Search results for "train"

Counting by Statistics on Search Trees: Application to Constraint Satisfaction Problems

1997

In 1975, Knuth proposed a simple statistical method for investigating search trees. We use this technique for estimating the number of solutions of constraint satisfaction problem CSP and boolean satisfiability problem SAT instances. We show that, depending on domain reductions, tree-based estimates have a lower variance than estimates based on uniform sampling from the search space. Nevertheless, because the variance remains extremely high in the general case, a confidence interval cannot be derived, but a lower bound of the number of solutions. These results are confirmed by many experiments.

Comparison Of Patient Satisfaction And Compliance With Two Respiratory Muscle Training Programs In The Frail Elderly

2012

Numerical and Experimental Analysis of the Frictional Effects on 4ENF Delamination Tests Performed on Unidirectional CFRP

2015

Abstract Progressive delamination in composite materials under static or fatigue loading condition are, in many structures, one of the predominant cause of failure. In the paper, an accurate study of quasi-static delamination growth under mode II loading condition is conducted. Several experimental tests are performed on composite laminates consisting of unidirectional carbon/epoxy layers. Four-point end-notched flexure (4ENF) test is employed in order to characterize the mode II interlaminar fracture toughness. The R-curve is obtained by means of optical and numerical determination of crack tip position. The energy release rate and the crack length are calculated through experimental deter…

A Fiber Optic Strain Gage Sensor for Measuring Preload in Thick Composite Bolted Joints

2019

Mechanical fastening is a popular choice in joining composites because of the ability to transfer high loads and the ease of assembly and disassembly. In this study, the failure behavior of composite–aluminum single lap bolted joint is investigated. In particular, the effects of varying the preload on the bolt are examined. In order to accurately measure the preload, a specialized sensor that uses a fiber Bragg grating sensor embedded in the bolt is proposed and created. This sensor is realized for the current tests but can be expanded to other applications. An experimental study of bolted single-lap joints varying the tightening torque value has been carried out and, in order to validate t…

Moving Learning Machine Towards Fast Real-Time Applications: A High-Speed FPGA-based Implementation of the OS-ELM Training Algorithm

2018

Currently, there are some emerging online learning applications handling data streams in real-time. The On-line Sequential Extreme Learning Machine (OS-ELM) has been successfully used in real-time condition prediction applications because of its good generalization performance at an extreme learning speed, but the number of trainings by a second (training frequency) achieved in these continuous learning applications has to be further reduced. This paper proposes a performance-optimized implementation of the OS-ELM training algorithm when it is applied to real-time applications. In this case, the natural way of feeding the training of the neural network is one-by-one, i.e., training the neur…

A Similarity Evaluation Technique for Cooperative Problem Solving with a Group of Agents

1999

Evaluation of distance or similarity is very important in cooperative problem solving with a group of agents. Distance between problems is used by agents to recognize nearest solved problems for a new problem, distance between solutions is necessary to compare and evaluate the solutions made by different agents, and distance between agents is useful to evaluate weights of the agents to be able to integrate them by weighted voting. The goal of this paper is to develop a similarity evaluation technique to be used for cooperative problem solving with a group of agents. Virtual training environment used for this goal is represented by predicates that define relationships within three sets: prob…

Integrated dimensional and drive-train design optimization of a light-weight anthropomorphic arm

2012

An approach to minimize the mass of robotic manipulators is developed by integrated dimensional and drive-train optimization. The method addresses the influences of dimensions and characteristics of drive-trains in the design optimization. Constraints are formulated on the basis of kinematic performance and dynamic requirements, whereas the main objective is to minimize the total mass. Case studies are included to demonstrate the application of the optimization method in the design of assistive robots.

Continuing Education in the Health Sciences in Spain

2008

<div class="ftSection"><span class="ftInlineSubsectionTitle">Background:</span><p>Employers have long been concerned about the professional qualifications of their employees. Decision makers in the health sciences are no exception, particularly now that they are seriously considering the improvement and full accreditation of continuing education as part of the planned European convergence.</p></div><div class="ftSection"><span class="ftInlineSubsectionTitle">Method:</span><p>Medical and nursing professionals were questioned about their views on continuing education, suitable content of possible programs, and implementation, in comp…

Extended constrained deformations: a new sculpturing tool

1999

Modelling tools tend to virtual sculpturing, in which a basic object is deformed by user supplied actions. The model we present aims to be generic: whatever the geometric description of the object, we can deform it to satisfy location constraints. Our model deforms the whole space, the image of a point is a blend of deformation functions with a projection matrix which allows the satisfaction of the constraints. The user can define the extent of the deformation (i.e. the part of the object to be deformed), the shape of the deformation function to create profiles and the displacement of the constraint points to be satisfied.

Combining conjunctive rule extraction with diffusion maps for network intrusion detection

2013

Network security and intrusion detection are important in the modern world where communication happens via information networks. Traditional signature-based intrusion detection methods cannot find previously unknown attacks. On the other hand, algorithms used for anomaly detection often have black box qualities that are difficult to understand for people who are not algorithm experts. Rule extraction methods create interpretable rule sets that act as classifiers. They have mostly been combined with already labeled data sets. This paper aims to combine unsupervised anomaly detection with rule extraction techniques to create an online anomaly detection framework. Unsupervised anomaly detectio…