Journal of Robotics, Networking and Artificial Life

Volume 5, Issue 1, June 2018
Research Article

1. Optimal Hohmann-Type Impulsive Ellipse-to-Ellipse Coplanar Rendezvous

Xiwen Tian, Yingmin Jia
Pages: 1 - 5
This paper devotes to the problem of ellipse-to-ellipse coplanar rendezvous, where the solution and distribution of Hohmann-type optimal impulsive rendezvous are investigated. The analytical relation between the initial states and rendezvous time are derived for Hohmann-type, and the optimal impulse...
Research Article

2. Natural Computing Paradigm – A Concise Introduction

Takashi Yokomori
Pages: 6 - 9
Natural computing (NC) is an emerging area of research that investigates computing techniques and models inspired by nature on one hand, and it also investigates phenomena taking place in nature in terms of computational methodologies on the other hand. Thus, research in NC congenitally has interdisciplinary...
Research Article

3. Advanced Rolling Bearing Fault Diagnosis Using Ensemble Empirical Mode Decomposition, Principal Component Analysis and Probabilistic Neural Network

Caixia Gao, Tong Wu, Ziyi Fu
Pages: 10 - 14
Aiming at the problem that the vibration signal of the incipient fault is weak, an automatic and intelligent fault diagnosis algorithm combined with ensemble empirical mode decomposition (EEMD), principal component analysis (PCA) and probabilistic neural network (PNN) is proposed for rolling bearing...
Research Article

4. A Comparative Study on the Delisting Ratings of Firms from the UN Global Compact in the International Management Environment

Kanako Negishi
Pages: 15 - 18
This study clarifies unique characteristics of Japanese manufacturing firms in the international business management environment using the United Nations Global Compact delisting ratio through a comparative study on Japan, China, Spain, and the US. Analyzing the number of countries and delisting ratios...
Research Article

5. Parameter Optimization with Input/Output Data via DE for Adaptive Control System with Neural Network

Taro Takagi, Ikuro Mizumoto
Pages: 19 - 22
In this paper, adaptive control system with neural network (NN) will be designed. At the beginning, parallel feedforward compensator (PFC) will be designed by using one-shot experimental data of controlled system via differential evolution (DE). From the obtained PFC and the ideal almost strictly positive...
Research Article

6. Management of digital records with RADAR by data dilution into Complex System

Anne Jeannin-Girardon, Alexandre Bruyant, Nicolas Toussaint, Ismaila Diouf, Pierre Collet, Pierre Parrend
Pages: 23 - 26
Storing sensitive data in a centralized way can lead to significant loss, should the central node or networks links be defective as is the case in numerous countries, especially developing countries. Consequently, this paper proposes to deal with this problem by diluting sensitive data into an ecosystem...
Research Article

7. Design and Development of a Constant-Temperature Reservoir for a Database-Driven Smart Cultivation System

Shin Wakitani, Sneha Sharma, Toru Yamamoto
Pages: 27 - 31
Decreasing the number of people working in the agriculture sector is a serious problem in Japan. Production of agricultural products in a plant factory is one of the solutions to the above problem. However, setting optimal environmental conditions is difficult owing to the nonlinearity of the system....
Research Article

8. A Metaheuristic Approach for Parameter Fitting in Digital Spiking Silicon Neuron Model

Takuya Nanami, Filippo Grassia, Takashi Kohno
Pages: 32 - 36
DSSN model is a qualitative neuronal model designed for efficient implementation in digital arithmetic circuit. In our previous studies, we developed automatic parameter fitting method using the differential evolution algorithm for regular and fast spiking neuron classes. In this work, we extended the...
Research Article

9. Facial Expression Analysis and its Visualization While Writing Messages

Yasunari Yoshitomi, Taro Asada, Kenta Mori, Ryoichi Shimada, Yuiko Yano, Masayoshi Tabuse
Pages: 37 - 40
We have developed a real-time system for expressing emotion as a pictograph selected according to the facial expression while writing a message. The image signal is analyzed by our real-time system using image processing software (OpenCV) and a previously proposed feature parameter. We applied the system...
Research Article

10. Improving EEG-based BCI Neural Networks for Mobile Robot Control by Bayesian Optimization

Takuya Hayakawa, Jun Kobayashi
Pages: 41 - 44
The aim of this study is to improve classification performance of neural networks as an EEG-based BCI for mobile robot control by means of hyperparameter optimization in training the neural networks. The hyperparameters were intuitively decided in our preceding study. It is expected that the classification...
Research Article

11. Development of A Passively Powered Knee Exoskeleton for Squat Lifting

R.K.P.S. Ranaweera, R.A.R.C. Gopura, T.S.S. Jayawardena, G.K.I. Mann
Pages: 45 - 51
This paper proposes a knee exoskeleton with passive-powering mechanism to provide power assistance to the knee joint during squat lifting of objects from the ground. It is designed to capture and store 20% of the biomechanical energy dissipated at the biological knee joint during decent phase and return...
Research Article

12. Design System of Cell Type Assembly Machine with Dual Arms Robot by GA

Hidehiko Yamamoto, Keita Honda, Takayoshi Yamada
Pages: 52 - 55
The purpose of this research is to develop a system named DELUGA which automatically decides by genetic algorithm (GA) where to place a lot of assembled parts, jigs and robot hands in the workstation when designing a cell type assembly machine with a dual arms robot. In DELUGA, since the left and right...
Research Article

13. Technique of Recovery Process and Application of AI in Error Recovery Using Task Stratification and Error Classification

Akira Nakamura, Kazuyuki Nagata, Kensuke Harada, Natsuki Yamanobe
Pages: 56 - 62
We have proposed an error recovery method using the concepts of task stratification and error classification. In this paper, the recovery process after the judgment of error is described in detail. In particular, we explain how to change the parameters of planning, modeling, and sensing when error recovery...
Research Article

14. Simulation of Main Steam Temperature Control System Based on Neural Network

Fengzhi Dai, Yujie Yan, Baochang Wei, Yuxing Ouyang, Lingran An
Pages: 63 - 66
This paper designs a PID control system based on the BP neural network. The control system can adjust three adjustable parameters of PID controller through BP neural network algorithm. The main steam temperature control system of the thermal power plant was taken as the object, and simulation analysis...
Research Article

15. Efficient collective search by agents that remember failures

Masao Kubo, Nhuhai Phung, Hiroshi Sato
Pages: 67 - 70
The BRT agent is an algorithm that can find appropriate collective behavior by changing the agreement contents in a trial and error manner. Computer experiments show that it is necessary to change the agreement contents the number of times that is proportional to the square of the number of choices....
Research Article

16. Finding appropriate parameter voltages for driving a low-power analog silicon neuron circuit

Atsuya Tange, Takashi Kohno
Pages: 71 - 74
This research focuses on a silicon neuron circuit designed utilizing a qualitative neuronal modeling approach. In this circuit, temperature, fabrication mismatch, and secondary effects of transistors cause the difference between the intended characteristics and those in the implemented circuits. Therefore,...
Research Article

17. Unsupervised Image Classification Using Multi-Autoencoder and K-means++

Shingo Mabu, Kyoichiro Kobayashi, Masanao Obayashi, Takashi Kuremoto
Pages: 75 - 78
Supervised learning algorithms such as deep neural networks have been actively applied to various problems. However, in image classification problem, for example, supervised learning needs a large number of data with correct labels. In fact, the cost of giving correct labels to the training data is large;...