Ideophones (giongo/gitaigo) are sound-symbolic or iconic words found in many languages. They have been attracting increasing attention in the fields of linguistics, psychology, and more broadly, cognitive science. Japanese ideophones have been extensively studied due to their highly conventionalized sound symbolic system; however, research often relies on native speaker linguists’ introspection, particularly concerning the form-meaning correlation. This study provides an automatic analysis of Japanese ideophones using full dictionary entries with Python3 and its library Polas. Additionally, this study offers an initial analysis using the automatically generated comprehensive data, with a special focus on their form-meaning correspondences, particularly whether they refer to sound. The study not only reduces researchers’ workload, but also enables more objective, detailed, and comprehensive analysis of sound symbolism in Japanese ideophones and other languages, facilitating large-scale cross-linguistic comparisons.

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Tourism digital transformation, where efficient management using Information and Communication Technologies is required including data utilization for evidence-based decision making. Many kinds of data are collected, and people are struggling to utilize them for efficient decision making. One of the ways to show the data to users is data-visualization dashboards. Some dashboards are used to show data to ordinary people who are interested in data or data utilization but not good at analyzing them by themselves. Conventional data dashboards only show graphs and data. Ordinary people find it difficult to make full use of them. It has two main reasons; people have little sense to new kinds of data which are unfamiliar to them; they can’t imagine what actions they should take based on the data or dashboards. In this paper, we identify what is required to help such people utilize data, and propose a new action-first dashboard for data utilization and how to develop it

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In this paper, a method for detecting microsatellite instability (MSI) status from colorectal cancer biopsy samples by deep learning with a convolutional neural network (CNN) using a pathological Whole Slide Image (WSI) is proposed. The proposed model has a mechanism to add weights to feature maps obtained from images of multiple sizes and resolutions as inputs. The MSI detection for a specimen is performed by adding a process to expand the cancer cell area and a confidence measure in consideration for the characteristic of the biopsy samples. In addition, the model used was changed according to the size of the specimen. The method used in the previous study detected the MSI status on the patch with an accuracy of 76.0%, whereas the method used in this study achieved an accuracy of 88.3%.

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This study focuses on overcoming various management challenges in achieving Green Transformation (GX). Digital Transformation (DX) serves as a key driving force for realizing GX through Information and Communication　Technology (ICT). Specifically, by improving data accessibility and analysis and utilizing IoT and AI, companies can　enhance environmental data management and predictive capabilities, thereby increasing transparency and efficiency. The study suggests that further development of DX may lead to a more effective realization of GX.

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Since the proposal of the RSA cryptosystem as an implementation of public-key cryptography proposed by Diffie-Hemann in 1976, public key cryptosystems became the essential infrastructure to ensure three basic elements of information security such as confidentiality, integrity, and availability in today’s advanced information society. Not only RSA cryptosystem but also the system using elliptic or hyper-elliptic curves, their security depend on the difficulties of order counting problems in each field. However, the algorithm proposed on the quantum computer by Shor enables to solve these types of problem in polynomial time order operations and threaten the securities. Thus a cryptographic system that is expected to maintain security in consideration of currently known algorithms on quantum computers and future possibilities called Post-Quantum Computer Cryptography (PQCC) is required. In this paper, among PQCC which is said to be unbreakable even with a quantum computer in a practical time, we consider one using self-dual error-correcting code over a integer module ring. We also refer to a decoding algorithm using Information set on the cryptosystem.

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In this talk, we will give some method of construction and classification of self-orthogonal and self-dual codes over rings of order four. We will also introduce the notion of duality for codes over non-unital rings, and will also discuss about quasi self-dual codes. This discussion is a compilation of some of my recent works with different co-authors.

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We introduce a non-unital and non-commutative ring Sm(F1), called ring of ordered sum over F2, the binary eld. We discuss linear codes over this ring, also known as Sm-codes, and their algebraic structure, particularly, their residue and torsion codes. We explore the generalized notion of duality of Sm-codes.

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Cronbach’s α coefficient is used for practical purposes to evaluate its value of 0 to 1. However, according to the definition formula, this value can also be negative. This article discusses how this situation can be used to improve test items, based on the mathematical properties of the formula.

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Given the importance of ensuring that medications are discontinued appropriately before surgery, particularly in　elderly patients, it is crucial to manage these medications to avoid potential impacts on blood pressure, heart rate, bleeding risk, and blood sugar levels. Therefore, in this paper, we emphasize the development of an application aimed at enhancing patient understanding and confirmation of the medications that should be discontinued preoperatively. This is essential for successful surgical outcomes and optimal anesthetic management.

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This study aims to enhance the effectiveness of medical education by exploring the application of multimedia teaching materials in surgical education. Using robot-assisted radical prostatectomy as a case study, we have introduced an AI Q&Asystem based on ChatGPT-4 into a previously developed multifunctional learning platform. This system integrates external knowledge bases and utilizes natural language processing technology to provide instant answers to students' questions, thereby offering personalized learning support and increasing the interactivity and specificity of the teaching materials. In the future, we plan to expand the content of the teaching materials to include more surgical cases to comprehensively validate the system's effectiveness in medical education.

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This paper explores the cultural heritage and influence of Manpukuji Temple and Master Ingen, focusing on their role in Sino-Japanese cultural exchange and how animation can be used to preserve and promote their legacy. Master Ingen, who founded Manpukuji Temple in the 17th century, introduced many Chinese cultural elements to Japan, including tea culture, vegetarianism, and artistic practices. The study uses historical research, field studies, and case analysis to understand the cultural activities at Manpukuji Temple today. It also examines how animation can make Master Ingen's story and cultural contributions more engaging and accessible. The animation project described uses traditional Chinese ink painting style to depict Master Ingen's journey and his impact on Japanese culture. The paper concludes that animation is an effective tool for cultural transmission. It makes traditional stories more appealing and helps in cultural education by attracting and engaging a wider audience. Future possibilities include using technologies like virtual reality (VR) and artificial intelligence (AI) to further enhance the learning experience.

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As Large Language Models continue to evolve, GPT-generated technology has significantly impacted various aspects　of human life, especially demonstrating unique value in the realm of game development. Game development, an　interdisciplinary field, relies on the close collaboration of individuals from diverse professional backgrounds, making the development process inherently complex and challenging. In this context, GPT-generated technology not only simplifies the development workflow but also substantially enhances efficiency. This study focuses on a game development team composed of six students, examining typical issues they encountered in short-term game development projects through their actual participation and systematic evaluation. It explores how GPT technology can be leveraged to address these challenges, aiming to improve students' learning efficiency and development experience in short-term projects.

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In education, it is considered important to take into account the personality and characteristics of each child, pupil, and student, and attempts have been made to implement educational practices that respond to this. However, when a single teacher is dealing with a large number of students, they are forced to adopt a uniform approach. In particular, at universities, education has traditionally been conducted in a one-way, teacher-centered manner, but the situation is changing with the advancement and spread of e-learning systems. Systems for understanding learners’ personalities and educational preferences and improving educational effectiveness are thought to be in the research stage, but basic theories have long been studied in the fields of psychology and pedagogy. This paper examines the relationship between the MBTI, a representative indicator of personality diagnosis in psychology, and the Felder-Silverman learning style model, which is widely used to understand learning styles.

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The use of the Internet for information gathering, including web browsing and social media, has become a common practice, and there has been a corresponding increase in demand for information gathering support by recommender systems. In our previous research, we developed a system that supports the collection of tourism-related information by utilizing the user's gaze information during web search and recommending search keywords related to tourism information that reflect the user's preferences. This is achieved by acquiring the text written at the gazing point on the screen [1]. In this study, we refined a methodology to determine a gazing point on a screen for the system. In addition, a new system is developed based on the preceding system to enhance the precision of personalization and incorporated a mechanism for acquiring image data. The modified system is reported in this paper.

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The research focuses on the development of a programming learning support web system with functionalities to identify errors in mixed grammars of multiple programming languages and errors in the use of double-byte characters, to check grammars from reserved words, and to display correct grammars. This study, another function was added to the existing system[1] to point out to programmers that they forget to write “include” statements in the C language. In addition, to enable real-time assistance, the system was modified to enable dynamic changes to the web pages. Furthermore, with the aim of improving the interface to make it easier for beginners to find errors, the differences in eye movement patterns between intermediate, advanced programmers and beginners were investigated during the correction of compilation errors.

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For the sustainable development in the agricultural sector, Japan is promoting the expansion of the area of conventional agriculture, i.e. environmental conservation agriculture that does not use pesticides or chemical fertilisers. In the paddy fields of the Hiki Hills region in northern Saitama Prefecture, reservoirs are formed at the head of eroded valleys to efficiently store rainwater and use it as a source of irrigation water for rice cultivation. The water storage system and the geographical location of the valley prevent the inflow of pesticides and chemical fertilisers. Paddy fields using the reservoirs are called 'yatsu-fields' in the region, and the farming form of yatsufields is known as yatsunuma agriculture. Yatsunuma agriculture was selected as a Japanese Nationally Important Agricultural Heritage Systems（J-NIAS）in 2023. However, paddy rice cultivation in valley rice paddies relies heavily on experience, as it cannot be controlled with pesticides and chemical fertilisers as in conventional cultivation. As a result, the retention rate of new farmers is low. In addition, Japanese farmers are rapidly ageing, and the amount of abandoned land in yatsuta fields is increasing year by year. Remote sensing (RS) has often been used in the agricultural sector, but has been limited to acquiring images at regional scales due to image scale limitations. The development of unmanned aerial vehicles (UAVs) has made it possible to acquire imagery at higher spatio-temporal resolutions than regional scales.

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This study aims to construct an evaluation model of nitrogen balance from a reservoir to a valley rice field by combining geo-informatics, chemical analysis, and biological analysis, targeting rice cultivated in Yatsuda (rice field in a valley) connected to a reservoir. First, the biomass of rice and weeds were obtained from UAV images, and the growth process of rice and weeds was grasped by organizing them in a GIS, and the biomass of rice and weeds was estimated separately to estimate the amount of nitrogen fixation in rice. Furthermore, the contribution of soil microorganisms to nitrogen fixation in paddy rice was qualitatively evaluated using soil microbial diversity activity values (BIOTREX), and a model was constructed to evaluate the nitrogen cycle originating from total nitrogen, including organic nitrogen supplied from reservoirs.

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“Structure and Function of the Human Body (Anatomy and Physiology)” is a basic subject for medical professionals, but many students have difficulty with it. The question of how to make knowledge of the subject take root and be converted into skills is a source of concern for teachers. Here, I 1) analyzed the use of Gagné’s nine events of instruction in lectures; 2) emphasized ways of relating to students and asking “loose” questions (pair-works and structured-group encounters (SGE)) by using a career counseling approach to lectures to promote job understanding; and 3) performed group work describing organs and blood vessels on a “diagrams of the body.” However, with the expansion of COVID-19 infection starting in FY 2020, the need arose to distance-teach Structure and Function of the Human Body. With “student engagement” in mind, the application of 1), 2), or 3) produced significant improvements in final exam marks, and the online use of Google Classroom produced marks that were equal to those produced by 1). I intend also to report the results of studies currently under way of the use of VR/AR teaching materials.

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This study was conducted to investigate rubrics: their usefulness in higher education and their evaluation by students. Specifically, the study compares the usefulness of returning rubric evaluations in two formats: face-to-face and using the Microsoft Teams (Microsoft Corp.) assignment feature. The survey was administered to female students enrolled in programming courses during 2018–2024, asking them to rate the rubric usefulness on a scale of 1 to 10. The analysis revealed no significant difference in assigned usefulness ratings between the two groups. However, results showed that establishing individual evaluation criteria contributed significantly to the perceived usefulness of the rubrics. Grade notifications and feedback had no marked effect on the usefulness ratings of the rubrics. These findings suggest that evaluation criteria must be defined clearly to ensure the effective use of rubrics.

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Generative AI is easy to operate and can be used for a variety of purposes, so I think it is essential knowledge for university students who will be entering the workforce and working in business within the next few years. This research aims to deepen the understanding of this Generative AI and research education to make use of it. The results of the exercises will be utilized in building an educational system, and the introduction of new methods will also be considered. It's something that will happen.

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Uncertainty about the future is an obstacle to economic growth because it discourages consumption. Since 2022, prices have been rising due to the depreciation of the yen against the U.S. dollar. This makes life difficult for many Japanese. Are students worried about the future? The purpose of the first survey was to determine “the extent to which students are worried about their future. As a result, when asked, “Are you worried about your future?” 54.7% said they did, and 39.1% said they felt a little, for a total of 93.8%.Many students feel anxious about their future. The second survey was designed to find out if acquiring skills would reduce anxiety about the future. The results showed that 34.3% said it would decrease and 51.4% said it would decrease a little, giving a total of 85.7%, when asked if mastering economics would reduce their anxiety about the future. Many students are less worried about their future if they receive an education. Education plays an important role in Japan's economic growth. We will attempt to identify what kind of education decreases students' anxiety about their future.

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The focus of this paper is on next-generation psychology, such as virtual reality psychology, AI and robot psychology, etc. In the field of ICT, the paper focus on reports on virtual reality, the metaverse, and their collaboration with AI and robots. As virtual reality-related equipment has been gradually improving, the psychology will likely become even more important in the future.

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Japan's population aging rate is 29.1%, a high percentage. Previous research approaches to the elderly have mainly focused on topics related to the medical and welfare fields of the elderly. Prior research has shown that the elderly are known to prefer positive information and that focusing on positive information can stabilize their mood. In this study, therefore, we analyze the data on complaints posted by the elderly, targeting complaints, a comment that tends to be negative, and clarify the characteristics of information transmission by the elderly.

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For medical staff, proficiency in medical English is paramount. The increasing internationalization of the healthcare sector, driven by rising inbound medical tourism, necessitates effective communication with foreign patients and access to the latest global medical advancements. As integral members of medical teams, healthcare professionals require medical English to collaborate seamlessly with colleagues and exchange critical information. This includes comprehending complex medical terminology, abbreviations, and documents, as well as delivering presentations at international conferences. Mastering medical English enhances the quality of care provided by medical staff and ultimately improves patient outcomes. This study outlines a medical English learning system developed using Google Forms and Spreadsheets to facilitate medical English acquisition among healthcare professionals, building upon a previously created prototype.

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In our laboratory, four types of computerised large shogi varients are currently used for playing games. This paper describes the design and development of the game server among the various functions of the computerised large Shogi. The communication protocol does not include piece type information, but only the position coordinates of the pieces before and after a move. If the coordinates do not change before and after a move, it is assumed that an Igui function has been played, and the position coordinates of enemy pieces captured by IGUI are added after the normal data. As there is no piece type information, this protocol is easy to apply to various types of large shogi varients and is highly versatile. It is also useful in that it is flexible to rule changes.

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The literature on Ban Sugoroku is scattered, and much of it is written in Kuzushiji, making them difficult to decipher unless one is an expert. One example that can be cited is the recent discovery of “Sugoroku Youki”. In recent years, AI-based Kuzushiji deciphering apps have been gaining attention. This paper examines whether Kuzushiji recognition AI can be utilized for the transcription of ancient literature and aims to analyze the first part of “Sugoroku Youki”.

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This study attempted to convert the arrival range and arrival time of lava flows marked on the volcano disaster prevention map, created in raster format, into a vector data format that can be analyzed in a GIS. Next, by superimposing the distribution of evacuation sites at the time of a disaster (lava flow) and people in need of assistance during a disaster (in this study, this refers to the elderly) on the information mentioned above, we attempted to evaluate whether the evacuation sites are appropriate for people in need of assistance during a disaster. The results showed that evacuation centers were adequately set up in areas with many people requiring assistance in times of disaster, and the number of people required for rescue operations (the total number of people aged 15 and over and those aged 65 and under) was sufficient. On the other hand, in suburban areas where the number of people in need of assistance during disasters is low, it was necessary to set up shelters appropriately and increase the number of rescue workers.

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