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Title: A New Concept of Modular Parallel Mechanism for Machining Applications |
Abstract: The subject of this paper is the design of a new concept of modular parallel mechanisms for three, four or five-axis machining applications. Most parallel mechanisms are designed for three- or six-axis machining applications. In the last case, the position and the orientation of the tool are coupled and the s... |
Title: A Workspace based Classification of 3R Orthogonal Manipulators |
Abstract: A classification of a family of 3-revolute (3R) positioning manipulators is established. This classification is based on the topology of their workspace. The workspace is characterized in a half-cross section by the singular curves of the manipulator. The workspace topology is defined by the number of cusps a... |
Title: Singularity Surfaces and Maximal Singularity-Free Boxes in the Joint Space of Planar 3-RPR Parallel Manipulators |
Abstract: In this paper, a method to compute joint space singularity surfaces of 3-RPR planar parallel manipulators is first presented. Then, a procedure to determine maximal joint space singularity-free boxes is introduced. Numerical examples are given in order to illustrate graphically the results. This study is of h... |
Title: Kinematics analysis of the parallel module of the VERNE machine |
Abstract: The paper derives the inverse and forward kinematic equations of a spatial three-degree-of-freedom parallel mechanism, which is the parallel module of a hybrid serial-parallel 5-axis machine tool. This parallel mechanism consists of a moving platform that is connected to a fixed base by three non-identical le... |
Title: An Algorithm for Computing Cusp Points in the Joint Space of 3-RPR Parallel Manipulators |
Abstract: This paper presents an algorithm for detecting and computing the cusp points in the joint space of 3-RPR planar parallel manipulators. In manipulator kinematics, cusp points are special points, which appear on the singular curves of the manipulators. The nonsingular change of assembly mode of 3-RPR parallel m... |
Title: HMM Speaker Identification Using Linear and Non-linear Merging Techniques |
Abstract: Speaker identification is a powerful, non-invasive and in-expensive biometric technique. The recognition accuracy, however, deteriorates when noise levels affect a specific band of frequency. In this paper, we present a sub-band based speaker identification that intends to improve the live testing performance... |
Title: Application of Girsanov Theorem to Particle Filtering of Discretely Observed Continuous-Time Non-Linear Systems |
Abstract: This article considers the application of particle filtering to continuous-discrete optimal filtering problems, where the system model is a stochastic differential equation, and noisy measurements of the system are obtained at discrete instances of time. It is shown how the Girsanov theorem can be used for ev... |
Title: Determining full conditional independence by low-order conditioning |
Abstract: A concentration graph associated with a random vector is an undirected graph where each vertex corresponds to one random variable in the vector. The absence of an edge between any pair of vertices (or variables) is equivalent to full conditional independence between these two variables given all the other var... |
Title: Non-Computability of Consciousness |
Abstract: With the great success in simulating many intelligent behaviors using computing devices, there has been an ongoing debate whether all conscious activities are computational processes. In this paper, the answer to this question is shown to be no. A certain phenomenon of consciousness is demonstrated to be full... |
Title: Using artificial intelligence for data reduction in mechanical engineering |
Abstract: In this paper artificial neural networks and support vector machines are used to reduce the amount of vibration data that is required to estimate the Time Domain Average of a gear vibration signal. Two models for estimating the time domain average of a gear vibration signal are proposed. The models are tested... |
Title: Evolutionary Optimisation Methods for Template Based Image Registration |
Abstract: This paper investigates the use of evolutionary optimisation techniques to register a template with a scene image. An error function is created to measure the correspondence of the template to the image. The problem presented here is to optimise the horizontal, vertical and scaling parameters that register th... |
Title: A first-order Temporal Logic for Actions |
Abstract: We present a multi-modal action logic with first-order modalities, which contain terms which can be unified with the terms inside the subsequent formulas and which can be quantified. This makes it possible to handle simultaneously time and states. We discuss applications of this language to action theory wher... |
Title: Multi-Dimensional Recurrent Neural Networks |
Abstract: Recurrent neural networks (RNNs) have proved effective at one dimensional sequence learning tasks, such as speech and online handwriting recognition. Some of the properties that make RNNs suitable for such tasks, for example robustness to input warping, and the ability to access contextual information, are al... |
Title: Bagging multiple comparisons from microarray data |
Abstract: The problem of large-scale simultaneous hypothesis testing is re-visited. Bagging and subagging procedures are put forth with the purpose of improving the discovery power of the tests. The procedures are implemented in both simulated and real data. It is shown that bagging and subagging significantly improve ... |
Title: Response Prediction of Structural System Subject to Earthquake Motions using Artificial Neural Network |
Abstract: This paper uses Artificial Neural Network (ANN) models to compute response of structural system subject to Indian earthquakes at Chamoli and Uttarkashi ground motion data. The system is first trained for a single real earthquake data. The trained ANN architecture is then used to simulate earthquakes with vari... |
Title: Fault Classification using Pseudomodal Energies and Neuro-fuzzy modelling |
Abstract: This paper presents a fault classification method which makes use of a Takagi-Sugeno neuro-fuzzy model and Pseudomodal energies calculated from the vibration signals of cylindrical shells. The calculation of Pseudomodal Energies, for the purposes of condition monitoring, has previously been found to be an acc... |
Title: Variance reduction for particle filters of systems with time-scale separation |
Abstract: We present a particle filter construction for a system that exhibits time-scale separation. The separation of time-scales allows two simplifications that we exploit: i) The use of the averaging principle for the dimensional reduction of the system needed to solve for each particle and ii) the factorization of... |
Title: Fuzzy and Multilayer Perceptron for Evaluation of HV Bushings |
Abstract: The work proposes the application of fuzzy set theory (FST) to diagnose the condition of high voltage bushings. The diagnosis uses dissolved gas analysis (DGA) data from bushings based on IEC60599 and IEEE C57-104 criteria for oil impregnated paper (OIP) bushings. FST and neural networks are compared in terms... |
Title: A Study in a Hybrid Centralised-Swarm Agent Community |
Abstract: This paper describes a systems architecture for a hybrid Centralised/Swarm based multi-agent system. The issue of local goal assignment for agents is investigated through the use of a global agent which teaches the agents responses to given situations. We implement a test problem in the form of a Pursuit game... |
Title: On-Line Condition Monitoring using Computational Intelligence |
Abstract: This paper presents bushing condition monitoring frameworks that use multi-layer perceptrons (MLP), radial basis functions (RBF) and support vector machines (SVM) classifiers. The first level of the framework determines if the bushing is faulty or not while the second level determines the type of fault. The d... |
Title: Statistical Mechanics of Nonlinear On-line Learning for Ensemble Teachers |
Abstract: We analyze the generalization performance of a student in a model composed of nonlinear perceptrons: a true teacher, ensemble teachers, and the student. We calculate the generalization error of the student analytically or numerically using statistical mechanics in the framework of on-line learning. We treat t... |
Title: Lasso type classifiers with a reject option |
Abstract: We consider the problem of binary classification where one can, for a particular cost, choose not to classify an observation. We present a simple proof for the oracle inequality for the excess risk of structural risk minimizers using a lasso type penalty. |
Title: Using Genetic Algorithms to Optimise Rough Set Partition Sizes for HIV Data Analysis |
Abstract: In this paper, we present a method to optimise rough set partition sizes, to which rule extraction is performed on HIV data. The genetic algorithm optimisation technique is used to determine the partition sizes of a rough set in order to maximise the rough sets prediction accuracy. The proposed method is test... |
Title: Condition Monitoring of HV Bushings in the Presence of Missing Data Using Evolutionary Computing |
Abstract: The work proposes the application of neural networks with particle swarm optimisation (PSO) and genetic algorithms (GA) to compensate for missing data in classifying high voltage bushings. The classification is done using DGA data from 60966 bushings based on IEEEc57.104, IEC599 and IEEE production rates meth... |
Title: On the monotonization of the training set |
Abstract: We consider the problem of minimal correction of the training set to make it consistent with monotonic constraints. This problem arises during analysis of data sets via techniques that require monotone data. We show that this problem is NP-hard in general and is equivalent to finding a maximal independent set... |
Title: Scanning and Sequential Decision Making for Multi-Dimensional Data - Part II: the Noisy Case |
Abstract: We consider the problem of sequential decision making on random fields corrupted by noise. In this scenario, the decision maker observes a noisy version of the data, yet judged with respect to the clean data. In particular, we first consider the problem of sequentially scanning and filtering noisy random fiel... |
Title: Codage arithmetique pour la description d'une distribution |
Abstract: Using predictive adaptive arithmetic coding and the Minimum Description Length principle, we derive an efficient tool for model selection problems : the RIC information criterion. We then present an extension of these coding techniques to non-parametrical estimation of a distribution and illustrate it on the ... |
Title: The Road to Quantum Artificial Intelligence |
Abstract: This paper overviews the basic principles and recent advances in the emerging field of Quantum Computation (QC), highlighting its potential application to Artificial Intelligence (AI). The paper provides a very brief introduction to basic QC issues like quantum registers, quantum gates and quantum algorithms ... |
Title: Generalizing Consistency and other Constraint Properties to Quantified Constraints |
Abstract: Quantified constraints and Quantified Boolean Formulae are typically much more difficult to reason with than classical constraints, because quantifier alternation makes the usual notion of solution inappropriate. As a consequence, basic properties of Constraint Satisfaction Problems (CSP), such as consistency... |
Title: MI image registration using prior knowledge |
Abstract: Subtraction of aligned images is a means to assess changes in a wide variety of clinical applications. In this paper we explore the information theoretical origin of Mutual Information (MI), which is based on Shannon's entropy.However, the interpretation of standard MI registration as a communication channel ... |
Title: Structural Health Monitoring Using Neural Network Based Vibrational System Identification |
Abstract: Composite fabrication technologies now provide the means for producing high-strength, low-weight panels, plates, spars and other structural components which use embedded fiber optic sensors and piezoelectric transducers. These materials, often referred to as smart structures, make it possible to sense interna... |
Title: Morphing Ensemble Kalman Filters |
Abstract: A new type of ensemble filter is proposed, which combines an ensemble Kalman filter (EnKF) with the ideas of morphing and registration from image processing. This results in filters suitable for nonlinear problems whose solutions exhibit moving coherent features, such as thin interfaces in wildfire modeling. ... |
Title: On complexity of optimized crossover for binary representations |
Abstract: We consider the computational complexity of producing the best possible offspring in a crossover, given two solutions of the parents. The crossover operators are studied on the class of Boolean linear programming problems, where the Boolean vector of variables is used as the solution representation. By means ... |
Title: Fast computation by block permanents of cumulative distribution functions of order statistics from several populations |
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