Fusion visualization for fluid dynamics in blood vessel

The speed up of supercomputers has increased the complexity of simulations. To analyze such kind of data, new types of visualization software are needed. As one of approach for meeting this requirement, we are developing the “Fusion Visualization” in a project sponsored by the Japan Science and Technology Agency (JST). It can execute fused visualization of simulation data combining both volume and surface rendering. The overall concept was reported last year at the AROB 18th International Symposium in Korea. In this work, we are reporting the ongoing research with an application example related to blood flow simulation.     

Review of the International Symposium on Artificial Life and Robotics (AROB)

In this article, we review the growth of AROB conferences, and assess the various contributions, which have covered digital life, the artificial brain, artificial society, and evolutionary robots, etc. We analyze the relations between artificial life, complexity, and intelligent robots, and finally give our view of the expected future of AROB. This work was presented in part at the 5th International Symposium on Artificial Life and Robotics, Oita, Japan, January 26–28, 2000     

Path planning of a mobile robot by optimization and reinforcement learning

At AROB5, we proposed a solution to the path planning of a mobile robot. In our approach, we formulated the problem as a discrete optimization problem at each time step. To solve the optimization problem, we used an objective function consisting of a goal term, a smoothness term, and a collision term. While the results of our simulation showed the effectiveness of our approach, the values of the weights in the objective function were not given by any theoretical method. This article presents a theoretical method using reinforcement learning for adjusting the weight parameters. We applied Williams' learning algorithm, episodic REINFORCE, to derive a learning rule for the weight parameters. We verified the learning rule by some experiments. This work was presented, in part, at the Sixth International Symposium on Artificial Life and Robotics, Tokyo, Japan, January 15–17, 2001     

Feature extraction method for a robot map using neural networks

Many map-building algorithms using ultrasonic sensors have been developed for mobile robot applications. In indoor environments, the ultrasonic sensor system gives some uncertain data. To compensate for this effect, a new feature extraction method using neural networks is proposed. A new, effective representation of the target is defined, and the reflection wave data patterns are learnt using neural networks. As a consequence, the targets are classified as planes, corners, or edges, which all frequently occur in indoor environments. We constructed our own robot system for the experiments which were carried out to show the performance. This work was presented in part at the 7th International Symposium on Artificial Life and Robotics, Oita, Japan, January 16–18, 2002     

The encoder of a switched reluctance motor for the breech automation of a tank

To open and close the breech-block of a tank automatically, we used a switched reluctance motor (SRM) which has the characteristics of high speed, high torque, high efficiency, durability, and environmental robustness. For the stable operation of a tank’s automatic breech system, a new type of SRM encoder with a simple configuration is proposed. This work was presented in part at the 7th International Symposium on Artificial Life and Robotics, Oita, Japan, January 16–18, 2002     

A rescue robot designed for ease of use: development of exploration system using behavior of bombycid

Rescue operation is one of most effective applications of robots. However, previous rescue systems that use robots have a serious problem that is a shortage of professional operators. In this paper, we develop an exploration system of survivors using carbon dioxide, and to solve the problem we apply searching mechanism of bombycid to our system. To demonstrate the effectiveness of the proposed system, experiments have been conducted. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Knowledge-based unmanned automation and control systems for the SBR wastewater treatment process

Wastewater treatment processes are usually located in rural seclusion. we designed an unmanned and automated control system for a sequencing batch reactor (SBR) wastewater treatment pilot plant. The pilot plant was constructed in the countryside, a small distance from a large city. Networks and wireless modules were employed for data transmission. A local controller was installed in the SBR pilot plant as a client, and a monitoring system was located in another place as a server. The communication system consisted of an asymmetric digital subscriber line (ADSL) network and a code division multiple access (CDMA) module. A remote control and monitoring system were constructed in a laboratory in the city. We describe a fuzzy inference system which was constructed with the operator's assistance, and acquired sensor data to determine the threshold and influent. This work was presented in part at the 7th International Symposium on Artificial Life and Robotics, Oita, Japan, January 16–18, 2002     

Speech recognition using pulse-coupled neural networks with a radial basis function

We have developed a novel pulse-coupled neural network (PCNN) for speech recognition. One of the advantages of the PCNN is in its biologically based neural dynamic structure using feedback connections. To recall the memorized pattern, a radial basis function (RBF) is incorporated into the proposed PCNN. Simulation results show that the PCNN with a RBF can be useful for phoneme recognition. This work was presented in part at the 7th International Symposium on Artificial Life and Robotics, Oita, Japan, January 16–18, 2002     

Test Technology TC Newsletter

This month's Test Technology TC Newsletter reviews the July 2009 2nd IEEE Workshop on Hardware-Oriented Security and Trust, and features upcoming events for November 2009: 40th International Test Conference, 18th Asian Test Symposium, and 10th IEEE Workshop on RTL and High-Level Testing.     

Editorial: Visual Information Communication and Interaction

Visual information has increasingly been used to enable human-human communication and knowledge discovery with the vast information, not only in typical normal displays but also in immersive environments and small mobile devices. Visual information communication and interaction synergises state-of-the-art research in visual communications, designs and applications. By marrying multi-disciplinary research works in visualization, graphical user-interface, and interaction together with art concepts and designs, it has opened a new opportunity to present and analyse information on different perspectives. This special issue of the International Journal of Software and Informatics (IJSI) on Visual Information Communication and Interaction includes five selected papers presented at the 7th International Symposium on Visual Information Communication and Interaction (VINCI''14), which was successfully held in Sydney, 5-8 August 2014. The papers have been substantially extended with at least 30% additional contents from the symposium versions. Each was also reviewed by two reviewers through a rigorous review process. They cover a wide range in information visualization, mobile web interface, interaction to design and art.     

Tele-immersive collaborative virtual environment for intuitive interpretation

The purpose of tele-immersive collaboration is to enable people in separate locations to work together effectively by the Virtual Reality (VR) technology facilitating the human intuitive insight and interpretation. Consequently, it is important to cogitate with figures and characters as well as voice communication in Collaborative Virtual Environment (CVE). In this paper, we constructed tele-immersive CVE with annotation capability and free-hand drawing of characters and figures into Immersive Projection Technology (IPT) environment. In addition, participants from remote sites connected over a Wide Area Network (WAN) were enabled to interact with each other by sharing annotations via a PDA application. Moreover, we developed applications for scientific visualization and, for intellectual work based on KJ Method inside a tele-immersive CVE. From these results, we are able to maintain essential information for thinking by making annotation on IPT environment, and have proved the system can support intuitive understanding in remote collaborative work. This work was presented in part at the 12th International Symposium on Artificial Life and Robotics, Oita, Japan, January 25–27, 2007     

Fractals in neurodynamics: From hybrid dynamical systems point of view

Recently, hybrid dynamical systems have attracted considerable attention in the automatic control domain. In this article, a theory for recurrent neural networks is presented from a hybrid dynamical systems point of view. The hybrid dynamical system is defined by a continuous dynamical system discretely switched by external temporal inputs. The theory suggests that the dynamics of continuous-time recurrent neural networks, which are stochastically excited by external temporal inputs, are generally characterized by a set of continuous trajectories with a fractal-like structure in hyper-cylindrical phase space. This work was presented, in part, at the 7th International Symposium on Artificial Life and Robotics, Oita, Japan, January 16–18, 2002     

Emergence of auto-catalytic structure in stochastic self-reinforcing reaction networks

We consider a chemical reaction network model in which some of the reactions are stochastic and depend on past history. In this chemical reaction network, we found the emergence of autocatalytic sets (ACS) and complex dynamics in which ACS are repeatedly created and destroyed. This work was presented in part at the 7th International Symposium on Artificial Life and Robotics, Oita, Japan, January 16–18, 2002     

Modeling of motor control on manual tracking for developing a handmovement-compensation technique

Skillful motor control by humans is achieved by the appropriate motor commands generating from the central nervous system. An internal model in the cerebellum may contribute to the realization of accurate motor control. In this work, a model of human motor control of manual tracking to move a visible target was constructed based on experimental data from a visual tracking test with normal healthy adults and with patients with cerebellar ataxia. A compensation method to improve the motor function of patients was also developed by using the model. This work was presented in part at the 7th International Symposium on Artificial Life and Robotics, Oita, Japan, January 16–18, 2002     

Development of rescue manipulator to search narrow space for victims

Recently, disasters such as earthquakes and so on occur at various places, and rescue operation using robots has attracted much attention. In this paper, we propose a new rescue robot with duplex mechanism that is realized by connecting two manipulators in parallel. We have demonstrated the validity and effectiveness of the proposed system by developing a prototype system. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Parallel algorithms for arbitrary dimensional Euclidean distance transforms with applications on arrays with reconfigurable optical buses.

In this paper, we present algorithms for computing the Euclidean distance transform (EDT) of a binary image on the array with reconfigurable optical buses (AROB). First, we develop a parallel algorithm termed as Algorithm Expander which can be implemented in O(1) time on an AROB with N x Ndelta processors, where delta = 1/k, k is a constant and a positive integer. Algorithm Expander is designed to compute a higher dimensional EDT based on the computed lower dimensional EDT. It functions as a general EDT expander for us to expand EDT from a lower dimension to a higher dimension. We then develop parallel algorithms for the two-dimensional (2-D)_EDT of a binary image array of size N x N in O(1) time on an AROB with N x N x Ndelta processors and for the three-dimensional (3-D)_EDT of a binary image of size N x N x N in O(1) time on an AROB with N x N x N x Ndelta processors. To the best of our knowledge, all results derived above are the best O(1) time algorithms known. We then extend it to compute the nD_EDT of a binary image of size Nn in O(n) time on an AROB with Nn+delta processors. We also apply our parallel EDT algorithms to build Voronoi diagram and Voronoi polyhetra (polygons), to find all maximal empty spheres and the largest empty sphere, and to compute the medial axis transform. All of these applications can be solved in the same time complexity on an AROB with the same number of processors as needed for solving the EDT problems in the same dimensions.     

Backward movement control with two-trailer truck system using genetic programming

In this paper, we propose a control system using genetic programming (GP) for backward movement control of a two-trailer truck, known as a nonholonomic system. We have already achieved the control of a single trailer using GP. In this study, we aim to design a control system for complex problem of two trailers. In order to verify the effectiveness of the proposed method, it is compared to neuro controller (NC) system evolved by genetic algorithm (GA). This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Performance evaluation system for probabilistic neural network hardware

The probabilistic neural network (PNN) is one of the most promising neural networks, and is now applied to some real-world applications. In order to speed up the PNN calculation considerably, we have developed a PNN hardware system for video image recognition. The performance of the PNN hardware cannot be evaluated precisely until the evaluation system is completed. In this study, we developed a performance evaluation system for the PNN hardware and demonstrated it using the developed evaluation system.This work was presented, in part, at the 8th International Symposium on Artificial Life and Robotics, Oita, Japan, January 24–26, 2003     

Realization of a self-recognition algorithm based on the biological immune system

As the use of the computer is popularized, the damage from computer viruses and hacking by malicious users is increasing rapidly. To block the hacking that is an intrusion into a person's computer, and the viruses that destroy data, a study into an intrusion detection and virus detection system based on the biological immune system is in progress. In this article, we describe a model of positive and negative selection for self-recognition, which has a similar function to the cytotoxic T cells that play an important role in the biological immune system. We propose a self/nonself discrimination algorithm for a computer system, which will the important when we detect data infected by a computer virus, of data modified by an intrusion from outside. We also show the validity and effectiveness of the proposed self-recognition algorithm by a computer simulation of some infected data obtained from cell changes and string changes in the self-file. This work was presented, in part, at the Seventh International Symposium on Artificial Life and Robotics, Oita, Japan, January 16–18, 2002