Research Article
1.Applying Method of Generating Checkered Pattern Images Using Prewitt Filter to RGB-D Images
Toru Hiraoka¹, Ryosuke Takaki^2
1Department of Information Systems, University of Nagasaki, 1-1-1, Manabino Nagayo, Nishisonogi, Nagasaki, 815-2195, Japan
²Division of Computer Science, Graduate School of Regional Design and Creation, University of Nagasaki, 1-1-1, Manabino, Nagayo-chou, Nishisonogi-gun, Nagasaki-ken, 815-2195, Japan
pp. 167-170
ABSTRACT
A non-photorealistic rendering (NPR) method for automatically generating checkered pattern images from gray-scale photographic images using Prewitt filter with an expanded window size has been proposed. In this paper, we propose an extension of the conventional method to apply to RGB-D images. Our method can change the size of the checkered patterns depending on the depth. To verify the effectiveness of our method, we conducted experiments that are visually confirmed the checkered patterns by changing the parameters in our method. As a result of the experiment, it was found that the size of the checkered patterns can be automatically changed according to the depth. Additionally, it was found that the size and density of the checkered patterns can be adjusted by changing the value of the parameters

ARTICLE INFO
Article History
Received 08 November 2021
Accepted 17 March 2022

Keywords
Non-photorealistic rendering
Checkered pattern
RGB-D image
Prewitt filter

JAALR2401

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Research Article
2.Dense pedestrian-vehicle detection based on improved YOLOV5
Zhihui Chen¹, Xiaoyan Chen¹, Xiaoning Yan², Shuangwu Zheng²
1Tianjin University of Science and Technology, No. 1038 Dagu Nanlu, Hexi District, Tianjin, China
²Shenzhen softsz co. ltd, Shenzhen, China
pp. 171-176
ABSTRACT
With the continuous improvement of social development level, traffic has become complicated. Therefore, the detection of pedestrian and vehicles becomes important. There are many application scenarios for pedestrian-vehicle detection, such as autonomous driving and transportation. This paper mainly introduces the research status of pedestrian-vehicle detection, analyzes the advantages and disadvantages of various current target detection algorithms, and focuses on YOLOv5 algorithm. Because the YOLOv5 model is much smaller than YOLOv4, and YOLOv5 also has strong detection ability. Finally, YOLOv5 is used to carry out pedestrian-vehicle detection experiments. The results the detection accuracy is improved slightly.

ARTICLE INFO
Article History
Received 25 November 2021
Accepted 27 September 2022

Keywords
Pedestrian
Vehicle
Detection
YOLOv5

JAALR2402

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Research Article
3.A Concrete Crack Inspection Embedded in the Drone-Based System by Using Sub-Pixel Width Estimation and Morphological Component Analysis
Ankur Dixit¹, Wataru Oshiumi¹, Hiroaki Wagatsuma^1,2
1Kyushu Institute of Technology, 2-4 Hibikino, Wakamatsu-Ku, Kitakyushu, 808-0196, Japan
²RIKEN CBS, Japan
pp. 177-183
ABSTRACT
Human experts have assured social infrastructure inspections, and recently an automated inspection is expected as an integrated system of the flight vehicle with software algorithms of the image processing. For the submillimeter-width concrete-crack detection, we have introduced Morphological Component Analysis (MCA) to be able to find those positions. Conventional image processing methods work well for thick-width crack detections, while the thin-width crack detection is highly difficult. We successfully demonstrated a concrete crack detection from images through proximity cameras in a specialized multi-copter and MCA-based crack position estimations and the linear regression-based sub-pixel width estimation were integrated together. It will open a new door to engineering in the actual field work, which can be widely applicable for social infrastructure inspections in general.

ARTICLE INFO
Article History
Received 25 November 2021
Accepted 22 March 2022

Keywords
Morphological component analysis (MCA)
Multicopter
Concrete crack detection
Sub-pixel estimation

JAALR2403

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Research Article
4.Competitive Positioning of R&D Strategies at Productive Frontier: The Case study on Cooperative Relationship between EV and Battery Makers
Yousin Park¹, Iori Nakaoka², Yunju Chen^3
1Faculty of Regional Development, Prefectural University of Hiroshima, Hiroshima City, Hiroshima Prefecture, 732-0821, Japan
²Faculty of Business Administration, Seijoh University, Tokai City, Prefecture, 476-8588, Japan
³Faculty of Economics, Shiga University, 1-1-1 Banba Hikone City, Shiga Prefecture, 522-8522, Japan
pp. 184-188
ABSTRACT
This paper focuses on the R&D direction and the business strategy of EV firms and battery makers with reference to Porter’s productive frontier. M. E. Porter (1996) claimed that the productivity frontier represents the maximum value that the organization can deliver at any a given cost, using technologies, skills and purchased inputs. He argued that strategic decisions are ones that are aimed at differentiating an organization from its competitors in a sustainable way in the future. We use the patent information of EV firms (Toyota, Tesla, Volkswagen) and battery makers (Panasonic, CATL, LG Chem) as the cases. We examine our propositions by social network analysis and text mining. The analysis in this paper includes: 1) trying to distinguish between differentiation and cost leadership strategy from R&D direction, and visualizing productivity frontier, 2) making discussing on the inter-organizational relation of EV firms and battery makers. In this paper, we clarify those patterns of cooperation EV firms and battery makers.

ARTICLE INFO
Article History
Received 08 November 2021
Accepted 26 March 2022

Keywords
R&D strategies
EV makers
Battery makers
Patent analysis

JAALR2404

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Research Article
5.Proposal of a Method to Generate Classes and Instance Variable Definitions in VDM++ Specification by Using Machine Learning
Kensuke Suga¹, Tetsuro Katayama¹, Yoshihiro Kita², Hisaaki Yamaba¹, Kentaro Aburada¹, Naonobu Okazaki^1
1Department of Computer Science and Systems Engineering, Faculty of Engineering, University of Miyazaki, 1-1 Gakuen-kibanadai nishi, Miyazaki, 889-2192 Japan
²Department of Information Security, Faculty of Information Systems, Siebold Campus, University of Nagasaki, 1-1-1 Manabino, Nagayo-cho, Nishi-Sonogi-gun, Nagasaki, 851-2195 Japan
pp. 189-194
ABSTRACT
Writing VDM++ specifications is difficult. The existing method can automatically generate only type and constant definitions in VDM++ specification from natural language specification by using machine learning. This paper proposes a method to generate classes and instance variable definitions in VDM++ specification from natural language specification to improve the usefulness of the existing method. From the evaluation experiment by using F-values, it has been confirmed that the proposed method can improve the usefulness of the existing method.

ARTICLE INFO
Article History
Received 25 November 2021
Accepted 28 March 2022

Keywords
Natural language specification
Machine learning
VDM++ specification
Automatic generation

JAALR2405

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Research Article
6.A Study on Multi-sensor Data Fusion Algorithm
Peng Lu¹, Fengzhi Dai^1,2
1Tianjin University of Science and Technology, China
²Tianjin Tianke Intelligent and Manufacture Technology CO., LTD, China
pp. 195-200
ABSTRACT
As an important research direction in the field of sensors, multi-sensor data fusion has received greater attention and development in areas such as robotics and autonomous driving. This paper provides a comprehensive introduction to the physical model-like and parameter-based data fusion algorithms that are often used in current engineering. Meanwhile, the process, steps and recent developments of the weighted average method and the extended Kalman filter method are highlighted, and multi-sensor data fusion experiments are conducted for each of the two algorithms. The simulation results prove that the data fusion algorithm has a good fusion effect.

ARTICLE INFO
Article History
Received 22 November 2021
Accepted 28 March 2022

Keywords
Multi-sensor
Data fusion
Weighted average method
Extended kalman filter

JAALR2406

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Research Article
7.Measuring the Entire Degree Centrality in Mazda’s Yokokai Keiretsu: A Parts-Importance Weighted Model
Tsutomu Ito¹, Seigo Matsuno¹, Makoto Sakamoto², Satoshi Ikeda², Mei Ootani³, Takao Ito⁴, Rajiv Mehta^5
1Department of Business and Administration, Ube National College of Technology, 2-14-1 Tokiwadai, Ube, Yamaguchi, 755-0096, Japan
²Faculty of Engineering, University of Miyazaki, 1-1 Gakuen Kibanadai-Nishi, Miyazaki, 889-2192, Japan
³System Development Department Manufacturing Technology Office, NOK Corporation, 1-12-15 Shibadaimon, Minato-ku, Tokyo, Japan
⁴Graduate School of advanced Science and Engineering, Hiroshima University, 1-4-1 Kagamiyama, Higashi-Hiroshima, 739-8527, Japan
⁵Martin Tuchman School of Management, New Jersey Institute of Technology, Newark, New Jersey, 07102-1982, U.S.A
pp. 201-205
ABSTRACT
As a most important index in calculating network interrelationships, there are many definitions and more than 400 different centrality dimensions, such as degree, and betweenness, among many others, have been developed. All centrality indexes are calculated using the number of connection lines, and its position in a given network. In the automotive industry, interrelationships among partner firms are tied within a typical systemic network known as keiretsu. As it is widely known that different partners play different roles in assembly line, it is crucial to measure the centrality of transaction network in the keiretsu.. Thus, the relative importance of each partner in a connection line in a transaction network should be measured based upon the pivotal nature of each part, which has never been proposed. This paper contributes and advances our knowledge to the literature by proposing a new parts-importance weighted centrality model.

ARTICLE INFO
Article History
Received 24 November 2021
Accepted 06 April 2022

Keywords
Keiretsu loosening
Degree centrality
Entire degree centrality
Diameter
Production cost rate.

JAALR2407

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Research Article
8.Autoencoder with Gramian Angular Summation Field for Anomaly Detection in Multivariate Time Series Data
Umaporn Yokkampon¹, Abbe Mowshowitz², Sakmongkon Chumkamon¹, Eiji Hayashi^1
1Graduate School of Computer Science and Systems Engineering, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka, Fukuoka 820-8502, Japan
²Department of Computer Science, The City College of New York, 160 Convent Avenue, New York, NY 10031, USA
pp. 206-210
ABSTRACT
Uncertainty is ubiquitous in data and constitutes a challenge in real-life data analysis applications. To deal with this challenge, we propose a novel method for detecting anomalies in time series data based on the Autoencoder method, which encodes a multivariate time series as images by means of the Gramian Angular Summation Field (GASF). Multivariate time series data is represented as 2D image data to enhance the performance of anomaly detection. The proposed method is validated with four time-series data sets. Experimental results show that our proposed method can improve validity and accuracy on all criteria. Therefore, effective anomaly detection in multivariate time series data can be achieved by combining the methods of Autoencoder and Gramian Angular Summation Field.

ARTICLE INFO
Article History
Received 26 November 2021
Accepted 23 April 2022

Keywords
Anomaly detection
Factory automation
Autoencoder
Multivariate time series

JAALR2408

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Research Article
9.A Low-intensity Laser Control System Design
Yuhui Cheng, Fengzhi Dai
Tianjin University of Science and Technology, 300222, China
pp. 211-215
ABSTRACT
Low-power laser therapy is widely used in the treatment of various diseases as a clinical adjuvant therapy. In this paper, a multi-channel low-power laser physiotherapy equipment design scheme is proposed. The laser exciter used in this scheme can generate laser light with a wavelength of 650±20nm. In order to realize the requirement of multi-point irradiation, the device has designed 8 laser channels, and these channels are controlled by the main control unit composed of STM32F407ZGT6 single-chip microcomputer. The user can control the power, frequency and working time of the laser generator only by making some simple settings on the operation unit. In order to ensure the integrity of the treatment process, the system has designed a power-off protection mechanism, which can automatically save the working parameters in progress.

ARTICLE INFO
Article History
Received 26 November 2021
Accepted 27 April 2022

Keywords
Single chip microcomputer
Laser
Pulse width modulation
Power failure protection

JAALR2409

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Research Article
10.How does a TTS or highlighting system work for learning?
Sota Kobayashi, Masayoshi Tabuse
Graduate School of Life and Environmental Sciences, Kyoto Prefectural University, 1-5 Shimogamohangi-cho, Sakyo-ku, Kyoto 606-8522, Japan
pp. 216-219
ABSTRACT
There are individual differences in human cognitive function, and that is a widely known fact. A hypothesis we made is that; giving both visual and audio stimuli may make it easier for people to catch information. In this research, three indicators are set consisting of memory, understanding, and concentration for an experiment. The difference in learning effect due to the reading situation was measured. We concluded that a Text-to-Speech (TTS) and the highlighting system can help reading in some cases.

ARTICLE INFO
Article History
Received 25 November 2021
Accepted 25 April 2022

Keywords
Psychology of learning
Cognitive science
Verbatim memory
Text-to-speak
Highlighting

JAALR2410

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