494 research outputs found

    An Integrated Solution for Pavement Management and Monitoring Systems

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    AbstractThe aim of this paper is to present a holistic platform for pavement monitoring and maintenance management (PMMP). Our solution tries to exploit new technologies in order to design, integrate and implement an automated and portable visual road inspection system for traffic-speed pavement distress monitoring and analysis that can be installed on non-specialized vehicles. PAV3M developed based on solution based on PMMS requirements and recommendation made in EU programs as a modular decomposition based on business process analysis. For road monitoring and maintenance we opted for LCCA methods. Our solution includes Risk management module

    ARC-TEC : acquisition, representation and compilation of technical knowledge

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    A global description of an expert system shell for the domain of mechanical engineering is presented. The ARC-TEC project constitutes an AI approach to realize the CIM idea. Along with conceptual solutions, it provides a continuous sequence of software tools for the acquisition, representation and compilation of technical knowledge. The shell combines the KADS knowledge-acquisition methodology, the KL-ONE representation theory and the WAM compilation technology. For its evaluation a prototypical expert system for production planning is developed. A central part of the system is a knowledge base formalizing the relevant aspects of common sense in mechanical engineering. Thus, ARC-TEC is less general than the CYC project but broader than specific expert systems for planning or diagnosis

    Control Patterns - Bridging The Gap Between Is Controls And BPM

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

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    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

    Definition of avionics concepts for a heavy lift cargo vehicle, volume 2

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    A cost effective, multiuser simulation, test, and demonstration facility to support the development of avionics systems for future space vehicles is defined. The technology needs and requirements of future Heavy Lift Cargo Vehicles (HLCVs) are analyzed and serve as the basis for sizing of the avionics facility although the lab is not limited in use to support of HLCVs. Volume 2 is the technical volume and provides the results of the vehicle avionics trade studies, the avionics lab objectives, the lab's functional requirements and design, physical facility considerations, and a summary cost estimate

    Adaptive scheduling for adaptive sampling in pos taggers construction

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    We introduce an adaptive scheduling for adaptive sampling as a novel way of machine learning in the construction of part-of-speech taggers. The goal is to speed up the training on large data sets, without significant loss of performance with regard to an optimal configuration. In contrast to previous methods using a random, fixed or regularly rising spacing between the instances, ours analyzes the shape of the learning curve geometrically in conjunction with a functional model to increase or decrease it at any time. The algorithm proves to be formally correct regarding our working hypotheses. Namely, given a case, the following one is the nearest ensuring a net gain of learning ability from the former, it being possible to modulate the level of requirement for this condition. We also improve the robustness of sampling by paying greater attention to those regions of the training data base subject to a temporary inflation in performance, thus preventing the learning from stopping prematurely. The proposal has been evaluated on the basis of its reliability to identify the convergence of models, corroborating our expectations. While a concrete halting condition is used for testing, users can choose any condition whatsoever to suit their own specific needs.Agencia Estatal de Investigación | Ref. TIN2017-85160-C2-1-RAgencia Estatal de Investigación | Ref. TIN2017-85160-C2-2-RXunta de Galicia | Ref. ED431C 2018/50Xunta de Galicia | Ref. ED431D 2017/1

    Classification of Schedule Management Barriers Through Concept Mapping

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    Barriers to adoption of schedule management processes are a matter of serious concern to the acquisition community. Schedule management has been widely accepted to contribute to the successful execution of complicated system development processes since the 1950s. However, studies of recent acquisition failures illustrate that over the last 15 years, there has been significant internal resistance to the adoption of schedule management processes. This exploratory effort used concept mapping to identify and classify the types of barriers existing in the Aeronautical Systems Center (ASC). A series of open-ended questions were posed to four experienced program managers in ASC. Units of Analysis were extracted from the survey responses, and grouped and sorted by a representative set of proxy sorters. Multidimensional scaling was applied to the sorted groups to identify affinity of the responses, and cluster analysis was employed to identify emerging themes from the program manager responses. The results indicated 10 barrier groups, which can be mapped using two conceptual axes (internal-external, and tactical-strategic). As a result of this analysis, a series of focused recommendations are provided to the ASC Acquisition Center of Excellence to improve acceptance and adoption of schedule management practices

    Knowledge-based systems for knowledge management in enterprises : Workshop held at the 21st Annual German Conference on AI (KI-97)

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