Optimum combination of operating parameters in abrasive cut-off

For optimization of abrasive cut-off operation, wheel wear equation must be identified before the operation is optimized. The equation is obtained by using GMDH algorithm with successive determination of trends containing interactive terms. In the model equation factors of grinding fluid are taken into consideration in addition to the factors of wheel, work material, feed (table speed) and wheel speed. For the identification of the model wheel wear tests are performed under the experimental design treating the above-mentioned factors as independent variables. The grinding ratio (output in the model) can be predicted for combinations of various factors using the model. With the wheel wear equation and machining cost model, the optimum combination of wheel, fluid, feed and wheel speed can be selected for a given work material. The relationships between these variables and the costs are investigated.     

Construction of living cellular automata using the Physarum plasmodium

The plasmodium of Physarum polycephalum is a unicellular and multinuclear giant amoeba that has an amorphous cell body. To clearly observe how the plasmodium makes decisions in its motile and exploratory behaviours, we developed a new experimental system to pseudo-discretize the motility of the organism. In our experimental space that has agar surfaces arranged in a two-dimensional lattice, the continuous and omnidirectional movement of the plasmodium was limited to the stepwise one, and the direction of the locomotion was also limited to four neighbours. In such an experimental system, a cellular automata-like system was constructed using the living cell. We further analysed the exploratory behaviours of the plasmodium by duplicating the experimental results in the simulation models of cellular automata. As a result, it was revealed that the behaviours of the plasmodium are not reproduced by only local state transition rules; and for the reproduction, a kind of historical rule setting is needed.     

Two‐way multi‐view 2‐D/3‐D display combining LC lens and HVxDP panel using novel pixel arrangement

We have developed a two‐way multi‐view 2‐D/3‐D display combining a liquid crystal lens and horizontally and vertically x times‐density pixels (HVxDP) arrangement. The two‐way multi‐view display features the same display resolution in 2‐D and 3‐D modes and a quite small color moiré for landscape and portrait, respectively, when using the HVxDP arrangement. In this paper, we realized suitable 3‐D properties for achieving a good balance between 3‐D moiré and 3‐D crosstalk for landscape and portrait by a two‐way liquid crystal lens with two kinds of focal lengths for the edge part and the center part of the lens.     

Chain-reaction solution update in MOEA/D and its effects on multi- and many-objective optimization

MOEA/D is one of the promising evolutionary algorithms for multi- and many-objective optimization. To improve the search performance of MOEA/D, this work focuses on the solution update method in the conventional MOEA/D and proposes its alternative, the chain-reaction solution update. The proposed method is designed to maintain and improve the variable (genetic) diversity in the population by avoiding duplication of solutions in the population. In addition, the proposed method determines the order of existing solutions to be updated depending on the location of each offspring in the objective space. Furthermore, when an existing solution in the population is replaced by a new offspring, the proposed method tries to reutilize the existing solution for other search directions by recursively performing the proposed chain-reaction update procedure. This work uses discrete knapsack and continuous WFG4 problems with 2–8 objectives. Experimental results using knapsack problems show the proposed chain-reaction update contributes to improving the search performance of MOEA/D by enhancing the diversity of solutions in the objective space. In addition, experimental results using WFG4 problems show that the search performance of MOEA/D can be further improved using the proposed method.     

Variable space diversity, crossover and mutation in MOEA solving many-objective knapsack problems

In this work, we analyze variable space diversity of Pareto optimal solutions (POS) and study the effectiveness of crossover and mutation operators in evolutionary many-objective optimization. First we examine the diversity of variables in the true POS on many-objective 0/1 knapsack problems with up to 20 items (bits), showing that variables in POS become noticeably diverse as we increase the number of objectives. We also verify the effectiveness of conventional two-point and uniform crossovers, Local Recombination that selects mating parents based on proximity in objective space, and two-point and uniform crossover operators which Controls the maximum number of Crossed Genes (CCG). We use NSGA-II, SPEA2, IBEA _??+? and MSOPS, which adopt different selection methods, and many-objective 0/1 knapsack problems with $n=\{100,250,500,750,\mbox{1,000}\}$ items (bits) and m?=?{2,4,6,8,10} objectives to verify the search performance of each crossover operator. Simulation results reveal that Local Recombination and CCG operators significantly improve search performance especially for NSGA-II and MSOPS, which have high diversity of genes in the population. Also, results show that CCG operators achieve higher search performance than Local Recombination for m?≥?4 objectives and that their effectiveness becomes larger as the number of objectives m increases. In addition, the contribution of CCG and mutation operators for the solutions search is analyzed and discussed.     

Log-polar height maps for multiple range image registration

We propose a method for coarse registration of multiple range images that uses a log-polar height map (LPHM) as the key for establishing correspondence. The LPHM is a local height map orthogonally mapped on the tangent plane with the log-polar coordinate system. The input range images are roughly represented by signed distance field (SDF) samples. For each SDF sample, an LPHM is generated and is converted to an invariant feature vector. Point correspondence is established by a nearest neighbor search in feature space. The RANSAC algorithm is applied on the corresponding point pairs between each pair of range images, and the pairwise registration of input range images is determined by the extracted inlier point pairs. Finally, the global registration is determined by constructing a view tree, which is the spanning tree that maximizes the total number of inlier point pairs. The result of coarse registration is used as the initial state of the fine registration and modeling. The proposed method was tested on multiple real range image datasets.     

Robust control method for the inverted pendulum system with structured uncertainty caused by measurement error

In this article, we propose a design method for an inverted pendulum system with a structured uncertainty. We consider that such an uncertainty is caused by a measurement error in the rotation angle of the pendulum and effects on the system structure that cannot be included in the nominal elements. For the uncertain system obtained, we apply an integral tracking control and the guaranteed cost control to design a robust, stable, tracking control system. Finally, we show the effectiveness of our method through a numerical example.