In this study, a well-shaped microelectrode array (MEA) for fabricating a high-density complementary metal-oxide semiconductor amperometric electrochemical sensor array was designed and verified. By integrating an auxiliary electrode with the well-shaped structure of the MEA, the footprint was reduced and high density and high resolution were also achieved. The results of three-dimensional electrochemical simulations confirmed the effectiveness of the proposed MEA structure and possibility of increasing the density to four times than that achieved by the conventional two-dimensional structure.

Several kinds of capacitor-less DRAM cells based on planar SOI-MOSFET technology have been proposed and researched to overcome the integration limit of the conventional DRAM. In this paper, we propose the Floating Body type DRAM cell array architecture with the Vertical MOSFET and discuss its basic operation using a 3-D device simulator. In contrast to previous planar SOI-MOSFET technology, the Floating Body type DRAM with the Vertical MOSFET achieves a cell area of 4F2 and obtain its floating body cell by isolating the body from the substrate vertically by the bottom-electrode. Therefore, the necessity for a SOI substrate is eliminated. In this paper, the cell array architecture of Floating Body type 1T-DRAM is proposed, and furthermore, the basic memory operations of read, write, and erase for Vertical type 1 transistor (1T) DRAM in the 45 nm technology node are shown. In addition, the retention and disturb characteristics of the Vertical type 1T-DRAM are discussed.

The excellent performance of the 10 nm gate Multi-Nano-Pillar type (M-) Vertical MOSFET has been numerically shown for the first time. It is made clear that the M-Vertical MOSFET, in comparison with the conventional Single Pillar type (S-) Vertical MOSFET, has achieved an increased driving current by more than 2 times, a nearly ideal S-factor, and a suppressed cutoff-leakage current by less than 1/60 by suppressing both the short channel effect and the DIBL effect. Moreover, mechanisms of these improvements of the M-Vertical MOSFET are made clear. From all of the above, it is shown that the M-Vertical MOSFET is a key device candidate for future high speed and low power LSI's in the sub-10 nm generation.

The construction of photo-realistic 3D scenes from video data is an active and competitive area of research in the fields of computer vision, image processing and computer graphics. In this paper we address our recent work in this area. Unlike most methods of 3D scene construction, we consider the generation of virtual environments from video sequence with a video-cam's forward motion. Each frame is decomposed into sub-images, which are registered correspondingly using the Levenberg-Marquardt iterative algorithm to estimate motion parameters. The registered sub-images are correspondingly pasted together to form a pseudo-3D space. By controlling the position and direction, the virtual camera can walk through this virtual space to generate novel 2D views to acquire an immersive impression. Even if the virtual camera goes deep into this virtual environment, it can still obtain a novel view while maintaining relatively high resolution.

This paper proposes a new method that can robustly recover 3D structure and 3D motion of 3D moving objects from a few multi-views. It recovers 3D feature points by obtaining intersections of back-projection lines which are connected from the camera's optical centers thorough projected feature points on the image planes corresponding to the different cameras. We show that our method needs only six views to suppress false 3D feature points in most cases by discussing the relation between the occurrence probability of false 3D feature points and the number of views. This discussion gives us a criterion to design the optimal multi-camera system for recovering 3D structure and 3D motion of 3D moving objects. An experimental multi-camera system is constructed to confirm the validity of our method. This system can take images from six different views at once and record motion image sequence from each view over a period of a few seconds. It is tested successfully on recovering the 3D structure of Vinus's plaster head and on recovering the 3D structure and 3D motion of a moving hand.