Expert Systems Research Papers - Academia.edu (original) (raw)

This article examines how 'safety case' experts working on Finland’s nuclear waste repository project at Olkiluoto summoned, conjured, or channeled memories of Seppo—a deceased colleague whose ‘specter,’ as some put it, still ‘haunts’ their scientific community. For some, Seppo’s postmortem presence manifested as gaps in knowledge left behind by an expert often reluctant to document the methodological assumptions underlying his knowledge-practices. For others, it manifested as anecdotes about Seppo’s stubbornness, irritability, and intellectual intensity as well as his more jovial demeanor during sauna nights, workplace parties, or trips abroad. Still others caught themselves asking ‘What Would Seppo Do?’ while troubleshooting at work. Inspired by anthropological and philosophical work on ancestors and haunting, the article unpacks how the multi-millennial time horizons of nuclear waste risk, the intergenerational time horizons of expert succession, and the everyday time horizons of a single expert life-course shared entwined fates. It focuses less on what knowledge disappeared when an expert’s body died – or how it could have been preventatively backed-up or managed – and more on what has lived on of the expert in and through surviving colleagues. Analysis of 'afterlives of expertise' like these can, it concludes, provide insights for a current moment of intergenerational transition in nuclear energy sectors in Europe, North America, and beyond.

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- Nuclear Engineering, European Studies, Expert Systems, Nuclear Physics

Focusing on experts in technology and science, ‘Building Europe on Expertise’ delivers a new reading of European history. The authors show that modern European history was defined by experts using their new knowledge to shape societies, set political agendas and establish research institutions and agendas which proved decisive in integrating the continent.

Nonverbal behaviors play a crucial role in shaping outcomes in face-toface clinical interactions. Experienced clinicians use nonverbals to foster rapport and "read" their clients to inform diagnoses. The rise of telemedicine and virtual health agents creates new opportunities, but it also strips away much of this nonverbal channel. Recent advances in low-cost computer vision and sensing technologies have the potential to address this challenge by learning to recognize nonverbal cues from large datasets of clinical interactions. These techniques can enhance both telemedicine and the emerging technology of virtual health agents. This article describes our current research in addressing these challenges in the domain of PTSD and depression screening for U.S. Veterans. We describe our general approach and report on our initial contribution: the creation of a large dataset of clinical interview data that facilitates the training of user-state sensing technology.

- by Skip Rizzo
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- Computer Science, Expert Systems, Nonverbal Communication, Telemedicine
- by Clive Spenser
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- Expert Systems, Legal Rule Based Expert Systems
- by Khaled Shaalan
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- Expert Systems, Knowledge-Based Systems, Knowledge Engineering

A mechanical device or system that can think and look, observe, hear, walk, speak and feel like a human can be developed using a knowledge-based technique known as the expert system. The expert system can be integrated with robotics to connect human intelligence to machines to perform intelligent work like that of humans by incorporating functions such as reasoning, knowledge/intelligence and problem-solving. The methods implemented in expert systems were examined in this article as well as the review of the literature of the different applications of expert systems in the field of robotics. In this article, articles with a keyword index and articles from several literature reviews are discussed to explore the various applications of the expert system. Different types of expert systems are also presented in this article, P. B. Rules for expert systems based on knowledge and expert systems based on diffuse properties, properties and characteristics of the expert system and its advantages.

- by IJRASET Publication
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- Robotics, Artificial Intelligence, Expert Systems

The aim of this research was to develop an intelligent system for pasteurised milk quality assessment and prediction that could help the quality decision makers to assess and predict the pasteurised milk quality. Utilizing Expert System and Artificial Neural Network (ANN), which called SINKUAL-SP, did these analyses. The reasoning strategy used was “Forward Chaining” and the tracing method used was “Best First Search”. Certainty Factor (CF) was used for handling uncertainty. Multi-layer neural network architecture was used. The suited activation function was Sigmoid Bipolar, which gave the best performance network with learning rate 0.005 and momentum 0.9 together with RMSE, MSE and SSE as an error criterion. The validation for neural network indicated the conformity between the output of neural network and the goal output with RMSE value of 0.0099. The system was verified and validated by using real data collected from pasteurised milk and milk Products Company at West Java, Indone...

- by Winnie Septiani
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- Expert Systems, Fuzzy Logic, Intelligent Systems, Milk production and quality

This paper presents a system proposed for the intelligent management of computer networks. The system is based on the use of Arti cial Intelligence t e chniques | data mining, expert systems and multi-agent systems. The work is based on the following lines of actions: a the use of distributed agents for the intelligent search of information in the network, supplying it in a more abstract way, adapted to the decision-making task; b the use of machine learning and data-mining techniques that, starting from the log les which register previous problems and their solution, allow the use of experience thus obtained in the solution new problems; and c the use of heuristics and conduction rules supplied by experts, through a decision support system, as an advisor element to network operators. This paper presents a discussion about the techniques employed along these three r esearch lines and the results already obtained.

- by Emerson Paraiso and +1
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- Artificial Intelligence, Expert Systems, Decision Making, Machine Learning

In this study, artificial neural networks (ANNs) were applied to predict the mean monthly wind speed of any target station using the mean monthly wind speeds of neighboring stations which are indicated as reference stations. Hourly wind speed data, collected by the Turkish State Meteorological Service (TSMS) at 8 measuring stations located in the eastern Mediterranean region of Turkey were used. The long-term wind data, containing hourly wind speeds, directions and related information, cover the period between 1992 and 2001. These data were divided into two sections. According to the correlation coefficients, reference and target stations were defined. The mean monthly wind speeds of reference stations were used and also corresponding months were specified in the input layer of the network. On the other hand, the mean monthly wind speed of the target station was utilized in the output layer of the network. Resilient propagation (RP) learning algorithm was applied in the present simulation. The hidden layers and output layer of the network consist of logistic sigmoid transfer function (logsig) and linear transfer function (purelin) as an activation function. Finally, the values determined by ANN model were compared with the actual data. The maximum mean absolute percentage error was found to be 14.13% for Antakya meteorological station and the best result was found to be 4.49% for Mersin meteorological station. r

- by Martin Bigec
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- Mechanical Engineering, Chemical Engineering, Civil Engineering, Cognitive Science

To design a medical decision support system (MDSS) that would accurately predict the rehabilitation protocols prescribed by the physicians for patients with knee osteoarthritis (OA) using only their demographic and clinical characteristics. The demographic and clinical variables for 170 patients receiving one of three treatment protocols for knee OA were entered into the MDSS. Demographic variables in the model were age and sex. Clinical variables entered into the model were height, weight, BMI, affected side, severity of knee OA, and severity of pain. All patients in the study received one of three treatment protocols for patients with knee OA: (a) hot packs, followed by electrotherapy and exercise, (b) ice packs, followed by ultrasound and exercise and (c) exercise alone. The resilient back propagation artificial neural network algorithm was used, with a ten-fold cross-validation. It was estimated that the MDSS is able to accurately predict the treatment prescribed by the physician for 87% of the patients. We developed an artificial neural network-based decision support system that can viably aid physicians in determining which treatment protocol would best match the anthropometric and clinical characteristics of patients with knee OA. Ziel der vorliegenden Studie war die Konzipierung eines Systems zur Unterstü tzung von medizinischen Entscheidungen (MDSS), das Ä rzten die akkurate Prognose der bei Patienten mit Gonarthrose verordneten Rehabilitation nur anhand ihrer demographischen und klinischen Eigenschaften erlaubt. Die demographischen und klinischen Variablen von 170 Patienten, die eine von drei Behandlungen fü r die Gonarthrose erhielten, wurden in das MDSS ü bertragen. Die demographischen Variablen in dem Modell waren Alter und Geschlecht. Die in das Modell ü bertragenen klinischen Variablen waren Kö rpergrö ße, Kö rpergewicht, BMI, betroffene Seite, Schweregrad der Gonarthrose und Schweregrad der Schmerzen. Alle Studienteilnehmer erhielten eine von drei Behandlungen fü r Patienten mit Gonarthrose: (a) Wä rmebehandlung, gefolgt von Elektrotherapie und Krankengymnastik, (b) Kä lte-Sofortkompressen, gefolgt von Ultraschall und Krankengymnastik, und (c) Krankengymnastik als Monotherapie. Angewandt wurde ein kü nstliches neuronales Netz auf der Basis des belastbaren Backpropagation-Algorithmus mit einer zehnfachen Kreuzvalidierung. Schä tzungen zufolge kann das MDSS die ä rztlich verordnete Therapie bei 87% der

- by Ziad Hawamdeh
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- Expert Systems, Rehabilitation, Prediction, Decision Support Systems

PID controllers are widely used to control the industrial plants because of their robustness and simple structures. Tuning of the controller's parameters to get a desired response is difficult and time consuming. The main purpose of this paper is to sue wireless technology and design a Knowledge Based expert system to tune the parameters of the PID controller without using any mathematical model of the plant. The designed expert system uses pattern recognition techniques to tune the parameters of the controller, as a human expert does. The expert system uses input output to and from the plant under control, using wireless technology. The expert system uses a number of tuning rules to change the parameters of the controller based on the shape of the closed-loop step response to get a desired performance, which has been set by the control engineer. The developed expert system is able to tune the parameters of the controller for fixed, time-varying, time-delayed and noisy plants. The performance of the expert system has been examined using a laboratory ri. .

- by Kamran Khakpour
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- Expert Systems, Control Engineering, Pattern Recognition, Robust control

Driver assistance systems that supply force feedback (FF) on the accelerator commonly use relative distance and velocity with respect to the closest lead vehicle in front of the own vehicle. This 1-D feedback might not accurately represent the situation and can cause unwanted step-shaped changes in the FFs during lateral maneuvers. To address these shortcomings, a 2-D system is proposed that calculates FF using a weighted average of the influences of lead vehicles. Offline simulations and an experiment in a driving simulator were performed to compare no feedback, 1-D systems, and the novel 2-D system during a car-following task with cut-in maneuvers. Results show that the 2-D feedback resulted in lower mean forces, lower response times to cut-in vehicles, and favorable subjective experiences as compared to the 1-D systems.

- by Marinus Van Paassen
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- Algorithms, Expert Systems, Human Factors, Statistical Analysis
- by Sebastien Destercke
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- Expert Systems, Fuzzy set theory, Probability, Decision Trees

In vitro chemical safety testing methods offer the potential for efficient and economical tools to provide relevant assessments of human health risk. To realize this potential, methods are needed to relate in vitro effects to in vivo responses, i.e., in vitro to in vivo extrapolation (IVIVE). Currently available IVIVE approaches need to be refined before they can be utilized for regulatory decision-making. To explore the capabilities and limitations of IVIVE within this context, the U.S. Environmental Protection Agency Office of Research and Development and the National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods co-organized a workshop and webinar series. Here, we integrate content from the webinars and workshop to discuss activities and resources that would promote inclusion of IVIVE in regulatory decision-making. We discuss properties of models that successfully generate predictions of in vivo doses from effective in vitro concent...

- by Xiaoqing Chang
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- Computer Science, Expert Systems, Computational Biology, Medicine

Long non-coding RNAs (lncRNAs) regulate pathological processes, yet their potential roles in papillary thyroid carcinoma (PTC) are poorly understood. To profile transcriptionally dysregulated lncRNAs in PTC and identify lncRNAs associated with clinicopathological characteristics. We performed RNA sequencing of 12 paired PTC tumors and matched noncancerous tissues and correlated the expression of lncRNAs with clinical parameters. The 2 most significantly dysregulated lncRNAs were studied in an Ohio PTC cohort (n=109) and in PTC data (n=497) from TCGA. A combination of laboratory-based studies and computational analysis using clinical data and samples and a publically available database. Correlation between expression values and clinical parameters. We identified 218 lncRNAs showing differential expression in PTC (fold change ≥2.0, p value <0.01). Significant correlation was observed between the expression of two lncRNAs (XLOC_051122 and XLOC_006074) and (i) lymph node metastasis (...

- by Huiling He
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- Expert Systems, Computational Biology, Biology, Medicine

‡ This work was partially suported by ISA/DGOT/JNICT contract 28/94. Abstract: A new classification method which permits the integration of expert knowledge in satellite image classification is presented. This approach differs from other knowledge based ones for the following reasons: 1) it is a low-cost procedure; 2) it allows that the available experts explicitly express all their knowledge on the area to be classified, and 3) it does not have to face the problem of rule generalization over the whole area. The method is applied to a real image data set and it is shown that the achieved classification is more accurate than the classification just based on spectral data.

- by Manuel Campagnolo
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- Mathematics, Expert Systems, Forestry, Image Processing

AI concepts and technologies can assist engineers in safety management by providing new software components to the existing information systems, such as real-time interpretation systems linked to the data acquisition units, qualitative models, and reasoning agents supporting the off-line management of information and interpretation.
In this article, we describe four decision - support systems that use such concepts and technologies to better manage the safety of civil engineering structures. During the last six years, the software development unit of ISMES -an R &D company involved in structural and mechanical engineering, environmental and land -use engineering, and information and communication technologies -has focused on AI applications to structural safety. We have addressed two main problems: the safety management of dams and monuments and the seismic risk assessment of buildings.
This led to the development of the four systems: Mistral, Damsafe, Kaleidos, and Igor.
We exploit AI tools for designing intelligent modules of our support systems, including causal networks of processes, qualitative modeling, model -based reasoning, and hierarchical object-oriented representations.
The systems also employ AI techniques such as rule -based systems, pattern matching, and neural networks, in conjunction with conventional techniques, to implement these representation and reasoning schemes.

- by M. Cedei and +1
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- Artificial Intelligence, Expert Systems, Decision Support Systems, Structural Health Monitoring

This paper presents an application of the steady state network equivalents and expert system for voltage and reactive power (VAR) control in large-scale power systems. A steady state network equivalencing technique is used to construct the "three tier" subsystem which is adequate to solve voltage violation problems. An expert system utilises the sensitivity tree method to select the optimal set of control actions to alleviate the voltage problem. The expert system was developed using the VP-EXPERT system shell. VP-EXPERT interacts with the power system analysis software providing analysis of the network sensitivity matrix and data for the knowledge base. Practical application of the developed expert system is demonstrated on the example of the HydroElectric Commission (HEC) power system of Tasmania, however the proposed approach is not limited by the system size.

- by M. Negnevitsky
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- Engineering, Expert Systems, Power Systems, Optimal Control

The development of individualized educational programs (IEPs) has become a burden for many secondary school systems. The primary objective of the project described in this report was to develop a computer system that would help in the development of IEPs for all 15,000 handicapped and/or disadvantaged students enrolled in Pennsylvania's vocational programs. Collection of tests and their criteria used in IEP development was the method used to obtain data, using a 10% sampling of school districts. The Singer Vocational Evaluative System and the Vocationa Interest Assessment Survey were incorpora,_ed in the program. Information was put in the proper computer syntax, and logic sequence models for data usage were constructed. The instrument was tested using data appropriate for handicapped students enrolled in the programs. The system performs the following operations: (1) locates discrepancies and results of intelligence quotient (IQ) tests; (2) classifies the IQ score; (3) clmpares achievement and IQ standardized results; (4) classifies isolated IQ results into educational terms; and (5) offers some guidelines related to a student's probable ecademic abilities. The following factors may affect the results offerbd by the program: physical limitations of the student; basing decision on aptitude or interest results as isolated test scores; and evaluator errora-these may be eliminated by reviewing test procedures. (Five appendices forming the bulk of the document are: (1) list of professional contacts and organizations; (2) sampling of special needs students' assessment instruments; (3) users' guide-IEP assessment aid; (4) sample computer assessment output; and (5) computer programmed information.) (NLA)

- by Connie Baggett
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- Psychology, Expert Systems, Intelligence quotient, Diagnostic Tests

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- by Benjamin Djulbegovic
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- Expert Systems, Cancer, Decision Support Systems, Interviewing

Expert Systems (ES) is increasing its importance, impacting not only personal life but also professional life and its workplace. With ES's growing impact on tax areas, tasks of tax practitioners will change and progress. In addition to financial, legal and tax knowledge, these workers will need to develop and apply technical and analytical knowledge for the use of ES. This research proposal proposes to study the relationship between the presence of ES in taxation and the skills that the labour market imposes. The aim of this study is not only to identify the skills required for technological work within taxation, but also to build and validate a model that contributes to an improvement in the ability to predict workers' ability to adapt to new work demands.

- by Bráulio Alturas
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- Expert Systems, Taxation, Competencies

Historically, engineers at the National Aeronautics and Space Administration (NASA) had few opportunities or incentives to share their technical expertise across the Agency. Its centerand projectfocused culture often meant that knowledge never left organizational and geographic boundaries. With increasingly complex missions, the closeout of the Shuttle Program, and a new generation entering the workforce, developing a knowledge sharing culture became critical. To address this need, the Office of the Chief Engineer established communities of practice on the NASA Engineering Network. These communities were strategically aligned with NASA’s core competencies in such disciplines as avionics, flight mechanics, life support, propulsion, structures, loads and dynamics, human factors, and guidance, navigation, and control. This paper describes the process used to identify and develop communities, from establishing simple websites that compiled discipline-specific resources to fostering a kn...

- by Cornelius Dennehy
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- Computer Science, Expert Systems, Complex Systems, Organizations

The Spaceport Processing Systems Branch at NASA Kennedy Space Center has developed and deployed an agent based tool to monitor the Space Shuttle's ground processing telemetry stream. The application, the NASA Engineering Shuttle Telemetry Agent, increases situational awareness for system and hardware engineers during ground processing of the Shuttle's subsystems. The agent provides autonomous monitoring of the telemetry stream and automatically alerts system engineers when predefined criteria have been met. Efficiency and safety are improved through increased automation. Sandia National Labs' Java Expert System Shell is employed as the rule engine. The shell's predicate logic lends itself well to capturing the heuristics and specifying the engineering rules of this spaceport domain. The declarative paradigm of the rule-based agent yields a highly modular and scalable design spanning multiple subsystems of the Shuttle. Several hundred monitoring rules have been written thus far with corresponding notifications sent to Shuttle engineers. This paper discusses the rule-based telemetry agent used for Space Shuttle ground processing and explains the problem domain, development of the agent software, benefits of AI technology, and deployment and sustaining engineering of the product.

- by STEPHAN DAVIS
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- Software Engineering, Artificial Intelligence, Expert Systems, Situation awareness

A design and application of adaptive online exam system are carried out in this paper. Adaptive exam systems determine different question sets automatically and interactively for each student and measure their competence on a certain area of discipline instead of comparing their gains with each other. Through an adaptive exam technique, a student's distraction and motivation loss that is led by the questions with quite lower hardness level than his/her competency is prevented. In addition, negative effects of questions requiring higher knowledge than his/her competency over a student's self confidence and morale are dismissed. Since questions are specialized so that they can allow making clear deductions about student gains, they are able to detect student competencies more effectively. Requiring less total time for measuring and being more flexible in the exam management are among the advantages provided by the system. Self sufficiency of the system in terms of planning, repeating and assessment of the measurement process especially allows itself to be used in the individual education sets. Through this system, student competencies can be determined more effectively in cases such as distant-learning, in which some challenges are experienced frequently.

- by menderes ünal
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- Expert Systems

Leishmaniasis is neglected tropical a protozoan infectious disease caused by Leishmania parasites. VL (also known as Kala-Azar) is the most severechronicform of Leishmaniasis, almost always fatal if untreated. The annual burden of VL in Ethiopia is estimated to be between 4,500 and 5,000 cases. In a medical environment, incomplete information and imprecise are driven to making an incorrect medical decision and maximize the rate of morbidity and mortality. Fuzzy logic technology enables to provide a simple way to attain to a certain conclusion from vague, imprecise and ambiguous medical data. Clinical suspicion of VL is complex because of its clinical manifestation are shared by other commonly occurring tropical disease like malaria, typhoid and tuberculosis.Several studies were conducted on VL, nevertheless, no one addresses the VL diagnosis using learning capacity. This thesis, we developed and investigated the application of an intelligent interval Type-2 Fuzzy Logic Expert System for diagnosis Visceral Leishmaniasis (VLDES) to assist health workers easy diagnosis a patient and decision-makers to prevent the expansion epidemic. The Type-2 Fuzzy Logic System would be clear to present a highly interpretable and transparent model that is very suitable for the handling uncertainties in the input factors and converting the accumulated data to linguistic formats. First we acquired well organized domain expert knowledge via interview questions and relevant document from the university of Gondar Kala-Azar Treatment and Research center. Secondly, we defined the parameters of fuzzy membership functions of Type-1 Fuzzy Logic System mentioned based on domain knowledge with intensive discussion. Finally, we employed to define uncertainty of the Footprint of Uncertainty (FOU) percentage of Interval Type-2 Fuzzy Logic System. We obtained 93.33% classification accuracy, 90%+ sensitivity and 96%+ specificity usingthirty patients (5 mild,5 moderate, 10 sever and 10 very sever VL patients)as testing case. This show that the proposed Interval Type-2 Fuzzy Logic Classification System provides a more interpretable model that Diagnosis VL.

- by Yosef Berhanu
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- Expert Systems, Image Processing

Some problems of governance regularly resurface, and the use and role of ‘quangos’— public bodies operating at arm’s-length to ministers—is a case in point. The administrative history of the British state is littered with official reviews and political debates about quangos. Historically, governments, whatever their reforming zeal, have found it difficult to make substantial changes. Now the UK government has initiated a rapid and large-scale set of reforms. This article analyses these changes and highlights five challenges for governments wishing to reform arm’s-length bodies: mapping, assessing, reconfiguring, saving, and accounting.

- by Matthew Flinders
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- Expert Systems, Public Administration, Delegation, Democracy and Good Governance
- by Jürgen Dorn
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- Cognitive Science, Expert Systems, Production, Automatic Control

Mapping the cover of invasive species using remotely sensed data alone is challenging, because many invaders occur as mid-level canopy species or as subtle understorey species and therefore contribute little to the spectral signatures captured by passive remote sensing devices. In this study, two common non-parametric classifiers namely, the neural network and support vector machine were used to map four cover classes of the invasive shrub Lantana camara in a protected game reserve and the adjacent area under communal land management in Zimbabwe. These classifiers were each combined with a geographic information system (GIS) expert system, in order to test whether the new hybrid classifiers yielded significantly more accurate invasive species cover maps than the single classifiers. The neural network, when used on its own, mapped the cover of L. camara with an overall accuracy of 71% and a Kappa index of agreement of 0.61. When the neural network was combined with an expert system, the overall accuracy and Kappa index of agreement significantly increased to 83% and 0.77, respectively. Similarly, the support vector machine achieved an overall accuracy of 64% with a Kappa index of agreement of 0.52, whereas the hybrid support vector machine and expert system classifier achieved a significantly higher overall accuracy of 76% and a Kappa index of agreement of 0.67. These results suggest that integrating conventional image classifiers with an expert system increases the accuracy of invasive species mapping.

- by Mhosisi Masocha
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- Expert Systems, Remote Sensing, Image Analysis, Neural Networks

This paper presents a survey of voltage/Var control techniques. It introduces both the control devices for individual reactive power sources and several popular control systems (OPRF, hierarchical voltage control, expert system and fuzzy... more

- by Sandhya Samarasinghe
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- Expert Systems, Fuzzy Logic

In plant factory, optimal control, expert systems, and robotics applications for obtaining higher yield and better quality of plant is essential. Sunagoke moss is one of the plant products which are produced by plant factory. The objectives of this research are developing an intelligent irrigation system, line tracer robot transporter, and precision artificial lighting system in a cultured moss mat production factory. In the intelligent irrigation system, machine vision device is used as non-destructive sensing to detect water stress in cultured moss mat. A miniature of line tracer robot transporter has been developed to simulate the transport process of moss mat in plant factory. A combination of machine vision and scanning type laser diodes lighting system is used to control the light condition. The intelligent irrigation system using artificial neural network is able to predict the deficit water content of moss accurately and fulfil the water needs in moss mat precisely. The line tracer robot transporter has been tested successfully to describe the relationship between the load variations and the transport speed and energy. The precision artificial lighting system can recognize the moss mat area which lack of light and provide accurate light in each moss mat area according to their needs. Overall, the proposed control systems in this study are acceptable to develop automated precision plant factory.

- by Yusuf Hendrawan
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- Expert Systems, Remote Sensing, Precision Agriculture, Neural Networks
- by William Swartout
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- Expert Systems, Explanation
- by Sonny Nwankwo
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- Expert Systems, Quality Management, Knowledge Based System, Competitive advantage

Publtc reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing Instructions, searching eKisting data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to

- by Michael Hamman
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- Engineering, Computer Architecture, Expert Systems, Philosophy

This paper presents the current state-of-the-art of residual generation techniques adopted in instrument fault detection and isolation. Both traditional and innovative methods are described with their advantages and their limits. The improvement of analytical redundancy technique performances for better dealing with high-dynamics systems and/or with online applications is pointed out as the most interesting need to focus the research efforts.

- by G. Betta
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- Computer Science, Expert Systems, Fault Detection, Automatic Control

The identi®cation of an expert is vital to any study or application involving expertise. If external criterion (a``gold standard'') exists, then identi®cation is straightforward: Simply compare people against the standard and select whoever is closest. However, such criteria are seldom available for domains where experts work; that's why experts are needed in the ®rst place. The purpose here is to explore various methods for identifying experts in the absence of a gold standard. One particularly promising approach (labeled CWS for Cochran±Weiss±Shanteau) is explored in detail. We illustrate CWS through reanalyses of three previous studies of experts. In each case, CWS provided new insights into identifying experts. When applied to auditors, CWS correctly detected group dierences in expertise. For agricultural judges, CWS revealed subtle distinctions between subspecialties of experts. In personnel selection, CWS showed that irrelevant attributes were more informative than relevant attributes. We believe CWS provides a valuable tool for identi®cation and evaluation of experts. Ó

- by James Shanteau and +1
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- Management, Psychology, Expert Systems, Auditing
- by Ron Good
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- Cognitive Psychology, Artificial Intelligence, Expert Systems, Science Education

The paper presents a conception of the Semantic Web Expert System which is the logical continuation of the expert system development. The Semantic Web Expert System emerges as the result of evolution of expert system concept and it means expert system moving toward the Web and using new Semantic Web technologies. The proposed conception of the Semantic Web Expert System promises to have new useful features that distinguish it from other types of expert systems.

- by Olegs Verhodubs and +1
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- Expert Systems, Semantic Web Technologies, Semantic Web

The development and application of the Spacecraft Health Automated Reasoning Prototype (SHARP) for the operations of the telecommunications systems and link analysis functions in Voyager mission operations are presented. An overview is... more

- by David Atkinson
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- Artificial Intelligence, Expert Systems, Spacecraft Operations, Forecasting
- by Ben Djulbegovic
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- Expert Systems, Cancer, Decision Support Systems, Interviewing

This is an introduction to the forthcoming special issue, "Artificial Intelligence and its Discontents."

- by Shunryu Garvey
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- History of Science and Technology, Sociology, Psychology, Computer Science

Abstract: Highway engineers face complicated problems that are influenced by various conditions during the construction of flexible highway pavements. Identifying such problems and recommending effective solutions demand considerable engineering expertise, which is difficult to obtain at all construction sites. Thus, the development of an expert system can effectively help engineers control and analyze such problems. In addition, an expert system can effectively archive the storage and distribution of expertise among pavement ...

The idea is to conceive an intelligent computing system of decision-making aid, in this context of teaching training, the quantification of the human behaviors is the key to this system's innovation. Seeing that it gives opportunity of measuring the professional acts of the teachers in class. This makes it possible to locate these practices compared to the pedagogical theories, into force and especially compared to the constructive approach. In addition, this system helps to identify the student's styles of learning; therefore it places, at the disposal, information which facilitates to the teachers the adaptation of their pedagogical methods so that the student benefit a maximum assimilation. For what concerns them, the students also profit from an innovating alternative: result of the web based performances analysis in summative evaluation. It is a generated report, for each pupil, automatically at the end of the seizure of the marks stipulating in details their weak points and specifying the adequate remedies in terms of activities to be realized to proceed to reflexive regulations in order to raise their levels of assimilation. An able system, starting from observable behaviors in classrooms and of performances seized remotely via the Web, to quantify in a rational way the cognitive and emotional states of the actors of the context of teaching training. An expert system whose general objectives would be: classifying the profiles of the teachers starting from their professional competences based on their pedagogy, behavior and attitude, classifying the learners' profiles by analyzing their interactions and analyzing their performances in summative evaluations, adapting the resources of the teacher's pedagogical methods in order to have a better coherence with the profiles of identities, the profiles of motivation and the profiles of comprehension of learner.

- by mohamed fethi
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- Expert Systems, Statistics, Cognition, Evaluation

Smart Home Energy Management is a very hot topic for the scientific community and some interesting solutions have also recently appeared on the market. One key issue is represented by the capability of planning the usage of energy resources in order to reduce the overall energy costs. This means that, considering the dynamic electricity price and the availability of adequately sized storage system, the expert system is supposed to automatically decide the more convenient policy for energy management from and towards the grid. In this work a comparison among different linear and nonlinear methods for home energy resource scheduling is proposed, considering the presence of data uncertainty into account. Indeed, whereas the employment of advanced optimization frameworks can take advantage by their inherent offline approach, the need to forecast the energy price and the amount of self-generated power. A residential scenario, in which a system storage and renewable resources are available and exploitable to match the user load demand, has been considered for performed computer simulations: obtained results show how the offline approaches provide good performance also in presence of uncertain data.

- by Stefano Squartini
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- Expert Systems, Linear Programming, Particle Swarm Optimization, Optimization

A planetary trains for multi-speed is mainly used for automation in industries of automobile. A planetary
gear train is represented by a graph. It is identified by (i) number of vertices and their connectivity (ii) number of edges and their types and values (iii) fundamental circuits, their size and adjancy. Connectivity of individual link is a property characteristic of kinematic chain. It is possible to identify a planetary gear,therefore of using sets of labele (decimal numbers representing connectivity ) of individual link. The
connectivity of vertices , edges values and circuit values, related to design invariants which in turn indicates the possible behavior of the gear train ( for example capacity of power transmission, speed ratio and power carculation). For a specified degree – of – freedom a number of planetary gear kinematic chain (PGKCs) are selected and hence planetary gear trains (PGTs) can be formed with a given number of links
and joints so that designer must be able to select to select the best train from the view point of say velocity ratio and capacity of power transmission, space requirements etc. Synthesis of planetary gear kinematic chain and planetary gear trains has been studied(1-9). Almost all reported work deals with only
identification of distinct chains. Besides providing an atlus of chains, this in itself does not provide any help to designer in the selection of best possible gear train. In the present paper a simple method based of circuit property ( based on link-link shortest path distance and degree of links) is presented to determine the topology values of power transmission efficiency and topology power transmission capacity of five-links PGKCs and their distinct inversions