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      • KCI등재

        매복된 상악 전치부의 자가이식 치험례

        김신,음종혁,이애련,서수정,김주미,김주영,황보민 大韓小兒齒科學會 1994 大韓小兒齒科學會誌 Vol.21 No.2

        The autotransplantation procedure were performed for the cases with impacted maxillary anterior teeth, which were thought unrealistic by the treatment with surgical exposure and orthodontic traction into the arches. The results were as follow : 1. As the treatment with autotransplantation is the last resort, the case indicated should be selected cautiously by adequate case analysis. 2. In order to reduce postoperative complication, damages to periodontal ligaments and adjacent bony structures should be minimized by conservative surgical procedures. 3. After autotransplantation procedures, postoperative endodonic treatment and continuous follow-up check with clinical and radiographic examination should be followed. Although the autotransplantation procedure is not the treatment of choice in most cases, it was thought to be a good alternative in certain cases when orthodontic treatment is unrealistic with continuous study to overcome the handicaps.

      • KCI등재

        Vision Sensor-Based Driving Algorithm for Indoor Automatic Guided Vehicles

        Quan Nguyen Van,Hyuk-Min Eum,Jeisung Lee,Chang-Ho Hyun 한국지능시스템학회 2013 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.13 No.2

        In this paper, we describe a vision sensor-based driving algorithm for indoor automatic guided vehicles (AGVs) that facilitates a path tracking task using two mono cameras for navigation. One camera is mounted on vehicle to observe the environment and to detect markers in front of the vehicle. The other camera is attached so the view is perpendicular to the floor, which compensates for the distance between the wheels and markers. The angle and distance from the center of the two wheels to the center of marker are also obtained using these two cameras. We propose five movement patterns for AGVs to guarantee smooth performance during path tracking: starting, moving straight, pre-turning, left/right turning, and stopping. This driving algorithm based on two vision sensors gives greater flexibility to AGVs, including easy layout change, autonomy, and even economy. The algorithm was validated in an experiment using a two-wheeled mobile robot.

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