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71.
Francisco J. Rubio Francisco J. Valero Jose Luis Suñer Vicente Mata 《Asian journal of control》2010,12(4):468-479
This paper addresses the solution of smooth trajectory planning for industrial robots in environments with obstacles using a direct method, creating the trajectory gradually as the robot moves. The presented method deals with the uncertainties associated with the lack of knowledge of kinematic properties of intermediate via‐points since they are generated as the algorithm evolves looking for the solution. Several cost functions are also proposed, which use the time that has been calculated to guide the robot motion. The method has been applied successfully to a PUMA 560 robot and four operational parameters (execution time, computational time, distance travelled and number of configurations) have been computed to study the properties and influence of each cost function on the trajectory obtained. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society 相似文献
72.
This article proposes an optimization–simulation model for planning the transport of supplies to large public infrastructure
works located in congested urban areas. The purpose is to minimize their impact on the environment and on private transportation
users on the local road network. To achieve this goal, the authors propose and solve an optimization problem for minimizing
the total system cost made up of operating costs for various alternatives for taking supplies to the worksite and the costs
supported by private vehicle users as a result of increased congestion due to the movement of heavy goods vehicles transporting
material to the worksite. The proposed optimization problem is a bi-level Math Program model. The upper level defines the
total cost of the system, which is minimized taking into account environmental constraints on atmospheric and noise pollution.
The lower level defines the optimization problem representing the private transportation user behavior, assuming they choose
the route that minimizes their total individual journey costs. Given the special characteristics of the problem, a heuristic
algorithm is proposed for finding optimum solutions. Both the model developed and the specific solution algorithm are applied
to the real case of building a new port at Laredo (Northern Spain). A series of interesting conclusions are obtained from
the corresponding sensitivity analysis. 相似文献
73.
Liquid recirculation in microfluidic channels by the interplay of capillary and centrifugal forces 总被引:1,自引:1,他引:0
Jose L. Garcia-Cordero Lourdes Basabe-Desmonts Jens Ducrée Antonio J. Ricco 《Microfluidics and nanofluidics》2010,9(4-5):695-703
We demonstrate a technique to recirculate liquids in a microfluidic channel by alternating predominance of centrifugal and capillary forces to rapidly bring the entire volume of a liquid sample to within one diffusion length, δ, of the surface, even for sample volumes hundreds of times the product of δ and the geometric device area. This is accomplished by repetitive, random sampling of an on-disc sample reservoir to form a thin fluid layer of thickness δ in a microchannel, maintaining contact for the diffusion time, then rapidly exchanging the fluid layer for a fresh aliquot by disc rotation and stoppage. With this technique, liquid volumes of microlitres to millilitres can be handled in many sizes of microfluidic channels, provided the channel wall with greatest surface area is hydrophilic. We present a theoretical model describing the balance of centrifugal and capillary forces in the device and validate the model experimentally. 相似文献
74.
Jose A. Belloch Alberto Gonzalez F. J. Martínez-Zaldívar Antonio M. Vidal 《The Journal of supercomputing》2011,58(3):449-457
Massive convolution is the basic operation in multichannel acoustic signal processing. This field has experienced a major
development in recent years. One reason for this has been the increase in the number of sound sources used in playback applications
available to users. Another reason is the growing need to incorporate new effects and to improve the hearing experience. Massive
convolution requires high computing capacity. GPUs offer the possibility of parallelizing these operations. This allows us
to obtain the processing result in much shorter time and to free up CPU resources. One important aspect lies in the possibility
of overlapping the transfer of data from CPU to GPU and vice versa with the computation, in order to carry out real-time applications.
Thus, a synthesis of 3D sound scenes could be achieved with only a peer-to-peer music streaming environment using a simple
GPU in your computer, while the CPU in the computer is being used for other tasks. Nowadays, these effects are obtained in
theaters or funfairs at a very high cost, requiring a large quantity of resources. Thus, our work focuses on two mains points:
to describe an efficient massive convolution implementation and to incorporate this task to real-time multichannel-sound applications. 相似文献
75.
Francisco Almeida Domingo Giménez Jose J. López-Espín 《The Journal of supercomputing》2011,58(3):292-301
This paper presents a parameterized shared-memory scheme for parameterized metaheuristics. The use of a parameterized metaheuristic
facilitates experimentation with different metaheuristics and hybridation/combinations to adapt them to the particular problem
we are working with. Due to the large number of experiments necessary for the metaheuristic selection and tuning, parallelism
should be used to reduce the execution time. To obtain parallel versions of the metaheuristics and to adapt them to the characteristics
of the parallel system, a unified parameterized shared-memory scheme is developed. Given a particular computational system
and fixed parameters for the sequential metaheuristic, the appropriate selection of parameters in the unified parallel scheme
eases the development of parallel efficient metaheuristics. 相似文献
76.
Time series prediction is a complex problem that consists of forecasting the future behavior of a set of data with the only
information of the previous data. The main problem is the fact that most of the time series that represent real phenomena
include local behaviors that cannot be modelled by global approaches. This work presents a new procedure able to find predictable
local behaviors, and thus, attaining a better level of total prediction. This new method is based on a division of the input
space into Voronoi regions by means of Evolution Strategies. Our method has been tested using different time series domains.
One of them that represents the water demand in a water tank, through a long period of time. The other two domains are well
known examples of chaotic time series (Mackey-Glass) and natural phenomenon time series (Sunspot). Results prove that, in
most of cases, the proposed algorithm obtain better results than other algorithms commonly used. 相似文献
77.
Designing adaptive learning itineraries using features modelling and swarm intelligence 总被引:1,自引:1,他引:0
Jose Manuel Marquez Vazquez Juan Antonio Ortega Ramirez Luis Gonzalez-Abril Francisco Velasco Morente 《Neural computing & applications》2011,20(5):623-639
In this paper, Bayesian network (BN) and ant colony optimization (ACO) techniques are combined in order to find the best path through a graph representing all available itineraries to acquire a professional competence. The combination of these methods allows us to design a dynamic learning path, useful in a rapidly changing world. One of the most important advances in this work, apart from the variable amount of pheromones, is the automatic processing of the learning graph. This processing is carried out by the learning management system and helps towards understanding the learning process as a competence-oriented itinerary instead of a stand-alone course. The amount of pheromones is calculated by taking into account the results acquired in the last completed course in relation to the minimum score required and by feeding this into the learning tree in order to obtain a relative impact on the path taken by the student. A BN is used to predict the probability of success, by taking historical data and student profiles into account. Usually, these profiles are defined beforehand; however, in our approach, some characteristics of these profiles, such as the level of knowledge, are classified automatically through supervised and/or unsupervised learning. By using ACO and BN, a fitness function, responsible for automatically selecting the next course in the learning graph, is defined. This is done by generating a path which maximizes the probability of each user??s success on the course. Therefore, the path can change in order to adapt itself to learners?? preferences and needs, by taking into account the pedagogical weight of each learning unit and the social behaviour of the system. 相似文献
78.
79.
Francisco Gomez‐Donoso Miguel Cazorla Alberto Garcia‐Garcia Jose Garcia‐Rodriguez 《Expert Systems》2016,33(5):480-488
Schaeffer's sign language consists of a reduced set of gestures designed to help children with autism or cognitive learning disabilities to develop adequate communication skills. Our automatic recognition system for Schaeffer's gesture language uses the information provided by an RGB‐D camera to capture body motion and recognize gestures using dynamic time warping combined with k‐nearest neighbors methods. The learning process is reinforced by the interaction with the proposed system that accelerates learning itself thus helping both children and educators. To demonstrate the validity of the system, a set of qualitative experiments with children were carried out. As a result, a system which is able to recognize a subset of 11 gestures of Schaeffer's sign language online was achieved. 相似文献
80.
José Aguilar 《Applied Artificial Intelligence》2016,30(7):720-743
Cognitive maps are a tool to represent knowledge from a qualitative perspective, allowing to create models of complex systems where an exact mathematical model cannot be used because of the complexity of the system. In the literature, several tools have been proposed to develop cognitive maps and fuzzy cognitive maps (FCMs); one of them is FCM Designer. This paper designs and implements an extension to the FCM Designer tool that allows creating multilayer FCM. With this extension, it is possible to have several FCMs for the same problem, where each one expresses a different level of knowledge of the system under study, but interlinked. Thus, one can have a first level of detailed abstraction of the system with specific information and then more general levels. In addition, we can have different levels where the variables of one level depend on those of another level. That is, the multilayer approach enriches the modeled systems with flow of information between layers, to derive information about the concepts involved in layers from the concepts in other layers. In our multilayer approach, the relationship between the cognitive maps in different layers can be carried out in various ways: with fuzzy rules, connections with weights and with mathematical equations. This work presents the design and the implementation of the extension of the FCM Designer tool, and several test cases in different domains: a FCM to analyze emergent properties of Wikipedia a FCM for medical analysis for diagnosis, and another like recommender system. 相似文献