10,371 research outputs found

    An information fusion framework for context-based accidents prevention

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    The oil and gas industry is increasingly concerned with achieving and demonstrating good performance with regard occupational health and safety (OHS) issues, through the control of its OHS risks, which is consistent with its core policy and objectives. There are standards to identify and record workplace accidents and incidents to provide guiding means on prevention efforts, indicating specific failures or reference, means of correction of conditions or circumstances that culminated in an accident. Therefore, events recognition is central to OHS, since the system can selectively start proper prediction services according to the user current situation and past knowledge taken from huge databases. In this sense, a fusion framework that combines data from multiples sources to achieve more specific inferences is needed. In this paper we propose a machine learning algorithm to learn from past anomalous events related to accident events in time and space. It also uses additional knowledge, like the contextual knowledge: user profile, event location and time, etc. Our proposed model provides the big picture about risk analysis for that employee at that place in that moment in a real world environment. Our main contribution lies in building a causality model for accident investigation by means of well-defined spatiotemporal constraints in the offshore oil industry domain.This work was partially funded by CNPq BJT Project 407851/2012–7 and CNPq PVE Project 314017/2013–5

    Continuous Improvement Through Knowledge-Guided Analysis in Experience Feedback

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    Continuous improvement in industrial processes is increasingly a key element of competitiveness for industrial systems. The management of experience feedback in this framework is designed to build, analyze and facilitate the knowledge sharing among problem solving practitioners of an organization in order to improve processes and products achievement. During Problem Solving Processes, the intellectual investment of experts is often considerable and the opportunities for expert knowledge exploitation are numerous: decision making, problem solving under uncertainty, and expert configuration. In this paper, our contribution relates to the structuring of a cognitive experience feedback framework, which allows a flexible exploitation of expert knowledge during Problem Solving Processes and a reuse such collected experience. To that purpose, the proposed approach uses the general principles of root cause analysis for identifying the root causes of problems or events, the conceptual graphs formalism for the semantic conceptualization of the domain vocabulary and the Transferable Belief Model for the fusion of information from different sources. The underlying formal reasoning mechanisms (logic-based semantics) in conceptual graphs enable intelligent information retrieval for the effective exploitation of lessons learned from past projects. An example will illustrate the application of the proposed approach of experience feedback processes formalization in the transport industry sector

    Knowledge-based information fusion for improved situational awareness

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    Heterogeneous substitution systems revisited

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    Matthes and Uustalu (TCS 327(1-2):155-174, 2004) presented a categorical description of substitution systems capable of capturing syntax involving binding which is independent of whether the syntax is made up from least or greatest fixed points. We extend this work in two directions: we continue the analysis by creating more categorical structure, in particular by organizing substitution systems into a category and studying its properties, and we develop the proofs of the results of the cited paper and our new ones in UniMath, a recent library of univalent mathematics formalized in the Coq theorem prover.Comment: 24 page

    Multisensor Data Fusion Implementation for a Sensor Based Fertilizer Application System

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    "Mapping systems" (“mapping approach”), real-time sensor-actuator systems ("sensor approach") or the combination of both (“Real-time approach with map overlay”) determine the process control in mobile application systems for spatially variable fertilization. Within the integrated research project “Information Systems Precision Farming Duernast” (IKB Duernast) the implementation of the “Real-time approach with map overlay” was done for intensive nitrogen fertilization. The bottom line of this sophisticated approach is a comprehensive situation assessment, a typical multisensor data fusion task. Based on a functional and procedural modelling of the multisensor data fusion and decision making process, it could be pointed out that an expert system is an adequate fusion paradigm and algorithm. Therefore, a software simulation with an expert system as core element was implemented to fuse on-line sensor technology measurements (REIP), maps (yield, EM38, environmental constraints, draft force) and user inputs in order to derive an application set point in real-time. The development of an expert system can be viewed as a structured transformation in five levels from the “specification level”, the “task level”, the “problem solving level” and the “knowledge base level” to the “tool level”. In the “tool level” the hybrid expert system shell JESS (Java Expert System Shell) was selected for implementation due to the results of preceding levels. Knowledge acquisition was done within another IKB-subproject by the means of data mining. Typical and maximal times of 10 ms and 60 ms for one fusion cycle were measured running this application on a 32-bit processor hardware (Intel Pentium III Mobile, 1 GHz)

    Genuine Process Logic

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    The Genuine Process Logic described here (abbreviation: GPL) places the object-bound process itself at the center of formalism. It should be suitable for everyday use, i.e. it is not primarily intended for the formalization of computer programs, but instead, as a counter-conception to the classical state logics. The new and central operator of the GPL is an action symbol replacing the classical state symbols, e.g. of equivalence or identity. The complete renunciation of object-language state expressions also results in a completely new metalinguistic framework, both regarding the axioms and the expressive possibilities of this system. A mixture with state logical terms is readily possible
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