• Journal of Software Engineering Society
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• v.25 no.1
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• pp.1-9
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• 2012

RFID systems have been widely used in various fields such as logistics, distribution, food, security, traffic and others. A RFID middleware, one of the key components of the RFID system, perform an important role in many functions such as filtering, grouping, reporting tag data according to given user specifications and so on. However, manual test data generation is very hard because the inputs of the RFID middleware are generated according to the RFID middleware standards and complex encoding rules. To solve this problem, in this paper, we propose a black box test technique based on RFID middleware standards. Firstly, we define ten types of input conversion rules to generate new test data from existing test data based on the standard specifications. And then, using these input conversion rules, we generate various additional test data automatically. To validate the effectiveness of generated test data, we measure coverage of generated test data on actual RFID middleware. The results show that our test data achieve 78% statement coverage and 58% branch coverage in the classes of filtering and grouping, 79% statement coverage and 64% branch coverage in the classes of reporting.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.545-548
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• 2016

Big data is all data generated in the digital environment which has a variety of large and a short life cycle. The amount and type of data are becoming more and more produced on a larger scale, as a smart phone and the internet are popular, and consequently it has been converted into time for users to take advantage and extract only the valuable and useful data from the generated big data. Big data can also be applied to the medical industry and health sectors. It has created the synergy to be fused with ICT such as IoT, smart healthcare, and so on. However, there will be challenges like data security in order securely to use a meaningful and useful vast amounts of data. In this study, we analyze the future prospects of the healthcare, applications and issues of medical big data, and the expected challenges.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.359-360
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• 2023

As data management and analysis technology advances, there is active discussion on how to utilize data generated in construction projects. Among them, the materials produced during the supervision work are highly useful because their generation cycle and format are regulated according to relevant laws. In this study, we analyzed whether the data produced during the supervision work in the construction phase of apartment housing can be utilized for project performance management. First, this study identified key data necessary for performance management through FGI with experts in the field of apartment housing. Next, we collected supervisory data from the case project and identified whether the data was generated, its cycle, and storage format. As a result of the analysis, the supervisory data contained various information that could measure the performance of construction projects and had the advantage of standardized data. In the future, utilizing supervisory data is expected to enable effective performance management of apartment housing construction projects.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.1144-1148
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• 1991

The problems occurred when developing a automatic wheel deburring system are to make effective flexibility in model change and the irregularity of the position/shape of the burr, to select optimal robotic manufacturing process and to develope optimal end effector. The locations where burr exists are on flange, rim and spoke. Here will be discussed the optimal solution for the removal of rim burr by using robot. The research can be summarized as the automatic robot path generation by recognizing rim contour and automatic deburring process technique. Various rim contour data is generated automatically when the sensor which is fixed to robot is moving with the parallel motion to the wheel center axis and this generated data is transferred to the data storage system and converted to the robot path data. The robotic tool system which is suitable to the rim deburring process is developed by integrating tool, compliance function and sensor. And factory automation system controlled by robot controller and PC is developed. This system shows good productivity and flexibility.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.11 no.1
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• pp.32-37
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• 2002

The use of hexagonal ceramic inserts for copper extrusion dies offers significant technical and economic advantages over other forms of manufacture. In this paper the data on the loading of the tools is determined from a commercial FEM package as the contact stress distribution on the die-workpiece interface and as temperature distributions in the die. This data can be processed as load input data for a finite element die-stress analysis. Process simulation and stress analysis are thus combined during the design and a data exchange program has been developed that enables optimal design of the dies taking into account the elastic deflections generated in shrink fitting the die inserts and that caused by the stresses generated in the process. The stress analysis of the dies is used to determine the stress conditions on the ceramic insert by considering contact and interference effects under both mechanical and thermal loads.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.04a
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• pp.72-77
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• 2001

The use of hexagonal ceramic inserts for copper extrusion dies offers significant technical and economic advantages over other forms of manufacture. In this paper the data on the loading of the tools is determined from a commercial FEM package as the contact stress distribution on the die-workpiece interface and as temperature distributions in the die. This data can be processed as load input data for a finite element die-stress analysis. Process simulation and stress analysis are thus combined during the design, and a data exchange program has been developed that enables optimal design of the dies taking into account the elastic deflections generated in shrink fitting the die inserts and that caused by the stresses generated in the process. The stress analysis of the dies is used to determine the stress conditions on the ceramic insert by considering contact and interference effects under both mechanical and thermal loads.

• Asian-Australasian Journal of Animal Sciences
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• v.13 no.8
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• pp.1035-1039
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• 2000

This study developed a Poisson generalized linear mixed model and a procedure to estimate genetic parameters for count traits. The method derived from a frequentist perspective was based on hierarchical likelihood, and the maximum adjusted profile hierarchical likelihood was employed to estimate dispersion parameters of genetic random effects. Current approach is a generalization of Henderson's method to non-normal data, and was applied to simulated data. Underestimation was observed in the genetic variance component estimates for the data simulated with large heritability by using the Poisson generalized linear mixed model and the corresponding maximum adjusted profile hierarchical likelihood. However, the current method fitted the data generated with small heritability better than those generated with large heritability.

• Journal of Biomedical Engineering Research
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• v.41 no.1
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• pp.28-34
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• 2020

In this paper, we introduce motion artifact reduction algorithm for interleaved MRI using an advanced 3D approximation algorithm. The motion artifact framework of this paper is data corrected by post-processing with a new 3-D approximation algorithm which uses data structure for each voxel. In this study, we simulate and evaluate our algorithm using Shepp-Logan phantom and T1-MRI template for both scattered dataset and uniform dataset. We generated motion artifact using random generated motion parameters for the interleaved MRI. In simulation, we use image coregistration by SPM12 (https://www.fil.ion.ucl.ac.uk/spm/) to estimate the motion parameters. The motion artifact correction is done with using full dataset with estimated motion parameters, as well as use only one half of the full data which is the case when the half volume is corrupted by severe movement. We evaluate using numerical metrics and visualize error images.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.82.3-82.3
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• 2019

In this study, we generate future full disk magnetograms in 12, 24, 36 and 48 hours advance from SDO/HMI images using deep learning. To perform this generation, we apply the convolutional generative adversarial network (cGAN) algorithm to a series of SDO/HMI magnetograms. We use SDO/HMI data from 2011 to 2016 for training four models. The models make AI-generated images for 2017 HMI data and compare them with the actual HMI magnetograms for evaluation. The AI-generated images by each model are very similar to the actual images. The average correlation coefficient between the two images for about 600 data sets are about 0.85 for four models. We are examining hundreds of active regions for more detail comparison. In the future we will use pix2pix HD and video2video translation networks for image prediction.

• Journal of IKEEE
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• v.27 no.1
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• pp.59-64
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• 2023

Deep learning can solve various computer vision problems, but it requires a large dataset. Data augmentation technique based on image binarization for constructing large-scale datasets is proposed in this paper. By extracting features using image binarization and randomly placing the remaining pixels, new images are generated. The generated images showed similar quality to the original images and demonstrated excellent performance in deep learning models.