We present an approach and a web-based system implementation for modeling shapes using real distance functions. The system consists of an applet supporting the HyperFun modeling language. The applet is extended with primitives defined by Euclidean distance from a point to the surface of the shape. Set-theoretic operations (union, intersection, difference) that provide an approximation of the Euclidean distance to a shape built in a constructive way are introduced. Such operations have a controllable error of the exact Euclidean distance to the shape and preserve C1 continuity of the overall function, which is an important condition for further operations and applications. The proposed system should help model various shapes, store them in a concise form, and exchange them easily between different entities on a network. The applet offers also the possibility to export the models defined in the HyperFun language to other formats for raytracing or rapid prototyping.

With the development and spread of Internet of Things (IoT) technology, various kinds of data are now being generated from IoT devices. Some data generated from IoT devices depend on geographical location and time, and we refer to them as spatio-temporal data (STD). Since the “locally produced and consumed” paradigm of STD use is effective for location-dependent applications, the authors have previously proposed a vehicle-based STD retention system. However, in low vehicle density environments, the data retention becomes difficult due to the decrease in the number of data transmissions in this method. In this paper, we propose a new data transmission control method for data retention in the low vehicle density environments.

A reverse mode liquid crystal (LC) display has been investigated. A driving voltage strongly depends on a morphology which changes by reactive mesogens, photo initiators and LCs. It becomes higher when the domain size of the liquid crystal and the particle of the polymer reactive mesogen are smaller.

As in other fields, the automatization of railway maintenance work is a firm requirement. The authors have developed a system detecting obstacles around a railway for practical railway inspection. The system is based on an original laser-sectioning method and characterized by high accuracy with wide view and in-motion operation. It was confirmed that a static calibration was performed at an accuracy of within 5 mm. Furthermore, a theoretical estimation predicted that dynamic errors can be eliminated within a resolution of 4 mm by means of rail movement detection. In field tests on the Chuo Line, facilities were successfully inspected at speeds up to 40km/h.