32 resultados para order-picking system


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We investigate the phase behavior of a single-component system in three dimensions with spherically-symmetric, pairwise-additive, soft-core interactions with an attractive well at a long distance, a repulsive soft-core shoulder at an intermediate distance, and a hard-core repulsion at a short distance, similar to potentials used to describe liquid systems such as colloids, protein solutions, or liquid metals. We showed [Nature (London) 409, 692 (2001)] that, even with no evidence of the density anomaly, the phase diagram has two first-order fluid-fluid phase transitions, one ending in a gas¿low-density-liquid (LDL) critical point, and the other in a gas¿high-density-liquid (HDL) critical point, with a LDL-HDL phase transition at low temperatures. Here we use integral equation calculations to explore the three-parameter space of the soft-core potential and perform molecular dynamics simulations in the interesting region of parameters. For the equilibrium phase diagram, we analyze the structure of the crystal phase and find that, within the considered range of densities, the structure is independent of the density. Then, we analyze in detail the fluid metastable phases and, by explicit thermodynamic calculation in the supercooled phase, we show the absence of the density anomaly. We suggest that this absence is related to the presence of only one stable crystal structure.

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Visual perception is initiated in the photoreceptor cells of the retina via the phototransduction system.This system has shown marked evolution during mammalian divergence in such complex attributes as activation time and recovery time. We have performed a molecular evolutionary analysis of proteins involved in mammalianphototransduction in order to unravel how the action of natural selection has been distributed throughout thesystem to evolve such traits. We found selective pressures to be non-randomly distributed according to both a simple protein classification scheme and a protein-interaction network representation of the signaling pathway. Proteins which are topologically central in the signaling pathway, such as the G proteins, as well as retinoid cycle chaperones and proteins involved in photoreceptor cell-type determination, were found to be more constrained in their evolution. Proteins peripheral to the pathway, such as ion channels and exchangers, as well as the retinoid cycle enzymes, have experienced a relaxation of selective pressures. Furthermore, signals of positive selection were detected in two genes: the short-wave (blue) opsin (OPN1SW) in hominids and the rod-specific Na+/Ca2+,K+ ion exchanger (SLC24A1) in rodents. The functions of the proteins involved in phototransduction and the topology of the interactions between them have imposed non-random constraints on their evolution. Thus, in shaping or conserving system-level phototransduction traits, natural selection has targeted the underlying proteins in a concerted manner.

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In this work we explore the multivariate empirical mode decomposition combined with a Neural Network classifier as technique for face recognition tasks. Images are simultaneously decomposed by means of EMD and then the distance between the modes of the image and the modes of the representative image of each class is calculated using three different distance measures. Then, a neural network is trained using 10- fold cross validation in order to derive a classifier. Preliminary results (over 98 % of classification rate) are satisfactory and will justify a deep investigation on how to apply mEMD for face recognition.

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The SeDeM Diagram Expert System has been used to study excipients, Captopril and designed formulations for their galenic characterization and to ascertain the critical points of the formula affecting product quality to obtain suitable formulations of Captopril Direct Compression SR Matrix Tablets. The application of the Sedem Diagram Expert System enables selecting excipients with in order to optimize the formula in the preformulation and formulation studies. The methodology is based on the implementation of ICH Q8, establishing the design space of the formula with the use of experiment design, using the parameters of the SeDeM Diagram Expert System as system responses.

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In this paper, we present the experimental results and evaluation of the SmartBox stimulation device in P2P e-learning system which is based on JXTA-Overlay. We also show the design and implementation of the SmartBox environment that is used for stimulating the learners motivation to increase the learning efficiency. The SmartBox is integrated with our P2P system as a useful tool for monitoring and controlling learners¿ activity. We found by experimental results that the SmartBox is an effective way to increase the learner¿s concentration. We also investigated the relation between learner¿s body movement, concentration, and amount of study. From the experimental results, we conclude that the use of SmartBox is an effective way to stimulate the learners in order to continue studying while maintaining the concentration.

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This paper presents an Italian to CatalanRBMT system automatically built bycombining the linguistic data of theexisting pairs Spanish-Catalan andSpanish-Italian. A lightweight manualpostprocessing is carried out in order tofix inconsistencies in the automaticallyderived dictionaries and to add very frequentwords that are missing accordingto a corpus analysis. The system isevaluated on the KDE4 corpus and outperformsGoogle Translate by approximatelyten absolute points in terms ofboth TER and GTM.

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In this paper we develop a new linear approach to identify the parameters of a moving average (MA) model from the statistics of the output. First, we show that, under some constraints, the impulse response of the system can be expressed as a linear combination of cumulant slices. Then, thisresult is used to obtain a new well-conditioned linear methodto estimate the MA parameters of a non-Gaussian process. Theproposed method presents several important differences withexisting linear approaches. The linear combination of slices usedto compute the MA parameters can be constructed from dif-ferent sets of cumulants of different orders, providing a generalframework where all the statistics can be combined. Further-more, it is not necessary to use second-order statistics (the autocorrelation slice), and therefore the proposed algorithm stillprovides consistent estimates in the presence of colored Gaussian noise. Another advantage of the method is that while mostlinear methods developed so far give totally erroneous estimates if the order is overestimated, the proposed approach doesnot require a previous estimation of the filter order. The simulation results confirm the good numerical conditioning of thealgorithm and the improvement in performance with respect to existing methods.

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In the last years there has been an increasing demand of a variety of logical systems, prompted mostly by applications of logic in AI, logic programming and other related areas. Labeled Deductive Systems (LDS) were developed as a flexible methodology to formalize such a kind of complex logical systems. In the last decade, defeasible argumentation has proven to be a confluence point for many approaches to formalizing commonsense reasoning. Different formalisms have been developed, many of them sharing common features. This paper presents a formalization of an LDS for defensible argumentation, in which the main issues concerning defeasible argumentation are captured within a unified logical framework. The proposed framework is defined in two stages. First, defeasible inference will be formalized by characterizing an argumentative LDS. That system will be then extended in order to capture conflict among arguments using a dialectical approach. We also present some logical properties emerging from the proposed framework, discussing also its semantical characterization.

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This work proposes the development of an embedded real-time fruit detection system for future automatic fruit harvesting. The proposed embedded system is based on an ARM Cortex-M4 (STM32F407VGT6) processor and an Omnivision OV7670 color camera. The future goal of this embedded vision system will be to control a robotized arm to automatically select and pick some fruit directly from the tree. The complete embedded system has been designed to be placed directly in the gripper tool of the future robotized harvesting arm. The embedded system will be able to perform real-time fruit detection and tracking by using a three-dimensional look-up-table (LUT) defined in the RGB color space and optimized for fruit picking. Additionally, two different methodologies for creating optimized 3D LUTs based on existing linear color models and fruit histograms were implemented in this work and compared for the case of red peaches. The resulting system is able to acquire general and zoomed orchard images and to update the relative tracking information of a red peach in the tree ten times per second.

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We report on the results of the spectral and timing analysis of a BeppoSAX observation of the microquasar system LS 5039/RX J1826.2-1450. The source was found in a low-flux state with Fx(1-10 keV)= 4.7 x 10^{-12} erg cm^{-2} s^{-1}, which represents almost one order of magnitude lower than a previous RXTE observation 2.5 years before. The 0.1--10 keV spectrum is described by an absorbed power-law continuum with photon-number spectral index Gamma=1.8+-0.2 and hydrogen column density of NH=1.0^{+0.4}_{-0.3} x 10^{22} cm^{-2}. According to the orbital parameters of the system the BeppoSAX observation covers the time of an X-ray eclipse should one occur. However, the 1.6-10 keV light curve does not show evidence for such an event, which allows us to give an upper limit to the inclination of the system. The low X-ray flux detected during this observation is interpreted as a decrease in the mass accretion rate onto the compact object due to a decrease in the mass-loss rate from the primary.

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The possible coexistence of ferromagnetism and charge/orbital order in Bi3/4Sr1/4MnO3 has been investigated. The manganite Bi0.75Sr0.25MnO3, with commensurate charge balance, undergoes an electronic transition at TCO~600 K that produces a longrange modulation with double periodicity along a and c axis, and unusual anisotropic evolution of the lattice parameters. The previously proposed ferromagnetic properties of this new ordered phase were studied by magnetometry and diffraction techniques. In zero field the magnetic structure is globally antiferromagnetic, ruling out the apparition of spontaneous ferromagnetism. However, the application of magnetic fields produces a continuous progressive canting of the moments, inducing a ferromagnetic phase even for relatively small fields (H<<1 T). Application of pulsed high fields produces a remarkable and reversible spin polarization (under 30 T, the ferromagnetic moment is ~3 ¿B/Mn, without any sign of charge order melting). The coexistence of ferromagnetism and charge order at low and very-high fields is a remarkable property of this system.

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Control of brown spot of pear requires fungicide treatments of pear trees during the growing season. Scheduling fungicide sprays with the Brown spot of pear forecasting system (BSPcast) provides significantfungicide savings but does not increase the efficacy of disease control. Modifications in BSPcast wereintroduced in order to increase system performance. The changes consisted of: (1) the use of a daily infectionrisk (Rm≥0.2) instead of the 3-day cumulative risk (CR≥0.4) to guide the fungicide scheduling, and (2) theinclusion of the effect of relative humidity during interrupted wetness periods. Trials were performed during2 years in an experimental pear orchard in Spain. The modifications introduced did not result in increaseddisease control efficacy, compared with the original BSPcast system. In one year, no reduction in the numberof fungicide applications was obtained using the modified BSPcast system in comparison to the original system, but in the second year the number of treatments was reduced from 15 to 13. The original BSPcast model overestimated the daily infection risk in 6.5% of days with wetness periods with low relative humidity during the wetness interruption, and in these cases the modified version was more adequate

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Stochastic learning processes for a specific feature detector are studied. This technique is applied to nonsmooth multilayer neural networks requested to perform a discrimination task of order 3 based on the ssT-block¿ssC-block problem. Our system proves to be capable of achieving perfect generalization, after presenting finite numbers of examples, by undergoing a phase transition. The corresponding annealed theory, which involves the Ising model under external field, shows good agreement with Monte Carlo simulations.

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The purpose of this article is to offer a practical approach to the new European dimension for regional parliaments signified by the entry into force of the Treaty of Lisbon. The parliamentary scrutiny of subsidiarity by way of the early warning system has assigned a new mission to legislative assemblies with the aim of reinforcing the intervention of regions in the drafting of policies by Union institutions. In the Spanish case, the institutionalisation of this mechanism came about with Act nº 24/2009, which attributes to the Joint Committee for the European Union, in the name of the Cortes Generales [the Spanish Parliament], the function of receiving the proposals for legislative acts by the EU and transferring them to the regional parliaments in order for the latter to issue, in a brief period of four weeks, a report on compliance with the principle of subsidiarity. The majority of regional parliaments have also carried out normative reforms to regulate the procedure of participation in the early warning system.

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As part of the Affective Computing research field, the development of automatic affective recognition systems can enhance human-computer interactions by allowing the creation of interfaces that react to the user's emotional state. To that end, this Master Thesis brings affect recognition to nowadays most used human computer interface, mobile devices, by developing a facial expression recognition system able to perform detection under the difficult conditions of viewing angle and illumination that entails the interaction with a mobile device. Moreover, this Master Thesis proposes to combine emotional features detected from expression with contextual information of the current situation, to infer a complex and extensive emotional state of the user. Thus, a cognitive computational model of emotion is defined that provides a multicomponential affective state of the user through the integration of the detected emotional features into appraisal processes. In order to account for individual differences in the emotional experience, these processes can be adapted to the culture and personality of the user.