• ETRI Journal
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• v.37 no.4
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• pp.787-792
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• 2015

To accomplish a high-speed test on low-speed automatic test equipment (ATE), a new instruction-based fully programmable memory built-in self-test (BIST) is proposed. The proposed memory BIST generates a highspeed internal clock signal by multiplying an external low-speed clock signal from an ATE by a clock multiplier embedded in a DRAM. For maximum programmability and small area overhead, the proposed memory BIST stores the unique sets of instructions and corresponding test sequences that are implicit within the test algorithms that it receives from an external ATE. The proposed memory BIST is managed by an external ATE on-the-fly to perform complicated and hard-to-implement functions, such as loop operations and refresh-interrupts. Therefore, the proposed memory BIST has a simple hardware structure compared to conventional memory BIST schemes. The proposed memory BIST is a practical test solution for reducing the overall test cost for the mass production of commodity DDRx SDRAMs.

• Journal of the Korean Data and Information Science Society
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• v.9 no.2
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• pp.179-188
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• 1998

Local polynomial regression estimation is the most popular one among kernel type regression estimator. In local polynomial regression function esimation bandwidth selection is crucial problem like the kernel estimation. When the regression curve has complicated structure variable bandwidth selection will be appropriate. In this paper, we propose a variable bandwidth selection method fully data driven. We will choose the bandwdith by selecting minimising estiamted MSE which is estimated by the pilot bandwidth study via croos-validation method. Monte carlo simulation was conducted in order to show the superiority of proposed bandwidth selection method.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.10
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• pp.1294-1304
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• 1995

In this paper, a method has been proposed for the fully automatic detection of left ventricular endocardial boundary in B-mode short axis echocardiography without manual intervention by human operator. The proposed method makes use of the weighted model that approximates to endocardium and incomplete edge information for echocardiography. Therefore, this method is more effective than boundary detection by only edge information. The implementation of this method is as follows. First, the proposed algorithms are used in order to detect the approximate boundary, then a weighted model with the approximate boundary is constructed. Finally, the cavity center of the left ventricle performing the Hough transform with the weighted model and edge image can be found automatically, and then the endocardial boundary using detected center, original image, weighted model, and edge image can be detected. validations of this method with experimental results on echo image of dog's heart and clinical echocardiography is verified.

• Journal of Biomedical Engineering Research
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• v.28 no.6
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• pp.791-797
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• 2007

This paper proposes a semiautomatic vertebra segmentation method that overcomes limitations of both manual segmentation requiring tedious user interactions and fully automatic segmentation that is sensitive to initial conditions. The proposed method extracts fence surfaces between vertebrae, and segments a vertebra using fence-limited region growing. A fence surface is generated by a deformable model utilizing valley information in a valley emphasized Gaussian image. Fence-limited region growing segments a vertebra using gray value homogeneity and fence surfaces acting as barriers. The proposed method has been applied to ten patient data sets, and produced promising results accurately and efficiently with minimal user interaction.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2010-2014
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• 2005

Object detection and parameter estimation in point cloud data is a relevant subject to robotics, reverse engineering, computer vision, and sport mechanics. In this paper a software is presented for fully-automatic object detection and parameter estimation in unordered, incomplete and error-contaminated point cloud with a large number of data points. The software consists of three algorithmic modules each for object identification, point segmentation, and model fitting. The newly developed algorithms for orthogonal distance fitting (ODF) play a fundamental role in each of the three modules. The ODF algorithms estimate the model parameters by minimizing the square sum of the shortest distances between the model feature and the measurement points. Curvature analysis of the local quadric surfaces fitted to small patches of point cloud provides the necessary seed information for automatic model selection, point segmentation, and model fitting. The performance of the software on a variety of point cloud data will be demonstrated live.

• Transactions of the Korean Society of Mechanical Engineers
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• v.12 no.3
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• pp.561-565
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• 1988

In the present study, a new method of generating a nearly orthogonal boundary-fitted coordinate systems with automatic grid spacing control is introduced. Applications of the method to a two dimensional simply-connected region is then demonstrated. The nearly orthogonal boundary-fitted method has the following features, (a) Strong grid control in the .eta.-direction can be made, (b) The generated boundary-fitted coordinates are nearly orthoronal, (c) Both the .xi.-and .eta.-direction control function are mathematically derived. Especially the .eta.-direction control function is derived under the assumption that the .eta.-direction grid spacing is by far smaller than the .xi.-direction grid spacing when the .eta.-direction grid line is strongly clustered. (d) The grid control functions are dynamically adjusted by the metric scale factors imposed on the boundary. The control function is fully automatic and eliminates the need of user manipulation of the control function.

• Korean Journal of Computational Design and Engineering
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• v.5 no.1
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• pp.95-101
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• 2000

For last two decades numerous automatic mesh generation algorithms for various two dimensional objects have been introduced continuously and among them triangular mesh generation schemes have been majority because of efficiency and controllability. In our study, an existing triangular mesh generation algorithm developed by Lo is totally modified to more improve node distribution, element shape, and objects shape independency. ft is composed of node generation part and element generation part. In order to find a suitable node position within geometry, the suggested algorithm searches desirable positions of points within boundary and optimizes node position to generate comparatively well-shaped elements. More over, the suggested algorithm handles various complex two dimensional objects and its meshing speed shows superiority to those of the existing triangulation mesh generation algorithms. It is fully automated in a sense of constructing object boundary and hence can be directly used as an independent meshing software.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.8-13
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• 2000

Die polishing technology is very critical to determine quality and performance of the final products. Die polishing processes have not been automated because the automation requires a great deal of experience and skill of experts. Thus, to implement a fully automated polishing process, the development of polishing status monitoring system replacing the skill of experts is critical. AE is known to be closely related to material removal rate(MRR). As the surface is rougher, MRR gets larger and AE increased. The surface roughness can be indirectly estimated using the AE signal measured during automatic die polishing process. In this study, The polishing state monitoring system using AEms signal was developed. This system can be not only to monitor the abnormal state but also to estimate a state of surface roughness of polishing surface qualitatively.

• Smart Media Journal
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• v.9 no.3
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• pp.59-70
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• 2020

This paper presents a fully automatic tool to recognize the liver region from CT images based on a deep learning model, namely Multiple Filter U-net, MFUnet. The advantages of both U-net and Multiple Filters were utilized to construct an autoencoder model, called MFUnet for segmenting the liver region from computed tomograph. The MFUnet architecture includes the autoencoding model which is used for regenerating the liver region, the backbone model for extracting features which is trained on ImageNet, and the predicting model used for liver segmentation. The LiTS dataset and Chaos dataset were used for the evaluation of our research. This result shows that the integration of Multiple Filter to U-net improves the performance of liver segmentation and it opens up many research directions in medical imaging processing field.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.319-320
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• 2006

In this paper, automatic sunvisor system is introduced for driver's safety and convenience. This system has the mechanism which keeps the sun off without obstruction of driver's sight. The mechanism can make the sunvisor move forward or rotate left while remaining inside inner roof. The control system consists of a CPU, a motor driver, light sensors, and the algorithm that can control the movement of sunvisor efficiently. When the light sensors take the sun light, they give the signal to the CPU and the CPU calculates the best position of the sunvisor with the information of driver's eyes height. Then, the CPU gives the signal to motors that can move the sunvisor.