• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.9
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• pp.817-825
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• 2013

The UHDTV system, which provides realistic service with ultra-high definite video and multi-channel audio, has been studied as a next generation broadcasting service. Since the conventional digital terrestrial transmission system is not capable to cover the increased transmission data rate of the UHDTV service, there are great necessity of researches about increase of data rate. Accordingly, the researches has been studied to increase the transmission data rate of the DVB-T2 system using dual-polarized MIMO technique and high order modulation. In order to optimize the MIMO DVB-T2 system where irregular LDPC codes are used, it is necessary to study the design of the bit mapper that matches the LDPC code and QAM symbols in MIMO channel. However, the research related to the design of the bit mapper has been limited to the SISO system. Therefore, this paper defines a new parameter that indicates the VND distribution of MIMO DVB-T2 system and performs the performance analysis according to the parameter which will be helpful for designing a MIMO bit mapper.

• The KIPS Transactions:PartB
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• v.13B no.2 s.105
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• pp.77-82
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• 2006

Digital halftoning is the technique to obtain a bilevel-toned image from continuous-toned image. Among halftoning methods, the error diffusion method gives better subjective quality than other halftoning ones. But it also makes edges of objects blurred. To overcome the defect, we proposes the modified error diffusion to enhance the edges using the property that human vision perceives the local average luminance and doesn't perceive a little variation of the spatial variation. The proposed method computes a spatialactivity, which is the difference between a pixel luminance and the average of its $3{\times}3$ neighborhood pixels' Iuminance weighted according to the spatial positioning. The system also usesof edge enhancement (IEE), which is computed from the normalized spatial activitymultiplied by the average luminance. The IEE is added to the quantizer's input pixel and feeds into the halftoning quantizer. The quantizer produces the halftone image having the enhanced edge. The computer experimental results show that the proposed method produces clearer bilevel-toned images than conventional methodsand the edge of objects is preserved well. Also the performance of the preposed method is improved, compared with that of the conventional method by measuring the edge correlation and the local average accordance at some ranges of viewing distance.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1155-1166
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• 2021

In this study, statistical analysis was performed to suggest the optimal analysis techniques for the main measuring instruments of the fill dam, such as seepage, crest settlement, and porewater pressure gauge. In addition, correlation analysis with water level and rainfall data was performed. Based on the results of descriptive statistical analysis for each instrument, porewater pressure gauges could be classified into 3 groups or 2 groups through principal component analysis, In the case of the group having a high correlation with the water level instrument, the correlation between the gauges was also large. In the case of seepage instrument, the distribution showed an extremely asymmetric distribution, so for quantitative analysis, the average seepage during non-precipitation and precipitation could be estimated through decision tree analysis. In the case of the crest settlement instrument, the correlation analysis showed that the correlation between the gauges was large, but the relationship with the water level instrument did not show a significant linear relationship, so EMD analysis was performed to analyze it in more detail. It is judged that principal component analysis, decision tree analysis, and data filtering method can be applied to analyze the behavior of pore water pressure meters, seepage, and crest settlement instrument as major measurement items of fill dam.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1149-1161
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• 2021

With a trend of the utilization of computer vision for satellite images, cloud detection using deep learning also attracts attention recently. In this study, we conducted a U-Net cloud detection modeling using SPARCS (Spatial Procedures for Automated Removal of Cloud and Shadow) Cloud Dataset with the image data augmentation and carried out 10-fold cross-validation for an objective assessment of the model. Asthe result of the blind test for 1800 datasets with 512 by 512 pixels, relatively high performance with the accuracy of 0.821, the precision of 0.847, the recall of 0.821, the F1-score of 0.831, and the IoU (Intersection over Union) of 0.723. Although 14.5% of actual cloud shadows were misclassified as land, and 19.7% of actual clouds were misidentified as land, this can be overcome by increasing the quality and quantity of label datasets. Moreover, a state-of-the-art DeepLab V3+ model and the NAS (Neural Architecture Search) optimization technique can help the cloud detection for CAS500 (Compact Advanced Satellite 500) in South Korea.

• The Journal of Society for e-Business Studies
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• v.23 no.4
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• pp.63-85
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• 2018

The "About Us" page on the website of a corporation provides information regarding the organization's vision, philosophy, and values. We examine the association between institutional information provided on corporate websites (i.e., the "About Us" section) with present and future financial performance. Utilizing a text mining technique, we analyze the institutional information of S&P500 firms in the year 2016. We conduct a factor analysis including words that are intentionally repeated in the introductory text of corporate websites. The results of the analysis reveal that keywords from this institutional information can be grouped into six factors. We then carry out an ordinary least squares regression analysis to determine the associations between these six factors and present financial performance. The results show that keywords in Factor 2 (those related to Purchasing experience) are positively associated with ROE, a variable representing present financial performance, while keywords in Factor 1 (those related to Note to customers) show a negative relationship with ROE. On the other hand, keywords in Factor 1 have a positive relationship with Tobin's Q, a variable representing future financial performance. These results indicate that there is some relationship between the words used in the institutional information in this section of corporate websites and firms' financial performance. Hence, the institutional information on a website may be a useful indicator of current firm performance and future firm value.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.577-582
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• 2021

Recently, with the development of AR, VR, and smart device technologies, the demand for services based on non-face-to-face environments is also increasing in the fitness industry. The non-face-to-face online home training service has the advantage of not being limited by time and place compared to the existing offline service. However, there are disadvantages including the absence of exercise equipment, difficulty in measuring the amount of exercise and chekcing whether the user maintains an accurate exercise posture or not. In this study, we develop a standard exercise program that can compensate for these shortcomings and propose a new non-face-to-face home training application by using a deep learning-based body posture estimation image processing algorithm. This application allows the user to directly watch and follow the trainer of the standard exercise program video, correct the user's own posture, and perform an accurate exercise. Furthermore, if the results of this study are customized according to their purpose, it will be possible to apply them to performances, films, club activities, and conferences

• Journal of Cadastre & Land InformatiX
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• v.51 no.2
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• pp.169-184
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• 2021

Recently, land cover spectral libraries have been widely used in studies to classify land cover based on hyperspectral images. Overseas, various institutions have built and provided land cover spectral libraries, but in Korea, the building and provision of land cover spectral libraries is insufficient. Against this background, the purpose of this study is to suggest the possibility of using domestic and foreign spectral libraries in the classification studies of domestic land cover. Band matching is required for comparative analysis of the spectral libraries and land cover classification using the spectral libraries, and in this study, an automation logic to automatically perform this is presented. In addition, the directly constructed domestic land cover spectral library and the existing overseas land cover spectral library were comparatively analyzed. As a result, the directly constructed land cover spectral library had the highest correlation coefficient of 0.974. Finally, for the accuracy evaluation, aerial hyperspectral images of the study area were supervised and classified using the domestic and foreign land cover spectral libraries using the SAM technique. As a result of the accuracy evaluation, it is judged that Soils, Artificial Materials, and Coatings among the classification items of the foreign land cover spectral library can be sufficiently applied to classify the cover in Korea.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.4
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• pp.542-548
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• 2022

In order to reduce marine accidents, each contracting Government needs to implement the instruments enacted and amended by the International Maritime Organization (IMO). The III Code requires each administration of the government to have a system for improvement through periodic review and evaluation and to include performance indicators in its evaluation methods. Thus, each IMO Member State needs to develop its own performance indicators. The purpose of this paper is to develop and present an evaluation model using the Balanced Scorecard (BSC) and Key Performance Indicators (KPI) in order to quantify and evaluate the level of implementation of the instruments by the administrations. From the perspective of 'III-BSC', which applies the BSC concept to the III code requirements, the Critical Success Factors (CSF) that must be secured to achieve the established vision were drawn up, and candidate KPIs for each evaluation area were developed to measure the derived key success factors and an initial study model was designed composed of four levels. The validity of the KPIs was verified and the study model was finalized using the survey design using the SMART technique. Furthermore, based on the developed study model, an evaluation model for the implementation of the BSC-based IMO instruments was developed by deriving the weights of elements for each level through AHP analysis. The developed evaluation model is expected to contribute toward improving the administrations' level of implementation of the IMO instruments as a tool for quantitatively grasping the level of performance of the implementation.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.179-184
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• 2021

Along with the development of the fourth industry, the public sector has increasingly paid more attention to search using drones and real-time monitoring, for various goals. The drones are used and researched to complete a variety of searching and monitoring missions, including search for missing persons, security, coastal patrol and monitoring, speed enforcement, highway and urban traffic monitoring, fire and wildfire monitoring, monitoring of illegal fishing in reservoirs and protest rally monitoring. Police stations, fire departments and military authorities, however, concentrate on the hardware part, so there are little research on efficient communication systems for the real-time monitoring of data collected from high-performance resolution and infrared thermal imagining cameras, and analysis programs suitable for special missions. In order to increase the efficiency of drones with the searching mission, this paper, therefore, attempts to propose an image analysis technique to increase the precision of search by producing image data suitable for searching missions, based on images obtained from drones and provide the foundation for improving relevant policies and establishing proper platforms, based on actual field cases and experiments.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.10
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• pp.409-418
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• 2022

In this paper, we propose SAAnnot-C3Pap, a semi-automatic annotation method for obtaining ground truth of a player's posture. In order to obtain ground truth about the two-dimensional joint position in the existing music domain, openpose, a two-dimensional posture estimation method, was used or manually labeled. However, automatic annotation methods such as the existing openpose have the disadvantages of showing inaccurate results even though they are fast. Therefore, this paper proposes SAAnnot-C3Pap, a semi-automated annotation method that is a compromise between the two. The proposed approach consists of three main steps: extracting postures using openpose, correcting the parts with errors among the extracted parts using supervisely, and then analyzing the results of openpose and supervisely. Perform the synchronization process. Through the proposed method, it was possible to correct the incorrect 2D joint position detection result that occurred in the openpose, solve the problem of detecting two or more people, and obtain the ground truth in the playing posture. In the experiment, we compare and analyze the results of the semi-automated annotation method openpose and the SAAnnot-C3Pap proposed in this paper. As a result of comparison, the proposed method showed improvement of posture information incorrectly collected through openpose.