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Assessment on adequate dosage of superplasticizer in eco-friendly ultra-high performance concrete (UHPC) containing industrial by-products was carried out from the standpoint of workability. Various types of industrial by-products, including blast-furnace slag, coal bottom ash and rapid-cooled electric arc furnace oxidizing slag, were utilized, and the effects of dosage of superplasticizer on the workability and strength of UHPC containing the by-products were evaluated. By utilizing the by-products, the workability of UHPC was improved and required dosage of superplasticizer was reduced. In addition, the material cost for UHPC with by-products was decreased due to reduced dosage of superplasticizer.

Recently, the researches of object tracking and recognition using Microsoft's Kinect are being actively studied. In this environment human hand detection and tracking is the most basic technique for human computer interaction. This paper proposes a method of improving the accuracy of the detected hand region's boundary in the cluttered background. To do this, we combine the hand detection results using the skin color with the extracted depth image from Kinect. From the experimental results, we show that the proposed method increase the accuracy of the hand region detection than the method of detecting a hand region with a depth image only. If the proposed method is applied to the sign language or gesture recognition system it is expected to contribute much to accuracy improvement.