999 resultados para parallel sorting


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 Determining an analytical solution to the inverse kinematics problem for a parallel manipulator is typically a straightforward problem. However, lower mobility parallel manipulators with 2-5 degrees of freedom (DOFs) often suffer from an unwanted parasitic motion in one or more DOFs. For such manipulators, the inverse kinematics problem can be significantly more difficult. This paper contains an analysis of the inverse kinematics problem for a class of 3-DOF parallel manipulators with axis-symmetric arm systems. All manipulators in the studied class exhibit parasitic motion in one DOF. For manipulators in the studied class, the general solution to the inverse kinematics problem is reduced to solving a univariate equation, while analytical solutions are presented for several important special cases.

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In order to alleviate the traffic congestion and reduce the complexity of traffic control and management, it is necessary to exploit traffic sub-areas division which should be effective in planing traffic. Some researchers applied the K-Means algorithm to divide traffic sub-areas on the taxi trajectories. However, the traditional K-Means algorithms faced difficulties in processing large-scale Global Position System(GPS) trajectories of taxicabs with the restrictions of memory, I/O, computing performance. This paper proposes a Parallel Traffic Sub-Areas Division(PTSD) method which consists of two stages, on the basis of the Parallel K-Means(PKM) algorithm. During the first stage, we develop a process to cluster traffic sub-areas based on the PKM algorithm. Then, the second stage, we identify boundary of traffic sub-areas on the base of cluster result. According to this method, we divide traffic sub-areas of Beijing on the real-word (GPS) trajectories of taxicabs. The experiment and discussion show that the method is effective in dividing traffic sub-areas.

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Massive, parallel sequencing is a potent tool for dissecting the regulation of biological processes by revealing the dynamics of the cellular RNA profile under different conditions. Similarly, massive, parallel sequencing can be used to reveal the complexity of viral quasispecies that are often found in the RNA virus infected host. However, the production of cDNA libraries for next-generation sequencing (NGS) necessitates the reverse transcription of RNA into cDNA and the amplification of the cDNA template using PCR, which may introduce artefact in the form of phantom nucleic acids species that can bias the composition and interpretation of original RNA profiles.

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Abstract Massive, raw concrete structures – the likes of the Telecommunications Building (1972–81) by Janko Konstantinov; the campus of Ss. Cyril and Methodius University (1974) by Marko Musˇicˇ; the National Hydraulic Institute (1972) by Krsto Todorovski; and the Bank Complex (1970) by R. Lalovik and O. Papesˇ – have led to the production of an enduring monumental presence and helped inspire Skopje’s title as the “Brutalist capital of the world”. These works followed Kenzo Tange’s introduction of Japanese Metabolism to Skopje through his role in the 1965 United Nations sponsored reconstruction competition. The unique position of a Non-Aligned Yugoslavia staged and facilitated architectural and professional exchange during the Cold War. Each trajectory and manifestation illustrates the complex picture of international architectural exchange and local production. Skopje and its numerous Brutalist edifices is an elucidative story, because it represents a meeting point between Brutalism, Metabolism and its American parallel. This article discusses, in particular, the Skopje Archive Building (1966) and the “Goce Delcˇev” Student Dormitory (1969) – two buildings designed by the architect Georgi Konstantinovski, realised on his return from a Masters program at Yale University and employment within I. M. Pei’s New York office. Their architecture illustrates the simultaneous preoccupations of leading architects at the time in regaining a conceptual ground made explicit through a complete and apprehensible image. From this particular position, the article explores the question of ethics and aesthetics central to Banham’s outline of the “New Brutalism”.

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This paper presents the design, analysis and fabrication of a novel low-cost soft parallel robot for biomedical applications, including bio-micromanipulation devices. The robot consists of two active flexible polymer actuator-based links, which are connected to two rigid links by means of flexible joints. A mathematical model is established between the input voltage to the polymer actuators and the robot's end effector position. The robot has two degrees-of-freedom, making it suitable for handling planar micromanipulation tasks. Moreover, a number of robots can be configured to operate in a cooperative manner for increasing micromanipulation dexterity. Finally, the experimental results demonstrate two main motion modes of the robot.

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In this paper, an agent-based distributed control scheme is presented to control single-phase parallel inverters in solar photovoltaic (PV) systems connected to microgrids. A communication assisted multi-agent framework is developed within microgrids where agents perform their tasks in a distributed manner with an aim of stabilizing load voltage and current under normal and faulted conditions through the asymptotic tracking of the reference current signal. The distributed agent-based control scheme requires information from the neighboring agents through communication network to decide control actions. The proposed control scheme utilizes Ziegler-Nichols (Z-N) tuning approach to design proportional integral (PI) controllers for controlling inverters within the multi-agent system (MAS). A microgrid with parallel inverter-connected solar PV systems is considered for simulations under normal and faulted conditions where results show the excellency of the proposed agent-based scheme in comparison to the conventional scheme without MAS.

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This paper explores the impact of parallel trade in an export market by cross-border travellers on welfare of the home country in a model with heterogeneous consumers' perceptions. We show that such parallel trade when it is organised trading always hurts the home-country welfare. However, when parallel trade is unorganised trading, it might benefit the home-country welfare provided that the size of the export market is relatively small. Along these lines, we suggest optimal policy responses in the home country to parallel trade by cross-border travellers. The results of the paper yield insightful policy implications for Asian economies.

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It is crucial for a neuron spike sorting algorithm to cluster data from different neurons efficiently. In this study, the search capability of the Genetic Algorithm (GA) is exploited for identifying the optimal feature subset for neuron spike sorting with a clustering algorithm. Two important objectives of the optimization process are considered: to reduce the number of features and increase the clustering performance. Specifically, we employ a binary GA with the silhouette evaluation criterion as the fitness function for neuron spike sorting using the Super-Paramagnetic Clustering (SPC) algorithm. The clustering results of SPC with and without the GA-based feature selector are evaluated using benchmark synthetic neuron spike data sets. The outcome indicates the usefulness of the GA in identifying a smaller feature set with improved clustering performance.

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Artificial neural network (ANN) models are able to predict future events based on current data. The usefulness of an ANN lies in the capacity of the model to learn and adjust the weights following previous errors during training. In this study, we carefully analyse the existing methods in neuronal spike sorting algorithms. The current methods use clustering as a basis to establish the ground truths, which requires tedious procedures pertaining to feature selection and evaluation of the selected features. Even so, the accuracy of clusters is still questionable. Here, we develop an ANN model to specially address the present drawbacks and major challenges in neuronal spike sorting. New enhancements are introduced into the conventional backpropagation ANN for determining the network weights, input nodes, target node, and error calculation. Coiflet modelling of noise is employed to enhance the spike shape features and overshadow noise. The ANN is used in conjunction with a special spiking event detection technique to prioritize the targets. The proposed enhancements are able to bolster the training concept, and on the whole, contributing to sorting neuronal spikes with close approximations.

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Application of optimization algorithm to PDE modeling groundwater remediation can greatly reduce remediation cost. However, groundwater remediation analysis requires a computational expensive simulation, therefore, effective parallel optimization could potentially greatly reduce computational expense. The optimization algorithm used in this research is Parallel Stochastic radial basis function. This is designed for global optimization of computationally expensive functions with multiple local optima and it does not require derivatives. In each iteration of the algorithm, an RBF is updated based on all the evaluated points in order to approximate expensive function. Then the new RBF surface is used to generate the next set of points, which will be distributed to multiple processors for evaluation. The criteria of selection of next function evaluation points are estimated function value and distance from all the points known. Algorithms created for serial computing are not necessarily efficient in parallel so Parallel Stochastic RBF is different algorithm from its serial ancestor. The application for two Groundwater Superfund Remediation sites, Umatilla Chemical Depot, and Former Blaine Naval Ammunition Depot. In the study, the formulation adopted treats pumping rates as decision variables in order to remove plume of contaminated groundwater. Groundwater flow and contamination transport is simulated with MODFLOW-MT3DMS. For both problems, computation takes a large amount of CPU time, especially for Blaine problem, which requires nearly fifty minutes for a simulation for a single set of decision variables. Thus, efficient algorithm and powerful computing resource are essential in both cases. The results are discussed in terms of parallel computing metrics i.e. speedup and efficiency. We find that with use of up to 24 parallel processors, the results of the parallel Stochastic RBF algorithm are excellent with speed up efficiencies close to or exceeding 100%.

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A presente pesquisa foi conduzida na forma de um estudo de caso de duas instituições culturais no contexto francês e brasileiro. O Centro Pompidou é um projeto presidencial de museu financiado pelo Estado, com a missão de tornar a arte moderna em todas as suas expressões acessíveis ao público em geral. O Sesc Pompeia é um centro multidisciplinar de cultura e esporte - financiado pelo dinheiro dos impostos e administrado pela Federação do Comércio . O Sesc Pompéia é dedicado à oferta de educação informal através do cultivo da mente e do corpo. O estudo examina se as teorias de dependência de recursos e de poder podem ser utilizadas para conceituar a relação que o Centro Pompidou e do Sesc Pompéia tem com seus stakeholders financeiros. Mais especificamente, será discutido em que medida o grau de dependência influencia a estratégia de gestão das instituições. O objetivo é de responder a pergunta seguinte: quais são as estratégias que as instituições adotam para reduzir sua dependência com relação a seus principais stakeholders financeiros? Finalmente algumas implicações práticas de gestão serão elaboradas a partir do paralelo entre as estratégias das duas instituições.