Search results for "Machine"
showing 10 items of 2592 documents
Design and Characterization of a Miniature Hydraulic Power Supply for High-Bandwidth Control of Soft Robotics
2020
Soft robotics holds enormous promise for a wide class of applications. However, system controllability, bandwidth, portability, and energy efficiency of soft robot power supplies are often inadequate. Soft robotics desperately needs improved solutions to drive soft actuators either pneumatically or hydraulically. This research paper offers a contribution to bridge this gap. It deals with small-scale power supplies for hydraulically-driven soft robots based on fluidic elastomer actuators in the power range 5-400 W. A design procedure for such power supplies is developed with an emphasis on high-bandwidth control. The performance requirements are established based on a literature survey, and …
Design and Experimental Test of a Thermomagnetic Motor
2012
Abstract This paper presents a Thermomagnetic Motor. The design of the motor is based on a thermal-magnetic coupled dynamic model, which is obtained by assuming the use of a ferromagnetic material working at temperatures near the curie point. The motor is modeled in terms of both its magnetic as well thermal properties (magnetic permeability and thermal conductivity) and the thermal processes are supposed to be influenced by the thermal conductivity, the convection and the advection. An analytical expression of the generated torque, which links this quantity to the magnetic, thermal and geometrical parameters of the generated torque is given. A design of a machine, based on this theory is p…
Comparison of different cooperation strategies in the prey-predator problem
2006
The paper describes two cooperating strategies among several homogeneous agents to reach a given target. In our case we used the prey-predators paradigm in which a set of agents (predators) have the purpose to reach a target (prey). The problem is addressed as an optimization problem that has been faced with two different algorithms (a genetic algorithm and a particle swam optimization algorithm). The two approaches are evaluated by using a simulator for each strategy and the results show that the strategies are very different in terms of prey-predator successes. Genetic algorithm can be used by the prey to solve at the best the problem to reach the lair, otherwise the Particle Swarm Optimi…
A Playful Experiential Learning System With Educational Robotics
2020
This article reports on two studies that aimed to evaluate the effective impact of educational robotics in learning concepts related to Physics and Geography. The reported studies involved two courses from an upper secondary school and two courses from a lower secondary school. Upper secondary school classes studied topics of motion physics, and lower secondary school classes explored issues related to geography. In each grade, there was an “experimental group” that carried out their study using robotics and cooperative learning and a “control group” that studied the same concepts without robots. Students in both classes were subjected to tests before and after the robotics laboratory, to c…
Learning-automaton-based online discovery and tracking of spatiotemporal event patterns.
2013
Discovering and tracking of spatiotemporal patterns in noisy sequences of events are difficult tasks that have become increasingly pertinent due to recent advances in ubiquitous computing, such as community-based social networking applications. The core activities for applications of this class include the sharing and notification of events, and the importance and usefulness of these functionalities increase as event sharing expands into larger areas of one's life. Ironically, instead of being helpful, an excessive number of event notifications can quickly render the functionality of event sharing to be obtrusive. Indeed, any notification of events that provides redundant information to the…
Artificial neural networks for predicting dorsal pressures on the foot surface while walking
2012
In this work, artificial neural networks (ANNs) are proposed to predict the dorsal pressure over the foot surface exerted by the shoe upper while walking. A model that is based on the multilayer perceptron (MLP) is used since it can provide a single equation to model the exerted pressure for all the materials used as shoe uppers. Five different models are produced, one model for each one of the four subjects under study and an overall model for the four subjects. The inputs to the neural model include the characteristics of the material and the positions during a whole step of 14 pressure sensors placed on the foot surface. The goal is to find models with good generalization capabilities, (…
On the Evaluation of Images Complexity: A Fuzzy Approach
2006
The inherently multidimensional problem of evaluating the complexity of an image is of a certain relevance in both computer science and cognitive psychology. Computer scientists usually analyze spatial dimensions, to deal with automatic vision problems, such as feature-extraction. Psychologists seem more interested in the temporal dimension of complexity, to explore attentional models. Is it possible, by merging both approaches, to define an more general index of visual complexity? We have defined a fuzzy mathematical model of visual complexity, using a specific entropy function; results obtained by applying this model to pictorial images have a strong correlation with ones from an experime…
One-Counter Verifiers for Decidable Languages
2013
Condon and Lipton (FOCS 1989) showed that the class of languages having a space-bounded interactive proof system (IPS) is a proper subset of decidable languages, where the verifier is a probabilistic Turing machine. In this paper, we show that if we use architecturally restricted verifiers instead of restricting the working memory, i.e. replacing the working tape(s) with a single counter, we can define some IPS’s for each decidable language. Such verifiers are called two-way probabilistic one-counter automata (2pca’s). Then, we show that by adding a fixed-size quantum memory to a 2pca, called a two-way one-counter automaton with quantum and classical states (2qcca), the protocol can be spac…
The impact of feature extraction on the performance of a classifier : kNN, Naïve Bayes and C4.5
2005
"The curse of dimensionality" is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and the classification error in high dimensions. In this paper, different feature extraction techniques as means of (1) dimensionality reduction, and (2) constructive induction are analyzed with respect to the performance of a classifier. Three commonly used classifiers are taken for the analysis: kNN, Naïve Bayes and C4.5 decision tree. One of the main goals of this paper is to show the importance of the use of class information in feature extraction for classification and (in)appropriateness of random projection or conventional PCA to feature extraction for …
Improving Nearest Neighbor Based Multi-target Prediction Through Metric Learning
2017
The purpose of this work is to learn specific distance functions to be applied for multi-target regression problems using nearest neighbors. The idea of preserving the order relation between input and output vectors considering their corresponding distances is used along a maximal margin criterion to formulate a specific metric learning problem. Extensive experiments and the corresponding discussion try to put forward the advantages of the proposed algorithm that can be considered as a generalization of previously proposed approaches. Preliminary results suggest that this line of work can lead to very competitive algorithms with convenient properties.