Volume 2, Issue 1, June 2021

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 Datausing 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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Volume 2, Issue 2, Septmber 2021

1.A Study of Boiler Water Level System with Fuzzy Control Method
Tianyi Zhang, Fengzhi Dai, Peng Lu
Page 270-274
Abstract
In this paper, the performance characteristics of the boiler water level system are analyzed, and a fuzzy control method is used to control it based on the three-stroke water supply system. This fuzzy control method is to reason out the appropriate fuzzy control rules, design fuzzy controller, and applied to the control system, so that the system for self-adjustment of PID parameters, constitute a fuzzy PID control system. On this basis, this paper analyzes the performance, advantages and characteristics of two control systems: the traditional PID control system and the fuzzy PID control system, and simulates the parameters of the input variables for comparison and analysis.
Keywords: Fuzzy PID, three-pulse, MATLAB, PID control

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2.Research on Feature Point Measurement Technology Based on Stereo Vision
Jiwu Wang, Xin Pei
Page 275-279
Abstract
In view of the high similarity of feature points in low texture environment, this paper proposes an interactive method of manual selection of feature points based on stereo vision under the condition that automatic modeling cannot meet the requirement of 3D environment.Firstly, the model of binocular stereo vision camera with parallel optical axis is designed, then the camera calibration is carried out, and the 3D ranging system of interactive manual selection of feature point pairs is developed.In order to verify the effectiveness of the system, this paper uses corridor floor tiles with fewer texture features to carry out experimental tests. By verifying the three-dimensional coordinates of the measured feature point pairs, and comparing with the actual measured values, it is found that the measurement error is less than 1%.
Keywords:stereo vision;camera calibration; distance measurement.

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3.A Brief Overview of Autonomous Path Planning Algorithms for UAV Applications; reflections from a survey
Anees ul Husnain, Norrima Binti Mokhtar, Noraisyah Binti Mohamed Shah, Mahidzal Bin Dahari
Page 780-286
Abstract
The past two decades of research on UAVs has revealed that about seventy percent of it had been published in the previous four years. To serve the exponentially increasing role of UAVs in multi-disciplinary research, the choice for most suitable path planning algorithms is presented in this work. The extent of autonomy in path planning for a UAV primarily depends upon the capabilities of its algorithm. Hence, a comprehensive survey study was proposed and conducted. This article presents a summary of the survey and suggests most suitable path planning algorithms for a UAV application. A collective consciousness was also developed while going through the process and presented on how the research work on intelligent robots should be categorized to cater future needs.
Keywords: Autonomous UAV, Survey, UAV Path Planning

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4.A Study of YOLO Algorithm for Multi-target Detection
Haokang Wen, Fengzhi Dai
Page 787-290
Abstract
With the development of deep learning, target detection has become one of the research directions of many scholars. As one of the more mature algorithms, the single-stage YOLO algorithms have been widely used in real life. Combining the development history of the YOLO algorithm, this article focuses on the main framework and main content of the current latest YOLOv5 algorithm, and uses the YOLOv5s model to identify and detect multi-target. The test results show that YOLOv5s algorithm has good detection effect and wide application meaning in real life.
Keywords: target detection, YOLOv5, deep learning, computer vision technology

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5.A Design and Implementation of Family Potted Plant Maintenance System
Songyun Shi, Yizhun Peng, Xinpeng Yang, Yuze Si, Junjie Tai
Page 791-294
Abstract
This device is designed for the phenomenon that people often ignore the potted plants at home and lead to the death of potted plants. The intelligent flowerpot can make potted plants survive and grow better without supervision. It is a smart home product based on Internet of things technology. STM32 single chip microcomputer is used to collect the data of temperature sensor, humidity sensor, soil humidity sensor, harmful gas sensor, photosensitive sensor and other sensors, and it is used with intelligent tracking system composed of four DC motors, automatic irrigation system and mobile phone app; Through machine learning, potted plants can adapt to a variety of potted plants, so as to achieve the purpose of potted cultivation, beautification and improvement of living environment. Aiming at the disadvantages of artificial cultivation and potted plants in traditional family life, the maintenance of scientific intelligence is realized. We designed this smart flowerpot. This flowerpot not only solves the problem of life, but also adds green to the homes of those who have no time or ability to raise flowers, even the disabled
Key words: Internet of things technology, MCU, embedded, smart home, ecology, WiFi, machine learning.

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6.Forest Management using Internet of Things in the Fushan Botanical Garden in Taiwan
Shuo-Tsung Chen, Chih-Chiang Hua. Ching-Chun Chuang
Page 795-299
Abstract
In recent years, the technology of the Internet of Things (IoT) has developed rapidly and has been successfully used in different fields. Moreover, the application context of the IoT will be extended more widely. This work applies the IoT technology to forestry management, including: 1. Transmission of sensing data about forest information using wireless network communication technology of Low Power Wide Area Network (LPWAN) such as LoRa and NB-IoT; 2. Apply different sensing technologies to survey resource of forest and monitor the microclimate changes in forest. In order to verify the proposed LPWAN communication technology, sensors, and sensor deployment, we built LoRa and NB-IoT communication equipment (including repeat equipment) and various sensors to transmit the real-time sensing data in the Fushan Botanical Garden with the most diverse and complex terrain in Taiwan. The returned data also proves the successful operation of various communication devices and sensors.
Keywords:Internet of Things (IoT), Low Power Wide Area Network (LPWAN), LoRa, NB-IoT

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7.Robust attitude control of micro-satellite based on Generation Adversarial Networks fault detection and Cerebellar Model Articulation Controller fault tolerant control
Ho-Nien Shou
Page 300-303
Abstract
This paper proposes a new robust attitude control architecture for microsatellites. Based on deep learning fault detection method, Cerebellar Model Articulation Controller (CMAC) is used as fault-tolerant control. Using the image recognition function of Generation Adversarial Networks (GAN), the microsatellite actuator fault wavelet spectrum is used as the basis of training generator and discriminator for real-time fault diagnosis and classification. When the system fault diagnosis determines that the fault occurs, the cerebellar neural network participates in the fault-tolerant control. Using the Gan learning ability of generating confrontation network, the problems of insufficient sample data and insufficient sample labeling are solved respectively. As a kind of local learning network, CMAC has the advantages of strong generalization ability, fast convergence speed and simple hardware and software implementation. The simulation results show that, compared with the traditional methods, the fault detection and fault-tolerant control of GAN method combined with CMAC has higher accuracy and robustness
Keywords: deep learning, fault-detection, fault-tolerant control, Cerebellar Model Articulation Controller, Generation Adversarial Networks, wavelet

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8.Design a Mobile Robot with Image Recognition Function based on LabVIEW and KNRm
Kuo-Hsien Hsia, Bo-Jung Yang, Jr-Hung Guo, Chang-Sheng Xiao
Page 304-309
Abstract
The main purpose of this paper is to use the image recognition function of LabVIEW to construct a mobile robot with various functions, and make it applicable to the industry having web monitoring applications. The core of the robot is the KNRm controller which is suitable for beginners, and can be connected to DC servo motor, RC servo motor, infrared, ultrasonic and camera to achieve various functions of the robot. The structure of the robot uses metal parts sold by Studica company, which can be in accordance with the desired function to assemble the robot. Since the company is a designated equipment sponsor company for World Skills competitions, it can also be in line with international standards. Finally, PID control and sensors are added to make the robot movement and position more accurately.
Keywords: Image Recognition, Mobile Robot, Web monitoring, KNRm

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9.Isolated Pixel Filtering-Based Image Inpainting Methods for Drawing Robots
Chun-Chieh Wang
Page 310-314
Abstract
The purpose of this thesis is to show that isolated pixel filtering-based image inpainting methods for drawing robots. For watercolor painting, HSI color space is used to improve the effect of color simplification such that the recognition of image processing results is enhanced, firstly. Second, that less-affected isolated point color is replaced with the surrounding color via isolated pixel filtering methods. Third, we use image inpainting technology to reduce the distortion caused by the isolated pixel filtering. Besides, we adjusted the path planning as well as reduced isolated points to dramatically reduce drawing time. For sketch painting, through the image resolution adjustment as well as the shortening of the spacing of the drawing lines, the robot can draw more detailed pictures in the same size of drawing space. To allow LabVIEW to directly issue commands to control the drawing robot, the communication function has been added. The measured results confirm that the application of the technology in this paper can shorten the drawing time by about 57% to 59% on the drawing robot system.
Keywords: Isolated pixel filtering, Image inpainting, Watercolor, Sketch, Drawing robots

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10.Towards Multiple Perspectives of Cross-National Culture Using Self-Organizing Map (SOM)
Li-Min Chuang, Yu-Po Lee, Shu-Tsung Chao
Page 315-320
Abstract
This study integrates the previous cross-cultural literature and aims to construct an analysis model of cross-national culture with multiple dimensions from three important cultural dimension theoretical models commonly used in cross-cultural studies: Hofstede, Global Leadership and Organizational Effectiveness (GLOBE) and World Values Survey (WVS). Traditional statistical analysis seems to be
unable to solve the problem of the integration of relevant scales and units in different dimensions of cultural analysis. Therefore, this study uses a self-organizing map (SOM) as an analysis method to integrate 17 cultural variables from this multicultural dimension for cluster analysis and explains the cultural types in 26 countries based on the results. This study explores the differences and similarities of
different countries in different cultural dimension analyses and provides a comparative model of multicultural analysis. This study takes samples from three cross-cultural analysis databases as data sources and employs the self-organizing map for analysis based on a neural network algorithm that can be used for type discrimination, map analysis, process monitoring, and error analysis. The results identify the
cross-cultural groups of 26 countries and reveal their key cultural similarities and differences. We also elaborate upon the findings of these cultural characteristics and multi-cultural dimensions. The signification of this study is presented as a reference for subsequent studies of transnational and cross-cultural analysis and its applications

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Volume 2, Issue 3, December 2021











Volume 2, Issue 4, March 2022