The purpose of this study was to create a scale to measure non-cognitive skills that can be developed through sport. To begin, a draft of a non-cognitive ability measurement scale was developed based on previous research. A preliminary survey of 346 elementary school students (318 males and 28 females, mean age 8.90 ± 1.76 years) was conducted, and a preliminary scale was created using exploratory factor analysis. A subsequent main survey was conducted with 1171 elementary school students (1025 males and 146 females, mean age 8.77 ± 1.73). In the present study, confirmatory factor analysis, reliability testing using cronbach's alpha, and structural validity of the entire scale were examined using structural analysis of covariance. Furthermore, theoretical interpretations were also taken into account, and finally, a non-cognitive ability measurement scale that can be developed through sports for elementary school students was created, consisting of 50 items with 5 factors: "self-management," "problem-solving," "cooperativeness," "leadership," and "greetings/polite".

抄録全体を表示

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.

抄録全体を表示

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.

抄録全体を表示

This study aimed to determine how college sports team identifications and university identifications of college sports media viewers differ depending on the presence or absence of live play-by-play announcements and commentary. The participants in the experiment were 115 students from University A. A screening survey was conducted to confirm that these were essential attributes, resulting in 58 and 57 participants in the groups with commentary and without commentary, respectively. We conducted an Internet survey with these two groups of experimental participants before and after watching videos of the games. The results showed that only the group with commentary demonstrated improvements in the “public evaluation” of the college sports team and university identification (College sports team: F (1, 113) = 5.28, p < .05; University: F (1, 113) = 5.28, p < .05).

抄録全体を表示

Augmented reality (AR) is a technology that renders computer-generated (CG) images onto the physical world in real time. To establish technology to alter weight perception using CG images in an AR environment, we investigated whether the size of virtual objects superimposed on a physical object would affect perceived heaviness. Participants (n = 22) wore a head-mounted display with a stereo camera and observed an object overlaid with a CG image. They lifted the object vertically and rated its subjective heaviness. We found that the virtually smaller object was perceived to be heavier than the virtually larger object among a large share of participants, indicating that a well-known phenomenon, the size-weight illusion (SWI), occurred. The SWI did not occur when the virtual size became larger or smaller after movement to reach the object was initiated. Our results suggest that presenting virtual objects in an AR environment effectively altered weight perception.

抄録全体を表示

Recently, the number of students who can develop applications that can actually be used has increased. We thought that this power could be used for regional revitalization, we tried to connect the students and the region. As a result, we were able to create some interesting applications, some of which have become widely used in practice. For students, before going out to society, they can work on practical application development and know what kind of ingenuity is necessary to get them to actually use it. Although quality is not necessarily guaranteed in rural areas, the possibility of using the latest AI technology at a short development time and at a low cost was shown.

抄録全体を表示

In its i-Construction policy, the Ministry of Land, Infrastructure, Transport and Tourism has stipulated a manual for public surveying using by UAV photogrammetry with the aim of improving productivity at construction sites. However, UAV photogrammetry requires a huge amount of time to generate point cloud data from photographs, causing a problem that it is difficult to monitor the daily progress of the construction site. There is another problem that it is incapable of taking measurements except daylight hours. Against this backdrop, we have been developing laser scanner units for UAV equipped with LiDAR, IMU and GNSS receiver. Then, we clarified the error factors that are expected to affect the precision prescribed of point cloud data and summarized the requirements for the onboard equipment and the method of generating point cloud data. However, we have not yet proposed nor developed the laser scanner units as well as for generating point cloud data considering these requirements. Thus, in this paper, we developed the laser scanner units and a new method for generating point cloud data within the laser scanner units to optimize the error factors based on these requirements clarified in the existing study.

抄録全体を表示

Virtual reality is a promising technology that can be used to assess and train decision-making skills in sports. However, it is not necessarily clear what benefits this technology offers compared to previous technologies. The present study investigated the differences in option generation related to tactical decision-making when the same tactical scene was observed in 2D video and 3D VR. Soccer players (N = 27) were asked to observe tactical scenes and verbally report as many tactical options as possible under 2D video and 3D VR conditions. They were classified into high-, medium-, or low-decision capability groups based on the decision-making test. Irrespective of the capability, the 2D video and 3D VR had the same number of generated options. However, 3D VR generated more aggressive options that led to the goal, even though the exact same scene was observed between the conditions. This result may be because 3D VR can reproduce more realistic information exploration behavior than 2D video. Given that differences were observed regardless of skill level, the results suggest that VR technology has the potential for use as a more accurate decision evaluation method and effective training tool compared to previous methods for a wide variety of learners.

抄録全体を表示

The authors have developed "xG-1", a sports sensing unit capable of visualizing the performance and flow of play while recognizing each player in field sports such as soccer, rugby, and American football. Utilization of this sensing unit in the field of sports makes it possible to provide scientific data-driven services with the aim of transforming subjective coaching methods based on experience into new coaching methods based on data. This system consists of sensor devices and software, utilizing real-time kinematic (RTK) positioning, which is a surveying technology. Therefore, the system not only provides highly accurate positional data in real time but also visualizes the overall performance of the entire team, including formation analysis. This allows one-stop management of the overall team and individual performance, as well as efficient information management of the player's exercise load. "xG-1" can support sports businesses by providing highly extensible API and SDK and linking data among end users and systems. In the future, we aim to develop a global open data platform.

抄録全体を表示

This research examines the feasibility of using ChatGPT as a subject in an auction experiment. The author will also test the idea of giving ChatGPT a “persona” to participate as a human. Without personas, the author finds overbidding in the FPA and slight underbidding in the SPA; the FPA results are consistent with prior studies, but the SPA results differ. Given the persona as an excellent economics student, ChatGPT bid close to the theoretical prediction in the FPA but significantly underbid in the SPA. These results raise questions about using LLM-based AI subjects in auctions.

抄録全体を表示

The Nintendo Ring Fit Adventure (RFA) (Nintendo, Kyoto, Japan) is a novel exergame that combines exercise and video game elements. Although previous RFA intervention studies have reported the health effects of the RFA, exercise intensity among older adults has not yet been documented. We hypothesized that the exercise intensity of older adults in the current RFA setting may be low. This preliminary study developed a range of prototype RFA intensity conditions and to evaluate exercise intensity among older adults. Six older adults (1 male/5 females, mean age 75.2±10.3 years old) participated in this study. Three RFA conditions were developed: “LOW” (the ‘default’ load. Older individual input actual gender and age), “MODERATE” (as defined by the American College of Sports Medicine [ACSM]: 40%-59% heart rate reserve [HRR]), and “HIGH” (highest exercise intensity that older individuals could set in the game). Exercise intensity was assessed using the %HRR. The results show that the %HRR values for the conditions were 34.9%±4.1% (LOW), 40.0%±2.9% (MODERATE), and 52.3%±3.1% (HIGH). In conclusion, this preliminary study showed that, among the three prototype RFA conditions, both MODERATE and HIGH conditions generally attain moderate or greater intensity for older adults when assessed using the heart rate.

抄録全体を表示