Sequence-Pair, which is a topological representation for packing rectangles, was invented in Japan and has become one of the standard electronic design automation（EDA）techniques used in the physical designs of integrated circuits. In this article, I try to share how people started this unique research in a new university in 1994, what efforts were taken later in the industry to apply the idea in chip designs, and what challenges still remain today. If I contributed some parts in this history, it was mostly because I was happened to be a student with some work experience in the original research team. Thus, I hope that this article motivates young engineers in the industry, and refreshes them academically.

The recent success of AI and machine learning has been based on the background that big data are available. On the other hand, as spreading application fields of machine learning, there is a growing need to apply machine learning to small data collected at a high cost. In this paper, we introduce machine learning frameworks such as sparse modeling and Bayesian modeling, which are suitable for small data. In addition, we introduce transfer learning for deep neural networks to deal with small data, and active learning and Bayesian optimization for efficient data acquisition. We discuss not only user aspects of machine learning but also some mathematical problems.

Sound source separation, which separates multiple sound sources from a mixture, has continued to evolve by incorporating beamforming techniques in wireless communication, signal processing, optimization techniques based on probabilistic models, and deep learning techniques. This paper prondes an overview of sound source separation techniques for multiple microphones based on a spatial model and a probabilistic sound source model, for a single microphone with deep learning, and for multiple microphones using a deep-learning-based sound source model and a spatial model.

The number of transistors per semiconductor chip has consistently and exponentially increased over the past 50 years. Therefore, a larger amount and more complex functions can be implemented in the chip. In order to tackle this trend, design methodologies have evolved from being schematic-based to being more abstract language-based, and design productivity has been increased through the reuse of design assets and the adoption of standard bus interfaces. Similarly, functional verification can no longer keep up with conventional verification methods, mainly because verification coverage and productivity issues have become critical. In this paper, verification techniques, methodologies, and the history of standardization to resolve these verification issues are described. On top of these, new verification items that arise with asynchronous and low-power consumption designs, as well as issues that require more functional verification effort, such as security measures and compliance with functional safety standards and their countermeasures, are descussed. Verification technologies that have been developed in line with leading software development technologies and look ahead to the possibilities for future advancements in verification technologies.

Explainability is a crucial component of natural language processing（NLP）systems. Explanation is communication, and research on explainability is expected to address notions such as communicative goals and common grounding. Automated Writing Evaluation（AWE）is an ideal field to contribute to such research. AWE refers to NLP tasks designed to support human learners by evaluating the quality of text produced in educational contexts, such as written answers to questions and argumentative essays, and providing constructive feedback. Since explanations are vital in educational assessment, pedagogical literature is rich with insights that can facilitate research on explainability in AWE systems. In this paper, what style of explanations are pedagogically suitable and technologically feasible at each layer of language production, ranging from content planning to surface realization, is explored and open research issues are identified to encourage researchers to enter this emerging field.

Information Centric Networking（ICN), an information-oriented network that focuses on transmitted and received contents, has been attracting attention as an alternative to the host-oriented network based on Internet Protocol（IP). Many protocols have been proposed for the practical use of ICN, and the implementation of ICN in wired networks has begun. On the other hand, many problems still remain in applying ICN to the mobile network environment because of the unique characteristics of mobile networks, such as terminal mobility and power consumption limitations. In this paper, we provide an overview of ICN and its basic features, and discuss the problems and solutions related to its application to mobile network environments. We also introduce methods that have been proposed so far and discuss their effectiveness determined on the basis of the results of performance evaluations.

In this paper, we describe the history and background of the Code of Ethics of the Institute of Electronics, Information and Communication Engineers（IEICE), which is the largest society for electronics, information and communication engineers in Japan. The IEICE members who established and revised this code did so after examining what a code of ethics should be and considering the social, technological, and ideological aspects of the institute's goals and operations. In this work, the history of the Code of Ethics of the IEICE is divided into three periods focuing on the development of the character of the ethical code and its relationship to the milieux of the institute:the foundation period when the code reflected the ethics of electronic networks;the 2011 revision period, when the code was made to reflect engineering ethics instead;and the 2023 re-revision period when ethics for an age of diversity and communication among various actors were added to the code.