Miniaturized inertia Generators as power supplies for small-caliber fuzes

This paper describes miniaturized inertia generators for converting mechanical energy into electrical energy for military applications, especially as power supplies for electrical fuzes. In order to minimize the volume of the generators, our design adopted a ring-shaped magnet enclosing a coil assembly. The inertia generators are intended not to ignite an electrical detonator but to charge a capacitor that drives the electric circuit of fuze. A mechanical safety system, a shear plate, is used as a release mechanism for the inertia generators to prevent them from operating accidentally. We designed the inertia generators by using the simulation results of an electromagnetic analysis tool. In an experimental study, we performed safety tests on the shear plate and firing tests of the fabricated inertia generators. The present inertia generators show that a voltage of 14.2 V was charged on a capacitor of 30 /spl mu/F within the charging time of 0.68 ms and the critical acceleration for safety was 5000 G, verifying that the inertia generators can be used as power supplies for small-caliber electrical fuzes.     

Improved reliability of low-temperature polysilicon TFT by post-annealing gate oxide

We have investigated the electrical characteristics of gate oxide films deposited by plasma enhanced chemical vapor deposition (PECVD) with respect to gate oxide integrity (GOI) and its reliability. In the investigation, post-annealed gate oxide was compared with as-deposited oxide. It was shown that the characteristics of GOI strongly depended on the charge trapping characteristics and deep level interface states generation under FN stress, which was remarkably improved by post-annealing after gate oxide deposition. Improved FN stress and hot carrier stress reliability of CMOS devices implemented on the glass substrate are also discussed.     

Effect of seepage force on tunnel face stability reinforced with multi-step pipe grouting

Tunneling in difficult geological conditions is often inevitable especially in urban areas. Ground improvement and reinforcement techniques are required to guarantee safe tunnel excavations and/or to prevent damage to adjacent structures. The steel pipe-reinforced multi-step grouting method has been recently applied to tunnel sites as an auxiliary technique in Korea for impermeabilization in underwater tunnels as well as for reinforcement. However, this technique has been usually employed empirically without much understanding with regard to its effect on the tunnel safety. In this study, the face stability with steel pipe-reinforced multi-step grouting in underwater tunnels was evaluated by simultaneously considering two factors: one is the effective stress acting on the tunnel face calculated by limit theorem and limit equilibrium method; the other is the seepage force obtained by means of numerical analysis. This study revealed that the influence of the steel pipe-reinforced multi-step grouting on the support pressure required for the stability of the tunnel face in dry condition is not significant while there is relatively a significant reduction in seepage forces by adopting the technique in the underwater tunnel. The effect of permeability anisotropy on the seepage force acting on the tunnel face was also assessed by conducting a coupled analysis.     

Effective detection of exposed target regions based on deep learning from multimedia data

With the development of high-performance visual sensors, it has been very easy to obtain a variety of image data. Of these image data, human face regions contain personal information to distinguish one from the others. Therefore, it is important to accurately detect unhidden face regions from an input image. This paper proposes a method of robustly detecting human face regions from an input color image with the use of a deep learning algorithm, one of the machine learning algorithms. The proposed method first transforms the RGB color model of an input image to the YC_bC_r color model, and then removes other regions than face regions to segment skin regions with the use of the pre-learned elliptical skin color distribution model. Subsequently, a CNN model-based deep learning algorithm was applied to robustly detect human face regions from the detected skin regions in the previous step. As a result, the proposed method segments face regions more efficiently than an existing method. The face region detection method proposed in this paper is expected to be usefully applied to practical areas related to multimedia data processing, such as video surveillance, target blocking, image security, visual data analysis, and object recognition and tracking.

     

Effect of tunnel advance rate on seepage forces acting on the underwater tunnel face

In this paper, the effect of seepage forces arising from the groundwater flow on the tunnel face stability was studied for underwater tunnels. The groundwater flow equation was solved and the seepage forces acting on the tunnel face were calculated using the upper bound solution in limit analysis. Especially, the effect of tunnel advance rate on the seepage forces and thus on the tunnel face stability was studied. A finite element program to analyze the groundwater flow around a tunnel with the consideration of tunnel advance rate was made. Example problem showed that the seepage force is greatly influenced by the tunnel advance rate in case of less permeable ground. Finally, a rational design methodology for the assessment of support pressures required for maintaining the stability of the tunnel face was suggested for underwater tunnels.     

Robust hand pose estimation using visual sensor in IoT environment

The Journal of Supercomputing - In Internet of Things (IoT) environments, visual sensors with good performance have been used to create and apply various kinds of image data. Particularly, in the...     

Micro grooving simulation and optimization in the roughing stage

The micro pattern machining on the surface of a wide mold is not easily simulated and optimized using conventional methods. This paper represents the micro pattern cutting simulation software. The software simulates micro pattern grooving in 3D geometry, predicts the cutting force and optimizes the time factor in the roughing stage. The v-groove for prism and pyramid patterns and the rectangular groove for rectangular and pillar patterns are simulated. The code of this program is built using visual C++ and OpenGL.     

Performance of a coal gasification pilot plant with hot fuel gas desulfurization

A coal gasification pilot plant operation with hot fuel gas desulfurization (HGD) was performed taking two coals (Indonesian ABK and MSJ) that differ in their carbon and sulfur contents. A dry-feeding entrained-bed type gasifier was used for gasification with oxygen and capable of operating at 30 bar pressure and 1,550 °C. The HGD unit consisted of a transport desulfurizer, a bubbling regenerator and a multi-cyclone. Attention was focused on attaining high carbon conversion and cold gas efficiency in the entrained bed reactor and the sulfur removal efficiency of the hot fuel gas desulfurization unit. The optimum conditions for achieving high performance of the operation are reported.