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Volume 2

Issue 1 (June)

1.Emotion recognition classification by EEG based on spectrum analysis
Tianyi Zhang, Fengzhi Dai, Di Yin, JichaoZhao
Pages 218-222
Abstract
Research shows that human emotion is closely related to the activity correlation of cerebral cortex, so the research of emotion classification by EEG (Electroencephalogram) provides a reliable basis. The feature extraction and classification application for EEG has been greatly improved in recent years, so we use EEG to study emotion classification. However, there are differences between EEG signals of different subjects, which have a certain impact on emotion classification. How to ensure the high accuracy and robustness of recognition is a problem. For this problem, when studying different subjects in different states, spectrum analysis can be used for their feature extraction. When the extracted features are classified, discriminant analysis algorithm is used and achieved better classification results. There are many methods involved in feature extraction, and different feature extraction methods will be compared later, so as to improve the robustness and efficiency of emotional classification by EEG signals.
Keywords: EEG; Feature extraction; Channel selection; Spectrum analysis; Sentiment classification

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2.Graph-Based Path Generation for Robot Navigation in a Forest Environment
Ayumu Tominaga, Eiji Hayashi, Ryusuke Fujisawa, Abbe Mowshowitz
Pages 223-228
Abstract
This study evaluates a trajectory generation method for the efficient navigation of autonomous mobile robots in forests. We propose a graph-based cycle generation method. A graph was generated using environmental landmarks as nodes, and the graph was modified to be Eulerian. The Hamiltonian cycle contained nodes that could be regarded as the midpoint between a pair of landmarks; an efficient path could then be found. We applied this method to an artificial forest to verify the feasibility
Keywords: Path Generation, Area Coverage, Field Robot, Navigation, Graph, Forestry

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3.An Automatic Water Supply System Based on KingView and PLC
Peng Lu, Fengzhi Dai, Tianyi Zhang
Pages 229-233
Abstract
The existing water supply system has poor water supply quality and low level of automatic control. Therefore, this paper designed an automatic water supply system based on Siemens PLC and the software of KingView . The pressure sensor in the water supply pipeline is used to detect the pressure of the pipeline, and the liquid level sensor monitors the liquid level in the tank. The sensor transmits the data to the PLC, and the PLC issues the control instruction after the computation processing. The KingView can realize real-time monitoring and fault alarm. The system can not only avoid the problem of large fluctuation of water pressure, reduce the failure rate of water supply equipment, but also realize the automatic control of water supply system
Keywords: KingView, constant pressure water supply, PLC, upper computer system, remote control

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4.Extension of Striped Image by Inverse Line Convergence Index Filter to Video
Toru Hiraoka. Ryosuke Takaki
Pages 234-238
Abstract
A non-photorealistic rendering method has been proposed for generating a striped image which is overlaid striped patterns in a photograph. The conventional method generates the striped image by an iterative process using an inverse line convergence index filter from the photograph. In this paper, we propose a method to extend the method of generating the striped image so that it can be applied to a video. In the proposed method, it is possible to suppress flicker due to the striped patterns. To verify the effectiveness of the proposed method, an experiment was conducted to visually and quantitatively evaluate the degree of flicker using Yuzenzome video. As a result of the experiment, it was found that the proposed method can suppress flicker.
Keywords: Non-photorealistic rendering, video, striped pattern, inverse line convergence index filter

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5.Deep Learning Methods for Robotic Arm Workspace Scene Reconstruction
Pei Yingjian, Sakmongkon Chumkamon, Eiji Hayashi
Pages 239-243
Abstract
This research is part of the Yaskawa Motoman Robot Autonomous Control Project, which aims to map the real workspace in a virtual environment using a depth camera mounted on the robot, and to plan the robot's autonomous obstacle avoidance path based on the 3D octomap. The main tool used in this study is RTAB-Map, which is based on the built-in handheld mapping scheme to improve it to meet our actual needs. After the actual test, our solution shows finer mapping accuracy, can update the map data in real time, and the perception of obstacles within the field of view is more comprehensive, but there is still a lot of room for optimizing the mapping speed
Keywords: 3D SLAM, Semantic Segmentation, Point Cloud, ROS

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6.Experimental Consideration on Requirements Specification of Haptic Device that Presents Sensation Corresponding to Palm on Back of Hand for Teleoperation of Robot Hand
Kyosuke Ushimaru, Noritaka Sato, Yoshifumi Morita
Pages 244-248
Abstract
Teleoperated rescue robots have recently been on demand. However, it is known that the teleoperation of a robot hand mounted on a rescue robot is difficult. Therefore, we proposed a new haptic device that presents a haptic sensation for the teleoperation of a robot hand. The device stimulates the back of the hand instead of the palm of the operator. The determination of the required specifications by an experiment with subjects is presented in this paper. To design the device, the interval of the stimulation points (i), the diameter of the stimulation point (d), and the force of the stimulation (f) should be optimized. From the experimental results, we found that the accuracy rate was highest, when (i, d, f) = (30mm, 6mm, 0.9kgf). Moreover, we considered the decided specification in an additional experiment
Keywords: Rescue robot, Haptic Device, Teleoperation, Robot Hand, Palm

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7.Real-Time AGVs moving control of Autonomous decentralized FMS by mind change with deep learning
Hidehiko Yamamoto, Ryunosuke Yamane
Pages 249-253
Abstract
This study describes the control method of Automated Guided Vehicles (AGV) movements by using a mind model in order to avoid AGVs interferences. The mind uses the two types of mind, the arrogant mind and the modest mind model. The interferences between AGVs are avoided by repeating the two types of mind changes, the arrogant mind and the modest mind. The mind model includes the deep learning system. By the mind including the deep learning, we can improve the decrease of the route interference time
Keywords: Autonomous decentralized FMS, AGV, Mind, Deep learning

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8.Extension of the Function to Ensure Real-time Traceability between UML Sequence Diagram and Java Source Code on RETUSS
Kaoru Arima, Tetsuro Katayama, Yoshihiro Kita, Hisaaki Yamaba, Kentaro Aburada, Naonobu Okazaki
Pages 254-258
Abstract
Ensuring traceability of software deliverables is one of the methods to ensure software quality. RETUSS (Real-time Ensure Traceability between UML and Source-code System) is a tool that saves labor and time, and eliminates mistakes by human handling in ensuring traceability between UML and source code. However, RETUSS is not useful due to its limited scope of application. This paper improves the usefulness of RETUSS by extending the function to ensure real-time traceability between UML sequence diagrams and Java source code on RETUSS
Keywords: software quality, traceability, UML, sequence diagram, Java

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9.Wallet Operation Inspection System Using Deep Learning for Image Processing
Junichiro Yamawaki, Yasunari Yoshitomi, Masayoshi Tabuse, Taro Asada
Pages 259-264
Abstract
As the average age of Japan’s population increases, it is becoming increasingly important to identify persons suffering from mild cognitive impairment (MCI), which is one of the pre-stages of dementia, to ensure they have proper care while working to suppress the progression of the disease. As a method for investigating MCI, wallet operation evaluations have been receiving considerable attention recently. Herein, we propose a system for inspecting wallet operation based on deep learning for image processing. In our system, the bills and coins extracted from a wallet are automatically scanned and recognized, which makes it possible to evaluate a person’s ability to correctly select and extract the correct bills and coins from the wallet within a reasonable period
Keywords: Mild cognitive impairment, Dementia, Wallet operation inspection, Deep learning, Image processing

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10.Design of a Data-Driven Controller based on Estimated I/O Data using Open-Loop Data
Yasuteru Nishiya, Takuya Kinoshita, Toru Yamamoto
Pages 265-269
Abstract
In recent years, data-driven control that does not require system modeling has been proposed and extended to a non-linear system by using the database. At this time, various data are required to obtain good control performance but the cost is required. In this paper, a new scheme that enables various data generation and control system design from a set of open-loop data is proposed. Besides, the filter is designed to keep the value of the reference signal constant. A simulation example numerically verifies the effectiveness of the proposed scheme
Keywords: data-driven control, PID controller, response prediction, offline, reference signal, filter

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Issue 3 (December)











Issue 4 (March)