Set-based particle swarm optimization with status memory for knapsack problem

Set-based particle swarm optimization (S-PSO) operates on discrete space. S-PSO can solve combinatorial optimization problem with high quality and is successful to apply to the large-scale problem. In S-PSO, a velocity is a set with possibility and a position is a candidate solution. In this paper, we present a novel algorithm of set-based particle swarm optimization with status memory (S-PSOSM) to decide the position based on the previous position for solving knapsack problem. Some operators are redefined for S-PSOSM. S-PSOSM is a simple algorithm because the state of probability reduces. In addition, the weight of S-PSOSM is discussed. S-PSOSM shows high qualities in experimental results.     

Reliability and mechanical durability tests of flexible OLED with ALD coating

To improve the reliability and mechanical durability of a flexible organic light‐emitting diode display, the entire flexible display is coated with an aluminum oxide film by atomic layer deposition (ALD). Because the step coverage of ALD is excellent, the AlO_x film was deposited not only on the front and back surfaces but also on the side surfaces of the display. A high‐temperature and high‐humidity preservation test, repetitive bending tests, and a pencil hardness test were conducted on the flexible display with ALD‐AlO_x coating. The display survived 500 h of a 65°C, 95% preservation test, endured a 100,000‐time repetitive bending test with a curvature radius of 4 mm, and was found to have a pencil hardness of 4H.     

Development of a flexible autonomous robot without sensors or controllers

Recently, various robots with many degrees of freedom, such as rescue robots and domestic robots, have been developed and used in practical applications. It is difficult to control such robots autonomously in real environments, because in order to control the many degrees of freedom, we have to observe many states, calculate huge amounts of information, and operate many actuators. In this study, we consider a flexible robot without sensors or controllers that can determine the inclination of a slope and climb up the slope. In order to demonstrate the effectiveness of the proposed framework, we have developed a prototype robot and conducted experiments. The result indicates that the robot could determine the inclination and climb up a gentle slope autonomously. Thus, we have realized an autonomous robot that has no explicit sensors or controllers.     

Modified Bagolini striated glass test: clinical applications of starlight test in binocular visual field screening

AIM: To introduce the "starlight" test which was devised to check binocular vision in normal conditions of seeing in a rapid, easy, and cost effective manner and to estimate the possibility of its clinical use in screening the binocular visual field of patients. METHOD: The Bagolini striated glass test consists of optically plano lenses with imperceptible parallel scratches that barely blur the environment but produce two perpendicular luminous stripes (right eye stripe of 45 degrees and left eye stripe of 135 degrees) when subjects with normal binocular vision view one light source. Unlike the original Bagolini test, the starlight test uses three light sources in horizontal or vertical lines according to the testing purposes and the subject is asked to fixate upon the centre light. Through Bagolini glasses, the subject observes the resulting grid-like pattern and the state of binocular visual field of the subject can be roughly estimated. RESULTS: Normal subjects and patients with strabismus, visual field loss from intracranial diseases, glaucoma, retinitis pigmentosa, and functional visual loss were examined using the starlight test and findings from each case were discussed. CONCLUSIONS: The starlight test, which was made by hand at a low cost, is a simple test that can be used clinically. It provides information about the state of binocular vision of patients in normal conditions of seeing. It is also useful because it enables the examiner to share similar experiences with the examinee. The results suggest it can be effective in visual field screening.     

Effect of temperature on humido-sensitive conducting polymer actuators

Temperature dependence of water vapor sorption and electro-active polymer actuating behavior of free-standing films made of poly(3,4-ethylenedioxythiophene) doped with poly(4-styrenesulfonate) (PEDOT/PSS) was investigated by means of sorption isotherm and electromechanical analyses. The non-porous PEDOT/PSS film, having a specific surface area of 0.13 m² g^?1, sorbed water vapor of 1080 cm³(STP) g^?1, corresponding to 87 wt%, at relative water vapor pressure of 0.95. A temperature rise from 25 °C to 40 °C lowered sorption degree, indicative of an exothermic process, where isosteric heat of sorption decreased with increasing water vapor sorption and the value reached 43.9 kJ mol^?1, being consistent with the heat of water condensation (44 kJ mol^?1). Upon application of 10 V, the film underwent contraction of 2.46% at 5 °C caused by desorption of water vapor due to Joule heating, which slightly decreased to 2.10% at 45 °C. The speed of contraction was one order of magnitude faster than that of expansion and less dependent on the temperature since water vapor sorbed in the film were forced to desorb by Joule heating. In contrast, the higher the temperature the faster the film expansion because diffusion coefficient increased as the temperature became higher.     

A biped static balance control and torque pattern learning under unknown periodic external forces

This paper addresses a biped balancing task in which an unknown external force is exerted, using the so-called ‘ankle strategy’ model. When an external force is periodic, a human adaptively maintains the balance, next learns how much force should be produced at the ankle joint from its repeatability, and finally memorized it as a motion pattern. To acquire motion patterns with balancing, we propose a control and learning method: as the control method, we adopt ground reaction force feedback to cope with an uncertain external force, while, as the learning method, we introduce a motion pattern generator that memorizes the torque pattern of the ankle joint by use of Fourier series expansion. In this learning process, the period estimation of the external force is crucial; this estimation is achieved based on local autocorrelation of joint trajectories. Computer simulations and robot experiments show effective control and learning results with respect to unknown periodic external forces.     

Semi-autonomous serially connected multi-crawler robot for search and rescue

In this paper, we develop a semi-autonomous serially connected multi-crawler robot for search and rescue. In large-scale disasters, such as earthquakes and tornadoes, the application of rescue robots to search for survivors under rubble would be beneficial. Snake-like robots (robots composed of serially connected units) are an effective candidate for such robots. Their long body enables them to overcome obstacles, and they can move into narrow spaces because of their thin shape. However, conventional snake-like robots have significant problems with operability. The numerous degrees of freedom of their bodies require complex operation to overcome obstacles, and training is required for the operators. Thus, survivors or community members cannot operate conventional robots to search for victims, despite the availability of such rescue robots. Here, we address this problem and develop a semi-autonomous serially connected multi-crawler robot designed for non-trained operators, such as community members or rescued survivors. It can be controlled easily by a conventional two-channel user interface with levers for turning and straight line motion. To demonstrate the effectiveness of our proposed mechanism, a prototype robot was developed and experiments were conducted. The results confirm that the proposed robot had both higher operability and higher mobility than conventional robots.     

Parameterizing cut sets in a graph by the number of their components

For a connected graph G=(V,E), a subset U⊆V is a disconnected cut if U disconnects G and the subgraph G[U] induced by U is disconnected as well. A cut U is a k-cut if G[U] contains exactly k(≥1) components. More specifically, a k-cut U is a (k,?)-cut if V?U induces a subgraph with exactly ?(≥2) components. The Disconnected Cut problem is to test whether a graph has a disconnected cut and is known to be NP-complete. The problems k-Cut and (k,?)-Cut are to test whether a graph has a k-cut or (k,?)-cut, respectively. By pinpointing a close relationship to graph contractibility problems we show that (k,?)-Cut is in P for k=1 and any fixed constant ?≥2, while it is NP-complete for any fixed pair k,?≥2. We then prove that k-Cut is in P for k=1 and NP-complete for any fixed k≥2. On the other hand, for every fixed integer g≥0, we present an FPT algorithm that solves (k,?)-Cut on graphs of Euler genus at most g when parameterized by k+?. By modifying this algorithm we can also show that k-Cut is in FPT for this graph class when parameterized by k. Finally, we show that Disconnected Cut is solvable in polynomial time for minor-closed classes of graphs excluding some apex graph.     

Editorial

Higher-Order and Symbolic Computation -     

Codevelopmental learning between human and humanoid robot using a dynamic neural-network model.

This paper examines characteristics of interactive learning between human tutors and a robot having a dynamic neural-network model, which is inspired by human parietal cortex functions. A humanoid robot, with a recurrent neural network that has a hierarchical structure, learns to manipulate objects. Robots learn tasks in repeated self-trials with the assistance of human interaction, which provides physical guidance until the tasks are mastered and learning is consolidated within the neural networks. Experimental results and the analyses showed the following: 1) codevelopmental shaping of task behaviors stems from interactions between the robot and a tutor; 2) dynamic structures for articulating and sequencing of behavior primitives are self-organized in the hierarchically organized network; and 3) such structures can afford both generalization and context dependency in generating skilled behaviors.