• Korean Journal of Computational Design and Engineering
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• v.20 no.1
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• pp.1-10
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• 2015

Using BIM (Building Information Modeling)-based design information to analyze various engineering processes has been widely adopted in construction projects. However, since typical building permit processes often require traditional 2D-based design information for submission and to obtain building approval, there are some challenges in delivering such data thru BIM-based design information. This paper proposed a methodology to generate and meet information requirements for permit applications and approvals based on BIM-based design information. To that end, we analyzed the required information necessary to make submissions for building approvals using the Seumter system. We then suggested a process to collect the required information from BIM-based data, and classified this into two types: BIM-internal and BIM-external information requirements. In addition, we proposed three algorithms to extract and to match between extracted BIM data and BIM-internal information requirements using IFC(Industry Foundation Classes). The proposed methodology enables to ensure the efficiency and the accuracy when providing data for building permit review and approval.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.2
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• pp.137-143
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• 2002

In this study we generated digital orthophoto from LIDAR data. To generate digital orthophoto, we make TIN from raw laser scanning data(XYZ point data) and compiled DSM from this TIN. In this procedure much noise appeared along the break lines in DSM and this can give bad effect to the quality of digital orthophoto. Therefore, we applied various techniques which can refine the break line. In the result, we concluded that the fusion of LIDAR DEM of lowland and extracted buildings was adequate to generating DSM. So we generated the digital orthophoto from DSM generated from this technique. In the result of quality test, the positional accuracy of this digital orthophoto was better than the positional accuracy of 1:5,000 map.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1295-1297
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• 1996

CCITT G.721, G.723 standard ADPCM algorithm is implemented by using TI's fixed point DSP start kit (DSK). ADPCM can be implemented on a various rates, such as 16K, 24K, 32K and 40K. The ADPCM is sample based compression technique and its complexity is not so high as the other speech compression techniques such as CELP, VSELP and GSM, etc. ADPCM is widely applicable to most of the low cost speech compression application and they are tapeless answering machine, simultaneous voice and fax modem, digital phone, etc. TMS320C50 DSP is a low cost fixed point DSP chip and C50 DSK system has an AIC (analog interface chip) which operates as a single chip A/D and D/A converter with 14 bit resolution, C50 DSP chip with on-chip memory of 10K and RS232C interface module. ADPCM C code is compiled by TI C50 C-compiler and implemented on the DSK on-chip memory. Speech signal input is converted into 14 bit linear PCM data and encoded into ADPCM data and the data is sent to PC through RS232C. The ADPCM data on PC is received by the DSK through RS232C and then decoded to generate the 14 bit linear PCM data and converted into the speech signal. The DSK system has audio in/out jack and we can input and out the speech signal.

• Proceedings of the Korean Society of Applied Pharmacology
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• 2007.11a
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• pp.19-27
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• 2007

An important potential of metabolomics-based approach is the possibility to develop fingerprints of diseases or cellular responses to classes of compounds with known common biological effect. Such fingerprints have the potential to allow classification of disease states or compounds, to provide mechanistic information on cellular perturbations and pathways and to identify biomarkers specific for disease severity and drug efficacy. Metabolic profiles of biological fluids contain a vast array of endogenous metabolites. Changes in those profiles resulting from perturbations of the system can be observed using analytical techniques, such as NMR and MS. $^1H$ NMR was used to generate a molecular fingerprint of serum or urinary sample, and then pattern recognition technique was applied to identity molecular signatures associated with the specific diseases or drug efficiency. Several metabolites that differentiate disease samples from the control were thoroughly characterized by NMR spectroscopy. We investigated the metabolic changes in human normal and clinical samples using $^1H$ NMR. Spectral data were applied to targeted profiling and spectral binning method, and then multivariate statistical data analysis (MVDA) was used to examine in detail the modulation of small molecule candidate biomarkers. We show that targeted profiling produces robust models, generates accurate metabolite concentration data, and provides data that can be used to help understand metabolic differences between healthy and disease population. Such metabolic signatures could provide diagnostic markers for a disease state or biomarkers for drug response phenotypes.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.5
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• pp.389-395
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• 2019

Unlike aerial images covering small region, satellite data show high potential to detect urban scale geospatial changes. The change detection using satellite images can be carried out using single image or stereo images. The single image approach is based on radiometric differences between two images of different times. It has limitations to detect building level changes when the significant occlusion and relief displacement appear in the images. In contrast, stereo satellite data can be used to generate DSM (Digital Surface Model) that contain information of relief-corrected objects. Therefore, they have high potential for the object change detection. Therefore, we carried out a study for the change detection over an urban area using stereo satellite data of two different times. First, the RPC correction was performed for two DSMs generation via stereo image matching. Then, D-DSM (Differential DSM) was generated by differentiating two DSMs. The D-DSM was used for the topographic change detection and the performance was checked by applying different height thresholds to D-DSM.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.9
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• pp.235-242
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• 2021

Most data scrambling schemes generate pure random codes. Unlike these schemes, we propose a variable density scrambling scheme (VDSC) that differentiates densities of generated codes. First, we describe conditions and methods to translate plain codes to cipher codes with different densities. Then we apply the VDSC to flash memory such that preferred cell states occur more than others. To restrain error rate, specifically, the VDSC controls code densities so as to increase the ratio of center state among all possible cell states in flash memory. Scrambling experiments of data in Windows and Linux systems show that the VDSC increases the ratio of cells having near-center states in flash memory.

• Electronics and Telecommunications Trends
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• v.33 no.6
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• pp.69-80
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• 2018

Sensory devices have been developed to help people with disabled or weakened sensory functions. Such devices play a role in collecting and transferring data for the five senses (vision, sound, smell, taste, and tactility) and also stimulating nerves. To provide brain or prosthesis devices with more sophisticated senses, hyper sensory devices with a high resolution comparable to or even better than the human system based on individual neuron cells are essential. As for data collecting components, technologies for sensors with higher resolution and sensitivity, and the conversion of algorithms from physical sensing data to human neuron signals, are needed. Converted data can be transferred to neurons that are responsible for human senses through communication with high security, and neural interfaces with high resolution. When communication deals with human data, security is the most important consideration, and intra-body communication is expected to be a candidate with high priority. To generate sophisticated human senses by modulating neurons, neural interfaces should modulate individual neurons, and therefore a high resolution compared to human neurons (~ several tens of um) with a large area covering neuron cells for human senses (~ several tens of mm) should be developed. The technological challenges for developing sensory devices with human and even beyond-human capabilities have been tackled by various research groups, the details of which are described in this paper.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.338-340
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• 2019

Recently, the speed and size of data accumulation are increasing due to the development of networks. There are many difficulties in classifying these data. One of the difficulties is the difficulty of labeling. Labeling is usually done by people, but it is very difficult for everyone to understand the data in the same way and it is very difficult to label them on the same basis. In order to solve this problem, we implemented GAN to generate new image based on input image and to learn input data indirectly by using it for learning. This suggests that the accuracy of classification can be increased by increasing the number of learning data.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.727-734
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• 2021

The study aims to examine and analyze the factors that affect the return on assets (ROA) by placing net interest margin (NIM) as a moderating variable in influencing ROA. This research was conducted on 27 banks listed on the Indonesia Stock Exchange (IDX) for the period 2015 to 2018 with a total sample data of 91. The data used is a combination of time series data and cross-section data. The sampling technique used was the purposive sampling method. The data analysis technique used was path analysis with multiple regression analysis technique. The results of the analysis showed that the capital adequacy ratio (CAR) and loan to deposit ratio (LDR) have a positive but insignificant effect on ROA. NIM as a moderating variable does not influence the impact of CAR on ROA. However, NIM as a moderating variable is able to influence the impact of LDR on ROA. From the results of this study, it is evident that the LDR will increase the ROA at banks that generate high NIM.

• Journal of KIBIM
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• v.12 no.3
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• pp.1-17
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• 2022

As the technology of Smart City and Digital Twin is developing, techniques to integrate BIM data of infrastructure facilities into GIS are becoming more critical. Hence, this study aims to manage BIM data representing bridge and tunnel structures through the Industry Foundation Classes (IFC) standard and to develop a method to link these IFC-compliant files to the GIS standard CityGML without loss of information. We analyze the criteria for creating BIM data for bridges and tunnels by reviewing the BIM guidelines set by each client. We use these criteria to suggest methods for data management based on InfraBIM as a specific IFC class standard. Furthermore, we perform model analysis to determine the necessary design and construction field-appropriate model process and Level of Detail (LOD). From the model analysis, we conclude that the classified BIM models can be used as base data to generate BIM models of bridges and tunnels for facility management.