くじら産業の街である下関市と北九州市は、くじらや捕鯨の歴史や文化を持ちながら、従前よりそれらが観光ツアー商品の対象となることは無かった。2019（令和元）年に商業捕鯨が再開され、下関市が国内唯一の母船式捕鯨基地となったことを契機に、関門両市に存在するくじらの歴史、文化等を辿るツアーが新たな商品となりうるのか、行政や旅行会社へのヒアリング等を行い、その実現可能性について検証した。

This study investigated the status of learning statistical inference based on the new high school curriculum guidelines, focusing on problems related to the standard normal distribution to assess understanding. Furthermore, based on past incorrect answer data for the standard normal distribution, effective teaching methods were proposed, implemented in educational practice, and their effectiveness was verified. Regarding problems on the standard normal distribution, having students draw graphs to understand the relationship with the formula and then review their work led to an increase in the correct answer rate. However, a significant number of errors persisted, including those based solely on rote understanding and careless mistakes. Measures to address careless mistakes still have room for improvement.

Despite the widespread adoption of Gradient Boosting Decision Trees (GBDTs), practitioners lack systematic criteria for determining when linear models are more effective. This knowledge gap impacts model selection in applications where computational efficiency, interpretability, and extrapolation capabilities are required. This study addresses this issue through five systematic experiments that isolate data characteristics: linearity dominance, feature interactions, extrapolation requirements, small-sample scenarios, and interpretability needs. Our multi-dimensional evaluation framework integrates predictive performance with computational and interpretability costs, providing a comprehensive empirical comparison of linear regression and GBDTs. Linear models significantly outperformed GBDTs under four critical conditions.

South Korea ranks seventh globally in container cargo handling, whereas Japan does not hold a comparable position among leading countries. This study aims to analyze the status of global maritime container cargo, examine the relationship between maritime container ports in Japan and South Korea, and provide insights into Japan's current situation. Although the global logistics metric is primarily based on container cargo volume (TEU), Japan’s unique industrial characteristics result in significant imports of coal, oil, iron ore, and grain—commodities unsuited to container transport—and exports of passenger vehicles. Consequently, Japan's contribution to global competitiveness in this area is limited. Meanwhile, global port development trends focus on accommodating larger vessels and enhancing container cargo transport technologies. However, Japanese ports face limitations, as the world’s largest container ships cannot dock due to depth constraints, making it difficult to attract primary-route vessels. Furthermore, Japan’s stagnant economy necessitates prioritizing feeder services.

Rough set methods are often used to reduce decision rules. Specific techniques using rough sets are used as a method for extracting decision rules. However, when dealing with many decision rules, the computational load becomes an issue. The problem of calculating all minimum-length decision rules is a NP-hard problem with combinatorial explosion. To address this computational challenge, this article describes a method to introduce biocomputing technology. This method applies DNA molecular technology to the reduction of decision rules, and can effectively reduce the computational complexity of the problem. Since L.M. Adleman pioneered the concept of the biological computing paradigm in 1998, this technology has provided the ability to develop new problem-solving algorithms by utilizing and implementing them in existing algorithms. However, algorithms using interdisciplinary DNA molecular technology for industrial engineering decision-making problems are still limited to areas where DNA is used in a limited way, and it cannot be said that they are widely used as a computational technology. This article describes the mechanisms and techniques of molecular engineering that manipulate DNA molecular structures and properties, and introduces the use of general molecular algorithms. In particular, we describe an algorithm we developed to minimize decision rules for minimum rule searches of rough sets.