Magnesium alloys, among various non-ferrous metals, are utilized in diverse fields from the automotive industry to aerospace due to their light weight and excellent specific strength. In the previous Part I study, fiber laser BOP experiments were conducted to derive basic welding characteristics and appropriate bu竹 welding conditions. Subsequently, in the Part II experiment, butt welding was performed, and through tensile tests, hardness tests, and cross-sectional observations, it was found that at laser power of 2.0 kW and welding speed of 50 mm/s, 93% of the base metafs tensile strength and 63.4% of its elongation could be achieved. In this Part III experiment, the microstructures of the base metal and the center of the weld were observed in butt-welded specimens. Through this, laser power and welding speed, on the mechanical behavior and microstructure of magnesium alloys were analyzed

여섯 성분의 지진에 의한 지반속도를 받는 회전기계-기초시스템의 거동을 해석하기 위해 회전기계-기초시스템을 회전원판, 회전축, 윤활유막 베어링, 주각, 그리고 뼈대기초로 구성된 것으로 이상화한다. 이때 회전기계-기초의 동적거동을 나타내는 지배운동방정식은 Gyroscope 효과와 Coriolis 효과, 윤활유막의 동적특성 그리고 지반의 병진과 회전거동을 고려하여 얻는다. 지반의 회전거동, Gyroscope 효과, 그리고 Coriolis 효과들이 회전기계-기초시스템의 전체거동에 미치는 영향을 해석예젤르 통해 고찰한다. 해석결과 회전기계-기초시스템의 지진해석에 있어서 지반의 회전거동 성분과 Gyroscope 효과의 영향을 포함하여야함을 알 수 있다.

Body gesture Recognition has been one of the interested research field for Human-Robot Interaction(HRI). Most of the conventional body gesture recognition algorithms used Hidden Markov Model(HMM) for modeling gestures which have spatio-temporal variabilities. However, HMM-based algorithms have difficulties excluding meaningless gestures. Besides, it is necessary for conventional body gesture recognition algorithms to perform gesture segmentation first, then sends the extracted gesture to the HMM for gesture recognition. This separated system causes time delay between two continuing gestures to be recognized, and it makes the system inappropriate for continuous gesture recognition. To overcome these two limitations, this paper suggests primitive body model encoding, which performs spatio/temporal quantization of motions from human body model and encodes them into predefined primitive codes for each link of a body model, and Selective/Asynchronous Input-Parallel State machine(SAI-PSM) for multiple-simultaneous gesture recognition. The experimental results showed that the proposed gesture recognition system using primitive body model encoding and SAI-PSM can exclude meaningless gestures well from the continuous body model data, while performing multiple-simultaneous gesture recognition without losing recognition rates compared to the previous HMM-based work.