Special Issue Information Sciences

Research on Indoor Self-Location Estimation Technique Using Similar Image Retrieval Considering Environmental Changes

In Japan, the shortage of human resources due to the declining birthrate and aging population is becoming a social problem. Particularly in the security industry, the irregular working hours and associated risks are making it increasingly challenging to secure workers. This has led to a rise in use of security systems that utilize security cameras and drones. However, in factories and other buildings with a lot of equipment and intricate structures, there is the problem of blind spots caused by occlusion. This situation necessitates the use of automated drone patrols, and a problem arises when self-position estimation fails in areas where acquiring feature points is difficult, such as corridors. To solve these problems, in a previous study, we devised a technique for position estimation using a method that can calculate similarity based on changes in the distribution of color information across the entire image. In this study, we propose a method that can cope with environmental changes caused by object movement while combining feature point-based methods.

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Special Issue Engineering in General Information Sciences Others

A Study on the Development of a Traffic Volume Counting Method by Vehicle Type and Direction Using Deep Learning

The turning movement count is investigated to understand the traffic conditions at intersections and identify bottleneck locations. In recent years, methods utilizing probe data and AI-based analysis of video images have been developed to streamline the survey process. Existing methods can count vehicles as they pass but struggle to classify vehicle types. Therefore, the objective of this study is to develop a method for counting turning movement count by vehicle type using deep learning. In this method, YOLOv8 is used to detect cars, buses, and trucks in video images, and BoT-SORT is used for tracking. When a vehicle being tracked crosses the cross-sectional lines and auxiliary lines at the intersection captured in the video images, it is counted by class. In this case, the entry direction of vehicles that cannot be determined upon entering the intersection is estimated based on accurately counted vehicles. Additionally, the entry direction is inferred from a series of vector information within the detection bounding boxes. The results of the verification experiment showed that the proposed method can count the directional traffic volume with an accuracy of over 95.0% and classify the three vehicle classes—car, bus, and truck—with an accuracy of over 90.0%.

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Special Issue Engineering in General Information Sciences Others

Detecting Near-Miss Actions and Estimating Physical Fatigue among Construction Workers Using Wearable Sensors

Labor shortages in the construction industry have become a serious issue in developed countries, particularly in Japan, where workforce aging and declining recruitment of young workers are significant challenges. In this context, ensuring worker safety has become increasingly critical. While occupational accidents in Japan's construction industry have decreased annually due to proper safety measures, the construction industry still has the highest number of fatalities among all industries. Falls from height and falls on the same level are the leading causes of injuries and fatalities. Therefore, detecting near-miss incidents (such as tripping and slipping) that precede falls, along with physical fatigue, could help prevent occupational accidents. This study investigated the feasibility of detecting near-miss incidents and estimating fatigue levels using wearable sensors suitable for continuous monitoring at construction sites. We conducted validation experiments simulating near-miss actions and fatigue conditions. Results showed that applying a Convolutional Neural Network (CNN) to data collected from an iPhone® placed in workers' trouser pockets achieved an F1-score of 0.95 in detecting near-miss actions. Additionally, by comparing body sway magnitudes before and after fatigue, we confirmed the potential for estimating physical fatigue.

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Special Issue Engineering in General

Challenges of Tourists Evacuation in Tsunami Considering with Population Distribution

Tourist attractions on islands are concentrated in coastal areas, and tourists are at high risk of being struck by a tsunami. It is acknowledged that tourists, due to their unfamiliarity with the area, may benefit from the evacuation guidance provided by residents. However, it is important to note that numerous issues persist within the current disaster risk reduction measures. In this study, the number of disaster victims was clarified based on the distribution of people by time of day in Ishigaki city and Miyakojima city, Okinawa Prefecture. From the perspective of evacuation support, the overlap between residents and tourists was analyzed using a “niche overlap index” to identify areas where evacuation guidance by residents is difficult and areas and time periods where support can be expected.

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Special Issue Information Sciences

Study on Automatic Detection of Dust Mask Wearing Status in Factories

In construction and industrial work environments, workers are mandated to wear dust masks to ensure their health and safety. However, in actual field conditions, many workers neglect this requirement due to breathing discomfort and the heat and humidity within the factory. To address this issue, it is necessary to detect workers who are not wearing masks in real time and prompt them to put them on. Therefore, this study proposes a method to determine the wearing status of dust masks using deep learning based on video footage captured within the factory.

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Article Others

A practical evaluation method using item response theory to evaluate children’s form of Jumping-over and crawling-under

In order to develop the test battery evaluating the movement of Jumping-over and crawling-under for young children, we measured and videotaped it performed by 350 kindergarten children. After that, 16 movements by body part were assess using three categories of “possible,” “no idea” and “impossible.” Since the change of eigenvalues derived from this data represented a one-dimensional structure having a high homogeneous each other, successively, the parameters of step difficulty and samples were computed using IRT. Among various IRT models, this study used Partial Credit model because obtained data is ordinal and the sample size is few. Then we found the outcomes as follows: 1) The correlation between the two sets of parameters of step difficulty computed from two sets of randomly divided samples was high, so that it can be concluded that the difficulty parameters are not depended on any ability level of samples. Again, the correlation between the two sets of sample parameters calculated from two groups of randomly grouped item parameters was also significant. This fact allowed us to conclude the obtained sample parameters did not depend on any difficulty level of items. 2) As significant difference between ages in obtained thetas was found, it is considered that thetas reflect motor ability that advances with maturity. There was also high correlation between thetas and measurements of Jumping-over and crawling-under. 3) Judging from information function consisting of 16 items, this test is suitable to determine the ability with from middle to a little low level because the information reached around there. 4) A practical estimation and evaluation sheet utilizing thetas by total score based on Zhu and Cole (1996) was developed and the application examples were represented. 5) As a result that the relationship between strictly computed indexes of fitness and the number of aberrant patterns detected in the practical method in this study was examined, the high correlation was found. Judging from this fact, it can be concluded that IRT is useful to estimate and evaluate the movement of Jumping-over and crawling-under.

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Technical Article Business & Management Economics Psychology and Education

A Survey on BeReal among University Students: Focus on Learning Motivation and Privacy Consciousness

The purpose of this study was to determine university students' thoughts on the use of BeReal. After clarifying these ideas, we compared and examined the differences in learning motivation and privacy consciousness by use, non-use, and differences in thinking. The survey population consisted of 368 university students. The survey included “items on thoughts about using BeReal”, “Learning Motivation Scale”, and “Privacy Consciousness Scale”. The results of this study indicated that BeReal is becoming more common among university students, and that many of them are willing to contribute during class.Also, It revealed that university students who use BeReal tend to be less learning motivation than those who do not use BeReal. Furthermore, the group that posts BeReal during class tends to have lower awareness of and behavior to maintain their own privacy than the group that does not post BeReal during class.

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Review Article Others

Methodological examination of methods for analyzing factors that affect home team advantage: from univariate analysis to multivariate correlation models and causal models

While most researchers agree that home advantage (HA) exists in soccer, baseball, field hockey, basketball, and other sports regardless of whether they are collegiate or professional, there is no common view on the relationship between “travel,” “familiarity with the game environment,” and “spectator effect” and the factors derived from them and home advantage. However, there is no common view on the relationship between “travel,” “familiarity with the game environment,” “spectator effect,” and their derived factors, and HA. In other words, unless there are new factors that are not addressed here, it is more appropriate to think of the factors that affect HA, which clearly exists, as “multiple factors that relate to each other and affect it comprehensively,” rather than as “factors that affect it independently. Therefore, a possible methodology for examining HA factors is the use of multivariate analysis, such as multiple regression analysis or logistic regression analysis. Then, when illustrating the findings obtained from correlation analysis, one-way arrows are used to show the relationship between the factors, and the focus shifts from the correlation relationship to the search for causal relationships. When the scope of correlation analysis is extended to include causal relationships, path analysis is used to examine not only direct effects but also indirect effects. Furthermore, as a natural development of the methodology of causal analysis, a new direction is considered to be the analysis of covariance structure, which examines the causal relationships between factors, rather than only the observed variables.

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Article Engineering in General

Evaluation of Revitalization Measures for Central City Areas Considering Changes in Human Flows

In recent years, a declining population and an aging and decline have led to a reduction in the vibrancy and economic activity of the city. Various regional cities have taken measures to revitalize their central city areas. However, they have yet to develop a method to quantify the effects of these measures. In this study, using a device equipped with Internet of Things (IoT), we obtained basic data on the number of visitors before the COVID-19 to quantify pedestrian traffic along Kokusai Street. Our findings revealed that the implementation of revitalization strategies led to a notable increase in the number of individuals visiting the area, as well as in the average duration of their stay. This suggests that the implemented measures have the potential to contribute to the revitalization of the area, thereby fostering the creation of a vibrant town center.

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Article Education Information Sciences Psychology and Education

An Inquiry-Based Learning Support System for Children in Sports Acquisition Processes

This study examined an inquiry-based learning support system for children in sports acquisition processes and describes the characteristics of a case study on the long-term collaborative process of children’s forward and backward cycle practices on horizontal bars. We analyzed 18 horizontal-bar practices for two elementary schoolchildren who had not succeeded in their backward cycle for approximately half a year. They were required to make practice plans collaboratively to succeed in their forward and backward cycles. To support their practices, we provided them with “HDMi (HDMi is the name of a system we developed in the past.),” which was developed to support reflecting on one’s physical movements using movies. The movies were also used for discourse analysis to determine where the children focused, and OpenPose software was used for motion analysis to examine how the children’s actions improved on a horizontal bar. Both the HDMi and the discourse analysis suggested that two children selected their focusing points for their practice and they gradually became referring to “move toes toward opposite side of the bar” in the periods of practices. However, the motion analysis revealed that the focused points and actual movement of the body did not match completely.

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