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.

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.

Elicitation of quantitative data from a heterogeneous expert panel: formal process and application in animal health.

PubMed

Van der Fels-Klerx, Ine H J; Goossens, Louis H J; Saatkamp, Helmut W; Horst, Suzan H S

2002-02-01

This paper presents a protocol for a formal expert judgment process using a heterogeneous expert panel aimed at the quantification of continuous variables. The emphasis is on the process's requirements related to the nature of expertise within the panel, in particular the heterogeneity of both substantive and normative expertise. The process provides the opportunity for interaction among the experts so that they fully understand and agree upon the problem at hand, including qualitative aspects relevant to the variables of interest, prior to the actual quantification task. Individual experts' assessments on the variables of interest, cast in the form of subjective probability density functions, are elicited with a minimal demand for normative expertise. The individual experts' assessments are aggregated into a single probability density function per variable, thereby weighting the experts according to their expertise. Elicitation techniques proposed include the Delphi technique for the qualitative assessment task and the ELI method for the actual quantitative assessment task. Appropriately, the Classical model was used to weight the experts' assessments in order to construct a single distribution per variable. Applying this model, the experts' quality typically was based on their performance on seed variables. An application of the proposed protocol in the broad and multidisciplinary field of animal health is presented. Results of this expert judgment process showed that the proposed protocol in combination with the proposed elicitation and analysis techniques resulted in valid data on the (continuous) variables of interest. In conclusion, the proposed protocol for a formal expert judgment process aimed at the elicitation of quantitative data from a heterogeneous expert panel provided satisfactory results. Hence, this protocol might be useful for expert judgment studies in other broad and/or multidisciplinary fields of interest.

Three CLIPS-based expert systems for solving engineering problems

NASA Technical Reports Server (NTRS)

Parkinson, W. J.; Luger, G. F.; Bretz, R. E.

1990-01-01

We have written three expert systems, using the CLIPS PC-based expert system shell. These three expert systems are rule based and are relatively small, with the largest containing slightly less than 200 rules. The first expert system is an expert assistant that was written to help users of the ASPEN computer code choose the proper thermodynamic package to use with their particular vapor-liquid equilibrium problem. The second expert system was designed to help petroleum engineers choose the proper enhanced oil recovery method to be used with a given reservoir. The effectiveness of each technique is highly dependent upon the reservoir conditions. The third expert system is a combination consultant and control system. This system was designed specifically for silicon carbide whisker growth. Silicon carbide whiskers are an extremely strong product used to make ceramic and metal composites. The manufacture of whiskers is a very complicated process. which to date. has defied a good mathematical model. The process was run by experts who had gained their expertise by trial and error. A system of rules was devised by these experts both for procedure setup and for the process control. In this paper we discuss the three problem areas of the design, development and evaluation of the CLIPS-based programs.

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.

A Model-Based Expert System for Space Power Distribution Diagnostics

NASA Technical Reports Server (NTRS)

Quinn, Todd M.; Schlegelmilch, Richard F.

1994-01-01

When engineers diagnose system failures, they often use models to confirm system operation. This concept has produced a class of advanced expert systems that perform model-based diagnosis. A model-based diagnostic expert system for the Space Station Freedom electrical power distribution test bed is currently being developed at the NASA Lewis Research Center. The objective of this expert system is to autonomously detect and isolate electrical fault conditions. Marple, a software package developed at TRW, provides a model-based environment utilizing constraint suspension. Originally, constraint suspension techniques were developed for digital systems. However, Marple provides the mechanisms for applying this approach to analog systems such as the test bed, as well. The expert system was developed using Marple and Lucid Common Lisp running on a Sun Sparc-2 workstation. The Marple modeling environment has proved to be a useful tool for investigating the various aspects of model-based diagnostics. This report describes work completed to date and lessons learned while employing model-based diagnostics using constraint suspension within an analog system.

Diagnosis - Using automatic test equipment and artificial intelligence expert systems

NASA Astrophysics Data System (ADS)

Ramsey, J. E., Jr.

Three expert systems (ATEOPS, ATEFEXPERS, and ATEFATLAS), which were created to direct automatic test equipment (ATE), are reviewed. The purpose of the project was to develop an expert system to troubleshoot the converter-programmer power supply card for the F-15 aircraft and have that expert system direct the automatic test equipment. Each expert system uses a different knowledge base or inference engine, basing the testing on the circuit schematic, test requirements document, or ATLAS code. Implementing generalized modules allows the expert systems to be used for any different unit under test. Using converted ATLAS to LISP code allows the expert system to direct any ATE using ATLAS. The constraint propagated frame system allows for the expansion of control by creating the ATLAS code, checking the code for good software engineering techniques, directing the ATE, and changing the test sequence as needed (planning).

Expert system and process optimization techniques for real-time monitoring and control of plasma processes

NASA Astrophysics Data System (ADS)

Cheng, Jie; Qian, Zhaogang; Irani, Keki B.; Etemad, Hossein; Elta, Michael E.

1991-03-01

To meet the ever-increasing demand of the rapidly-growing semiconductor manufacturing industry it is critical to have a comprehensive methodology integrating techniques for process optimization real-time monitoring and adaptive process control. To this end we have accomplished an integrated knowledge-based approach combining latest expert system technology machine learning method and traditional statistical process control (SPC) techniques. This knowledge-based approach is advantageous in that it makes it possible for the task of process optimization and adaptive control to be performed consistently and predictably. Furthermore this approach can be used to construct high-level and qualitative description of processes and thus make the process behavior easy to monitor predict and control. Two software packages RIST (Rule Induction and Statistical Testing) and KARSM (Knowledge Acquisition from Response Surface Methodology) have been developed and incorporated with two commercially available packages G2 (real-time expert system) and ULTRAMAX (a tool for sequential process optimization).

An Intelligent Content Discovery Technique for Health Portal Content Management

PubMed Central

2014-01-01

Background Continuous content management of health information portals is a feature vital for its sustainability and widespread acceptance. Knowledge and experience of a domain expert is essential for content management in the health domain. The rate of generation of online health resources is exponential and thereby manual examination for relevance to a specific topic and audience is a formidable challenge for domain experts. Intelligent content discovery for effective content management is a less researched topic. An existing expert-endorsed content repository can provide the necessary leverage to automatically identify relevant resources and evaluate qualitative metrics. Objective This paper reports on the design research towards an intelligent technique for automated content discovery and ranking for health information portals. The proposed technique aims to improve efficiency of the current mostly manual process of portal content management by utilising an existing expert-endorsed content repository as a supporting base and a benchmark to evaluate the suitability of new content Methods A model for content management was established based on a field study of potential users. The proposed technique is integral to this content management model and executes in several phases (ie, query construction, content search, text analytics and fuzzy multi-criteria ranking). The construction of multi-dimensional search queries with input from Wordnet, the use of multi-word and single-word terms as representative semantics for text analytics and the use of fuzzy multi-criteria ranking for subjective evaluation of quality metrics are original contributions reported in this paper. Results The feasibility of the proposed technique was examined with experiments conducted on an actual health information portal, the BCKOnline portal. Both intermediary and final results generated by the technique are presented in the paper and these help to establish benefits of the technique and its contribution towards effective content management. Conclusions The prevalence of large numbers of online health resources is a key obstacle for domain experts involved in content management of health information portals and websites. The proposed technique has proven successful at search and identification of resources and the measurement of their relevance. It can be used to support the domain expert in content management and thereby ensure the health portal is up-to-date and current. PMID:25654440

Expert systems for automated maintenance of a Mars oxygen production system

NASA Astrophysics Data System (ADS)

Huang, Jen-Kuang; Ho, Ming-Tsang; Ash, Robert L.

1992-08-01

Application of expert system concepts to a breadboard Mars oxygen processor unit have been studied and tested. The research was directed toward developing the methodology required to enable autonomous operation and control of these simple chemical processors at Mars. Failure detection and isolation was the key area of concern, and schemes using forward chaining, backward chaining, knowledge-based expert systems, and rule-based expert systems were examined. Tests and simulations were conducted that investigated self-health checkout, emergency shutdown, and fault detection, in addition to normal control activities. A dynamic system model was developed using the Bond-Graph technique. The dynamic model agreed well with tests involving sudden reductions in throughput. However, nonlinear effects were observed during tests that incorporated step function increases in flow variables. Computer simulations and experiments have demonstrated the feasibility of expert systems utilizing rule-based diagnosis and decision-making algorithms.

Rule groupings in expert systems using nearest neighbour decision rules, and convex hulls

NASA Technical Reports Server (NTRS)

Anastasiadis, Stergios

1991-01-01

Expert System shells are lacking in many areas of software engineering. Large rule based systems are not semantically comprehensible, difficult to debug, and impossible to modify or validate. Partitioning a set of rules found in CLIPS (C Language Integrated Production System) into groups of rules which reflect the underlying semantic subdomains of the problem, will address adequately the concerns stated above. Techniques are introduced to structure a CLIPS rule base into groups of rules that inherently have common semantic information. The concepts involved are imported from the field of A.I., Pattern Recognition, and Statistical Inference. Techniques focus on the areas of feature selection, classification, and a criteria of how 'good' the classification technique is, based on Bayesian Decision Theory. A variety of distance metrics are discussed for measuring the 'closeness' of CLIPS rules and various Nearest Neighbor classification algorithms are described based on the above metric.

The Desired Learning Outcomes of School-Based Nutrition/Physical Activity Health Education: A Health Literacy Constructed Delphi Survey of Finnish Experts

ERIC Educational Resources Information Center

Ormshaw, Michael James; Kokko, Sami Petteri; Villberg, Jari; Kannas, Lasse

2016-01-01

Purpose: The purpose of this paper is to utilise the collective opinion of a group of Finnish experts to identify the most important learning outcomes of secondary-level school-based health education, in the specific domains of physical activity and nutrition. Design/ Methodology/ Approach: The study uses a Delphi survey technique to collect the…

A knowledge based expert system for propellant system monitoring at the Kennedy Space Center

NASA Technical Reports Server (NTRS)

Jamieson, J. R.; Delaune, C.; Scarl, E.

1985-01-01

The Lox Expert System (LES) is the first attempt to build a realtime expert system capable of simulating the thought processes of NASA system engineers, with regard to fluids systems analysis and troubleshooting. An overview of the hardware and software describes the techniques used, and possible applications to other process control systems. LES is now in the advanced development stage, with a full implementation planned for late 1985.

Forum for Injection Technique and Therapy Expert Recommendations, India: The Indian Recommendations for Best Practice in Insulin Injection Technique, 2017

PubMed Central

Tandon, Nikhil; Kalra, Sanjay; Balhara, Yatan Pal Singh; Baruah, Manash P.; Chadha, Manoj; Chandalia, Hemraj B.; Prasanna Kumar, K. M.; Madhu, S. V.; Mithal, Ambrish; Sahay, Rakesh; Shukla, Rishi; Sundaram, Annamalai; Unnikrishnan, Ambika G.; Saboo, Banshi; Gupta, Vandita; Chowdhury, Subhankar; Kesavadev, Jothydev; Wangnoo, Subhash K.

2017-01-01

Health-care professionals in India frequently manage injection or infusion therapies in persons with diabetes (PWD). Patients taking insulin should know the importance of proper needle size, correct injection process, complication avoidance, and all other aspects of injection technique from the first visit onward. To assist health-care practitioners in their clinical practice, Forum for Injection Technique and Therapy Expert Recommendations, India, has updated the practical advice and made it more comprehensive evidence-based best practice information. Adherence to these updated recommendations, learning, and translating them into clinical practice should lead to effective therapies, improved outcomes, and lower costs for PWD. PMID:28670547

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.

Expertise transfer for expert system design

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

Boose, J.H.

This book is about the Expertise Transfer System-a computer program which interviews experts and helps them build expert systems, i.e. computer programs that use knowledge from experts to make decisions and judgements under conditions of uncertainty. The techniques are useful to anyone who uses decision-making information based on the expertise of others. The methods can also be applied to personal decision-making. The interviewing methodology is borrowed from a branch of psychology called Personal Construct Theory. It is not necessary to use a computer to take advantage of the techniques from Personal Construction Theory; the fundamental procedures used by the Expertisemore » Transfer System can be performed using paper and pencil. It is not necessary that the reader understand very much about computers to understand the ideas in this book. The few relevant concepts from computer science and expert systems that are needed are explained in a straightforward manner. Ideas from Personal Construct Psychology are also introduced as needed.« less

Guidelines for using the Delphi Technique to develop habitat suitability index curves

USGS Publications Warehouse

Crance, Johnie H.

1987-01-01

Habitat Suitability Index (SI) curves are one method of presenting species habitat suitability criteria. The curves are often used with the Habitat Evaluation Procedures (HEP) and are necessary components of the Instream Flow Incremental Methodology (IFIM) (Armour et al. 1984). Bovee (1986) described three categories of SI curves or habitat suitability criteria based on the procedures and data used to develop the criteria. Category I curves are based on professional judgment, with 1ittle or no empirical data. Both Category II (utilization criteria) and Category III (preference criteria) curves have as their source data collected at locations where target species are observed or collected. Having Category II and Category III curves for all species of concern would be ideal. In reality, no SI curves are available for many species, and SI curves that require intensive field sampling often cannot be developed under prevailing constraints on time and costs. One alternative under these circumstances is the development and interim use of SI curves based on expert opinion. The Delphi technique (Pill 1971; Delbecq et al. 1975; Linstone and Turoff 1975) is one method used for combining the knowledge and opinions of a group of experts. The purpose of this report is to describe how the Delphi technique may be used to develop expert-opinion-based SI curves.

Quantitative knowledge acquisition for expert systems

NASA Technical Reports Server (NTRS)

Belkin, Brenda L.; Stengel, Robert F.

1991-01-01

A common problem in the design of expert systems is the definition of rules from data obtained in system operation or simulation. While it is relatively easy to collect data and to log the comments of human operators engaged in experiments, generalizing such information to a set of rules has not previously been a direct task. A statistical method is presented for generating rule bases from numerical data, motivated by an example based on aircraft navigation with multiple sensors. The specific objective is to design an expert system that selects a satisfactory suite of measurements from a dissimilar, redundant set, given an arbitrary navigation geometry and possible sensor failures. The systematic development is described of a Navigation Sensor Management (NSM) Expert System from Kalman Filter convariance data. The method invokes two statistical techniques: Analysis of Variance (ANOVA) and the ID3 Algorithm. The ANOVA technique indicates whether variations of problem parameters give statistically different covariance results, and the ID3 algorithms identifies the relationships between the problem parameters using probabilistic knowledge extracted from a simulation example set. Both are detailed.

The development of expertise in pediatric rehabilitation therapists: changes in approach, self-knowledge, and use of enabling and customizing strategies.

PubMed

King, Gillian; Currie, Melissa; Bartlett, Doreen J; Gilpin, Michelle; Willoughby, Colleen; Tucker, Mary Ann; Strachan, Deborah; Baxter, Donna

2007-01-01

To examine the clinical decision making of novice, intermediate, and expert pediatric rehabilitation therapists from various disciplines. Two qualitative studies were conducted. Thirteen therapists took part in a study using the critical incident interview technique and 11 therapists took part in a study using the 'think aloud' technique. Therapists were classified as novice, intermediate, or expert in developmental level based on a cluster analysis of data collected using a multifaceted battery of assessment tools. Data were analyzed using a grounded theory approach. Expert and intermediate therapists differed from novices with respect to content, self-, and procedural knowledge. With increasing expertise, therapists use a supportive, educational, holistic, functional, and strengths-based approach; have heightened humility yet increased self-confidence; and understand how to facilitate and support client change and adaptation by using principles of engagement, coherence, and manageability. Expert therapists use enabling and customizing strategies to ensure a successful therapeutic session, optimize the child's functioning in the mid-term, and ensure child and family adaptation and accommodation over the longer-term.

Graph-based real-time fault diagnostics

NASA Technical Reports Server (NTRS)

Padalkar, S.; Karsai, G.; Sztipanovits, J.

1988-01-01

A real-time fault detection and diagnosis capability is absolutely crucial in the design of large-scale space systems. Some of the existing AI-based fault diagnostic techniques like expert systems and qualitative modelling are frequently ill-suited for this purpose. Expert systems are often inadequately structured, difficult to validate and suffer from knowledge acquisition bottlenecks. Qualitative modelling techniques sometimes generate a large number of failure source alternatives, thus hampering speedy diagnosis. In this paper we present a graph-based technique which is well suited for real-time fault diagnosis, structured knowledge representation and acquisition and testing and validation. A Hierarchical Fault Model of the system to be diagnosed is developed. At each level of hierarchy, there exist fault propagation digraphs denoting causal relations between failure modes of subsystems. The edges of such a digraph are weighted with fault propagation time intervals. Efficient and restartable graph algorithms are used for on-line speedy identification of failure source components.

Using cognitive task analysis to develop simulation-based training for medical tasks.

PubMed

Cannon-Bowers, Jan; Bowers, Clint; Stout, Renee; Ricci, Katrina; Hildabrand, Annette

2013-10-01

Pressures to increase the efficacy and effectiveness of medical training are causing the Department of Defense to investigate the use of simulation technologies. This article describes a comprehensive cognitive task analysis technique that can be used to simultaneously generate training requirements, performance metrics, scenario requirements, and simulator/simulation requirements for medical tasks. On the basis of a variety of existing techniques, we developed a scenario-based approach that asks experts to perform the targeted task multiple times, with each pass probing a different dimension of the training development process. In contrast to many cognitive task analysis approaches, we argue that our technique can be highly cost effective because it is designed to accomplish multiple goals. The technique was pilot tested with expert instructors from a large military medical training command. These instructors were employed to generate requirements for two selected combat casualty care tasks-cricothyroidotomy and hemorrhage control. Results indicated that the technique is feasible to use and generates usable data to inform simulation-based training system design. Reprint & Copyright © 2013 Association of Military Surgeons of the U.S.

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.

Frontline over ivory tower: key competencies in community-based curricula.

PubMed

Millar, Adam; Malcolm, Janine; Cheng, Alice; Fine, Rebecca; Wong, Rene

2015-01-01

The Royal College of Physicians and Surgeons of Canada mandates that community experiences be incorporated into medicine-based specialties. Presently there is wide variability in community endocrine experiences across Canadian training programs. This is complicated by the paucity of literature providing guidance on what constitutes a 'community' rotation. A modified Delphi technique was used to determine the CanMEDS competencies best taught in a community endocrinology curriculum. The Delphi technique is a qualitative-research method that uses a series of questionnaires sent to a group of experts with controlled feedback provided by the researchers after each survey round. The experts in this study included endocrinology program directors, community endocrinologists, endocrinology residents and recent endocrinology graduates. Thirty four out of 44 competencies rated by the panel were deemed suitable for a community curriculum. The experts considered the "Manager" role best taught in the community, while they considered the community least suitable to learn the "Medical Expert" competency. To our knowledge, this is the first time the content of a community-based subspecialty curriculum was determined using the Delphi process in Canada. These findings suggest that community settings have potential to fill in gaps in residency training in regards to the CanMEDS Manager role. The results will aid program directors in designing competency-based community endocrinology rotations and competency-based community rotations in other medical subspecialty programs.

An integrated approach to improving noisy speech perception

NASA Astrophysics Data System (ADS)

Koval, Serguei; Stolbov, Mikhail; Smirnova, Natalia; Khitrov, Mikhail

2002-05-01

For a number of practical purposes and tasks, experts have to decode speech recordings of very poor quality. A combination of techniques is proposed to improve intelligibility and quality of distorted speech messages and thus facilitate their comprehension. Along with the application of noise cancellation and speech signal enhancement techniques removing and/or reducing various kinds of distortions and interference (primarily unmasking and normalization in time and frequency fields), the approach incorporates optimal listener expert tactics based on selective listening, nonstandard binaural listening, accounting for short-term and long-term human ear adaptation to noisy speech, as well as some methods of speech signal enhancement to support speech decoding during listening. The approach integrating the suggested techniques ensures high-quality ultimate results and has successfully been applied by Speech Technology Center experts and by numerous other users, mainly forensic institutions, to perform noisy speech records decoding for courts, law enforcement and emergency services, accident investigation bodies, etc.

Methods to elicit probability distributions from experts: a systematic review of reported practice in health technology assessment.

PubMed

Grigore, Bogdan; Peters, Jaime; Hyde, Christopher; Stein, Ken

2013-11-01

Elicitation is a technique that can be used to obtain probability distribution from experts about unknown quantities. We conducted a methodology review of reports where probability distributions had been elicited from experts to be used in model-based health technology assessments. Databases including MEDLINE, EMBASE and the CRD database were searched from inception to April 2013. Reference lists were checked and citation mapping was also used. Studies describing their approach to the elicitation of probability distributions were included. Data was abstracted on pre-defined aspects of the elicitation technique. Reports were critically appraised on their consideration of the validity, reliability and feasibility of the elicitation exercise. Fourteen articles were included. Across these studies, the most marked features were heterogeneity in elicitation approach and failure to report key aspects of the elicitation method. The most frequently used approaches to elicitation were the histogram technique and the bisection method. Only three papers explicitly considered the validity, reliability and feasibility of the elicitation exercises. Judged by the studies identified in the review, reports of expert elicitation are insufficient in detail and this impacts on the perceived usability of expert-elicited probability distributions. In this context, the wider credibility of elicitation will only be improved by better reporting and greater standardisation of approach. Until then, the advantage of eliciting probability distributions from experts may be lost.

High-level user interfaces for transfer function design with semantics.

PubMed

Salama, Christof Rezk; Keller, Maik; Kohlmann, Peter

2006-01-01

Many sophisticated techniques for the visualization of volumetric data such as medical data have been published. While existing techniques are mature from a technical point of view, managing the complexity of visual parameters is still difficult for non-expert users. To this end, this paper presents new ideas to facilitate the specification of optical properties for direct volume rendering. We introduce an additional level of abstraction for parametric models of transfer functions. The proposed framework allows visualization experts to design high-level transfer function models which can intuitively be used by non-expert users. The results are user interfaces which provide semantic information for specialized visualization problems. The proposed method is based on principal component analysis as well as on concepts borrowed from computer animation.

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.

Development and Evaluation of an Adaptive Computerized Training System (ACTS). R&D Report 78-1.

ERIC Educational Resources Information Center

Knerr, Bruce W.; Nawrocki, Leon H.

This report describes the development of a computer based system designed to train electronic troubleshooting procedures. The ACTS uses artificial intelligence techniques to develop models of student and expert troubleshooting behavior as they solve a series of troubleshooting problems on the system. Comparisons of the student and expert models…

A Delphi Study: The Characteristics of Democratic Schools

ERIC Educational Resources Information Center

Korkmaz, H. Eylem; Erden, Münire

2014-01-01

The authors aim to identify characteristics of democratic schools. The Delphi technique used in this study is based on attaining a consensus among a group of experts over 3 rounds with 22 experts from 9 countries participating in the first round. By the end of the third round, 339 items referring to democratic school characteristics were…

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

Model authoring system for fail safe analysis

NASA Technical Reports Server (NTRS)

Sikora, Scott E.

1990-01-01

The Model Authoring System is a prototype software application for generating fault tree analyses and failure mode and effects analyses for circuit designs. Utilizing established artificial intelligence and expert system techniques, the circuits are modeled as a frame-based knowledge base in an expert system shell, which allows the use of object oriented programming and an inference engine. The behavior of the circuit is then captured through IF-THEN rules, which then are searched to generate either a graphical fault tree analysis or failure modes and effects analysis. Sophisticated authoring techniques allow the circuit to be easily modeled, permit its behavior to be quickly defined, and provide abstraction features to deal with complexity.

Complex method to calculate objective assessments of information systems protection to improve expert assessments reliability

NASA Astrophysics Data System (ADS)

Abdenov, A. Zh; Trushin, V. A.; Abdenova, G. A.

2018-01-01

The paper considers the questions of filling the relevant SIEM nodes based on calculations of objective assessments in order to improve the reliability of subjective expert assessments. The proposed methodology is necessary for the most accurate security risk assessment of information systems. This technique is also intended for the purpose of establishing real-time operational information protection in the enterprise information systems. Risk calculations are based on objective estimates of the adverse events implementation probabilities, predictions of the damage magnitude from information security violations. Calculations of objective assessments are necessary to increase the reliability of the proposed expert assessments.

Expert judgement and uncertainty quantification for climate change

NASA Astrophysics Data System (ADS)

Oppenheimer, Michael; Little, Christopher M.; Cooke, Roger M.

2016-05-01

Expert judgement is an unavoidable element of the process-based numerical models used for climate change projections, and the statistical approaches used to characterize uncertainty across model ensembles. Here, we highlight the need for formalized approaches to unifying numerical modelling with expert judgement in order to facilitate characterization of uncertainty in a reproducible, consistent and transparent fashion. As an example, we use probabilistic inversion, a well-established technique used in many other applications outside of climate change, to fuse two recent analyses of twenty-first century Antarctic ice loss. Probabilistic inversion is but one of many possible approaches to formalizing the role of expert judgement, and the Antarctic ice sheet is only one possible climate-related application. We recommend indicators or signposts that characterize successful science-based uncertainty quantification.

Method for evaluation of human induced pluripotent stem cell quality using image analysis based on the biological morphology of cells.

PubMed

Wakui, Takashi; Matsumoto, Tsuyoshi; Matsubara, Kenta; Kawasaki, Tomoyuki; Yamaguchi, Hiroshi; Akutsu, Hidenori

2017-10-01

We propose an image analysis method for quality evaluation of human pluripotent stem cells based on biologically interpretable features. It is important to maintain the undifferentiated state of induced pluripotent stem cells (iPSCs) while culturing the cells during propagation. Cell culture experts visually select good quality cells exhibiting the morphological features characteristic of undifferentiated cells. Experts have empirically determined that these features comprise prominent and abundant nucleoli, less intercellular spacing, and fewer differentiating cellular nuclei. We quantified these features based on experts' visual inspection of phase contrast images of iPSCs and found that these features are effective for evaluating iPSC quality. We then developed an iPSC quality evaluation method using an image analysis technique. The method allowed accurate classification, equivalent to visual inspection by experts, of three iPSC cell lines.

An Electronic Engineering Curriculum Design Based on Concept-Mapping Techniques

ERIC Educational Resources Information Center

Toral, S. L.; Martinez-Torres, M. R.; Barrero, F.; Gallardo, S.; Duran, M. J.

2007-01-01

Curriculum design is a concern in European Universities as they face the forthcoming European Higher Education Area (EHEA). This process can be eased by the use of scientific tools such as Concept-Mapping Techniques (CMT) that extract and organize the most relevant information from experts' experience using statistics techniques, and helps a…

Maintenance Audit through Value Analysis Technique: A Case Study

NASA Astrophysics Data System (ADS)

Carnero, M. C.; Delgado, S.

2008-11-01

The increase in competitiveness, technological changes and the increase in the requirements of quality and service have forced a change in the design and application of maintenance, as well as the way in which it is considered within the managerial strategy. There are numerous maintenance activities that must be developed in a service company. As a result the maintenance functions as a whole have to be outsourced. Nevertheless, delegating this subject to specialized personnel does not exempt the company from responsibilities, but rather leads to the need for control of each maintenance activity. In order to achieve this control and to evaluate the efficiency and effectiveness of the company it is essential to carry out an audit that diagnoses the problems that could develop. In this paper a maintenance audit applied to a service company is developed. The methodology applied is based on the expert systems. The expert system by means of rules uses the weighting technique SMART and value analysis to obtain the weighting between the decision functions and between the alternatives. The expert system applies numerous rules and relations between different variables associated with the specific maintenance functions, to obtain the maintenance state by sections and the general maintenance state of the enterprise. The contributions of this paper are related to the development of a maintenance audit in a service enterprise, in which maintenance is not generally considered a strategic subject and to the integration of decision-making tools such as the weighting technique SMART with value analysis techniques, typical in the design of new products, in the area of the rule-based expert systems.

Expert system verification and validation study: ES V/V Workshop

NASA Technical Reports Server (NTRS)

French, Scott; Hamilton, David

1992-01-01

The primary purpose of this document is to build a foundation for applying principles of verification and validation (V&V) of expert systems. To achieve this, some V&V as applied to conventionally implemented software is required. Part one will discuss the background of V&V from the perspective of (1) what is V&V of software and (2) V&V's role in developing software. Part one will also overview some common analysis techniques that are applied when performing V&V of software. All of these materials will be presented based on the assumption that the reader has little or no background in V&V or in developing procedural software. The primary purpose of part two is to explain the major techniques that have been developed for V&V of expert systems.

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…

Pediatric regional examination of the musculoskeletal system: a practice- and consensus-based approach.

PubMed

Foster, Helen; Kay, Lesley; May, Carl; Rapley, Tim

2011-11-01

Competent examination of the pediatric musculoskeletal (MSK) system is a vital component of clinical assessment of children with MSK presentations. The aim was to develop a regional MSK examination for school-age children that is age appropriate and reflects clinical practice. Qualitative and quantitative analyses involving video observation of clinical examination technique, systematic review, and expert consensus were employed to reveal descriptions, frequencies, and variations in technique for joint regions in various clinical scenarios. Systematic review and data from clinical observation were combined with feedback from a group of pediatric MSK experts through a web-based survey. All results were collated and discussed by consensus development groups to derive the pediatric Regional Examination of the Musculoskeletal System (pREMS). A total of 48 pediatric MSK expert clinicians were involved to derive pREMS. Systematic review revealed a paucity of evidence about regional pediatric MSK examination. Video observations of MSK examinations (a total of 2,901 maneuvers) performed by pediatric MSK experts (n = 11 doctors and 8 therapists) of 89 school-age children attending outpatient clinics in 7 UK pediatric rheumatology centers were followed by semistructured interviews with 14 of 19 clinicians. Video observation showed variation in examination techniques, most frequently at the hip and knee in the context of mechanical and inflammatory clinical scenarios. pREMS is the first practice- and consensus-based regional pediatric MSK examination for school-age children. The structured approach is an important step toward improved pediatric MSK clinical skills relevant to clinical training. Copyright © 2011 by the American College of Rheumatology.

Expertise of using striking techniques for power stroke in badminton.

PubMed

Zhu, Qin

2013-10-01

Two striking techniques (fast swing and angled striking) were examined to see if they allowed effective use of string tension for the power stroke in badminton. 12 participants (4 novices, 4 recreational, and 4 expert badminton players) were recorded by a fast-speed camera while striking a shuttlecock with racquets of 8 different string tensions. The peak speed of the shuttlecock, the racquet angle and the shuttlecock angle were analyzed. The results showed that expert players succeeded in using both striking techniques to overcome the constraint of string tension and produce a consistently superior stroke. Failure to use either striking technique resulted in inferior performance that was constrained by string tension. Expertise in badminton allows the necessary motor adjustments based on the affordance perception of the string tension.

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.

Development of a QFD-based expert system for CNC turning centre selection

NASA Astrophysics Data System (ADS)

Prasad, Kanika; Chakraborty, Shankar

2015-12-01

Computer numerical control (CNC) machine tools are automated devices capable of generating complicated and intricate product shapes in shorter time. Selection of the best CNC machine tool is a critical, complex and time-consuming task due to availability of a wide range of alternatives and conflicting nature of several evaluation criteria. Although, the past researchers had attempted to select the appropriate machining centres using different knowledge-based systems, mathematical models and multi-criteria decision-making methods, none of those approaches has given due importance to the voice of customers. The aforesaid limitation can be overcome using quality function deployment (QFD) technique, which is a systematic approach for integrating customers' needs and designing the product to meet those needs first time and every time. In this paper, the adopted QFD-based methodology helps in selecting CNC turning centres for a manufacturing organization, providing due importance to the voice of customers to meet their requirements. An expert system based on QFD technique is developed in Visual BASIC 6.0 to automate the CNC turning centre selection procedure for different production plans. Three illustrative examples are demonstrated to explain the real-time applicability of the developed expert system.

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.

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.

Method for distributed agent-based non-expert simulation of manufacturing process behavior

DOEpatents

Ivezic, Nenad; Potok, Thomas E.

2004-11-30

A method for distributed agent based non-expert simulation of manufacturing process behavior on a single-processor computer comprises the steps of: object modeling a manufacturing technique having a plurality of processes; associating a distributed agent with each the process; and, programming each the agent to respond to discrete events corresponding to the manufacturing technique, wherein each discrete event triggers a programmed response. The method can further comprise the step of transmitting the discrete events to each agent in a message loop. In addition, the programming step comprises the step of conditioning each agent to respond to a discrete event selected from the group consisting of a clock tick message, a resources received message, and a request for output production message.

Planning and Resource Management in an Intelligent Automated Power Management System

NASA Technical Reports Server (NTRS)

Morris, Robert A.

1991-01-01

Power system management is a process of guiding a power system towards the objective of continuous supply of electrical power to a set of loads. Spacecraft power system management requires planning and scheduling, since electrical power is a scarce resource in space. The automation of power system management for future spacecraft has been recognized as an important R&D goal. Several automation technologies have emerged including the use of expert systems for automating human problem solving capabilities such as rule based expert system for fault diagnosis and load scheduling. It is questionable whether current generation expert system technology is applicable for power system management in space. The objective of the ADEPTS (ADvanced Electrical Power management Techniques for Space systems) is to study new techniques for power management automation. These techniques involve integrating current expert system technology with that of parallel and distributed computing, as well as a distributed, object-oriented approach to software design. The focus of the current study is the integration of new procedures for automatically planning and scheduling loads with procedures for performing fault diagnosis and control. The objective is the concurrent execution of both sets of tasks on separate transputer processors, thus adding parallelism to the overall management process.

Application of fuzzy fault tree analysis based on modified fuzzy AHP and fuzzy TOPSIS for fire and explosion in the process industry.

PubMed

Yazdi, Mohammad; Korhan, Orhan; Daneshvar, Sahand

2018-05-09

This study aimed at establishing fault tree analysis (FTA) using expert opinion to compute the probability of an event. To find the probability of the top event (TE), all probabilities of the basic events (BEs) should be available when the FTA is drawn. In this case, employing expert judgment can be used as an alternative to failure data in an awkward situation. The fuzzy analytical hierarchy process as a standard technique is used to give a specific weight to each expert, and fuzzy set theory is engaged for aggregating expert opinion. In this regard, the probability of BEs will be computed and, consequently, the probability of the TE obtained using Boolean algebra. Additionally, to reduce the probability of the TE in terms of three parameters (safety consequences, cost and benefit), the importance measurement technique and modified TOPSIS was employed. The effectiveness of the proposed approach is demonstrated with a real-life case study.

Identification and assessment of professional competencies for implementation of nanotechnology in engineering education

NASA Astrophysics Data System (ADS)

Jean, Ming-Der; Jiang, Ji-Bin; Chien, Jia-Yi

2017-11-01

The purpose of this study was to construct the indicators of professional competencies of the nanotechnology-based sputtering system industry based on industry requirements and analyse the core competencies of the industry for promoting the human resource of physical vapour deposition technology. The document analysis, expert interview, and Delphi technique surveys were considered and the survey items with 32 items divided into 7 domains were selected according to consensus opinions of 10 experts by the Delphi survey technique. Through three questionnaire surveys' analysis, the professional competence scales for the K-S tests showed a good internal consistency. The findings of this study provide guidelines for professional competence for nanotechnology-based sputtering technology by applying surface heat-treatment industry. These guidelines can also reveal the practical competency requirements of nanotechnology-based sputtering technology to deal with any subsequent challenges, future developments, and invisible services for students in a technology institute programme.

Expert systems for automated maintenance of a Mars oxygen production system

NASA Technical Reports Server (NTRS)

Ash, Robert L.; Huang, Jen-Kuang; Ho, Ming-Tsang

1989-01-01

A prototype expert system was developed for maintaining autonomous operation of a Mars oxygen production system. Normal operation conditions and failure modes according to certain desired criteria are tested and identified. Several schemes for failure detection and isolation using forward chaining, backward chaining, knowledge-based and rule-based are devised to perform several housekeeping functions. These functions include self-health checkout, an emergency shut down program, fault detection and conventional control activities. An effort was made to derive the dynamic model of the system using Bond-Graph technique in order to develop the model-based failure detection and isolation scheme by estimation method. Finally, computer simulations and experimental results demonstrated the feasibility of the expert system and a preliminary reliability analysis for the oxygen production system is also provided.

Capital Expert System

NASA Astrophysics Data System (ADS)

Dowell, Laurie; Gary, Jack; Illingworth, Bill; Sargent, Tom

1987-05-01

Gathering information, necessary forms, and financial calculations needed to generate a "capital investment proposal" is an extremely complex and difficult process. The intent of the capital investment proposal is to ensure management that the proposed investment has been thoroughly investigated and will have a positive impact on corporate goals. Meeting this requirement typically takes four or five experts a total of 12 hours to generate a "Capital Package." A Capital Expert System was therefore developed using "Personal Consultant." The completed system is hybrid and as such does not depend solely on rules but incorporates several different software packages that communicate through variables and functions passed from one to another. This paper describes the use of expert system techniques, methodology in building the knowledge base, contexts, LISP functions, data base, and special challenges that had to be overcome to create this system. The Capital Expert System is the successful result of a unique integration of artificial intelligence with business accounting, financial forms generation, and investment proposal expertise.

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.

Expert Opinion Is Necessary: Delphi Panel Methodology Facilitates a Scientific Approach to Consensus.

PubMed

Hohmann, Erik; Brand, Jefferson C; Rossi, Michael J; Lubowitz, James H

2018-02-01

Our current trend and focus on evidence-based medicine is biased in favor of randomized controlled trials, which are ranked highest in the hierarchy of evidence while devaluing expert opinion, which is ranked lowest in the hierarchy. However, randomized controlled trials have weaknesses as well as strengths, and no research method is flawless. Moreover, stringent application of scientific research techniques, such as the Delphi Panel methodology, allows survey of experts in a high quality and scientific manner. Level V evidence (expert opinion) remains a necessary component in the armamentarium used to determine the answer to a clinical question. Copyright © 2017 Arthroscopy Association of North America. Published by Elsevier Inc. All rights reserved.

[Environmental protection techniques used in the federal state of Baden-Württemberg in Germany].

PubMed

Vasilić, Zelimira

2006-09-01

Within the framework of the programme "Partnership for Sustainable Development" The Ministry of Environment of the German Federal State of Baden-Württemberg has come up with a project "Study Visit--Environmental Protection Techniques". It was intended as a three-week study visit for environmental protection experts from Central and Eastern European Countries (CEEC) to learn about the environmental protection techniques used in this federal state. Visits were paid to companies producing, applying or installing plants based on the state-of-the-art environmental protection techniques. The project started in 2005 and will last five years. The first visit to Baden-Württemberg was scheduled for 25 September-14 October 2005 for 12 experts from 12 countries: Bulgaria, Croatia, Cyprus, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia and Ukraine.

Beyond New and Appropriate: Who Decides What Is Creative?

ERIC Educational Resources Information Center

Kaufman, James C.; Baer, John

2012-01-01

The Consensual Assessment Technique (CAT) is a common creativity assessment. According to this technique, the best judges of creativity are qualified experts. Yet what does it mean to be an expert in a domain? What level of expertise is needed to rate creativity? This article reviews the literature on novice, expert, and quasi-expert creativity…

Rating scale for the assessment of competence in ultrasound-guided peripheral vascular access - a Delphi Consensus Study.

PubMed

Primdahl, Stine C; Todsen, Tobias; Clemmesen, Louise; Knudsen, Lars; Weile, Jesper

2016-09-21

Peripheral vascular access is vital for treatment and diagnostics of hospitalized patients. Ultrasound-guided vascular access (UGVA) is superior to the landmark technique. To ensure competence-based education, an assessment tool of UGVA competence is needed. We aimed to develop a global rating scale (RS) for assessment of UGVA competence based on opinions on the content from ultrasound experts in a modified Delphi consensus study. We included experts from anesthesiology, emergency medicine and radiology across university hospitals in Denmark. Nine elements were drafted based on existing literature and recommendations from international societies. In a multi-round survey, the experts rated the elements on a five-point Likert scale according to importance, and suggested missing elements. The final Delphi round occurred when >80% of the experts rated all elements ≥4 on the Likert scale. Sixteen experts consented to participate in the study, one withdrew consent prior to the first Delphi round, and 14 completed all three Delphi rounds. In the first Delphi round the experts excluded one element from the scale and changed the content of two elements. In the second Delphi round, the experts excluded one element from the scale. In the third Delphi round, consensus was obtained on the eight elements: preparation of utensils, ergonomics, preparation of the ultrasound device, identification of blood vessels, anatomy, hygiene, coordination of the needle, and completion of the procedure. We developed an RS for assessment of UGVA competence based on opinions of ultrasound experts through a modified Delphi consensus study.

TES: A modular systems approach to expert system development for real-time space applications

NASA Technical Reports Server (NTRS)

Cacace, Ralph; England, Brenda

1988-01-01

A major goal of the Space Station era is to reduce reliance on support from ground based experts. The development of software programs using expert systems technology is one means of reaching this goal without requiring crew members to become intimately familiar with the many complex spacecraft subsystems. Development of an expert systems program requires a validation of the software with actual flight hardware. By combining accurate hardware and software modelling techniques with a modular systems approach to expert systems development, the validation of these software programs can be successfully completed with minimum risk and effort. The TIMES Expert System (TES) is an application that monitors and evaluates real time data to perform fault detection and fault isolation tasks as they would otherwise be carried out by a knowledgeable designer. The development process and primary features of TES, a modular systems approach, and the lessons learned are discussed.

Knowledge based systems: A preliminary survey of selected issues and techniques

NASA Technical Reports Server (NTRS)

Dominick, Wayne D. (Editor); Kavi, Srinu

1984-01-01

It is only recently that research in Artificial Intelligence (AI) is accomplishing practical results. Most of these results can be attributed to the design and use of expert systems (or Knowledge-Based Systems, KBS) - problem-solving computer programs that can reach a level of performance comparable to that of a human expert in some specialized problem domain. But many computer systems designed to see images, hear sounds, and recognize speech are still in a fairly early stage of development. In this report, a preliminary survey of recent work in the KBS is reported, explaining KBS concepts and issues and techniques used to construct them. Application considerations to construct the KBS and potential KBS research areas are identified. A case study (MYCIN) of a KBS is also provided.

Gold-standard for computer-assisted morphological sperm analysis.

PubMed

Chang, Violeta; Garcia, Alejandra; Hitschfeld, Nancy; Härtel, Steffen

2017-04-01

Published algorithms for classification of human sperm heads are based on relatively small image databases that are not open to the public, and thus no direct comparison is available for competing methods. We describe a gold-standard for morphological sperm analysis (SCIAN-MorphoSpermGS), a dataset of sperm head images with expert-classification labels in one of the following classes: normal, tapered, pyriform, small or amorphous. This gold-standard is for evaluating and comparing known techniques and future improvements to present approaches for classification of human sperm heads for semen analysis. Although this paper does not provide a computational tool for morphological sperm analysis, we present a set of experiments for comparing sperm head description and classification common techniques. This classification base-line is aimed to be used as a reference for future improvements to present approaches for human sperm head classification. The gold-standard provides a label for each sperm head, which is achieved by majority voting among experts. The classification base-line compares four supervised learning methods (1- Nearest Neighbor, naive Bayes, decision trees and Support Vector Machine (SVM)) and three shape-based descriptors (Hu moments, Zernike moments and Fourier descriptors), reporting the accuracy and the true positive rate for each experiment. We used Fleiss' Kappa Coefficient to evaluate the inter-expert agreement and Fisher's exact test for inter-expert variability and statistical significant differences between descriptors and learning techniques. Our results confirm the high degree of inter-expert variability in the morphological sperm analysis. Regarding the classification base line, we show that none of the standard descriptors or classification approaches is best suitable for tackling the problem of sperm head classification. We discovered that the correct classification rate was highly variable when trying to discriminate among non-normal sperm heads. By using the Fourier descriptor and SVM, we achieved the best mean correct classification: only 49%. We conclude that the SCIAN-MorphoSpermGS will provide a standard tool for evaluation of characterization and classification approaches for human sperm heads. Indeed, there is a clear need for a specific shape-based descriptor for human sperm heads and a specific classification approach to tackle the problem of high variability within subcategories of abnormal sperm cells. Copyright © 2017 Elsevier Ltd. 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.

Adaptive neuro-fuzzy and expert systems for power quality analysis and prediction of abnormal operation

NASA Astrophysics Data System (ADS)

Ibrahim, Wael Refaat Anis

The present research involves the development of several fuzzy expert systems for power quality analysis and diagnosis. Intelligent systems for the prediction of abnormal system operation were also developed. The performance of all intelligent modules developed was either enhanced or completely produced through adaptive fuzzy learning techniques. Neuro-fuzzy learning is the main adaptive technique utilized. The work presents a novel approach to the interpretation of power quality from the perspective of the continuous operation of a single system. The research includes an extensive literature review pertaining to the applications of intelligent systems to power quality analysis. Basic definitions and signature events related to power quality are introduced. In addition, detailed discussions of various artificial intelligence paradigms as well as wavelet theory are included. A fuzzy-based intelligent system capable of identifying normal from abnormal operation for a given system was developed. Adaptive neuro-fuzzy learning was applied to enhance its performance. A group of fuzzy expert systems that could perform full operational diagnosis were also developed successfully. The developed systems were applied to the operational diagnosis of 3-phase induction motors and rectifier bridges. A novel approach for learning power quality waveforms and trends was developed. The technique, which is adaptive neuro fuzzy-based, learned, compressed, and stored the waveform data. The new technique was successfully tested using a wide variety of power quality signature waveforms, and using real site data. The trend-learning technique was incorporated into a fuzzy expert system that was designed to predict abnormal operation of a monitored system. The intelligent system learns and stores, in compressed format, trends leading to abnormal operation. The system then compares incoming data to the retained trends continuously. If the incoming data matches any of the learned trends, an alarm is instigated predicting the advent of system abnormal operation. The incoming data could be compared to previous trends as well as matched to trends developed through computer simulations and stored using fuzzy learning.

Adaptive neural network/expert system that learns fault diagnosis for different structures

NASA Astrophysics Data System (ADS)

Simon, Solomon H.

1992-08-01

Corporations need better real-time monitoring and control systems to improve productivity by watching quality and increasing production flexibility. The innovative technology to achieve this goal is evolving in the form artificial intelligence and neural networks applied to sensor processing, fusion, and interpretation. By using these advanced Al techniques, we can leverage existing systems and add value to conventional techniques. Neural networks and knowledge-based expert systems can be combined into intelligent sensor systems which provide real-time monitoring, control, evaluation, and fault diagnosis for production systems. Neural network-based intelligent sensor systems are more reliable because they can provide continuous, non-destructive monitoring and inspection. Use of neural networks can result in sensor fusion and the ability to model highly, non-linear systems. Improved models can provide a foundation for more accurate performance parameters and predictions. We discuss a research software/hardware prototype which integrates neural networks, expert systems, and sensor technologies and which can adapt across a variety of structures to perform fault diagnosis. The flexibility and adaptability of the prototype in learning two structures is presented. Potential applications are discussed.

A methodology for uncertainty quantification in quantitative technology valuation based on expert elicitation

NASA Astrophysics Data System (ADS)

Akram, Muhammad Farooq Bin

The management of technology portfolios is an important element of aerospace system design. New technologies are often applied to new product designs to ensure their competitiveness at the time they are introduced to market. The future performance of yet-to- be designed components is inherently uncertain, necessitating subject matter expert knowledge, statistical methods and financial forecasting. Estimates of the appropriate parameter settings often come from disciplinary experts, who may disagree with each other because of varying experience and background. Due to inherent uncertain nature of expert elicitation in technology valuation process, appropriate uncertainty quantification and propagation is very critical. The uncertainty in defining the impact of an input on performance parameters of a system makes it difficult to use traditional probability theory. Often the available information is not enough to assign the appropriate probability distributions to uncertain inputs. Another problem faced during technology elicitation pertains to technology interactions in a portfolio. When multiple technologies are applied simultaneously on a system, often their cumulative impact is non-linear. Current methods assume that technologies are either incompatible or linearly independent. It is observed that in case of lack of knowledge about the problem, epistemic uncertainty is the most suitable representation of the process. It reduces the number of assumptions during the elicitation process, when experts are forced to assign probability distributions to their opinions without sufficient knowledge. Epistemic uncertainty can be quantified by many techniques. In present research it is proposed that interval analysis and Dempster-Shafer theory of evidence are better suited for quantification of epistemic uncertainty in technology valuation process. Proposed technique seeks to offset some of the problems faced by using deterministic or traditional probabilistic approaches for uncertainty propagation. Non-linear behavior in technology interactions is captured through expert elicitation based technology synergy matrices (TSM). Proposed TSMs increase the fidelity of current technology forecasting methods by including higher order technology interactions. A test case for quantification of epistemic uncertainty on a large scale problem of combined cycle power generation system was selected. A detailed multidisciplinary modeling and simulation environment was adopted for this problem. Results have shown that evidence theory based technique provides more insight on the uncertainties arising from incomplete information or lack of knowledge as compared to deterministic or probability theory methods. Margin analysis was also carried out for both the techniques. A detailed description of TSMs and their usage in conjunction with technology impact matrices and technology compatibility matrices is discussed. Various combination methods are also proposed for higher order interactions, which can be applied according to the expert opinion or historical data. The introduction of technology synergy matrix enabled capturing the higher order technology interactions, and improvement in predicted system performance.

Flow-Visualization Techniques Used at High Speed by Configuration Aerodynamics Wind-Tunnel-Test Team

NASA Technical Reports Server (NTRS)

Lamar, John E. (Editor)

2001-01-01

This paper summarizes a variety of optically based flow-visualization techniques used for high-speed research by the Configuration Aerodynamics Wind-Tunnel Test Team of the High-Speed Research Program during its tenure. The work of other national experts is included for completeness. Details of each technique with applications and status in various national wind tunnels are given.

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

PubMed

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

2018-01-01

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

An expert system based software sizing tool, phase 2

NASA Technical Reports Server (NTRS)

Friedlander, David

1990-01-01

A software tool was developed for predicting the size of a future computer program at an early stage in its development. The system is intended to enable a user who is not expert in Software Engineering to estimate software size in lines of source code with an accuracy similar to that of an expert, based on the program's functional specifications. The project was planned as a knowledge based system with a field prototype as the goal of Phase 2 and a commercial system planned for Phase 3. The researchers used techniques from Artificial Intelligence and knowledge from human experts and existing software from NASA's COSMIC database. They devised a classification scheme for the software specifications, and a small set of generic software components that represent complexity and apply to large classes of programs. The specifications are converted to generic components by a set of rules and the generic components are input to a nonlinear sizing function which makes the final prediction. The system developed for this project predicted code sizes from the database with a bias factor of 1.06 and a fluctuation factor of 1.77, an accuracy similar to that of human experts but without their significant optimistic bias.

Design and implementation of expert decision system in Yellow River Irrigation

NASA Astrophysics Data System (ADS)

Fuping, Wang; Bingbing, Lei; Jie, Pan

2018-03-01

How to make full use of water resources in the Yellow River irrigation is a problem needed to be solved urgently. On account of the different irrigation strategies in various growth stages of wheat, this paper proposes a novel irrigation expert decision system basing on fuzzy control technique. According to the control experience, expert knowledge and MATLAB simulation optimization, we obtain the irrigation fuzzy control table stored in the computer memory. The controlling irrigation is accomplished by reading the data from fuzzy control table. The experimental results show that the expert system can be used in the production of wheat to achieve timely and appropriate irrigation, and ensure that wheat growth cycle is always in the best growth environment.

Expert system verification and validation study. Phase 2: Requirements Identification. Delivery 2: Current requirements applicability

NASA Technical Reports Server (NTRS)

1991-01-01

The second phase of a task is described which has the ultimate purpose of ensuring that adequate Expert Systems (ESs) Verification and Validation (V and V) tools and techniques are available for Space Station Freedom Program Knowledge Based Systems development. The purpose of this phase is to recommend modifications to current software V and V requirements which will extend the applicability of the requirements to NASA ESs.

New quality assurance program integrating "modern radiotherapy" within the German Hodgkin Study Group.

PubMed

Kriz, J; Baues, C; Engenhart-Cabillic, R; Haverkamp, U; Herfarth, K; Lukas, P; Schmidberger, H; Marnitz-Schulze, S; Fuchs, M; Engert, A; Eich, H T

2017-02-01

Field design changed substantially from extended-field RT (EF-RT) to involved-field RT (IF-RT) and now to involved-node RT (IN-RT) and involved-site RT (IS-RT) as well as treatment techniques in radiotherapy (RT) of Hodgkin's lymphoma (HL). The purpose of this article is to demonstrate the establishment of a quality assurance program (QAP) including modern RT techniques and field designs within the German Hodgkin Study Group (GHSG). In the era of modern conformal RT, this QAP had to be fundamentally adapted and a new evaluation process has been intensively discussed by the radiotherapeutic expert panel of the GHSG. The expert panel developed guidelines and criteria to analyse "modern" field designs and treatment techniques. This work is based on a dataset of 11 patients treated within the sixth study generation (HD16-17). To develop a QAP of "modern RT", the expert panel defined criteria for analysing current RT procedures. The consensus of a modified QAP in ongoing and future trials is presented. With this schedule, the QAP of the GHSG could serve as a model for other study groups.

Automated eddy current analysis of materials

NASA Technical Reports Server (NTRS)

Workman, Gary L.

1990-01-01

This research effort focused on the use of eddy current techniques for characterizing flaws in graphite-based filament-wound cylindrical structures. A major emphasis was on incorporating artificial intelligence techniques into the signal analysis portion of the inspection process. Developing an eddy current scanning system using a commercial robot for inspecting graphite structures (and others) has been a goal in the overall concept and is essential for the final implementation for expert system interpretation. Manual scans, as performed in the preliminary work here, do not provide sufficiently reproducible eddy current signatures to be easily built into a real time expert system. The expert systems approach to eddy current signal analysis requires that a suitable knowledge base exist in which correct decisions as to the nature of the flaw can be performed. In eddy current or any other expert systems used to analyze signals in real time in a production environment, it is important to simplify computational procedures as much as possible. For that reason, we have chosen to use the measured resistance and reactance values for the preliminary aspects of this work. A simple computation, such as phase angle of the signal, is certainly within the real time processing capability of the computer system. In the work described here, there is a balance between physical measurements and finite element calculations of those measurements. The goal is to evolve into the most cost effective procedures for maintaining the correctness of the knowledge base.

Ecosystem service valuations of mangrove ecosystems to inform decision making and future valuation exercises.

PubMed

Mukherjee, Nibedita; Sutherland, William J; Dicks, Lynn; Hugé, Jean; Koedam, Nico; Dahdouh-Guebas, Farid

2014-01-01

The valuation of ecosystem services is a complex process as it includes several dimensions (ecological, socio-cultural and economic) and not all of these can be quantified in monetary units. The aim of this paper is to conduct an ecosystem services valuation study for mangroves ecosystems, the results of which can be used to inform governance and management of mangroves. We used an expert-based participatory approach (the Delphi technique) to identify, categorize and rank the various ecosystem services provided by mangrove ecosystems at a global scale. Subsequently we looked for evidence in the existing ecosystem services literature for monetary valuations of these ecosystem service categories throughout the biogeographic distribution of mangroves. We then compared the relative ranking of ecosystem service categories between the monetary valuations and the expert based analysis. The experts identified 16 ecosystem service categories, six of which are not adequately represented in the literature. There was no significant correlation between the expert based valuation (the Delphi technique) and the economic valuation, indicating that the scope of valuation of ecosystem services needs to be broadened. Acknowledging this diversity in different valuation approaches, and developing methodological frameworks that foster the pluralism of values in ecosystem services research, are crucial for maintaining the credibility of ecosystem services valuation. To conclude, we use the findings of our dual approach to valuation to make recommendations on how to assess and manage the ecosystem services provided by mangrove ecosystems.

Ecosystem Service Valuations of Mangrove Ecosystems to Inform Decision Making and Future Valuation Exercises

PubMed Central

Mukherjee, Nibedita; Sutherland, William J.; Dicks, Lynn; Hugé, Jean; Koedam, Nico; Dahdouh-Guebas, Farid

2014-01-01

The valuation of ecosystem services is a complex process as it includes several dimensions (ecological, socio-cultural and economic) and not all of these can be quantified in monetary units. The aim of this paper is to conduct an ecosystem services valuation study for mangroves ecosystems, the results of which can be used to inform governance and management of mangroves. We used an expert-based participatory approach (the Delphi technique) to identify, categorize and rank the various ecosystem services provided by mangrove ecosystems at a global scale. Subsequently we looked for evidence in the existing ecosystem services literature for monetary valuations of these ecosystem service categories throughout the biogeographic distribution of mangroves. We then compared the relative ranking of ecosystem service categories between the monetary valuations and the expert based analysis. The experts identified 16 ecosystem service categories, six of which are not adequately represented in the literature. There was no significant correlation between the expert based valuation (the Delphi technique) and the economic valuation, indicating that the scope of valuation of ecosystem services needs to be broadened. Acknowledging this diversity in different valuation approaches, and developing methodological frameworks that foster the pluralism of values in ecosystem services research, are crucial for maintaining the credibility of ecosystem services valuation. To conclude, we use the findings of our dual approach to valuation to make recommendations on how to assess and manage the ecosystem services provided by mangrove ecosystems. PMID:25243852

[Applying the Modified Delphi Technique to Develop the Role of HIV Case Managers and Essential Nursing Competencies in HIV Care].

PubMed

Ko, Nai-Ying; Hsieh, Chia-Yin; Chen, Yen-Chin; Tsai, Chen-Hsi; Liu, Hsiao-Ying; Liu, Li-Fang

2015-08-01

Since 2005, the Taiwan Centers for Disease Control (Taiwan CDC) initiated an HIV case management program in AIDS-designated hospitals to provide integrative services and risk-reduction counseling for HIV-infected individuals. In light of the increasingly complex and highly specialized nature of clinical care, expanding and improving competency-based professional education is important to enhance the quality of HIV/AIDS care. The aim of this study was to develop the essential competency framework for HIV care for HIV case managers in Taiwan. We reviewed essential competencies of HIV care from Canada, the United Kingdom, and several African countries and devised descriptions of the roles of case managers and of the associated core competencies for HIV care in Taiwan. The modified Delphi technique was used to evaluate the draft framework of these roles and core competencies. A total of 15 HIV care experts were invited to join the expert panel to review and rank the draft framework. The final framework consisted of 7 roles and 27 competencies for HIV case managers. In Round 1, only 3 items did not receive consensus approval from the experts. After modification based on opinions of the experts, 7 roles and 27 competencies received 97.06% consensus approval in Round 2 and were organized into the final framework for HIV case managers. These roles and associated core competencies were: HIV Care Expert (9 competencies), Communicator (1 competency), Collaborator (4 competencies), Navigator (2 competencies), Manager (4 competencies), Advocate (2 competencies), and Professional (5 competencies). The authors developed an essential competency framework for HIV care using the consensus of a multidisciplinary expert panel. Curriculum developers and advanced nurses and practitioners may use this framework to support developments and to ensure a high quality of HIV care.

Defining the Bobath concept using the Delphi technique.

PubMed

Raine, Sue

2006-03-01

The Bobath concept, based on the work of Berta and Karel Bobath, offers therapists working in the field of neurological rehabilitation a framework for their clinical interventions. It is the most commonly used approach in the UK. Although they recognize that over the last half-century the concept has undergone considerable developments, proponents of the Bobath concept have been criticized for not publishing these changes. The aim of the present study was to use the Delphi technique to enable experts in the field to define the current Bobath concept. A four-round Delphi study design was used. The sample included all members of the British Bobath Tutor's Association, who are considered experts in the field. Initial statements were identified from the literature, with respondents generating additional statements during the study. The level of agreement was determined using a five-point Likert scale. The respondents were then provided with feedback on group opinions and given an opportunity to re-rate each statement. The level of group consensus was set at 80%. Fifteen experts took part. The response rate was 85% in the first round, and 93% in each subsequent round. Ten statements from the literature were rated with a further 12 generated by the experts. Thirteen statements achieved consensus for agreement and seven for disagreement. The Delphi study was an effective research tool, maintaining anonymity of responses and exploring expert opinions on the Bobath concept. The experts stated that Bobath's work has been misunderstood if it is considered as the inhibition of spasticity and the facilitation of normal movement, as described in some literature. They agreed that the Bobath concept was developed by the Bobaths as a living concept, understanding that as therapists' knowledge base grows their view of treatment broadens.

Tuberculosis-Diagnostic Expert System: an architecture for translating patients information from the web for use in tuberculosis diagnosis.

PubMed

Osamor, Victor C; Azeta, Ambrose A; Ajulo, Oluseyi O

2014-12-01

Over 1.5-2 million tuberculosis deaths occur annually. Medical professionals are faced with a lot of challenges in delivering good health-care with unassisted automation in hospitals where there are several patients who need the doctor's attention. To automate the pre-laboratory screening process against tuberculosis infection to aid diagnosis and make it fast and accessible to the public via the Internet. The expert system we have built is designed to also take care of people who do not have access to medical experts, but would want to check their medical status. A rule-based approach has been used, and unified modeling language and the client-server architecture technique were applied to model the system and to develop it as a web-based expert system for tuberculosis diagnosis. Algorithmic rules in the Tuberculosis-Diagnosis Expert System necessitate decision coverage where tuberculosis is either suspected or not suspected. The architecture consists of a rule base, knowledge base, and patient database. These units interact with the inference engine, which receives patient' data through the Internet via a user interface. We present the architecture of the Tuberculosis-Diagnosis Expert System and its implementation. We evaluated it for usability to determine the level of effectiveness, efficiency and user satisfaction. The result of the usability evaluation reveals that the system has a usability of 4.08 out of a scale of 5. This is an indication of a more-than-average system performance. Several existing expert systems have been developed for the purpose of supporting different medical diagnoses, but none is designed to translate tuberculosis patients' symptomatic data for online pre-laboratory screening. Our Tuberculosis-Diagnosis Expert System is an effective solution for the implementation of the needed web-based expert system diagnosis. © The Author(s) 2013.

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.

Expert models and modeling processes associated with a computer-modeling tool

NASA Astrophysics Data System (ADS)

Zhang, Baohui; Liu, Xiufeng; Krajcik, Joseph S.

2006-07-01

Holding the premise that the development of expertise is a continuous process, this study concerns expert models and modeling processes associated with a modeling tool called Model-It. Five advanced Ph.D. students in environmental engineering and public health used Model-It to create and test models of water quality. Using think aloud technique and video recording, we captured their computer screen modeling activities and thinking processes. We also interviewed them the day following their modeling sessions to further probe the rationale of their modeling practices. We analyzed both the audio-video transcripts and the experts' models. We found the experts' modeling processes followed the linear sequence built in the modeling program with few instances of moving back and forth. They specified their goals up front and spent a long time thinking through an entire model before acting. They specified relationships with accurate and convincing evidence. Factors (i.e., variables) in expert models were clustered, and represented by specialized technical terms. Based on the above findings, we made suggestions for improving model-based science teaching and learning using Model-It.

Factors Affecting the Location of Road Emergency Bases in Iran Using Analytical Hierarchy Process (AHP).

PubMed

Bahadori, Mohammadkarim; Hajebrahimi, Ahmad; Alimohammadzadeh, Khalil; Ravangard, Ramin; Hosseini, Seyed Mojtaba

2017-10-01

To identify and prioritize factors affecting the location of road emergency bases in Iran using Analytical Hierarchy Process (AHP). This was a mixed method (quantitative-qualitative) study conducted in 2016. The participants in this study included the professionals and experts in the field of pre-hospital and road emergency services issues working in the Health Deputy of Iran Ministry of Health and Medical Education, which were selected using purposive sampling method. In this study at first, the factors affecting the location of road emergency bases in Iran were identified using literature review and conducting interviews with the experts. Then, the identified factors were scored and prioritized using the studied professionals and experts' viewpoints through using the analytic hierarchy process (AHP) technique and its related pair-wise questionnaire. The collected data were analyzed using MAXQDA 10.0 software to analyze the answers given to the open question and Expert Choice 10.0 software to determine the weights and priorities of the identified factors. The results showed that eight factors were effective in locating the road emergency bases in Iran from the viewpoints of the studied professionals and experts in the field of pre-hospital and road emergency services issues, including respectively distance from the next base, region population, topography and geographical situation of the region, the volume of road traffic, the existence of amenities such as water, electricity, gas, etc. and proximity to the village, accident-prone sites, University ownership of the base site, and proximity to toll-house. Among the eight factors which were effective in locating the road emergency bases from the studied professionals and experts' perspectives, "distance from the next base" and "region population" were respectively the most important ones which had great differences with other factors.

VEG: An intelligent workbench for analysing spectral reflectance data

NASA Technical Reports Server (NTRS)

Harrison, P. Ann; Harrison, Patrick R.; Kimes, Daniel S.

1994-01-01

An Intelligent Workbench (VEG) was developed for the systematic study of remotely sensed optical data from vegetation. A goal of the remote sensing community is to infer the physical and biological properties of vegetation cover (e.g. cover type, hemispherical reflectance, ground cover, leaf area index, biomass, and photosynthetic capacity) using directional spectral data. VEG collects together, in a common format, techniques previously available from many different sources in a variety of formats. The decision as to when a particular technique should be applied is nonalgorithmic and requires expert knowledge. VEG has codified this expert knowledge into a rule-based decision component for determining which technique to use. VEG provides a comprehensive interface that makes applying the techniques simple and aids a researcher in developing and testing new techniques. VEG also provides a classification algorithm that can learn new classes of surface features. The learning system uses the database of historical cover types to learn class descriptions of one or more classes of cover types.

Ranking experts' preferences regarding measures and methods of assessment of welfare in dairy herds using Adaptive Conjoint Analysis.

PubMed

Lievaart, J J; Noordhuizen, J P T M

2011-07-01

Welfare in dairy herds can be addressed using different concepts. The difficulty is to extract which measures are the most important to practically address welfare at the herd level and the methods to assess traits considered most important. Therefore, the preferences of 24 acknowledged European welfare experts were ranked regarding 70 measures suitable to assess dairy cattle welfare at herd level using the Adaptive Conjoint Analysis (ACA; Sawtooth Software, Inc., Sequim, WA) technique. The experts were selected on the basis of 3 criteria: at least 5 yr experience in animal welfare research; recent scientific publications in the field of animal welfare; and, at the most, 3 animal species including dairy cattle as their field of expertise. The 70 traits were ranked by using the median ACA questionnaire utility scores and the range between the answers of the 24 experts. A high utility score with a low range between the answers of the experts was considered as suitable to assess welfare at farm level. Measures meeting these criteria were prevalence of lameness cases (107.3±11.7), competition for feed and water (96.4±13.9), and number of freestalls per 10 cows (84.8±13.3). Based on the utility score alone, these former measures were replaced by stereotypic behavior (111.7±17.1), prevalence of lameness cases (107.3±11.7), body condition score (108.0±18.9), and hock lesions (104.7±16.1). Subsequently, to demonstrate that the ACA technique can be used to rank either well-known or inconclusive methods of assessment, the methods for the traits lameness cases and the hygiene of the calving pen were ranked using another 2 ACA questionnaires. The results are based on the opinions of selected, internationally acknowledged dairy cattle welfare experts within the European Union. In the future, other parties like dairy farmers and farmers' organization should be included to achieve consensus about the most suitable traits applicable in practice. The currently investigated traits do not always apply to all dairy husbandry systems across the world, but are based on a system that includes indoor housing during winter. It is concluded that ACA is a useful technique to rank the different scientific opinions of experts regarding suitable traits and methods of assessment of dairy cattle at the herd level. Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

A Data-Driven Solution for Performance Improvement

NASA Technical Reports Server (NTRS)

2002-01-01

Marketed as the "Software of the Future," Optimal Engineering Systems P.I. EXPERT(TM) technology offers statistical process control and optimization techniques that are critical to businesses looking to restructure or accelerate operations in order to gain a competitive edge. Kennedy Space Center granted Optimal Engineering Systems the funding and aid necessary to develop a prototype of the process monitoring and improvement software. Completion of this prototype demonstrated that it was possible to integrate traditional statistical quality assurance tools with robust optimization techniques in a user- friendly format that is visually compelling. Using an expert system knowledge base, the software allows the user to determine objectives, capture constraints and out-of-control processes, predict results, and compute optimal process settings.

Expert system verification and validation study. Phase 2: Requirements identification. Delivery 1: Updated survey report

NASA Technical Reports Server (NTRS)

1990-01-01

The purpose is to report the state-of-the-practice in Verification and Validation (V and V) of Expert Systems (ESs) on current NASA and Industry applications. This is the first task of a series which has the ultimate purpose of ensuring that adequate ES V and V tools and techniques are available for Space Station Knowledge Based Systems development. The strategy for determining the state-of-the-practice is to check how well each of the known ES V and V issues are being addressed and to what extent they have impacted the development of Expert Systems.

Which Behavior Change Techniques May Help Waterpipe Smokers to Quit? An Expert Consensus Using a Modified Delphi Technique.

PubMed

O'Neill, Nancy; Dogar, Omara; Jawad, Mohammed; Kellar, Ian; Kanaan, Mona; Siddiqi, Kamran

2018-01-05

Waterpipe smoking is addictive and harmful. The determinants of waterpipe smoking may differ from those of cigarette smoking; therefore, behavioral approaches to support quitting may also differ between these two tobacco products. While some evidence exists on effective behavioral change techniques (BCTs) to facilitate cigarette smoking cessation, there is little research on waterpipe smoking cessation. Twenty-four experts were selected from the author lists of peer-reviewed, randomized controlled trials on waterpipe smoking cessation. They were invited to two rounds of a consensus development exercise using modified Delphi technique. Experts ranked 55 BCTs categorized further into those that promote; "awareness of harms of waterpipe smoking and advantages of quitting" (14), "preparation and planning to quit" (29), and "relapse prevention and sustaining an ex-smoker identity" (12) on their potential effectiveness. Kendall's W statistics was used to assess agreement. Fifteen experts responded in round 1 and 14 completed both rounds. A strong consensus was achieved for BCTs that help in "relapse prevention and sustaining ex-smoker identity" (w = 0.7; p < .001) and a moderate for those that promote "awareness of harms of waterpipe smoking and advantages of quitting" (w = 0.6; p < .001) and "preparation and planning to quit" (w = 0.6; p < .001). Providing information on the consequences of waterpipe smoking and its cessation, assessing readiness and ability to quit, and making people aware of the withdrawal symptoms, were the three highest-ranking BCTs. Based on expert consensus, an inventory of BCTs ordered for their potential effectiveness can be useful for health professionals offering cessation support to waterpipe smokers. Waterpipe smoking is addictive, harmful, and gaining global popularity, particularly among youth. An expert consensus on behavior change techniques, likely to be effective in supporting waterpipe smokers to quit, has practice and research implications. Smoking cessation advisors can use these techniques to counsel waterpipe smokers who wish to quit. Behavioral and public health scientists can also use these to develop and evaluate behavioral support interventions for this client group. © The Author(s) 2016. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Evidence flow graph methods for validation and verification of expert systems

NASA Technical Reports Server (NTRS)

Becker, Lee A.; Green, Peter G.; Bhatnagar, Jayant

1989-01-01

The results of an investigation into the use of evidence flow graph techniques for performing validation and verification of expert systems are given. A translator to convert horn-clause rule bases into evidence flow graphs, a simulation program, and methods of analysis were developed. These tools were then applied to a simple rule base which contained errors. It was found that the method was capable of identifying a variety of problems, for example that the order of presentation of input data or small changes in critical parameters could affect the output from a set of rules.

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

Computer-assisted expert case definition in electronic health records.

PubMed

Walker, Alexander M; Zhou, Xiaofeng; Ananthakrishnan, Ashwin N; Weiss, Lisa S; Shen, Rongjun; Sobel, Rachel E; Bate, Andrew; Reynolds, Robert F

2016-02-01

To describe how computer-assisted presentation of case data can lead experts to infer machine-implementable rules for case definition in electronic health records. As an illustration the technique has been applied to obtain a definition of acute liver dysfunction (ALD) in persons with inflammatory bowel disease (IBD). The technique consists of repeatedly sampling new batches of case candidates from an enriched pool of persons meeting presumed minimal inclusion criteria, classifying the candidates by a machine-implementable candidate rule and by a human expert, and then updating the rule so that it captures new distinctions introduced by the expert. Iteration continues until an update results in an acceptably small number of changes to form a final case definition. The technique was applied to structured data and terms derived by natural language processing from text records in 29,336 adults with IBD. Over three rounds the technique led to rules with increasing predictive value, as the experts identified exceptions, and increasing sensitivity, as the experts identified missing inclusion criteria. In the final rule inclusion and exclusion terms were often keyed to an ALD onset date. When compared against clinical review in an independent test round, the derived final case definition had a sensitivity of 92% and a positive predictive value of 79%. An iterative technique of machine-supported expert review can yield a case definition that accommodates available data, incorporates pre-existing medical knowledge, is transparent and is open to continuous improvement. The expert updates to rules may be informative in themselves. In this limited setting, the final case definition for ALD performed better than previous, published attempts using expert definitions. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Knowledge-based operation and management of communications systems

NASA Technical Reports Server (NTRS)

Heggestad, Harold M.

1988-01-01

Expert systems techniques are being applied in operation and control of the Defense Communications System (DCS), which has the mission of providing reliable worldwide voice, data and message services for U.S. forces and commands. Thousands of personnel operate DCS facilities, and many of their functions match the classical expert system scenario: complex, skill-intensive environments with a full spectrum of problems in training and retention, cost containment, modernization, and so on. Two of these functions are: (1) fault isolation and restoral of dedicated circuits at Tech Control Centers, and (2) network management for the Defense Switched Network (the modernized dial-up voice system currently replacing AUTOVON). An expert system for the first of these is deployed for evaluation purposes at Andrews Air Force Base, and plans are being made for procurement of operational systems. In the second area, knowledge obtained with a sophisticated simulator is being embedded in an expert system. The background, design and status of both projects are described.

Knowledge-based operation and management of communications systems

NASA Astrophysics Data System (ADS)

Heggestad, Harold M.

1988-11-01

Expert systems techniques are being applied in operation and control of the Defense Communications System (DCS), which has the mission of providing reliable worldwide voice, data and message services for U.S. forces and commands. Thousands of personnel operate DCS facilities, and many of their functions match the classical expert system scenario: complex, skill-intensive environments with a full spectrum of problems in training and retention, cost containment, modernization, and so on. Two of these functions are: (1) fault isolation and restoral of dedicated circuits at Tech Control Centers, and (2) network management for the Defense Switched Network (the modernized dial-up voice system currently replacing AUTOVON). An expert system for the first of these is deployed for evaluation purposes at Andrews Air Force Base, and plans are being made for procurement of operational systems. In the second area, knowledge obtained with a sophisticated simulator is being embedded in an expert system. The background, design and status of both projects are described.

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.

Determinants of adolescents' ineffective and improved coping with cyberbullying: a Delphi study.

PubMed

Jacobs, Niels C L; Dehue, Francine; Völlink, Trijntje; Lechner, Lilian

2014-06-01

The study's aim was to obtain an overview of all relevant variables involved in ineffective coping behavior and improvement in coping behavior as it pertains to cyberbullying among adolescents, in order to systematically develop a theory- and evidence-based intervention. This was done by means of a three round online Delphi study. First, 20 key experts listed possible relevant determinants. Next, 70 experts scored these determinants on their relevance and finally, experts rerated relevance of each determinant based on group median scores. The experts agreed that 115 items are relevant for ineffective (62) or improvement in (53) coping behavior. New found determinants were the extent to which one can adjust behavior upon feedback, impulsivity, self-confidence, communication style, personality, decision-making skills, conflict resolution skills, previous participation in personal resilience training, social relationships, rumors and self-disclosure. We conclude that the Delphi technique is useful in discovering new and relevant determinants of behavior. Copyright © 2014 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Translating expert system rules into Ada code with validation and verification

NASA Technical Reports Server (NTRS)

Becker, Lee; Duckworth, R. James; Green, Peter; Michalson, Bill; Gosselin, Dave; Nainani, Krishan; Pease, Adam

1991-01-01

The purpose of this ongoing research and development program is to develop software tools which enable the rapid development, upgrading, and maintenance of embedded real-time artificial intelligence systems. The goals of this phase of the research were to investigate the feasibility of developing software tools which automatically translate expert system rules into Ada code and develop methods for performing validation and verification testing of the resultant expert system. A prototype system was demonstrated which automatically translated rules from an Air Force expert system was demonstrated which detected errors in the execution of the resultant system. The method and prototype tools for converting AI representations into Ada code by converting the rules into Ada code modules and then linking them with an Activation Framework based run-time environment to form an executable load module are discussed. This method is based upon the use of Evidence Flow Graphs which are a data flow representation for intelligent systems. The development of prototype test generation and evaluation software which was used to test the resultant code is discussed. This testing was performed automatically using Monte-Carlo techniques based upon a constraint based description of the required performance for the system.

The effect of fidelity: how expert behavior changes in a virtual reality environment.

PubMed

Ioannou, Ioanna; Avery, Alex; Zhou, Yun; Szudek, Jacek; Kennedy, Gregor; O'Leary, Stephen

2014-09-01

We compare the behavior of expert surgeons operating on the "gold standard" of simulation-the cadaveric temporal bone-against a high-fidelity virtual reality (VR) simulation. We aim to determine whether expert behavior changes within the virtual environment and to understand how the fidelity of simulation affects users' behavior. Five expert otologists performed cortical mastoidectomy and cochleostomy on a human cadaveric temporal bone and a VR temporal bone simulator. Hand movement and video recordings were used to derive a range of measures, to facilitate an analysis of surgical technique, and to compare expert behavior between the cadaveric and simulator environments. Drilling time was similar across the two environments. Some measures such as total time and burr change count differed predictably due to the ease of switching burrs within the simulator. Surgical strokes were generally longer in distance and duration in VR, but these measures changed proportionally to cadaveric measures across the stages of the procedure. Stroke shape metrics differed, which was attributed to the modeling of burr behavior within the simulator. This will be corrected in future versions. Slight differences in drill interaction between a virtual environment and the real world can have measurable effects on surgical technique, particularly in terms of stroke length, duration, and curvature. It is important to understand these effects when designing and implementing surgical training programs based on VR simulation--and when improving the fidelity of VR simulators to facilitate use of a similar technique in both real and simulated situations. © 2014 The American Laryngological, Rhinological and Otological Society, Inc.

Intra- and inter-rater reliability of digital image analysis for skin color measurement

PubMed Central

Sommers, Marilyn; Beacham, Barbara; Baker, Rachel; Fargo, Jamison

2013-01-01

Background We determined the intra- and inter-rater reliability of data from digital image color analysis between an expert and novice analyst. Methods Following training, the expert and novice independently analyzed 210 randomly ordered images. Both analysts used Adobe® Photoshop lasso or color sampler tools based on the type of image file. After color correction with Pictocolor® in camera software, they recorded L*a*b* (L*=light/dark; a*=red/green; b*=yellow/blue) color values for all skin sites. We computed intra-rater and inter-rater agreement within anatomical region, color value (L*, a*, b*), and technique (lasso, color sampler) using a series of one-way intra-class correlation coefficients (ICCs). Results Results of ICCs for intra-rater agreement showed high levels of internal consistency reliability within each rater for the lasso technique (ICC ≥ 0.99) and somewhat lower, yet acceptable, level of agreement for the color sampler technique (ICC = 0.91 for expert, ICC = 0.81 for novice). Skin L*, skin b*, and labia L* values reached the highest level of agreement (ICC ≥ 0.92) and skin a*, labia b*, and vaginal wall b* were the lowest (ICC ≥ 0.64). Conclusion Data from novice analysts can achieve high levels of agreement with data from expert analysts with training and the use of a detailed, standard protocol. PMID:23551208

Intra- and inter-rater reliability of digital image analysis for skin color measurement.

PubMed

Sommers, Marilyn; Beacham, Barbara; Baker, Rachel; Fargo, Jamison

2013-11-01

We determined the intra- and inter-rater reliability of data from digital image color analysis between an expert and novice analyst. Following training, the expert and novice independently analyzed 210 randomly ordered images. Both analysts used Adobe(®) Photoshop lasso or color sampler tools based on the type of image file. After color correction with Pictocolor(®) in camera software, they recorded L*a*b* (L*=light/dark; a*=red/green; b*=yellow/blue) color values for all skin sites. We computed intra-rater and inter-rater agreement within anatomical region, color value (L*, a*, b*), and technique (lasso, color sampler) using a series of one-way intra-class correlation coefficients (ICCs). Results of ICCs for intra-rater agreement showed high levels of internal consistency reliability within each rater for the lasso technique (ICC ≥ 0.99) and somewhat lower, yet acceptable, level of agreement for the color sampler technique (ICC = 0.91 for expert, ICC = 0.81 for novice). Skin L*, skin b*, and labia L* values reached the highest level of agreement (ICC ≥ 0.92) and skin a*, labia b*, and vaginal wall b* were the lowest (ICC ≥ 0.64). Data from novice analysts can achieve high levels of agreement with data from expert analysts with training and the use of a detailed, standard protocol. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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 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

Expertise, Domains, and the Consensual Assessment Technique

ERIC Educational Resources Information Center

Kaufman, James C.; Baer, John; Cole, Jason C.

2009-01-01

The Consensual Assessment Technique (CAT) argues that the most valid judgments of the creativity are those of the combined opinions of experts in the field. Yet who exactly qualifies as an expert to evaluate a creative product such as a short story? This study examines both novice and expert judgments of student short fiction. Results indicate a…

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.

TDAS: The Thermal Expert System (TEXSYS) data acquisition system

NASA Technical Reports Server (NTRS)

Hack, Edmund C.; Healey, Kathleen J.

1987-01-01

As part of the NASA Systems Autonomy Demonstration Project, a thermal expert system (TEXSYS) is being developed. TEXSYS combines a fast real time control system, a sophisticated human interface for the user and several distinct artificial intelligence techniques in one system. TEXSYS is to provide real time control, operations advice and fault detection, isolation and recovery capabilities for the space station Thermal Test Bed (TTB). TEXSYS will be integrated with the TTB and act as an intelligent assistant to thermal engineers conducting TTB tests and experiments. The results are presented from connecting the real time controller to the knowledge based system thereby creating an integrated system. Special attention will be paid to the problem of filtering and interpreting the raw, real time data and placing the important values into the knowledge base of the expert system.

Management of cytotoxic extravasation - ASORS expert opinion for diagnosis, prevention and treatment.

PubMed

de Wit, Maike; Ortner, Petra; Lipp, Hans-Peter; Sehouli, Jalid; Untch, Michael; Ruhnke, Markus; Mayer-Steinacker, Regine; Bokemeyer, Carsten; Jordan, Karin

2013-01-01

Cytotoxic extravasation is a rare but potentially serious and painful complication of intravenous drug administration in oncology. Literature is anecdotal, and systematic clinical trials are scarce. The German working group for Supportive Care in Cancer (ASORS) has prepared an expert opinion for the diagnosis, prophylaxis and management of cytotoxic extravasation based on an interdisciplinary expert panel. A Pubmed search was conducted for diagnosis, risk factors, symptoms, prophylaxis, and treatment of extravasation by the respective responsible expert. A writing committee compiled the manuscript and proposed the level of recommendation. In a consensus meeting, 13 experts reviewed and discussed the current practice in diagnosis and management of cytotoxic extravasation. In a telephone voting among the experts, the level of recommendation by ASORS was determined. Every effort should be made to reduce the risk of extravasation. Staff training, patient education, usage of right materials and infusion techniques have been identified to be mandatory to minimalize the risk of extravasation. Extravasation must be diagnosed as soon as possible, and specific therapy including antidotes dependent on the extravasated drug should be initiated immediately. An extravasation emergency set should be available wherever intravenous cytotoxics are applied. Documentation and post-treatment follow-up are recommended. We have developed a literature- and expert-based consensus recommendation to avoid cytotoxic extravasation. It also provides practical management instructions which should help to avoid surgery and serious late effects. Copyright © 2013 S. Karger AG, Basel.

Eliciting expert opinion for economic models: an applied example.

PubMed

Leal, José; Wordsworth, Sarah; Legood, Rosa; Blair, Edward

2007-01-01

Expert opinion is considered as a legitimate source of information for decision-analytic modeling where required data are unavailable. Our objective was to develop a practical computer-based tool for eliciting expert opinion about the shape of the uncertainty distribution around individual model parameters. We first developed a prepilot survey with departmental colleagues to test a number of alternative approaches to eliciting opinions on the shape of the uncertainty distribution around individual parameters. This information was used to develop a survey instrument for an applied clinical example. This involved eliciting opinions from experts to inform a number of parameters involving Bernoulli processes in an economic model evaluating DNA testing for families with a genetic disease, hypertrophic cardiomyopathy. The experts were cardiologists, clinical geneticists, and laboratory scientists working with cardiomyopathy patient populations and DNA testing. Our initial prepilot work suggested that the more complex elicitation techniques advocated in the literature were difficult to use in practice. In contrast, our approach achieved a reasonable response rate (50%), provided logical answers, and was generally rated as easy to use by respondents. The computer software user interface permitted graphical feedback throughout the elicitation process. The distributions obtained were incorporated into the model, enabling the use of probabilistic sensitivity analysis. There is clearly a gap in the literature between theoretical elicitation techniques and tools that can be used in applied decision-analytic models. The results of this methodological study are potentially valuable for other decision analysts deriving expert opinion.

Evaluating sustainable energy harvesting systems for human implantable sensors

NASA Astrophysics Data System (ADS)

AL-Oqla, Faris M.; Omar, Amjad A.; Fares, Osama

2018-03-01

Achieving most appropriate energy-harvesting technique for human implantable sensors is still challenging for the industry where keen decisions have to be performed. Moreover, the available polymeric-based composite materials are offering plentiful renewable applications that can help sustainable development as being useful for the energy-harvesting systems such as photovoltaic, piezoelectric, thermoelectric devices as well as other energy storage systems. This work presents an expert-based model capable of better evaluating and examining various available renewable energy-harvesting techniques in urban surroundings subject to various technical and economic, often conflicting, criteria. Wide evaluation criteria have been adopted in the proposed model after examining their suitability as well as ensuring the expediency and reliability of the model by worldwide experts' feedback. The model includes establishing an analytic hierarchy structure with simultaneous 12 conflicting factors to establish a systematic road map for designers to better assess such techniques for human implantable medical sensors. The energy-harvesting techniques considered were limited to Wireless, Thermoelectric, Infrared Radiator, Piezoelectric, Magnetic Induction and Electrostatic Energy Harvesters. Results have demonstrated that the best decision was in favour of wireless-harvesting technology for the medical sensors as it is preferable by most of the considered evaluation criteria in the model.

Rule groupings: An approach towards verification of expert systems

NASA Technical Reports Server (NTRS)

Mehrotra, Mala

1991-01-01

Knowledge-based expert systems are playing an increasingly important role in NASA space and aircraft systems. However, many of NASA's software applications are life- or mission-critical and knowledge-based systems do not lend themselves to the traditional verification and validation techniques for highly reliable software. Rule-based systems lack the control abstractions found in procedural languages. Hence, it is difficult to verify or maintain such systems. Our goal is to automatically structure a rule-based system into a set of rule-groups having a well-defined interface to other rule-groups. Once a rule base is decomposed into such 'firewalled' units, studying the interactions between rules would become more tractable. Verification-aid tools can then be developed to test the behavior of each such rule-group. Furthermore, the interactions between rule-groups can be studied in a manner similar to integration testing. Such efforts will go a long way towards increasing our confidence in the expert-system software. Our research efforts address the feasibility of automating the identification of rule groups, in order to decompose the rule base into a number of meaningful units.

Using cognitive task analysis to create a teaching protocol for bovine dystocia.

PubMed

Read, Emma K; Baillie, Sarah

2013-01-01

When learning skilled techniques and procedures, students face many challenges. Learning is easier when detailed instructions are available, but experts often find it difficult to articulate all of the steps involved in a task or relate to the learner as a novice. This problem is further compounded when the technique is internal and unsighted (e.g., obstetrical procedures). Using expert bovine practitioners and a life-size model cow and calf, the steps and decision making involved in performing correction of two different dystocia presentations (anterior leg back and breech) were deconstructed using cognitive task analysis (CTA). Video cameras were positioned to capture movement inside and outside the cow model while the experts were asked to first perform the technique as they would in a real situation and then perform the procedure again as if articulating the steps to a novice learner. The audio segments were transcribed and, together with the video components, analyzed to create a list of steps for each expert. Consensus was achieved between experts during individual interviews followed by a group discussion. A "gold standard" list or teaching protocol was created for each malpresentation. CTA was useful in defining the technical and cognitive steps required to both perform and teach the tasks effectively. Differences between experts highlight the need for consensus before teaching the skill. In addition, the study identified several different, yet effective, techniques and provided information that could allow experts to consider other approaches they might use when their own technique fails.

Using cooperative learning for a drug information assignment.

PubMed

Earl, Grace L

2009-11-12

To implement a cooperative learning activity to engage students in analyzing tertiary drug information resources in a literature evaluation course. The class was divided into 4 sections to form expert groups and each group researched a different set of references using the jigsaw technique. Each member of each expert group was reassigned to a jigsaw group so that each new group was composed of 4 students from 4 different expert groups. The jigsaw groups met to discuss search strategies and rate the usefulness of the references. In addition to group-based learning, teaching methods included students' writing an independent research paper to enhance their abilities to search and analyze drug information resources. The assignment and final course grades improved after implementation of the activity. Students agreed that class discussions were a useful learning experience and 75% (77/102) said they would use the drug information references for other courses. The jigsaw technique was successful in engaging students in cooperative learning to improve critical thinking skills regarding drug information.

The European Society of Regional Anaesthesia and Pain Therapy and the American Society of Regional Anesthesia and Pain Medicine Joint Committee Practice Advisory on Controversial Topics in Pediatric Regional Anesthesia.

PubMed

Ivani, Giorgio; Suresh, Santhanam; Ecoffey, Claude; Bosenberg, Adrian; Lonnqvist, Per-Anne; Krane, Elliot; Veyckemans, Francis; Polaner, David M; Van de Velde, Marc; Neal, Joseph M

2015-01-01

Some topics in the clinical management of regional anesthesia in children remain controversial. To evaluate and come to a consensus regarding some of these topics, The European Society of Regional Anaesthesia and Pain Therapy (ESRA) and the American Society of Regional Anesthesia and Pain Medicine (ASRA) developed a joint committee practice advisory on pediatric regional anesthesia (PRA). Representatives from both ASRA and ESRA comprised the joint committee practice advisory on PRA. Evidence-based recommendations were based on a systematic search of the literature. In cases where no literature was available, expert opinion was elicited. Experts selected controversial topics in PRA. The performance of PRA under general anesthesia or deep sedation is associated with acceptable safety and should be viewed as the standard of care (Evidence B2 and Evidence B3). Because of the difficulty interpreting a negative test dose, the use of test dosing should remain discretionary (Evidence B4). The use of either air-loss of resistance or saline-loss of resistance techniques is supported by expert opinion, but the literature supporting one technique over the other is sparse and controversial; when used appropriately, each technique may be safely used in children. There are no current evidence-based data that the use of RA increases the risk for acute compartment syndrome or delays its diagnosis in children. High-level evidence is not yet available for the topics evaluated, and most recommendations are based on Evidence B studies. The ESRA/ASRA recommendations intend to provide guidance for the safe practice of regional anesthesia in children.

Evidence flow graph methods for validation and verification of expert systems

NASA Technical Reports Server (NTRS)

Becker, Lee A.; Green, Peter G.; Bhatnagar, Jayant

1988-01-01

This final report describes the results of an investigation into the use of evidence flow graph techniques for performing validation and verification of expert systems. This was approached by developing a translator to convert horn-clause rule bases into evidence flow graphs, a simulation program, and methods of analysis. These tools were then applied to a simple rule base which contained errors. It was found that the method was capable of identifying a variety of problems, for example that the order of presentation of input data or small changes in critical parameters could effect the output from a set of rules.

Intelligent fault isolation and diagnosis for communication satellite systems

NASA Technical Reports Server (NTRS)

Tallo, Donald P.; Durkin, John; Petrik, Edward J.

1992-01-01

Discussed here is a prototype diagnosis expert system to provide the Advanced Communication Technology Satellite (ACTS) System with autonomous diagnosis capability. The system, the Fault Isolation and Diagnosis EXpert (FIDEX) system, is a frame-based system that uses hierarchical structures to represent such items as the satellite's subsystems, components, sensors, and fault states. This overall frame architecture integrates the hierarchical structures into a lattice that provides a flexible representation scheme and facilitates system maintenance. FIDEX uses an inexact reasoning technique based on the incrementally acquired evidence approach developed by Shortliffe. The system is designed with a primitive learning ability through which it maintains a record of past diagnosis studies.

Content-Based Curriculum for High-Ability Learners, Second Edition

ERIC Educational Resources Information Center

VanTassel-Baska, Joyce, Ed.; Little, Catherine A., Ed.

2011-01-01

The newly updated "Content-Based Curriculum for High-Ability Learners" provides a solid introduction to curriculum development in gifted and talented education. Written by experts in the field of gifted education, this text uses cutting-edge design techniques and aligns the core content with national and state standards. In addition to a revision…

Operating Hours Based Inventory Management.

DTIC Science & Technology

1986-12-01

forecasting can be based on the expert opinion. The Delphi technique is one such method of forecasting which uses a group of decision makers with a...errors occ.ur. If larce a’nounts of’ material are procured and warehoused, there could be a greater chance that the material will no longer be needed

A new method for evaluating compliance with industry self-regulation codes governing the content of alcohol advertising.

PubMed

Babor, Thomas F; Xuan, Ziming; Damon, Donna

2013-10-01

This study evaluated the use of a modified Delphi technique in combination with a previously developed alcohol advertising rating procedure to detect content violations in the U.S. Beer Institute Code. A related aim was to estimate the minimum number of raters needed to obtain reliable evaluations of code violations in television commercials. Six alcohol ads selected for their likelihood of having code violations were rated by community and expert participants (N = 286). Quantitative rating scales were used to measure the content of alcohol advertisements based on alcohol industry self-regulatory guidelines. The community group participants represented vulnerability characteristics that industry codes were designed to protect (e.g., age <21); experts represented various health-related professions, including public health, human development, alcohol research, and mental health. Alcohol ads were rated on 2 occasions separated by 1 month. After completing Time 1 ratings, participants were randomized to receive feedback from 1 group or the other. Findings indicate that (i) ratings at Time 2 had generally reduced variance, suggesting greater consensus after feedback, (ii) feedback from the expert group was more influential than that of the community group in developing group consensus, (iii) the expert group found significantly fewer violations than the community group, (iv) experts representing different professional backgrounds did not differ among themselves in the number of violations identified, and (v) a rating panel composed of at least 15 raters is sufficient to obtain reliable estimates of code violations. The Delphi technique facilitates consensus development around code violations in alcohol ad content and may enhance the ability of regulatory agencies to monitor the content of alcoholic beverage advertising when combined with psychometric-based rating procedures. Copyright © 2013 by the Research Society on Alcoholism.

A New Method for Evaluating Compliance with Industry Self-regulation Codes Governing the Content of Alcohol Advertising

PubMed Central

Babor, Thomas F.; Xuan, Ziming; Damon, Donna

2013-01-01

Background This study evaluated the use of a modified Delphi technique in combination with a previously developed alcohol advertising rating procedure to detect content violations in the US Beer Institute code. A related aim was to estimate the minimum number of raters needed to obtain reliable evaluations of code violations in television commercials. Methods Six alcohol ads selected for their likelihood of having code violations were rated by community and expert participants (N=286). Quantitative rating scales were used to measure the content of alcohol advertisements based on alcohol industry self-regulatory guidelines. The community group participants represented vulnerability characteristics that industry codes were designed to protect (e.g., age < 21); experts represented various health-related professions, including public health, human development, alcohol research and mental health. Alcohol ads were rated on two occasions separated by one month. After completing Time 1 ratings, participants were randomized to receive feedback from one group or the other. Results Findings indicate that (1) ratings at Time 2 had generally reduced variance, suggesting greater consensus after feedback, (2) feedback from the expert group was more influential than that of the community group in developing group consensus, (3) the expert group found significantly fewer violations than the community group, (4) experts representing different professional backgrounds did not differ among themselves in the number of violations identified; (5) a rating panel composed of at least 15 raters is sufficient to obtain reliable estimates of code violations. Conclusions The Delphi Technique facilitates consensus development around code violations in alcohol ad content and may enhance the ability of regulatory agencies to monitor the content of alcoholic beverage advertising when combined with psychometric-based rating procedures. PMID:23682927

Embedded expert system for space shuttle main engine maintenance

NASA Technical Reports Server (NTRS)

Pooley, J.; Thompson, W.; Homsley, T.; Teoh, W.; Jones, J.; Lewallen, P.

1987-01-01

The SPARTA Embedded Expert System (SEES) is an intelligent health monitoring system that directs analysis by placing confidence factors on possible engine status and then recommends a course of action to an engineer or engine controller. The technique can prevent catastropic failures or costly rocket engine down time because of false alarms. Further, the SEES has potential as an on-board flight monitor for reusable rocket engine systems. The SEES methodology synergistically integrates vibration analysis, pattern recognition and communications theory techniques with an artificial intelligence technique - the Embedded Expert System (EES).

Research and development of LANDSAT-based crop inventory techniques

NASA Technical Reports Server (NTRS)

Horvath, R.; Cicone, R. C.; Malila, W. A. (Principal Investigator)

1982-01-01

A wide spectrum of technology pertaining to the inventory of crops using LANDSAT without in situ training data is addressed. Methods considered include Bayesian based through-the-season methods, estimation technology based on analytical profile fitting methods, and expert-based computer aided methods. Although the research was conducted using U.S. data, the adaptation of the technology to the Southern Hemisphere, especially Argentina was considered.

Quality assurance paradigms for artificial intelligence in modelling and simulation

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

Oren, T.I.

1987-04-01

New classes of quality assurance concepts and techniques are required for the advanced knowledge-processing paradigms (such as artificial intelligence, expert systems, or knowledge-based systems) and the complex problems that only simulative systems can cope with. A systematization of quality assurance problems as well as examples are given to traditional and cognizant quality assurance techniques in traditional and cognizant modelling and simulation.

Modeling of ETL-Processes and Processed Information in Clinical Data Warehousing.

PubMed

Tute, Erik; Steiner, Jochen

2018-01-01

Literature describes a big potential for reuse of clinical patient data. A clinical data warehouse (CDWH) is a means for that. To support management and maintenance of processes extracting, transforming and loading (ETL) data into CDWHs as well as to ease reuse of metadata between regular IT-management, CDWH and secondary data users by providing a modeling approach. Expert survey and literature review to find requirements and existing modeling techniques. An ETL-modeling-technique was developed extending existing modeling techniques. Evaluation by exemplarily modeling existing ETL-process and a second expert survey. Nine experts participated in the first survey. Literature review yielded 15 included publications. Six existing modeling techniques were identified. A modeling technique extending 3LGM² and combining it with openEHR information models was developed and evaluated. Seven experts participated in the evaluation. The developed approach can help in management and maintenance of ETL-processes and could serve as interface between regular IT-management, CDWH and secondary data users.

Automating the expert consensus paradigm for robust lung tissue classification

NASA Astrophysics Data System (ADS)

Rajagopalan, Srinivasan; Karwoski, Ronald A.; Raghunath, Sushravya; Bartholmai, Brian J.; Robb, Richard A.

2012-03-01

Clinicians confirm the efficacy of dynamic multidisciplinary interactions in diagnosing Lung disease/wellness from CT scans. However, routine clinical practice cannot readily accomodate such interactions. Current schemes for automating lung tissue classification are based on a single elusive disease differentiating metric; this undermines their reliability in routine diagnosis. We propose a computational workflow that uses a collection (#: 15) of probability density functions (pdf)-based similarity metrics to automatically cluster pattern-specific (#patterns: 5) volumes of interest (#VOI: 976) extracted from the lung CT scans of 14 patients. The resultant clusters are refined for intra-partition compactness and subsequently aggregated into a super cluster using a cluster ensemble technique. The super clusters were validated against the consensus agreement of four clinical experts. The aggregations correlated strongly with expert consensus. By effectively mimicking the expertise of physicians, the proposed workflow could make automation of lung tissue classification a clinical reality.

Comparing Text-based and Graphic User Interfaces for Novice and Expert Users

PubMed Central

Chen, Jung-Wei; Zhang, Jiajie

2007-01-01

Graphic User Interface (GUI) is commonly considered to be superior to Text-based User Interface (TUI). This study compares GUI and TUI in an electronic dental record system. Several usability analysis techniques compared the relative effectiveness of a GUI and a TUI. Expert users and novice users were evaluated in time required and steps needed to complete the task. A within-subject design was used to evaluate if the experience with either interface will affect task performance. The results show that the GUI interface was not better than the TUI for expert users. GUI interface was better for novice users. For novice users there was a learning transfer effect from TUI to GUI. This means a user interface is user-friendly or not depending on the mapping between the user interface and tasks. GUI by itself may or may not be better than TUI. PMID:18693811

Comparing Text-based and Graphic User Interfaces for novice and expert users.

PubMed

Chen, Jung-Wei; Zhang, Jiajie

2007-10-11

Graphic User Interface (GUI) is commonly considered to be superior to Text-based User Interface (TUI). This study compares GUI and TUI in an electronic dental record system. Several usability analysis techniques compared the relative effectiveness of a GUI and a TUI. Expert users and novice users were evaluated in time required and steps needed to complete the task. A within-subject design was used to evaluate if the experience with either interface will affect task performance. The results show that the GUI interface was not better than the TUI for expert users. GUI interface was better for novice users. For novice users there was a learning transfer effect from TUI to GUI. This means a user interface is user-friendly or not depending on the mapping between the user interface and tasks. GUI by itself may or may not be better than TUI.

GESA--a two-dimensional processing system using knowledge base techniques.

PubMed

Rowlands, D G; Flook, A; Payne, P I; van Hoff, A; Niblett, T; McKee, S

1988-12-01

The successful analysis of two-dimensional (2-D) polyacrylamide electrophoresis gels demands considerable experience and understanding of the protein system under investigation as well as knowledge of the separation technique itself. The present work concerns the development of a computer system for analysing 2-D electrophoretic separations which incorporates concepts derived from artificial intelligence research such that non-experts can use the technique as a diagnostic or identification tool. Automatic analysis of 2-D gel separations has proved to be extremely difficult using statistical methods. Non-reproducibility of gel separations is also difficult to overcome using automatic systems. However, the human eye is extremely good at recognising patterns in images, and human intervention in semi-automatic computer systems can reduce the computational complexities of fully automatic systems. Moreover, the expertise and understanding of an "expert" is invaluable in reducing system complexity if it can be encapsulated satisfactorily in an expert system. The combination of user-intervention in the computer system together with the encapsulation of expert knowledge characterises the present system. The domain within which the system has been developed is that of wheat grain storage proteins (gliadins) which exhibit polymorphism to such an extent that cultivars can be uniquely identified by their gliadin patterns. The system can be adapted to other domains where a range of polymorpic protein sub-units exist. In its generalised form, the system can also be used for comparing more complex 2-D gel electrophoretic separations.

A Simulation of AI Programming Techniques in BASIC.

ERIC Educational Resources Information Center

Mandell, Alan

1986-01-01

Explains the functions of and the techniques employed in expert systems. Offers the program "The Periodic Table Expert," as a model for using artificial intelligence techniques in BASIC. Includes the program listing and directions for its use on: Tandy 1000, 1200, and 2000; IBM PC; PC Jr; TRS-80; and Apple computers. (ML)

Guidance, navigation, and control subsystem equipment selection algorithm using expert system methods

NASA Technical Reports Server (NTRS)

Allen, Cheryl L.

1991-01-01

Enhanced engineering tools can be obtained through the integration of expert system methodologies and existing design software. The application of these methodologies to the spacecraft design and cost model (SDCM) software provides an improved technique for the selection of hardware for unmanned spacecraft subsystem design. The knowledge engineering system (KES) expert system development tool was used to implement a smarter equipment section algorithm than that which is currently achievable through the use of a standard data base system. The guidance, navigation, and control subsystems of the SDCM software was chosen as the initial subsystem for implementation. The portions of the SDCM code which compute the selection criteria and constraints remain intact, and the expert system equipment selection algorithm is embedded within this existing code. The architecture of this new methodology is described and its implementation is reported. The project background and a brief overview of the expert system is described, and once the details of the design are characterized, an example of its implementation is demonstrated.

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.

An expert fitness diagnosis system based on elastic cloud computing.

PubMed

Tseng, Kevin C; Wu, Chia-Chuan

2014-01-01

This paper presents an expert diagnosis system based on cloud computing. It classifies a user's fitness level based on supervised machine learning techniques. This system is able to learn and make customized diagnoses according to the user's physiological data, such as age, gender, and body mass index (BMI). In addition, an elastic algorithm based on Poisson distribution is presented to allocate computation resources dynamically. It predicts the required resources in the future according to the exponential moving average of past observations. The experimental results show that Naïve Bayes is the best classifier with the highest accuracy (90.8%) and that the elastic algorithm is able to capture tightly the trend of requests generated from the Internet and thus assign corresponding computation resources to ensure the quality of service.

An expert system for wind shear avoidance

NASA Technical Reports Server (NTRS)

Stengel, Robert F.; Stratton, D. Alexander

1990-01-01

A study of intelligent guidance and control concepts for protecting against the adverse effects of wind shear during aircraft takeoffs and landings is being conducted, with current emphasis on developing an expert system for wind shear avoidance. Principal objectives are to develop methods for assessing the likelihood of wind shear encounter (based on real-time information in the cockpit), for deciding what flight path to pursue (e.g., takeoff abort, landing go-around, or normal climbout or glide slope), and for using the aircraft's full potential for combating wind shear. This study requires the definition of both deterministic and statistical techniques for fusing internal and external information , for making go/no-go decisions, and for generating commands to the manually controlled flight. The program has begun with the development of the WindShear Safety Advisor, an expert system for pilot aiding that is based on the FAA Windshear Training Aid; a two-volume manual that presents an overview , pilot guide, training program, and substantiating data provides guidelines for this initial development. The WindShear Safety Advisor expert system currently contains over 200 rules and is coded in the LISP programming language.

Automated eddy current analysis of materials

NASA Technical Reports Server (NTRS)

Workman, Gary L.

1991-01-01

The use of eddy current techniques for characterizing flaws in graphite-based filament-wound cylindrical structures is described. A major emphasis was also placed upon incorporating artificial intelligence techniques into the signal analysis portion of the inspection process. Developing an eddy current scanning system using a commercial robot for inspecting graphite structures (and others) was a goal in the overall concept and is essential for the final implementation for the expert systems interpretation. Manual scans, as performed in the preliminary work here, do not provide sufficiently reproducible eddy current signatures to be easily built into a real time expert system. The expert systems approach to eddy current signal analysis requires that a suitable knowledge base exist in which correct decisions as to the nature of a flaw can be performed. A robotic workcell using eddy current transducers for the inspection of carbon filament materials with improved sensitivity was developed. Improved coupling efficiencies achieved with the E-probes and horseshoe probes are exceptional for graphite fibers. The eddy current supervisory system and expert system was partially developed on a MacIvory system. Continued utilization of finite element models for predetermining eddy current signals was shown to be useful in this work, both for understanding how electromagnetic fields interact with graphite fibers, and also for use in determining how to develop the knowledge base. Sufficient data was taken to indicate that the E-probe and the horseshoe probe can be useful eddy current transducers for inspecting graphite fiber components. The lacking component at this time is a large enough probe to have sensitivity in both the far and near field of a thick graphite epoxy component.

Evidential Reasoning in Expert Systems for Image Analysis.

DTIC Science & Technology

1985-02-01

techniques to image analysis (IA). There is growing evidence that these techniques offer significant improvements in image analysis , particularly in the...2) to provide a common framework for analysis, (3) to structure the ER process for major expert-system tasks in image analysis , and (4) to identify...approaches to three important tasks for expert systems in the domain of image analysis . This segment concluded with an assessment of the strengths

Improved Real-Time Monitoring Using Multiple Expert Systems

NASA Technical Reports Server (NTRS)

Schwuttke, Ursula M.; Angelino, Robert; Quan, Alan G.; Veregge, John; Childs, Cynthia

1993-01-01

Monitor/Analyzer of Real-Time Voyager Engineering Link (MARVEL) computer program implements combination of techniques of both conventional automation and artificial intelligence to improve monitoring of complicated engineering system. Designed to support ground-based operations of Voyager spacecraft, also adapted to other systems. Enables more-accurate monitoring and analysis of telemetry, enhances productivity of monitoring personnel, reduces required number of such personnel by performing routine monitoring tasks, and helps ensure consistency in face of turnover of personnel. Programmed in C language and includes commercial expert-system software shell also written in C.

Weather forecasting expert system study

NASA Technical Reports Server (NTRS)

1985-01-01

Weather forecasting is critical to both the Space Transportation System (STS) ground operations and the launch/landing activities at NASA Kennedy Space Center (KSC). The current launch frequency places significant demands on the USAF weather forecasters at the Cape Canaveral Forecasting Facility (CCFF), who currently provide the weather forecasting for all STS operations. As launch frequency increases, KSC's weather forecasting problems will be great magnified. The single most important problem is the shortage of highly skilled forecasting personnel. The development of forecasting expertise is difficult and requires several years of experience. Frequent personnel changes within the forecasting staff jeopardize the accumulation and retention of experience-based weather forecasting expertise. The primary purpose of this project was to assess the feasibility of using Artificial Intelligence (AI) techniques to ameliorate this shortage of experts by capturing aria incorporating the forecasting knowledge of current expert forecasters into a Weather Forecasting Expert System (WFES) which would then be made available to less experienced duty forecasters.

An intelligent user interface for browsing satellite data catalogs

NASA Technical Reports Server (NTRS)

Cromp, Robert F.; Crook, Sharon

1989-01-01

A large scale domain-independent spatial data management expert system that serves as a front-end to databases containing spatial data is described. This system is unique for two reasons. First, it uses spatial search techniques to generate a list of all the primary keys that fall within a user's spatial constraints prior to invoking the database management system, thus substantially decreasing the amount of time required to answer a user's query. Second, a domain-independent query expert system uses a domain-specific rule base to preprocess the user's English query, effectively mapping a broad class of queries into a smaller subset that can be handled by a commercial natural language processing system. The methods used by the spatial search module and the query expert system are explained, and the system architecture for the spatial data management expert system is described. The system is applied to data from the International Ultraviolet Explorer (IUE) satellite, and results are given.

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.

Artificial intelligence techniques for ground test monitoring of rocket engines

NASA Technical Reports Server (NTRS)

Ali, Moonis; Gupta, U. K.

1990-01-01

An expert system is being developed which can detect anomalies in Space Shuttle Main Engine (SSME) sensor data significantly earlier than the redline algorithm currently in use. The training of such an expert system focuses on two approaches which are based on low frequency and high frequency analyses of sensor data. Both approaches are being tested on data from SSME tests and their results compared with the findings of NASA and Rocketdyne experts. Prototype implementations have detected the presence of anomalies earlier than the redline algorithms that are in use currently. It therefore appears that these approaches have the potential of detecting anomalies early eneough to shut down the engine or take other corrective action before severe damage to the engine occurs.

Expert system shell to reason on large amounts of data

NASA Technical Reports Server (NTRS)

Giuffrida, Gionanni

1994-01-01

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

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.

Robot path planning using expert systems and machine vision

NASA Astrophysics Data System (ADS)

Malone, Denis E.; Friedrich, Werner E.

1992-02-01

This paper describes a system developed for the robotic processing of naturally variable products. In order to plan the robot motion path it was necessary to use a sensor system, in this case a machine vision system, to observe the variations occurring in workpieces and interpret this with a knowledge based expert system. The knowledge base was acquired by carrying out an in-depth study of the product using examination procedures not available in the robotic workplace and relates the nature of the required path to the information obtainable from the machine vision system. The practical application of this system to the processing of fish fillets is described and used to illustrate the techniques.

The Expert Witness

ERIC Educational Resources Information Center

Environmental Science and Technology, 1975

1975-01-01

As consumers organize and industry begins to feel the economic pinch of pollution control laws, litigation may increase as will the need for the expert witness. Discussed are the functions and preparations of expert witnesses, their role and conduct in judicial proceedings, and the techniques of being an expert witness. (BT)

Aspergillus antibody detection: diagnostic strategy and technical considerations from the Société Française de Mycologie Médicale (French Society for Medical Mycology) expert committee.

PubMed

Persat, F; Hennequin, C; Gangneux, J P

2017-04-01

Until now, there has been no consensus on the best method for the detection of anti-Aspergillus antibodies, a key diagnostic tool for chronic aspergilloses. To better appreciate the usage of and confidence in these techniques, the Société Française de Mycologie Médicale (French Society for Medical Mycology; SFMM) performed a two-step survey of French experts. First, we administered an initial survey to French labs performing Aspergillus serology to depict usage of the different techniques available for Aspergillus serology. Second, an opinion poll was conducted of 40 experts via an online questionnaire. Each item was rated from 1 to 9 according to the level of agreement. The initial survey revealed that enzyme-linked immunosorbent assay (ELISA) (81%) and immunoelectrophoresis (IEP) (67%) were the most commonly used techniques for screening and confirmation, respectively. The distinction between screening and confirmation techniques was confirmed by the experts (median = 7) with a 44.2% variation coefficient. Only ELISA for screening and IEP and Western blot (WB) for confirmation were clearly considered valuable methods (median ≥8 with variation coefficients less than 30%). The use of a confirmation technique was recommended in the case of a positive result in a compatible clinical context (cystic fibrosis, for example) or during the patient's follow-up. In the case of discordant results between the screening and confirmation techniques, the experts recommended greater confidence in the results obtained with the confirmation technique. All experts emphasized the need to standardize Aspergillus serology techniques and to better define the place of each of them in the diagnosis of aspergillosis. © The Author 2016. Published by Oxford University Press on behalf of The International Society for Human and Animal Mycology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Machine intelligence and autonomy for aerospace systems

NASA Technical Reports Server (NTRS)

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

1988-01-01

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

Application of omics data in regulatory toxicology: report of an international BfR expert workshop.

PubMed

Marx-Stoelting, P; Braeuning, A; Buhrke, T; Lampen, A; Niemann, L; Oelgeschlaeger, M; Rieke, S; Schmidt, F; Heise, T; Pfeil, R; Solecki, R

2015-11-01

Advances in omics techniques and molecular toxicology are necessary to provide new perspectives for regulatory toxicology. By the application of modern molecular techniques, more mechanistic information should be gained to support standard toxicity studies and to contribute to a reduction and refinement of animal experiments required for certain regulatory purposes. The relevance and applicability of data obtained by omics methods to regulatory purposes such as grouping of chemicals, mode of action analysis or classification and labelling needs further improvement, defined validation and cautious expert judgment. Based on the results of an international expert workshop organized 2014 by the Federal Institute for Risk Assessment in Berlin, this paper is aimed to provide a critical overview of the regulatory relevance and reliability of omics methods, basic requirements on data quality and validation, as well as regulatory criteria to decide which effects observed by omics methods should be considered adverse or non-adverse. As a way forward, it was concluded that the inclusion of omics data can facilitate a more flexible approach for regulatory risk assessment and may help to reduce or refine animal testing.

Smart Sensor-Based Motion Detection System for Hand Movement Training in Open Surgery.

PubMed

Sun, Xinyao; Byrns, Simon; Cheng, Irene; Zheng, Bin; Basu, Anup

2017-02-01

We introduce a smart sensor-based motion detection technique for objective measurement and assessment of surgical dexterity among users at different experience levels. The goal is to allow trainees to evaluate their performance based on a reference model shared through communication technology, e.g., the Internet, without the physical presence of an evaluating surgeon. While in the current implementation we used a Leap Motion Controller to obtain motion data for analysis, our technique can be applied to motion data captured by other smart sensors, e.g., OptiTrack. To differentiate motions captured from different participants, measurement and assessment in our approach are achieved using two strategies: (1) low level descriptive statistical analysis, and (2) Hidden Markov Model (HMM) classification. Based on our surgical knot tying task experiment, we can conclude that finger motions generated from users with different surgical dexterity, e.g., expert and novice performers, display differences in path length, number of movements and task completion time. In order to validate the discriminatory ability of HMM for classifying different movement patterns, a non-surgical task was included in our analysis. Experimental results demonstrate that our approach had 100 % accuracy in discriminating between expert and novice performances. Our proposed motion analysis technique applied to open surgical procedures is a promising step towards the development of objective computer-assisted assessment and training systems.

[Key informers. When and How?].

PubMed

Martín González, R

2009-03-01

When information obtained through duly designed and developed studies is not available, the solution to certain problems that affect the population or that respond to certain questions may be approached by using the information and experience provided by the so-called key informer. The key informer is defined as a person who is in contact with the community or with the problem to be studied, who is considered to have good knowledge of the situation and therefore who is considered an expert. The search for consensus is the basis to obtain information through the key informers. The techniques used have different characteristics based on whether the experts chosen meet together or not, whether they are guided or not, whether they interact with each other or not. These techniques include the survey, the Delphi technique, the nominal group technique, brainwriting, brainstorming, the Phillips 66 technique, the 6-3-5 technique, the community forum and the community impressions technique. Information provided by key informers through the search for consensus is relevant when this is not available or cannot be obtained by other methods. It has permitted the analysis of the existing neurological care model, elaboration of recommendations on visit times for the out-patient neurological care, and the elaboration of guidelines and recommendations for the management of prevalent neurological problems.

Controlling Real-Time Processes On The Space Station With Expert Systems

NASA Astrophysics Data System (ADS)

Leinweber, David; Perry, John

1987-02-01

Many aspects of space station operations involve continuous control of real-time processes. These processes include electrical power system monitoring, propulsion system health and maintenance, environmental and life support systems, space suit checkout, on-board manufacturing, and servicing of attached vehicles such as satellites, shuttles, orbital maneuvering vehicles, orbital transfer vehicles and remote teleoperators. Traditionally, monitoring of these critical real-time processes has been done by trained human experts monitoring telemetry data. However, the long duration of space station missions and the high cost of crew time in space creates a powerful economic incentive for the development of highly autonomous knowledge-based expert control procedures for these space stations. In addition to controlling the normal operations of these processes, the expert systems must also be able to quickly respond to anomalous events, determine their cause and initiate corrective actions in a safe and timely manner. This must be accomplished without excessive diversion of system resources from ongoing control activities and any events beyond the scope of the expert control and diagnosis functions must be recognized and brought to the attention of human operators. Real-time sensor based expert systems (as opposed to off-line, consulting or planning systems receiving data via the keyboard) pose particular problems associated with sensor failures, sensor degradation and data consistency, which must be explicitly handled in an efficient manner. A set of these systems must also be able to work together in a cooperative manner. This paper describes the requirements for real-time expert systems in space station control, and presents prototype implementations of space station expert control procedures in PICON (process intelligent control). PICON is a real-time expert system shell which operates in parallel with distributed data acquisition systems. It incorporates a specialized inference engine with a specialized scheduling portion specifically designed to match the allocation of system resources with the operational requirements of real-time control systems. Innovative knowledge engineering techniques used in PICON to facilitate the development of real-time sensor-based expert systems which use the special features of the inference engine are illustrated in the prototype examples.

Image processing and machine learning techniques to automate diagnosis of Lugol's iodine cervigrams for a low-cost point-of-care digital colposcope

NASA Astrophysics Data System (ADS)

Asiedu, Mercy Nyamewaa; Simhal, Anish; Lam, Christopher T.; Mueller, Jenna; Chaudhary, Usamah; Schmitt, John W.; Sapiro, Guillermo; Ramanujam, Nimmi

2018-02-01

The world health organization recommends visual inspection with acetic acid (VIA) and/or Lugol's Iodine (VILI) for cervical cancer screening in low-resource settings. Human interpretation of diagnostic indicators for visual inspection is qualitative, subjective, and has high inter-observer discordance, which could lead both to adverse outcomes for the patient and unnecessary follow-ups. In this work, we a simple method for automatic feature extraction and classification for Lugol's Iodine cervigrams acquired with a low-cost, miniature, digital colposcope. Algorithms to preprocess expert physician-labelled cervigrams and to extract simple but powerful color-based features are introduced. The features are used to train a support vector machine model to classify cervigrams based on expert physician labels. The selected framework achieved a sensitivity, specificity, and accuracy of 89.2%, 66.7% and 80.6% with majority diagnosis of the expert physicians in discriminating cervical intraepithelial neoplasia (CIN +) relative to normal tissues. The proposed classifier also achieved an area under the curve of 84 when trained with majority diagnosis of the expert physicians. The results suggest that utilizing simple color-based features may enable unbiased automation of VILI cervigrams, opening the door to a full system of low-cost data acquisition complemented with automatic interpretation.

Development of an Adolescent Alcohol Misuse Intervention Based on the Prototype Willingness Model: A Delphi Study

ERIC Educational Resources Information Center

Davies, Emma; Martin, Jilly; Foxcroft, David

2016-01-01

Purpose: The purpose of this paper is to report on the use of the Delphi method to gain expert feedback on the identification of behaviour change techniques (BCTs) and development of a novel intervention to reduce adolescent alcohol misuse, based on the Prototype Willingness Model (PWM) of health risk behaviour. Design/methodology/approach: Four…

Internal Medicine House Officers' Performance as Assessed by Experts and Standardized Patients.

ERIC Educational Resources Information Center

Calhoun, Judith G.; And Others

1987-01-01

Three chronically ill patients were trained to evaluate the performance of 31 second-year internal medicine house officers based upon: a checklist for the medical data elicited during the medical interview; the process of the interview; and the physical examination technique. (Author/MLW)

Semi-automatic segmentation of nonviable cardiac tissue using cine and delayed enhancement magnetic resonance images

NASA Astrophysics Data System (ADS)

O'Donnell, Thomas P.; Xu, Ning; Setser, Randolph M.; White, Richard D.

2003-05-01

Post myocardial infarction, the identification and assessment of non-viable (necrotic) tissues is necessary for effective development of intervention strategies and treatment plans. Delayed Enhancement Magnetic Resonance (DEMR) imaging is a technique whereby non-viable cardiac tissue appears with increased signal intensity. Radiologists typically acquire these images in conjunction with other functional modalities (e.g., MR Cine), and use domain knowledge and experience to isolate the non-viable tissues. In this paper, we present a technique for automatically segmenting these tissues given the delineation of myocardial borders in the DEMR and in the End-systolic and End-diastolic MR Cine images. Briefly, we obtain a set of segmentations furnished by an expert and employ an artificial intelligence technique, Support Vector Machines (SVMs), to "learn" the segmentations based on features culled from the images. Using those features we then allow the SVM to predict the segmentations the expert would provide on previously unseen images.

Comparison of climate envelope models developed using expert-selected variables versus statistical selection

USGS Publications Warehouse

Brandt, Laura A.; Benscoter, Allison; Harvey, Rebecca G.; Speroterra, Carolina; Bucklin, David N.; Romañach, Stephanie; Watling, James I.; Mazzotti, Frank J.

2017-01-01

Climate envelope models are widely used to describe potential future distribution of species under different climate change scenarios. It is broadly recognized that there are both strengths and limitations to using climate envelope models and that outcomes are sensitive to initial assumptions, inputs, and modeling methods Selection of predictor variables, a central step in modeling, is one of the areas where different techniques can yield varying results. Selection of climate variables to use as predictors is often done using statistical approaches that develop correlations between occurrences and climate data. These approaches have received criticism in that they rely on the statistical properties of the data rather than directly incorporating biological information about species responses to temperature and precipitation. We evaluated and compared models and prediction maps for 15 threatened or endangered species in Florida based on two variable selection techniques: expert opinion and a statistical method. We compared model performance between these two approaches for contemporary predictions, and the spatial correlation, spatial overlap and area predicted for contemporary and future climate predictions. In general, experts identified more variables as being important than the statistical method and there was low overlap in the variable sets (<40%) between the two methods Despite these differences in variable sets (expert versus statistical), models had high performance metrics (>0.9 for area under the curve (AUC) and >0.7 for true skill statistic (TSS). Spatial overlap, which compares the spatial configuration between maps constructed using the different variable selection techniques, was only moderate overall (about 60%), with a great deal of variability across species. Difference in spatial overlap was even greater under future climate projections, indicating additional divergence of model outputs from different variable selection techniques. Our work is in agreement with other studies which have found that for broad-scale species distribution modeling, using statistical methods of variable selection is a useful first step, especially when there is a need to model a large number of species or expert knowledge of the species is limited. Expert input can then be used to refine models that seem unrealistic or for species that experts believe are particularly sensitive to change. It also emphasizes the importance of using multiple models to reduce uncertainty and improve map outputs for conservation planning. Where outputs overlap or show the same direction of change there is greater certainty in the predictions. Areas of disagreement can be used for learning by asking why the models do not agree, and may highlight areas where additional on-the-ground data collection could improve the models.

A novel iris transillumination grading scale allowing flexible assessment with quantitative image analysis and visual matching.

PubMed

Wang, Chen; Brancusi, Flavia; Valivullah, Zaheer M; Anderson, Michael G; Cunningham, Denise; Hedberg-Buenz, Adam; Power, Bradley; Simeonov, Dimitre; Gahl, William A; Zein, Wadih M; Adams, David R; Brooks, Brian

2018-01-01

To develop a sensitive scale of iris transillumination suitable for clinical and research use, with the capability of either quantitative analysis or visual matching of images. Iris transillumination photographic images were used from 70 study subjects with ocular or oculocutaneous albinism. Subjects represented a broad range of ocular pigmentation. A subset of images was subjected to image analysis and ranking by both expert and nonexpert reviewers. Quantitative ordering of images was compared with ordering by visual inspection. Images were binned to establish an 8-point scale. Ranking consistency was evaluated using the Kendall rank correlation coefficient (Kendall's tau). Visual ranking results were assessed using Kendall's coefficient of concordance (Kendall's W) analysis. There was a high degree of correlation among the image analysis, expert-based and non-expert-based image rankings. Pairwise comparisons of the quantitative ranking with each reviewer generated an average Kendall's tau of 0.83 ± 0.04 (SD). Inter-rater correlation was also high with Kendall's W of 0.96, 0.95, and 0.95 for nonexpert, expert, and all reviewers, respectively. The current standard for assessing iris transillumination is expert assessment of clinical exam findings. We adapted an image-analysis technique to generate quantitative transillumination values. Quantitative ranking was shown to be highly similar to a ranking produced by both expert and nonexpert reviewers. This finding suggests that the image characteristics used to quantify iris transillumination do not require expert interpretation. Inter-rater rankings were also highly similar, suggesting that varied methods of transillumination ranking are robust in terms of producing reproducible results.

Theoretical Calculations of Atomic Data for Spectroscopy

NASA Technical Reports Server (NTRS)

Bautista, Manuel A.

2000-01-01

Several different approximations and techniques have been developed for the calculation of atomic structure, ionization, and excitation of atoms and ions. These techniques have been used to compute large amounts of spectroscopic data of various levels of accuracy. This paper presents a review of these theoretical methods to help non-experts in atomic physics to better understand the qualities and limitations of various data sources and assess how reliable are spectral models based on those data.

Expert system decision support for low-cost launch vehicle operations

NASA Technical Reports Server (NTRS)

Szatkowski, G. P.; Levin, Barry E.

1991-01-01

Progress in assessing the feasibility, benefits, and risks associated with AI expert systems applied to low cost expendable launch vehicle systems is described. Part one identified potential application areas in vehicle operations and on-board functions, assessed measures of cost benefit, and identified key technologies to aid in the implementation of decision support systems in this environment. Part two of the program began the development of prototypes to demonstrate real-time vehicle checkout with controller and diagnostic/analysis intelligent systems and to gather true measures of cost savings vs. conventional software, verification and validation requirements, and maintainability improvement. The main objective of the expert advanced development projects was to provide a robust intelligent system for control/analysis that must be performed within a specified real-time window in order to meet the demands of the given application. The efforts to develop the two prototypes are described. Prime emphasis was on a controller expert system to show real-time performance in a cryogenic propellant loading application and safety validation implementation of this system experimentally, using commercial-off-the-shelf software tools and object oriented programming techniques. This smart ground support equipment prototype is based in C with imbedded expert system rules written in the CLIPS protocol. The relational database, ORACLE, provides non-real-time data support. The second demonstration develops the vehicle/ground intelligent automation concept, from phase one, to show cooperation between multiple expert systems. This automated test conductor (ATC) prototype utilizes a knowledge-bus approach for intelligent information processing by use of virtual sensors and blackboards to solve complex problems. It incorporates distributed processing of real-time data and object-oriented techniques for command, configuration control, and auto-code generation.

Defining quality criteria for online continuing medical education modules using modified nominal group technique.

PubMed

Shortt, S E D; Guillemette, Jean-Marc; Duncan, Anne Marie; Kirby, Frances

2010-01-01

The rapid increase in the use of the Internet for continuing education by physicians suggests the need to define quality criteria for accredited online modules. Continuing medical education (CME) directors from Canadian medical schools and academic researchers participated in a consensus process, Modified Nominal Group Technique, to develop agreement on the most important quality criteria to guide module development. Rankings were compared to responses to a survey of a subset of Canadian Medical Association (CMA) members. A list of 17 items was developed, of which 10 were deemed by experts to be important and 7 were considered secondary. A quality module would: be needs-based; presented in a clinical format; utilize evidence-based information; permit interaction with content and experts; facilitate and attempt to document practice change; be accessible for later review; and include a robust course evaluation. There was less agreement among CMA members on criteria ranking, with consensus on ranking reached on only 12 of 17 items. In contrast to experts, members agreed that the need to assess performance change as a result of an educational experience was not important. This project identified 10 quality criteria for accredited online CME modules that representatives of Canadian organizations involved in continuing education believe should be taken into account when developing learning products. The lack of practitioner support for documentation of change in clinical behavior may suggest that they favor traditional attendance- or completion-based CME; this finding requires further research.

Active and Passive Haptic Training Approaches in VR Laparoscopic Surgery Training.

PubMed

Marutani, Takafumi; Kato, Toma; Tagawa, Kazuyoshi; Tanaka, Hiromi T; Komori, Masaru; Kurumi, Yoshimasa; Morikawa, Shigehiro

2016-01-01

Laparoscopic surgery has become a widely performed surgery as it is one of the most common minimally invasive surgeries. Doctors perform the surgery by manipulating thin and long surgical instruments precisely with the assistance of laparoscopic video with limited field of view. The power control of the instruments' tip is especially very important, because excessive power may damage internal organs. The training of this surgical technique is mainly supervised by an expert in hands-on coaching program. However, it is difficult for the experts to spend sufficient time for coaching. Therefore, we aim to teach the expert's hand movements in laparoscopic surgery to trainees using VR-based simulator, which is equipped with a guidance force display device. To realize the system, we propose two haptic training approaches for transferring the expert's hand movements to the trainee. One is active training, and the other is passive training. The former approach shows the expert's movements only when the trainee makes large errors while the latter shows the expert's movements continuously. In this study, we validate the applicability of these approaches through tasks in VR laparoscopic surgery training simulator, and identify the differences between these approaches.

A Bibliography of Externally Published Works by the SEI Engineering Techniques Program

DTIC Science & Technology

1992-08-01

media, and virtual reality * model- based engineering * programming languages * reuse * software architectures * software engineering as a discipline...Knowledge- Based Engineering Environments." IEEE Expert 3, 2 (May 1988): 18-23, 26-32. Audience: Practitioner [Klein89b] Klein, D.V. "Comparison of...Terms with Software Reuse Terminology: A Model- Based Approach." ACM SIGSOFT Software Engineering Notes 16, 2 (April 1991): 45-51. Audience: Practitioner

A Step-Wise Approach to Elicit Triangular Distributions

NASA Technical Reports Server (NTRS)

Greenberg, Marc W.

2013-01-01

Adapt/combine known methods to demonstrate an expert judgment elicitation process that: 1.Models expert's inputs as a triangular distribution, 2.Incorporates techniques to account for expert bias and 3.Is structured in a way to help justify expert's inputs. This paper will show one way of "extracting" expert opinion for estimating purposes. Nevertheless, as with most subjective methods, there are many ways to do this.

Evaluating Pillar Industry’s Transformation Capability: A Case Study of Two Chinese Steel-Based Cities

PubMed Central

Li, Zhidong; Marinova, Dora; Guo, Xiumei; Gao, Yuan

2015-01-01

Many steel-based cities in China were established between the 1950s and 1960s. After more than half a century of development and boom, these cities are starting to decline and industrial transformation is urgently needed. This paper focuses on evaluating the transformation capability of resource-based cities building an evaluation model. Using Text Mining and the Document Explorer technique as a way of extracting text features, the 200 most frequently used words are derived from 100 publications related to steel- and other resource-based cities. The Expert Evaluation Method (EEM) and Analytic Hierarchy Process (AHP) techniques are then applied to select 53 indicators, determine their weights and establish an index system for evaluating the transformation capability of the pillar industry of China’s steel-based cities. Using real data and expert reviews, the improved Fuzzy Relation Matrix (FRM) method is applied to two case studies in China, namely Panzhihua and Daye, and the evaluation model is developed using Fuzzy Comprehensive Evaluation (FCE). The cities’ abilities to carry out industrial transformation are evaluated with concerns expressed for the case of Daye. The findings have policy implications for the potential and required industrial transformation in the two selected cities and other resource-based towns. PMID:26422266

Evaluating Pillar Industry's Transformation Capability: A Case Study of Two Chinese Steel-Based Cities.

PubMed

Li, Zhidong; Marinova, Dora; Guo, Xiumei; Gao, Yuan

2015-01-01

Many steel-based cities in China were established between the 1950s and 1960s. After more than half a century of development and boom, these cities are starting to decline and industrial transformation is urgently needed. This paper focuses on evaluating the transformation capability of resource-based cities building an evaluation model. Using Text Mining and the Document Explorer technique as a way of extracting text features, the 200 most frequently used words are derived from 100 publications related to steel- and other resource-based cities. The Expert Evaluation Method (EEM) and Analytic Hierarchy Process (AHP) techniques are then applied to select 53 indicators, determine their weights and establish an index system for evaluating the transformation capability of the pillar industry of China's steel-based cities. Using real data and expert reviews, the improved Fuzzy Relation Matrix (FRM) method is applied to two case studies in China, namely Panzhihua and Daye, and the evaluation model is developed using Fuzzy Comprehensive Evaluation (FCE). The cities' abilities to carry out industrial transformation are evaluated with concerns expressed for the case of Daye. The findings have policy implications for the potential and required industrial transformation in the two selected cities and other resource-based towns.

Clinical and Para Clinical Information Needs of Infertility Electronic Health Records in Iran: A Delphi Study.

PubMed

Farzandipour, Mehrdad; Jeddi, Fateme Rangraz; Gilasi, Hamid Reza; Shirzadi, Diana

2017-09-01

infertility is referred to the person's inability to conceive pregnancy after one year of intercourse without using protection. This study paves the ground for creating a complete, united, and coherent source of patients' medical information. this is an applied research of descriptive-cross sectional type which has been carried out through qualitative - quantitative methods. The sample of the present study was 50 specialists in the field of infertility which has been chosen based on purposive sampling method. Designing the questionnaire was done based on library studies and Gathering experts' views was done based on Delphi technique. 261 items from clinical and Para clinical information of infertile patients' electronic health records were subjected to an opinion poll by experts. During this process 223 items were accepted and 38 items have been rejected after two sessions of surveys by infertility experts. Para clinical information section consisted of 57 items that all of them have been accepted by the experts. Also, clinical information section consisted of 242 items from which 204 items were accepted and 38 items were rejected by the experts. existence of a structured electronic record system of infertile patients' information leads to the integration of patients' information, improvement of health care services and a decrease in treatment costs: all working to increase information safety. Furthermore, only essential and relevant information would be provided for the specialists and it will facilitate and direct the future infertility related studies due to the coherence, unity and relevance of the information.

International, Expert-Based, Consensus Statement Regarding the Management of Acute Diverticulitis.

PubMed

O'Leary, D Peter; Lynch, Noel; Clancy, Cillian; Winter, Desmond C; Myers, Eddie

2015-09-01

This Delphi study provides consensus related to many aspects of acute diverticulitis and identifies other areas in need of research. To generate an international, expert-based, consensus statement to address controversies in the management of acute diverticulitis. This study was conducted using the Delphi technique from April 3 through October 21, 2014. A survey website was used and a panel of acute diverticulitis experts was formed via the snowball method. The top 5 acute diverticulitis experts in 5 international geographic regions were identified based on their number of publications related to acute diverticulitis. The Delphi study used 3 rounds of questions, after which the consensus statement was collated. A consensus statement related to the management of acute diverticulitis. Twenty items were selected for inclusion in the consensus statement following 3 rounds of questioning. A clear definition of uncomplicated and complicated diverticulitis is provided. In uncomplicated diverticulitis, consensus was reached regarding appropriate laboratory and radiological evaluation of patients as well as nonsurgical, surgical, and follow-up strategies. A number of important topics, including antibiotic treatment, failed to reach consensus. In addition, consensus was reached regarding many nonsurgical and surgical treatment strategies in complicated diverticulitis. Controversy continues internationally regarding the management of acute diverticulitis. This study demonstrates that there is more nonconsensus among experts than consensus regarding most issues, even in the same region. It also provides insight into the status quo regarding the treatment of acute diverticulitis and provides important direction for future research.

Five secrets to leveraging maximum buying power with your media project.

PubMed

Hirsch, Lonnie

2010-11-01

Planning and executing a successful media campaign or project requires knowledge and expert execution of specific techniques and skills, including understanding of the requirements for proper media research and competitive intelligence, effective planning of media schedules, negotiation of best rates with media companies, monitoring the campaign, accurately tracking and evaluating results, and making smart adjustments based on tracking data to maximize the profitability and success of the enterprise. Some of the most important knowledge and techniques are not generally known by most advertisers, particularly small businesses like health care practices. This article reveals these tips that are the most effective and includes information on the use of experts and other professional resources that help increase the likelihood of a successful outcome for a well-planned and executed media campaign. Copyright © 2010 Elsevier Inc. All rights reserved.

Do experts and novices direct attention differently in examining physics diagrams? A study of change detection using the flicker technique

NASA Astrophysics Data System (ADS)

Morphew, Jason W.; Mestre, Jose P.; Ross, Brian H.; Strand, Natalie E.

2015-12-01

It is known that experts identify or perceive meaningful patterns in visual stimuli related to their domain of expertise. This study explores the speed with which experts and novices detect changes in physics diagrams. Since change detection depends on where individuals direct their attention, differences in the speed with which experts and novices detect changes to diagrams would suggest differences in attention allocation between experts and novices. We present data from an experiment using the "flicker technique," in which both physics experts and physics novices viewed nearly identical pairs of diagrams that are representative of typical introductory physics situations. The two diagrams in each pair contain a subtle difference that either does or does not change the underlying physics depicted in the diagram. Findings indicate that experts are faster at detecting physics-relevant changes than physics-irrelevant changes; however, there is no difference in response time for novices, suggesting that expertise guides attention for experts when inspecting physics diagrams. We discuss the cognitive implications of our findings.

Teaching artificial neural systems to drive: Manual training techniques for autonomous systems

NASA Technical Reports Server (NTRS)

Shepanski, J. F.; Macy, S. A.

1987-01-01

A methodology was developed for manually training autonomous control systems based on artificial neural systems (ANS). In applications where the rule set governing an expert's decisions is difficult to formulate, ANS can be used to extract rules by associating the information an expert receives with the actions taken. Properly constructed networks imitate rules of behavior that permits them to function autonomously when they are trained on the spanning set of possible situations. This training can be provided manually, either under the direct supervision of a system trainer, or indirectly using a background mode where the networks assimilates training data as the expert performs its day-to-day tasks. To demonstrate these methods, an ANS network was trained to drive a vehicle through simulated freeway traffic.

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.

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.

Aerothermal Assment Of The Expert Flap In The SCIROCCO Wind Tunnel

NASA Astrophysics Data System (ADS)

Walpot, L.; Di Clemente, M.; Vos, J.; Etchells, J.; Trifoni, E.; Thoemel, J.; Gavira, J.

2011-05-01

In the frame of the “In-Flight Test Measurement Techniques for Aerothermodynamics” activity of the EXPERT Program, the EXPERT Instrumented Open Flap Assembly experiment has the objective to verify the design/sensor integration and validate the CFD tools. Ground based measurements were made in Europe’s largest high enthalpy plasma facility, Scirocco in Italy. Two EXPERT flaps of the flight article, instrumented with 14 thermocouples, 5 pressure ports, a pyrometer and an IR camera mounted in the cavity instrumented flap will collect in-flight data. During the Scirocco experiment, an EXPERT flap model identical to the flight article was mounted at 45 deg on a holder including cavity and was subjected to a hot plasma flow at an enthalpy up to 11MJ/kg at a stagnation pressure of 7 bar. The test model sports the same pressure sensors as the flight article. Hypersonic state-of-the-art codes were then be used to perform code-to-code and wind tunnel-to-code comparisons, including thermal response of the flap as collected during the tests by the sensors and camera.

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 reconnaissance method for delineation of tracts for regional-scale mineral-resource assessment based on geologic-map data

USGS Publications Warehouse

Raines, G.L.; Mihalasky, M.J.

2002-01-01

The U.S. Geological Survey (USGS) is proposing to conduct a global mineral-resource assessment using geologic maps, significant deposits, and exploration history as minimal data requirements. Using a geologic map and locations of significant pluton-related deposits, the pluton-related-deposit tract maps from the USGS national mineral-resource assessment have been reproduced with GIS-based analysis and modeling techniques. Agreement, kappa, and Jaccard's C correlation statistics between the expert USGS and calculated tract maps of 87%, 40%, and 28%, respectively, have been achieved using a combination of weights-of-evidence and weighted logistic regression methods. Between the experts' and calculated maps, the ranking of states measured by total permissive area correlates at 84%. The disagreement between the experts and calculated results can be explained primarily by tracts defined by geophysical evidence not considered in the calculations, generalization of tracts by the experts, differences in map scales, and the experts' inclusion of large tracts that are arguably not permissive. This analysis shows that tracts for regional mineral-resource assessment approximating those delineated by USGS experts can be calculated using weights of evidence and weighted logistic regression, a geologic map, and the location of significant deposits. Weights of evidence and weighted logistic regression applied to a global geologic map could provide quickly a useful reconnaissance definition of tracts for mineral assessment that is tied to the data and is reproducible. ?? 2002 International Association for Mathematical Geology.

Expert system verification and validation survey, delivery 4

NASA Technical Reports Server (NTRS)

1990-01-01

The purpose is to determine the state-of-the-practice in Verification and Validation (V and V) of Expert Systems (ESs) on current NASA and Industry applications. This is the first task of a series which has the ultimate purpose of ensuring that adequate ES V and V tools and techniques are available for Space Station Knowledge Based Systems development. The strategy for determining the state-of-the-practice is to check how well each of the known ES V and V issues are being addressed and to what extent they have impacted the development of ESs.

Expert system verification and validation survey. Delivery 2: Survey results

NASA Technical Reports Server (NTRS)

1990-01-01

The purpose is to determine the state-of-the-practice in Verification and Validation (V and V) of Expert Systems (ESs) on current NASA and industry applications. This is the first task of the series which has the ultimate purpose of ensuring that adequate ES V and V tools and techniques are available for Space Station Knowledge Based Systems development. The strategy for determining the state-of-the-practice is to check how well each of the known ES V and V issues are being addressed and to what extent they have impacted the development of ESs.

Expert system verification and validation survey. Delivery 5: Revised

NASA Technical Reports Server (NTRS)

1990-01-01

The purpose is to determine the state-of-the-practice in Verification and Validation (V and V) of Expert Systems (ESs) on current NASA and Industry applications. This is the first task of a series which has the ultimate purpose of ensuring that adequate ES V and V tools and techniques are available for Space Station Knowledge Based Systems development. The strategy for determining the state-of-the-practice is to check how well each of the known ES V and V issues are being addressed and to what extent they have impacted the development of ESs.

Expert system verification and validation survey. Delivery 3: Recommendations

NASA Technical Reports Server (NTRS)

1990-01-01

The purpose is to determine the state-of-the-practice in Verification and Validation (V and V) of Expert Systems (ESs) on current NASA and Industry applications. This is the first task of a series which has the ultimate purpose of ensuring that adequate ES V and V tools and techniques are available for Space Station Knowledge Based Systems development. The strategy for determining the state-of-the-practice is to check how well each of the known ES V and V issues are being addressed and to what extent they have impacted the development of ESs.

An expert system for wind shear avoidance

NASA Technical Reports Server (NTRS)

Stengel, Robert F.; Stratton, D. Alexander

1990-01-01

The principal objectives are to develop methods for assessing the likelihood of wind shear encounter (based on real-time information in the cockpit), for deciding what flight path to pursue (e.g., takeoff abort, landing go-around, or normal climbout or glide slope), and for using the aircraft's full potential for combating wind shear. This study requires the definition of both deterministic and statistical techniques for fusing internal and external information, for making go/no-go decisions, and for generating commands to the aircraft's autopilot and flight directors for both automatic and manually controlled flight. The expert system for pilot aiding is based on the results of the FAA Windshear Training Aids Program, a two-volume manual that presents an overview, pilot guide, training program, and substantiating data that provides guidelines for this initial development. The Windshear Safety Advisor expert system currently contains over 140 rules and is coded in the LISP programming language for implementation on a Symbolics 3670 LISP Machine.

A Model for Intelligent Computer-Aided Education Systems.

ERIC Educational Resources Information Center

Du Plessis, Johan P.; And Others

1995-01-01

Proposes a model for intelligent computer-aided education systems that is based on cooperative learning, constructive problem-solving, object-oriented programming, interactive user interfaces, and expert system techniques. Future research is discussed, and a prototype for teaching mathematics to 10- to 12-year-old students is appended. (LRW)

Helping Students Overcome Depression and Anxiety: A Practical Guide. Second Edition

ERIC Educational Resources Information Center

Merrell, Kenneth W.

2008-01-01

This guide provides expert information and clear-cut strategies for assessing and treating internalizing problems in school settings. More than 40 specific psychoeducational and psychosocial intervention techniques are detailed, with a focus on approaches that are evidence based, broadly applicable, and easy to implement. Including 26…

Proceedings of Tenth Annual Software Engineering Workshop

NASA Technical Reports Server (NTRS)

1985-01-01

Papers are presented on the following topics: measurement of software technology, recent studies of the Software Engineering Lab, software management tools, expert systems, error seeding as a program validation technique, software quality assurance, software engineering environments (including knowledge-based environments), the Distributed Computing Design System, and various Ada experiments.

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.

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

NASA Astrophysics Data System (ADS)

Demigha, Souâd.

2016-03-01

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

Automatic ICD-10 multi-class classification of cause of death from plaintext autopsy reports through expert-driven feature selection.

PubMed

Mujtaba, Ghulam; Shuib, Liyana; Raj, Ram Gopal; Rajandram, Retnagowri; Shaikh, Khairunisa; Al-Garadi, Mohammed Ali

2017-01-01

Widespread implementation of electronic databases has improved the accessibility of plaintext clinical information for supplementary use. Numerous machine learning techniques, such as supervised machine learning approaches or ontology-based approaches, have been employed to obtain useful information from plaintext clinical data. This study proposes an automatic multi-class classification system to predict accident-related causes of death from plaintext autopsy reports through expert-driven feature selection with supervised automatic text classification decision models. Accident-related autopsy reports were obtained from one of the largest hospital in Kuala Lumpur. These reports belong to nine different accident-related causes of death. Master feature vector was prepared by extracting features from the collected autopsy reports by using unigram with lexical categorization. This master feature vector was used to detect cause of death [according to internal classification of disease version 10 (ICD-10) classification system] through five automated feature selection schemes, proposed expert-driven approach, five subset sizes of features, and five machine learning classifiers. Model performance was evaluated using precisionM, recallM, F-measureM, accuracy, and area under ROC curve. Four baselines were used to compare the results with the proposed system. Random forest and J48 decision models parameterized using expert-driven feature selection yielded the highest evaluation measure approaching (85% to 90%) for most metrics by using a feature subset size of 30. The proposed system also showed approximately 14% to 16% improvement in the overall accuracy compared with the existing techniques and four baselines. The proposed system is feasible and practical to use for automatic classification of ICD-10-related cause of death from autopsy reports. The proposed system assists pathologists to accurately and rapidly determine underlying cause of death based on autopsy findings. Furthermore, the proposed expert-driven feature selection approach and the findings are generally applicable to other kinds of plaintext clinical reports.

Automatic ICD-10 multi-class classification of cause of death from plaintext autopsy reports through expert-driven feature selection

PubMed Central

Mujtaba, Ghulam; Shuib, Liyana; Raj, Ram Gopal; Rajandram, Retnagowri; Shaikh, Khairunisa; Al-Garadi, Mohammed Ali

2017-01-01

Objectives Widespread implementation of electronic databases has improved the accessibility of plaintext clinical information for supplementary use. Numerous machine learning techniques, such as supervised machine learning approaches or ontology-based approaches, have been employed to obtain useful information from plaintext clinical data. This study proposes an automatic multi-class classification system to predict accident-related causes of death from plaintext autopsy reports through expert-driven feature selection with supervised automatic text classification decision models. Methods Accident-related autopsy reports were obtained from one of the largest hospital in Kuala Lumpur. These reports belong to nine different accident-related causes of death. Master feature vector was prepared by extracting features from the collected autopsy reports by using unigram with lexical categorization. This master feature vector was used to detect cause of death [according to internal classification of disease version 10 (ICD-10) classification system] through five automated feature selection schemes, proposed expert-driven approach, five subset sizes of features, and five machine learning classifiers. Model performance was evaluated using precisionM, recallM, F-measureM, accuracy, and area under ROC curve. Four baselines were used to compare the results with the proposed system. Results Random forest and J48 decision models parameterized using expert-driven feature selection yielded the highest evaluation measure approaching (85% to 90%) for most metrics by using a feature subset size of 30. The proposed system also showed approximately 14% to 16% improvement in the overall accuracy compared with the existing techniques and four baselines. Conclusion The proposed system is feasible and practical to use for automatic classification of ICD-10-related cause of death from autopsy reports. The proposed system assists pathologists to accurately and rapidly determine underlying cause of death based on autopsy findings. Furthermore, the proposed expert-driven feature selection approach and the findings are generally applicable to other kinds of plaintext clinical reports. PMID:28166263

Estimating distribution and connectivity of recolonizing American marten in the northeastern United States using expert elicitation techniques

USGS Publications Warehouse

Aylward, C.M.; Murdoch, J.D.; Donovan, Therese M.; Kilpatrick, C.W.; Bernier, C.; Katz, J.

2018-01-01

The American marten Martes americana is a species of conservation concern in the northeastern United States due to widespread declines from over‐harvesting and habitat loss. Little information exists on current marten distribution and how landscape characteristics shape patterns of occupancy across the region, which could help develop effective recovery strategies. The rarity of marten and lack of historical distribution records are also problematic for region‐wide conservation planning. Expert opinion can provide a source of information for estimating species–landscape relationships and is especially useful when empirical data are sparse. We created a survey to elicit expert opinion and build a model that describes marten occupancy in the northeastern United States as a function of landscape conditions. We elicited opinions from 18 marten experts that included wildlife managers, trappers and researchers. Each expert estimated occupancy probability at 30 sites in their geographic region of expertise. We, then, fit the response data with a set of 58 models that incorporated the effects of covariates related to forest characteristics, climate, anthropogenic impacts and competition at two spatial scales (1.5 and 5 km radii), and used model selection techniques to determine the best model in the set. Three top models had strong empirical support, which we model averaged based on AIC weights. The final model included effects of five covariates at the 5‐km scale: percent canopy cover (positive), percent spruce‐fir land cover (positive), winter temperature (negative), elevation (positive) and road density (negative). A receiver operating characteristic curve indicated that the model performed well based on recent occurrence records. We mapped distribution across the region and used circuit theory to estimate movement corridors between isolated core populations. The results demonstrate the effectiveness of expert‐opinion data at modeling occupancy for rare species and provide tools for planning marten recovery in the northeastern United States.

Verification and Validation of KBS with Neural Network Components

NASA Technical Reports Server (NTRS)

Wen, Wu; Callahan, John

1996-01-01

Artificial Neural Network (ANN) play an important role in developing robust Knowledge Based Systems (KBS). The ANN based components used in these systems learn to give appropriate predictions through training with correct input-output data patterns. Unlike traditional KBS that depends on a rule database and a production engine, the ANN based system mimics the decisions of an expert without specifically formulating the if-than type of rules. In fact, the ANNs demonstrate their superiority when such if-then type of rules are hard to generate by human expert. Verification of traditional knowledge based system is based on the proof of consistency and completeness of the rule knowledge base and correctness of the production engine.These techniques, however, can not be directly applied to ANN based components.In this position paper, we propose a verification and validation procedure for KBS with ANN based components. The essence of the procedure is to obtain an accurate system specification through incremental modification of the specifications using an ANN rule extraction algorithm.

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.

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.

Design Of An Intelligent Robotic System Organizer Via Expert System Tecniques

NASA Astrophysics Data System (ADS)

Yuan, Peter H.; Valavanis, Kimon P.

1989-02-01

Intelligent Robotic Systems are a special type of Intelligent Machines. When modeled based on Vle theory of Intelligent Controls, they are composed of three interactive levels, namely: organization, coordination, and execution, ordered according, to the ,Principle of Increasing, Intelligence with Decreasing Precl.sion. Expert System techniques, are used to design an Intelligent Robotic System Organizer with a dynamic Knowledge Base and an interactive Inference Engine. Task plans are formulated using, either or both of a Probabilistic Approach and Forward Chapling Methodology, depending on pertinent information associated with a spec;fic requested job. The Intelligent Robotic System, Organizer is implemented and tested on a prototype system operating in an uncertain environment. An evaluation of-the performance, of the prototype system is conducted based upon the probability of generating a successful task sequence versus the number of trials taken by the organizer.

System Diagnostic Builder - A rule generation tool for expert systems that do intelligent data evaluation. [applied to Shuttle Mission Simulator

NASA Technical Reports Server (NTRS)

Nieten, Joseph; Burke, Roger

1993-01-01

Consideration is given to the System Diagnostic Builder (SDB), an automated knowledge acquisition tool using state-of-the-art AI technologies. The SDB employs an inductive machine learning technique to generate rules from data sets that are classified by a subject matter expert. Thus, data are captured from the subject system, classified, 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 knowledge bases captured from the Shuttle Mission Simulator can be used as black box simulations by the Intelligent Computer Aided Training devices. The SDB can also be used to construct knowledge bases for the process control industry, such as chemical production or oil and gas production.

Counseling, Artificial Intelligence, and Expert Systems.

ERIC Educational Resources Information Center

Illovsky, Michael E.

1994-01-01

Considers the use of artificial intelligence and expert systems in counseling. Limitations are explored; candidates for counseling versus those for expert systems are discussed; programming considerations are reviewed; and techniques for dealing with rational, nonrational, and irrational thoughts and feelings are described. (Contains 46…

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.

Using expert opinion surveys to rank threats to endangered species: a case study with sea turtles.

PubMed

Donlan, C Josh; Wingfield, Dana K; Crowder, Larry B; Wilcox, Chris

2010-12-01

Little is known about how specific anthropogenic hazards affect the biology of organisms. Quantifying the effect of regional hazards is particularly challenging for species such as sea turtles because they are migratory, difficult to study, long lived, and face multiple anthropogenic threats. Expert elicitation, a technique used to synthesize opinions of experts while assessing uncertainty around those views, has been in use for several decades in the social science and risk assessment sectors. We conducted an internet-based survey to quantify expert opinion on the relative magnitude of anthropogenic hazards to sea turtle populations at the regional level. Fisheries bycatch and coastal development were most often ranked as the top hazards to sea turtle species in a geographic region. Nest predation and direct take followed as the second and third greatest threats, respectively. Survey results suggest most experts believe sea turtles are threatened by multiple factors, including substantial at-sea threats such as fisheries bycatch. Resources invested by the sea turtle community, however, appear biased toward terrestrial-based impacts. Results from the survey are useful for conservation planning because they provide estimates of relative impacts of hazards on sea turtles and a measure of consensus on the magnitude of those impacts among researchers and practitioners. Our survey results also revealed patterns of expert bias, which we controlled for in our analysis. Respondents with no experience with respect to a sea turtle species tended to rank hazards affecting that sea turtle species higher than respondents with experience. A more-striking pattern was with hazard-based expertise: the more experience a respondent had with a specific hazard, the higher the respondent scored the impact of that hazard on sea turtle populations. Bias-controlled expert opinion surveys focused on threatened species and their hazards can help guide and expedite species recovery plans. © 2010 Society for Conservation Biology.

Physical Restraints: Consensus of a Research Definition Using a Modified Delphi Technique.

PubMed

Bleijlevens, Michel H C; Wagner, Laura M; Capezuti, Elizabeth; Hamers, Jan P H

2016-11-01

To develop an internationally accepted research definition of physical restraint. Comprehensive literature search followed by a web-based, three-round, modified Delphi technique comprising reviews and feedback. Clinical care settings. An international group of 48 experts consisting of researchers and clinicians from 14 countries who have made sustained contribution to research and clinical application in the field of physical restraint in clinical care. Data were collected using an online survey program and one in-person meeting. Results of the online survey and the in-person meeting were used for distribution in subsequent rounds until consensus on a definition was reached. Consensus was defined as 90% of the participating experts agreeing with the proposed definition of physical restraint. Thirty-four different definitions were identified during the literature search and served as a starting point for the modified Delphi technique. After three rounds, 45 (95.7%) of 47 remaining experts agreed with the newly proposed definition: "Physical restraint is defined as any action or procedure that prevents a person's free body movement to a position of choice and/or normal access to his/her body by the use of any method, attached or adjacent to a person's body that he/she cannot control or remove easily." A multidisciplinary, internationally representative panel of experts reached consensus on a research definition for physical restraints in older persons. This is a necessary step toward improved comparisons of the prevalence of physical restraint use across studies and countries. This definition can further guide research interventions aimed at reducing use of physical restraints. © 2016, Copyright the Authors Journal compilation © 2016, The American Geriatrics Society.

Reasoning process characteristics in the diagnostic skills of beginner, competent, and expert dentists.

PubMed

Crespo, Kathleen E; Torres, José E; Recio, María E

2004-12-01

The purpose of this study was to evaluate qualitative differences in the diagnostic reasoning process at different developmental stages of expertise. A qualitative design was used to study cognitive processes that characterize the diagnosis of oral disease at the stages of beginner (five junior students who had passed the NBDE I), competent (five GPR first-year residents), and expert dentists (five general dentists with ten or more years of experience). Individually, each participant was asked to determine the diagnosis of an oral condition based on a written clinical case, using the think aloud technique and retrospective reports. A subsequent interview was conducted to obtain the participants' diagnostic process model and pathophysiology of the case. The analysis of the verbal protocols indicated that experts referred to the patient's sociomedical context more frequently, demonstrated better organization of ideas, could determine key clinical findings, and had an ability to plan for the search of pertinent information. Fewer diagnostic hypotheses were formulated by participants who used forward reasoning, independent of the stage of development. Beginners requested additional diagnostic aids (radiographs, laboratory tests) more frequently than the competent/expert dentists. Experts recalled typical experiences with patients, while competent/beginner dentists recalled information from didactic courses. Experts evidenced cognitive diagnostic schemas that integrate pathophysiology of disease, while competent and beginner participants had not achieved this integration. We conclude that expert performance is a combination of a knowledge base, reasoning skills, and an accumulation of experiences with patients that is qualitatively different from that of competent and beginner dentists. It is important for dental education to emphasize the teaching of cognitive processes and to incorporate a wide variety of clinical experiences in addition to the teaching of disciplinary content.

Expert Consensus Contouring Guidelines for Intensity Modulated Radiation Therapy in Esophageal and Gastroesophageal Junction Cancer.

PubMed

Wu, Abraham J; Bosch, Walter R; Chang, Daniel T; Hong, Theodore S; Jabbour, Salma K; Kleinberg, Lawrence R; Mamon, Harvey J; Thomas, Charles R; Goodman, Karyn A

2015-07-15

Current guidelines for esophageal cancer contouring are derived from traditional 2-dimensional fields based on bony landmarks, and they do not provide sufficient anatomic detail to ensure consistent contouring for more conformal radiation therapy techniques such as intensity modulated radiation therapy (IMRT). Therefore, we convened an expert panel with the specific aim to derive contouring guidelines and generate an atlas for the clinical target volume (CTV) in esophageal or gastroesophageal junction (GEJ) cancer. Eight expert academically based gastrointestinal radiation oncologists participated. Three sample cases were chosen: a GEJ cancer, a distal esophageal cancer, and a mid-upper esophageal cancer. Uniform computed tomographic (CT) simulation datasets and accompanying diagnostic positron emission tomographic/CT images were distributed to each expert, and the expert was instructed to generate gross tumor volume (GTV) and CTV contours for each case. All contours were aggregated and subjected to quantitative analysis to assess the degree of concordance between experts and to generate draft consensus contours. The panel then refined these contours to generate the contouring atlas. The κ statistics indicated substantial agreement between panelists for each of the 3 test cases. A consensus CTV atlas was generated for the 3 test cases, each representing common anatomic presentations of esophageal cancer. The panel agreed on guidelines and principles to facilitate the generalizability of the atlas to individual cases. This expert panel successfully reached agreement on contouring guidelines for esophageal and GEJ IMRT and generated a reference CTV atlas. This atlas will serve as a reference for IMRT contours for clinical practice and prospective trial design. Subsequent patterns of failure analyses of clinical datasets using these guidelines may require modification in the future. Copyright © 2015 Elsevier Inc. All rights reserved.

Expert Consensus Contouring Guidelines for Intensity Modulated Radiation Therapy in Esophageal and Gastroesophageal Junction Cancer

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

Wu, Abraham J., E-mail: wua@mskcc.org; Bosch, Walter R.; Chang, Daniel T.

Purpose/Objective(s): Current guidelines for esophageal cancer contouring are derived from traditional 2-dimensional fields based on bony landmarks, and they do not provide sufficient anatomic detail to ensure consistent contouring for more conformal radiation therapy techniques such as intensity modulated radiation therapy (IMRT). Therefore, we convened an expert panel with the specific aim to derive contouring guidelines and generate an atlas for the clinical target volume (CTV) in esophageal or gastroesophageal junction (GEJ) cancer. Methods and Materials: Eight expert academically based gastrointestinal radiation oncologists participated. Three sample cases were chosen: a GEJ cancer, a distal esophageal cancer, and a mid-upper esophagealmore » cancer. Uniform computed tomographic (CT) simulation datasets and accompanying diagnostic positron emission tomographic/CT images were distributed to each expert, and the expert was instructed to generate gross tumor volume (GTV) and CTV contours for each case. All contours were aggregated and subjected to quantitative analysis to assess the degree of concordance between experts and to generate draft consensus contours. The panel then refined these contours to generate the contouring atlas. Results: The κ statistics indicated substantial agreement between panelists for each of the 3 test cases. A consensus CTV atlas was generated for the 3 test cases, each representing common anatomic presentations of esophageal cancer. The panel agreed on guidelines and principles to facilitate the generalizability of the atlas to individual cases. Conclusions: This expert panel successfully reached agreement on contouring guidelines for esophageal and GEJ IMRT and generated a reference CTV atlas. This atlas will serve as a reference for IMRT contours for clinical practice and prospective trial design. Subsequent patterns of failure analyses of clinical datasets using these guidelines may require modification in the future.« less

Sensor data validation and reconstruction. Phase 1: System architecture study

NASA Technical Reports Server (NTRS)

1991-01-01

The sensor validation and data reconstruction task reviewed relevant literature and selected applicable validation and reconstruction techniques for further study; analyzed the selected techniques and emphasized those which could be used for both validation and reconstruction; analyzed Space Shuttle Main Engine (SSME) hot fire test data to determine statistical and physical relationships between various parameters; developed statistical and empirical correlations between parameters to perform validation and reconstruction tasks, using a computer aided engineering (CAE) package; and conceptually designed an expert system based knowledge fusion tool, which allows the user to relate diverse types of information when validating sensor data. The host hardware for the system is intended to be a Sun SPARCstation, but could be any RISC workstation with a UNIX operating system and a windowing/graphics system such as Motif or Dataviews. The information fusion tool is intended to be developed using the NEXPERT Object expert system shell, and the C programming language.

Developing material for promoting problem-solving ability through bar modeling technique

NASA Astrophysics Data System (ADS)

Widyasari, N.; Rosiyanti, H.

2018-01-01

This study aimed at developing material for enhancing problem-solving ability through bar modeling technique with thematic learning. Polya’s steps of problem-solving were chosen as the basis of the study. The methods of the study were research and development. The subject of this study were five teen students of the fifth grade of Lab-school FIP UMJ elementary school. Expert review and student’ response analysis were used to collect the data. Furthermore, the data were analyzed using qualitative descriptive and quantitative. The findings showed that material in theme “Selalu Berhemat Energi” was categorized as valid and practical. The validity was measured by using the aspect of language, contents, and graphics. Based on the expert comments, the materials were easy to implement in the teaching-learning process. In addition, the result of students’ response showed that material was both interesting and easy to understand. Thus, students gained more understanding in learning problem-solving.

Expert system verification and validation study. Delivery 3A and 3B: Trip summaries

NASA Technical Reports Server (NTRS)

French, Scott

1991-01-01

Key results are documented from attending the 4th workshop on verification, validation, and testing. The most interesting part of the workshop was when representatives from the U.S., Japan, and Europe presented surveys of VV&T within their respective regions. Another interesting part focused on current efforts to define industry standards for artificial intelligence and how that might affect approaches to VV&T of expert systems. The next part of the workshop focused on VV&T methods of applying mathematical techniques to verification of rule bases and techniques for capturing information relating to the process of developing software. The final part focused on software tools. A summary is also presented of the EPRI conference on 'Methodologies, Tools, and Standards for Cost Effective Reliable Software Verification and Validation. The conference was divided into discussion sessions on the following issues: development process, automated tools, software reliability, methods, standards, and cost/benefit considerations.

In Situ Distribution Guided Analysis and Visualization of Transonic Jet Engine Simulations.

PubMed

Dutta, Soumya; Chen, Chun-Ming; Heinlein, Gregory; Shen, Han-Wei; Chen, Jen-Ping

2017-01-01

Study of flow instability in turbine engine compressors is crucial to understand the inception and evolution of engine stall. Aerodynamics experts have been working on detecting the early signs of stall in order to devise novel stall suppression technologies. A state-of-the-art Navier-Stokes based, time-accurate computational fluid dynamics simulator, TURBO, has been developed in NASA to enhance the understanding of flow phenomena undergoing rotating stall. Despite the proven high modeling accuracy of TURBO, the excessive simulation data prohibits post-hoc analysis in both storage and I/O time. To address these issues and allow the expert to perform scalable stall analysis, we have designed an in situ distribution guided stall analysis technique. Our method summarizes statistics of important properties of the simulation data in situ using a probabilistic data modeling scheme. This data summarization enables statistical anomaly detection for flow instability in post analysis, which reveals the spatiotemporal trends of rotating stall for the expert to conceive new hypotheses. Furthermore, the verification of the hypotheses and exploratory visualization using the summarized data are realized using probabilistic visualization techniques such as uncertain isocontouring. Positive feedback from the domain scientist has indicated the efficacy of our system in exploratory stall analysis.

An evaluation of consensus techniques for diagnostic interpretation

NASA Astrophysics Data System (ADS)

Sauter, Jake N.; LaBarre, Victoria M.; Furst, Jacob D.; Raicu, Daniela S.

2018-02-01

Learning diagnostic labels from image content has been the standard in computer-aided diagnosis. Most computer-aided diagnosis systems use low-level image features extracted directly from image content to train and test machine learning classifiers for diagnostic label prediction. When the ground truth for the diagnostic labels is not available, reference truth is generated from the experts diagnostic interpretations of the image/region of interest. More specifically, when the label is uncertain, e.g. when multiple experts label an image and their interpretations are different, techniques to handle the label variability are necessary. In this paper, we compare three consensus techniques that are typically used to encode the variability in the experts labeling of the medical data: mean, median and mode, and their effects on simple classifiers that can handle deterministic labels (decision trees) and probabilistic vectors of labels (belief decision trees). Given that the NIH/NCI Lung Image Database Consortium (LIDC) data provides interpretations for lung nodules by up to four radiologists, we leverage the LIDC data to evaluate and compare these consensus approaches when creating computer-aided diagnosis systems for lung nodules. First, low-level image features of nodules are extracted and paired with their radiologists semantic ratings (1= most likely benign, , 5 = most likely malignant); second, machine learning multi-class classifiers that handle deterministic labels (decision trees) and probabilistic vectors of labels (belief decision trees) are built to predict the lung nodules semantic ratings. We show that the mean-based consensus generates the most robust classi- fier overall when compared to the median- and mode-based consensus. Lastly, the results of this study show that, when building CAD systems with uncertain diagnostic interpretation, it is important to evaluate different strategies for encoding and predicting the diagnostic label.

Right adrenal vein: comparison between adaptive statistical iterative reconstruction and model-based iterative reconstruction.

PubMed

Noda, Y; Goshima, S; Nagata, S; Miyoshi, T; Kawada, H; Kawai, N; Tanahashi, Y; Matsuo, M

2018-06-01

To compare right adrenal vein (RAV) visualisation and contrast enhancement degree on adrenal venous phase images reconstructed using adaptive statistical iterative reconstruction (ASiR) and model-based iterative reconstruction (MBIR) techniques. This prospective study was approved by the institutional review board, and written informed consent was waived. Fifty-seven consecutive patients who underwent adrenal venous phase imaging were enrolled. The same raw data were reconstructed using ASiR 40% and MBIR. The expert and beginner independently reviewed computed tomography (CT) images. RAV visualisation rates, background noise, and CT attenuation of the RAV, right adrenal gland, inferior vena cava (IVC), hepatic vein, and bilateral renal veins were compared between the two reconstruction techniques. RAV visualisation rates were higher with MBIR than with ASiR (95% versus 88%, p=0.13 in expert and 93% versus 75%, p=0.002 in beginner, respectively). RAV visualisation confidence ratings with MBIR were significantly greater than with ASiR (p<0.0001, both in the beginner and the expert). The mean background noise was significantly lower with MBIR than with ASiR (p<0.0001). Mean CT attenuation values of the RAV, right adrenal gland, IVC, and hepatic vein were comparable between the two techniques (p=0.12-0.91). Mean CT attenuation values of the bilateral renal veins were significantly higher with MBIR than with ASiR (p=0.0013 and 0.02). Reconstruction of adrenal venous phase images using MBIR significantly reduces background noise, leading to an improvement in the RAV visualisation compared with ASiR. Copyright © 2018 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Determination of Flaw Type and Location Using an Expert Module in Ultrasonic Nondestructive Testing for Weld Inspection

NASA Astrophysics Data System (ADS)

Shahriari, D.; Zolfaghari, A.; Masoumi, F.

2011-01-01

Nondestructive evaluation is explained as nondestructive testing, nondestructive inspection, and nondestructive examination. It is a desire to determine some characteristic of the object or to determine whether the object contains irregularities, discontinuities, or flaws. Ultrasound based inspection techniques are used extensively throughout industry for detection of flaws in engineering materials. The range and variety of imperfections encountered is large, and critical assessment of location, size, orientation and type is often difficult. In addition, increasing quality requirements of new standards and codes of practice relating to fitness for purpose are placing higher demands on operators. Applying of an expert knowledge-based analysis in ultrasonic examination is a powerful tool that can help assure safety, quality, and reliability; increase productivity; decrease liability; and save money. In this research, an expert module system is coupled with ultrasonic examination (A-Scan Procedure) to determine and evaluate type and location of flaws that embedded during welding parts. The processing module of this expert system is implemented based on EN standard to classify welding defects, acceptance condition and measuring of their location via echo static pattern and image processing. The designed module introduces new system that can automate evaluating of the results of A-scan method according to EN standard. It can simultaneously recognize the number and type of defects, and determine flaw position during each scan.

Balancing Self-Directed Learning with Expert Mentoring: The Science Writing Heuristic Approach

ERIC Educational Resources Information Center

Shelley, Mack; Fostvedt, Luke; Gonwa-Reeves, Christopher; Baenziger, Joan; McGill, Michael; Seefeld, Ashley; Hand, Brian; Therrien, William; Taylor, Jonte; Villanueva, Mary Grace

2012-01-01

This study focuses on the implementation of the Science Writing Heuristic (SWH) curriculum (Hand, 2007), which combines current understandings of learning as a cognitive and negotiated process with the techniques of argument-based inquiry, critical thinking skills, and writing to strengthen student outcomes. Success of SWH is dependent on the…

Pattern recognition and expert image analysis systems in biomedical image processing (Invited Paper)

NASA Astrophysics Data System (ADS)

Oosterlinck, A.; Suetens, P.; Wu, Q.; Baird, M.; F. M., C.

1987-09-01

This paper gives an overview of pattern recoanition techniques (P.R.) used in biomedical image processing and problems related to the different P.R. solutions. Also the use of knowledge based systems to overcome P.R. difficulties, is described. This is illustrated by a common example ofabiomedical image processing application.

Terminating Sequential Delphi Survey Data Collection

ERIC Educational Resources Information Center

Kalaian, Sema A.; Kasim, Rafa M.

2012-01-01

The Delphi survey technique is an iterative mail or electronic (e-mail or web-based) survey method used to obtain agreement or consensus among a group of experts in a specific field on a particular issue through a well-designed and systematic multiple sequential rounds of survey administrations. Each of the multiple rounds of the Delphi survey…

Practice guidelines for endoscopic ultrasound-guided celiac plexus neurolysis.

PubMed

Wyse, Jonathan M; Battat, Robert; Sun, Siyu; Saftoiu, Adrian; Siddiqui, Ali A; Leong, Ang Tiing; Arturo Arias, Brenda Lucia; Fabbri, Carlo; Adler, Douglas G; Santo, Erwin; Kalaitzakis, Evangelos; Artifon, Everson; Mishra, Girish; Okasha, Hussein Hassan; Poley, Jan Werner; Guo, Jintao; Vila, Juan J; Lee, Linda S; Sharma, Malay; Bhutani, Manoop S; Giovannini, Marc; Kitano, Masayuki; Eloubeidi, Mohamad Ali; Khashab, Mouen A; Nguyen, Nam Q; Saxena, Payal; Vilmann, Peter; Fusaroli, Pietro; Garg, Pramod Kumar; Ho, Sammy; Mukai, Shuntaro; Carrara, Silvia; Sridhar, Subbaramiah; Lakhtakia, Sundeep; Rana, Surinder S; Dhir, Vinay; Sahai, Anand V

2017-01-01

The objective of guideline was to provide clear and relevant consensus statements to form a practical guideline for clinicians on the indications, optimal technique, safety and efficacy of endoscopic ultrasound guided celiac plexus neurolysis (EUS-CPN). Six important clinical questions were determined regarding EUS-CPN. Following a detailed literature review, 6 statements were proposed attempting to answer those questions. A group of expert endosonographers convened in Chicago, United States (May 2016), where the statements were presented and feedback provided. Subsequently a consensus group of 35 expert endosonographers voted based on their individual level of agreement. A strong recommendation required 80% voter agreement. The modified GRADE (Grading of Recommendations Assessment, Development, and Evaluation) criteria were used to rate the strength of recommendations and the quality of evidence. Eighty percent agreement was reached on 5 of 6 consensus statements, 79.4% agreement was reached on the remaining one. EUS-CPN is efficacious, should be integrated into the management of pancreas cancer pain, and can be considered early at the time of diagnosis of inoperable disease. Techniques may still vary based on operator experience. Serious complications exist, but are rare.

A Delphi Investigation into Future Trends in E-Learning in Israel

ERIC Educational Resources Information Center

Aharony, Noa; Bronstein, Jenny

2014-01-01

The purpose of this study is to investigate the views and opinions of e-learning experts regarding future trends in the e-learning arena. The Delphi technique was chosen as a method of study. This technique is an efficient and effective group communication process designed to systematically elicit judgments from experts in their selected area of…

A Delphi Study on Staff Bereavement Training in the Intellectual and Developmental Disabilities Field

ERIC Educational Resources Information Center

Gray, Jennifer A.; Truesdale, Jesslyn

2015-01-01

The Delphi technique was used to obtain expert panel consensus to prioritize content areas and delivery methods for developing staff grief and bereavement curriculum training in the intellectual and developmental disabilities (IDD) field. The Delphi technique was conducted with a panel of 18 experts from formal and informal disability caregiving,…

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

NASA Technical Reports Server (NTRS)

Lambright, Jonathan Paul

1996-01-01

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

Integrated Formulation of Beacon-Based Exception Analysis for Multimissions

NASA Technical Reports Server (NTRS)

Mackey, Ryan; James, Mark; Park, Han; Zak, Mickail

2003-01-01

Further work on beacon-based exception analysis for multimissions (BEAM), a method of real-time, automated diagnosis of a complex electromechanical systems, has greatly expanded its capability and suitability of application. This expanded formulation, which fully integrates physical models and symbolic analysis, is described. The new formulation of BEAM expands upon previous advanced techniques for analysis of signal data, utilizing mathematical modeling of the system physics, and expert-system reasoning,

Improving linear transport infrastructure efficiency by automated learning and optimised predictive maintenance techniques (INFRALERT)

NASA Astrophysics Data System (ADS)

Jiménez-Redondo, Noemi; Calle-Cordón, Alvaro; Kandler, Ute; Simroth, Axel; Morales, Francisco J.; Reyes, Antonio; Odelius, Johan; Thaduri, Aditya; Morgado, Joao; Duarte, Emmanuele

2017-09-01

The on-going H2020 project INFRALERT aims to increase rail and road infrastructure capacity in the current framework of increased transportation demand by developing and deploying solutions to optimise maintenance interventions planning. It includes two real pilots for road and railways infrastructure. INFRALERT develops an ICT platform (the expert-based Infrastructure Management System, eIMS) which follows a modular approach including several expert-based toolkits. This paper presents the methodologies and preliminary results of the toolkits for i) nowcasting and forecasting of asset condition, ii) alert generation, iii) RAMS & LCC analysis and iv) decision support. The results of these toolkits in a meshed road network in Portugal under the jurisdiction of Infraestruturas de Portugal (IP) are presented showing the capabilities of the approaches.

Do Experts and Novices Direct Attention Differently in Examining Physics Diagrams? A Study of Change Detection Using the Flicker Technique

ERIC Educational Resources Information Center

Morphew, Jason W.; Mestre, Jose P.; Ross, Brian H.; Strand, Natalie E.

2015-01-01

It is known that experts identify or perceive meaningful patterns in visual stimuli related to their domain of expertise. This study explores the speed with which experts and novices detect changes in physics diagrams. Since change detection depends on where individuals direct their attention, differences in the speed with which experts and…

Knowledge-based geographic information systems (KBGIS): New analytic and data management tools

USGS Publications Warehouse

Albert, T.M.

1988-01-01

In its simplest form, a geographic information system (GIS) may be viewed as a data base management system in which most of the data are spatially indexed, and upon which sets of procedures operate to answer queries about spatial entities represented in the data base. Utilization of artificial intelligence (AI) techniques can enhance greatly the capabilities of a GIS, particularly in handling very large, diverse data bases involved in the earth sciences. A KBGIS has been developed by the U.S. Geological Survey which incorporates AI techniques such as learning, expert systems, new data representation, and more. The system, which will be developed further and applied, is a prototype of the next generation of GIS's, an intelligent GIS, as well as an example of a general-purpose intelligent data handling system. The paper provides a description of KBGIS and its application, as well as the AI techniques involved. ?? 1988 International Association for Mathematical Geology.

Criteria for clinical audit of the quality of hospital-based obstetric care in developing countries.

PubMed Central

Graham, W.; Wagaarachchi, P.; Penney, G.; McCaw-Binns, A.; Antwi, K. Y.; Hall, M. H.

2000-01-01

Improving the quality of obstetric care is an urgent priority in developing countries, where maternal mortality remains high. The feasibility of criterion-based clinical audit of the assessment and management of five major obstetric complications is being studied in Ghana and Jamaica. In order to establish case definitions and clinical audit criteria, a systematic review of the literature was followed by three expert panel meetings. A modified nominal group technique was used to develop consensus among experts on a final set of case definitions and criteria. Five main obstetric complications were selected and definitions were agreed. The literature review led to the identification of 67 criteria, and the panel meetings resulted in the modification and approval of 37 of these for the next stage of audit. Criterion-based audit, which has been devised and tested primarily in industrialized countries, can be adapted and applied where resources are poorer. The selection of audit criteria for such settings requires local expert opinion to be considered in addition to research evidence, so as to ensure that the criteria are realistic in relation to conditions in the field. Practical methods for achieving this are described in the present paper. PMID:10859855

Applications of advanced data analysis and expert system technologies in the ATLAS Trigger-DAQ Controls framework

NASA Astrophysics Data System (ADS)

Avolio, G.; Corso Radu, A.; Kazarov, A.; Lehmann Miotto, G.; Magnoni, L.

2012-12-01

The Trigger and Data Acquisition (TDAQ) system of the ATLAS experiment is a very complex distributed computing system, composed of more than 20000 applications running on more than 2000 computers. The TDAQ Controls system has to guarantee the smooth and synchronous operations of all the TDAQ components and has to provide the means to minimize the downtime of the system caused by runtime failures. During data taking runs, streams of information messages sent or published by running applications are the main sources of knowledge about correctness of running operations. The huge flow of operational monitoring data produced is constantly monitored by experts in order to detect problems or misbehaviours. Given the scale of the system and the rates of data to be analyzed, the automation of the system functionality in the areas of operational monitoring, system verification, error detection and recovery is a strong requirement. To accomplish its objective, the Controls system includes some high-level components which are based on advanced software technologies, namely the rule-based Expert System and the Complex Event Processing engines. The chosen techniques allow to formalize, store and reuse the knowledge of experts and thus to assist the shifters in the ATLAS control room during the data-taking activities.

Genetic algorithm based fuzzy control of spacecraft autonomous rendezvous

NASA Technical Reports Server (NTRS)

Karr, C. L.; Freeman, L. M.; Meredith, D. L.

1990-01-01

The U.S. Bureau of Mines is currently investigating ways to combine the control capabilities of fuzzy logic with the learning capabilities of genetic algorithms. Fuzzy logic allows for the uncertainty inherent in most control problems to be incorporated into conventional expert systems. Although fuzzy logic based expert systems have been used successfully for controlling a number of physical systems, the selection of acceptable fuzzy membership functions has generally been a subjective decision. High performance fuzzy membership functions for a fuzzy logic controller that manipulates a mathematical model simulating the autonomous rendezvous of spacecraft are learned using a genetic algorithm, a search technique based on the mechanics of natural genetics. The membership functions learned by the genetic algorithm provide for a more efficient fuzzy logic controller than membership functions selected by the authors for the rendezvous problem. Thus, genetic algorithms are potentially an effective and structured approach for learning fuzzy membership functions.

Simple methods of exploiting the underlying structure of rule-based systems

NASA Technical Reports Server (NTRS)

Hendler, James

1986-01-01

Much recent work in the field of expert systems research has aimed at exploiting the underlying structures of the rule base for reasons of analysis. Such techniques as Petri-nets and GAGs have been proposed as representational structures that will allow complete analysis. Much has been made of proving isomorphisms between the rule bases and the mechanisms, and in examining the theoretical power of this analysis. In this paper we describe some early work in a new system which has much simpler (and thus, one hopes, more easily achieved) aims and less formality. The technique being examined is a very simple one: OPS5 programs are analyzed in a purely syntactic way and a FSA description is generated. In this paper we describe the technique and some user interface tools which exploit this structure.

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.

Wireless device connection problems and design solutions

NASA Astrophysics Data System (ADS)

Song, Ji-Won; Norman, Donald; Nam, Tek-Jin; Qin, Shengfeng

2016-09-01

Users, especially the non-expert users, commonly experience problems when connecting multiple devices with interoperability. While studies on multiple device connections are mostly concentrated on spontaneous device association techniques with a focus on security aspects, the research on user interaction for device connection is still limited. More research into understanding people is needed for designers to devise usable techniques. This research applies the Research-through-Design method and studies the non-expert users' interactions in establishing wireless connections between devices. The "Learning from Examples" concept is adopted to develop a study focus line by learning from the expert users' interaction with devices. This focus line is then used for guiding researchers to explore the non-expert users' difficulties at each stage of the focus line. Finally, the Research-through-Design approach is used to understand the users' difficulties, gain insights to design problems and suggest usable solutions. When connecting a device, the user is required to manage not only the device's functionality but also the interaction between devices. Based on learning from failures, an important insight is found that the existing design approach to improve single-device interaction issues, such as improvements to graphical user interfaces or computer guidance, cannot help users to handle problems between multiple devices. This study finally proposes a desirable user-device interaction in which images of two devices function together with a system image to provide the user with feedback on the status of the connection, which allows them to infer any required actions.

Group elicitations yield more consistent, yet more uncertain experts in understanding risks to ecosystem services in New Zealand bays

PubMed Central

Sinner, Jim; Ellis, Joanne; Kandlikar, Milind; Halpern, Benjamin S.; Satterfield, Terre; Chan, Kai

2017-01-01

The elicitation of expert judgment is an important tool for assessment of risks and impacts in environmental management contexts, and especially important as decision-makers face novel challenges where prior empirical research is lacking or insufficient. Evidence-driven elicitation approaches typically involve techniques to derive more accurate probability distributions under fairly specific contexts. Experts are, however, prone to overconfidence in their judgements. Group elicitations with diverse experts can reduce expert overconfidence by allowing cross-examination and reassessment of prior judgements, but groups are also prone to uncritical “groupthink” errors. When the problem context is underspecified the probability that experts commit groupthink errors may increase. This study addresses how structured workshops affect expert variability among and certainty within responses in a New Zealand case study. We find that experts’ risk estimates before and after a workshop differ, and that group elicitations provided greater consistency of estimates, yet also greater uncertainty among experts, when addressing prominent impacts to four different ecosystem services in coastal New Zealand. After group workshops, experts provided more consistent ranking of risks and more consistent best estimates of impact through increased clarity in terminology and dampening of extreme positions, yet probability distributions for impacts widened. The results from this case study suggest that group elicitations have favorable consequences for the quality and uncertainty of risk judgments within and across experts, making group elicitation techniques invaluable tools in contexts of limited data. PMID:28767694

Effectiveness of Podcasts Delivered on Mobile Devices as a Support for Student Learning during General Chemistry Laboratories

ERIC Educational Resources Information Center

Powell, Cynthia B.; Mason, Diana S.

2013-01-01

Chemistry instructors in teaching laboratories provide expert modeling of techniques and cognitive processes and provide assistance to enrolled students that may be described as scaffolding interaction. Such student support is particularly essential in laboratories taught with an inquiry-based curriculum. In a teaching laboratory with a high…

Does Medical Students' Diagnostic Performance Improve by Observing Examples of Self-Explanation Provided by Peers or Experts?

ERIC Educational Resources Information Center

Chamberland, Martine; Mamede, Sílvia; St-Onge, Christina; Setrakian, Jean; Schmidt, Henk G.

2015-01-01

Educational strategies that promote the development of clinical reasoning in students remain scarce. Generating self-explanations (SE) engages students in active learning and has shown to be an effective technique to improve clinical reasoning in clerks. Example-based learning has been shown to support the development of accurate knowledge…

Delphi in Criminal Justice Policy: A Case Study on Judgmental Forecasting

ERIC Educational Resources Information Center

Loyens, Kim; Maesschalck, Jeroen; Bouckaert, Geert

2011-01-01

This article provides an in-depth case study analysis of a pilot project organized by the section "Strategic Analysis" of the Belgian Federal Police. Using the Delphi method, which is a judgmental forecasting technique, a panel of experts was questioned about future developments of crime, based on their expertise in criminal or social…

Building Literacy in Social Studies: Strategies for Improving Comprehension and Critical Thinking

ERIC Educational Resources Information Center

Klemp, Ron; McBride, Bill; Ogle, Donna

2007-01-01

It's tough to teach social studies and history to students who have trouble reading and understanding textbooks and other resources. But you can overcome those obstacles and motivate students to excel in social studies classes by using the concepts and research-based techniques in this guide. Renowned reading expert Donna Ogle teams up with two…

Model of experts for decision support in the diagnosis of leukemia patients.

PubMed

Corchado, Juan M; De Paz, Juan F; Rodríguez, Sara; Bajo, Javier

2009-07-01

Recent advances in the field of biomedicine, specifically in the field of genomics, have led to an increase in the information available for conducting expression analysis. Expression analysis is a technique used in transcriptomics, a branch of genomics that deals with the study of messenger ribonucleic acid (mRNA) and the extraction of information contained in the genes. This increase in information is reflected in the exon arrays, which require the use of new techniques in order to extract the information. The purpose of this study is to provide a tool based on a mixture of experts model that allows the analysis of the information contained in the exon arrays, from which automatic classifications for decision support in diagnoses of leukemia patients can be made. The proposed model integrates several cooperative algorithms characterized for their efficiency for data processing, filtering, classification and knowledge extraction. The Cancer Institute of the University of Salamanca is making an effort to develop tools to automate the evaluation of data and to facilitate de analysis of information. This proposal is a step forward in this direction and the first step toward the development of a mixture of experts tool that integrates different cognitive and statistical approaches to deal with the analysis of exon arrays. The mixture of experts model presented within this work provides great capacities for learning and adaptation to the characteristics of the problem in consideration, using novel algorithms in each of the stages of the analysis process that can be easily configured and combined, and provides results that notably improve those provided by the existing methods for exon arrays analysis. The material used consists of data from exon arrays provided by the Cancer Institute that contain samples from leukemia patients. The methodology used consists of a system based on a mixture of experts. Each one of the experts incorporates novel artificial intelligence techniques that improve the process of carrying out various tasks such as pre-processing, filtering, classification and extraction of knowledge. This article will detail the manner in which individual experts are combined so that together they generate a system capable of extracting knowledge, thus permitting patients to be classified in an automatic and efficient manner that is also comprehensible for medical personnel. The system has been tested in a real setting and has been used for classifying patients who suffer from different forms of leukemia at various stages. Personnel from the Cancer Institute supervised and participated throughout the testing period. Preliminary results are promising, notably improving the results obtained with previously used tools. The medical staff from the Cancer Institute considers the tools that have been developed to be positive and very useful in a supporting capacity for carrying out their daily tasks. Additionally the mixture of experts supplies a tool for the extraction of necessary information in order to explain the associations that have been made in simple terms. That is, it permits the extraction of knowledge for each classification made and generalized in order to be used in subsequent classifications. This allows for a large amount of learning and adaptation within the proposed system.

An expert system shell for inferring vegetation characteristics: Implementation of additional techniques (task E)

NASA Technical Reports Server (NTRS)

Harrison, P. Ann

1992-01-01

The NASA VEGetation Workbench (VEG) is a knowledge based system that infers vegetation characteristics from reflectance data. The VEG subgoal PROPORTION.GROUND.COVER has been completed and a number of additional techniques that infer the proportion ground cover of a sample have been implemented. Some techniques operate on sample data at a single wavelength. The techniques previously incorporated in VEG for other subgoals operated on data at a single wavelength so implementing the additional single wavelength techniques required no changes to the structure of VEG. Two techniques which use data at multiple wavelengths to infer proportion ground cover were also implemented. This work involved modifying the structure of VEG so that multiple wavelength techniques could be incorporated. All the new techniques were tested using both the VEG 'Research Mode' and the 'Automatic Mode.'

Knowledge acquisition for medical diagnosis using collective intelligence.

PubMed

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

2012-11-01

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

Using Vector and Extended Boolean Matching in an Expert System for Selecting Foster Homes.

ERIC Educational Resources Information Center

Fox, Edward A.; Winett, Sheila G.

1990-01-01

Describes FOCES (Foster Care Expert System), a prototype expert system for choosing foster care placements for children which integrates information retrieval techniques with artificial intelligence. The use of prototypes and queries in Prolog routines, extended Boolean matching, and vector correlation are explained, as well as evaluation by…

CRN5EXP: Expert system for statistical quality control

NASA Technical Reports Server (NTRS)

Hentea, Mariana

1991-01-01

The purpose of the Expert System CRN5EXP is to assist in checking the quality of the coils at two very important mills: Hot Rolling and Cold Rolling in a steel plant. The system interprets the statistical quality control charts, diagnoses and predicts the quality of the steel. Measurements of process control variables are recorded in a database and sample statistics such as the mean and the range are computed and plotted on a control chart. The chart is analyzed through patterns using the C Language Integrated Production System (CLIPS) and a forward chaining technique to reach a conclusion about the causes of defects and to take management measures for the improvement of the quality control techniques. The Expert System combines the certainty factors associated with the process control variables to predict the quality of the steel. The paper presents the approach to extract data from the database, the reason to combine certainty factors, the architecture and the use of the Expert System. However, the interpretation of control charts patterns requires the human expert's knowledge and lends to Expert Systems rules.

Assessing nutrient flows in septic tanks by eliciting expert judgement: a promising method in the context of developing countries.

PubMed

Montangero, Agnes; Belevi, Hasan

2007-03-01

Simple models based on the physical and biochemical processes occurring in septic tanks, pit and urine diversion latrines were developed to determine the nutrient flows in these systems. Nitrogen and phosphorus separation in different output materials from these on-site sanitation installations were thus determined. Moreover, nutrient separation in septic tanks was also assessed through literature values and by eliciting expert judgement. Use of formal expert elicitation technique proved to be effective, particularly in the context of developing countries where data is often scarce but expert judgement readily available. In Vietnam, only 5-14% and 11-27% of the nitrogen and phosphorus input, respectively, are removed from septic tanks with the faecal sludge. The remaining fraction leaves the tank via the liquid effluent. Unlike septic tanks, urine diversion latrines allow to immobilize most of the nutrients either in form of stored urine or dehydrated faecal matter. These latrines thus contribute to reducing the nutrient load in the environment and lowering consumption of energy and non-renewable resources for fertiliser production.

EULAR recommendations for conducting clinical studies and/or clinical trials in systemic vasculitis: focus on anti‐neutrophil cytoplasm antibody‐associated vasculitis

PubMed Central

Hellmich, Bernhard; Flossmann, Oliver; Gross, Wolfgang L; Bacon, Paul; Cohen‐Tervaert, Jan Willem; Guillevin, Loic; Jayne, David; Mahr, Alfred; Merkel, Peter A; Raspe, Heiner; Scott, David G I; Witter, James; Yazici, Hasan; Luqmani, Raashid A

2007-01-01

Objectives To develop the European League Against Rheumatism (EULAR) recommendations for conducting clinical studies and/or clinical trials in systemic vasculitis. Methods An expert consensus group was formed consisting of rheumatologists, nephrologists and specialists in internal medicine representing five European countries and the USA, a clinical epidemiologist and representatives from regulatory agencies. Using an evidence‐based and expert opinion‐based approach in accordance with the standardised EULAR operating procedures, the group identified nine topics for a systematic literature search through a modified Delphi technique. On the basis of research questions posed by the group, recommendations were derived for conducting clinical studies and/or clinical trials in systemic vasculitis. Results Based on the results of the literature research, the expert committee concluded that sufficient evidence to formulate guidelines on conducting clinical trials was available only for anti‐neutrophil cytoplasm antibody‐associated vasculitides (AAV). It was therefore decided to focus the recommendations on these diseases. Recommendations for conducting clinical trials in AAV were elaborated and are presented in this summary document. It was decided to consider vasculitis‐specific issues rather than general issues of trial methodology. The recommendations deal with the following areas related to clinical studies of vasculitis: definitions of disease, activity states, outcome measures, eligibility criteria, trial design including relevant end points, and biomarkers. A number of aspects of trial methodology were deemed important for future research. Conclusions On the basis of expert opinion, recommendations for conducting clinical trials in AAV were formulated. Furthermore, the expert committee identified a strong need for well‐designed research in non‐AAV systemic vasculitides. PMID:17170053

Identification and management of comorbidity in psoriatic arthritis: evidence- and expert-based recommendations from a multidisciplinary panel from Spain.

PubMed

Torre-Alonso, Juan Carlos; Carmona, Loreto; Moreno, Mireia; Galíndez, Eva; Babío, Jesús; Zarco, Pedro; Linares, Luis; Collantes-Estevez, Eduardo; Barrial, Manuel Fernández; Hermosa, Juan Carlos; Coto, Pablo; Suárez, Carmen; Almodóvar, Raquel; Luelmo, Jesús; Castañeda, Santos; Gratacós, Jordi

2017-08-01

The objective is to establish recommendations, based on evidence and expert opinion, for the identification and management of comorbidities in patients with psoriatic arthritis (PsA). The following techniques were applied: discussion group, systematic review, and Delphi survey for agreement. A panel of professionals from four specialties defined the users, the sections of the document, possible recommendations, and what systematic reviews should be performed. A second discussion was held with the results of the systematic reviews. Recommendations were formulated in the second meeting and voted online from 1 (total disagreement) to 10 (total agreement). Agreement was considered if at least 70% voted ≥7. The level of evidence and grade of recommendation were assigned using the Oxford Centre for Evidence-Based Medicine guidance. The full document was critically appraised by the experts, and the project was supervised at all times by a methodologist. In a final step, the document was reviewed and commented by a patient and a health management specialist. Fourteen recommendations were produced, together with a checklist to facilitate the implementation. The items with the largest support from evidence were those related to cardiovascular disease and risk factors. The panel recommends paying special attention to obesity, smoking, and alcohol consumption, as they are all modifiable factors with an impact on treatment response or complications of PsA. Psychological and organizational aspects were also deemed important. We herein suggest practical recommendations for the management of comorbidities in PsA based on evidence and expert opinion.

Fluorescein angiography-based diagnosis for retinopathy of prematurity: expert-non expert comparison.

PubMed

Guagliano, Rosanna; Barillà, Donatella; Bertone, Chiara; Maffia, Anna; Periti, Francesca; Spallone, Laura; Anselmetti, Giovanni; Giacosa, Elisabetta; Stronati, Mauro; Tinelli, Carmine; Bianchi, Paolo Emilio

2013-01-01

To evaluate accuracy and inter-rater reliability of RetCam fundus images and digital camera fluorangioscopic images in acute retinopathy of prematurity (ROP) by comparing diagnoses given by trainee ophthalmologists with those provided by expert ophthalmologists. 
 This is a multicenter retrospective observational study of diagnostic data from 48 eyes of 24 premature infants with classical ROP, stage II, as evaluated by RetCam 3 and fluorescein angiography (FA). Average gestational age was 25.4 weeks, average weight 804.7 g. A staging grid (with ocular fundus divided into 3 concentric zones) and 24 15° sectors centered around the optic papilla were superimposed on 360° retina photomontages (Photoshop) made from RetCam and FA images. Non expert vs expert diagnosis agreement was measured for each sector by means of Cohen kappa (Fleiss, 1981).
 A high degree of concordance was found. Inter-rater agreement between expert and non expert interpretations of retinal photomontages was greater for fluorangiographic images than for RetCam images, with κ = 0.61-1 for 120/152 (78.9%) sectors examined on the RetCam images and 
κ = 0.61-1 for 168/198 (84.8%) sectors examined on the FA images.
 The FA images appear to be easier to interpret than RetCam images, both by expert and non expert ophthalmologists. The results confirm that FA is a good examination technique with a high degree of reliability, even where trainee practitioners are involved. This suggests that retinopathy management can be improved by entrusting diagnostic responsibilities to trainee ophthalmologists, in order to extend access to correct diagnosis, recognition of threshold lesions, and prompt treatment.

Test blueprints for psychiatry residency in-training written examinations in Riyadh, Saudi Arabia

PubMed Central

Gaffas, Eisha M; Sequeira, Reginald P; Namla, Riyadh A Al; Al-Harbi, Khalid S

2012-01-01

Background The postgraduate training program in psychiatry in Saudi Arabia, which was established in 1997, is a 4-year residency program. Written exams comprising of multiple choice questions (MCQs) are used as a summative assessment of residents in order to determine their eligibility for promotion from one year to the next. Test blueprints are not used in preparing examinations. Objective To develop test blueprints for the written examinations used in the psychiatry residency program. Methods Based on the guidelines of four professional bodies, documentary analysis was used to develop global and detailed test blueprints for each year of the residency program. An expert panel participated during piloting and final modification of the test blueprints. Their opinion about the content, weightage for each content domain, and proportion of test items to be sampled in each cognitive category as defined by modified Bloom’s taxonomy were elicited. Results Eight global and detailed test blueprints, two for each year of the psychiatry residency program, were developed. The global test blueprints were reviewed by experts and piloted. Six experts participated in the final modification of test blueprints. Based on expert consensus, the content, total weightage for each content domain, and proportion of test items to be included in each cognitive category were determined for each global test blueprint. Experts also suggested progressively decreasing the weightage for recall test items and increasing problem solving test items in examinations, from year 1 to year 4 of the psychiatry residence program. Conclusion A systematic approach using a documentary and content analysis technique was used to develop test blueprints with additional input from an expert panel as appropriate. Test blueprinting is an important step to ensure the test validity in all residency programs. PMID:23762000

Test blueprints for psychiatry residency in-training written examinations in Riyadh, Saudi Arabia.

PubMed

Gaffas, Eisha M; Sequeira, Reginald P; Namla, Riyadh A Al; Al-Harbi, Khalid S

2012-01-01

The postgraduate training program in psychiatry in Saudi Arabia, which was established in 1997, is a 4-year residency program. Written exams comprising of multiple choice questions (MCQs) are used as a summative assessment of residents in order to determine their eligibility for promotion from one year to the next. Test blueprints are not used in preparing examinations. To develop test blueprints for the written examinations used in the psychiatry residency program. Based on the guidelines of four professional bodies, documentary analysis was used to develop global and detailed test blueprints for each year of the residency program. An expert panel participated during piloting and final modification of the test blueprints. Their opinion about the content, weightage for each content domain, and proportion of test items to be sampled in each cognitive category as defined by modified Bloom's taxonomy were elicited. Eight global and detailed test blueprints, two for each year of the psychiatry residency program, were developed. The global test blueprints were reviewed by experts and piloted. Six experts participated in the final modification of test blueprints. Based on expert consensus, the content, total weightage for each content domain, and proportion of test items to be included in each cognitive category were determined for each global test blueprint. Experts also suggested progressively decreasing the weightage for recall test items and increasing problem solving test items in examinations, from year 1 to year 4 of the psychiatry residence program. A systematic approach using a documentary and content analysis technique was used to develop test blueprints with additional input from an expert panel as appropriate. Test blueprinting is an important step to ensure the test validity in all residency programs.

Expert consensus contouring guidelines for IMRT in esophageal and gastroesophageal junction cancer

PubMed Central

Wu, Abraham J.; Bosch, Walter R.; Chang, Daniel T.; Hong, Theodore S.; Jabbour, Salma K.; Kleinberg, Lawrence R.; Mamon, Harvey J.; Thomas, Charles R.; Goodman, Karyn A.

2015-01-01

Purpose/Objective(s) Current guidelines for esophageal cancer contouring are derived from traditional two-dimensional fields based on bony landmarks, and do not provide sufficient anatomical detail to ensure consistent contouring for more conformal radiotherapy techniques such as intensity-modulated radiation therapy (IMRT). Therefore, we convened an expert panel with the specific aim to derive contouring guidelines and generate an atlas for the clinical target volume (CTV) in esophageal or gastroesophageal junction (GEJ) cancer. Methods and Materials Eight expert academically-based gastrointestinal radiation oncologists participated. Three sample cases were chosen: a GEJ cancer, a distal esophageal cancer, and a mid-upper esophageal cancer. Uniform CT simulation datasets and an accompanying diagnostic PET-CT were distributed to each expert, and he/she was instructed to generate gross tumor volume (GTV) and CTV contours for each case. All contours were aggregated and subjected to quantitative analysis to assess the degree of concordance between experts and generate draft consensus contours. The panel then refined these contours to generate the contouring atlas. Results Kappa statistics indicated substantial agreement between panelists for each of the three test cases. A consensus CTV atlas was generated for the three test cases, each representing common anatomic presentations of esophageal cancer. The panel agreed on guidelines and principles to facilitate the generalizability of the atlas to individual cases. Conclusions This expert panel successfully reached agreement on contouring guidelines for esophageal and GEJ IMRT and generated a reference CTV atlas. This atlas will serve as a reference for IMRT contours for clinical practice and prospective trial design. Subsequent patterns of failure analyses of clinical datasets utilizing these guidelines may require modification in the future. PMID:26104943

Ultrasound Guidance for Botulinum Neurotoxin Chemodenervation Procedures.

PubMed

Alter, Katharine E; Karp, Barbara I

2017-12-28

Injections of botulinum neurotoxins (BoNTs) are prescribed by clinicians for a variety of disorders that cause over-activity of muscles; glands; pain and other structures. Accurately targeting the structure for injection is one of the principle goals when performing BoNTs procedures. Traditionally; injections have been guided by anatomic landmarks; palpation; range of motion; electromyography or electrical stimulation. Ultrasound (US) based imaging based guidance overcomes some of the limitations of traditional techniques. US and/or US combined with traditional guidance techniques is utilized and or recommended by many expert clinicians; authors and in practice guidelines by professional academies. This article reviews the advantages and disadvantages of available guidance techniques including US as well as technical aspects of US guidance and a focused literature review related to US guidance for chemodenervation procedures including BoNTs injection.

SSME fault monitoring and diagnosis expert system

NASA Technical Reports Server (NTRS)

Ali, Moonis; Norman, Arnold M.; Gupta, U. K.

1989-01-01

An expert system, called LEADER, has been designed and implemented for automatic learning, detection, identification, verification, and correction of anomalous propulsion system operations in real time. LEADER employs a set of sensors to monitor engine component performance and to detect, identify, and validate abnormalities with respect to varying engine dynamics and behavior. Two diagnostic approaches are adopted in the architecture of LEADER. In the first approach fault diagnosis is performed through learning and identifying engine behavior patterns. LEADER, utilizing this approach, generates few hypotheses about the possible abnormalities. These hypotheses are then validated based on the SSME design and functional knowledge. The second approach directs the processing of engine sensory data and performs reasoning based on the SSME design, functional knowledge, and the deep-level knowledge, i.e., the first principles (physics and mechanics) of SSME subsystems and components. This paper describes LEADER's architecture which integrates a design based reasoning approach with neural network-based fault pattern matching techniques. The fault diagnosis results obtained through the analyses of SSME ground test data are presented and discussed.

Consensus development on the essential competencies for Iranian public health nutritionists.

PubMed

Sadeghi-Ghotbabadi, Farzaneh; Shakibazadeh, Elham; Omidvar, Nasrin; Mortazavi, Fathieh; Kolahdooz, Fariba

2015-03-01

To assess key experts' opinion regarding essential competencies required for effective public health nutrition practice within the health-care system of Iran. Qualitative study using the modified Delphi technique through an email-delivered questionnaire. Iran. Fifty-five experts were contacted through email. The inclusion criterion for the study panel was being in a relevant senior-level position in nutrition science or public health nutrition in Iran. In the first round, forty-two out of fifty-five experts responded to the questionnaire (response rate=76 %). A sixty-five-item questionnaire was designed with nine competency areas, including 'nutrition science', 'planning and implementing nutritional interventions', 'health and nutrition services', 'advocacy and communication', 'assessment and analysis', 'evaluation', 'cultural, social and political aspects', 'using technology' and 'leadership and management'. All experts who had participated in the first round completed a modified version of the questionnaire with seventy-seven items in the second round. The experts scored 'nutrition science' as the most essential competency area, while more applied areas such as 'management and leadership' were less emphasized. In both rounds, the mean difference between the opinions of the necessity of each area was 5.6 %. The Iranian experts had general agreement on most of the core competency areas of public health nutritionists. The results indicated the need for capacity building and revisions to educational curricula for public health nutritionist programmes, with more emphasis on skill-based competency development.

The application of artificial intelligence techniques to large distributed networks

NASA Technical Reports Server (NTRS)

Dubyah, R.; Smith, T. R.; Star, J. L.

1985-01-01

Data accessibility and transfer of information, including the land resources information system pilot, are structured as large computer information networks. These pilot efforts include the reduction of the difficulty to find and use data, reducing processing costs, and minimize incompatibility between data sources. Artificial Intelligence (AI) techniques were suggested to achieve these goals. The applicability of certain AI techniques are explored in the context of distributed problem solving systems and the pilot land data system (PLDS). The topics discussed include: PLDS and its data processing requirements, expert systems and PLDS, distributed problem solving systems, AI problem solving paradigms, query processing, and distributed data bases.

Knowledge-Based Reinforcement Learning for Data Mining

NASA Astrophysics Data System (ADS)

Kudenko, Daniel; Grzes, Marek

Data Mining is the process of extracting patterns from data. Two general avenues of research in the intersecting areas of agents and data mining can be distinguished. The first approach is concerned with mining an agent’s observation data in order to extract patterns, categorize environment states, and/or make predictions of future states. In this setting, data is normally available as a batch, and the agent’s actions and goals are often independent of the data mining task. The data collection is mainly considered as a side effect of the agent’s activities. Machine learning techniques applied in such situations fall into the class of supervised learning. In contrast, the second scenario occurs where an agent is actively performing the data mining, and is responsible for the data collection itself. For example, a mobile network agent is acquiring and processing data (where the acquisition may incur a certain cost), or a mobile sensor agent is moving in a (perhaps hostile) environment, collecting and processing sensor readings. In these settings, the tasks of the agent and the data mining are highly intertwined and interdependent (or even identical). Supervised learning is not a suitable technique for these cases. Reinforcement Learning (RL) enables an agent to learn from experience (in form of reward and punishment for explorative actions) and adapt to new situations, without a teacher. RL is an ideal learning technique for these data mining scenarios, because it fits the agent paradigm of continuous sensing and acting, and the RL agent is able to learn to make decisions on the sampling of the environment which provides the data. Nevertheless, RL still suffers from scalability problems, which have prevented its successful use in many complex real-world domains. The more complex the tasks, the longer it takes a reinforcement learning algorithm to converge to a good solution. For many real-world tasks, human expert knowledge is available. For example, human experts have developed heuristics that help them in planning and scheduling resources in their work place. However, this domain knowledge is often rough and incomplete. When the domain knowledge is used directly by an automated expert system, the solutions are often sub-optimal, due to the incompleteness of the knowledge, the uncertainty of environments, and the possibility to encounter unexpected situations. RL, on the other hand, can overcome the weaknesses of the heuristic domain knowledge and produce optimal solutions. In the talk we propose two techniques, which represent first steps in the area of knowledge-based RL (KBRL). The first technique [1] uses high-level STRIPS operator knowledge in reward shaping to focus the search for the optimal policy. Empirical results show that the plan-based reward shaping approach outperforms other RL techniques, including alternative manual and MDP-based reward shaping when it is used in its basic form. We showed that MDP-based reward shaping may fail and successful experiments with STRIPS-based shaping suggest modifications which can overcome encountered problems. The STRIPSbased method we propose allows expressing the same domain knowledge in a different way and the domain expert can choose whether to define an MDP or STRIPS planning task. We also evaluated the robustness of the proposed STRIPS-based technique to errors in the plan knowledge. In case that STRIPS knowledge is not available, we propose a second technique [2] that shapes the reward with hierarchical tile coding. Where the Q-function is represented with low-level tile coding, a V-function with coarser tile coding can be learned in parallel and used to approximate the potential for ground states. In the context of data mining, our KBRL approaches can also be used for any data collection task where the acquisition of data may incur considerable cost. In addition, observing the data collection agent in specific scenarios may lead to new insights into optimal data collection behaviour in the respective domains. In future work, we intend to demonstrate and evaluate our techniques on concrete real-world data mining applications.

A review of techniques to determine alternative selection in design for remanufacturing

NASA Astrophysics Data System (ADS)

Noor, A. Z. Mohamed; Fauadi, M. H. F. Md; Jafar, F. A.; Mohamad, N. R.; Yunos, A. S. Mohd

2017-10-01

This paper discusses the techniques used for optimization in manufacturing system. Although problem domain is focused on sustainable manufacturing, techniques used to optimize general manufacturing system were also discussed. Important aspects of Design for Remanufacturing (DFReM) considered include indexes, weighted average, grey decision making and Fuzzy TOPSIS. The limitation of existing techniques are most of them is highly based on decision maker’s perspective. Different experts may have different understanding and eventually scale it differently. Therefore, the objective of this paper is to determine available techniques and identify the lacking feature in it. Once all the techniques have been reviewed, a decision will be made by create another technique which should counter the lacking of discussed techniques. In this paper, shows that the hybrid computation of Fuzzy Analytic Hierarchy Process (AHP) and Artificial Neural Network (ANN) is suitable and fill the gap of all discussed technique.

An advanced artificial intelligence tool for menu design.

PubMed

Khan, Abdus Salam; Hoffmann, Achim

2003-01-01

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

Fuzzy logic and neural networks in artificial intelligence and pattern recognition

NASA Astrophysics Data System (ADS)

Sanchez, Elie

1991-10-01

With the use of fuzzy logic techniques, neural computing can be integrated in symbolic reasoning to solve complex real world problems. In fact, artificial neural networks, expert systems, and fuzzy logic systems, in the context of approximate reasoning, share common features and techniques. A model of Fuzzy Connectionist Expert System is introduced, in which an artificial neural network is designed to construct the knowledge base of an expert system from, training examples (this model can also be used for specifications of rules in fuzzy logic control). Two types of weights are associated with the synaptic connections in an AND-OR structure: primary linguistic weights, interpreted as labels of fuzzy sets, and secondary numerical weights. Cell activation is computed through min-max fuzzy equations of the weights. Learning consists in finding the (numerical) weights and the network topology. This feedforward network is described and first illustrated in a biomedical application (medical diagnosis assistance from inflammatory-syndromes/proteins profiles). Then, it is shown how this methodology can be utilized for handwritten pattern recognition (characters play the role of diagnoses): in a fuzzy neuron describing a number for example, the linguistic weights represent fuzzy sets on cross-detecting lines and the numerical weights reflect the importance (or weakness) of connections between cross-detecting lines and characters.

International Summit on Laparoscopic Pancreatic Resection (ISLPR) "Coimbatore Summit Statements".

PubMed

Palanivelu, Chinnusamy; Takaori, Kyoichi; Abu Hilal, Mohammad; Kooby, David A; Wakabayashi, Go; Agarwal, Anil; Berti, Stefano; Besselink, Marc G; Chen, Kuo Hsin; Gumbs, Andrew A; Han, Ho-Seong; Honda, Goro; Khatkov, Igor; Kim, Hong Jin; Li, Jiang Tao; Duy Long, Tran Cong; Machado, Marcel Autran; Matsushita, Akira; Menon, Krish; Min-Hua, Zheng; Nakamura, Masafumi; Nagakawa, Yuichi; Pekolj, Juan; Poves, Ignasi; Rahman, Shahidur; Rong, Liu; Sa Cunha, Antonio; Senthilnathan, Palanisamy; Shrikhande, Shailesh V; Gurumurthy, S Srivatsan; Sup Yoon, Dong; Yoon, Yoo-Seok; Khatri, Vijay P

2018-03-01

The International Summit on Laparoscopic Pancreatic Resection (ISLPR) was held in Coimbatore, India, on 7th and 8th of October 2016 and thirty international experts who regularly perform laparoscopic pancreatic resections participated in ISPLR from four continents, i.e., South and North America, Europe and Asia. Prior to ISLPR, the first conversation among the experts was made online on August 26th, 2016 and the structures of ISPLR were developed. The aims of ISPLR were; i) to identify indications and optimal case selection criteria for minimally invasive pancreatic resection (MIPR) in the setting of both benign and malignant diseases; ii) standardization of techniques to increase the safety of MIPR; iii) identification of common problems faced during MIPR and developing associated management strategies; iv) development of clinical protocols to allow early identification of complications and develop the accompanying management plan to minimize morbidity and mortality. As a process for interactive discussion, the experts were requested to complete an online questionnaire consisting of 65 questions about the various technical aspects of laparoscopic pancreatic resections. Two further web-based meetings were conducted prior to ISPLR. Through further discussion during ISPLR, we have created productive statements regarding the topics of Disease, Implementation, Patients, Techniques, and Instrumentations (DIPTI) and hereby publish them as "Coimbatore Summit Statements". Copyright © 2018 Elsevier Ltd. All rights reserved.

Idea Generation and Exploration: Benefits and Limitations of the Policy Delphi Research Method

ERIC Educational Resources Information Center

Franklin, Kathy K.; Hart, Jan K.

2007-01-01

Researchers use the policy Delphi method to explore a complex topic with little historical context that requires expert opinion to fully understand underlying issues. The benefit of this research technique is the use of experts who have more timely information than can be gleamed from extant literature. Additionally, those experts place…

Cooperative analysis expert situation assessment research

NASA Technical Reports Server (NTRS)

Mccown, Michael G.

1987-01-01

For the past few decades, Rome Air Development Center (RADC) has been conducting research in Artificial Intelligence (AI). When the recent advances in hardware technology made many AI techniques practical, the Intelligence and Reconnaissance Directorate of RADC initiated an applications program entitled Knowledge Based Intelligence Systems (KBIS). The goal of the program is the development of a generic Intelligent Analyst System, an open machine with the framework for intelligence analysis, natural language processing, and man-machine interface techniques, needing only the specific problem domain knowledge to be operationally useful. The development of KBIS is described.

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.

Experts: despite time constraints, motivational interviewing techniques can have lasting impact on drinkers, drug abusers.

PubMed

2013-04-01

Researchers have found that the Brief Negotiation Interview (BNI), a tool developed at Yale School of Medicine in New Haven, CT, can curb harmful drinking in patients when the tool is used with these patients in the emergency setting. Further, by using the same motivational interviewing techniques employed in the tool, experts say providers can help patients curb other harmful behaviors as well. The BNI consists of a series of questions that take about seven minutes to discuss with patients. The tool prompts patients to come up with their own reasons for changing harmful behaviors. To implement the BNI, emergency providers need training and constant reinforcement. Ideally, experts say the motivational interviewing techniques employed in the BNI need to become routine to have a lasting impact on patient care.

On Evaluating Brain Tissue Classifiers without a Ground Truth

PubMed Central

Martin-Fernandez, Marcos; Ungar, Lida; Nakamura, Motoaki; Koo, Min-Seong; McCarley, Robert W.; Shenton, Martha E.

2009-01-01

In this paper, we present a set of techniques for the evaluation of brain tissue classifiers on a large data set of MR images of the head. Due to the difficulty of establishing a gold standard for this type of data, we focus our attention on methods which do not require a ground truth, but instead rely on a common agreement principle. Three different techniques are presented: the Williams’ index, a measure of common agreement; STAPLE, an Expectation Maximization algorithm which simultaneously estimates performance parameters and constructs an estimated reference standard; and Multidimensional Scaling, a visualization technique to explore similarity data. We apply these different evaluation methodologies to a set eleven different segmentation algorithms on forty MR images. We then validate our evaluation pipeline by building a ground truth based on human expert tracings. The evaluations with and without a ground truth are compared. Our findings show that comparing classifiers without a gold standard can provide a lot of interesting information. In particular, outliers can be easily detected, strongly consistent or highly variable techniques can be readily discriminated, and the overall similarity between different techniques can be assessed. On the other hand, we also find that some information present in the expert segmentations is not captured by the automatic classifiers, suggesting that common agreement alone may not be sufficient for a precise performance evaluation of brain tissue classifiers. PMID:17532646

Determination of Secondary Students' Preferences Regarding Design Features Used in Digital Textbooks

ERIC Educational Resources Information Center

Öngöz, Sakine; Mollamehmetoglu, Mehmet Zülküf

2017-01-01

The aim of this study was to determine secondary school students' choice of design features for digital textbooks. As a part of the research--which was conducted using a mixed technique--a literature review was carried out to source points to consider in the designing of digital textbooks and experts' opinions were obtained. Based on the results,…

Quality Space and Launch Requirements Addendum to AS9100C

DTIC Science & Technology

2015-03-05

45 8.9.1 Statistical Process Control (SPC) .......................................................................... 45 8.9.1.1 Out of Control...Systems Center SME Subject Matter Expert SOW Statement of Work SPC Statistical Process Control SPO System Program Office SRP Standard Repair...individual data exceeding the control limits. Control limits are developed using standard statistical methods or other approved techniques and are based on

Formal Verification at System Level

NASA Astrophysics Data System (ADS)

Mazzini, S.; Puri, S.; Mari, F.; Melatti, I.; Tronci, E.

2009-05-01

System Level Analysis calls for a language comprehensible to experts with different background and yet precise enough to support meaningful analyses. SysML is emerging as an effective balance between such conflicting goals. In this paper we outline some the results obtained as for SysML based system level functional formal verification by an ESA/ESTEC study, with a collaboration among INTECS and La Sapienza University of Roma. The study focuses on SysML based system level functional requirements techniques.

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.

Classifying Facial Actions

PubMed Central

Donato, Gianluca; Bartlett, Marian Stewart; Hager, Joseph C.; Ekman, Paul; Sejnowski, Terrence J.

2010-01-01

The Facial Action Coding System (FACS) [23] is an objective method for quantifying facial movement in terms of component actions. This system is widely used in behavioral investigations of emotion, cognitive processes, and social interaction. The coding is presently performed by highly trained human experts. This paper explores and compares techniques for automatically recognizing facial actions in sequences of images. These techniques include analysis of facial motion through estimation of optical flow; holistic spatial analysis, such as principal component analysis, independent component analysis, local feature analysis, and linear discriminant analysis; and methods based on the outputs of local filters, such as Gabor wavelet representations and local principal components. Performance of these systems is compared to naive and expert human subjects. Best performances were obtained using the Gabor wavelet representation and the independent component representation, both of which achieved 96 percent accuracy for classifying 12 facial actions of the upper and lower face. The results provide converging evidence for the importance of using local filters, high spatial frequencies, and statistical independence for classifying facial actions. PMID:21188284

Assessing Food Preferences in Dogs and Cats: A Review of the Current Methods

PubMed Central

Tobie, Christelle; Péron, Franck; Larose, Claire

2015-01-01

Simple Summary The objective of this review is to present the different approaches and techniques used to assess petfood palatability, either with expert panels or naïve individuals (in-home panels). Abstract Food is a major aspect of pet care; therefore, ensuring that pet foods are not only healthful but attractive to companion animals and their owners is essential. The petfood market remains active and requires ongoing evaluation of the adaptation and efficiency of the new products. Palatability—foods’ characteristics enticing animals and leading them to consumption—is therefore a key element to look at. Based on the type of information needed, different pet populations (expert or naïve) can be tested to access their preference and acceptance for different food products. Classical techniques are the one-bowl and two-bowl tests, but complementary (i.e., operant conditioning) and novel (i.e., exploratory behavior) approaches are available to gather more information on the evaluation of petfood palatability. PMID:26479142

Extending Correlation Filter-Based Visual Tracking by Tree-Structured Ensemble and Spatial Windowing.

PubMed

Gundogdu, Erhan; Ozkan, Huseyin; Alatan, A Aydin

2017-11-01

Correlation filters have been successfully used in visual tracking due to their modeling power and computational efficiency. However, the state-of-the-art correlation filter-based (CFB) tracking algorithms tend to quickly discard the previous poses of the target, since they consider only a single filter in their models. On the contrary, our approach is to register multiple CFB trackers for previous poses and exploit the registered knowledge when an appearance change occurs. To this end, we propose a novel tracking algorithm [of complexity O(D) ] based on a large ensemble of CFB trackers. The ensemble [of size O(2 D ) ] is organized over a binary tree (depth D ), and learns the target appearance subspaces such that each constituent tracker becomes an expert of a certain appearance. During tracking, the proposed algorithm combines only the appearance-aware relevant experts to produce boosted tracking decisions. Additionally, we propose a versatile spatial windowing technique to enhance the individual expert trackers. For this purpose, spatial windows are learned for target objects as well as the correlation filters and then the windowed regions are processed for more robust correlations. In our extensive experiments on benchmark datasets, we achieve a substantial performance increase by using the proposed tracking algorithm together with the spatial windowing.

Predicting adherence of patients with HF through machine learning techniques.

PubMed

Karanasiou, Georgia Spiridon; Tripoliti, Evanthia Eleftherios; Papadopoulos, Theofilos Grigorios; Kalatzis, Fanis Georgios; Goletsis, Yorgos; Naka, Katerina Kyriakos; Bechlioulis, Aris; Errachid, Abdelhamid; Fotiadis, Dimitrios Ioannis

2016-09-01

Heart failure (HF) is a chronic disease characterised by poor quality of life, recurrent hospitalisation and high mortality. Adherence of patient to treatment suggested by the experts has been proven a significant deterrent of the above-mentioned serious consequences. However, the non-adherence rates are significantly high; a fact that highlights the importance of predicting the adherence of the patient and enabling experts to adjust accordingly patient monitoring and management. The aim of this work is to predict the adherence of patients with HF, through the application of machine learning techniques. Specifically, it aims to classify a patient not only as medication adherent or not, but also as adherent or not in terms of medication, nutrition and physical activity (global adherent). Two classification problems are addressed: (i) if the patient is global adherent or not and (ii) if the patient is medication adherent or not. About 11 classification algorithms are employed and combined with feature selection and resampling techniques. The classifiers are evaluated on a dataset of 90 patients. The patients are characterised as medication and global adherent, based on clinician estimation. The highest detection accuracy is 82 and 91% for the first and the second classification problem, respectively.

Program risk analysis handbook

NASA Technical Reports Server (NTRS)

Batson, R. G.

1987-01-01

NASA regulations specify that formal risk analysis be performed on a program at each of several milestones. Program risk analysis is discussed as a systems analysis approach, an iterative process (identification, assessment, management), and a collection of techniques. These techniques, which range from extremely simple to complex network-based simulation, are described in this handbook in order to provide both analyst and manager with a guide for selection of the most appropriate technique. All program risk assessment techniques are shown to be based on elicitation and encoding of subjective probability estimates from the various area experts on a program. Techniques to encode the five most common distribution types are given. Then, a total of twelve distinct approaches to risk assessment are given. Steps involved, good and bad points, time involved, and degree of computer support needed are listed. Why risk analysis should be used by all NASA program managers is discussed. Tools available at NASA-MSFC are identified, along with commercially available software. Bibliography (150 entries) and a program risk analysis check-list are provided.

Steps in Moving Evidence-Based Health Informatics from Theory to Practice.

PubMed

Rigby, Michael; Magrabi, Farah; Scott, Philip; Doupi, Persephone; Hypponen, Hannele; Ammenwerth, Elske

2016-10-01

To demonstrate and promote the importance of applying a scientific process to health IT design and implementation, and of basing this on research principles and techniques. A review by international experts linked to the IMIA Working Group on Technology Assessment and Quality Development. Four approaches are presented, linking to the creation of national professional expectations, adherence to research-based standards, quality assurance approaches to ensure safety, and scientific measurement of impact. Solely marketing- and aspiration-based approaches to health informatics applications are no longer ethical or acceptable when scientifically grounded evidence-based approaches are available and in use.

Identifying psychophysiological indices of expert vs. novice performance in deadly force judgment and decision making

PubMed Central

Johnson, Robin R.; Stone, Bradly T.; Miranda, Carrie M.; Vila, Bryan; James, Lois; James, Stephen M.; Rubio, Roberto F.; Berka, Chris

2014-01-01

Objective: To demonstrate that psychophysiology may have applications for objective assessment of expertise development in deadly force judgment and decision making (DFJDM). Background: Modern training techniques focus on improving decision-making skills with participative assessment between trainees and subject matter experts primarily through subjective observation. Objective metrics need to be developed. The current proof of concept study explored the potential for psychophysiological metrics in deadly force judgment contexts. Method: Twenty-four participants (novice, expert) were recruited. All wore a wireless Electroencephalography (EEG) device to collect psychophysiological data during high-fidelity simulated deadly force judgment and decision-making simulations using a modified Glock firearm. Participants were exposed to 27 video scenarios, one-third of which would have justified use of deadly force. Pass/fail was determined by whether the participant used deadly force appropriately. Results: Experts had a significantly higher pass rate compared to novices (p < 0.05). Multiple metrics were shown to distinguish novices from experts. Hierarchical regression analyses indicate that psychophysiological variables are able to explain 72% of the variability in expert performance, but only 37% in novices. Discriminant function analysis (DFA) using psychophysiological metrics was able to discern between experts and novices with 72.6% accuracy. Conclusion: While limited due to small sample size, the results suggest that psychophysiology may be developed for use as an objective measure of expertise in DFDJM. Specifically, discriminant function measures may have the potential to objectively identify expert skill acquisition. Application: Psychophysiological metrics may create a performance model with the potential to optimize simulator-based DFJDM training. These performance models could be used for trainee feedback, and/or by the instructor to assess performance objectively. PMID:25100966

Quality of Expert Systems: Methods and Techniques (Kwaliteit van Expertsystemen: Methoden en Technieken)

DTIC Science & Technology

1989-12-01

en Elektroniscb Laboratorium TNO (FEL-TNO), de Rijksuniversiteit Limburg (RL) en bet Research Instituut voor Kennis-Systemen (RIKS). In dit rapport...kwaliteitsbeheersing van kennissystemen. TNO rapport Pagina 2 report no : FEL-89-A267 bee Quality of Expert Systems: Methods and Techniques author(s) J.H.J. Lenting MA...Defence Research and Development. Participants in the project are TNO Physics and Electronics Laboratory (FEL-TNO), University of Limburg (RL) and

Utilization of artificial intelligence techniques for the Space Station power system

NASA Technical Reports Server (NTRS)

Evatt, Thomas C.; Gholdston, Edward W.

1988-01-01

Due to the complexity of the Space Station Electrical Power System (EPS) as currently envisioned, artificial intelligence/expert system techniques are being investigated to automate operations, maintenance, and diagnostic functions. A study was conducted to investigate this technology as it applies to failure detection, isolation, and reconfiguration (FDIR) and health monitoring of power system components and of the total system. Control system utilization of expert systems for load scheduling and shedding operations was also researched. A discussion of the utilization of artificial intelligence/expert systems for Initial Operating Capability (IOC) for the Space Station effort is presented along with future plans at Rocketdyne for the utilization of this technology for enhanced Space Station power capability.

Objective Assessment of Patient Inhaler User Technique Using an Audio-Based Classification Approach.

PubMed

Taylor, Terence E; Zigel, Yaniv; Egan, Clarice; Hughes, Fintan; Costello, Richard W; Reilly, Richard B

2018-02-01

Many patients make critical user technique errors when using pressurised metered dose inhalers (pMDIs) which reduce the clinical efficacy of respiratory medication. Such critical errors include poor actuation coordination (poor timing of medication release during inhalation) and inhaling too fast (peak inspiratory flow rate over 90 L/min). Here, we present a novel audio-based method that objectively assesses patient pMDI user technique. The Inhaler Compliance Assessment device was employed to record inhaler audio signals from 62 respiratory patients as they used a pMDI with an In-Check Flo-Tone device attached to the inhaler mouthpiece. Using a quadratic discriminant analysis approach, the audio-based method generated a total frame-by-frame accuracy of 88.2% in classifying sound events (actuation, inhalation and exhalation). The audio-based method estimated the peak inspiratory flow rate and volume of inhalations with an accuracy of 88.2% and 83.94% respectively. It was detected that 89% of patients made at least one critical user technique error even after tuition from an expert clinical reviewer. This method provides a more clinically accurate assessment of patient inhaler user technique than standard checklist methods.

29 CFR 18.703 - Bases of opinion testimony by experts.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Bases of opinion testimony by experts. The facts or data in the particular case upon which an expert bases an opinion or inference may be those perceived by or made known to the expert at or before the... 29 Labor 1 2010-07-01 2010-07-01 true Bases of opinion testimony by experts. 18.703 Section 18.703...

29 CFR 18.703 - Bases of opinion testimony by experts.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 29 Labor 1 2011-07-01 2011-07-01 false Bases of opinion testimony by experts. 18.703 Section 18... Bases of opinion testimony by experts. The facts or data in the particular case upon which an expert bases an opinion or inference may be those perceived by or made known to the expert at or before the...

29 CFR 18.703 - Bases of opinion testimony by experts.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 29 Labor 1 2013-07-01 2013-07-01 false Bases of opinion testimony by experts. 18.703 Section 18... Bases of opinion testimony by experts. The facts or data in the particular case upon which an expert bases an opinion or inference may be those perceived by or made known to the expert at or before the...

29 CFR 18.703 - Bases of opinion testimony by experts.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 29 Labor 1 2012-07-01 2012-07-01 false Bases of opinion testimony by experts. 18.703 Section 18... Bases of opinion testimony by experts. The facts or data in the particular case upon which an expert bases an opinion or inference may be those perceived by or made known to the expert at or before the...

Physical Examination Findings Among Children and Adolescents With Obesity: An Evidence-Based Review.

PubMed

Armstrong, Sarah; Lazorick, Suzanne; Hampl, Sarah; Skelton, Joseph A; Wood, Charles; Collier, David; Perrin, Eliana M

2016-02-01

Overweight and obesity affects 1 in 3 US children and adolescents. Clinical recommendations have largely focused on screening guidelines and counseling strategies. However, the physical examination of the child or adolescent with obesity can provide the clinician with additional information to guide management decisions. This expert-based review focuses on physical examination findings specific to children and adolescents with obesity. For each physical examination element, the authors define the finding and its prevalence among pediatric patients with obesity, discuss the importance and relevance of the finding, describe known techniques to assess severity, and review evidence regarding the need for additional evaluation. The recommendations presented represent a comprehensive review of current evidence as well as expert opinion. The goal of this review is to highlight the importance of conducting a targeted physical examination during pediatric weight management visits. Copyright © 2016 by the American Academy of Pediatrics.

Automatic Sleep Stage Determination by Multi-Valued Decision Making Based on Conditional Probability with Optimal Parameters

NASA Astrophysics Data System (ADS)

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

Data for human sleep study may be affected by internal and external influences. The recorded sleep data contains complex and stochastic factors, which increase the difficulties for the computerized sleep stage determination techniques to be applied for clinical practice. The aim of this study is to develop an automatic sleep stage determination system which is optimized for variable sleep data. The main methodology includes two modules: expert knowledge database construction and automatic sleep stage determination. Visual inspection by a qualified clinician is utilized to obtain the probability density function of parameters during the learning process of expert knowledge database construction. Parameter selection is introduced in order to make the algorithm flexible. Automatic sleep stage determination is manipulated based on conditional probability. The result showed close agreement comparing with the visual inspection by clinician. The developed system can meet the customized requirements in hospitals and institutions.

Alchemy of the Oracle: The Delphi Technique.

ERIC Educational Resources Information Center

Wilhelm, William J.

2001-01-01

Discusses the origins and foundations of the Delphi technique. Outlines procedures for using it in research to obtain the insights of experts. Addresses limitations of the technique. (Contains 44 references.) (SK)

A biomechanical comparison between expert and novice manual materials handlers using a multi-joint EMG-assisted optimization musculoskeletal model of the lumbar spine.

PubMed

Gagnon, Denis; Plamondon, André; Larivière, Christian

2016-09-06

Expertise is a key factor modulating the risk of low back disorders (LBD). Through years of practice in the workplace, the typical expert acquires high level specific skills and maintains a clean record of work-related injuries. Ergonomic observations of manual materials handling (MMH) tasks show that expert techniques differ from those of novices, leading to the idea that expert techniques are safer. Biomechanical studies of MMH tasks performed by experts/novices report mixed results for kinematic/kinetic variables, evoking potential internal effect of expertise. In the context of series of box transfers simulated by actual workers, detailed internal loads predicted by a multiple-joint EMG-assisted optimization lumbar spine model are compared between experts and novices. The results confirmed that the distribution of internal moments are modulated by worker expertise. Experts flexed less their lumbar spine and exerted more active muscle forces while novices relied more on passive resistance of the muscles and ligamentous spine. More specifically for novices, the passive contributions came from global extensor muscles, selected local extensor muscles, and passive structures of the lumbar spine (ligaments and discs). The distinctive distribution of internal forces was not concomitant with a similar effect on joint forces, these forces being dependent on external loading which was equivalent between experts and novices. From a safety standpoint, the present results suggest that experts were more efficient than novices in partitioning internal moment contributions to balance net (external) loading. Thus, safer handling practices might be seen as a result of experts׳ experience. Copyright © 2016 Elsevier Ltd. All rights reserved.

Reducing the cognitive workload: Trouble managing power systems

NASA Technical Reports Server (NTRS)

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

1993-01-01

The complexity of space-based systems makes monitoring them and diagnosing their faults taxing for human beings. Mission control operators are well-trained experts but they can not afford to have their attention diverted by extraneous information. During normal operating conditions monitoring the status of the components of a complex system alone is a big task. When a problem arises, immediate attention and quick resolution is mandatory. To aid humans in these endeavors we have developed an automated advisory system. Our advisory expert system, Trouble, incorporates the knowledge of the power system designers for Space Station Freedom. Trouble is designed to be a ground-based advisor for the mission controllers in the Control Center Complex at Johnson Space Center (JSC). It has been developed at NASA Lewis Research Center (LeRC) and tested in conjunction with prototype flight hardware contained in the Power Management and Distribution testbed and the Engineering Support Center, ESC, at LeRC. Our work will culminate with the adoption of these techniques by the mission controllers at JSC. This paper elucidates how we have captured power system failure knowledge, how we have built and tested our expert system, and what we believe are its potential uses.

New telemedicine techniques in dermatology - evaluation with reflectance confocal microscopy via cloud-based platform.

PubMed

Łudzik, Joanna; Witkowski, Alexander Michael; Roterman-Konieczna, Irena

Dermoscopically equivocal skin lesions may present a diagnostic challenge in daily clinical practice and are regularly sent for second expert opinion. We present a new approach to handling these cases in a consultation referral system that enables communication between the initial doctor at the image upload site and dermatology experts at a distance via cloud-based telemedicine. In our study we retrospectively evaluated 100 equivocal cases with complete digital dermoscopy-reflectance confocal microscopy image sets and compared suggested management of the initial doctor to a second expert confocal reader. We evaluated the effect of reader concordance on final management of these lesions resulting in a single reader overall sensitivity of 89% and specificity of 66% and double reader concordance method sensitivity of 98% and specificity of 54%. In conclusion, we found that application of double reader evaluation of these image sets with automatic referral of lesions for removal in the case of discordant diagnosis between two doctors improved the sensitivity of diagnosis in this subset of lesions and may increase the safety threshold of management choice reducing potential misdiagnosis in telemedicine settings. This paper concerns the application of telemedicine in practical medicine.

An expert system to advise astronauts during experiments: The protocol manager module

NASA Technical Reports Server (NTRS)

Haymann-Haber, Guido; Colombano, Silvano P.; Groleau, Nicolas; Rosenthal, Don; Szolovits, Peter; Young, Laurence R.

1990-01-01

Perhaps the scarcest resource for manned flight experiments - on Spacelab or on the Space Station Freedom - will continue to be crew time. To maximize the efficiency of the crew and to make use of their abilities to work as scientist collaborators as well as equipment operators, normally requires more training in a wide variety of disciplines than is practical. The successful application of on-board expert systems, as envisioned by the Principal Investigator in a Box program, should alleviate the training bottleneck and provide the astronaut with the guidance and coaching needed to permit him or her to operate an experiment according to the desires and knowledge of the PI, despite changes in conditions. The Protocol Manager module of the system is discussed. The Protocol Manager receives experiment data that has been summarized and categorized by the other modules. The Protocol Manager acts on the data in real-time, by employing expert system techniques. Its recommendations are based on heuristics provided by the Principal Investigator in charge of the experiment. This prototype was developed on a Macintosh II by employing CLIPS, a forward-chaining rule-based system, and HyperCard as an object-oriented user interface builder.

Knowledge-based and integrated monitoring and diagnosis in autonomous power systems

NASA Technical Reports Server (NTRS)

Momoh, J. A.; Zhang, Z. Z.

1990-01-01

A new technique of knowledge-based and integrated monitoring and diagnosis (KBIMD) to deal with abnormalities and incipient or potential failures in autonomous power systems is presented. The KBIMD conception is discussed as a new function of autonomous power system automation. Available diagnostic modelling, system structure, principles and strategies are suggested. In order to verify the feasibility of the KBIMD, a preliminary prototype expert system is designed to simulate the KBIMD function in a main electric network of the autonomous power system.

Collaborative writing: Tools and tips.

PubMed

Eapen, Bell Raj

2007-01-01

Majority of technical writing is done by groups of experts and various web based applications have made this collaboration easy. Email exchange of word processor documents with tracked changes used to be the standard technique for collaborative writing. However web based tools like Google docs and Spreadsheets have made the process fast and efficient. Various versioning tools and synchronous editors are available for those who need additional functionality. Having a group leader who decides the scheduling, communication and conflict resolving protocols is important for successful collaboration.

Graphical explanation in an expert system for Space Station Freedom rack integration

NASA Technical Reports Server (NTRS)

Craig, F. G.; Cutts, D. E.; Fennel, T. R.; Purves, B.

1990-01-01

The rationale and methodology used to incorporate graphics into explanations provided by an expert system for Space Station Freedom rack integration is examined. The rack integration task is typical of a class of constraint satisfaction problems for large programs where expertise from several areas is required. Graphically oriented approaches are used to explain the conclusions made by the system, the knowledge base content, and even at more abstract levels the control strategies employed by the system. The implemented architecture combines hypermedia and inference engine capabilities. The advantages of this architecture include: closer integration of user interface, explanation system, and knowledge base; the ability to embed links to deeper knowledge underlying the compiled knowledge used in the knowledge base; and allowing for more direct control of explanation depth and duration by the user. The graphical techniques employed range from simple statis presentation of schematics to dynamic creation of a series of pictures presented motion picture style. User models control the type, amount, and order of information presented.

Study plan to identify long term national telecommunications need and priorities applying Delphi techniques (handbook). [technological forecasting - United States of America

NASA Technical Reports Server (NTRS)

1974-01-01

A handbook that explains the basic Delphi methodology and discusses modified Delphi techniques is presented. The selection of communications experts to participate in a study, the construction of questionnaires on potential communications developments, and requisite technology is treated. No two modified Delphi studies were the same, which reflects the flexibility and adaptability of the technique. Each study must be specifically tailored to a particular case, and consists of seeking a consensus of opinion among experts about a particular subject and attendant conditions that may prevail in the future.

Prioritizing Measures of Digital Patient Engagement: A Delphi Expert Panel Study

PubMed Central

2017-01-01

Background Establishing a validated scale of patient engagement through use of information technology (ie, digital patient engagement) is the first step to understanding its role in health and health care quality, outcomes, and efficient implementation by health care providers and systems. Objective The aim of this study was to develop and prioritize measures of digital patient engagement based on patients’ use of the US Department of Veterans Affairs (VA)’s MyHealtheVet (MHV) portal, focusing on the MHV/Blue Button and Secure Messaging functions. Methods We aligned two models from the information systems and organizational behavior literatures to create a theory-based model of digital patient engagement. On the basis of this model, we conducted ten key informant interviews to identify potential measures from existing VA studies and consolidated the measures. We then conducted three rounds of modified Delphi rating by 12 national eHealth experts via Web-based surveys to prioritize the measures. Results All 12 experts completed the study’s three rounds of modified Delphi ratings, resulting in two sets of final candidate measures representing digital patient engagement for Secure Messaging (58 measures) and MHV/Blue Button (71 measures). These measure sets map to Donabedian’s three types of quality measures: (1) antecedents (eg, patient demographics); (2) processes (eg, a novel measure of Web-based care quality); and (3) outcomes (eg, patient engagement). Conclusions This national expert panel study using a modified Delphi technique prioritized candidate measures to assess digital patient engagement through patients’ use of VA’s My HealtheVet portal. The process yielded two robust measures sets prepared for future piloting and validation in surveys among Veterans. PMID:28550008

Prioritizing Measures of Digital Patient Engagement: A Delphi Expert Panel Study.

PubMed

Garvin, Lynn A; Simon, Steven R

2017-05-26

Establishing a validated scale of patient engagement through use of information technology (ie, digital patient engagement) is the first step to understanding its role in health and health care quality, outcomes, and efficient implementation by health care providers and systems. The aim of this study was to develop and prioritize measures of digital patient engagement based on patients' use of the US Department of Veterans Affairs (VA)'s MyHealtheVet (MHV) portal, focusing on the MHV/Blue Button and Secure Messaging functions. We aligned two models from the information systems and organizational behavior literatures to create a theory-based model of digital patient engagement. On the basis of this model, we conducted ten key informant interviews to identify potential measures from existing VA studies and consolidated the measures. We then conducted three rounds of modified Delphi rating by 12 national eHealth experts via Web-based surveys to prioritize the measures. All 12 experts completed the study's three rounds of modified Delphi ratings, resulting in two sets of final candidate measures representing digital patient engagement for Secure Messaging (58 measures) and MHV/Blue Button (71 measures). These measure sets map to Donabedian's three types of quality measures: (1) antecedents (eg, patient demographics); (2) processes (eg, a novel measure of Web-based care quality); and (3) outcomes (eg, patient engagement). This national expert panel study using a modified Delphi technique prioritized candidate measures to assess digital patient engagement through patients' use of VA's My HealtheVet portal. The process yielded two robust measures sets prepared for future piloting and validation in surveys among Veterans. ©Lynn A Garvin, Steven R Simon. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 26.05.2017.

Fast and robust estimation of ophthalmic wavefront aberrations

NASA Astrophysics Data System (ADS)

Dillon, Keith

2016-12-01

Rapidly rising levels of myopia, particularly in the developing world, have led to an increased need for inexpensive and automated approaches to optometry. A simple and robust technique is provided for estimating major ophthalmic aberrations using a gradient-based wavefront sensor. The approach is based on the use of numerical calculations to produce diverse combinations of phase components, followed by Fourier transforms to calculate the coefficients. The approach does not utilize phase unwrapping nor iterative solution of inverse problems. This makes the method very fast and tolerant to image artifacts, which do not need to be detected and masked or interpolated as is needed in other techniques. These features make it a promising algorithm on which to base low-cost devices for applications that may have limited access to expert maintenance and operation.

Blood-Banking Techniques for Plateletpheresis in Swine

DTIC Science & Technology

2014-05-01

automatically calculates the blood volume for that patient according to an internal formula . However, to circumvent the human-based algorithm, for a 60-kg...blood volume (µL) in the percentage recovery formula given earlier. The maximal recovery percent- age was calculated by setting the 3-min results to 100...Control Resuscitation Department, the Veterinary Support Department, and the Laboratory Support Department for their expert technical assistance

Distribution Planning: An Integration of Constraint Satisfaction & Heuristic Search Techniques

DTIC Science & Technology

1990-01-01

Proceedings of the Symposium on Aritificial Intelligence in ~~litary Logistics, Arlington, VA: American Defense Preparedness Assoc. pp. 177-182...dynamic changes, too many variables, and lack pf planning time. The Human Engineeri n ~ Laboratory (HEL) is developing artificial intelligence (AI...first attempt. The field of artificial intelligence includes a variety of knowledge-based approaches. Most widely known are Expert Systems, that are

Leveraging Health Care Simulation Technology for Human Factors Research: Closing the Gap Between Lab and Bedside.

PubMed

Deutsch, Ellen S; Dong, Yue; Halamek, Louis P; Rosen, Michael A; Taekman, Jeffrey M; Rice, John

2016-11-01

We describe health care simulation, designed primarily for training, and provide examples of how human factors experts can collaborate with health care professionals and simulationists-experts in the design and implementation of simulation-to use contemporary simulation to improve health care delivery. The need-and the opportunity-to apply human factors expertise in efforts to achieve improved health outcomes has never been greater. Health care is a complex adaptive system, and simulation is an effective and flexible tool that can be used by human factors experts to better understand and improve individual, team, and system performance within health care. Expert opinion is presented, based on a panel delivered during the 2014 Human Factors and Ergonomics Society Health Care Symposium. Diverse simulators, physically or virtually representing humans or human organs, and simulation applications in education, research, and systems analysis that may be of use to human factors experts are presented. Examples of simulation designed to improve individual, team, and system performance are provided, as are applications in computational modeling, research, and lifelong learning. The adoption or adaptation of current and future training and assessment simulation technologies and facilities provides opportunities for human factors research and engineering, with benefits for health care safety, quality, resilience, and efficiency. Human factors experts, health care providers, and simulationists can use contemporary simulation equipment and techniques to study and improve health care delivery. © 2016, Human Factors and Ergonomics Society.

Measuring elimination of podoconiosis, endemicity classifications, case definition and targets: an international Delphi exercise.

PubMed

Deribe, Kebede; Wanji, Samuel; Shafi, Oumer; Muheki Tukahebwa, Edridah; Umulisa, Irenee; Davey, Gail

2015-09-01

Podoconiosis is one of the major causes of lymphoedema in the tropics. Nonetheless, currently there are no endemicity classifications or elimination targets to monitor the effects of interventions. This study aimed at establishing case definitions and indicators that can be used to assess endemicity, elimination and clinical outcomes of podoconiosis. This paper describes the result of a Delphi technique used among 28 experts. A questionnaire outlining possible case definitions, endemicity classifications, elimination targets and clinical outcomes was developed. The questionnaire was distributed to experts working on podoconiosis and other neglected tropical diseases in two rounds. The experts rated the importance of case definitions, endemic classifications, elimination targets and the clinical outcome measures. Median and mode were used to describe the central tendency of expert responses. The coefficient of variation was used to describe the dispersals of expert responses. Consensus on definitions and indicators for assessing endemicity, elimination and clinical outcomes of podoconiosis directed at policy makers and health workers was achieved following the two rounds of Delphi approach among the experts. Based on the two Delphi rounds we discuss potential indicators and endemicity classification of this disabling disease, and the ongoing challenges to its elimination in countries with the highest prevalence. Consensus will help to increase effectiveness of podoconiosis elimination efforts and ensure comparability of outcome data. © The Author 2015. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene.

Potential application of machine vision technology to saffron (Crocus sativus L.) quality characterization.

PubMed

Kiani, Sajad; Minaei, Saeid

2016-12-01

Saffron quality characterization is an important issue in the food industry and of interest to the consumers. This paper proposes an expert system based on the application of machine vision technology for characterization of saffron and shows how it can be employed in practical usage. There is a correlation between saffron color and its geographic location of production and some chemical attributes which could be properly used for characterization of saffron quality and freshness. This may be accomplished by employing image processing techniques coupled with multivariate data analysis for quantification of saffron properties. Expert algorithms can be made available for prediction of saffron characteristics such as color as well as for product classification. Copyright © 2016. Published by Elsevier Ltd.

Conceptual FOM design tool

NASA Astrophysics Data System (ADS)

Krause, Lee S.; Burns, Carla L.

2000-06-01

This paper discusses the research currently in progress to develop the Conceptual Federation Object Model Design Tool. The objective of the Conceptual FOM (C-FOM) Design Tool effort is to provide domain and subject matter experts, such as scenario developers, with automated support for understanding and utilizing available HLA simulation and other simulation assets during HLA Federation development. The C-FOM Design Tool will import Simulation Object Models from HLA reuse repositories, such as the MSSR, to populate the domain space that will contain all the objects and their supported interactions. In addition, the C-FOM tool will support the conversion of non-HLA legacy models into HLA- compliant models by applying proven abstraction techniques against the legacy models. Domain experts will be able to build scenarios based on the domain objects and interactions in both a text and graphical form and export a minimal FOM. The ability for domain and subject matter experts to effectively access HLA and non-HLA assets is critical to the long-term acceptance of the HLA initiative.

Usability Evaluation of a Private Social Network on Mental Health for Relatives.

PubMed

Toribio-Guzmán, José Miguel; García-Holgado, Alicia; Soto Pérez, Felipe; García-Peñalvo, Francisco J; Franco Martín, Manuel

2017-09-01

Usability is one of the most prominent criteria that must be fulfilled by a software product. This study aims to evaluate the usability of SocialNet, a private social network for monitoring the daily progress of patients by their relatives, using a mixed usability approach: heuristic evaluation conducted by experts and user testing. A double heuristic evaluation with one expert evaluator identified the issues related to consistency, design, and privacy. User testing was conducted on 20 users and one evaluator using observation techniques and questionnaires. The main usability problems were found to be related to the structure of SocialNet, and the users presented some difficulties in locating the buttons or links. The results show a high level of usability and satisfaction with the product. This evaluation provides data on the usability of SocialNet based on the difficulties experienced by the users and the expert. The results help in redesigning the tool to resolve the identified problems as part of an iterative process.

Applied algorithm in the liner inspection of solid rocket motors

NASA Astrophysics Data System (ADS)

Hoffmann, Luiz Felipe Simões; Bizarria, Francisco Carlos Parquet; Bizarria, José Walter Parquet

2018-03-01

In rocket motors, the bonding between the solid propellant and thermal insulation is accomplished by a thin adhesive layer, known as liner. The liner application method involves a complex sequence of tasks, which includes in its final stage, the surface integrity inspection. Nowadays in Brazil, an expert carries out a thorough visual inspection to detect defects on the liner surface that may compromise the propellant interface bonding. Therefore, this paper proposes an algorithm that uses the photometric stereo technique and the K-nearest neighbor (KNN) classifier to assist the expert in the surface inspection. Photometric stereo allows the surface information recovery of the test images, while the KNN method enables image pixels classification into two classes: non-defect and defect. Tests performed on a computer vision based prototype validate the algorithm. The positive results suggest that the algorithm is feasible and when implemented in a real scenario, will be able to help the expert in detecting defective areas on the liner surface.

Method of App Selection for Healthcare Providers Based on Consumer Needs.

PubMed

Lee, Jisan; Kim, Jeongeun

2018-01-01

Mobile device applications can be used to manage health. However, healthcare providers hesitate to use them because selection methods that consider the needs of health consumers and identify the most appropriate application are rare. This study aimed to create an effective method of identifying applications that address user needs. Women experiencing dysmenorrhea and premenstrual syndrome were the targeted users. First, we searched for related applications from two major sources of mobile applications. Brainstorming, mind mapping, and persona and scenario techniques were used to create a checklist of relevant criteria, which was used to rate the applications. Of the 2784 applications found, 369 were analyzed quantitatively. Of those, five of the top candidates were evaluated by three groups: application experts, clinical experts, and potential users. All three groups ranked one application the highest; however, the remaining rankings differed. The results of this study suggest that the method created is useful because it considers not only the needs of various users but also the knowledge of application and clinical experts. This study proposes a method for finding and using the best among existing applications and highlights the need for nurses who can understand and combine opinions of users and application and clinical experts.

Expert System for ASIC Imaging

NASA Astrophysics Data System (ADS)

Gupta, Shri N.; Arshak, Khalil I.; McDonnell, Pearse; Boyce, Conor; Duggan, Andrew

1989-07-01

With the developments in the techniques of artificial intelligence over the last few years, development of advisory, scheduling and similar class of problems has become very convenient using tools such as PROLOG. In this paper an expert system has been described which helps lithographers and process engineers in several ways. The methodology used is to model each work station according to its input, output and control parameters, combine these work stations in a logical sequence based on past experience and work out process schedule for a job. In addition, all the requirements vis-a-vis a particular job parameters are converted into decision rules. One example is the exposure time, develop time for a wafer with different feature sizes would be different. This expert system has been written in Turbo Prolog. By building up a large number of rules, one can tune the program to any facility and use it for as diverse applications as advisory help, trouble shooting etc. Leitner (1) has described an advisory expert system that is being used at National Semiconductor. This system is quite different from the one being reported in the present paper. The approach is quite different for one. There is stress on job flow and process for another.

Criminal profiling as expert witness evidence: The implications of the profiler validity research.

PubMed

Kocsis, Richard N; Palermo, George B

The use and development of the investigative tool colloquially known as criminal profiling has steadily increased over the past five decades throughout the world. Coupled with this growth has been a diversification in the suggested range of applications for this technique. Possibly the most notable of these has been the attempted transition of the technique from a tool intended to assist police investigations into a form of expert witness evidence admissible in legal proceedings. Whilst case law in various jurisdictions has considered with mutual disinclination the evidentiary admissibility of criminal profiling, a disjunction has evolved between these judicial examinations and the scientifically vetted research testing the accuracy (i.e., validity) of the technique. This article offers an analysis of the research directly testing the validity of the criminal profiling technique and the extant legal principles considering its evidentiary admissibility. This analysis reveals that research findings concerning the validity of criminal profiling are surprisingly compatible with the extant legal principles. The overall conclusion is that a discrete form of crime behavioural analysis is supported by the profiler validity research and could be regarded as potentially admissible expert witness evidence. Finally, a number of theoretical connections are also identified concerning the skills and qualifications of individuals who may feasibly provide such expert testimony. Copyright © 2016 Elsevier Ltd. All rights reserved.

Optics Toolbox: An Intelligent Relational Database System For Optical Designers

NASA Astrophysics Data System (ADS)

Weller, Scott W.; Hopkins, Robert E.

1986-12-01

Optical designers were among the first to use the computer as an engineering tool. Powerful programs have been written to do ray-trace analysis, third-order layout, and optimization. However, newer computing techniques such as database management and expert systems have not been adopted by the optical design community. For the purpose of this discussion we will define a relational database system as a database which allows the user to specify his requirements using logical relations. For example, to search for all lenses in a lens database with a F/number less than two, and a half field of view near 28 degrees, you might enter the following: FNO < 2.0 and FOV of 28 degrees ± 5% Again for the purpose of this discussion, we will define an expert system as a program which contains expert knowledge, can ask intelligent questions, and can form conclusions based on the answers given and the knowledge which it contains. Most expert systems store this knowledge in the form of rules-of-thumb, which are written in an English-like language, and which are easily modified by the user. An example rule is: IF require microscope objective in air and require NA > 0.9 THEN suggest the use of an oil immersion objective The heart of the expert system is the rule interpreter, sometimes called an inference engine, which reads the rules and forms conclusions based on them. The use of a relational database system containing lens prototypes seems to be a viable prospect. However, it is not clear that expert systems have a place in optical design. In domains such as medical diagnosis and petrology, expert systems are flourishing. These domains are quite different from optical design, however, because optical design is a creative process, and the rules are difficult to write down. We do think that an expert system is feasible in the area of first order layout, which is sufficiently diagnostic in nature to permit useful rules to be written. This first-order expert would emulate an expert designer as he interacted with a customer for the first time: asking the right questions, forming conclusions, and making suggestions. With these objectives in mind, we have developed the Optics Toolbox. Optics Toolbox is actually two programs in one: it is a powerful relational database system with twenty-one search parameters, four search modes, and multi-database support, as well as a first-order optical design expert system with a rule interpreter which has full access to the relational database. The system schematic is shown in Figure 1.

Evaluation of automated decisionmaking methodologies and development of an integrated robotic system simulation. Volume 1: Study results

NASA Technical Reports Server (NTRS)

Lowrie, J. W.; Fermelia, A. J.; Haley, D. C.; Gremban, K. D.; Vanbaalen, J.; Walsh, R. W.

1982-01-01

A variety of artificial intelligence techniques which could be used with regard to NASA space applications and robotics were evaluated. The techniques studied were decision tree manipulators, problem solvers, rule based systems, logic programming languages, representation language languages, and expert systems. The overall structure of a robotic simulation tool was defined and a framework for that tool developed. Nonlinear and linearized dynamics equations were formulated for n link manipulator configurations. A framework for the robotic simulation was established which uses validated manipulator component models connected according to a user defined configuration.

Tracheotomy in the intensive care unit: Guidelines from a French expert panel: The French Intensive Care Society and the French Society of Anaesthesia and Intensive Care Medicine.

PubMed

Trouillet, Jean-Louis; Collange, Olivier; Belafia, Fouad; Blot, François; Capellier, Gilles; Cesareo, Eric; Constantin, Jean-Michel; Demoule, Alexandre; Diehl, Jean-Luc; Guinot, Pierre-Grégoire; Jegoux, Franck; L'Her, Erwan; Luyt, Charles-Edouard; Mahjoub, Yazine; Mayaux, Julien; Quintard, Hervé; Ravat, François; Vergez, Sébastien; Amour, Julien; Guillot, Max

2018-06-01

Tracheotomy is widely used in intensive care units, albeit with great disparities between medical teams in terms of frequency and modality. Indications and techniques are, however, associated with variable levels of evidence based on inhomogeneous or even contradictory literature. Our aim was to conduct a systematic analysis of the published data in order to provide guidelines. We present herein recommendations for the use of tracheotomy in adult critically ill patients developed using the grading of recommendations assessment, development and evaluation (GRADE) method. These guidelines were conducted by a group of experts from the French Intensive Care Society (Société de réanimation de langue française) and the French Society of Anesthesia and Intensive Care Medicine (Société francaise d'anesthésie réanimation) with the participation of the French Emergency Medicine Association (Société française de médecine d'urgence), the French Society of Otorhinolaryngology. Sixteen experts and two coordinators agreed to consider questions concerning tracheotomy and its practical implementation. Five topics were defined: indications and contraindications for tracheotomy in intensive care, tracheotomy techniques in intensive care, modalities of tracheotomy in intensive care, management of patients undergoing tracheotomy in intensive care, and decannulation in intensive care. The summary made by the experts and the application of GRADE methodology led to the drawing up of 8 formal guidelines, 10 recommendations, and 3 treatment protocols. Among the 8 formal guidelines, 2 have a high level of proof (Grade 1±) and 6 a low level of proof (Grade 2±). For the 10 recommendations, GRADE methodology was not applicable and instead 10 expert opinions were produced. Copyright © 2018 The Author(s). Published by Elsevier Masson SAS.. All rights reserved.

Infant polysomnography: reliability and validity of infant arousal assessment.

PubMed

Crowell, David H; Kulp, Thomas D; Kapuniai, Linda E; Hunt, Carl E; Brooks, Lee J; Weese-Mayer, Debra E; Silvestri, Jean; Ward, Sally Davidson; Corwin, Michael; Tinsley, Larry; Peucker, Mark

2002-10-01

Infant arousal scoring based on the Atlas Task Force definition of transient EEG arousal was evaluated to determine (1). whether transient arousals can be identified and assessed reliably in infants and (2). whether arousal and no-arousal epochs scored previously by trained raters can be validated reliably by independent sleep experts. Phase I for inter- and intrarater reliability scoring was based on two datasets of sleep epochs selected randomly from nocturnal polysomnograms of healthy full-term, preterm, idiopathic apparent life-threatening event cases, and siblings of Sudden Infant Death Syndrome infants of 35 to 64 weeks postconceptional age. After training, test set 1 reliability was assessed and discrepancies identified. After retraining, test set 2 was scored by the same raters to determine interrater reliability. Later, three raters from the trained group rescored test set 2 to assess inter- and intrarater reliabilities. Interrater and intrarater reliability kappa's, with 95% confidence intervals, ranged from substantial to almost perfect levels of agreement. Interrater reliabilities for spontaneous arousals were initially moderate and then substantial. During the validation phase, 315 previously scored epochs were presented to four sleep experts to rate as containing arousal or no-arousal events. Interrater expert agreements were diverse and considered as noninterpretable. Concordance in sleep experts' agreements, based on identification of the previously sampled arousal and no-arousal epochs, was used as a secondary evaluative technique. Results showed agreement by two or more experts on 86% of the Collaborative Home Infant Monitoring Evaluation Study arousal scored events. Conversely, only 1% of the Collaborative Home Infant Monitoring Evaluation Study-scored no-arousal epochs were rated as an arousal. In summary, this study presents an empirically tested model with procedures and criteria for attaining improved reliability in transient EEG arousal assessments in infants using the modified Atlas Task Force standards. With training based on specific criteria, substantial inter- and intrarater agreement in identifying infant arousals was demonstrated. Corroborative validation results were too disparate for meaningful interpretation. Alternate evaluation based on concordance agreements supports reliance on infant EEG criteria for assessment. Results mandate additional confirmatory validation studies with specific training on infant EEG arousal assessment criteria.

Caries preventive measures in orthodontic practice: the development of a clinical practice guideline.

PubMed

Oosterkamp, B C M; van der Sanden, W J M; Frencken, J E F M; Kuijpers-Jagtman, A M

2016-02-01

White spot lesions (WSLs) are a side effect of orthodontic treatment, causing esthetic problems and a risk of deeper enamel and dentine lesions. Many strategies have been developed for preventing WSLs, but great variability exists in preventive measures between orthodontists. This study developed statements on which a clinical practice guideline (CPG) can be developed in order to help orthodontists select preventive measures based on the best available evidence. A nominal group technique (RAND-e modified Delphi procedure) was used. A multidisciplinary expert panel rated 264 practice- and evidence-based statements related to the management of WSLs. To provide panel members with the same knowledge, a total of six articles obtained from a systematic review of the literature were read by the panel in preparation of three consensus rounds. According to the technique, a threshold of 75% of all ratings within any 3-point section of the 9-point scale regarding a specific statement was accepted as consensus. After the first and second consensus rounds, consensus was reached on 37.5 and 31.1% of statements, respectively. For the remaining 31.4% of statements, consensus was reached during a 4-h consensus meeting. Statements on the management of WSLs derived from a systematic literature review combined with expert opinion were formally integrated toward consensus through a nominal group technique. These statements formed the basis for developing a CPG on the management of WSLs before and during orthodontic treatment. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Evaluation of a Performance-Based Expert Elicitation: WHO Global Attribution of Foodborne Diseases.

PubMed

Aspinall, W P; Cooke, R M; Havelaar, A H; Hoffmann, S; Hald, T

2016-01-01

For many societally important science-based decisions, data are inadequate, unreliable or non-existent, and expert advice is sought. In such cases, procedures for eliciting structured expert judgments (SEJ) are increasingly used. This raises questions regarding validity and reproducibility. This paper presents new findings from a large-scale international SEJ study intended to estimate the global burden of foodborne disease on behalf of WHO. The study involved 72 experts distributed over 134 expert panels, with panels comprising thirteen experts on average. Elicitations were conducted in five languages. Performance-based weighted solutions for target questions of interest were formed for each panel. These weights were based on individual expert's statistical accuracy and informativeness, determined using between ten and fifteen calibration variables from the experts' field with known values. Equal weights combinations were also calculated. The main conclusions on expert performance are: (1) SEJ does provide a science-based method for attribution of the global burden of foodborne diseases; (2) equal weighting of experts per panel increased statistical accuracy to acceptable levels, but at the cost of informativeness; (3) performance-based weighting increased informativeness, while retaining accuracy; (4) due to study constraints individual experts' accuracies were generally lower than in other SEJ studies, and (5) there was a negative correlation between experts' informativeness and statistical accuracy which attenuated as accuracy improved, revealing that the least accurate experts drive the negative correlation. It is shown, however, that performance-based weighting has the ability to yield statistically accurate and informative combinations of experts' judgments, thereby offsetting this contrary influence. The present findings suggest that application of SEJ on a large scale is feasible, and motivate the development of enhanced training and tools for remote elicitation of multiple, internationally-dispersed panels.

Design of an expert-system flight status monitor

NASA Technical Reports Server (NTRS)

Regenie, V. A.; Duke, E. L.

1985-01-01

The modern advanced avionics in new high-performance aircraft strains the capability of current technology to safely monitor these systems for flight test prior to their generalized use. New techniques are needed to improve the ability of systems engineers to understand and analyze complex systems in the limited time available during crucial periods of the flight test. The Dryden Flight Research Facility of NASA's Ames Research Center is involved in the design and implementation of an expert system to provide expertise and knowledge to aid the flight systems engineer. The need for new techniques in monitoring flight systems and the conceptual design of an expert-system flight status monitor is discussed. The status of the current project and its goals are described.

Tracking and data relay satellite fault isolation and correction using PACES: Power and attitude control expert system

NASA Technical Reports Server (NTRS)

Erikson, Carol-Lee; Hooker, Peggy

1989-01-01

The Power and Attitude Control Expert System (PACES) is an object oriented and rule based expert system which provides spacecraft engineers with assistance in isolating and correcting problems within the Power and Attitude Control Subsystems of the Tracking and Data Relay Satellites (TDRS). PACES is designed to act in a consultant role. It will not interface to telemetry data, thus preserving full operator control over spacecraft operations. The spacecraft engineer will input requested information. This information will include telemetry data, action being performed, problem characteristics, spectral characteristics, and judgments of spacecraft functioning. Questions are answered either by clicking on appropriate responses (for text), or entering numeric values. A context sensitive help facility allows access to additional information when the user has difficulty understanding a question or deciding on an answer. The major functionality of PACES is to act as a knowledge rich system which includes block diagrams, text, and graphics, linked using hypermedia techniques. This allows easy movement among pieces of the knowledge. Considerable documentation of the spacecraft Power and Attitude Control Subsystems is embedded within PACES. The development phase of TDRSS expert system technology is intended to provide NASA with 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 and Data Relay Satellite Program.

Performance Engineering as an Expert System.

ERIC Educational Resources Information Center

Harmon, Paul

1984-01-01

Considers three powerful techniques--heuristics, context trees, and search via backward chaining--that a knowledge engineer might employ to develop an expert system to automate performance engineering, i.e., the branch of instructional technology that focuses on the problems of business and industry. (MBR)

Priority issues for pressure injury research: An Australian consensus study.

PubMed

Haesler, Emily; Carville, Keryln; Haesler, Paul

2018-06-08

Pressure injuries are a significant health concern in all clinical settings. The current body of research on pressure injuries reported in the literature presents primarily low level evidence. The purpose of the current study was to identify and prioritize pressure injury research issues. The approach entailed evidence scoping and implementing a formal consensus process using a modified nominal group technique based on the Research and Development/University of California at Los Angeles appropriateness method. Sixteen Australian pressure injury experts participated in five consensus voting rounds in May to June 2015. From 60 initial research issues, the experts reached agreement that 26 issues are a priority for future pressure injury research. The highest priorities were strategies to assess skin and tissues, appropriate outcome measures for indicators of pressure injury healing and recurrence, heel pressure off-loading and shear reduction strategies, economic cost of pressure injuries and their management and effectiveness of skin moisturizers and barrier products. Developing a prioritized research agenda, informed by clinical and academic pressure injury experts, can assist in reducing the burden of pressure injuries by identifying topics of the highest need for further research. A web-based nominal group voting process was successful in engaging expert decision-making and has wide-reaching international appeal in facilitating cost-effective consensus methodologies. The priority list generated from this research is currently used in Australia to inform government investment in pressure injury research. © 2018 Wiley Periodicals, Inc.

Adaptive control with an expert system based supervisory level. Thesis

NASA Technical Reports Server (NTRS)

Sullivan, Gerald A.

1991-01-01

Adaptive control is presently one of the methods available which may be used to control plants with poorly modelled dynamics or time varying dynamics. Although many variations of adaptive controllers exist, a common characteristic of all adaptive control schemes, is that input/output measurements from the plant are used to adjust a control law in an on-line fashion. Ideally the adjustment mechanism of the adaptive controller is able to learn enough about the dynamics of the plant from input/output measurements to effectively control the plant. In practice, problems such as measurement noise, controller saturation, and incorrect model order, to name a few, may prevent proper adjustment of the controller and poor performance or instability result. In this work we set out to avoid the inadequacies of procedurally implemented safety nets, by introducing a two level control scheme in which an expert system based 'supervisor' at the upper level provides all the safety net functions for an adaptive controller at the lower level. The expert system is based on a shell called IPEX, (Interactive Process EXpert), that we developed specifically for the diagnosis and treatment of dynamic systems. Some of the more important functions that the IPEX system provides are: (1) temporal reasoning; (2) planning of diagnostic activities; and (3) interactive diagnosis. Also, because knowledge and control logic are separate, the incorporation of new diagnostic and treatment knowledge is relatively simple. We note that the flexibility available in the system to express diagnostic and treatment knowledge, allows much greater functionality than could ever be reasonably expected from procedural implementations of safety nets. The remainder of this chapter is divided into three sections. In section 1.1 we give a detailed review of the literature in the area of supervisory systems for adaptive controllers. In particular, we describe the evolution of safety nets from simple ad hoc techniques, up to the use of expert systems for more advanced supervision capabilities.

Malaria chemoprophylaxis recommendations for immigrants to Europe, visiting relatives and friends - a Delphi method study

PubMed Central

2011-01-01

Background Numbers of travellers visiting friends and relatives (VFRs) from Europe to malaria endemic countries are increasing and include long-term and second generation immigrants, who represent the major burden of malaria cases imported back into Europe. Most recommendations for malaria chemoprophylaxis lack a solid evidence base, and often fail to address the cultural, social and economic needs of VFRs. Methods European travel medicine experts, who are members of TropNetEurop, completed a sequential series of questionnaires according to the Delphi method. This technique aims at evaluating and developing a consensus through repeated iterations of questionnaires. The questionnaires in this study included questions about professional experience with VFRs, controversial issues in malaria prophylaxis, and 16 scenarios exploring indications for prescribing and choice of chemoprophylaxis. Results The experience of participants was rather diverse as was their selection of chemoprophylaxis regimen. A significant consensus was observed in only seven of 16 scenarios. The analysis revealed a wide variation in prescribing choices with preferences grouped by region of practice and increased prescribing seen in Northern Europe compared to Central Europe. Conclusions Improving the evidence base on efficacy, adherence to chemoprophylaxis and risk of malaria and encouraging discussion among experts, using techniques such as the Delphi method, may reduce the variability in prescription in European travel clinics. PMID:21599909

Predicting subscriber dissatisfaction and improving retention in the wireless telecommunications industry.

PubMed

Mozer, M C; Wolniewicz, R; Grimes, D B; Johnson, E; Kaushansky, H

2000-01-01

Competition in the wireless telecommunications industry is fierce. To maintain profitability, wireless carriers must control churn, which is the loss of subscribers who switch from one carrier to another.We explore techniques from statistical machine learning to predict churn and, based on these predictions, to determine what incentives should be offered to subscribers to improve retention and maximize profitability to the carrier. The techniques include logit regression, decision trees, neural networks, and boosting. Our experiments are based on a database of nearly 47,000 U.S. domestic subscribers and includes information about their usage, billing, credit, application, and complaint history. Our experiments show that under a wide variety of assumptions concerning the cost of intervention and the retention rate resulting from intervention, using predictive techniques to identify potential churners and offering incentives can yield significant savings to a carrier. We also show the importance of a data representation crafted by domain experts. Finally, we report on a real-world test of the techniques that validate our simulation experiments.

Classification by diagnosing all absorption features (CDAF) for the most abundant minerals in airborne hyperspectral images

NASA Astrophysics Data System (ADS)

Mobasheri, Mohammad Reza; Ghamary-Asl, Mohsen

2011-12-01

Imaging through hyperspectral technology is a powerful tool that can be used to spectrally identify and spatially map materials based on their specific absorption characteristics in electromagnetic spectrum. A robust method called Tetracorder has shown its effectiveness at material identification and mapping, using a set of algorithms within an expert system decision-making framework. In this study, using some stages of Tetracorder, a technique called classification by diagnosing all absorption features (CDAF) is introduced. This technique enables one to assign a class to the most abundant mineral in each pixel with high accuracy. The technique is based on the derivation of information from reflectance spectra of the image. This can be done through extraction of spectral absorption features of any minerals from their respected laboratory-measured reflectance spectra, and comparing it with those extracted from the pixels in the image. The CDAF technique has been executed on the AVIRIS image where the results show an overall accuracy of better than 96%.

Measurements of Cuspal Slope Inclination Angles in Palaeoanthropological Applications

NASA Astrophysics Data System (ADS)

Gaboutchian, A. V.; Knyaz, V. A.; Leybova, N. A.

2017-05-01

Tooth crown morphological features, studied in palaeoanthropology, provide valuable information about human evolution and development of civilization. Tooth crown morphology represents biological and historical data of high taxonomical value as it characterizes genetically conditioned tooth relief features averse to substantial changes under environmental factors during lifetime. Palaeoanthropological studies are still based mainly on descriptive techniques and manual measurements of limited number of morphological parameters. Feature evaluation and measurement result analysis are expert-based. Development of new methods and techniques in 3D imaging creates a background provides for better value of palaeoanthropological data processing, analysis and distribution. The goals of the presented research are to propose new features for automated odontometry and to explore their applicability to paleoanthropological studies. A technique for automated measuring of given morphological tooth parameters needed for anthropological study is developed. It is based on using original photogrammetric system as a teeth 3D models acquisition device and on a set of algorithms for given tooth parameters estimation.

GIS-based bivariate statistical techniques for groundwater potential analysis (an example of Iran)

NASA Astrophysics Data System (ADS)

Haghizadeh, Ali; Moghaddam, Davoud Davoudi; Pourghasemi, Hamid Reza

2017-12-01

Groundwater potential analysis prepares better comprehension of hydrological settings of different regions. This study shows the potency of two GIS-based data driven bivariate techniques namely statistical index (SI) and Dempster-Shafer theory (DST) to analyze groundwater potential in Broujerd region of Iran. The research was done using 11 groundwater conditioning factors and 496 spring positions. Based on the ground water potential maps (GPMs) of SI and DST methods, 24.22% and 23.74% of the study area is covered by poor zone of groundwater potential, and 43.93% and 36.3% of Broujerd region is covered by good and very good potential zones, respectively. The validation of outcomes displayed that area under the curve (AUC) of SI and DST techniques are 81.23% and 79.41%, respectively, which shows SI method has slightly a better performance than the DST technique. Therefore, SI and DST methods are advantageous to analyze groundwater capacity and scrutinize the complicated relation between groundwater occurrence and groundwater conditioning factors, which permits investigation of both systemic and stochastic uncertainty. Finally, it can be realized that these techniques are very beneficial for groundwater potential analyzing and can be practical for water-resource management experts.

Seeing the System through the End Users' Eyes: Shadow Expert Technique for Evaluating the Consistency of a Learning Management System

NASA Astrophysics Data System (ADS)

Holzinger, Andreas; Stickel, Christian; Fassold, Markus; Ebner, Martin

Interface consistency is an important basic concept in web design and has an effect on performance and satisfaction of end users. Consistency also has significant effects on the learning performance of both expert and novice end users. Consequently, the evaluation of consistency within a e-learning system and the ensuing eradication of irritating discrepancies in the user interface redesign is a big issue. In this paper, we report of our experiences with the Shadow Expert Technique (SET) during the evaluation of the consistency of the user interface of a large university learning management system. The main objective of this new usability evaluation method is to understand the interaction processes of end users with a specific system interface. Two teams of usability experts worked independently from each other in order to maximize the objectivity of the results. The outcome of this SET method is a list of recommended changes to improve the user interaction processes, hence to facilitate high consistency.

Completing and Adapting Models of Biological Processes

NASA Technical Reports Server (NTRS)

Margaria, Tiziana; Hinchey, Michael G.; Raffelt, Harald; Rash, James L.; Rouff, Christopher A.; Steffen, Bernhard

2006-01-01

We present a learning-based method for model completion and adaptation, which is based on the combination of two approaches: 1) R2D2C, a technique for mechanically transforming system requirements via provably equivalent models to running code, and 2) automata learning-based model extrapolation. The intended impact of this new combination is to make model completion and adaptation accessible to experts of the field, like biologists or engineers. The principle is briefly illustrated by generating models of biological procedures concerning gene activities in the production of proteins, although the main application is going to concern autonomic systems for space exploration.

Considerations in development of expert systems for real-time space applications

NASA Technical Reports Server (NTRS)

Murugesan, S.

1988-01-01

Over the years, demand on space systems has increased tremendously and this trend will continue for the near future. Enhanced capabilities of space systems, however, can only be met with increased complexity and sophistication of onboard and ground systems. Artificial Intelligence and expert system techniques have great potential in space applications. Expert systems could facilitate autonomous decision making, improve in-orbit fault diagnosis and repair, enhance performance and reduce reliance on ground support. However, real-time expert systems, unlike conventional off-line consultative systems, have to satisfy certain special stringent requirements before they could be used for onboard space applications. Challenging and interesting new environments are faced while developing expert system space applications. This paper discusses the special characteristics, requirements and typical life cycle issues for onboard expert systems. Further, it also describes considerations in design, development, and implementation which are particularly important to real-time expert systems for space applications.

[Screening for atherosclerosis to prevent cardiovascular risk : a pro-contra debate].

PubMed

Nanchen, David; Genest, Jacques

2018-02-28

Detecting atherosclerosis using imaging techniques is the subject of intense debate in the scientific community. Among the arguments in favor of screening, a better identification or better stratification of cardiovascular risk is mentioned, compared to cardiovascular risk scores based solely on traditional risk factors, such as blood pressure or cholesterol levels. Imaging techniques are also used to monitor the progression of atherosclerosis among patients using lipid-lowering or antihypertensive drugs in primary prevention. However, several experts in recent years have challenged the clinical utility of these imaging techniques in asymptomatic adults. This article proposes a debate « for or against » to describe the main arguments for or against the use of imaging for screening for atherosclerosis.

Artificial intelligence in sports biomechanics: new dawn or false hope?

PubMed

Bartlett, Roger

2006-12-15

This article reviews developments in the use of Artificial Intelligence (AI) in sports biomechanics over the last decade. It outlines possible uses of Expert Systems as diagnostic tools for evaluating faults in sports movements ('techniques') and presents some example knowledge rules for such an expert system. It then compares the analysis of sports techniques, in which Expert Systems have found little place to date, with gait analysis, in which they are routinely used. Consideration is then given to the use of Artificial Neural Networks (ANNs) in sports biomechanics, focusing on Kohonen self-organizing maps, which have been the most widely used in technique analysis, and multi-layer networks, which have been far more widely used in biomechanics in general. Examples of the use of ANNs in sports biomechanics are presented for javelin and discus throwing, shot putting and football kicking. I also present an example of the use of Evolutionary Computation in movement optimization in the soccer throw in, which predicted an optimal technique close to that in the coaching literature. After briefly overviewing the use of AI in both sports science and biomechanics in general, the article concludes with some speculations about future uses of AI in sports biomechanics. Key PointsExpert Systems remain almost unused in sports biomechanics, unlike in the similar discipline of gait analysis.Artificial Neural Networks, particularly Kohonen Maps, have been used, although their full value remains unclear.Other AI applications, including Evolutionary Computation, have received little attention.

Management of nonalcoholic fatty liver disease: An evidence-based clinical practice review

PubMed Central

Arab, Juan P; Candia, Roberto; Zapata, Rodrigo; Muñoz, Cristián; Arancibia, Juan P; Poniachik, Jaime; Soza, Alejandro; Fuster, Francisco; Brahm, Javier; Sanhueza, Edgar; Contreras, Jorge; Cuellar, M Carolina; Arrese, Marco; Riquelme, Arnoldo

2014-01-01

AIM: To build a consensus among Chilean specialists on the appropriate management of patients with nonalcoholic fatty liver disease (NAFLD) in clinical practice. METHODS: NAFLD has now reached epidemic proportions worldwide. The optimal treatment for NAFLD has not been established due to a lack of evidence-based recommendations. An expert panel of members of the Chilean Gastroenterological Society and the Chilean Hepatology Association conducted a structured analysis of the current literature on NAFLD therapy. The quality of the evidence and the level of recommendations supporting each statement were assessed according to the recommendations of the United States Preventive Services Task Force. A modified three-round Delphi technique was used to reach a consensus among the experts. RESULTS: A group of thirteen experts was established. The survey included 17 open-ended questions that were distributed among the experts, who assessed the articles associated with each question. The levels of agreement achieved by the panel were 93.8% in the first round and 100% in the second and third rounds. The final recommendations support the indication of lifestyle changes, including diet and exercise, for all patients with NAFLD. Proven pharmacological therapies include only vitamin E and pioglitazone, which can be used in nondiabetic patients with biopsy-proven nonalcoholic steatohepatitis (the progressive form of NAFLD), although the long-term safety and efficacy of these therapies have not yet been established. CONCLUSION: Current NAFLD management is rapidly evolving, and new pathophysiology-based therapies are expected to be introduced in the near future. All NAFLD patients should be evaluated using a three-focused approach that considers the risks of liver disease, diabetes and cardiovascular events. PMID:25232252

Artificial Intelligence: Applications in Education.

ERIC Educational Resources Information Center

Thorkildsen, Ron J.; And Others

1986-01-01

Artificial intelligence techniques are used in computer programs to search out rapidly and retrieve information from very large databases. Programing advances have also led to the development of systems that provide expert consultation (expert systems). These systems, as applied to education, are the primary emphasis of this article. (LMO)

Evaluation of a Performance-Based Expert Elicitation: WHO Global Attribution of Foodborne Diseases

PubMed Central

Aspinall, W. P.; Cooke, R. M.; Havelaar, A. H.; Hoffmann, S.; Hald, T.

2016-01-01

For many societally important science-based decisions, data are inadequate, unreliable or non-existent, and expert advice is sought. In such cases, procedures for eliciting structured expert judgments (SEJ) are increasingly used. This raises questions regarding validity and reproducibility. This paper presents new findings from a large-scale international SEJ study intended to estimate the global burden of foodborne disease on behalf of WHO. The study involved 72 experts distributed over 134 expert panels, with panels comprising thirteen experts on average. Elicitations were conducted in five languages. Performance-based weighted solutions for target questions of interest were formed for each panel. These weights were based on individual expert’s statistical accuracy and informativeness, determined using between ten and fifteen calibration variables from the experts' field with known values. Equal weights combinations were also calculated. The main conclusions on expert performance are: (1) SEJ does provide a science-based method for attribution of the global burden of foodborne diseases; (2) equal weighting of experts per panel increased statistical accuracy to acceptable levels, but at the cost of informativeness; (3) performance-based weighting increased informativeness, while retaining accuracy; (4) due to study constraints individual experts’ accuracies were generally lower than in other SEJ studies, and (5) there was a negative correlation between experts' informativeness and statistical accuracy which attenuated as accuracy improved, revealing that the least accurate experts drive the negative correlation. It is shown, however, that performance-based weighting has the ability to yield statistically accurate and informative combinations of experts' judgments, thereby offsetting this contrary influence. The present findings suggest that application of SEJ on a large scale is feasible, and motivate the development of enhanced training and tools for remote elicitation of multiple, internationally-dispersed panels. PMID:26930595

A distributed agent architecture for real-time knowledge-based systems: Real-time expert systems project, phase 1

NASA Technical Reports Server (NTRS)

Lee, S. Daniel

1990-01-01

We propose a distributed agent architecture (DAA) that can support a variety of paradigms based on both traditional real-time computing and artificial intelligence. DAA consists of distributed agents that are classified into two categories: reactive and cognitive. Reactive agents can be implemented directly in Ada to meet hard real-time requirements and be deployed on on-board embedded processors. A traditional real-time computing methodology under consideration is the rate monotonic theory that can guarantee schedulability based on analytical methods. AI techniques under consideration for reactive agents are approximate or anytime reasoning that can be implemented using Bayesian belief networks as in Guardian. Cognitive agents are traditional expert systems that can be implemented in ART-Ada to meet soft real-time requirements. During the initial design of cognitive agents, it is critical to consider the migration path that would allow initial deployment on ground-based workstations with eventual deployment on on-board processors. ART-Ada technology enables this migration while Lisp-based technologies make it difficult if not impossible. In addition to reactive and cognitive agents, a meta-level agent would be needed to coordinate multiple agents and to provide meta-level control.

A Quality Function Deployment-Based Expert System for Cotton Fibre Selection

NASA Astrophysics Data System (ADS)

Chakraborty, Shankar; Prasad, Kanika

2018-01-01

The textile industries have seen resurgence in customers' demand for quality products during the preceding few years. This product range is extremely varied, with hand-spun and hand-woven products at one end of the spectrum, while products manufactured from the capital intensive sophisticated machineries at the other end. Since, cotton fibres are predominantly employed as the raw material for manufacturing these products, their proper selection is crucial for sustainable development of the textile/spinning industries. However, availability of numerous cotton fibre alternatives with various physical properties makes this selection process unwieldy and time consuming. Thus, there is need for a structured approach that can incorporate customers' demand into the selection process. This paper demonstrates the application of a structured and logical procedure of selecting the best cotton fibre type to fulfill a set of specified end product requirements through design and development of a quality function deployment (QFD)-based expert system. The QFD technique is employed here to provide due importance to the customers' spoken and unspoken needs, and subsequently calculate the priority weights of the considered cotton fibre properties. Two real time illustrative examples are presented to explicate the applicability and potentiality of the developed expert system to resolve cotton fibre selection problems.

Evaluation of color grading impact in restoration process of archive films

NASA Astrophysics Data System (ADS)

Fliegel, Karel; Vítek, Stanislav; Páta, Petr; Janout, Petr; Myslík, Jiří; Pecák, Josef; Jícha, Marek

2016-09-01

Color grading of archive films is a very particular task in the process of their restoration. The ultimate goal of color grading here is to achieve the same look of the movie as intended at the time of its first presentation. The role of the expert restorer, expert group and a digital colorist in this complicated process is to find the optimal settings of the digital color grading system so that the resulting image look is as close as possible to the estimate of the original reference release print adjusted by the expert group of cinematographers. A methodology for subjective assessment of perceived differences between the outcomes of color grading is introduced, and results of a subjective study are presented. Techniques for objective assessment of perceived differences are discussed, and their performance is evaluated using ground truth obtained from the subjective experiment. In particular, a solution based on calibrated digital single-lens reflex camera and subsequent analysis of image features captured from the projection screen is described. The system based on our previous work is further developed so that it can be used for the analysis of projected images. It allows assessing color differences in these images and predict their impact on the perceived difference in image look.

A Quality Function Deployment-Based Expert System for Cotton Fibre Selection

NASA Astrophysics Data System (ADS)

Chakraborty, Shankar; Prasad, Kanika

2018-06-01

The textile industries have seen resurgence in customers' demand for quality products during the preceding few years. This product range is extremely varied, with hand-spun and hand-woven products at one end of the spectrum, while products manufactured from the capital intensive sophisticated machineries at the other end. Since, cotton fibres are predominantly employed as the raw material for manufacturing these products, their proper selection is crucial for sustainable development of the textile/spinning industries. However, availability of numerous cotton fibre alternatives with various physical properties makes this selection process unwieldy and time consuming. Thus, there is need for a structured approach that can incorporate customers' demand into the selection process. This paper demonstrates the application of a structured and logical procedure of selecting the best cotton fibre type to fulfill a set of specified end product requirements through design and development of a quality function deployment (QFD)-based expert system. The QFD technique is employed here to provide due importance to the customers' spoken and unspoken needs, and subsequently calculate the priority weights of the considered cotton fibre properties. Two real time illustrative examples are presented to explicate the applicability and potentiality of the developed expert system to resolve cotton fibre selection problems.

Identification and interpretation of patterns in rocket engine data: Artificial intelligence and neural network approaches

NASA Technical Reports Server (NTRS)

Ali, Moonis; Whitehead, Bruce; Gupta, Uday K.; Ferber, Harry

1989-01-01

This paper describes an expert system which is designed to perform automatic data analysis, identify anomalous events, and determine the characteristic features of these events. We have employed both artificial intelligence and neural net approaches in the design of this expert system. The artificial intelligence approach is useful because it provides (1) the use of human experts' knowledge of sensor behavior and faulty engine conditions in interpreting data; (2) the use of engine design knowledge and physical sensor locations in establishing relationships among the events of multiple sensors; (3) the use of stored analysis of past data of faulty engine conditions; and (4) the use of knowledge-based reasoning in distinguishing sensor failure from actual faults. The neural network approach appears promising because neural nets (1) can be trained on extremely noisy data and produce classifications which are more robust under noisy conditions than other classification techniques; (2) avoid the necessity of noise removal by digital filtering and therefore avoid the need to make assumptions about frequency bands or other signal characteristics of anomalous behavior; (3) can, in effect, generate their own feature detectors based on the characteristics of the sensor data used in training; and (4) are inherently parallel and therefore are potentially implementable in special-purpose parallel hardware.

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.

Expert system verification and validation study. Delivery 1: Survey and interview questions

NASA Technical Reports Server (NTRS)

1990-01-01

The NASA funded questionnaire is presented to help define the state-of-the-practice in the formal evaluation of Expert Systems on current NASA and industry applications. The answers to this questionnaire, together with follow-up interviews, will provide realistic answers to the following questions: (1) How much evaluation is being performed; (2) What evaluation techniques are in use; and (3) What, if any, are the unique issues in evaluating Expert Systems.

A Reference and Referral System Using Expert System Techniques.

ERIC Educational Resources Information Center

Vickery, Alina; And Others

1987-01-01

Describes PLEXUS, an expert system for information retrieval related to gardening, designed at the University of London for use in public libraries. Focusing on the semantic problems encountered, methods used in artificial intelligence and information science to resolve them are discussed, including classification and facet analysis. (Author/LRW)

An Expert System for On-Site Instructional Advice.

ERIC Educational Resources Information Center

Martindale, Elizabeth S.; Hofmeister, Alan M.

1988-01-01

Describes Written Language Consultant, an expert system designed to help teachers teach special education students how to write business letters. Three main components of the system are described, including entry of students' test scores; analysis of teachers' uses of classroom time and management techniques; and suggestions for improving test…

Use of expert systems for the selection and the design of solar domestic hot water systems

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

Panteliou, S.; Dentsoras, A.; Daskalopoulos, E.

1996-07-01

The aim of this article is the study of the application of expert systems to a mechanical engineering research domain with practical and commercial interest, such as design and manufacturing of Solar Domestic Hot Water (SDHW) Systems. The issues studied were the selection and the design of SDHW systems. The application of an expert system was explored. Frame and class formalism was used for knowledge representation together with forward and backward chaining techniques for drawing conclusions and utilizing the accumulated information present. The appropriate computer program was developed to yield the selection of SDHW systems using the software tool LEONARDOmore » 3.0 (1989), an integrated environment for the development of expert systems. The developed program was tested with data according to the Greek standard ELOT corresponding to the ISO/DIS 9459-2 and it performed successfully for 21 SDHW systems available on the Greek market. Apart from the possibility of selection of a SDHW system, the program also supports the facility for updating its knowledge based with new data so that it can be adapted to changes appearing on the market. The program proved to be functional and user friendly to a high degree. 8 refs., 9 figs.« less

Fuzzy neural network methodology applied to medical diagnosis

NASA Technical Reports Server (NTRS)

Gorzalczany, Marian B.; Deutsch-Mcleish, Mary

1992-01-01

This paper presents a technique for building expert systems that combines the fuzzy-set approach with artificial neural network structures. This technique can effectively deal with two types of medical knowledge: a nonfuzzy one and a fuzzy one which usually contributes to the process of medical diagnosis. Nonfuzzy numerical data is obtained from medical tests. Fuzzy linguistic rules describing the diagnosis process are provided by a human expert. The proposed method has been successfully applied in veterinary medicine as a support system in the diagnosis of canine liver diseases.

Visualization techniques for tongue analysis in traditional Chinese medicine

NASA Astrophysics Data System (ADS)

Pham, Binh L.; Cai, Yang

2004-05-01

Visual inspection of the tongue has been an important diagnostic method of Traditional Chinese Medicine (TCM). Clinic data have shown significant connections between various viscera cancers and abnormalities in the tongue and the tongue coating. Visual inspection of the tongue is simple and inexpensive, but the current practice in TCM is mainly experience-based and the quality of the visual inspection varies between individuals. The computerized inspection method provides quantitative models to evaluate color, texture and surface features on the tongue. In this paper, we investigate visualization techniques and processes to allow interactive data analysis with the aim to merge computerized measurements with human expert's diagnostic variables based on five-scale diagnostic conditions: Healthy (H), History Cancers (HC), History of Polyps (HP), Polyps (P) and Colon Cancer (C).

A scenario for a web-based radiation treatment planning structure: A new tool for quality assurance procedure?

PubMed

Kouloulias, V E; Ntasis, E; Poortmans, Ph; Maniatis, T A; Nikita, K S

2003-01-01

The desire to develop web-based platforms for remote collaboration among physicians and technologists is becoming a great challenge. In this paper we describe a web-based radiotherapy treatment planning (WBRTP) system to facilitate decentralized radiotherapy services by allowing remote treatment planning and quality assurance (QA) of treatment delivery. Significant prerequisites are digital storage of relevant data as well as efficient and reliable telecommunication system between collaborating units. The system of WBRTP includes video conferencing, display of medical images (CT scans, dose distributions etc), replication of selected data from a common database, remote treatment planning, evaluation of treatment technique and follow-up of the treated patients. Moreover the system features real-time remote operations in terms of tele-consulting like target volume delineation performed by a team of experts at different and distant units. An appraisal of its possibilities in quality assurance in radiotherapy is also discussed. As a conclusion, a WBRTP system would not only be a medium for communication between experts in oncology but mainly a tool for improving the QA in radiotherapy.

Quantitative evaluation of variations in rule-based classifications of land cover in urban neighbourhoods using WorldView-2 imagery.

PubMed

Belgiu, Mariana; Dr Guţ, Lucian; Strobl, Josef

2014-01-01

The increasing availability of high resolution imagery has triggered the need for automated image analysis techniques, with reduced human intervention and reproducible analysis procedures. The knowledge gained in the past might be of use to achieving this goal, if systematically organized into libraries which would guide the image analysis procedure. In this study we aimed at evaluating the variability of digital classifications carried out by three experts who were all assigned the same interpretation task. Besides the three classifications performed by independent operators, we developed an additional rule-based classification that relied on the image classifications best practices found in the literature, and used it as a surrogate for libraries of object characteristics. The results showed statistically significant differences among all operators who classified the same reference imagery. The classifications carried out by the experts achieved satisfactory results when transferred to another area for extracting the same classes of interest, without modification of the developed rules.

Quantitative evaluation of variations in rule-based classifications of land cover in urban neighbourhoods using WorldView-2 imagery

PubMed Central

Belgiu, Mariana; Drǎguţ, Lucian; Strobl, Josef

2014-01-01

The increasing availability of high resolution imagery has triggered the need for automated image analysis techniques, with reduced human intervention and reproducible analysis procedures. The knowledge gained in the past might be of use to achieving this goal, if systematically organized into libraries which would guide the image analysis procedure. In this study we aimed at evaluating the variability of digital classifications carried out by three experts who were all assigned the same interpretation task. Besides the three classifications performed by independent operators, we developed an additional rule-based classification that relied on the image classifications best practices found in the literature, and used it as a surrogate for libraries of object characteristics. The results showed statistically significant differences among all operators who classified the same reference imagery. The classifications carried out by the experts achieved satisfactory results when transferred to another area for extracting the same classes of interest, without modification of the developed rules. PMID:24623959

Reducing the cognitive workload - Trouble managing power systems

NASA Technical Reports Server (NTRS)

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

1993-01-01

The complexity of space-based systems makes monitoring them and diagnosing their faults taxing for human beings. When a problem arises, immediate attention and quick resolution is mandatory. To aid humans in these endeavors we have developed an automated advisory system. Our advisory expert system, Trouble, incorporates the knowledge of the power system designers for Space Station Freedom. Trouble is designed to be a ground-based advisor for the mission controllers in the Control Center Complex at Johnson Space Center (JSC). It has been developed at NASA Lewis Research Center (LeRC) and tested in conjunction with prototype flight hardware contained in the Power Management and Distribution testbed and the Engineering Support Center, ESC, at LeRC. Our work will culminate with the adoption of these techniques by the mission controllers at JSC. This paper elucidates how we have captured power system failure knowledge, how we have built and tested our expert system, and what we believe its potential uses are.

Multivariate statistical model for 3D image segmentation with application to medical images.

PubMed

John, Nigel M; Kabuka, Mansur R; Ibrahim, Mohamed O

2003-12-01

In this article we describe a statistical model that was developed to segment brain magnetic resonance images. The statistical segmentation algorithm was applied after a pre-processing stage involving the use of a 3D anisotropic filter along with histogram equalization techniques. The segmentation algorithm makes use of prior knowledge and a probability-based multivariate model designed to semi-automate the process of segmentation. The algorithm was applied to images obtained from the Center for Morphometric Analysis at Massachusetts General Hospital as part of the Internet Brain Segmentation Repository (IBSR). The developed algorithm showed improved accuracy over the k-means, adaptive Maximum Apriori Probability (MAP), biased MAP, and other algorithms. Experimental results showing the segmentation and the results of comparisons with other algorithms are provided. Results are based on an overlap criterion against expertly segmented images from the IBSR. The algorithm produced average results of approximately 80% overlap with the expertly segmented images (compared with 85% for manual segmentation and 55% for other algorithms).

Quantitative evaluation of variations in rule-based classifications of land cover in urban neighbourhoods using WorldView-2 imagery

NASA Astrophysics Data System (ADS)

Belgiu, Mariana; ǎguţ, Lucian, , Dr; Strobl, Josef

2014-01-01

The increasing availability of high resolution imagery has triggered the need for automated image analysis techniques, with reduced human intervention and reproducible analysis procedures. The knowledge gained in the past might be of use to achieving this goal, if systematically organized into libraries which would guide the image analysis procedure. In this study we aimed at evaluating the variability of digital classifications carried out by three experts who were all assigned the same interpretation task. Besides the three classifications performed by independent operators, we developed an additional rule-based classification that relied on the image classifications best practices found in the literature, and used it as a surrogate for libraries of object characteristics. The results showed statistically significant differences among all operators who classified the same reference imagery. The classifications carried out by the experts achieved satisfactory results when transferred to another area for extracting the same classes of interest, without modification of the developed rules.

Artificial intelligent decision support for low-cost launch vehicle integrated mission operations

NASA Astrophysics Data System (ADS)

Szatkowski, Gerard P.; Schultz, Roger

1988-11-01

The feasibility, benefits, and risks associated with Artificial Intelligence (AI) Expert Systems applied to low cost space expendable launch vehicle systems are reviewed. This study is in support of the joint USAF/NASA effort to define the next generation of a heavy-lift Advanced Launch System (ALS) which will provide economical and routine access to space. The significant technical goals of the ALS program include: a 10 fold reduction in cost per pound to orbit, launch processing in under 3 weeks, and higher reliability and safety standards than current expendables. Knowledge-based system techniques are being explored for the purpose of automating decision support processes in onboard and ground systems for pre-launch checkout and in-flight operations. Issues such as: satisfying real-time requirements, providing safety validation, hardware and Data Base Management System (DBMS) interfacing, system synergistic effects, human interfaces, and ease of maintainability, have an effect on the viability of expert systems as a useful tool.

Artificial intelligent decision support for low-cost launch vehicle integrated mission operations

NASA Technical Reports Server (NTRS)

Szatkowski, Gerard P.; Schultz, Roger

1988-01-01

The feasibility, benefits, and risks associated with Artificial Intelligence (AI) Expert Systems applied to low cost space expendable launch vehicle systems are reviewed. This study is in support of the joint USAF/NASA effort to define the next generation of a heavy-lift Advanced Launch System (ALS) which will provide economical and routine access to space. The significant technical goals of the ALS program include: a 10 fold reduction in cost per pound to orbit, launch processing in under 3 weeks, and higher reliability and safety standards than current expendables. Knowledge-based system techniques are being explored for the purpose of automating decision support processes in onboard and ground systems for pre-launch checkout and in-flight operations. Issues such as: satisfying real-time requirements, providing safety validation, hardware and Data Base Management System (DBMS) interfacing, system synergistic effects, human interfaces, and ease of maintainability, have an effect on the viability of expert systems as a useful tool.

Pansharpening on the Narrow Vnir and SWIR Spectral Bands of SENTINEL-2

NASA Astrophysics Data System (ADS)

Vaiopoulos, A. D.; Karantzalos, K.

2016-06-01

In this paper results from the evaluation of several state-of-the-art pansharpening techniques are presented for the VNIR and SWIR bands of Sentinel-2. A procedure for the pansharpening is also proposed which aims at respecting the closest spectral similarities between the higher and lower resolution bands. The evaluation included 21 different fusion algorithms and three evaluation frameworks based both on standard quantitative image similarity indexes and qualitative evaluation from remote sensing experts. The overall analysis of the evaluation results indicated that remote sensing experts disagreed with the outcomes and method ranking from the quantitative assessment. The employed image quality similarity indexes and quantitative evaluation framework based on both high and reduced resolution data from the literature didn't manage to highlight/evaluate mainly the spatial information that was injected to the lower resolution images. Regarding the SWIR bands none of the methods managed to deliver significantly better results than a standard bicubic interpolation on the original low resolution bands.

Planetary Exploration Education: As Seen From the Point of View of Subject Matter Experts

NASA Astrophysics Data System (ADS)

Milazzo, M. P.; Anderson, R. B.; Gaither, T. A.; Vaughan, R. G.

2016-12-01

Planetary Learning that Advances the Nexus of Engineering, Technology, and Science (PLANETS) was selected as one of 27 new projects to support the NASA Science Mission Directorate's Science Education Cooperative Agreement Notice. Our goal is to develop and disseminate out-of-school time (OST) curricular and related educator professional development modules that integrate planetary science, technology, and engineering. We are a partnership between planetary science Subject Matter Experts (SMEs), curriculum developers, science and engineering teacher professional development experts and OST teacher networks. The PLANETS team includes the Center for Science Teaching and Learning (CSTL) at Northern Arizona University (NAU); the U.S. Geological Survey (USGS) Astrogeology Science Center (Astrogeology), and the Boston Museum of Science (MOS). Here, we present the work and approach by the SMEs at Astrogeology. As part of this overarching project, we will create a model for improved integration of SMEs, curriculum developers, professional development experts, and educators. For the 2016 and 2017 Fiscal Years, our focus is on creating science material for two OST modules designed for middle school students. We will begin development of a third module for elementary school students in the latter part of FY2017. The first module focuses on water conservation and treatment as applied on Earth, the International Space Station, and at a fictional Mars base. This unit involves the science and engineering of finding accessible water, evaluating it for quality, treating it for impurities (i.e., dissolved and suspended), initial use, a cycle of greywater treatment and re-use, and final treatment of blackwater. The second module involves the science and engineering of remote sensing as it is related to Earth and planetary exploration. This includes discussion and activities related to the electromagnetic spectrum, spectroscopy and various remote sensing systems and techniques. In these activities and discussions we include observation and measurement techniques and tools, as well as collection and use of specific data of interest to scientists. These two modules will be tested and refined based on educator and student feedback, with expected final release in late summer of 2017.

Intelligent fault management for the Space Station active thermal control system

NASA Technical Reports Server (NTRS)

Hill, Tim; Faltisco, Robert M.

1992-01-01

The Thermal Advanced Automation Project (TAAP) approach and architecture is described for automating the Space Station Freedom (SSF) Active Thermal Control System (ATCS). The baseline functionally and advanced automation techniques for Fault Detection, Isolation, and Recovery (FDIR) will be compared and contrasted. Advanced automation techniques such as rule-based systems and model-based reasoning should be utilized to efficiently control, monitor, and diagnose this extremely complex physical system. TAAP is developing advanced FDIR software for use on the SSF thermal control system. The goal of TAAP is to join Knowledge-Based System (KBS) technology, using a combination of rules and model-based reasoning, with conventional monitoring and control software in order to maximize autonomy of the ATCS. TAAP's predecessor was NASA's Thermal Expert System (TEXSYS) project which was the first large real-time expert system to use both extensive rules and model-based reasoning to control and perform FDIR on a large, complex physical system. TEXSYS showed that a method is needed for safely and inexpensively testing all possible faults of the ATCS, particularly those potentially damaging to the hardware, in order to develop a fully capable FDIR system. TAAP therefore includes the development of a high-fidelity simulation of the thermal control system. The simulation provides realistic, dynamic ATCS behavior and fault insertion capability for software testing without hardware related risks or expense. In addition, thermal engineers will gain greater confidence in the KBS FDIR software than was possible prior to this kind of simulation testing. The TAAP KBS will initially be a ground-based extension of the baseline ATCS monitoring and control software and could be migrated on-board as additional computation resources are made available.

Ingredientes Farmacéuticos Activos Potencialmente Inapropiados en Adultos Mayores: Lista IFAsPIAM: Panel de Consenso Argentino.

PubMed

Marzi, Marta M; Pires, Miryam S; Quaglia, Nora B

2018-04-18

To perform a list agreed by Argentinean experts and adapted to the local context containing potentially inappropriate (PI) medications in old people (OP) usingthe Delphi consensus technique optimized for this subject. A preliminary list of potentially inappropriate medications (PIM) was drawn up based on foreign PIM lists and a selective search in the scientific literature. The iterative Delphi process was used to submit the active pharmaceutical ingredients (APIs) of the preliminary PIM list to the panel of Argentinean experts. The analysis of theanswers to determine the arrival to the consensus was carried out applying three criteria specially defined for this purpose. After two Delphi rounds, it was not reached agreement about 12 APIs. The List of explicit criteria for PIAPIs for use in OP (IFAsPIAM List) was finally constituted by 128 APIs corresponding to 9 groups of the ATC classification system to which they were organized. In addition to each API, information justifying the unfavorable benefit/risk profile and therapeutic alternatives or recommendations/precautions was recorded. The group with the most PI APIs was N (NervousSystem) (60; 47%) followed by groups C (Cardiovascular) and M (Musculoskeletal). This study presents the first Latin American list of PIM in OP developed using an expert consensus technique. The IFAs PIAM List would contribute to the rational use of drugs in elderly population, constituting a valuable tool in Argentinean public health. Copyright © 2018. Published by Elsevier Inc.

Informal Evaluation.

ERIC Educational Resources Information Center

Engel, Brenda S.

Intended for non-experts in evaluative techniques, this monograph presents suggestions and examples for assessing: (1) the child; (2) the classroom; and (3) the program or the school. Illustrative techniques of recordkeeping are presented. Methods of collecting data include documentation and formal records. Techniques to be used during evaluation…

Behavioural Signs of Pain in Cats: An Expert Consensus

PubMed Central

Merola, Isabella; Mills, Daniel S.

2016-01-01

Objectives To identify where a consensus can be reached between veterinary experts in feline medicine on the core signs sufficient for pain (sufficient to indicate pain when they occur, but not necessarily present in all painful conditions) and necessary for pain (necessary in the presence of pain, but not always indicative of pain). Methods A modified Delphi technique was used, consisting of four rounds of questions and evaluation using nineteen participants during the period December 2014 and May 2015. Agreement was considered to be established when 80% of the experts concurred with the same opinion. Results Twenty-five signs were considered sufficient to indicate pain, but no single sign was considered necessary for it. Discussion Further studies are needed to evaluate the validity of these 25 behavioural signs if a specific pain assessment tool is to be developed that is capable of assessing pain in cats based on observational methods alone. The signs reported here may nonetheless help both vets and owners form an initial evaluation of the pain status of cats in their care. PMID:26909809

True-personality-assisted self-awareness expert system

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

Laleuf, M.

Based on psychoanalytic theory, the Who am I expert system explains in simple terms the individual's true personality, even it its unconscious or hidden aspects. Our overt personality traits are deeply rooted. The Who am I expert system gives access to an individual's primary personality, starting from his habitual everyday-life behavior: (1) describes the individual's basic personality, (2) explains this personality through the individual's deeply rooted experience and motivation, and (3) makes links with other people with a similar profile. The following are the primary features of the system: easy individual access, results in <20 minutes, and guaranteed confidentiality. Businessmore » applications include the following: (1) Individual training: Self-awareness improves a person's ability to fit in and to succeed within the group. (2) Communication: a homogeneous team has a better chance of success. (3) Human reliability: A close-knit team remains reliable even when faced with serious difficulties. (4) Recruitment: This technique enables the selection of individuals who will fit an existing homogeneous team. The system also enables a psychological diagnosis to be confirmed.« less

Battling fire and ice: remote guidance ultrasound to diagnose injury on the International Space Station and the ice rink.

PubMed

Kwon, David; Bouffard, J Antonio; van Holsbeeck, Marnix; Sargsyan, Asot E; Hamilton, Douglas R; Melton, Shannon L; Dulchavsky, Scott A

2007-03-01

National Aeronautical and Space and Administration (NASA) researchers have optimized training methods that allow minimally trained, non-physician operators to obtain diagnostic ultrasound (US) images for medical diagnosis including musculoskeletal injury. We hypothesize that these techniques could be expanded to non-expert operators including National Hockey League (NHL) and Olympic athletic trainers to diagnose musculoskeletal injuries in athletes. NHL and Olympic athletic trainers received a brief course on musculoskeletal US. Remote guidance musculoskeletal examinations were conducted by athletic trainers, consisting of hockey groin hernia, knee, ankle, elbow, or shoulder evaluations. US images were transmitted to remote experts for interpretation. Groin, knee, ankle, elbow, or shoulder images were obtained on 32 athletes; all real-time US video stream and still capture images were considered adequate for diagnostic interpretation. This experience suggests that US can be expanded for use in locations without a high level of on-site expertise. A non-physician with minimal training can perform complex, diagnostic-quality examinations when directed by a remote-based expert.

SpikeGUI: software for rapid interictal discharge annotation via template matching and online machine learning.

PubMed

Jing Jin; Dauwels, Justin; Cash, Sydney; Westover, M Brandon

2014-01-01

Detection of interictal discharges is a key element of interpreting EEGs during the diagnosis and management of epilepsy. Because interpretation of clinical EEG data is time-intensive and reliant on experts who are in short supply, there is a great need for automated spike detectors. However, attempts to develop general-purpose spike detectors have so far been severely limited by a lack of expert-annotated data. Huge databases of interictal discharges are therefore in great demand for the development of general-purpose detectors. Detailed manual annotation of interictal discharges is time consuming, which severely limits the willingness of experts to participate. To address such problems, a graphical user interface "SpikeGUI" was developed in our work for the purposes of EEG viewing and rapid interictal discharge annotation. "SpikeGUI" substantially speeds up the task of annotating interictal discharges using a custom-built algorithm based on a combination of template matching and online machine learning techniques. While the algorithm is currently tailored to annotation of interictal epileptiform discharges, it can easily be generalized to other waveforms and signal types.

SpikeGUI: Software for Rapid Interictal Discharge Annotation via Template Matching and Online Machine Learning

PubMed Central

Jin, Jing; Dauwels, Justin; Cash, Sydney; Westover, M. Brandon

2015-01-01

Detection of interictal discharges is a key element of interpreting EEGs during the diagnosis and management of epilepsy. Because interpretation of clinical EEG data is time-intensive and reliant on experts who are in short supply, there is a great need for automated spike detectors. However, attempts to develop general-purpose spike detectors have so far been severely limited by a lack of expert-annotated data. Huge databases of interictal discharges are therefore in great demand for the development of general-purpose detectors. Detailed manual annotation of interictal discharges is time consuming, which severely limits the willingness of experts to participate. To address such problems, a graphical user interface “SpikeGUI” was developed in our work for the purposes of EEG viewing and rapid interictal discharge annotation. “SpikeGUI” substantially speeds up the task of annotating interictal discharges using a custom-built algorithm based on a combination of template matching and online machine learning techniques. While the algorithm is currently tailored to annotation of interictal epileptiform discharges, it can easily be generalized to other waveforms and signal types. PMID:25570976

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)

Invited Article: Recommendations of the Neurolaryngology Study Group on Laryngeal Electromyography

PubMed Central

Blitzer, Andrew; Crumley, Roger L.; Dailey, Seth H.; Ford, Charles N.; Floeter, Mary Kay; Hillel, Allen D.; Hoffman, Henry T.; Ludlow, Christy L.; Merati, Albert; Munin, Michael C.; Robinson, Lawrence R.; Rosen, Clark; Saxon, Keith G.; Sulica, Lucian; Thibeault, Susan L.; Titze, Ingo; Woo, Peak; Woodson, Gayle E.

2009-01-01

The Neurolaryngology Study Group convened a multidisciplinary panel of experts in neuromuscular physiology, electromyography, physical medicine and rehabilitation, neurology, and laryngology to meet with interested members from the American Academy of Otolaryngology Head and Neck Surgery, the Neurolaryngology Subcommittee and the Neurolaryngology Study Group to address the use of laryngeal electromyography (LEMG) for electrodiagnosis of laryngeal disorders. The panel addressed the use of LEMG for: 1) diagnosis of vocal fold paresis, 2) best practice application of equipment and techniques for LEMG, 3) estimation of time of injury and prediction of recovery of neural injuries, 4) diagnosis of neuromuscular diseases of the laryngeal muscles, and, 5) differentiation between central nervous system and behaviorally based laryngeal disorders. The panel also addressed establishing standardized techniques and methods for future assessment of LEMG sensitivity, specificity and reliability for identification, assessment and prognosis of neurolaryngeal disorders. Previously an evidence-based review of the clinical utility of LEMG published in 2004 only found evidence supported that LEMG was possibly useful for guiding injections of botulinum toxin into the laryngeal muscles. An updated traditional/narrative literature review and expert opinions were used to direct discussion and format conclusions. In current clinical practice, LEMG is a qualitative and not a quantitative examination. Specific recommendations were made to standardize electrode types, muscles to be sampled, sampling techniques, and reporting requirements. Prospective studies are needed to determine the clinical utility of LEMG. Use of the standardized methods and reporting will support future studies correlating electro-diagnostic findings with voice and upper airway function. PMID:19467391

An expert system for the quantification of fault rates in construction fall accidents.

PubMed

Talat Birgonul, M; Dikmen, Irem; Budayan, Cenk; Demirel, Tuncay

2016-01-01

Expert witness reports, prepared with the aim of quantifying fault rates among parties, play an important role in a court's final decision. However, conflicting fault rates assigned by different expert witness boards lead to iterative objections raised by the related parties. This unfavorable situation mainly originates due to the subjectivity of expert judgments and unavailability of objective information about the causes of accidents. As a solution to this shortcoming, an expert system based on a rule-based system was developed for the quantification of fault rates in construction fall accidents. The aim of developing DsSafe is decreasing the subjectivity inherent in expert witness reports. Eighty-four inspection reports prepared by the official and authorized inspectors were examined and root causes of construction fall accidents in Turkey were identified. Using this information, an evaluation form was designed and submitted to the experts. Experts were asked to evaluate the importance level of the factors that govern fall accidents and determine the fault rates under different scenarios. Based on expert judgments, a rule-based expert system was developed. The accuracy and reliability of DsSafe were tested with real data as obtained from finalized court cases. DsSafe gives satisfactory results.

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.

Using C to build a satellite scheduling expert system: Examples from the Explorer platform planning system

NASA Technical Reports Server (NTRS)

Mclean, David R.; Tuchman, Alan; Potter, William J.

1991-01-01

Recently, many expert systems were developed in a LISP environment and then ported to the real world C environment before the final system is delivered. This situation may require that the entire system be completely rewritten in C and may actually result in a system which is put together as quickly as possible with little regard for maintainability and further evolution. With the introduction of high performance UNIX and X-windows based workstations, a great deal of the advantages of developing a first system in the LISP environment have become questionable. A C-based AI development effort is described which is based on a software tools approach with emphasis on reusability and maintainability of code. The discussion starts with simple examples of how list processing can easily be implemented in C and then proceeds to the implementations of frames and objects which use dynamic memory allocation. The implementation of procedures which use depth first search, constraint propagation, context switching and a blackboard-like simulation environment are described. Techniques for managing the complexity of C-based AI software are noted, especially the object-oriented techniques of data encapsulation and incremental development. Finally, all these concepts are put together by describing the components of planning software called the Planning And Resource Reasoning (PARR) shell. This shell was successfully utilized for scheduling services of the Tracking and Data Relay Satellite System for the Earth Radiation Budget Satellite since May 1987 and will be used for operations scheduling of the Explorer Platform in November 1991.

ART-Ada: An Ada-based expert system tool

NASA Technical Reports Server (NTRS)

Lee, S. Daniel; Allen, Bradley P.

1990-01-01

The Department of Defense mandate to standardize on Ada as the language for software systems development has resulted in an increased interest in making expert systems technology readily available in Ada environments. NASA's Space Station Freedom is an example of the large Ada software development projects that will require expert systems in the 1990's. Another large scale application that can benefit from Ada based expert system tool technology is the Pilot's Associate (PA) expert system project for military combat aircraft. The Automated Reasoning Tool-Ada (ART-Ada), an Ada expert system tool, is explained. ART-Ada allows applications of a C-based expert system tool called ART-IM to be deployed in various Ada environments. ART-Ada is being used to implement several prototype expert systems for NASA's Space Station Freedom program and the U.S. Air Force.

ART-Ada: An Ada-based expert system tool

NASA Technical Reports Server (NTRS)

Lee, S. Daniel; Allen, Bradley P.

1991-01-01

The Department of Defense mandate to standardize on Ada as the language for software systems development has resulted in increased interest in making expert systems technology readily available in Ada environments. NASA's Space Station Freedom is an example of the large Ada software development projects that will require expert systems in the 1990's. Another large scale application that can benefit from Ada based expert system tool technology is the Pilot's Associate (PA) expert system project for military combat aircraft. Automated Reasoning Tool (ART) Ada, an Ada Expert system tool is described. ART-Ada allow applications of a C-based expert system tool called ART-IM to be deployed in various Ada environments. ART-Ada is being used to implement several prototype expert systems for NASA's Space Station Freedom Program and the U.S. Air Force.

Quantitative assessment of multiple sclerosis lesion load using CAD and expert input

NASA Astrophysics Data System (ADS)

Gertych, Arkadiusz; Wong, Alexis; Sangnil, Alan; Liu, Brent J.

2008-03-01

Multiple sclerosis (MS) is a frequently encountered neurological disease with a progressive but variable course affecting the central nervous system. Outline-based lesion quantification in the assessment of lesion load (LL) performed on magnetic resonance (MR) images is clinically useful and provides information about the development and change reflecting overall disease burden. Methods of LL assessment that rely on human input are tedious, have higher intra- and inter-observer variability and are more time-consuming than computerized automatic (CAD) techniques. At present it seems that methods based on human lesion identification preceded by non-interactive outlining by CAD are the best LL quantification strategies. We have developed a CAD that automatically quantifies MS lesions, displays 3-D lesion map and appends radiological findings to original images according to current DICOM standard. CAD is also capable to display and track changes and make comparison between patient's separate MRI studies to determine disease progression. The findings are exported to a separate imaging tool for review and final approval by expert. Capturing and standardized archiving of manual contours is also implemented. Similarity coefficients calculated from quantities of LL in collected exams show a good correlation of CAD-derived results vs. those incorporated as expert's reading. Combining the CAD approach with an expert interaction may impact to the diagnostic work-up of MS patients because of improved reproducibility in LL assessment and reduced time for single MR or comparative exams reading. Inclusion of CAD-generated outlines as DICOM-compliant overlays into the image data can serve as a better reference in MS progression tracking.

Disorders of orgasm and ejaculation in men.

PubMed

McMahon, Chris G; Abdo, Carmita; Incrocci, Luca; Perelman, Michael; Rowland, David; Waldinger, Marcel; Xin, Zhong Cheng

2004-07-01

Ejaculatory/orgasmic disorders, common male sexual dysfunctions, include premature ejaculation, inhibited ejaculation, anejaculation, retrograde ejaculation and anorgasmia. To provide recommendations/guidelines concerning state-of-the-art knowledge for management of ejaculation/orgasmic disorders in men. An International Consultation in collaboration with the major urology and sexual medicine associations assembled over 200 multidisciplinary experts from 60 countries into 17 committees. Committee members established specific objectives and scopes for various male and female sexual medicine topics. The recommendations concerning state-of-the-art knowledge in the respective sexual medicine topic represent the opinion of experts from five continents developed in a process over a 2-year period. Concerning the Disorders of Ejaculation/Orgasm in Men Committee, there were nine experts from six countries. Expert opinion was based on grading of evidence-based medical literature, widespread internal committee discussion, public presentation and debate. Premature ejaculation management is dependent upon etiology. When secondary to ED, etiology-specific treatment is employed. When lifelong, initial pharmacotherapy (SSRI, topical anesthesia, PDE5 inhibitors) is appropriate. When associated with psychogenic/relationship factors, behavioral therapy is indicated. When acquired, pharmacotherapy and/or behavioral therapies are preferred. Retrograde ejaculation, diagnosed with spermatozoa and fructose in centrifuged post-ejaculatory voided urine, is managed by education, patient reassurance, pharmacotherapy or bladder neck reconstruction. Men with anejaculation or anorgasmia have a biologic failure of emission and/or psychogenic inhibited ejaculation. Men with age-related penile hypoanesthesia should be educated, reassured and be instructed in revised sexual techniques which maximize arousal. More research is needed in understanding management of men with ejaculation/orgasmic dysfunction.

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.

Testing expert systems

NASA Technical Reports Server (NTRS)

Chang, C. L.; Stachowitz, R. A.

1988-01-01

Software quality is of primary concern in all large-scale expert system development efforts. Building appropriate validation and test tools for ensuring software reliability of expert systems is therefore required. The Expert Systems Validation Associate (EVA) is a validation system under development at the Lockheed Artificial Intelligence Center. EVA provides a wide range of validation and test tools to check correctness, consistency, and completeness of an expert system. Testing a major function of EVA. It means executing an expert system with test cases with the intent of finding errors. In this paper, we describe many different types of testing such as function-based testing, structure-based testing, and data-based testing. We describe how appropriate test cases may be selected in order to perform good and thorough testing of an expert system.

A midas plugin to enable construction of reproducible web-based image processing pipelines

PubMed Central

Grauer, Michael; Reynolds, Patrick; Hoogstoel, Marion; Budin, Francois; Styner, Martin A.; Oguz, Ipek

2013-01-01

Image processing is an important quantitative technique for neuroscience researchers, but difficult for those who lack experience in the field. In this paper we present a web-based platform that allows an expert to create a brain image processing pipeline, enabling execution of that pipeline even by those biomedical researchers with limited image processing knowledge. These tools are implemented as a plugin for Midas, an open-source toolkit for creating web based scientific data storage and processing platforms. Using this plugin, an image processing expert can construct a pipeline, create a web-based User Interface, manage jobs, and visualize intermediate results. Pipelines are executed on a grid computing platform using BatchMake and HTCondor. This represents a new capability for biomedical researchers and offers an innovative platform for scientific collaboration. Current tools work well, but can be inaccessible for those lacking image processing expertise. Using this plugin, researchers in collaboration with image processing experts can create workflows with reasonable default settings and streamlined user interfaces, and data can be processed easily from a lab environment without the need for a powerful desktop computer. This platform allows simplified troubleshooting, centralized maintenance, and easy data sharing with collaborators. These capabilities enable reproducible science by sharing datasets and processing pipelines between collaborators. In this paper, we present a description of this innovative Midas plugin, along with results obtained from building and executing several ITK based image processing workflows for diffusion weighted MRI (DW MRI) of rodent brain images, as well as recommendations for building automated image processing pipelines. Although the particular image processing pipelines developed were focused on rodent brain MRI, the presented plugin can be used to support any executable or script-based pipeline. PMID:24416016

A midas plugin to enable construction of reproducible web-based image processing pipelines.

PubMed

Grauer, Michael; Reynolds, Patrick; Hoogstoel, Marion; Budin, Francois; Styner, Martin A; Oguz, Ipek

2013-01-01

Image processing is an important quantitative technique for neuroscience researchers, but difficult for those who lack experience in the field. In this paper we present a web-based platform that allows an expert to create a brain image processing pipeline, enabling execution of that pipeline even by those biomedical researchers with limited image processing knowledge. These tools are implemented as a plugin for Midas, an open-source toolkit for creating web based scientific data storage and processing platforms. Using this plugin, an image processing expert can construct a pipeline, create a web-based User Interface, manage jobs, and visualize intermediate results. Pipelines are executed on a grid computing platform using BatchMake and HTCondor. This represents a new capability for biomedical researchers and offers an innovative platform for scientific collaboration. Current tools work well, but can be inaccessible for those lacking image processing expertise. Using this plugin, researchers in collaboration with image processing experts can create workflows with reasonable default settings and streamlined user interfaces, and data can be processed easily from a lab environment without the need for a powerful desktop computer. This platform allows simplified troubleshooting, centralized maintenance, and easy data sharing with collaborators. These capabilities enable reproducible science by sharing datasets and processing pipelines between collaborators. In this paper, we present a description of this innovative Midas plugin, along with results obtained from building and executing several ITK based image processing workflows for diffusion weighted MRI (DW MRI) of rodent brain images, as well as recommendations for building automated image processing pipelines. Although the particular image processing pipelines developed were focused on rodent brain MRI, the presented plugin can be used to support any executable or script-based pipeline.

Guidance on Noncorticosteroid Systemic Immunomodulatory Therapy in Noninfectious Uveitis: Fundamentals Of Care for UveitiS (FOCUS) Initiative.

PubMed

Dick, Andrew D; Rosenbaum, James T; Al-Dhibi, Hassan A; Belfort, Rubens; Brézin, Antoine P; Chee, Soon Phaik; Davis, Janet L; Ramanan, Athimalaipet V; Sonoda, Koh-Hei; Carreño, Ester; Nascimento, Heloisa; Salah, Sawsen; Salek, Sherveen; Siak, Jay; Steeples, Laura

2018-05-01

An international, expert-led consensus initiative to develop systematic, evidence-based recommendations for the treatment of noninfectious uveitis in the era of biologics. The availability of biologic agents for the treatment of human eye disease has altered practice patterns for the management of noninfectious uveitis. Current guidelines are insufficient to assure optimal use of noncorticosteroid systemic immunomodulatory agents. An international expert steering committee comprising 9 uveitis specialists (including both ophthalmologists and rheumatologists) identified clinical questions and, together with 6 bibliographic fellows trained in uveitis, conducted a Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol systematic review of the literature (English language studies from January 1996 through June 2016; Medline [OVID], the Central Cochrane library, EMBASE, CINAHL, SCOPUS, BIOSIS, and Web of Science). Publications included randomized controlled trials, prospective and retrospective studies with sufficient follow-up, case series with 15 cases or more, peer-reviewed articles, and hand-searched conference abstracts from key conferences. The proposed statements were circulated among 130 international uveitis experts for review. A total of 44 globally representative group members met in late 2016 to refine these guidelines using a modified Delphi technique and assigned Oxford levels of evidence. In total, 10 questions were addressed resulting in 21 evidence-based guidance statements covering the following topics: when to start noncorticosteroid immunomodulatory therapy, including both biologic and nonbiologic agents; what data to collect before treatment; when to modify or withdraw treatment; how to select agents based on individual efficacy and safety profiles; and evidence in specific uveitic conditions. Shared decision-making, communication among providers and safety monitoring also were addressed as part of the recommendations. Pharmacoeconomic considerations were not addressed. Consensus guidelines were developed based on published literature, expert opinion, and practical experience to bridge the gap between clinical needs and medical evidence to support the treatment of patients with noninfectious uveitis with noncorticosteroid immunomodulatory agents. Copyright © 2018 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

A neural network architecture for implementation of expert systems for real time monitoring

NASA Technical Reports Server (NTRS)

Ramamoorthy, P. A.

1991-01-01

Since neural networks have the advantages of massive parallelism and simple architecture, they are good tools for implementing real time expert systems. In a rule based expert system, the antecedents of rules are in the conjunctive or disjunctive form. We constructed a multilayer feedforward type network in which neurons represent AND or OR operations of rules. Further, we developed a translator which can automatically map a given rule base into the network. Also, we proposed a new and powerful yet flexible architecture that combines the advantages of both fuzzy expert systems and neural networks. This architecture uses the fuzzy logic concepts to separate input data domains into several smaller and overlapped regions. Rule-based expert systems for time critical applications using neural networks, the automated implementation of rule-based expert systems with neural nets, and fuzzy expert systems vs. neural nets are covered.

Semi-automatic generation of medical tele-expert opinion for primary care physician.

PubMed

Biermann, E; Rihl, J; Schenker, M; Standl, E

2003-01-01

A computer-based system has been developed for the generation of medical expert opinions on the insulin-resistance syndrome, based on clinical data obtained from primary care physicians. An expert opinion for each patient was generated by using a decision tree for entering individual text modules and by adding optional free text. The expert opinions were returned by e-mail, telefax or by ordinary mail. 1389 primary care physician sent anonymous data sets and requested expert opinions for a total of 3768 patients. Through the set up of a rule-based system an automation of the generation of the expert opinions could be achieved and the generation time dropped from initially 40 minutes to less than 5 minutes at the end. By using predefined text modules and a rule based system, a large number of medical expert opinions can be generated with relatively few additional resources.

EMMA: The expert system for munition maintenance

NASA Technical Reports Server (NTRS)

Mullins, Barry E.

1988-01-01

Expert Missile Maintenance Aid (EMMA) is a first attempt to enhance maintenance of the tactical munition at the field and depot level by using artificial intelligence (AI) techniques. The ultimate goal of EMMA is to help a novice maintenance technician isolate and diagnose electronic, electromechanical, and mechanical equipment faults to the board/chassis level more quickly and consistently than the best human expert using the best currently available automatic test equipment (ATE). To this end, EMMA augments existing ATE with an expert system that captures the knowledge of design and maintenance experts. The EMMA program is described, including the evaluation of field-level expert system prototypes, the description of several study tasks performed during EMMA, and future plans for a follow-on program. This paper will briefly address several study tasks performed during EMMA. The paper concludes with a discussion of future plans for a follow-on program and other areas of concern.

An expert system shell for inferring vegetation characteristics: Atmospheric techniques (Task G)

NASA Technical Reports Server (NTRS)

Harrison, P. Ann; Harrison, Patrick R.

1993-01-01

The NASA VEGetation Workbench (VEG) is a knowledge based system that infers vegetation characteristics from reflectance data. The VEG Subgoals have been reorganized into categories. A new subgoal category 'Atmospheric Techniques' containing two new subgoals has been implemented. The subgoal Atmospheric Passes allows the scientist to take reflectance data measured at ground level and predict what the reflectance values would be if the data were measured at a different atmospheric height. The subgoal Atmospheric Corrections allows atmospheric corrections to be made to data collected from an aircraft or by a satellite to determine what the equivalent reflectance values would be if the data were measured at ground level. The report describes the implementation and testing of the basic framework and interface for the Atmospheric Techniques Subgoals.

Clustering Scientific Publications Based on Citation Relations: A Systematic Comparison of Different Methods.

PubMed

Šubelj, Lovro; van Eck, Nees Jan; Waltman, Ludo

2016-01-01

Clustering methods are applied regularly in the bibliometric literature to identify research areas or scientific fields. These methods are for instance used to group publications into clusters based on their relations in a citation network. In the network science literature, many clustering methods, often referred to as graph partitioning or community detection techniques, have been developed. Focusing on the problem of clustering the publications in a citation network, we present a systematic comparison of the performance of a large number of these clustering methods. Using a number of different citation networks, some of them relatively small and others very large, we extensively study the statistical properties of the results provided by different methods. In addition, we also carry out an expert-based assessment of the results produced by different methods. The expert-based assessment focuses on publications in the field of scientometrics. Our findings seem to indicate that there is a trade-off between different properties that may be considered desirable for a good clustering of publications. Overall, map equation methods appear to perform best in our analysis, suggesting that these methods deserve more attention from the bibliometric community.

Clustering Scientific Publications Based on Citation Relations: A Systematic Comparison of Different Methods

PubMed Central

Šubelj, Lovro; van Eck, Nees Jan; Waltman, Ludo

2016-01-01

Clustering methods are applied regularly in the bibliometric literature to identify research areas or scientific fields. These methods are for instance used to group publications into clusters based on their relations in a citation network. In the network science literature, many clustering methods, often referred to as graph partitioning or community detection techniques, have been developed. Focusing on the problem of clustering the publications in a citation network, we present a systematic comparison of the performance of a large number of these clustering methods. Using a number of different citation networks, some of them relatively small and others very large, we extensively study the statistical properties of the results provided by different methods. In addition, we also carry out an expert-based assessment of the results produced by different methods. The expert-based assessment focuses on publications in the field of scientometrics. Our findings seem to indicate that there is a trade-off between different properties that may be considered desirable for a good clustering of publications. Overall, map equation methods appear to perform best in our analysis, suggesting that these methods deserve more attention from the bibliometric community. PMID:27124610

Deep learning based tissue analysis predicts outcome in colorectal cancer.

PubMed

Bychkov, Dmitrii; Linder, Nina; Turkki, Riku; Nordling, Stig; Kovanen, Panu E; Verrill, Clare; Walliander, Margarita; Lundin, Mikael; Haglund, Caj; Lundin, Johan

2018-02-21

Image-based machine learning and deep learning in particular has recently shown expert-level accuracy in medical image classification. In this study, we combine convolutional and recurrent architectures to train a deep network to predict colorectal cancer outcome based on images of tumour tissue samples. The novelty of our approach is that we directly predict patient outcome, without any intermediate tissue classification. We evaluate a set of digitized haematoxylin-eosin-stained tumour tissue microarray (TMA) samples from 420 colorectal cancer patients with clinicopathological and outcome data available. The results show that deep learning-based outcome prediction with only small tissue areas as input outperforms (hazard ratio 2.3; CI 95% 1.79-3.03; AUC 0.69) visual histological assessment performed by human experts on both TMA spot (HR 1.67; CI 95% 1.28-2.19; AUC 0.58) and whole-slide level (HR 1.65; CI 95% 1.30-2.15; AUC 0.57) in the stratification into low- and high-risk patients. Our results suggest that state-of-the-art deep learning techniques can extract more prognostic information from the tissue morphology of colorectal cancer than an experienced human observer.

A blind human expert echolocator shows size constancy for objects perceived by echoes.

PubMed

Milne, Jennifer L; Anello, Mimma; Goodale, Melvyn A; Thaler, Lore

2015-01-01

Some blind humans make clicking noises with their mouth and use the reflected echoes to perceive objects and surfaces. This technique can operate as a crude substitute for vision, allowing human echolocators to perceive silent, distal objects. Here, we tested if echolocation would, like vision, show size constancy. To investigate this, we asked a blind expert echolocator (EE) to echolocate objects of different physical sizes presented at different distances. The EE consistently identified the true physical size of the objects independent of distance. In contrast, blind and blindfolded sighted controls did not show size constancy, even when encouraged to use mouth clicks, claps, or other signals. These findings suggest that size constancy is not a purely visual phenomenon, but that it can operate via an auditory-based substitute for vision, such as human echolocation.

From a Content Delivery Portal to a Knowledge Management System for Standardized Cancer Documentation.

PubMed

Schlue, Danijela; Mate, Sebastian; Haier, Jörg; Kadioglu, Dennis; Prokosch, Hans-Ulrich; Breil, Bernhard

2017-01-01

Heterogeneous tumor documentation and its challenges of interpretation of medical terms lead to problems in analyses of data from clinical and epidemiological cancer registries. The objective of this project was to design, implement and improve a national content delivery portal for oncological terms. Data elements of existing handbooks and documentation sources were analyzed, combined and summarized by medical experts of different comprehensive cancer centers. Informatics experts created a generic data model based on an existing metadata repository. In order to establish a national knowledge management system for standardized cancer documentation, a prototypical tumor wiki was designed and implemented. Requirements engineering techniques were applied to optimize this platform. It is targeted to user groups such as documentation officers, physicians and patients. The linkage to other information sources like PubMed and MeSH was realized.

[Cross-Mapping: diagnostic labels formulated according to the ICNP® versus diagnosis of NANDA International].

PubMed

Tannure, Meire Chucre; Salgado, Patrícia de Oliveira; Chianca, Tânia Couto Machado

2014-01-01

This descriptive study aimed at elaborating nursing diagnostic labels according to ICNP®; conducting a cross-mapping between the diagnostic formulations and the diagnostic labels of NANDA-I; identifying the diagnostic labels thus obtained that were also listed in the NANDA-I; and mapping them according to Basic Human Needs. The workshop technique was applied to 32 intensive care nurses, the cross-mapping and validation based on agreement with experts. The workshop produced 1665 diagnostic labels which were further refined into 120 labels. They were then submitted to a cross-mapping process with both NANDA-I diagnostic labels and the Basic Human Needs. The mapping results underwent content validation by two expert nurses leading to concordance rates of 92% and 100%. It was found that 63 labels were listed in NANDA-I and 47 were not.

Education, training, and human engineering in aerospace; SAE Aerotech '93, Costa Mesa, CA, Sep. 27-30, 1993

NASA Technical Reports Server (NTRS)

Shapiro, Diane C. (Editor); Norman, R. Michael (Editor)

1993-01-01

Advances in simulation technology are discussed by a number of government and industry experts, for both training and research and development applications. Advanced techniques, such as helmet-mounted information displays, neurocontrollers, automated training systems, and simulation for space-based systems are included. Advances in training methodology for air transportation are covered by a group of experts in that field, including discussions of advanced flight deck transition training, new training tools, and effective low cost alternatives for part-task training. With the ever-increasing emphasis on human factors in cockpit and cabin design, the section on research, advances, and certification criteria in that field is pertinent. NASA, aircraft manufacturing, and FAA representatives have compiled an informative group of presentations concerning active topics and considerations in human factors design.

Two-dimensional fuzzy fault tree analysis for chlorine release from a chlor-alkali industry using expert elicitation.

PubMed

Renjith, V R; Madhu, G; Nayagam, V Lakshmana Gomathi; Bhasi, A B

2010-11-15

The hazards associated with major accident hazard (MAH) industries are fire, explosion and toxic gas releases. Of these, toxic gas release is the worst as it has the potential to cause extensive fatalities. Qualitative and quantitative hazard analyses are essential for the identification and quantification of these hazards related to chemical industries. Fault tree analysis (FTA) is an established technique in hazard identification. This technique has the advantage of being both qualitative and quantitative, if the probabilities and frequencies of the basic events are known. This paper outlines the estimation of the probability of release of chlorine from storage and filling facility of chlor-alkali industry using FTA. An attempt has also been made to arrive at the probability of chlorine release using expert elicitation and proven fuzzy logic technique for Indian conditions. Sensitivity analysis has been done to evaluate the percentage contribution of each basic event that could lead to chlorine release. Two-dimensional fuzzy fault tree analysis (TDFFTA) has been proposed for balancing the hesitation factor involved in expert elicitation. Copyright © 2010 Elsevier B.V. All rights reserved.

Community Peer-Led Falls Prevention Presentations: What Do the Experts Suggest?

PubMed

Khong, Linda A M; Berlach, Richard G; Hill, Keith D; Hill, Anne-Marie

2018-04-01

Falls among older adults are a major problem. Despite considerable progress in falls prevention research, older adults often show low motivation to engage in recommended preventive strategies. Peer-led falls prevention education for older adults may have potential for bridging the research evidence-practice gap, thereby promoting the uptake of falls prevention strategies. We evaluated peer educators' presentations of falls prevention education to community-dwelling older adults in regard to established criteria that were consistent with adult learning principles, the framework of health behaviour change, falls prevention guidelines, and recommendations for providing falls prevention information. We conducted a within-stage mixed model study using purposive and snowball sampling techniques to recruit 10 experts to evaluate video recordings of the delivery of three peer-led falls prevention presentations. Each expert viewed three videos and rated them using a questionnaire containing both open-ended and closed items. There was a good level of expert agreement across the questionnaire domains. Though the experts rated some aspects of the presentations highly, they thought that the presentations were mainly didactic in delivery, not consistently personally relevant to the older adult audience, and did not encourage older adults to engage in the preventive strategies that were presented. Based on the experts' findings, we developed five key themes and recommendations for the effective delivery of peer-led falls prevention presentations. These included recommending that peer educators share falls prevention messages in a more interactive and experiential manner and that uptake of strategies should be facilitated by encouraging the older adults to develop a personalised action plan. Findings suggest that if peer-led falls prevention presentations capitalise on older adults' capability, opportunity, and motivation, the older adults may be more receptive to take up falls prevention messages.

Expert Consensus on the Management of Patients with Postmenopausal Osteoporosis in the Spanish Healthcare System.

PubMed

Del Pino-Montes, Javier; Blanch, Josep; Nogués, Xavier; Moro, María Jesús; Valero, María Del Carmen; Canals, Laura; Lizán, Luis

2016-04-01

The management of postmenopausal osteoporosis (PMO) in routine clinical practice differs considerably from guideline recommendations. The objective of our study was to reach a consensus on the management of PMO, considering prevention, diagnosis, treatment and follow-up, according to expert opinion in Spain. A two-round Delphi technique was conducted, including 38 experts. The questionnaire contained 35 sections, each one including 1-10 questions (n = 308) based on a literature review and contributions from the scientific steering committee. Each question was scored by experts from the current (1 = no occurrence, 9 = occurrence in all cases), wish (1 = total rejection; 9 = wish) and prediction (1 = no occurrence at all; 9 = occurs with maximum probability) perspectives. Consensus (wish and prediction perspectives) was considered when ≥75% of experts scored 7-9 (agreement) or 1-3 (disagreement). Overall, consensus was achieved on 75% of questions. While protocols of clinical management and consultation/referral should be followed, their implementation is unlikely. Furthermore, the medical specialties currently involved in PMO management are poorly defined. PMO patients without fracture should be managed (prevention, diagnosis, treatment and follow-up) in both primary care and rheumatology settings; however, experts predicted that only treatment and follow-up will be assumed by these specialties. A multidisciplinary team should be involved in patients with fracture. No assessment tools are usually applied, and prediction indicated that they will not be used. Efforts should be focused on questions with high divergence between wishes and predictions, defining actions that will improve PMO management. Collaboration between scientific societies and health authorities to address the identified opportunities of improvement is proposed. Amgen S.A.

A framework for the computer-aided planning and optimisation of manufacturing processes for components with functional graded properties

NASA Astrophysics Data System (ADS)

Biermann, D.; Gausemeier, J.; Heim, H.-P.; Hess, S.; Petersen, M.; Ries, A.; Wagner, T.

2014-05-01

In this contribution a framework for the computer-aided planning and optimisation of functional graded components is presented. The framework is divided into three modules - the "Component Description", the "Expert System" for the synthetisation of several process chains and the "Modelling and Process Chain Optimisation". The Component Description module enhances a standard computer-aided design (CAD) model by a voxel-based representation of the graded properties. The Expert System synthesises process steps stored in the knowledge base to generate several alternative process chains. Each process chain is capable of producing components according to the enhanced CAD model and usually consists of a sequence of heating-, cooling-, and forming processes. The dependencies between the component and the applied manufacturing processes as well as between the processes themselves need to be considered. The Expert System utilises an ontology for that purpose. The ontology represents all dependencies in a structured way and connects the information of the knowledge base via relations. The third module performs the evaluation of the generated process chains. To accomplish this, the parameters of each process are optimised with respect to the component specification, whereby the result of the best parameterisation is used as representative value. Finally, the process chain which is capable of manufacturing a functionally graded component in an optimal way regarding to the property distributions of the component description is presented by means of a dedicated specification technique.

Prioritizing public- private partnership models for public hospitals of iran based on performance indicators.

PubMed

Gholamzadeh Nikjoo, Raana; Jabbari Beyrami, Hossein; Jannati, Ali; Asghari Jaafarabadi, Mohammad

2012-01-01

The present study was conducted to scrutinize Public- Private Partnership (PPP) models in public hospitals of different countries based on performance indicators in order to se-lect appropriated models for Iran hospitals. In this mixed (quantitative-qualitative) study, systematic review and expert panel has been done to identify varied models of PPP as well as performance indicators. In the second step we prioritized performance indicator and PPP models based on selected performance indicators by Analytical Hierarchy process (AHP) technique. The data were analyzed by Excel 2007 and Expert Choice11 software's. In quality - effectiveness area, indicators like the rate of hospital infections (100%), hospital accidents prevalence rate (73%), pure rate of hospital mortality (63%), patient satisfaction percentage (53%), in accessibility equity area indicators such as average inpatient waiting time (100%) and average outpatient waiting time (74%), and in financial - efficiency area, indicators including average length of stay (100%), bed occupation ratio (99%), specific income to total cost ratio (97%) have been chosen to be the most key performance indicators. In the pri¬oritization of the PPP models clinical outsourcing, management, privatization, BOO (build, own, operate) and non-clinical outsourcing models, achieved high priority for various performance in¬dicator areas. This study had been provided the most common PPP options in the field of public hospitals and had gathered suitable evidences from experts for choosing appropriate PPP option for public hospitals. Effect of private sector presence in public hospital performance, based on which PPP options undertaken, will be different.

Prioritizing Public- Private Partnership Models for Public Hospitals of Iran Based on Performance Indicators

PubMed Central

Gholamzadeh Nikjoo, Raana; Jabbari Beyrami, Hossein; Jannati, Ali; Asghari Jaafarabadi, Mohammad

2012-01-01

Background: The present study was conducted to scrutinize Public- Private Partnership (PPP) models in public hospitals of different countries based on performance indicators in order to se-lect appropriated models for Iran hospitals. Methods: In this mixed (quantitative-qualitative) study, systematic review and expert panel has been done to identify varied models of PPP as well as performance indicators. In the second step we prioritized performance indicator and PPP models based on selected performance indicators by Analytical Hierarchy process (AHP) technique. The data were analyzed by Excel 2007 and Expert Choice11 software’s. Results: In quality – effectiveness area, indicators like the rate of hospital infections (100%), hospital accidents prevalence rate (73%), pure rate of hospital mortality (63%), patient satisfaction percentage (53%), in accessibility equity area indicators such as average inpatient waiting time (100%) and average outpatient waiting time (74%), and in financial – efficiency area, indicators including average length of stay (100%), bed occupation ratio (99%), specific income to total cost ratio (97%) have been chosen to be the most key performance indicators. In the pri¬oritization of the PPP models clinical outsourcing, management, privatization, BOO (build, own, operate) and non-clinical outsourcing models, achieved high priority for various performance in¬dicator areas. Conclusion: This study had been provided the most common PPP options in the field of public hospitals and had gathered suitable evidences from experts for choosing appropriate PPP option for public hospitals. Effect of private sector presence in public hospital performance, based on which PPP options undertaken, will be different. PMID:24688942

Knowledge-based fault diagnosis system for refuse collection vehicle

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

Tan, CheeFai; Juffrizal, K.; Khalil, S. N.

The refuse collection vehicle is manufactured by local vehicle body manufacturer. Currently; the company supplied six model of the waste compactor truck to the local authority as well as waste management company. The company is facing difficulty to acquire the knowledge from the expert when the expert is absence. To solve the problem, the knowledge from the expert can be stored in the expert system. The expert system is able to provide necessary support to the company when the expert is not available. The implementation of the process and tool is able to be standardize and more accurate. The knowledgemore » that input to the expert system is based on design guidelines and experience from the expert. This project highlighted another application on knowledge-based system (KBS) approached in trouble shooting of the refuse collection vehicle production process. The main aim of the research is to develop a novel expert fault diagnosis system framework for the refuse collection vehicle.« less

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

ART-Ada design project, phase 2

NASA Technical Reports Server (NTRS)

Lee, S. Daniel; Allen, Bradley P.

1990-01-01

Interest in deploying expert systems in Ada has increased. An Ada based expert system tool is described called ART-Ada, which was built to support research into the language and methodological issues of expert systems in Ada. ART-Ada allows applications of an existing expert system tool called ART-IM (Automated Reasoning Tool for Information Management) to be deployed in various Ada environments. ART-IM, a C-based expert system tool, is used to generate Ada source code which is compiled and linked with an Ada based inference engine to produce an Ada executable image. ART-Ada is being used to implement several expert systems for NASA's Space Station Freedom Program and the U.S. Air Force.

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.

- and Scene-Guided Integration of Tls and Photogrammetric Point Clouds for Landslide Monitoring

NASA Astrophysics Data System (ADS)

Zieher, T.; Toschi, I.; Remondino, F.; Rutzinger, M.; Kofler, Ch.; Mejia-Aguilar, A.; Schlögel, R.

2018-05-01

Terrestrial and airborne 3D imaging sensors are well-suited data acquisition systems for the area-wide monitoring of landslide activity. State-of-the-art surveying techniques, such as terrestrial laser scanning (TLS) and photogrammetry based on unmanned aerial vehicle (UAV) imagery or terrestrial acquisitions have advantages and limitations associated with their individual measurement principles. In this study we present an integration approach for 3D point clouds derived from these techniques, aiming at improving the topographic representation of landslide features while enabling a more accurate assessment of landslide-induced changes. Four expert-based rules involving local morphometric features computed from eigenvectors, elevation and the agreement of the individual point clouds, are used to choose within voxels of selectable size which sensor's data to keep. Based on the integrated point clouds, digital surface models and shaded reliefs are computed. Using an image correlation technique, displacement vectors are finally derived from the multi-temporal shaded reliefs. All results show comparable patterns of landslide movement rates and directions. However, depending on the applied integration rule, differences in spatial coverage and correlation strength emerge.

A genetic algorithms approach for altering the membership functions in fuzzy logic controllers

NASA Technical Reports Server (NTRS)

Shehadeh, Hana; Lea, Robert N.

1992-01-01

Through previous work, a fuzzy control system was developed to perform translational and rotational control of a space vehicle. This problem was then re-examined to determine the effectiveness of genetic algorithms on fine tuning the controller. This paper explains the problems associated with the design of this fuzzy controller and offers a technique for tuning fuzzy logic controllers. A fuzzy logic controller is a rule-based system that uses fuzzy linguistic variables to model human rule-of-thumb approaches to control actions within a given system. This 'fuzzy expert system' features rules that direct the decision process and membership functions that convert the linguistic variables into the precise numeric values used for system control. Defining the fuzzy membership functions is the most time consuming aspect of the controller design. One single change in the membership functions could significantly alter the performance of the controller. This membership function definition can be accomplished by using a trial and error technique to alter the membership functions creating a highly tuned controller. This approach can be time consuming and requires a great deal of knowledge from human experts. In order to shorten development time, an iterative procedure for altering the membership functions to create a tuned set that used a minimal amount of fuel for velocity vector approach and station-keep maneuvers was developed. Genetic algorithms, search techniques used for optimization, were utilized to solve this problem.

Advanced Automation for Ion Trap Mass Spectrometry-New Opportunities for Real-Time Autonomous Analysis

NASA Technical Reports Server (NTRS)

Palmer, Peter T.; Wong, C. M.; Salmonson, J. D.; Yost, R. A.; Griffin, T. P.; Yates, N. A.; Lawless, James G. (Technical Monitor)

1994-01-01

The utility of MS/MS for both target compound analysis and the structure elucidation of unknowns has been described in a number of references. A broader acceptance of this technique has not yet been realized as it requires large, complex, and costly instrumentation which has not been competitive with more conventional techniques. Recent advancements in ion trap mass spectrometry promise to change this situation. Although the ion trap's small size, sensitivity, and ability to perform multiple stages of mass spectrometry have made it eminently suitable for on-line, real-time monitoring applications, advance automation techniques are required to make these capabilities more accessible to non-experts. Towards this end we have developed custom software for the design and implementation of MS/MS experiments. This software allows the user to take full advantage of the ion trap's versatility with respect to ionization techniques, scan proxies, and ion accumulation/ejection methods. Additionally, expert system software has been developed for autonomous target compound analysis. This software has been linked to ion trap control software and a commercial data system to bring all of the steps in the analysis cycle under control of the expert system. These software development efforts and their utilization for a number of trace analysis applications will be described.

IRCAD recommendation on safe laparoscopic cholecystectomy.

PubMed

Conrad, Claudius; Wakabayashi, Go; Asbun, Horacio J; Dallemagne, Bernard; Demartines, Nicolas; Diana, Michele; Fuks, David; Giménez, Mariano Eduardo; Goumard, Claire; Kaneko, Hironori; Memeo, Riccardo; Resende, Alexandre; Scatton, Olivier; Schneck, Anne-Sophie; Soubrane, Olivier; Tanabe, Minoru; van den Bos, Jacqueline; Weiss, Helmut; Yamamoto, Masakazu; Marescaux, Jacques; Pessaux, Patrick

2017-11-01

An expert recommendation conference was conducted to identify factors associated with adverse events during laparoscopic cholecystectomy (LC) with the goal of deriving expert recommendations for the reduction of biliary and vascular injury. Nineteen hepato-pancreato-biliary (HPB) surgeons from high-volume surgery centers in six countries comprised the Research Institute Against Cancer of the Digestive System (IRCAD) Recommendations Group. Systematic search of PubMed, Cochrane, and Embase was conducted. Using nominal group technique, structured group meetings were held to identify key items for safer LC. Consensus was achieved when 80% of respondents ranked an item as 1 or 2 (Likert scale 1-4). Seventy-one IRCAD HPB course participants assessed the expert recommendations which were compared to responses of 37 general surgery course participants. The IRCAD recommendations were structured in seven statements. The key topics included exposure of the operative field, appropriate use of energy device and establishment of the critical view of safety (CVS), systematic preoperative imaging, cholangiogram and alternative techniques, role of partial and dome-down (fundus-first) cholecystectomy. Highest consensus was achieved on the importance of the CVS as well as dome-down technique and partial cholecystectomy as alternative techniques. The put forward IRCAD recommendations may help to promote safe surgical practice of LC and initiate specific training to avoid adverse events. © 2017 Japanese Society of Hepato-Biliary-Pancreatic Surgery.

Electrochemical immunoassay for tumor markers based on hydrogels.

PubMed

Yin, Shuang; Ma, Zhanfang

2018-05-08

Hydrogel-based electrochemical immunoassays exhibit a large surface-to-volume ratio, excellent biocompatibility, unique stimuli-responsive behavior, high permeability and hydrophilicity and, thus, have shown great potential in the sensitive and accurate detection of tumor markers. Electrochemical immunosensing techniques for tumor markers based on hydrogels have greatly progressed in recent years. Areas covered: In this review, the authors describe the recent advances of hydrogel-based electrochemical immunosensing interface of tumor markers based on the different functions of hydrogels including conductive, catalytic, redox, stimuli-responsive and antifouling hydrogels. Expert commentary: Hydrogels have been successfully employed in electrochemical immunoassay of tumor markers, which is accountable to their unique properties. For further exploitation of hydrogel-based electrochemical biosensors, more variety of hydrogels need be fabricated with improved functionality.

Expert Systems: An Overview for Teacher-Librarians.

ERIC Educational Resources Information Center

Orwig, Gary; Barron, Ann

1992-01-01

Provides an overview of expert systems for teacher librarians. Highlights include artificial intelligence and expert systems; the development of the MYCIN medical expert system; rule-based expert systems; the use of expert system shells to develop a specific system; and how to select an appropriate application for an expert system. (11 references)…

Better Field Instruction by Using Jigsaw Groups

NASA Astrophysics Data System (ADS)

Sammons, J. I.; Murray, D. P.

2006-12-01

Do any of these sound familiar? Most of my students do well at field stops, but there are always the few at the back. I'd like to guest speak at the local High School, but the students have too little background. I wish I could spark the interest of my introductory classes. Jigsaw is the solution to these problems. This easy-to-apply technique puts students in the driver's seat. They make the inferences-they own the discovery. You'll see that "A-ha!" as though it were a first time event. Jigsaw brings new excitement to familiar activities for every student in your class, even that guy in the back. Best of all, the technique does not depend on the style or force of personality of the instructor. It is easy to learn and suitable for use by Teaching Assistants. Here's how it works: 1. Identify the critical concepts necessary for a full understanding of the field stop or activity. 2. Divide your class into Expert Groups. The members of each Expert Group will master one of these critical concepts. 3.Dissolve the Expert Groups. Divide your class into new Jigsaw Groups to address the field stop or activity. Each Jigsaw Group includes members from each Expert Group. Like pieces of a puzzle, each Jigsaw Group member brings a critical piece to the problem. This talk will demonstrate Jigsaw Groups in action at a field stop. You'll see the crucial identification of critical concepts, small lab explorations carried out by the Expert Groups to master their assigned concepts, and Jigsaw Groups working a complex geological feature. You'll learn how to trouble-shoot less-than-successful first attempts and you'll leave with a step-by-step template that will allow you to adapt your existing activities to Jigsaw technique.

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…

Spatial modeling of environmental vulnerability of marine finfish aquaculture using GIS-based neuro-fuzzy techniques.

PubMed

Navas, Juan Moreno; Telfer, Trevor C; Ross, Lindsay G

2011-08-01

Combining GIS with neuro-fuzzy modeling has the advantage that expert scientific knowledge in coastal aquaculture activities can be incorporated into a geospatial model to classify areas particularly vulnerable to pollutants. Data on the physical environment and its suitability for aquaculture in an Irish fjard, which is host to a number of different aquaculture activities, were derived from a three-dimensional hydrodynamic and GIS models. Subsequent incorporation into environmental vulnerability models, based on neuro-fuzzy techniques, highlighted localities particularly vulnerable to aquaculture development. The models produced an overall classification accuracy of 85.71%, with a Kappa coefficient of agreement of 81%, and were sensitive to different input parameters. A statistical comparison between vulnerability scores and nitrogen concentrations in sediment associated with salmon cages showed good correlation. Neuro-fuzzy techniques within GIS modeling classify vulnerability of coastal regions appropriately and have a role in policy decisions for aquaculture site selection. Copyright © 2011 Elsevier Ltd. All rights reserved.

Use of the Delphi method in resolving complex water resources issues

USGS Publications Warehouse

Taylor, J.G.; Ryder, S.D.

2003-01-01

The tri-state river basins, shared by Georgia, Alabama, and Florida, are being modeled by the U.S. Fish and Wildlife Service and the U.S. Army Corps of Engineers to help facilitate agreement in an acrimonious water dispute among these different state governments. Modeling of such basin reservoir operations requires parallel understanding of several river system components: hydropower production, flood control, municipal and industrial water use, navigation, and reservoir fisheries requirements. The Delphi method, using repetitive surveying of experts, was applied to determine fisheries' water and lake-level requirements on 25 reservoirs in these interstate basins. The Delphi technique allowed the needs and requirements of fish populations to be brought into the modeling effort on equal footing with other water supply and demand components. When the subject matter is concisely defined and limited, this technique can rapidly assess expert opinion on any natural resource issue, and even move expert opinion toward greater agreement.

Video markers tracking methods for bike fitting

NASA Astrophysics Data System (ADS)

Rajkiewicz, Piotr; Łepkowska, Katarzyna; Cygan, Szymon

2015-09-01

Sports cycling is becoming increasingly popular over last years. Obtaining and maintaining a proper position on the bike has been shown to be crucial for performance, comfort and injury avoidance. Various techniques of bike fitting are available - from rough settings based on body dimensions to professional services making use of sophisticated equipment and expert knowledge. Modern fitting techniques use mainly joint angles as a criterion of proper position. In this work we examine performance of two proposed methods for dynamic cyclist position assessment based on video data recorded during stationary cycling. Proposed methods are intended for home use, to help amateur cyclist improve their position on the bike, and therefore no professional equipment is used. As a result of data processing, ranges of angles in selected joints are provided. Finally strengths and weaknesses of both proposed methods are discussed.

[The currently available possibilities for the application of photogrammetry in the forensic medical expertise of the blood stains at the scene of the crime].

PubMed

Fetisov, V A; Makarov, I Yu; Gusarov, A A; Lorents, A S; Smirenin, S A; Stragis, V B

The study of blood stains retained at the scene of the crime is of crucial importance for the preliminary inquiry. The present article is focused on the analysis of the possibilities and prospects for the use of photogrammetry (PM) as exemplified by the foreign expert practice of the blood stains examination at the site of the event. It is shown that the results of the application of digital photogrammetry in addition to the traditional methods of morphological investigations enables the forensic medical experts to reconstruct a number of unique features and circumstances that accompanied the commission of a crime at the site of the event. Such PM techniques supplemented by the ballistic analysis of the blood splatter and droplet trajectories provides additional evidence that allows the forensic medical experts to reconstruct the scene of the crime including the pose and position of the victim at the moment of causing injury. Moreover, these data make it possible to determine the maximum number and the sequence of injurious impacts (blows). The authors discuss the advantages and relative disadvantages of the application of the photogrammetric technique in the routine practical expert work. It is emphasized that the published decision making algorithms provide the specialists in various disciplines and professional experts with the ready-made technological tools for obtaining the additional criteria for the objective improvement of the quality of the studies they carry out and for the enhancement of the value of expert conclusions. It is concluded that the application of the modern photogrammetric technologies can be recommended for the solution of the applied forensic medical problems and conducting the relevant expert research.

The role of collaborative ontology development in the knowledge negotiation process

NASA Astrophysics Data System (ADS)

Rivera, Norma

Interdisciplinary research (IDR) collaboration can be defined as the process of integrating experts' knowledge, perspectives, and resources to advance scientific discovery. The flourishing of more complex research problems, together with the growth of scientific and technical knowledge has resulted in the need for researchers from diverse fields to provide different expertise and points of view to tackle these problems. These collaborations, however, introduce a new set of "culture" barriers as participating experts are trained to communicate in discipline-specific languages, theories, and research practices. We propose that building a common knowledge base for research using ontology development techniques can provide a starting point for interdisciplinary knowledge exchange, negotiation, and integration. The goal of this work is to extend ontology development techniques to support the knowledge negotiation process in IDR groups. Towards this goal, this work presents a methodology that extends previous work in collaborative ontology development and integrates learning strategies and tools to enhance interdisciplinary research practices. We evaluate the effectiveness of applying such methodology in three different scenarios that cover educational and research settings. The results of this evaluation confirm that integrating learning strategies can, in fact, be advantageous to overall collaborative practices in IDR groups.

Expert approaches to promote adolescent physical activity in Iran: development of the promoting strategies using the Nominal Group Technique meeting.

PubMed

Baheiraei, Azam; Hamzehgardeshi, Zeinab; Mohammadi, Mohammad Reza; Mohammadi, Eesa; Vedadhir, AbouAli

2014-07-01

Several studies have shown that physical activity decreases as the age increases. This study was for evaluating the perspectives of health sciences specialists or informants on the strategies for increasing physical activity among Iranian adolescents using Nominal Group Technique (NGT). a semiquantitative/qualitative methodology research using NGT for prioritizing the strategies for alleviating the physical activities among Iranian adolescents based on the opinions of health sciences experts. This study conducted in Tehran, Iran, 2011. Overall, 16 items received scores from 2-29 and were further listed as the accepted strategies for promoting physical activity among adolescents. The most and least recommended strategies were respectively in the categories of school, neighborhood and family. This study findings show 'the constructionist activities or strategies (eg, claim-making, image-making, myth-constructing and framing) among adolescents using main claim-makers of Iranian society, including the state-sponsored media.,' received the highest score by all the participants of NGT. The interesting finding of this study is the special view point of the specialists to role of socioecological factors in promoting physical activity in the context of Iranian society.

Development of a Postacute Hospital Item Bank for the New Pediatric Evaluation of Disability Inventory-Computer Adaptive Test

ERIC Educational Resources Information Center

Dumas, Helene M.

2010-01-01

The PEDI-CAT is a new computer adaptive test (CAT) version of the Pediatric Evaluation of Disability Inventory (PEDI). Additional PEDI-CAT items specific to postacute pediatric hospital care were recently developed using expert reviews and cognitive interviewing techniques. Expert reviews established face and construct validity, providing positive…

Quasi-Algorithm Methods and Techniques for Specifying Objective Job/Task Performance Requirements

DTIC Science & Technology

1978-07-01

succeeding experts. While "dottings of i’s and crossings of t’s" may still occur, these trivia no longer significantly affect the course of task...That is, as soon as a branch entered under the assunption that condi- tion A applied was completed, administrator and expert recycled to the

Risk analysis with a fuzzy-logic approach of a complex installation

NASA Astrophysics Data System (ADS)

Peikert, Tim; Garbe, Heyno; Potthast, Stefan

2016-09-01

This paper introduces a procedural method based on fuzzy logic to analyze systematic the risk of an electronic system in an intentional electromagnetic environment (IEME). The method analyzes the susceptibility of a complex electronic installation with respect to intentional electromagnetic interference (IEMI). It combines the advantages of well-known techniques as fault tree analysis (FTA), electromagnetic topology (EMT) and Bayesian networks (BN) and extends the techniques with an approach to handle uncertainty. This approach uses fuzzy sets, membership functions and fuzzy logic to handle the uncertainty with probability functions and linguistic terms. The linguistic terms add to the risk analysis the knowledge from experts of the investigated system or environment.

New Approach to Image Aerogels by Scanning Electron Microscopy

NASA Astrophysics Data System (ADS)

Solá, Francisco; Hurwitz, Frances; Yang, Jijing

2011-03-01

A new scanning electron microscopy (SEM) technique to image poor electrically conductive aerogels is presented. The process can be performed by non-expert SEM users. We showed that negative charging effects on aerogels can be minimized significantly by inserting dry nitrogen gas close to the region of interest. The process involves the local recombination of accumulated negative charges with positive ions generated from ionization processes. This new technique made possible the acquisition of images of aerogels with pores down to approximately 3nm in diameter using a positively biased Everhart-Thornley (E-T) detector. Well-founded concepts based on known models will also be presented with the aim to explain the results qualitatively.

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.

Consensus on Recording Deep Endometriosis Surgery: the CORDES statement.

PubMed

Vanhie, A; Meuleman, C; Tomassetti, C; Timmerman, D; D'Hoore, A; Wolthuis, A; Van Cleynenbreugel, B; Dancet, E; Van den Broeck, U; Tsaltas, J; Renner, S P; Ebert, A D; Carmona, F; Abbott, J; Stepniewska, A; Taylor, H; Saridogan, E; Mueller, M; Keckstein, J; Pluchino, N; Janik, G; Zupi, E; Minelli, L; Cooper, M; Dunselman, G; Koh, C; Abrao, M S; Chapron, C; D'Hooghe, T

2016-06-01

Which essential items should be recorded before, during and after endometriosis surgery and in clinical outcome based surgical trials in patients with deep endometriosis (DE)? A DE surgical sheet (DESS) was developed for standardized reporting of the surgical treatment of DE and an international expert consensus proposal on relevant items that should be recorded in surgical outcome trials in women with DE. Surgery is an important treatment for symptomatic DE. So far, data have been reported in such a way that comparison of different surgical techniques is impossible. Therefore, we present an international expert proposal for standardized reporting of surgical treatment and surgical outcome trials in women with DE. International expert consensus based on a systematic review of literature. Taking into account recommendations from Consolidated Standards of Reporting Trials (CONSORT), the Innovation Development Exploration Assessment and Long-term Study (IDEAL), the Initiative on Methods, Measurement and Pain Assessment in Clinical trials (IMMPACT) and the World Endometriosis Research Foundation Phenome and Biobanking Harmonisation Project (WERF EPHect), a systematic literature review on surgical treatment of DE was performed and resulted in a proposal for standardized reporting, adapted by contributions from eight members of the multidisciplinary Leuven University Hospitals Endometriosis Care Program, from 18 international experts and from audience feedback during three international meetings. We have developed the DESS to record in detail the surgical procedures for DE, and an international consensus on pre-, intra- and post-operative data that should be recorded in surgical outcome trials on DE. The recommendations in this paper represent a consensus among international experts based on a systematic review of the literature. For several items and recommendations, high-quality RCTs were not available. Further research is needed to validate and evaluate the recommendations presented here. This international expert consensus for standardized reporting of surgical treatment in women with DE, based on a systematic literature review and international consensus, can be used as a guideline to record and report surgical management of patients with DE and as a guideline to design, execute, interpret and compare clinical trials in this patient population. None of the authors received funding for the development of this paper. M.A. reports personal fees and non-financial support from Bayer Pharma outside the submitted work; H.T. reports a grant from Pfizer and personal fees for being on the advisory board of Perrigo, Abbvie, Allergan and SPD. N/A. © The Author 2016. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Efficient fuzzy Bayesian inference algorithms for incorporating expert knowledge in parameter estimation

NASA Astrophysics Data System (ADS)

Rajabi, Mohammad Mahdi; Ataie-Ashtiani, Behzad

2016-05-01

Bayesian inference has traditionally been conceived as the proper framework for the formal incorporation of expert knowledge in parameter estimation of groundwater models. However, conventional Bayesian inference is incapable of taking into account the imprecision essentially embedded in expert provided information. In order to solve this problem, a number of extensions to conventional Bayesian inference have been introduced in recent years. One of these extensions is 'fuzzy Bayesian inference' which is the result of integrating fuzzy techniques into Bayesian statistics. Fuzzy Bayesian inference has a number of desirable features which makes it an attractive approach for incorporating expert knowledge in the parameter estimation process of groundwater models: (1) it is well adapted to the nature of expert provided information, (2) it allows to distinguishably model both uncertainty and imprecision, and (3) it presents a framework for fusing expert provided information regarding the various inputs of the Bayesian inference algorithm. However an important obstacle in employing fuzzy Bayesian inference in groundwater numerical modeling applications is the computational burden, as the required number of numerical model simulations often becomes extremely exhaustive and often computationally infeasible. In this paper, a novel approach of accelerating the fuzzy Bayesian inference algorithm is proposed which is based on using approximate posterior distributions derived from surrogate modeling, as a screening tool in the computations. The proposed approach is first applied to a synthetic test case of seawater intrusion (SWI) in a coastal aquifer. It is shown that for this synthetic test case, the proposed approach decreases the number of required numerical simulations by an order of magnitude. Then the proposed approach is applied to a real-world test case involving three-dimensional numerical modeling of SWI in Kish Island, located in the Persian Gulf. An expert elicitation methodology is developed and applied to the real-world test case in order to provide a road map for the use of fuzzy Bayesian inference in groundwater modeling applications.

CE: Original Research: Creating an Evidence-Based Progression for Clinical Advancement Programs.

PubMed

Burke, Kathleen G; Johnson, Tonya; Sites, Christine; Barnsteiner, Jane

2017-05-01

: Background: The Institute of Medicine (IOM) and the Quality and Safety Education for Nurses (QSEN) project have identified six nursing competencies and supported their integration into undergraduate and graduate nursing curricula nationwide. But integration of those competencies into clinical practice has been limited, and evidence for the progression of competency proficiency within clinical advancement programs is scant. Using an evidence-based approach and building on the competencies identified by the IOM and QSEN, a team of experts at an academic health system developed eight competency domains and 186 related knowledge, skills, and attitudes (KSAs) for professional nursing practice. The aim of our study was to validate the eight identified competencies and 186 related KSAs and determine their developmental progression within a clinical advancement program. Using the Delphi technique, nursing leadership validated the newly identified competency domains and KSAs as essential to practice. Clinical experts from 13 Magnet-designated hospitals with clinical advancement programs then participated in Delphi rounds aimed at reaching consensus on the developmental progression of the 186 KSAs through four levels of clinical advancement. Two Delphi rounds resulted in consensus by the expert participants. All eight competency domains were determined to be essential at all four levels of clinical practice. At the novice level of practice, the experts identified a greater number of KSAs in the domains of safety and patient- and family-centered care. At more advanced practice levels, the experts identified a greater number of KSAs in the domains of professionalism, teamwork, technology and informatics, and continuous quality improvement. Incorporating the eight competency domains and the 186 KSAs into a framework for clinical advancement programs will likely result in more clearly defined role expectations; enhance accountability; and elevate and promote nursing practice, thereby improving clinical outcomes and quality of care. With their emphasis on quality and safety, the eight competency domains also offer a framework for enhancing position descriptions, performance evaluations, clinical recognition, initial and ongoing competency assessment programs, and orientation and residency programs.

Expert systems tools for Hubble Space Telescope observation scheduling

NASA Technical Reports Server (NTRS)

Miller, Glenn; Rosenthal, Don; Cohen, William; Johnston, Mark

1987-01-01

The utility of expert systems techniques for the Hubble Space Telescope (HST) planning and scheduling is discussed and a plan for development of expert system tools which will augment the existing ground system is described. Additional capabilities provided by these tools will include graphics-oriented plan evaluation, long-range analysis of the observation pool, analysis of optimal scheduling time intervals, constructing sequences of spacecraft activities which minimize operational overhead, and optimization of linkages between observations. Initial prototyping of a scheduler used the Automated Reasoning Tool running on a LISP workstation.

The "right" way is not always popular: comparison of surgeons' perceptions during laparoscopic cholecystectomy for acute cholecystitis among experts from Japan, Korea and Taiwan.

PubMed

Hibi, Taizo; Iwashita, Yukio; Ohyama, Tetsuji; Honda, Goro; Yoshida, Masahiro; Takada, Tadahiro; Han, Ho-Seong; Hwang, Tsann-Long; Shinya, Satoshi; Suzuki, Kenji; Umezawa, Akiko; Yoon, Yoo-Seok; Choi, In-Seok; Huang, Wayne Shih-Wei; Chen, Kuo-Hsin; Miura, Fumihiko; Watanabe, Manabu; Abe, Yuta; Misawa, Takeyuki; Nagakawa, Yuichi; Yoon, Dong-Sup; Jang, Jin-Young; Yu, Hee Chul; Ahn, Keun Soo; Kim, Song Cheol; Song, In Sang; Kim, Ji Hoon; Yun, Sung Su; Choi, Seong Ho; Jan, Yi-Yin; Sheen-Chen, Shyr-Ming; Shan, Yan-Shen; Ker, Chen-Guo; Chan, De-Chuan; Wu, Cheng-Chung; Toyota, Naoyuki; Higuchi, Ryota; Nakamura, Yoshiharu; Mizuguchi, Yoshiaki; Takeda, Yutaka; Ito, Masahiro; Norimizu, Shinji; Yamada, Shigetoshi; Matsumura, Naoki; Shindoh, Junichi; Sunagawa, Hiroki; Gocho, Takeshi; Hasegawa, Hiroshi; Rikiyama, Toshiki; Sata, Naohiro; Kano, Nobuyasu; Kitano, Seigo; Tokumura, Hiromi; Yamashita, Yuichi; Watanabe, Goro; Nakagawa, Kunitoshi; Kimura, Taizo; Yamakawa, Tatsuo; Wakabayashi, Go; Endo, Itaru; Miyazaki, Masaru; Yamamoto, Masakazu

2017-01-01

Generally, surgeons' perceptions of surgical safety are based on experience and institutional policy. Our recent pilot survey demonstrated that the acceptable duration of surgery and criteria for open conversion during laparoscopic cholecystectomy (LC) vary among workplaces. A web-based survey was distributed to 554 expert LC surgeons in Japan, Korea, and Taiwan. The questionnaire covered LC experience, safety measures and recognition of landmarks, decision-making regarding conversion to open/partial cholecystectomy and the implications of this decision. Overall responses were compared among nations, and then stratified by LC experience level (lifetime cases 200-499, 500-999, and ≥1,000). The response rate was 92.6% (513/554); 67 surgeons with ≤199 LCs were excluded, and responses from 446 surgeons were analyzed. We observed significant differences among nations on almost all questions. Differences that remained after stratification by LC experience were on questions related to acceptable duration of surgery, adoption rates of intraoperative cholangiography, the "critical view of safety" technique, identification of Rouvière's sulcus, recognition of the SS-Inner layer theory, and intraoperative judgment to abandon conventional LC. Even among experts, surgeons' perceptions during LC are workplace-dependent. A novel grading system of surgical difficulty and standardized LC procedures are paramount to generate high-level evidence. © 2016 Japanese Society of Hepato-Biliary-Pancreatic Surgery.

Development of an Expert Judgement Elicitation and Calibration Methodology for Risk Analysis in Conceptual Vehicle Design

NASA Technical Reports Server (NTRS)

Unal, Resit; Keating, Charles; Conway, Bruce; Chytka, Trina

2004-01-01

A comprehensive expert-judgment elicitation methodology to quantify input parameter uncertainty and analysis tool uncertainty in a conceptual launch vehicle design analysis has been developed. The ten-phase methodology seeks to obtain expert judgment opinion for quantifying uncertainties as a probability distribution so that multidisciplinary risk analysis studies can be performed. The calibration and aggregation techniques presented as part of the methodology are aimed at improving individual expert estimates, and provide an approach to aggregate multiple expert judgments into a single probability distribution. The purpose of this report is to document the methodology development and its validation through application to a reference aerospace vehicle. A detailed summary of the application exercise, including calibration and aggregation results is presented. A discussion of possible future steps in this research area is given.

Quality versus Quantity Debate in Swimming: Perceptions and Training Practices of Expert Swimming Coaches.

PubMed

Nugent, Frank J; Comyns, Thomas M; Warrington, Giles D

2017-06-01

The debate over low-volume, high-intensity training versus high-volume, low-intensity training, commonly known as Quality versus Quantity, respectively, is a frequent topic of discussion among swimming coaches and academics. The aim of this study was to explore expert coaches' perceptions of quality and quantity coaching philosophies in competitive swimming and to investigate their current training practices. A purposeful sample of 11 expert swimming coaches was recruited for this study. The study was a mixed methods design and involved each coach participating in 1 semi-structured interview and completing 1 closed-ended questionnaire. The main findings of this study were that coaches felt quality training programmes would lead to short term results for youth swimmers, but were in many cases more appropriate for senior swimmers. The coaches suggested that quantity training programmes built an aerobic base for youth swimmers, promoted technical development through a focus on slower swimming and helped to enhance recovery from training or competition. However, the coaches continuously suggested that quantity training programmes must be performed with good technique and they felt this was a misunderstood element. This study was a critical step towards gaining a richer and broader understanding on the debate over Quality versus Quantity training from an expert swimming coaches' perspective which was not currently available in the research literature.

Development of an Expert System as a Diagnostic Support of Cervical Cancer in Atypical Glandular Cells, Based on Fuzzy Logics and Image Interpretation

PubMed Central

Domínguez Hernández, Karem R.; Aguilar Lasserre, Alberto A.; Posada Gómez, Rubén; Palet Guzmán, José A.; González Sánchez, Blanca E.

2013-01-01

Cervical cancer is the second largest cause of death among women worldwide. Nowadays, this disease is preventable and curable at low cost and low risk when an accurate diagnosis is done in due time, since it is the neoplasm with the highest prevention potential. This work describes the development of an expert system able to provide a diagnosis to cervical neoplasia (CN) precursor injuries through the integration of fuzzy logics and image interpretation techniques. The key contribution of this research focuses on atypical cases, specifically on atypical glandular cells (AGC). The expert system consists of 3 phases: (1) risk diagnosis which consists of the interpretation of a patient's clinical background and the risks for contracting CN according to specialists; (2) cytology images detection which consists of image interpretation (IM) and the Bethesda system for cytology interpretation, and (3) determination of cancer precursor injuries which consists of in retrieving the information from the prior phases and integrating the expert system by means of a fuzzy logics (FL) model. During the validation stage of the system, 21 already diagnosed cases were tested with a positive correlation in which 100% effectiveness was obtained. The main contribution of this work relies on the reduction of false positives and false negatives by providing a more accurate diagnosis for CN. PMID:23690881

An expert system to perform on-line controller restructuring for abrupt model changes

NASA Technical Reports Server (NTRS)

Litt, Jonathan S.

1990-01-01

Work in progress on an expert system used to reconfigure and tune airframe/engine control systems on-line in real time in response to battle damage or structural failures is presented. The closed loop system is monitored constantly for changes in structure and performance, the detection of which prompts the expert system to choose and apply a particular control restructuring algorithm based on the type and severity of the damage. Each algorithm is designed to handle specific types of failures and each is applicable only in certain situations. The expert system uses information about the system model to identify the failure and to select the technique best suited to compensate for it. A depth-first search is used to find a solution. Once a new controller is designed and implemented it must be tuned to recover the original closed-loop handling qualities and responsiveness from the degraded system. Ideally, the pilot should not be able to tell the difference between the original and redesigned systems. The key is that the system must have inherent redundancy so that degraded or missing capabilities can be restored by creative use of alternate functionalities. With enough redundancy in the control system, minor battle damage affecting individual control surfaces or actuators, compressor efficiency, etc., can be compensated for such that the closed-loop performance in not noticeably altered. The work is applied to a Black Hawk/T700 system.

Quality versus Quantity Debate in Swimming: Perceptions and Training Practices of Expert Swimming Coaches

PubMed Central

Nugent, Frank J; Comyns, Thomas M; Warrington, Giles D

2017-01-01

Abstract The debate over low-volume, high-intensity training versus high-volume, low-intensity training, commonly known as Quality versus Quantity, respectively, is a frequent topic of discussion among swimming coaches and academics. The aim of this study was to explore expert coaches’ perceptions of quality and quantity coaching philosophies in competitive swimming and to investigate their current training practices. A purposeful sample of 11 expert swimming coaches was recruited for this study. The study was a mixed methods design and involved each coach participating in 1 semi-structured interview and completing 1 closed-ended questionnaire. The main findings of this study were that coaches felt quality training programmes would lead to short term results for youth swimmers, but were in many cases more appropriate for senior swimmers. The coaches suggested that quantity training programmes built an aerobic base for youth swimmers, promoted technical development through a focus on slower swimming and helped to enhance recovery from training or competition. However, the coaches continuously suggested that quantity training programmes must be performed with good technique and they felt this was a misunderstood element. This study was a critical step towards gaining a richer and broader understanding on the debate over Quality versus Quantity training from an expert swimming coaches’ perspective which was not currently available in the research literature. PMID:28713467

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…

Remote Sensing Applications with High Reliability in Changjiang Water Resource Management

NASA Astrophysics Data System (ADS)

Ma, L.; Gao, S.; Yang, A.

2018-04-01

Remote sensing technology has been widely used in many fields. But most of the applications cannot get the information with high reliability and high accuracy in large scale, especially for the applications using automatic interpretation methods. We have designed an application-oriented technology system (PIR) composed of a series of accurate interpretation techniques,which can get over 85 % correctness in Water Resource Management from the view of photogrammetry and expert knowledge. The techniques compose of the spatial positioning techniques from the view of photogrammetry, the feature interpretation techniques from the view of expert knowledge, and the rationality analysis techniques from the view of data mining. Each interpreted polygon is accurate enough to be applied to the accuracy sensitive projects, such as the Three Gorge Project and the South - to - North Water Diversion Project. In this paper, we present several remote sensing applications with high reliability in Changjiang Water Resource Management,including water pollution investigation, illegal construction inspection, and water conservation monitoring, etc.

Vocal Qualities in Music Theater Voice: Perceptions of Expert Pedagogues.

PubMed

Bourne, Tracy; Kenny, Dianna

2016-01-01

To gather qualitative descriptions of music theater vocal qualities including belt, legit, and mix from expert pedagogues to better define this voice type. This is a prospective, semistructured interview. Twelve expert teachers from United States, United Kingdom, Asia, and Australia were interviewed by Skype and asked to identify characteristics of music theater vocal qualities including vocal production, physiology, esthetics, pitch range, and pedagogical techniques. Responses were compared with published studies on music theater voice. Belt and legit were generally described as distinct sounds with differing physiological and technical requirements. Teachers were concerned that belt should be taught "safely" to minimize vocal health risks. There was consensus between teachers and published research on the physiology of the glottis and vocal tract; however, teachers were not in agreement about breathing techniques. Neither were teachers in agreement about the meaning of "mix." Most participants described belt as heavily weighted, thick folds, thyroarytenoid-dominant, or chest register; however, there was no consensus on an appropriate term. Belt substyles were named and generally categorized by weightedness or tone color. Descriptions of male belt were less clear than for female belt. This survey provides an overview of expert pedagogical perspectives on the characteristics of belt, legit, and mix qualities in the music theater voice. Although teacher responses are generally in agreement with published research, there are still many controversial issues and gaps in knowledge and understanding of this vocal technique. Breathing techniques, vocal range, mix, male belt, and vocal registers require continuing investigation so that we can learn more about efficient and healthy vocal function in music theater singing. Copyright © 2016 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Development and pilot testing of an informed consent video for patients with limb trauma prior to debridement surgery using a modified Delphi technique.

PubMed

Lin, Yen-Ko; Chen, Chao-Wen; Lee, Wei-Che; Lin, Tsung-Ying; Kuo, Liang-Chi; Lin, Chia-Ju; Shi, Leiyu; Tien, Yin-Chun; Cheng, Yuan-Chia

2017-11-29

Ensuring adequate informed consent for surgery in a trauma setting is challenging. We developed and pilot tested an educational video containing information regarding the informed consent process for surgery in trauma patients and a knowledge measure instrument and evaluated whether the audiovisual presentation improved the patients' knowledge regarding their procedure and aftercare and their satisfaction with the informed consent process. A modified Delphi technique in which a panel of experts participated in successive rounds of shared scoring of items to forecast outcomes was applied to reach a consensus among the experts. The resulting consensus was used to develop the video content and questions for measuring the understanding of the informed consent for debridement surgery in limb trauma patients. The expert panel included experienced patients. The participants in this pilot study were enrolled as a convenience sample of adult trauma patients scheduled to receive surgery. The modified Delphi technique comprised three rounds over a 4-month period. The items given higher scores by the experts in several categories were chosen for the subsequent rounds until consensus was reached. The experts reached a consensus on each item after the three-round process. The final knowledge measure comprising 10 questions was developed and validated. Thirty eligible trauma patients presenting to the Emergency Department (ED) were approached and completed the questionnaires in this pilot study. The participants exhibited significantly higher mean knowledge and satisfaction scores after watching the educational video than before watching the video. Our process is promising for developing procedure-specific informed consent and audiovisual aids in medical and surgical specialties. The educational video was developed using a scientific method that integrated the opinions of different stakeholders, particularly patients. This video is a useful tool for improving the knowledge and satisfaction of trauma patients in the ED. The modified Delphi technique is an effective method for collecting experts' opinions and reaching a consensus on the content of educational materials for informed consent. Institutions should prioritize patient-centered health care and develop a structured informed consent process to improve the quality of care. The ClinicalTrials.gov Identifier is NCT01338480 . The date of registration was April 18, 2011 (retrospectively registered).

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.

Optimisation of nano-silica modified self-compacting high-Volume fly ash mortar

NASA Astrophysics Data System (ADS)

Achara, Bitrus Emmanuel; Mohammed, Bashar S.; Fadhil Nuruddin, Muhd

2017-05-01

Evaluation of the effects of nano-silica amount and superplasticizer (SP) dosage on the compressive strength, porosity and slump flow on high-volume fly ash self-consolidating mortar was investigated. Multiobjective optimisation technique using Design-Expert software was applied to obtain solution based on desirability function that simultaneously optimises the variables and the responses. A desirability function of 0.811 gives the optimised solution. The experimental and predicted results showed minimal errors in all the measured responses.

LERC power system autonomy program 1990 demonstration

NASA Technical Reports Server (NTRS)

Faymon, Karl A.; Sundberg, Gale R.; Bercaw, Robert R.; Weeks, David J.

1987-01-01

The NASA Lewis Research Center has undertaken a program for the development of space systems automation, with a view to increased reliability, safety, payload capability, and decreased operational costs. The NASA Space Station is a primary area of application for the techniques thus developed. Attention is presently given to the activities associated with the Power Systems Autonomy Demonstration Project, which has a projected demonstration date in 1990 and will integrate knowledge-based systems into a real-time environment. Two coordinated systems under expert system control will be demonstrated.

Comprehensive embryo testing. Experts' opinions regarding future directions: an expert panel study on comprehensive embryo testing.

PubMed

Hens, Kristien; Dondorp, Wybo J; Geraedts, Joep P M; de Wert, Guido M

2013-05-01

What do scientists in the field of preimplantation genetic diagnosis (PGD) and preimplantation genetic screening (PGS) consider to be the future direction of comprehensive embryo testing? Although there are many biological and technical limitations, as well as uncertainties regarding the meaning of genetic variation, comprehensive embryo testing will impact the IVF/PGD practice and a timely ethical reflection is needed. Comprehensive testing using microarrays is currently being introduced in the context of PGD and PGS, and it is to be expected that whole-genome sequencing will also follow. Current ethical and empirical sociological research on embryo testing focuses on PGD as it is practiced now. However, empirical research and systematic reflection regarding the impact of comprehensive techniques for embryo testing is missing. In order to understand the potential of this technology and to be able to adequately foresee its implications, we held an expert panel with seven pioneers in PGD. We conducted an expert panel in October 2011 with seven PGD pioneers from Belgium, The Netherlands, Germany and the UK. Participants expected the use of comprehensive techniques in the context of PGD. However, the introduction of these techniques in embryo testing requires timely ethical reflection as it involves a shift from choosing an embryo without a particular genetic disease (i.e. PGD) or most likely to result in a successful pregnancy (i.e. PGS) to choosing the best embryo based on a much wider set of criteria. Such ethical reflection should take account of current technical and biological limitations and also of current uncertainties with regard to the meaning of genetic variance. However, ethicists should also not be afraid to look into the future. There was a general agreement that embryo testing will be increasingly preceded by comprehensive preconception screening, thus enabling smart combinations of genetic testing. The group was composed of seven participants from four Western Europe countries. As willingness to participate in this study may be connected with expectations regarding the pace and direction of future developments, selection bias cannot be excluded. The introduction of comprehensive screening techniques in embryo testing calls for further ethical reflection that is grounded in empirical work. Specifically, there is a need for studies querying the opinions of infertile couples undergoing IVF/PGS regarding the desirability of embryo screening beyond aneuploidy. This research was supported by the CSG, Centre for Society and Life Sciences (project number: 70.1.074). The authors declare no conflict of interest. N/A.

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.

From Theory-Inspired to Theory-Based Interventions: A Protocol for Developing and Testing a Methodology for Linking Behaviour Change Techniques to Theoretical Mechanisms of Action.

PubMed

Michie, Susan; Carey, Rachel N; Johnston, Marie; Rothman, Alexander J; de Bruin, Marijn; Kelly, Michael P; Connell, Lauren E

2018-05-18

Understanding links between behaviour change techniques (BCTs) and mechanisms of action (the processes through which they affect behaviour) helps inform the systematic development of behaviour change interventions. This research aims to develop and test a methodology for linking BCTs to their mechanisms of action. Study 1 (published explicit links): Hypothesised links between 93 BCTs (from the 93-item BCT taxonomy, BCTTv1) and mechanisms of action will be identified from published interventions and their frequency, explicitness and precision documented. Study 2 (expert-agreed explicit links): Behaviour change experts will identify links between 61 BCTs and 26 mechanisms of action in a formal consensus study. Study 3 (integrated matrix of explicit links): Agreement between studies 1 and 2 will be evaluated and a new group of experts will discuss discrepancies. An integrated matrix of BCT-mechanism of action links, annotated to indicate strength of evidence, will be generated. Study 4 (published implicit links): To determine whether groups of co-occurring BCTs can be linked to theories, we will identify groups of BCTs that are used together from the study 1 literature. A consensus exercise will be used to rate strength of links between groups of BCT and theories. A formal methodology for linking BCTs to their hypothesised mechanisms of action can contribute to the development and evaluation of behaviour change interventions. This research is a step towards developing a behaviour change 'ontology', specifying relations between BCTs, mechanisms of action, modes of delivery, populations, settings and types of behaviour.

A temporal bone surgery simulator with real-time feedback for surgical training.

PubMed

Wijewickrema, Sudanthi; Ioannou, Ioanna; Zhou, Yun; Piromchai, Patorn; Bailey, James; Kennedy, Gregor; O'Leary, Stephen

2014-01-01

Timely feedback on surgical technique is an important aspect of surgical skill training in any learning environment, be it virtual or otherwise. Feedback on technique should be provided in real-time to allow trainees to recognize and amend their errors as they occur. Expert surgeons have typically carried out this task, but they have limited time available to spend with trainees. Virtual reality surgical simulators offer effective, repeatable training at relatively low cost, but their benefits may not be fully realized while they still require the presence of experts to provide feedback. We attempt to overcome this limitation by introducing a real-time feedback system for surgical technique within a temporal bone surgical simulator. Our evaluation study shows that this feedback system performs exceptionally well with respect to accuracy and effectiveness.

Techniques for Developing Child Dummy Protection Reference Values. Event Report

DOT National Transportation Integrated Search

1996-10-01

The purpose of this report is to present background information and techniques : for developing protection reference values (PRV) to use with child dummies in : out-of-position (OOP) child/air bag interaction testing. Biomechanics experts : agree tha...

Where to search top-K biomedical ontologies?

PubMed

Oliveira, Daniela; Butt, Anila Sahar; Haller, Armin; Rebholz-Schuhmann, Dietrich; Sahay, Ratnesh

2018-03-20

Searching for precise terms and terminological definitions in the biomedical data space is problematic, as researchers find overlapping, closely related and even equivalent concepts in a single or multiple ontologies. Search engines that retrieve ontological resources often suggest an extensive list of search results for a given input term, which leads to the tedious task of selecting the best-fit ontological resource (class or property) for the input term and reduces user confidence in the retrieval engines. A systematic evaluation of these search engines is necessary to understand their strengths and weaknesses in different search requirements. We have implemented seven comparable Information Retrieval ranking algorithms to search through ontologies and compared them against four search engines for ontologies. Free-text queries have been performed, the outcomes have been judged by experts and the ranking algorithms and search engines have been evaluated against the expert-based ground truth (GT). In addition, we propose a probabilistic GT that is developed automatically to provide deeper insights and confidence to the expert-based GT as well as evaluating a broader range of search queries. The main outcome of this work is the identification of key search factors for biomedical ontologies together with search requirements and a set of recommendations that will help biomedical experts and ontology engineers to select the best-suited retrieval mechanism in their search scenarios. We expect that this evaluation will allow researchers and practitioners to apply the current search techniques more reliably and that it will help them to select the right solution for their daily work. The source code (of seven ranking algorithms), ground truths and experimental results are available at https://github.com/danielapoliveira/bioont-search-benchmark.

Standard operating procedures in the disorders of orgasm and ejaculation.

PubMed

McMahon, Chris G; Jannini, Emmanuele; Waldinger, Marcel; Rowland, David

2013-01-01

Ejaculatory/orgasmic disorders are common male sexual dysfunctions and include premature ejaculation (PE), inhibited ejaculation, anejaculation, retrograde ejaculation, and anorgasmia. To provide recommendations and guidelines of the current state-of-the-art knowledge for management of ejaculation/orgasmic disorders in men as standard operating procedures (SOPs) for the treating health care professional. The International Society of Sexual Medicine Standards Committee assembled over 30 multidisciplinary experts to establish SOPs for various male and female sexual medicine topics. The SOP for the management of disorders of orgasm and ejaculation represents the opinion of four experts from four countries developed in a process over a 2-year period. Expert opinion was based on grading of evidence-based medical literature, limited expert opinion, widespread internal committee discussion, public presentation, and debate. PE management is largely dependent upon etiology. Lifelong PE is best managed with PE pharmacotherapy (selective serotonin reuptake inhibitors and/or topical anesthetics). The management of acquired PE is etiology specific and may include erectile dysfunction (ED) pharmacotherapy in men with comorbid ED. All men seeking treatment for PE should receive basic psychosexual education. Graded behavioral therapy is indicated when psychogenic or relationship factors are present and is often best combined with PE pharmacotherapy in an integrated treatment program. Delayed ejaculation, anejaculation, and/or anorgasmia may have a biogenic and/or psychogenic etiology. Men with age-related penile hypoanesthesia should be educated, reassured, and instructed in revised sexual techniques which maximize arousal. Retrograde ejaculation is managed by education, patient reassurance, and pharmacotherapy. Additional research is required to further the understanding of the disorders of ejaculation and orgasm. © 2012 International Society for Sexual Medicine.

[A functional analysis of healthcare auditors' skills in Venezuela, 2008].

PubMed

Chirinos-Muñoz, Mónica S

2010-10-01

Using functional analysis for identifying the basic, working, specific and generic skills and values which a health service auditor must have. Implementing the functional analysis technique with 10 experts, identifying specific, basic, generic skills and values by means of deductive logic. A functional map was obtained which started by establishing a key purpose based on improving healthcare and service quality from which three key functions emerged. The main functions and skills' units were then broken down into the competitive elements defining what a health service auditor is able to do. This functional map (following functional analysis methodology) shows in detail the simple and complex tasks which a healthcare auditor should apply in the workplace, adopting a forward management approach for improving healthcare and health service quality. This methodology, expressing logical-deductive awareness raising, provides expert consensual information validating each element regarding overall skills.

Evaluating Alignment of Shapes by Ensemble Visualization

PubMed Central

Raj, Mukund; Mirzargar, Mahsa; Preston, J. Samuel; Kirby, Robert M.; Whitaker, Ross T.

2016-01-01

The visualization of variability in surfaces embedded in 3D, which is a type of ensemble uncertainty visualization, provides a means of understanding the underlying distribution of a collection or ensemble of surfaces. Although ensemble visualization for isosurfaces has been described in the literature, we conduct an expert-based evaluation of various ensemble visualization techniques in a particular medical imaging application: the construction of atlases or templates from a population of images. In this work, we extend contour boxplot to 3D, allowing us to evaluate it against an enumeration-style visualization of the ensemble members and other conventional visualizations used by atlas builders, namely examining the atlas image and the corresponding images/data provided as part of the construction process. We present feedback from domain experts on the efficacy of contour boxplot compared to other modalities when used as part of the atlas construction and analysis stages of their work. PMID:26186768

Staging scientific controversies: a gallery test on science museums' interactivity.

PubMed

Yaneva, Albena; Rabesandratana, Tania Mara; Greiner, Birgit

2009-01-01

The "transfer" model in science communication has been addressed critically from different perspectives, while the advantages of the interactive model have been continuously praised. Yet, little is done to account for the specific role of the interactive model in communicating "unfinished science." The traditional interactive methods in museums are not sufficient to keep pace with rapid scientific developments. Interactive exchanges between laypeople and experts are thought mainly through the lens of a dialogue that is facilitated and framed by the traditional "conference room" architecture. Drawing on the results of a small-scale experiment in a gallery space, we argue for the need for a new "architecture of interaction" in museum settings based on art installation and simulation techniques, which will enhance the communication potentials of science museums and will provide conditions for a fruitful even-handed exchange of expert and lay knowledge.

Intelligent guidance and control for wind shear encounter

NASA Technical Reports Server (NTRS)

Stengel, Robert F.

1988-01-01

The principal objective is to develop methods for assessing the likelihood of wind shear encounter, for deciding what flight path to pursue, and for using the aircraft's full potential for combating wind shear. This study requires the definition of both deterministic and statistical techniques for fusing internal and external information, for making go/no-go decisions, and for generating commands to the aircraft's cockpit displays and autopilot for both manually controlled and automatic flight. The program has begun with the development of a real-time expert system for pilot aiding that is based on the results of the FAA Windshear Training Aids Program. A two-volume manual that presents an overview, pilot guide, training program, and substantiating data provides guidelines for this initial development. The Expert System to Avoid Wind Shear (ESAWS) currently contains over 140 rules and is coded in the LISP programming language for implementation on a Symbolics 3670 LISP machine.

The role of complex emotions in inconsistent diagnoses of schizophrenia.

PubMed

Gara, Michael A; Vega, William A; Lesser, Ira; Escamilla, Michael; Lawson, William B; Wilson, Daniel R; Fleck, David E; Strakowski, Stephen M

2010-09-01

In the case of large-scale epidemiological studies, there is evidence of substantial disagreement when lay diagnoses of schizophrenia based on structured interviews are compared with expert diagnoses of the same patients. Reasons for this level of disagreement are investigated in the current study, which made use of advances in text-mining techniques and associated structural representations of language expressions. Specifically, the current study examined whether content analyses of transcribed diagnostic interviews obtained from 150 persons with serious psychiatric disorders yielded any discernable patterns that correlated with diagnostic inconsistencies of schizophrenia. In summary, it was found that the patterning or structure of spontaneous self-reports of emotion states in the diagnostic interview was associated with diagnostic inconsistencies of schizophrenia, irrespective of confounders; i.e., age of patient, gender, or ethnicity. In particular, complex emotion patterns were associated with greater disagreement between experts and trained lay interviewers than were simpler patterns.

Expert system development for commonality analysis in space programs

NASA Technical Reports Server (NTRS)

Yeager, Dorian P.

1987-01-01

This report is a combination of foundational mathematics and software design. A mathematical model of the Commonality Analysis problem was developed and some important properties discovered. The complexity of the problem is described herein and techniques, both deterministic and heuristic, for reducing that complexity are presented. Weaknesses are pointed out in the existing software (System Commonality Analysis Tool) and several improvements are recommended. It is recommended that: (1) an expert system for guiding the design of new databases be developed; (2) a distributed knowledge base be created and maintained for the purpose of encoding the commonality relationships between design items in commonality databases; (3) a software module be produced which automatically generates commonality alternative sets from commonality databases using the knowledge associated with those databases; and (4) a more complete commonality analysis module be written which is capable of generating any type of feasible solution.

Opponent Classification in Poker

NASA Astrophysics Data System (ADS)

Ahmad, Muhammad Aurangzeb; Elidrisi, Mohamed

Modeling games has a long history in the Artificial Intelligence community. Most of the games that have been considered solved in AI are perfect information games. Imperfect information games like Poker and Bridge represent a domain where there is a great deal of uncertainty involved and additional challenges with respect to modeling the behavior of the opponent etc. Techniques developed for playing imperfect games also have many real world applications like repeated online auctions, human computer interaction, opponent modeling for military applications etc. In this paper we explore different techniques for playing poker, the core of these techniques is opponent modeling via classifying the behavior of opponent according to classes provided by domain experts. We utilize windows of full observation in the game to classify the opponent. In Poker, the behavior of an opponent is classified into four standard poker-playing styles based on a subjective function.

Uncovering Clinical Principles and Techniques to Address Minority Stress, Mental Health, and Related Health Risks Among Gay and Bisexual Men

PubMed Central

Pachankis, John E.

2014-01-01

Gay and bisexual men disproportionately experience depression, anxiety, and related health risks at least partially because of their exposure to sexual minority stress. This paper describes the adaptation of an evidence-based intervention capable of targeting the psychosocial pathways through which minority stress operates. Interviews with key stakeholders, including gay and bisexual men with depression and anxiety and expert providers, suggested intervention principles and techniques for improving minority stress coping. These principles and techniques are consistent with general cognitive behavioral therapy approaches, the empirical tenets of minority stress theory, and professional guidelines for LGB-affirmative mental health practice. If found to be efficacious, the psychosocial intervention described here would be one of the first to improve the mental health of gay and bisexual men by targeting minority stress. PMID:25554721

The management of abdominal wall hernias – in search of consensus

PubMed Central

Bury, Kamil; Śmietański, Maciej

2015-01-01

Introduction Laparoscopic repair is becoming an increasingly popular alternative in the treatment of abdominal wall hernias. In spite of numerous studies evaluating this technique, indications for laparoscopic surgery have not been established. Similarly, implant selection and fixation techniques have not been unified and are the subject of scientific discussion. Aim To assess whether there is a consensus on the management of the most common ventral abdominal wall hernias among recognised experts. Material and methods Fourteen specialists representing the boards of European surgical societies were surveyed to determine their choice of surgical technique for nine typical primary ventral and incisional hernias. The access method, type of operation, mesh prosthesis and fixation method were evaluated. In addition to the laparoscopic procedures, the number of tackers and their arrangement were assessed. Results In none of the cases presented was a consensus of experts obtained. Laparoscopic and open techniques were used equally often. Especially in the group of large hernias, decisions on repair methods were characterised by high variability. The technique of laparoscopic mesh fixation was a subject of great variability in terms of both method selection and the numbers of tackers and sutures used. Conclusions Recognised experts have not reached a consensus on the management of abdominal wall hernias. Our survey results indicate the need for further research and the inclusion of large cohorts of patients in the dedicated registries to evaluate the results of different surgical methods, which would help in the development of treatment algorithms for surgical education in the future. PMID:25960793

An expert knowledge-based approach to landslide susceptibility mapping using GIS and fuzzy logic

NASA Astrophysics Data System (ADS)

Zhu, A.-Xing; Wang, Rongxun; Qiao, Jianping; Qin, Cheng-Zhi; Chen, Yongbo; Liu, Jing; Du, Fei; Lin, Yang; Zhu, Tongxin

2014-06-01

This paper presents an expert knowledge-based approach to landslide susceptibility mapping in an effort to overcome the deficiencies of data-driven approaches. The proposed approach consists of three generic steps: (1) extraction of knowledge on the relationship between landslide susceptibility and predisposing factors from domain experts, (2) characterization of predisposing factors using GIS techniques, and (3) prediction of landslide susceptibility under fuzzy logic. The approach was tested in two study areas in China - the Kaixian study area (about 250 km2) and the Three Gorges study area (about 4600 km2). The Kaixian study area was used to develop the approach and to evaluate its validity. The Three Gorges study area was used to test both the portability and the applicability of the developed approach for mapping landslide susceptibility over large study areas. Performance was evaluated by examining if the mean of the computed susceptibility values at landslide sites was statistically different from that of the entire study area. A z-score test was used to examine the statistical significance of the difference. The computed z for the Kaixian area was 3.70 and the corresponding p-value was less than 0.001. This suggests that the computed landslide susceptibility values are good indicators of landslide occurrences. In the Three Gorges study area, the computed z was 10.75 and the corresponding p-value was less than 0.001. In addition, we divided the susceptibility value into four levels: low (0.0-0.25), moderate (0.25-0.5), high (0.5-0.75) and very high (0.75-1.0). No landslides were found for areas of low susceptibility. Landslide density was about three times higher in areas of very high susceptibility than that in the moderate susceptibility areas, and more than twice as high as that in the high susceptibility areas. The results from the Three Gorge study area suggest that the extracted expert knowledge can be extrapolated to another study area and the developed approach can be used in large-scale projects. Results from these case studies suggest that the expert knowledge-based approach is effective in mapping landslide susceptibility and that its performance is maintained when it is moved to a new area from the model development area without changes to the knowledge base.

Improving Behavioral Support for Smoking Cessation in Pregnancy: What Are the Barriers to Stopping and Which Behavior Change Techniques Can Influence Them? Application of Theoretical Domains Framework

PubMed Central

Coleman-Haynes, Tom; Lorencatto, Fabiana; Ussher, Michael; Dyas, Jane; Coleman, Tim

2018-01-01

Behavioral support interventions are used to help pregnant smokers stop; however, of those tested, few are proven effective. Systematic research developing effective pregnancy-specific behavior change techniques (BCTs) is ongoing. This paper reports contributory work identifying potentially-effective BCTs relative to known important barriers and facilitators (B&Fs) to smoking cessation in pregnancy; to detect priority areas for BCTs development. A Nominal Group Technique with cessation experts (n = 12) elicited an expert consensus on B&Fs most influencing women’s smoking cessation and those most modifiable through behavioral support. Effective cessation interventions in randomized trials from a recent Cochrane review were coded into component BCTs using existing taxonomies. B&Fs were categorized using Theoretical Domains Framework (TDF) domains. Matrices, mapping BCT taxonomies against TDF domains, were consulted to investigate the extent to which BCTs in existing interventions target key B&Fs. Experts ranked ‘smoking a social norm’ and ‘quitting not a priority’ as most important barriers and ‘desire to protect baby’ an important facilitator to quitting. From 14 trials, 23 potentially-effective BCTs were identified (e.g., ‘information about consequences). Most B&Fs fell into ‘Social Influences’, ‘Knowledge’, ‘Emotions’ and ‘Intentions’ TDF domains; few potentially-effective BCTs mapped onto every TDF domain. B&Fs identified by experts as important to cessation, are not sufficiently targeted by BCT’s currently within interventions for smoking cessation in pregnancy. PMID:29462994

Artificial Intelligence in Sports Biomechanics: New Dawn or False Hope?

PubMed Central

Bartlett, Roger

2006-01-01

This article reviews developments in the use of Artificial Intelligence (AI) in sports biomechanics over the last decade. It outlines possible uses of Expert Systems as diagnostic tools for evaluating faults in sports movements (‘techniques’) and presents some example knowledge rules for such an expert system. It then compares the analysis of sports techniques, in which Expert Systems have found little place to date, with gait analysis, in which they are routinely used. Consideration is then given to the use of Artificial Neural Networks (ANNs) in sports biomechanics, focusing on Kohonen self-organizing maps, which have been the most widely used in technique analysis, and multi-layer networks, which have been far more widely used in biomechanics in general. Examples of the use of ANNs in sports biomechanics are presented for javelin and discus throwing, shot putting and football kicking. I also present an example of the use of Evolutionary Computation in movement optimization in the soccer throw in, which predicted an optimal technique close to that in the coaching literature. After briefly overviewing the use of AI in both sports science and biomechanics in general, the article concludes with some speculations about future uses of AI in sports biomechanics. Key Points Expert Systems remain almost unused in sports biomechanics, unlike in the similar discipline of gait analysis. Artificial Neural Networks, particularly Kohonen Maps, have been used, although their full value remains unclear. Other AI applications, including Evolutionary Computation, have received little attention. PMID:24357939

Improving Behavioral Support for Smoking Cessation in Pregnancy: What Are the Barriers to Stopping and Which Behavior Change Techniques Can Influence These? Application of Theoretical Domains Framework.

PubMed

Campbell, Katarzyna A; Fergie, Libby; Coleman-Haynes, Tom; Cooper, Sue; Lorencatto, Fabiana; Ussher, Michael; Dyas, Jane; Coleman, Tim

2018-02-17

Behavioral support interventions are used to help pregnant smokers stop; however, of those tested, few are proven effective. Systematic research developing effective pregnancy-specific behavior change techniques (BCTs) is ongoing. This paper reports contributory work identifying potentially-effective BCTs relative to known important barriers and facilitators (B&Fs) to smoking cessation in pregnancy; to detect priority areas for BCTs development. A Nominal Group Technique with cessation experts ( n = 12) elicited an expert consensus on B&Fs most influencing women's smoking cessation and those most modifiable through behavioral support. Effective cessation interventions in randomized trials from a recent Cochrane review were coded into component BCTs using existing taxonomies. B&Fs were categorized using Theoretical Domains Framework (TDF) domains. Matrices, mapping BCT taxonomies against TDF domains, were consulted to investigate the extent to which BCTs in existing interventions target key B&Fs. Experts ranked "smoking a social norm" and "quitting not a priority" as most important barriers and "desire to protect baby" an important facilitator to quitting. From 14 trials, 23 potentially-effective BCTs were identified (e.g., information about consequences). Most B&Fs fell into "Social Influences", "Knowledge", "Emotions" and "Intentions" TDF domains; few potentially-effective BCTs mapped onto every TDF domain. B&Fs identified by experts as important to cessation, are not sufficiently targeted by BCT's currently within interventions for smoking cessation in pregnancy.

Expert opinion on best practice guidelines and competency framework for visual screening in children.

PubMed

Lança, Carla

2013-09-01

Screening programs to detect visual abnormalities in children vary among countries. The aim of this study is to describe experts' perception of best practice guidelines and competency framework for visual screening in children. A qualitative focus group technique was applied during the Portuguese national orthoptic congress to obtain the perception of an expert panel of 5 orthoptists and 2 ophthalmologists with experience in visual screening for children (mean age 53.43 years, SD ± 9.40). The panel received in advance a script with the description of three tuning competencies dimensions (instrumental, systemic, and interpersonal) for visual screening. The session was recorded in video and audio. Qualitative data were analyzed using a categorical technique. According to experts' views, six tests (35.29%) have to be included in a visual screening: distance visual acuity test, cover test, bi-prism or 4/6(Δ) prism, fusion, ocular movements, and refraction. Screening should be performed according to the child age before and after 3 years of age (17.65%). The expert panel highlighted the influence of the professional experience in the application of a screening protocol (23.53%). They also showed concern about the false negatives control (23.53%). Instrumental competencies were the most cited (54.09%), followed by interpersonal (29.51%) and systemic (16.4%). Orthoptists should have professional experience before starting to apply a screening protocol. False negative results are a concern that has to be more thoroughly investigated. The proposed framework focuses on core competencies highlighted by the expert panel. Competencies programs could be important do develop better screening programs.

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.

Development of skills-based competencies for forensic nurse examiners providing elder abuse care

PubMed Central

Du Mont, Janice; Kosa, Daisy; Macdonald, Sheila; Elliot, Shannon; Yaffe, Mark

2016-01-01

Objective As a critical step in advancing a comprehensive response to elder abuse built on existing forensic nursing-led hospital-based programmes, we developed a list of skills-based competencies for use in an Elder Abuse Nurse Examiner curriculum. Participants and setting Programme leaders of 30 hospital-based forensic nursing-led sexual assault and domestic violence treatment centres. Primary and secondary outcome measures 149 verbatim recommendations for components of an elder abuse response were identified from a systematic scoping review. In 2 online Delphi consensus survey rounds, these components of care were evaluated by an expert panel for their overall importance to the elder abuse intervention under development and for their appropriateness to the scope of practice of an elder abuse nurse examiner. The components retained after evaluation were translated into skills-based competencies using Bloom's Taxonomy of Learning and, using the Nominal Group Technique, were subsequently reviewed and revised by a subset of members of the expert panel in a consensus meeting. Results Of the 148 recommendations evaluated, 119 were rated as important and achieved consensus or high level of agreement. Of these, 101 were determined to be within the scope of practice of an Elder Abuse Nurse Examiner and were translated into skills-based competencies. Following review and revision by meeting experts, 47 final competencies were organised by content into 5 metacompetencies: documentation, legal and legislative issues; interview with older adult, caregiver and other relevant contacts; assessment; medical and forensic examination; and case summary, discharge plan and follow-up care. Conclusions We determined the skills-based competencies of importance to training forensic nurse examiners to respond to elder abuse in the context of a hospital-based intervention. These findings may have implications for violence and abuse treatment programmes with a forensic nursing component that are considering the provision of a dedicated response to the abuse of older women and men. PMID:26864579

Formal verification of AI software

NASA Technical Reports Server (NTRS)

Rushby, John; Whitehurst, R. Alan

1989-01-01

The application of formal verification techniques to Artificial Intelligence (AI) software, particularly expert systems, is investigated. Constraint satisfaction and model inversion are identified as two formal specification paradigms for different classes of expert systems. A formal definition of consistency is developed, and the notion of approximate semantics is introduced. Examples are given of how these ideas can be applied in both declarative and imperative forms.

Investigating Cognitive Task Difficulties and Expert Skills in E-Learning Storyboards Using a Cognitive Task Analysis Technique

ERIC Educational Resources Information Center

Yusoff, Nor'ain Mohd; Salim, Siti Salwah

2012-01-01

E-learning storyboards have been a useful approach in distance learning development to support interaction between instructional designers and subject-matter experts. Current works show that researchers are focusing on different approaches for use in storyboards, and there is less emphasis on the effect of design and process difficulties faced by…

Report of the Workshop on Magnetic Information Technology - MINT (Washington, D.C., June 22-24, 1983).

ERIC Educational Resources Information Center

Bortz, Alfred B.; Dunkle, Susan B.

Magnetic Information Technology (MINT), which involves use of magnetic techniques and materials to store information, is a critical growth industry in the United States. However, experts from both industry and academe forecast the inability of the United States to meet demand in this area. According to these experts, growth of magnetic information…

An Embedded Rule-Based Diagnostic Expert System in Ada

NASA Technical Reports Server (NTRS)

Jones, Robert E.; Liberman, Eugene M.

1992-01-01

Ada is becoming an increasingly popular programming language for large Government-funded software projects. Ada with it portability, transportability, and maintainability lends itself well to today's complex programming environment. In addition, expert systems have also assumed a growing role in providing human-like reasoning capability expertise for computer systems. The integration is discussed of expert system technology with Ada programming language, especially a rule-based expert system using an ART-Ada (Automated Reasoning Tool for Ada) system shell. NASA Lewis was chosen as a beta test site for ART-Ada. The test was conducted by implementing the existing Autonomous Power EXpert System (APEX), a Lisp-based power expert system, in ART-Ada. Three components, the rule-based expert systems, a graphics user interface, and communications software make up SMART-Ada (Systems fault Management with ART-Ada). The rules were written in the ART-Ada development environment and converted to Ada source code. The graphics interface was developed with the Transportable Application Environment (TAE) Plus, which generates Ada source code to control graphics images. SMART-Ada communicates with a remote host to obtain either simulated or real data. The Ada source code generated with ART-Ada, TAE Plus, and communications code was incorporated into an Ada expert system that reads the data from a power distribution test bed, applies the rule to determine a fault, if one exists, and graphically displays it on the screen. The main objective, to conduct a beta test on the ART-Ada rule-based expert system shell, was achieved. The system is operational. New Ada tools will assist in future successful projects. ART-Ada is one such tool and is a viable alternative to the straight Ada code when an application requires a rule-based or knowledge-based approach.

Developing Statistical Physics Course Handout on Distribution Function Materials Based on Science, Technology, Engineering, and Mathematics

NASA Astrophysics Data System (ADS)

Riandry, M. A.; Ismet, I.; Akhsan, H.

2017-09-01

This study aims to produce a valid and practical statistical physics course handout on distribution function materials based on STEM. Rowntree development model is used to produce this handout. The model consists of three stages: planning, development and evaluation stages. In this study, the evaluation stage used Tessmer formative evaluation. It consists of 5 stages: self-evaluation, expert review, one-to-one evaluation, small group evaluation and field test stages. However, the handout is limited to be tested on validity and practicality aspects, so the field test stage is not implemented. The data collection technique used walkthroughs and questionnaires. Subjects of this study are students of 6th and 8th semester of academic year 2016/2017 Physics Education Study Program of Sriwijaya University. The average result of expert review is 87.31% (very valid category). One-to-one evaluation obtained the average result is 89.42%. The result of small group evaluation is 85.92%. From one-to-one and small group evaluation stages, averagestudent response to this handout is 87,67% (very practical category). Based on the results of the study, it can be concluded that the handout is valid and practical.

Fuzzy Based Decision Support System for Condition Assessment and Rating of Bridges

NASA Astrophysics Data System (ADS)

Srinivas, Voggu; Sasmal, Saptarshi; Karusala, Ramanjaneyulu

2016-09-01

In this work, a knowledge based decision support system has been developed to efficiently handle the issues such as distress diagnosis, assessment of damages and condition rating of existing bridges towards developing an exclusive and robust Bridge Management System (BMS) for sustainable bridges. The Knowledge Based Expert System (KBES) diagnoses the distresses and finds the cause of distress in the bridge by processing the data which are heuristic and combined with site inspection results, laboratory test results etc. The coupling of symbolic and numeric type of data has been successfully implemented in the expert system to strengthen its decision making process. Finally, the condition rating of the bridge is carried out using the assessment results obtained from the KBES and the information received from the bridge inspector. A systematic procedure has been developed using fuzzy mathematics for condition rating of bridges by combining the fuzzy weighted average and resolution identity technique. The proposed methodologies and the decision support system will facilitate in developing a robust and exclusive BMS for a network of bridges across the country and allow the bridge engineers and decision makers to carry out maintenance of bridges in a rational and systematic way.

Computer-Vision-Assisted Palm Rehabilitation With Supervised Learning.

PubMed

Vamsikrishna, K M; Dogra, Debi Prosad; Desarkar, Maunendra Sankar

2016-05-01

Physical rehabilitation supported by the computer-assisted-interface is gaining popularity among health-care fraternity. In this paper, we have proposed a computer-vision-assisted contactless methodology to facilitate palm and finger rehabilitation. Leap motion controller has been interfaced with a computing device to record parameters describing 3-D movements of the palm of a user undergoing rehabilitation. We have proposed an interface using Unity3D development platform. Our interface is capable of analyzing intermediate steps of rehabilitation without the help of an expert, and it can provide online feedback to the user. Isolated gestures are classified using linear discriminant analysis (DA) and support vector machines (SVM). Finally, a set of discrete hidden Markov models (HMM) have been used to classify gesture sequence performed during rehabilitation. Experimental validation using a large number of samples collected from healthy volunteers reveals that DA and SVM perform similarly while applied on isolated gesture recognition. We have compared the results of HMM-based sequence classification with CRF-based techniques. Our results confirm that both HMM and CRF perform quite similarly when tested on gesture sequences. The proposed system can be used for home-based palm or finger rehabilitation in the absence of experts.

Probabilistic techniques for obtaining accurate patient counts in Clinical Data Warehouses

PubMed Central

Myers, Risa B.; Herskovic, Jorge R.

2011-01-01

Proposal and execution of clinical trials, computation of quality measures and discovery of correlation between medical phenomena are all applications where an accurate count of patients is needed. However, existing sources of this type of patient information, including Clinical Data Warehouses (CDW) may be incomplete or inaccurate. This research explores applying probabilistic techniques, supported by the MayBMS probabilistic database, to obtain accurate patient counts from a clinical data warehouse containing synthetic patient data. We present a synthetic clinical data warehouse (CDW), and populate it with simulated data using a custom patient data generation engine. We then implement, evaluate and compare different techniques for obtaining patients counts. We model billing as a test for the presence of a condition. We compute billing’s sensitivity and specificity both by conducting a “Simulated Expert Review” where a representative sample of records are reviewed and labeled by experts, and by obtaining the ground truth for every record. We compute the posterior probability of a patient having a condition through a “Bayesian Chain”, using Bayes’ Theorem to calculate the probability of a patient having a condition after each visit. The second method is a “one-shot” approach that computes the probability of a patient having a condition based on whether the patient is ever billed for the condition Our results demonstrate the utility of probabilistic approaches, which improve on the accuracy of raw counts. In particular, the simulated review paired with a single application of Bayes’ Theorem produces the best results, with an average error rate of 2.1% compared to 43.7% for the straightforward billing counts. Overall, this research demonstrates that Bayesian probabilistic approaches improve patient counts on simulated patient populations. We believe that total patient counts based on billing data are one of the many possible applications of our Bayesian framework. Use of these probabilistic techniques will enable more accurate patient counts and better results for applications requiring this metric. PMID:21986292

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)

Predicting the graft survival for heart-lung transplantation patients: an integrated data mining methodology.

PubMed

Oztekin, Asil; Delen, Dursun; Kong, Zhenyu James

2009-12-01

Predicting the survival of heart-lung transplant patients has the potential to play a critical role in understanding and improving the matching procedure between the recipient and graft. Although voluminous data related to the transplantation procedures is being collected and stored, only a small subset of the predictive factors has been used in modeling heart-lung transplantation outcomes. The previous studies have mainly focused on applying statistical techniques to a small set of factors selected by the domain-experts in order to reveal the simple linear relationships between the factors and survival. The collection of methods known as 'data mining' offers significant advantages over conventional statistical techniques in dealing with the latter's limitations such as normality assumption of observations, independence of observations from each other, and linearity of the relationship between the observations and the output measure(s). There are statistical methods that overcome these limitations. Yet, they are computationally more expensive and do not provide fast and flexible solutions as do data mining techniques in large datasets. The main objective of this study is to improve the prediction of outcomes following combined heart-lung transplantation by proposing an integrated data-mining methodology. A large and feature-rich dataset (16,604 cases with 283 variables) is used to (1) develop machine learning based predictive models and (2) extract the most important predictive factors. Then, using three different variable selection methods, namely, (i) machine learning methods driven variables-using decision trees, neural networks, logistic regression, (ii) the literature review-based expert-defined variables, and (iii) common sense-based interaction variables, a consolidated set of factors is generated and used to develop Cox regression models for heart-lung graft survival. The predictive models' performance in terms of 10-fold cross-validation accuracy rates for two multi-imputed datasets ranged from 79% to 86% for neural networks, from 78% to 86% for logistic regression, and from 71% to 79% for decision trees. The results indicate that the proposed integrated data mining methodology using Cox hazard models better predicted the graft survival with different variables than the conventional approaches commonly used in the literature. This result is validated by the comparison of the corresponding Gains charts for our proposed methodology and the literature review based Cox results, and by the comparison of Akaike information criteria (AIC) values received from each. Data mining-based methodology proposed in this study reveals that there are undiscovered relationships (i.e. interactions of the existing variables) among the survival-related variables, which helps better predict the survival of the heart-lung transplants. It also brings a different set of variables into the scene to be evaluated by the domain-experts and be considered prior to the organ transplantation.

Using CLIPS as the cornerstone of a graduate expert systems course

NASA Technical Reports Server (NTRS)

Yue, Kwok-Bun

1991-01-01

The effective use of the C Language Integrated Production System (CLIPS) as a cornerstone in a graduate expert systems course is described. The course include 8 or 9 hours of in-depth lecturing in CLIPS, as well as a broad coverage of major topics and techniques in expert systems. As part of the requirements of the course, students solved two small yet non-trival problems in CLIPS before going on to develop a toy expert system in CLIPS in an incremental manner as the term project. Furthermore, students were required to evaluate CLIPS programs written by their classmates. An anonymous questionnaire at the end of the semester revealed that the students responded very favorably to the course, especially their experience with CLIPS.

Automation technology for aerospace power management

NASA Technical Reports Server (NTRS)

Larsen, R. L.

1982-01-01

The growing size and complexity of spacecraft power systems coupled with limited space/ground communications necessitate increasingly automated onboard control systems. Research in computer science, particularly artificial intelligence has developed methods and techniques for constructing man-machine systems with problem-solving expertise in limited domains which may contribute to the automation of power systems. Since these systems perform tasks which are typically performed by human experts they have become known as Expert Systems. A review of the current state of the art in expert systems technology is presented, and potential applications in power systems management are considered. It is concluded that expert systems appear to have significant potential for improving the productivity of operations personnel in aerospace applications, and in automating the control of many aerospace systems.

Exploring health literacy competencies towards patient education programme for Chinese-speaking healthcare professionals: a Delphi study

PubMed Central

Chang, Li-Chun; Chen, Yu-Chi; Wu, Fei Ling; Liao, Li-Ling

2017-01-01

Objectives To achieve consensus on a set of competencies in health literacy practice based on a literature review and expert consultation. Setting Hospitals and community health centres in Taiwan. Method A 2-stage modified Delphi study involving a literature review was conducted, followed by qualitative interviews and 3 rounds of email-based data collection over a 3-month period in 2011. Participants 15 Chinese healthcare practitioners with more than 6 months’ experience in patient education were interviewed to collect data on health literacy practice. 24 experts (12 academic scholars in health literacy and 12 professionals with training related to health literacy practice) were invited to participate in the Delphi process. Results Qualitative data from the interviews were analysed and summarised to form 99 competency items for health literacy practice, which were categorised into 5 domains of health literacy practice including those pertaining to knowledge and skills. Consensus was reached on 92 of 99 competencies, using a modified Delphi technique. Conclusions The 92 competencies in health literacy practice embraced core components of patient education in the Chinese healthcare profession. PMID:28093428

Teaching research methods in nursing using Aronson's Jigsaw Technique. A cross-sectional survey of student satisfaction.

PubMed

Leyva-Moral, Juan M; Riu Camps, Marta

2016-05-01

To adapt nursing studies to the European Higher Education Area, new teaching methods have been included that assign maximum importance to student-centered learning and collaborative work. The Jigsaw Technique is based on collaborative learning and everyone in the group must play their part because each student's mark depends on the other students. Home group members are given the responsibility to become experts in a specific area of knowledge. Experts meet together to reach an agreement and improve skills. Finally, experts return to their home groups to share all their findings. The aim of this study was to evaluate nursing student satisfaction with the Jigsaw Technique used in the context of a compulsory course in research methods for nursing. A cross-sectional study was conducted using a self-administered anonymous questionnaire administered to students who completed the Research Methods course during the 2012-13 and 2013-14 academic years. The questionnaire was developed taking into account the learning objectives, competencies and skills that should be acquired by students, as described in the course syllabus. The responses were compared by age group (younger or older than 22years). A total of 89.6% of nursing students under 22years believed that this methodology helped them to develop teamwork, while this figure was 79.6% in older students. Nursing students also believed it helped them to work independently, with differences according to age, 79.7% and 58% respectively (p=0.010). Students disagreed with the statement "The Jigsaw Technique involves little workload", with percentages of 88.5% in the group under 22years and 80% in older students. Most believed that this method should not be employed in upcoming courses, although there were differences by age, with 44.3% of the younger group being against and 62% of the older group (p=0.037). The method was not highly valued by students, mainly by those older than 22years, who concluded that they did not learn more with it than with other traditional techniques. The results of this study question whether this form of learning meets students' learning needs and its compatibility with individual and group realities. Copyright © 2016 Elsevier Ltd. All rights reserved.

Does an expert-based evaluation allow us to go beyond the Impact Factor? Experiences from building a ranking of national journals in Poland.

PubMed

Kulczycki, Emanuel; Rozkosz, Ewa A

2017-01-01

This article discusses the Polish Journal Ranking, which is used in the research evaluation system in Poland. In 2015, the ranking, which represents all disciplines, allocated 17,437 journals into three lists: A, B, and C. The B list constitutes a ranking of Polish journals that are indexed neither in the Web of Science nor the European Reference Index for the Humanities. This ranking was built by evaluating journals in three dimensions: formal, bibliometric, and expert-based. We have analysed data on 2035 Polish journals from the B list. Our study aims to determine how an expert-based evaluation influenced the results of final evaluation. In our study, we used structural equation modelling, which is regression based, and we designed three pairs of theoretical models for three fields of science: (1) humanities, (2) social sciences, and (3) engineering, natural sciences, and medical sciences. Each pair consisted of the full model and the reduced model (i.e., the model without the expert-based evaluation). Our analysis revealed that the multidimensional evaluation of local journals should not rely only on the bibliometric indicators, which are based on the Web of Science or Scopus. Moreover, we have shown that the expert-based evaluation plays a major role in all fields of science. We conclude with recommendations that the formal evaluation should be reduced to verifiable parameters and that the expert-based evaluation should be based on common guidelines for the experts.

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 CLIPS-based expert system for the evaluation and selection of robots

NASA Technical Reports Server (NTRS)

Nour, Mohamed A.; Offodile, Felix O.; Madey, Gregory R.

1994-01-01

This paper describes the development of a prototype expert system for intelligent selection of robots for manufacturing operations. The paper first develops a comprehensive, three-stage process to model the robot selection problem. The decisions involved in this model easily lend themselves to an expert system application. A rule-based system, based on the selection model, is developed using the CLIPS expert system shell. Data about actual robots is used to test the performance of the prototype system. Further extensions to the rule-based system for data handling and interfacing capabilities are suggested.

Development of Type 2 Diabetes Mellitus Phenotyping Framework Using Expert Knowledge and Machine Learning Approach.

PubMed

Kagawa, Rina; Kawazoe, Yoshimasa; Ida, Yusuke; Shinohara, Emiko; Tanaka, Katsuya; Imai, Takeshi; Ohe, Kazuhiko

2017-07-01

Phenotyping is an automated technique that can be used to distinguish patients based on electronic health records. To improve the quality of medical care and advance type 2 diabetes mellitus (T2DM) research, the demand for T2DM phenotyping has been increasing. Some existing phenotyping algorithms are not sufficiently accurate for screening or identifying clinical research subjects. We propose a practical phenotyping framework using both expert knowledge and a machine learning approach to develop 2 phenotyping algorithms: one is for screening; the other is for identifying research subjects. We employ expert knowledge as rules to exclude obvious control patients and machine learning to increase accuracy for complicated patients. We developed phenotyping algorithms on the basis of our framework and performed binary classification to determine whether a patient has T2DM. To facilitate development of practical phenotyping algorithms, this study introduces new evaluation metrics: area under the precision-sensitivity curve (AUPS) with a high sensitivity and AUPS with a high positive predictive value. The proposed phenotyping algorithms based on our framework show higher performance than baseline algorithms. Our proposed framework can be used to develop 2 types of phenotyping algorithms depending on the tuning approach: one for screening, the other for identifying research subjects. We develop a novel phenotyping framework that can be easily implemented on the basis of proper evaluation metrics, which are in accordance with users' objectives. The phenotyping algorithms based on our framework are useful for extraction of T2DM patients in retrospective studies.

Clinical Guidelines for Management of Bone Health in Rett Syndrome Based on Expert Consensus and Available Evidence.

PubMed

Jefferson, Amanda; Leonard, Helen; Siafarikas, Aris; Woodhead, Helen; Fyfe, Sue; Ward, Leanne M; Munns, Craig; Motil, Kathleen; Tarquinio, Daniel; Shapiro, Jay R; Brismar, Torkel; Ben-Zeev, Bruria; Bisgaard, Anne-Marie; Coppola, Giangennaro; Ellaway, Carolyn; Freilinger, Michael; Geerts, Suzanne; Humphreys, Peter; Jones, Mary; Lane, Jane; Larsson, Gunilla; Lotan, Meir; Percy, Alan; Pineda, Mercedes; Skinner, Steven; Syhler, Birgit; Thompson, Sue; Weiss, Batia; Witt Engerström, Ingegerd; Downs, Jenny

2016-01-01

We developed clinical guidelines for the management of bone health in Rett syndrome through evidence review and the consensus of an expert panel of clinicians. An initial guidelines draft was created which included statements based upon literature review and 11 open-ended questions where literature was lacking. The international expert panel reviewed the draft online using a 2-stage Delphi process to reach consensus agreement. Items describe the clinical assessment of bone health, bone mineral density assessment and technique, and pharmacological and non-pharmacological interventions. Agreement was reached on 39 statements which were formulated from 41 statements and 11 questions. When assessing bone health in Rett syndrome a comprehensive assessment of fracture history, mutation type, prescribed medication, pubertal development, mobility level, dietary intake and biochemical bone markers is recommended. A baseline densitometry assessment should be performed with accommodations made for size, with the frequency of surveillance determined according to individual risk. Lateral spine x-rays are also suggested. Increasing physical activity and initiating calcium and vitamin D supplementation when low are the first approaches to optimizing bone health in Rett syndrome. If individuals with Rett syndrome meet the ISCD criterion for osteoporosis in children, the use of bisphosphonates is recommended. A clinically significant history of fracture in combination with low bone densitometry findings is necessary for a diagnosis of osteoporosis. These evidence and consensus-based guidelines have the potential to improve bone health in those with Rett syndrome, reduce the frequency of fractures, and stimulate further research that aims to ameliorate the impacts of this serious comorbidity.

Models Used to Select Strategic Planning Experts for High Technology Productions

NASA Astrophysics Data System (ADS)

Zakharova, Alexandra A.; Grigorjeva, Antonina A.; Tseplit, Anna P.; Ozgogov, Evgenij V.

2016-04-01

The article deals with the problems and specific aspects in organizing works of experts involved in assessment of companies that manufacture complex high-technology products. A model is presented that is intended for evaluating competences of experts in individual functional areas of expertise. Experts are selected to build a group on the basis of tables used to determine a competence level. An expert selection model based on fuzzy logic is proposed and additional requirements for the expert group composition can be taken into account, with regard to the needed quality and competence related preferences of decision-makers. A Web-based information system model is developed for the interaction between experts and decision-makers when carrying out online examinations.

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.

Consulting the oracle: ten lessons from using the Delphi technique in nursing research.

PubMed

Keeney, Sinead; Hasson, Felicity; McKenna, Hugh

2006-01-01

The aim of this paper was to provide insight into the Delphi technique by outlining our personal experiences during its use over a 10-year period in a variety of applications. As a means of achieving consensus on an issue, the Delphi research method has become widely used in healthcare research generally and nursing research in particular. The literature on this technique is expanding, mainly addressing what it is and how it should be used. However, there is still much confusion and uncertainty surrounding it, particularly about issues such as modifications, consensus, anonymity, definition of experts, how 'experts' are selected and how non-respondents are pursued. This issues that arise when planning and carrying out a Delphi study include the definition of consensus; the issue of anonymity vs. quasi-anonymity for participants; how to estimate the time needed to collect the data, analyse each 'round', feed back results to participants, and gain their responses to this feedback; how to define and select the 'experts' who will be asked to participate; how to enhance response rates; and how many 'rounds' to conduct. Many challenges and questions are raised when using the Delphi technique, but there is no doubt that it is an important method for achieving consensus on issues where none previously existed. Researchers need to adapt the method to suit their particular study.

A bird's eye view: the cognitive strategies of experts interpreting seismic profiles

NASA Astrophysics Data System (ADS)

Bond, C. E.; Butler, R.

2012-12-01

Geoscience is perhaps unique in its reliance on incomplete datasets and building knowledge from their interpretation. This interpretation basis for the science is fundamental at all levels; from creation of a geological map to interpretation of remotely sensed data. To teach and understand better the uncertainties in dealing with incomplete data we need to understand the strategies individual practitioners deploy that make them effective interpreters. The nature of interpretation is such that the interpreter needs to use their cognitive ability in the analysis of the data to propose a sensible solution in their final output that is both consistent not only with the original data but also with other knowledge and understanding. In a series of experiments Bond et al. (2007, 2008, 2011, 2012) investigated the strategies and pitfalls of expert and non-expert interpretation of seismic images. These studies focused on large numbers of participants to provide a statistically sound basis for analysis of the results. The outcome of these experiments showed that techniques and strategies are more important than expert knowledge per se in developing successful interpretations. Experts are successful because of their application of these techniques. In a new set of experiments we have focused on a small number of experts to determine how they use their cognitive and reasoning skills, in the interpretation of 2D seismic profiles. Live video and practitioner commentary were used to track the evolving interpretation and to gain insight on their decision processes. The outputs of the study allow us to create an educational resource of expert interpretation through online video footage and commentary with associated further interpretation and analysis of the techniques and strategies employed. This resource will be of use to undergraduate, post-graduate, industry and academic professionals seeking to improve their seismic interpretation skills, develop reasoning strategies for dealing with incomplete datasets, and for assessing the uncertainty in these interpretations. Bond, C.E. et al. (2012). 'What makes an expert effective at interpreting seismic images?' Geology, 40, 75-78. Bond, C. E. et al. (2011). 'When there isn't a right answer: interpretation and reasoning, key skills for 21st century geoscience'. International Journal of Science Education, 33, 629-652. Bond, C. E. et al. (2008). 'Structural models: Optimizing risk analysis by understanding conceptual uncertainty'. First Break, 26, 65-71. Bond, C. E. et al., (2007). 'What do you think this is?: "Conceptual uncertainty" In geoscience interpretation'. GSA Today, 17, 4-10.

Automatic assessment of voice quality according to the GRBAS scale.

PubMed

Sáenz-Lechón, Nicolás; Godino-Llorente, Juan I; Osma-Ruiz, Víctor; Blanco-Velasco, Manuel; Cruz-Roldán, Fernando

2006-01-01

Nowadays, the most extended techniques to measure the voice quality are based on perceptual evaluation by well trained professionals. The GRBAS scale is a widely used method for perceptual evaluation of voice quality. The GRBAS scale is widely used in Japan and there is increasing interest in both Europe and the United States. However, this technique needs well-trained experts, and is based on the evaluator's expertise, depending a lot on his own psycho-physical state. Furthermore, a great variability in the assessments performed from one evaluator to another is observed. Therefore, an objective method to provide such measurement of voice quality would be very valuable. In this paper, the automatic assessment of voice quality is addressed by means of short-term Mel cepstral parameters (MFCC), and learning vector quantization (LVQ) in a pattern recognition stage. Results show that this approach provides acceptable results for this purpose, with accuracy around 65% at the best.

SCADA-based Operator Support System for Power Plant Equipment Fault Forecasting

NASA Astrophysics Data System (ADS)

Mayadevi, N.; Ushakumari, S. S.; Vinodchandra, S. S.

2014-12-01

Power plant equipment must be monitored closely to prevent failures from disrupting plant availability. Online monitoring technology integrated with hybrid forecasting techniques can be used to prevent plant equipment faults. A self learning rule-based expert system is proposed in this paper for fault forecasting in power plants controlled by supervisory control and data acquisition (SCADA) system. Self-learning utilizes associative data mining algorithms on the SCADA history database to form new rules that can dynamically update the knowledge base of the rule-based expert system. In this study, a number of popular associative learning algorithms are considered for rule formation. Data mining results show that the Tertius algorithm is best suited for developing a learning engine for power plants. For real-time monitoring of the plant condition, graphical models are constructed by K-means clustering. To build a time-series forecasting model, a multi layer preceptron (MLP) is used. Once created, the models are updated in the model library to provide an adaptive environment for the proposed system. Graphical user interface (GUI) illustrates the variation of all sensor values affecting a particular alarm/fault, as well as the step-by-step procedure for avoiding critical situations and consequent plant shutdown. The forecasting performance is evaluated by computing the mean absolute error and root mean square error of the predictions.

Autonomous self-organizing resource manager for multiple networked platforms

NASA Astrophysics Data System (ADS)

Smith, James F., III

2002-08-01

A fuzzy logic based expert system for resource management has been developed that automatically allocates electronic attack (EA) resources in real-time over many dissimilar autonomous naval platforms defending their group against attackers. The platforms can be very general, e.g., ships, planes, robots, land based facilities, etc. Potential foes the platforms deal with can also be general. This paper provides an overview of the resource manager including the four fuzzy decision trees that make up the resource manager; the fuzzy EA model; genetic algorithm based optimization; co-evolutionary data mining through gaming; and mathematical, computational and hardware based validation. Methods of automatically designing new multi-platform EA techniques are considered. The expert system runs on each defending platform rendering it an autonomous system requiring no human intervention. There is no commanding platform. Instead the platforms work cooperatively as a function of battlespace geometry; sensor data such as range, bearing, ID, uncertainty measures for sensor output; intelligence reports; etc. Computational experiments will show the defending networked platform's ability to self- organize. The platforms' ability to self-organize is illustrated through the output of the scenario generator, a software package that automates the underlying data mining problem and creates a computer movie of the platforms' interaction for evaluation.

Classification of drugs with different risk profiles.

PubMed

Saedder, Eva Aggerholm; Brock, Birgitte; Nielsen, Lars Peter; Bonnerup, Dorthe Krogsgaard; Lisby, Marianne

2015-08-01

A risk stratification approach is needed to identify patients at high risk of medication errors and a resulting high need of medication review. The aim of this study was to perform risk stratification (distinguishing between low-risk, medium-risk and high-risk drugs) for drugs found to cause serious adverse reactions due to medication errors. The study employed a modified Delphi technique. Drugs from a systematic literature search were included into two rounds of a Delphi process. A panel of experts was asked to evaluate each identified drug's potential for harm and for clinically relevant drug-drug interactions on a scale from 1 (low risk) to 9 (high risk). A total of 36 experts were appointed to serve on the panel. Consensus was reached for 29/57 (51%) drugs or drug classes that cause harm, and for 32/57 (56%) of the drugs or drug classes that cause interactions. For the remaining drugs, a decision was made based on the median score. Two lists, one stating the drugs' potential for causing harm and the other stating clinically relevant drug-drug interactions, were stratified into low-risk, medium-risk and high-risk drugs. Based on a modified Delphi technique, we created two lists of drugs stratified into a low-risk, a medium-risk and a high-risk group of clinically relevant interactions or risk of harm to patients. The lists could be incorporated into a risk-scoring tool that stratifies the performance of medication reviews according to patients' risk of experiencing adverse reactions. none. not relevant.

Utilisation de la teledetection, des SIG et de l'intelligence artificielle pour determiner le niveau de susceptibilite aux mouvements de terrain: Application dans les Andes de la Bolivie

NASA Astrophysics Data System (ADS)

Peloquin, Stephane

1999-11-01

The socio-economic impact of mass movements for our society is getting more and more serious. The loss of lives and economic losses are now ten times greater than they were at the beginning of the decade. In the hope of reducing these impacts, it is essential to adopt a preventive policy that will encourage mapping of mass movement susceptibility level (MMSL) in critical zones. However, this task is complex and only experts using present techniques can provide satisfactory results. To make possible the production of these maps by a larger number of individuals, we have developed an expert system called EXPERIM that uses remote sensing data and geographic information systems to facilitate the complex tasks without requiring the user to be highly competent in this field of study. This thesis presents the results obtained from a complete strategy developed for a region surrounding Cochabamba, Bolivia. The operational expert system prototype will soon be integrated within the watershed management program directed by the local executing organisation PROMIC. The knowledge acquisition and its expression in concrete terms constitute the principal axis of this research, while the results obtained are the heart of the EXPERIM expert system. These strategic steps aim to establish a knowledge base of data and rules that describe field conditions for each MMSL. We have been able to extract this information by using binary discriminant analysis of a MMSL map produced by an expert for a pilot zone called Cuenca Taquina, which is geoecologically representative of the 38 neighbouring watersheds. Using this technique, we were able to establish a sensitivity model that recreates the expert's map with a success rate of 89% and 78% when two or three MMS levels are used. Based on a detailed analysis of the susceptibility model it was evident that stability conditions are the result of the topographic, geologic and geomorphologic environments. The level of susceptibility was found to be independent of the vegetation condition. In order to apply the model to the surrounding watersheds, we integrated remotely sensed data within the spatial database to map the presence/absence of five essential geoecological units required by the susceptibility model. This was done using a hierarchical classification method. Three sensors were evaluated: Landsat, SPOT and RADARSAT. In the elaboration of this specific step, we evaluated the most efficient spectral band combinations within each image and between images for each of the five geoecological units. For each of the land cover types, the analysis shows that LANDSAT constitutes the most powerful sensor to map these units and that image fusion does not provide significantly better results when compared to the extra amount of work that this requires. Using remote sensing data instead of field data or airphotograph interpretation in watersheds where only topographic data are available decreases the level of accuracy by less than 10%.

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.

Structural Representations in Knowledge Acquisition.

ERIC Educational Resources Information Center

Gonzalvo, Pilar; And Others

1994-01-01

Multidimensional scaling (MDS) and Pathfinder techniques for assessing changes in the structural representation of a knowledge domain were studied with relatedness ratings collected from 72 Spanish college students. Comparison of student and expert similarity measures indicate that MDS and graph theoretic approaches are valid techniques. (SLD)

Using AI Planning Techniques to Automatically Generate Image Processing Procedures: A Preliminary Report

NASA Technical Reports Server (NTRS)

Chien, S.

1994-01-01

This paper describes work on the Multimission VICAR Planner (MVP) system to automatically construct executable image processing procedures for custom image processing requests for the JPL Multimission Image Processing Lab (MIPL). This paper focuses on two issues. First, large search spaces caused by complex plans required the use of hand encoded control information. In order to address this in a manner similar to that used by human experts, MVP uses a decomposition-based planner to implement hierarchical/skeletal planning at the higher level and then uses a classical operator based planner to solve subproblems in contexts defined by the high-level decomposition.

Knowledge-based machine vision systems for space station automation

NASA Technical Reports Server (NTRS)

Ranganath, Heggere S.; Chipman, Laure J.

1989-01-01

Computer vision techniques which have the potential for use on the space station and related applications are assessed. A knowledge-based vision system (expert vision system) and the development of a demonstration system for it are described. This system implements some of the capabilities that would be necessary in a machine vision system for the robot arm of the laboratory module in the space station. A Perceptics 9200e image processor, on a host VAXstation, was used to develop the demonstration system. In order to use realistic test images, photographs of actual space shuttle simulator panels were used. The system's capabilities of scene identification and scene matching are discussed.

Personal manufacturing systems

NASA Astrophysics Data System (ADS)

Bailey, P.

1992-04-01

Personal Manufacturing Systems are the missing link in the automation of the design-to- manufacture process. A PMS will act as a CAD peripheral, closing the loop around the designer enabling him to directly produce models, short production runs or soft tooling with as little fuss as he might otherwise plot a drawing. Whereas conventional 5-axis CNC machines are based on orthogonal axes and simple incremental movements, the PMS is based on a geodetic structure and complex co-ordinated 'spline' movements. The software employs a novel 3D pixel technique for give itself 'spatial awareness' and an expert system to determine the optimum machining conditions. A completely automatic machining strategy can then be determined.

Expanding Students' Perceptions of Scientists through the Dramatic Technique of Role on the Wall

ERIC Educational Resources Information Center

Swanson, Carolyn

2016-01-01

This paper highlights the use of a drama convention--"Role on the Wall"--to teach the Nature of Science (NOS) in a Year 7/8 classroom. Students were positioned as "expert" scientists re-investigating the science behind the sinking of the Wahine in a Mantle of the Expert unit. Students drew a "Role on the Wall" of a…

Machine Learning for Biological Trajectory Classification Applications

NASA Technical Reports Server (NTRS)

Sbalzarini, Ivo F.; Theriot, Julie; Koumoutsakos, Petros

2002-01-01

Machine-learning techniques, including clustering algorithms, support vector machines and hidden Markov models, are applied to the task of classifying trajectories of moving keratocyte cells. The different algorithms axe compared to each other as well as to expert and non-expert test persons, using concepts from signal-detection theory. The algorithms performed very well as compared to humans, suggesting a robust tool for trajectory classification in biological applications.

Using C to build a satellite scheduling expert system: Examples from the Explorer Platform planning system

NASA Technical Reports Server (NTRS)

Mclean, David R.; Tuchman, Alan; Potter, William J.

1991-01-01

A C-based artificial intelligence (AI) development effort which is based on a software tools approach is discussed with emphasis on reusability and maintainability of code. The discussion starts with simple examples of how list processing can easily be implemented in C and then proceeds to the implementations of frames and objects which use dynamic memory allocation. The implementation of procedures which use depth first search, constraint propagation, context switching, and blackboard-like simulation environment are described. Techniques for managing the complexity of C-based AI software are noted, especially the object-oriented techniques of data encapsulation and incremental development. Finally, all these concepts are put together by describing the components of planning software called the Planning And Resource Reasoning (PARR) Shell. This shell was successfully utilized for scheduling services of the Tracking and Data Relay Satellite System for the Earth Radiation Budget Satellite since May of 1987 and will be used for operations scheduling of the Explorer Platform in Nov. of 1991.

Expert training with standardized operative technique helps establish a successful penile prosthetics program for urologic resident education.

PubMed

King, Ashley B; Klausner, Adam P; Johnson, Corey M; Moore, Blake W; Wilson, Steven K; Grob, B Mayer

2011-10-01

The challenge of resident education in urologic surgery programs is to overcome disparity imparted by diverse patient populations, limited training times, and inequalities in the availability of expert surgical educators. Specifically, in the area of prosthetic urology, only a small proportion of programs have full-time faculty available to train residents in this discipline. To examine whether a new model using yearly training sessions from a recognized expert can establish a successful penile prosthetics program and result in better outcomes, higher case volumes, and willingness to perform more complex surgeries. A recognized expert conducted one to two operative training sessions yearly to teach standardized technique for penile prosthetics to residents. Each session consisted of three to four operative cases performed under the direct supervision of the expert. Retrospective data were collected from all penile prosthetic operations before (February, 2000 to June, 2004: N = 44) and after (July, 2004 to October, 2007: N = 79) implementation of these sessions. Outcomes reviewed included patient age, race, medical comorbidities, operative time, estimated blood loss, type of prosthesis, operative approach, drain usage, length of stay, and complications including revision/explantation rates. Statistical analysis was performed using Student's t-tests, Fisher's tests, and survival curves using the Kaplan-Meier technique (P value ≤ 0.05 to define statistical significance). Patient characteristics were not significantly different pre- vs. post-training. Operative time and estimated blood loss significantly decreased. Inflatable implants increased from 19/44 (43.2%, pre-training) to 69/79 (87.3%, post-training) (P < 0.01). Operations per year increased from 9.96 (pre-training) to 24 (post-training) (P < 0.01). Revision/explantation occurred in 11/44 patients (25%, pre-training) vs. 7/79 (8.9%, post-training) (P < 0.05). These data demonstrate that yearly sessions with a recognized expert can improve surgical outcomes, type, and volume of implants and can reduce explantation/revision rates. This represents an excellent model for improved training of urologic residents in penile prosthetics surgery. © 2011 International Society for Sexual Medicine.

Logic-based assessment of the compatibility of UMLS ontology sources

PubMed Central

2011-01-01

Background The UMLS Metathesaurus (UMLS-Meta) is currently the most comprehensive effort for integrating independently-developed medical thesauri and ontologies. UMLS-Meta is being used in many applications, including PubMed and ClinicalTrials.gov. The integration of new sources combines automatic techniques, expert assessment, and auditing protocols. The automatic techniques currently in use, however, are mostly based on lexical algorithms and often disregard the semantics of the sources being integrated. Results In this paper, we argue that UMLS-Meta’s current design and auditing methodologies could be significantly enhanced by taking into account the logic-based semantics of the ontology sources. We provide empirical evidence suggesting that UMLS-Meta in its 2009AA version contains a significant number of errors; these errors become immediately apparent if the rich semantics of the ontology sources is taken into account, manifesting themselves as unintended logical consequences that follow from the ontology sources together with the information in UMLS-Meta. We then propose general principles and specific logic-based techniques to effectively detect and repair such errors. Conclusions Our results suggest that the methodologies employed in the design of UMLS-Meta are not only very costly in terms of human effort, but also error-prone. The techniques presented here can be useful for both reducing human effort in the design and maintenance of UMLS-Meta and improving the quality of its contents. PMID:21388571

Study on the performance of different craniofacial superimposition approaches (II): Best practices proposal.

PubMed

Damas, S; Wilkinson, C; Kahana, T; Veselovskaya, E; Abramov, A; Jankauskas, R; Jayaprakash, P T; Ruiz, E; Navarro, F; Huete, M I; Cunha, E; Cavalli, F; Clement, J; Lestón, P; Molinero, F; Briers, T; Viegas, F; Imaizumi, K; Humpire, D; Ibáñez, O

2015-12-01

Craniofacial superimposition, although existing for one century, is still a controversial technique within the scientific community. Objective and unbiased validation studies over a significant number of cases are required to establish a more solid picture on the reliability. However, there is lack of protocols and standards in the application of the technique leading to contradictory information concerning reliability. Instead of following a uniform methodology, every expert tends to apply his own approach to the problem, based on the available technology and deep knowledge on human craniofacial anatomy, soft tissues, and their relationships. The aim of this study was to assess the reliability of different craniofacial superimposition methodologies and the corresponding technical approaches to this type of identification. With all the data generated, some of the most representative experts in craniofacial identification joined in a discussion intended to identify and agree on the most important issues that have to be considered to properly employ the craniofacial superimposition technique. As a consequence, the consortium has produced the current manuscript, which can be considered the first standard in the field; including good and bad practices, sources of error and uncertainties, technological requirements and desirable features, and finally a common scale for the craniofacial matching evaluation. Such a document is intended to be part of a more complete framework for craniofacial superimposition, to be developed during the FP7-founded project MEPROCS, which will favour and standardize its proper application. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

[Analysis of syndrome discipline of generalized anxiety disorder using data mining techniques].

PubMed

Tang, Qi-sheng; Sun, Wen-jun; Qu, Miao; Guo, Dong-fang

2012-09-01

To study the use of data mining techniques in analyzing the syndrome discipline of generalized anxiety disorder (GAD). From August 1, 2009 to July 31, 2010, 705 patients with GAD in 10 hospitals of Beijing were investigated over one year. Data mining techniques, such as Bayes net and cluster analysis, were used to analyze the syndrome discipline of GAD. A total of 61 symptoms of GAD were screened out. By using Bayes net, nine syndromes of GAD were abstracted based on the symptoms. Eight syndromes were abstracted by cluster analysis. After screening for duplicate syndromes and combining the experts' experience and traditional Chinese medicine theory, six syndromes of GAD were defined. These included depressed liver qi transforming into fire, phlegm-heat harassing the heart, liver depression and spleen deficiency, heart-kidney non-interaction, dual deficiency of the heart and spleen, and kidney deficiency and liver yang hyperactivity. Based on the results, the draft of Syndrome Diagnostic Criteria for Generalized Anxiety Disorder was developed. Data mining techniques such as Bayes net and cluster analysis have certain future potential for establishing syndrome models and analyzing syndrome discipline, thus they are suitable for the research of syndrome differentiation.

An expert system to manage the operation of the Space Shuttle's fuel cell cryogenic reactant tanks

NASA Technical Reports Server (NTRS)

Murphey, Amy Y.

1990-01-01

This paper describes a rule-based expert system to manage the operation of the Space Shuttle's cryogenic fuel system. Rules are based on standard fuel tank operating procedures described in the EECOM Console Handbook. The problem of configuring the operation of the Space Shuttle's fuel tanks is well-bounded and well defined. Moreover, the solution of this problem can be encoded in a knowledge-based system. Therefore, a rule-based expert system is the appropriate paradigm. Furthermore, the expert system could be used in coordination with power system simulation software to design operating procedures for specific missions.

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.