The demand for high energy efficiency in IoT devices continues to increase, necessitating the development of low energy consumption techniques to enhance the computation performance of these devices. In this study, we present a CMOS clock generator that operates at high operating voltage, achieves low frequency, and exhibits low power (LP) consumption, thus obviating the need for scaling-unfriendly step-down converters. The avoidance of step-down converters, which require passive components in their design, facilitates the development of scaling-friendly IoTs. The architecture of the prototype chip is composed of a voltage stacking and charge recycling design, which is achieved by the implementation of stacked oscillator and multiple frequency dividers in a configuration. The fabrication of the prototype chip is conducted using a 65-nm CMOS process. This work presents two configurations that are based on the concept of voltage stacking. The first configuration prioritizes LP consumption, yielding a clock generation of 2.09 Hz with a power of 0.22 nW at a voltage supply of 1.2 V and an operating range of 1.2–2.2 V. Notably, this configuration represents the lowest power achieved at a foundry-recommended nominal voltage in a sub-10-Hz clock generator. Another configuration is oriented toward generating low-frequency output signals, and the test chip attains an output frequency of 0.079 Hz and a supply voltage range of 0.88–1.3 V. The proposed architecture exhibits potential benefits in advanced technology nodes, particularly in the context of technology scaling.

In this study, we developed LingoAI with the aim of solving the limitations that have arisen in chatbot language learning. The proposed method automatically generates natural responses in real time according to the learner’s inputs (i.e., voice and text), and a 3D character with facial expression changes and lip-sync is output as voice. This paper presents a functional overview and implementation of the LingoAI system.

Thermal display is a useful device for representing the haptic sense; however most such devices are used in a sitting position. We have used an immersive projection technology (IPT) display for scientific visualization, which is very useful for comprehending complex phenomena. However, in the IPT, the observer generally watches and controls 3D objects in standing position. Therefore it is necessary to develop a thermal display that can be used in a standing position. In addition, in scientific visualization, the response time is very important for observing physical phenomena, especially in dynamic numerical simulation results. One solution is to provide two types of thermal information: information about the rate of thermal change, and information about the real temperature. Using the two types of information, the observer can recognize the change and the real thermal value immediately.

We propose a new room-sized immersive projection display. The display consists of a cylindrical screen that can be moved horizontally and vertically, allowing the user to easily change his/her field of view by moving the screen to any angle. The angle of the screen is measured by a motion sensor, and the projected stereo images are changed in response to the measured angle.

We propose a new task scheduling algorithm for timed-functional simulation of concurrent software tasks. It attains efficiency by reducing the frequency of context-switching between concurrent tasks. It also provides a high-degree of portability in the sense that it only needs the underlying system to support a very small number of primitives. We provide a concrete implementation built on top of the SystemC scheduler and show some results of preliminary evaluation

The need for incremental algorithms for evaluating database queries is well known, but constructing algorithms that work on object-oriented databases (OODBs) has been difficult. The reason is that OODB query languages involve complex data types including composite objects and nested collections. As a result, existing algorithms have limitations in that the kinds of database updates are restricted, the operations found in many query languages are not supported, or the algorithms are too complex to be described precisely. We present an incremental computation algorithm that can handle any kind of database updates, can accept any expressions in complex query languages such as OQL, and can be described precisely. By translating primitive values and records into collections, we can reduce all query expressions comprehension. This makes the problems with incremental computation less complicated and thus allows us to decribe of two parts: one is to maintain the consistency in each comprehension occurrence and the other is to update the value of an entire expression. The algorithm is so flexible that we can use strict updates, lazy updates, and their combinations. By comparing the performance of applications built with our mechanism and that of equivalent hand written update programs, we show that our incremental algorithm can be iplemented efficiently.