We describe dipolar nematic colloids comprising mutually bound solid microspheres, three-dimensional skyrmions, and point defects in a molecular alignment field of chiral nematic liquid crystals. Nonlinear optical ima...
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We describe dipolar nematic colloids comprising mutually bound solid microspheres, three-dimensional skyrmions, and point defects in a molecular alignment field of chiral nematic liquid crystals. Nonlinear optical imaging and numerical modeling based on minimization of Landau–de Gennes free energy reveal that the particle-induced skyrmions resemble torons and hopfions, while matching surface boundary conditions at the interfaces of liquid crystal and colloidal spheres. Laser tweezers and videomicroscopy reveal that the skyrmion-colloidal hybrids exhibit purely repulsive elastic pair interactions in the case of parallel dipoles and an unexpected reversal of interaction forces from repulsive to attractive as the center-to-center distance decreases for antiparallel dipoles. The ensuing elastic self-assembly gives rise to colloidal chains of antiparallel dipoles with particles entangled by skyrmions.
The relatively low price of devices that enable capture of 3D data such as Microsoft Kinect will certainly accelerate the development and popularization of a new generation of user interaction in the business applicat...
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In this paper, it is presented a utilization of tool for symbolic regression, which is analytic programming, for the purpose of the synthesis of a new control law. This synthesized chaotic controller secures the stabi...
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Due to the increasing number of conferences, researchers need to spend more and more time browsing through the respective calls for papers (CFPs) to identify those conferences which might be of interest to them. In th...
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We consider the following simple network design problem. The input consists of n weighted nodes, and the output is an edge-weighted connected network such that the total weight of the edges incident to a node is at le...
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This paper describes a geospatial knowledge discovery model of historical maps data set with relative geographic referenced. The knowledge about spatiotemporal dynamic is represented by the transition rules of cellula...
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This paper describes a geospatial knowledge discovery model of historical maps data set with relative geographic referenced. The knowledge about spatiotemporal dynamic is represented by the transition rules of cellular automata model. Set of transition rules obtained by applying three data mining techniques on large amount of data grid. First, multiple linear regression analysis applied on each subsequent pair of N data grid to obtained (N-1) rules. Second, by applying clustering analysis, then they extracted into a small number of rules, which is represented all of the rules, and they associated with the first data grid of the related pair. Finally, the selected rules used in determining the next value of the given data using classification analysis. Selection of the rule applied to the data based on the distance between the data and the associated data grid of the selected rule. The model had been evaluated on ordinal data type from fire danger rating and nominal data from land use and land cover status. Model accuration measured and visualized by comparing actual data and the simulated data. The accuration ranges between 80%-95% in the first case and 90,5%-95,2% in the second. In the first case, by the segmentation of the model, the performance can be improved significantly, especially for von Neumann scheme.
In a classification problem typically we face two challenging issues, the diverse characteristic of negative documents and sometimes a lot of negative documents that are closed to positive documents. Therefore, it is ...
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This paper proposes a traffic signal control optimization using not only Multi-Element Genetics Algorithms (ME-GA) but also modification of signaling model. The aim of this method is to find out the best signaling mod...
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This paper proposes a traffic signal control optimization using not only Multi-Element Genetics Algorithms (ME-GA) but also modification of signaling model. The aim of this method is to find out the best signaling model for considered network with the ME-GA for defining the optimum signal parameter. In this case, three signaling models are proposed for the considered road networks. Several experiments were carried out using simple network model and real network model (Ooe-Toroku Kumamoto City Road Network) for evaluating the proposed method. The experimental results show that the first signaling model with ME-GA provides the best performance which is shown by higher percentage of vehicle flow and less vehicle delay time than others signaling models for considered networks.
This paper propose parallel implementation of Ant Colony System (ACS) algorithm for automated combinational circuit design. Ant Colony System is one of the most popular and widely used Ant Colony Optimization (ACO) al...
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This paper propose parallel implementation of Ant Colony System (ACS) algorithm for automated combinational circuit design. Ant Colony System is one of the most popular and widely used Ant Colony Optimization (ACO) algorithm and heuristic algorithm in general. As digital logic circuits become more complex, efficient circuit design is priority and use of heuristic methods are unavoidable. Unfortunately, the optimization problems became so complex in sense of their size, even the most powerful heuristic algorithms can't solve them on single CPU. In order to be able to tackle the problem, parallel version of ACS is needed and this paper presents CUDA (Compute Unified Device Architecture) C language implementation.
The main purpose of this paper is to present a service called Teaching Assistant. The aim of the assistant is to facilitate the task and assessment management in collaborative learning scenarios. This assistant intend...
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