Article Information Sciences Others Psychology and Education Sociology

Clarifying the Sharpened network diversity in French flair rugby

This study aimed that open rugby, known as flair rugby, drives the modern game by analyzing the 2022-2023 international test matches of France representative team. We examined the superiority of a spatial tactic called French flair rugby. First, the advantage of creating a relatively large number of networks was demonstrated. From the transitivity analysis of the network (CUG test; Conditional Uniform Graph test), the cooperation occurs at a higher level than in other networks. The network graph structure showed which players functioned centrally at which time of match as unusual positions, i.e., multi-position and multi-skill. In this study, we operationally defined this diversity as the sum of the standardized eigenvector centralities. We found that the increase in the time-series score balance tended to reduce and sharpened the diversity. As a result of examining a scale-free model in network theory, Sharpening the diversity (central and transitive role players) tended of the network power law scaling.

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Special Issue Information Sciences

Research for Supporting Tactical Analysis Concerning Pass Skeleton in American Football

The authors have been conducting researches on the measurement and analysis of athletes, things and events in field sports. In particular, we focused on American Football which is the most intelligent and complicated sports, and carried out the possibility of matchup analysis of its pass play. Based on the past researches, it was found that it was possible to estimate success or failure for each play by applying to the time-series trajectory image data of pass matchup players using the CNN（Convolutional Neural Network）. However, it is necessary to improve versatility by supporting pass skeletons considering not only one-on-one defense but also formation of zone defense that are close to the match format. Therefore, we aim to support the analysis of pass skeletons, which had to consider huge parameters such as the position and movement of each player from the start of play to the success or failure of the pass. The research was carried out based on a hypothesis that the success or failure of a pass from the position several seconds before the origin of the QB pass throw could be determined by taking into consideration the skill that is the compatibility of each player, the positions and the movement trajectory of the receiver team（WR, TE, and RB）, and the defenders（LB，DB，S）that mark them. As a result, the success rate and failure rate of the assumed pass player could be predicted by using the position and its trajectory image of each player from 3 seconds before the pass pitch. And then, by determining that the pass to the maximum likelihood receiver is optimal, we confirmed that useful information can be provided to support strategy planning during the game and guidance during practice.

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Article Information Sciences

Measurement of Motor-vehicle Traffic Volume Using Camera Images and Artificial Intelligence

In Japan, road traffic censuses are conducted to assess road traffic conditions. Recently, techniques for counting traffic volume from video images have been attracting considerable attention in order to improve work efficiency and save labor, and a large number of technologies have been developed. However, since traffic volume surveys are often conducted 24 hours a day, day and night, at various sites and under various weather conditions, existing technologies have yet to reach the counting accuracy required in practice. The authors aim to develop techniques for traffic volume surveys applicable in practice by applying artificial intelligence. This paper reports the results of a case study in which the proposed techniques were applied to the video taken during actual traffic volume surveys.

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Technical Article Information Sciences Others

3D Point Studio: Utilization Platform for Point Cloud Data

As Laser measurement technology has made remarkable progress in recent years and the means of measuring the three-dimensional shapes of road spaces as point cloud data have diversified, point cloud data has been measured and accumulated throughout Japan. Point cloud data is useful as a means of accurately grasping the present shape and is expected to be utilized for a wide range of purposes with i-Construction as a turning point. Existing efforts have promoted development of new technologies and open data, steadily increasing opportunities to use point cloud data. However, it is difficult to use point cloud data wisely in accordance with its intended purpose because it is merely a vast set of points that indicate locations in space and does not hold information about the features indicated by the points or about their relationships to other points. Therefore, it is essential to develop an environment for utilizing point cloud data. In this study, we develop 3D Point Studio, a platform for utilizing and sharing 3D data including point cloud data by utilizing area data. The usefulness of this research will be confirmed through examples of applications in the actual sites, and its future development will be discussed.

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