Python is gaining attention as a fundamental programming language for machine learning and data science. In this paper, we describe a detailed Python approach to nonlinear problems, especially the bifurcation problems of periodic solutions. It is a highly readable implementation of the bifurcation algorithm, independent of the computer and the operating system, and it allows interactive trial-and-error processing. We describe the advantages of Python for bifurcation problems with some illustrated codes. We also show a compact implementation of computation for Neimark-Sacker bifurcation using the bialternate product and an automated process for generating the Hessian using Sympy.

The direct and active use of explosively evolved information technology in our physical daily lives can realize many advanced information services, contributing to the qualitative improvement of our individual life and, as an extension, our entire society. In such services with the active interaction between cyber and physical spaces, integrated systems consisting of numerous integrated circuits always exist as a physical entity at the boundary between the two spaces. In this paper, the required interface functionalities for the integrated system as the physical entity gateway connecting the boundaries are reviewed, and the physical shape of the efficient integrated system to realize these functionalities is determined. The direction of future research on such an interfacing integrated system is also discussed.

Tapping inspection is generally used for the inspection of concrete structures, but as the number of skilled workers decreases, the efficiency of inspection work must be improved. Various methods have been developed, but only a few of them have been linked to the improvement of work efficiency, because they must be used close to the inspection surface. Therefore, a noncontact acoustic inspection technique using acoustic-irradiation-induced vibration and a laser Doppler vibrometer has been developed, which enables a noncontact inspection similar to a hitting inspection from a long distance. Since verification experiments on specimens and actual structures have already been conducted and the effectiveness of this technique has been clarified, the latest trends will be introduced.

The application of extended reality/cross reality technologies such as virtual reality (VR), Mixed Reality (MR), and Augmented Reality (AR) is expanding in the medical field, and the market size is expected to grow markedly from around 2020. Various applications have been proposed, including surgical support, treatment, diagnosis support, rehabilitation, medical education, and informed consent. In this paper, recent medical applications of XR technology.

To realize a stable power supply, power grids have been developed and controlled by highly reliable communications. In recent years, to achieve a carbon neutral society, power grids have been subject to great changes to maximize the use of renewable energy sources, and a stable operation of the power girds has also been required. In this paper, the future of highly reliable communications that support electric power networks and expectations for them is described.

In this article, the challenges and future prospects in biometrics modalities are discussed. First, typical biometric modalities are introduced. Next, as current challenges in biometrics, a privacy issue and spoofing issues are discussed. For resolving the spoofing issue in system-user management, continuous authentication is necessary for which new biometrics modalities such as brain waves and intrabody propagation signals are introduced. Finally, as future prospects, smell- and taste-based authentication and some new perspectives on biometrics are introduced.

Recently, constructing and operating platforms have achieved secure data sharing and/or usage between organizations (i.e., cloud services and blockchain networks). According to the latest trends, studies are under way in various fields to improve internal operations and generate new business values using the above platforms. In particular, organizations that use machine learning in their internal processes and/or services focus on federated learning. Federated learning is a technology that can train machine learning models using the datasets stored at different locations without sharing these datasets. Recently, the usage of this technology to improve the efficiency/quality of marketing and internal operation has been increasingly studied. In this paper, we introduce the concept of federated learning and show the recent trends in attack models and their countermeasures and implementation platforms.