愛知大学

This study employs hierarchical Bayesian binomial logit models to examine the store image indicators that influence customer satisfaction at competing shopping malls in Malaysia, and whether area attractiveness and brand asset indicators affect shopping mall satisfaction. We construct proposed shopping mall satisfaction and area attractiveness ranking models for quantification with store image indicators and area attractiveness as explanatory variables, and the area attractiveness ranking model uses area brand asset indicators. The areas under assessment are Subang Jaya and Petaling Jaya. The shopping malls examined in this study are Sunway Pyramid, located in Subang Jaya, and 1Utama shopping center, located in Petaling Jaya. As the two areas are adjacent, the malls share a competitive relationship. We also estimate the two models simultaneously, providing measures to enhance shopping mall satisfaction and area attractiveness based on the estimation results of the models.

The conventional food self-sufficiency ratio (CFSSR), which primarily focuses on grains, fails to capture the full spectrum of daily food consumption. This limitation reduces its effectiveness in cross-country comparisons and global food security assessments. In response to this issue, a new indicator termed the supply-side food self-sufficiency ratio (SSFSSR) has been proposed to encompass a broad range of food products and capture the entire food supply chain. The SSFSSR aims to provide a comprehensive and practical framework for assessing food self-sufficiency at the global level. Its calculation draws on multiple data sources, including FAOSTAT, the FAO’s Food Balance Sheets, statistics from the U.S. Department of Agriculture (USDA) and Japan’s Ministry of Agriculture, Forestry and Fisheries (MAFF), as well as original farm-level survey data collected by the author. The SSFSSR is calculated based on the total quantity of food available for domestic consumption, taking into account production, trade, and losses while eliminating double counting. Secondary products such as meat, dairy, and oils are converted into their primary equivalents using primary product conversion rates (PPCRs). Based primarily on 2021 data, the SSFSSR was estimated for over 180 countries, with an average value of 58.8

With the growing aging population, the demand for reliable fall detection systems is increasing. Owing to safety concerns, real-world fall data-especially for tripping-induced falls-are often limited in existing studies. To address this limitation, we developed a largescale fall-protection system and conducted controlled experiments specifically targeting tripping falls, ensuring subject safety throughout. Subjects wore two inertial measurement units mounted on the torso-one on the chest and the other on the abdomen-and performed both tripping falls and fall-like behaviors. These wearable inertial sensors continuously captured torso motion signals, providing time-series acceleration and angular velocity data for subsequent analysis. On the basis of the collected time-series data, three long short-term memory-based models were developed: two single-sensor models and one dual-sensor model. A leave-one-subject-out cross-validation approach was applied, and a low sigmoid decision threshold together with a consecutive-window decision rule was adopted to reduce missed detections. Experimental results demonstrated high classification performance across all models, with the dual-sensor model achieving the best accuracy, precision, recall, and F1-score. These findings confirm the effectiveness of the proposed method in distinguishing tripping falls from similar daily activities.

The effectiveness of problem-solving using a Multi-agent System (MAS) depends on the design of cooperative strategies, but this design is difficult. The difficulty arises because the performance of cooperative strategies strongly depends on environmental characteristics. This study focusses on the RoboCupRescue Simulation, a disaster rescue simulation based on a multi-agent approach. To establish a map-adaptive strategy design method, we clarify how specific map characteristics affect individual rescue activities. We introduce new map and agent activity metrics, and analyze their relationship with cooperative strategy performance using LASSO regression and SHAP values. The results reveal that characteristics such as building density, D-value, and bridge ratios affect debris cleaning and movement efficiency. These findings clarify environmental dependency and provide a crucial foundation for designing map-adaptive strategies.