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On the fusion and transference of knowledge. I

On the fusion and transference of knowledge. I

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IEEE International conference on Information Reuse and Integration (IRI)

作者： S.H. Rubin SPAWAR Systems Center San Diego CA USA

Contemporary neural architectures having one or more hidden layers suffer from the same deficiencies that genetic algorithms and methodologies for non-trivial automatic programming do; namely, they cannot exploit inherent domain symmetries for the transference of knowledge from an application of lesser to greater rank, or across similar applications. As a direct consequence, no ensemble of contemporary neural architectures allows for the effective codification and transference of knowledge within a society of individuals (i.e., swarm knowledge). These deficiencies stem from the fact that contemporary neural architectures cannot reason symbolically using heuristic ontologies. They cannot directly provide symbolic explanations of what was learned for purposes of inspection and verification. Moreover, they do not allow the knowledge engineer to precondition the internal feature space through the application of domain-specific modeling languages. A symbolic representation can support the heuristic evolution of an ensemble of neural architectures. Each neural network in the ensemble imbues a hidden layer and for this reason is NP-hard in its learning performance. It may be argued that the internal use of a neat representation subsumes the heuristic evolution of a scruffy one. It follows that there is a duality of representation under transformation. The goal of AI then is to find symbolic representations, transformations, and associated heuristic ontologies. This paper provides an introduction to this quest. Consider the game of chess for example. If a neural network or symbolic heuristic is used to evaluate board positions, then the best found iterate (i.e., of weights or symbols) serves as a starting point for iterative refinement. This paper addresses the ordering and similarity of the training instances in refining subsequent iterates. If we fix the learning technology, then we need to focus on reducing the problem, composing intermediate results, and transferring th

关键词： Neural networks Ontologies Genetic algorithms Automatic programming Inspection Knowledge engineering Machine learning sensor phenomena and characterization USA Councils Domain specific languages

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Multi-sensor fusion for airport surface movement area surveillance and safety

Multi-sensor fusion for airport surface movement area survei...

引用

conference on sensor fusion - architectures, algorithms, and applications VI

作者： Pendergast, SL CACI Technol Inc San Diego CA 92108 USA

ISBN: (纸本)0819444812

In this paper we describe the nature of the problem of surveillance of airport surface movement. We describe the characteristics, performance, and unique problems of various airport sensors available, and the need to develop a fusion system to provide an integrated surveillance picture. Parallel sensor fusion developments are described in terms of their applicability to the sensor fusion task in surface surveillance. Paradigms for sensor fusion, including alternative architectures, algorithms, and performance metrics will be described. Finally we describe system implementation and quantitative performance of sensor fusion applied to the surface surveillance problem at demonstrations in Atlanta Hartsfield International Airport (1998, ATL), Dallas Fort Worth International Airport (1999, 2000, DFW), and in-process and planned future developments in sensor fusion.

关键词： airport surveillance runway incursion safety ATIDS RIPS RIRP ASDE AMASS

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sensor data fusion with support vector machine techniques

Sensor data fusion with support vector machine techniques

引用

conference on sensor fusion - architectures, algorithms, and applications VI

作者： Braun, JJ MIT Lincoln Lab Lexington MA 02420 USA

ISBN: (纸本)0819444812

This paper presents an approach to multisensor data fusion based on the use of Support Vector Machines (SVM). The approach is investigated using simulated generic sensor data, representative of data imperfections that may be encountered in multisensor fusion applications. In particular the issue of data incompleteness is addressed and a method exploiting vicinity of training points is proposed for incompleteness correction. The paper also investigates applicability of vicinal kernels in SVM-based sensor data fusion.

关键词： multisensor data fusion Support Vector Machines data incompleteness machine learning recognition

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Multi-level enhanced target identification fusion method

Multi-level enhanced target identification fusion method

引用

conference on sensor fusion - architectures, algorithms, and applications VI

作者： Ku, JK Ock, SY LG Innotek Co. Ltd. (South Korea)

ISBN: (纸本)0819444812

Data fusion architecture can be categorized into data-level fusion, feature-level fusion and decision-level fusion by its characteristics. In this paper, we provide a new target identification fusion technology in which we adopt not only feature-level fusion approach but also decision-level fusion approach in order to consider even sensors' uncertain reports and improve fusion performance. In feature-level fusion stage, we applied fuzzy set theory and Bayesian theory based on the sensor data, such as sensor parameter and detected target information. In decision-level fusion stage, we applied advanced Bayesian theory to decide final target identification. Experimental results with various kinds of sensor data have verified the robustness of our algorithms comparing with conventional feature-level, decision-level fusion algorithms.

关键词： multi-level data fusion fuzzy set theory Bayesian method target identification

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Syntax and semantics in knowledge fusion:: a mixed approach

Syntax and semantics in knowledge fusion:: a mixed approach

引用

conference on sensor fusion - architectures, algorithms, and applications VI

作者： Grégoire, É Univ Artois CRIL F-62307 Lens France

ISBN: (纸本)0819444812

In this paper, a series of knowledge fusion operators are motivated and analyzed. They are defined in a semantic way, although syntactical facets of knowledge are taken into account. More precisely, they rely on a rank-ordering of interpretations that is based on the number of formulas that the interpretations falsify. It is briefly discussed how these operators could be refined, by taking into account various distribution policies of the falsified information among the knowledge sources, syntactical properties of formulas to be fused and forms of integrity constraints preference among literals.

关键词： knowledge fusion knowledge representation

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The principle for synthesizing measurements of multiple system parameters into a single parameter

The principle for synthesizing measurements of multiple syst...

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conference on sensor fusion - architectures, algorithms, and applications VI

作者： Pu, QG Univ Sci & Technol Suzhou Ctr Comp Suzhou 215011 Jiangsu Peoples R China

ISBN: (纸本)0819444812

Modern technology provides a great amount of information. In computer monitoring systems or computer control systems, especially real-time expert systems, in order to have the situation in hand, we need one or two parameters to express the quality and/or security of the whole system. This paper presents a principle for synthesizing measurements of multiple system parameters into a single parameter. This principle has been successfully applied in the monitoring of an ultra-energy efficient house in Canada and other applications.

关键词： sensor fusion parameter synthesis computer monitoring systems computer control systems real -time expert systems

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Multisensor statistical interval estimation fusion

Multisensor statistical interval estimation fusion

引用

conference on sensor fusion - architectures, algorithms, and applications VI

作者： Zhu, YM Gan, Y Li, XR Sichuan Univ Dept Math Chengdu 610064 Sichuan Peoples R China

ISBN: (纸本)0819444812

This paper deals with multisensor statistical interval interval estimation fusion, that is, data fusion from multiple statistical interval estimators for the purpose of estimation of a parameter theta. A multisensor convex linear statistic fusion model for optimal interval estimation fusion is established. A Gaussian-Seidel iteration algorithm for searching for the fusion weights is proposed. In particular, we suggest convex combination minimum variance fusion that reduces huge computation of fusion weights and yields near optimal estimate performance generally, and moreover, may achieve exactly optimal performance for some specific distributions of obsevation data. Numerical examples are provided and give additional support to the above results.

关键词： interval estimation coverage probability convex linear fusion least mean square

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sensor fusion: architectures, algorithms, and applications VI

Sensor fusion: Architectures, algorithms, and applications V...

引用

sensor fusion: architectures, algorithms, and applications VI

The proceedings contains 31 papers from the conference on sensor fusion: architectures, algorithms, and applications VI. Topics discussed include: adaptive sequential Bayesian classification using Page's test;ontology-based multiagent approach to data fusion;unified approach to the fusion of imperfect data;fusion approach to stereo vision uncertainity;robust fusion with reliabilities weights;distributed air-to-ground targeting;and fuser design for thick film pH sensor electrodes using emperical data.

关键词： sensor data fusion

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Active perception in a sensor fusion model

Active perception in a sensor fusion model

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conference on sensor fusion - architectures, algorithms, and applications VI

作者： Biel, L Wide, P Univ Orebro Ctr Appl Autonomous Sensor Syst Orebro Sweden

ISBN: (纸本)0819444812

During the last decades the research in the sensor fusion area has mainly been focused on fusion methods and feature selection methods. A possible further development in this area is to incorporate a process referred to as active perception. This means that the system is able to manipulate the sensing mechanisms to create a focus on selected information in the surrounding environment. This process may also be able to handle the feature selection process with respect to which features to be used and/or the number of features to use. This paper presents a model that contains a decision system based on active perception integrated with previous sensor fusion algorithms. The human body has perhaps one of the most advanced perceptual processing systems. The human perception process can be divided into sensation (measurement collection) and perception (interpret the surroundings). During the sensation process a huge amount of data is collected from different sensors that reflect the environment. The information has to be interpreted in an effective way, i.e. in the fusion process. The interpretation together with a decision system to control the sensors to focus on important information will correspond to the (active) perception process. The model presented in this paper capitalizes on the properties presented by the biological counterpart to achieve more human-like processes for a sensor fusion. Finally, the paper presents the testing of the model in two examples. The applications used have a safety approach of fire indication, identification and decision-making. The goal is to enlarge a conventional fire alarm system to not only detect fire, but also to propose different actions for a human in a dangerous area for example.

关键词： sensors sensor fusion Data fusion Fuzzy systems Carbon monoxide Oxygen Systems modeling Environmental sensing Control systems Signal processing

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Multiple sources distributed information fusion based on multi-agent system

Multiple sources distributed information fusion based on mul...

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conference on sensor fusion - architectures, algorithms, and applications VI

作者： Xia, ZX E China Shipbldg Inst Dept Comp Sci Zhenjiang 212003 Peoples R China

ISBN: (纸本)0819444812

In a multi-node distributed decision system under some conditions there are few or none permitted information exchange between the nodes, this makes the information fusion and final decision difficult. However if we treat this distributed system as a multi-agent system, and each node acts as an agent, it has some other node's historical experiences or knowledge for resolving problems and stored in additional case bases, so it can uses case based reasoning (CBR) and transposition reasoning to obtain the possible viewpoints or decisions of other nodes and then makes information fusion by itself This approach may reduce the subjectivism which is the weakness of pure transposition reasoning.

关键词： distributed decision system multi-agent case based reasoning transposition reasoning

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