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.     

Relaxation approach to topology optimization of frame structure under frequency constraint

This paper deals with the frame topology optimization under the frequency constraint and proposes an algorithm that solves a sequence of relaxation problems to obtain a local optimal solution with high quality. It is known that an optimal solution of this problem often has multiple eigenvalues and the feasible set is disconnected. Due to these two difficulties, conventional nonlinear programming approaches often converge to a local optimal solution that is unacceptable from a practical point of view. In this paper, we formulate the frequency constraint as a positive semidefinite constraint of a certain symmetric matrix, and then relax this constraint to make the feasible set connected. The proposed algorithm solves a sequence of the relaxation problems with gradually decreasing the relaxation parameter. The positive semidefinite constraint is treated with the logarithmic barrier function and, hence, the algorithm finds no difficulty in multiple eigenvalues of a solution. Numerical experiments show that global optimal solutions, or at least local optimal solutions with high qualities, can be obtained with the proposed algorithm.     

Emergency response to the nuclear accident at the Fukushima Daiichi Nuclear Power Plants using mobile rescue robots

On March 11, 2011, a massive earthquake (magnitude 9.0) and accompanying tsunami hit the Tohoku region of eastern Japan. Since then, the Fukushima Daiichi Nuclear Power Plants have been facing a crisis due to the loss of all power that resulted from the meltdown accidents. Three buildings housing nuclear reactors were seriously damaged from hydrogen explosions, and, in one building, the nuclear reactions became out of control. It was too dangerous for humans to enter the buildings to inspect the damage because radioactive materials were also being released. In response to this crisis, it was decided that mobile rescue robots would be used to carry out surveillance missions. The mobile rescue robots needed could not be delivered to the Tokyo Electric Power Company (TEPCO) until various technical issues were resolved. Those issues involved hardware reliability, communication functions, and the ability of the robots' electronic components to withstand radiation. Additional sensors and functionality that would enable the robots to respond effectively to the crisis were also needed. Available robots were therefore retrofitted for the disaster reponse missions. First, the radiation tolerance of the electronic componenets was checked by means of gamma ray irradiation tests, which were conducted using the facilities of the Japan Atomic Energy Agency (JAEA). The commercial electronic devices used in the original robot systems operated long enough (more than 100 h at a 10% safety margin) in the assumed environment (100 mGy/h). Next, the usability of wireless communication in the target environment was assessed. Such tests were not possible in the target environment itself, so they were performed at the Hamaoka Daiichi Nuclear Power Plants, which are similar to the target environment. As previously predicted, the test results indicated that robust wireless communication would not be possible in the reactor buildings. It was therefore determined that a wired communication device would need to be installed. After TEPCO's official urgent mission proposal was received, the team mounted additional devices to facilitate the installation of a water gauge in the basement of the reactor buildings to determine flooding levels. While these preparations were taking place, prospective robot operators from TEPCO trained in a laboratory environment. Finally, one of the robots was delivered to the Fukushima Daiichi Nuclear Power Plants on June 20, 2011, where it performed a number of important missions inside the buildings. In this paper, the requirements for the exploration mission in the Fukushima Daiichi Nuclear Power Plants are presented, the implementation is discussed, and the results of the mission are reported.     

Polytetrafluoroethylene processing characteristics using high-energy X-ray

Polytetrafluoroethylene (PTFE) microstructures’ processing characteristics using X-ray photo dcomposition and desorption are studied in the highest energy region (2 keV to >12 keV). While the exposed surface states are seen melting and boiling from the remaining bubble structure of the irradiated surface, basic photochemistry of PTFE is also same as previous reports and high-aspect ratio structures are successfully formed. We developed new Ni stencil electroformed stencil masks and successfully fabricated first and practical example of PTFE micro fluidic parts. The characteristics of fabricated micro fluidic parts, a PTFE fluid filter for vertical fluid flow operation which works as passive valve, agreed with the calculated results. This suggests that the accuracy of patterning is adequate to apply this technique to fabricate microfluidic parts and other various microparts.     

A new scaling algorithm for the maximum mean cut problem

We present a new scaling algorithm for the maximum mean cut problem. The mean of a cut is defined by the cut capacity divided by the number of arcs crossing the cut. The algorithm uses an approximate binary search and solves the circulation feasibility problem with relaxed capacity bounds. The maximum mean cut problem has recently been studied as a dual analogue of the minimum mean cycle problem in the framework of the minimum cost flow problem by Ervolina and McCormick. A networkN=(G, lower, upper) with lower and upper arc capacities is said to be -feasible ifN has a feasible circulation when we relax the capacity bounds by ; that is, we use (lower(a)- , upper(a)+) bounds instead of (lower(a), upper(a)) bounds for each arca A. During an approximate binary search we maintain two bounds,LB andUB, such thatN is LB-infeasible andUB-feasible, and we reduce the interval size (LB, UB) by at least one-third at each iteration. For a graph withn vertices, m arcs, and integer capacities bounded byU, the running time of this algorithm is O(mn log(nU). This time bound is better than the time achieved by McCormick and Ervolina under thesimilarity condition (that is,U=O(n^o(1))). Our algorithm can be naturally used for the circulation feasibility problem, and thus provides a new scaling algorithm for the minimum cut problem.Research supported by a grant-in-aid of the Ministry of Education, Science and Culture of Japan.     

Parametric polynomial spectral factorization using the sum of roots and its application to a control design problem

This paper presents an algebraic approach to polynomial spectral factorization, an important mathematical tool in signal processing and control. The approach exploits an intriguing relationship between the theory of Gröbner bases and polynomial spectral factorization which can be observed through the sum of roots, and allows us to perform polynomial spectral factorization in the presence of real parameters. It is discussed that parametric polynomial spectral factorization enables us to express quantities such as the optimal cost in terms of parameters and the sum of roots. Furthermore an optimization method over parameters is suggested that makes use of the results from parametric polynomial spectral factorization and also employs two quantifier elimination techniques. This proposed approach is demonstrated in a numerical example of a particular control problem.     

Two-stage subspace identification for softsensor design and disturbance estimation

Softsensors or virtual sensors are key technologies in industry because important variables such as product quality are not always measured on-line. In the present work, two-stage subspace identification (SSID) is proposed to develop highly accurate softsensors that can take into account the influence of unmeasured disturbances on estimated key variables explicitly. The proposed two-stage SSID method can estimate unmeasured disturbances without the assumptions that the conventional Kalman filtering technique must make. Therefore, it can outperform the Kalman filtering technique when innovations are not Gaussian white noises or the characteristics of disturbances do not stay constant with time. The superiority of the proposed method over the conventional methods is demonstrated through numerical examples and application to an industrial ethylene fractionator.     

Solving the irregular strip packing problem via guided local search for overlap minimization

The irregular strip-packing problem (ISP) requires a given set of non-convex polygons to be placed without overlap within a rectangular container having a fixed width and a variable length, which is to be minimized. As a core sub-problem to solve ISP, we consider an overlap minimization problem (OMP) whose objective is to place all polygons into a container with given width and length so that the total amount of overlap between polygons is made as small as possible. We propose to use directional penetration depths to measure the amount of overlap between a pair of polygons, and present an efficient algorithm to find a position with the minimum overlap for each polygon when it is translated in a specified direction. Based on this, we develop a local search algorithm for OMP that translates a polygon in horizontal and vertical directions alternately. Then we incorporate it in our algorithm for OMP, which is a variant of the guided local search algorithm. Computational results show that our algorithm improves the best-known values of some well-known benchmark instances.     

Direct Ray Tracing of Phong Tessellation

There are two major ways of calculating ray and parametric surface intersections in rendering. The first is through the use of tessellated triangles, and the second is to use parametric surfaces together with numerical methods such as Newton's method. Both methods are computationally expensive and complicated to implement. In this paper, we focus on Phong Tessellation and introduce a simple direct ray tracing method for Phong Tessellation. Our method enables rendering smooth surfaces in a computationally inexpensive yet robust way.