Virtual decomposition control is applied to control a KUKA 361 six-joint industrial robot performing hybrid tasks with a rigid unilateral constraint. In order to accommodate motion/force control, the required velocity is re-designed by introducing filtered contact forces in full control dimensions, which makes the controlled robot behave as hybrid controlled for a known contact geometry and imp...

Although most parameters in a speech recognition system are estimated from data, the unit inventory and lexicon are generally hand crafted and therefore unlikely to be optimal. This paper describes a joint solution to the problems of learning a unit inventory and corresponding lexicon from data. The methodology, which requires multiple training tokens per word, is then extended to handle infreq...

This paper presents an overview of Nexus 3D Soccer Simulation Team. Our main concentration was on developing a new hybrid methodology for an evolutionary gait generator that uses trigonometric truncated Fourier series formulations with coefficients optimized by a Genetic Algorithm. The Fourier series is used to model joint angle trajectories of a simulated humanoid robot with 25 degrees of free...

The trends in expansion of electric power systems and changes in the conditions of their operation have led to complicate power system operation, increased its changeability and unpredictability that call for prompter and more adequate response of controls systems. This paper presents the hybrid model for the short-term prediction the parameters of expected operating conditions based on joint u...

Mixtures of Truncated Basis Functions (MoTBFs) have recently been proposed for modelling univariate and joint distributions in hybrid Bayesian networks. In this paper we analyse the problem of learning conditional MoTBF distributions from data. Our approach utilizes a new technique for learning joint MoTBF densities, then propose a method for using these to generate the conditional distribution...

We present an approach for Hybrid Machine Translation, based on a Machine-Learning framework. Our method combines output from several source systems. We first define an extensible, total order on translations and use it to estimate a ranking on the sentence level for a given set of systems. We introduce and define the notion of joint, binarised feature vectors. We train an SVM-based classifier ...

An important class of hybrid Bayesian networks are those that have conditionally deterministic variables (a variable that is a deterministic function of its parents). In this case, if some of the parents are continuous, then the joint density function does not exist. Conditional linear Gaussian (CLG) distributions can handle such cases when the deterministic function is linear and continuous va...

We propose an improved local appearance and color modeling method, as an extension of Moghaddam & Zhou [lo], for object detection and recognition in cluttered scenes. The approach is based on the joint distribution of local feature vectors at multiple salient points and factorization with Independent Component Analysis (ICA). We we are able to obtain a tractable set of joint probability densiti...

This paper presents a hybrid Decision Support System (DSS) for slow moving spare parts joint replenishment in a nuclear power plant. In this study, we integrate the fuzzy and grey theory-based spare parts criticality class evaluation model to confirm the target service level, and the web-based joint replenishment DSS to obtain reasonable purchase parameters that can be helpful for reducing tota...

channel quality indicator and hybrid automatic repeat –request acknowledgement are important feedback information in system of 3GPP LTE, adopted joint or separate coding when transmitted via Physical uplink control channel. When uplink control information adopted type of joint coding, performance of channel estimation will decline and the number of reference signal will decrease because the ACK...