development can be regarded as an example of knowledge delivery process because the developers have to receive knowledge transferred from subject-matter experts (SMEs), to translate the received knowledge with appropriate instructional design, and to transform the project outcomes to fulfill learner's learning needs. As…

Sea Stories: A Collaborative Tool for Articulating Tactical Knowledge.

ERIC Educational Resources Information Center

Radtke, Paul H.; Frey, Paul R.

Having subject matter experts (SMEs) identify the skills and knowledge to be taught is among the more difficult and time-consuming steps in the training development process. A procedure has been developed for identifying specific tactical decision-making knowledge requirements and translating SME knowledge into appropriate multimedia…

Coastal Resilience and Adaptation:Working Together to go from Information to Action on Alaska's Coasts

NASA Astrophysics Data System (ADS)

Holman, A.; Poe, A.; Murphy, K.; Littell, J. S.; Pletnikoff, K.; Holen, D.

2016-12-01

The phrases "coastal resilience" and "climate adaptation" appear everywhere now—but how do they meet the needs of communities and natural resource managers on Alaska's coast? A regional consortium of The Aleutian Pribilof Islands Association, four of Alaska's Landscape Conservation Cooperatives (LCCs), NOAA, University of Alaska Fairbanks and the Alaska Climate Science Center joined numerous local partners including several Tribes and Alaska Native Organizations to host workshops in five regions to find out.The project brought together audiences from Tribal and local government, State and Federal agencies, scientists and local experts to share the state of existing knowledge on current and anticipated environmental changes and impacts and discuss potential response actions. Targeting information and tools needed for decision making and resource management, the hundreds of workshop participants identified gaps in available data, information and knowledge that needs to be filled to help communities and managers better respond to climate change. Each of the workshops built upon the other and connected stakeholders and increase resiliency by bringing local decision makers together with the researchers who can fill their needs, consolidating and leveraging research being done in the region by many different parties (western and traditional) and ensuring those results get to those who need them, and creating an adaptive, collaborative process of identifying needs, conducting work, gathering the latest science from local to national sources, presenting results for evaluation and feedback, and using that information to drive future research and management investments. The resulting "toolbox" will help management agencies and others to better understand the dynamic changes Alaska is experiencing, their impacts on communities and habitats, as well as tools and information that can help managers and community leaders work better together to adapt to climate change.

Reassembling epidemiology: mapping, monitoring and making-up people in the context of HIV prevention in India.

PubMed

Lorway, Robert; Khan, Shamshad

2014-07-01

This paper explores how the Gates-funded HIV Initiative in India, known as Avahan, produces sociality. Drawing upon ethnographic research conducted between 2006 and 2012, we illustrate how epidemiological surveillance procedures, undergirded by contemporary managerial and entrepreneurial logics, entwine with and become transformed by the everyday practices of men who have sex with men (many of whom sell sex). The coevolution of epidemiology and sociality, with respect to these communities, is explored in relation to: 1) how individual identities are reproduced in association with standardized units of space and time; 2) how knowledge of mapping and enumeration data is employed in the making up of group membership boundaries, revealing how collective interests come to cohere around the project of epidemic prevention; and 3) how knowledge of epidemiological surveillance and procedures provides a basis on which groups collectively realize and execute local security strategies. While monitoring and evaluation (M&E) specialists continually track and standardize the identities, behaviours and social spaces of local populations (through various mapping, typologization and random sampling procedures, which treat space and time as predictable variables), community members simultaneously retranslate and reroute these standardizing processes into "the local" through everyday spatial management practices for health protection. These grounded epidemiologies, we argue, point to vital sites in the co-creation of scientific knowledge-where the quotidian practices of sex workers reassemble epidemiology, continually altering the very objects that surveillance experts are tracking. We further argue that attention to these re-workings can help us unravel the tremendous successes that have been claimed under Avahan in terms of HIV infections averted. Copyright © 2014 Elsevier Ltd. All rights reserved.

International Expert Consensus Document on Takotsubo Syndrome (Part I): Clinical Characteristics, Diagnostic Criteria, and Pathophysiology.

PubMed

Ghadri, Jelena-Rima; Wittstein, Ilan Shor; Prasad, Abhiram; Sharkey, Scott; Dote, Keigo; Akashi, Yoshihiro John; Cammann, Victoria Lucia; Crea, Filippo; Galiuto, Leonarda; Desmet, Walter; Yoshida, Tetsuro; Manfredini, Roberto; Eitel, Ingo; Kosuge, Masami; Nef, Holger M; Deshmukh, Abhishek; Lerman, Amir; Bossone, Eduardo; Citro, Rodolfo; Ueyama, Takashi; Corrado, Domenico; Kurisu, Satoshi; Ruschitzka, Frank; Winchester, David; Lyon, Alexander R; Omerovic, Elmir; Bax, Jeroen J; Meimoun, Patrick; Tarantini, Guiseppe; Rihal, Charanjit; Y-Hassan, Shams; Migliore, Federico; Horowitz, John D; Shimokawa, Hiroaki; Lüscher, Thomas Felix; Templin, Christian

2018-06-07

Takotsubo syndrome (TTS) is a poorly recognized heart disease that was initially regarded as a benign condition. Recently, it has been shown that TTS may be associated with severe clinical complications including death and that its prevalence is probably underestimated. Since current guidelines on TTS are lacking, it appears timely and important to provide an expert consensus statement on TTS. The clinical expert consensus document part I summarizes the current state of knowledge on clinical presentation and characteristics of TTS and agrees on controversies surrounding TTS such as nomenclature, different TTS types, role of coronary artery disease, and etiology. This consensus also proposes new diagnostic criteria based on current knowledge to improve diagnostic accuracy.