The three-color triangle problem is a mathematical quiz: Consider regular hexagonal tiles arranged in an inverted triangle shape of n stages, and paint them in three colors so that any three adjacent tiles have the same color or all different colors. The quiz asks to determine the general form of n that satisfies the condition that the colors for the three vertices of the inverted triangle are always the same or different. This quiz was given in the column “Seeking an elegant answer” of the journal “Suugaku Seminar”, and it was shown that the general form of n is 3^k. The paper implements a formalized proof for the three-color triangle problem in Coq. It gives a proof for the problem on paper, and then discusses the devised points for formalization and the benefits obtained by the formal proof on Coq compared to the proof on paper.

In this study, we focus on incremental class continual learning for image classification, and improve the replay method that retains a part of the data given in the past and uses it to train a newly increased class. In the existing studies of replay methods, the number of data to be retained is fixed for each class. In this study, we propose a method to control the capacity of the number of core data according to the difficulty of each class, and a continual learning method CC-replay using this method. We also propose a continuous learning method, cc-replay, which uses the calculated number of core data per class. In our experiments, we evaluate the performance of cc-replay based on accuracy and training time on several benchmarks, and discuss the behavior of cc-replay when the size of the dataset and the similarity between classes are changed.

We propose Waffle, a novel experiment workflow control framework for large-scale social simulation experiments utilizing high-performance computing clusters (HPCCs). Advancement in computer technology has enabled large-scale experiments in computational social science. However, with the expansion in the scale of the experiment, the cost of manually managing the experiment increases considerably. To address this issue, we provide the experiment workflow control framework that uses a recursive meta-level control mechanism and a chain of procedures by the guarded suspension to automate management. The framework manages task queuing in parallel processing, experimental results, and HPCC jobs. We evaluate the functionality and efficiency of the proposed framework using a case study, which is a data assimilation experiment involving virus infection simulation. The framework supports evidence-based policymaking against long-term urban planning or emergencies, such as pandemics, because of the ability to handle large-scale experiments.

Siv3D, a C++ framework for information visualization and interaction, has incorporated more than 5,500 additions and improvements to the public repository since it became open-source in 2016. They include various new features and API design revisions based on the recent evolution of hardware, development tools, and language specifications, verification of user use cases, and other interesting examples, as well as support for C++17/C++20. This paper presents design choices, changes, and dissemination efforts in the five years since Siv3D became OSS, and shares insights useful for the design and operation of a modern C++ framework for information visualization and interaction.

System failures are increasing and problems due to unexpected causes continue to occur. Safety is defined as "freedom from intolerable risk," New analysis methods and accident models for software-centric systems are needed to prevent accidents and losses that could become intolerable risks. This paper describes the original concepts and methods of STAMP (System Theoretic Accident Model and Processes) , resilience engineering, and safety case as new safety analysis methods and models. It also introduces the procedures and characteristics of CAST (Causal Analysis using System Theory) , a new accident analysis method that models from the perspective of the entire system, including people and organizations.

In recent years, as the IoT has become popular, there are more requirements for sharing operation/mechanisms of IoT devices, such as Arduino and M5Stack. In addition, because of the corona disaster, many educational institutions adopted online lectures, such as on-demand tutorial videos and live lectures using video conference systems. For IoT programming education, these methods have problems such as lack of linkage with real-world devices and source codes. In this study, we propose a system called “IoTeach”, which supports learning of IoT programming by attaching a script language on sequential contents such as videos and slides shared on the Web. Thus, the IoTeach can link videos and slides with real-world IoT devices and source code. In this paper, we describe the concept and implementation of the system. We also perform a basic evaluation and discuss challenges and prospects.

Wearable devices for life-logging and healthcare have been studied, but the need for frequent charging imposes inconvenience for long-term use. Integrating textile-based wireless chargers (i.e., coil) into clothing enables sustainable wearable computing by charging the on-body devices in use. However, the electromagnetic field generated by conventional coil chargers strongly interferes with the human body, and the high resistance of conductive threads leads to inefficient power delivery. This paper presents Meander Coil++, enabling safe, energy-efficient, and body-scale wireless power delivery. Meander Coil++ uses a wiring pattern that suppresses electromagnetic exposure to the human body without compromising power delivery performance and a liquid-metal-based low-loss conductive cord. With these advancements, Meander Coil++ could transmit up to 2.5W power to on-body devices with 1/400 size of charging area at 40% AC-to-AC efficiency while complying with international safety guidelines regarding electromagnetic exposure.