• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.5
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• pp.1203-1212
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• 2013

In this paper, an intra prediction hardware architecture is proposed to reduce computational complexity of intra prediction in HEVC decoder. The architecture uses shared operation units and common operation units and adopts a fast smoothing decision algorithm and a fast algorithm to generate coefficients of a filter. The shared operation unit shares adders processing common equations to remove the computational redundancy. The unit computes an average value in DC mode for reducing the number of execution cycles in DC mode. In order to reduce operation units, the common operation unit uses one operation unit generating predicted pixels and filtered pixels in all prediction modes. In order to reduce processing time and operators, the decision algorithm uses only bit-comparators and the fast algorithm uses LUT instead of multiplication operators. The proposed architecture using four shared operation units and eight common operation units which can reduce execution cycles of intra prediction. The architecture is synthesized using TSMC 0.13um CMOS technology. The gate count and the maximum operating frequency are 40.5k and 164MHz, respectively. As the result of measuring the performance of the proposed architecture using the extracted data from HM 7.1, the execution cycle of the architecture is about 93.7% less than the previous design.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.568-573
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• 2018

UAV(Unmanned Aerial Vehicle) is widely used in space information construction, agriculture, fisheries, weather observation, communication, and entertainment fields because they are cheaper and easier to operate than manned aircraft. In particular, UAV have attracted much attention due to the speed and cost of data acquisition in the field of spatial information construction. However, ortho image images produced using UAVs are distorted in buildings and forests. It is necessary to solve these problems in order to utilize the geospatial information field. In this study, fixed wing, rotary wing, vertical take off and landing type UAV were used to detect distortions of ortho image of UAV under various conditions, and various object areas such as construction site, urban area, and forest area were captured and analysed. Through the research, it was found that the redundancy of the unmanned aerial vehicle image is the biggest factor of the distortion phenomenon, and the higher the flight altitude, the less the distortion phenomenon. We also proposed a method to reduce distortion of orthoimage by lowering the resolution of original image using DTM (Digital Terrain Model) to improve distortion. Future high-quality unmanned aerial vehicles without distortions will contribute greatly to the application of UAV in the field of precision surveying.

• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.318-331
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• 2022

With the recent development of hardware computing devices and software based frameworks, machine tasks using deep learning networks are expected to be utilized in various industrial fields and personal IoT devices. However, in order to overcome the limitations of high cost device for utilizing the deep learning network and that the user may not receive the results requested when only the machine task results are transmitted from the server, Collaborative Intelligence (CI) proposed the transmission of feature maps as a solution. In this paper, an efficient compression method for feature maps with vast data sizes to support the CI paradigm was analyzed and presented through experiments. This method increases redundancy by applying feature map reordering to improve compression efficiency in traditional video codecs, and proposes a feature map method that improves compression efficiency and maintains the performance of machine tasks by simultaneously utilizing image compression format and video compression format. As a result of the experiment, the proposed method shows 14.29% gain in BD-rate of BPP and mAP compared to the feature compression anchor of MPEG-VCM.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.2
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• pp.95-107
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• 2023

The purpose of this study is to investigate the impact of export promotion programs (EPPs) on the export performance of small- and medium-sized enterprises (SMEs), with a specific focus on the influence of EPPs for promising SMEs in the export market. Using data on SMEs provided by the Industrial Bank of Korea (IBK), we conducted a fixed-effects model analysis from 2016 to 2019. Our study shows that EPPs have a positive and significant relationship with export intensity. Further analysis reveals that SMEs utilizing the financing support system provided by EPPs tend to improve their export growth and financial performance relative to their counterparts. While EPPs can assist SMEs with their internationalization efforts, their similarity and redundancy are recognized as potential limitations. This study complements the existing literature that has mainly focused on surveys and cross-sectional analysis by specifying the research subject to promising SMEs in export, and analyzing the effects of the export promotion program supported by IBK Industrial Bank. The results of this study are expected to provide implications for improving SMEs' export capabilities.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.2
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• pp.401-408
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• 2017

GNSS(Global Navigation Satellite System) is positioning and navigation system using satellites. Accurate positioning is possible in all regions of the world using satellite signals. In Korea, GPS was introduced in the late 1980s. GPS is used in research and work in various fields such as navigation, surveying, and GIS. Since 1995, NGII(National Geographic Information Institute) has installed and operated CORS(Continuously Operating Reference Station) for the practical use of GNSS surveying, RINEX download and VRS(Virtual Reference Station) service was provided for precise positioning. Demand for these services is explosively increasing in the field of surveying. Therefore, there is a need for research to provide good service. In this study, status of national surveying infra structure was researched focused on CORS and its services. As a results, current status of CORS and service were presented. Users of VRS service has increased greatly. In order to provide stable service and advanced surveying, it is necessary to continuously upgrade services such as providing services for various GNSS satellites and securing stability through server redundancy in the data center.

• Journal of Korean Academy of Nursing
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• v.53 no.3
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• pp.295-308
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• 2023

Purpose: This study evaluated the validity and reliability of Shively and colleagues' self-efficacy for HIV disease management skills (HIV-SE) among Korean participants. Methods: The original HIV-SE questionnaire, comprising 34 items, was translated into Korean using a translation and back-translation process. To enhance clarity and eliminate redundancy, the author and expert committee engaged in multiple discussions and integrated two items with similar meanings into a single item. Further, four HIV nurse experts tested content validity. Survey data were collected from 227 individuals diagnosed with HIV from five Korean hospitals. Construct validity was verified through confirmatory factor analysis. Criterion validity was evaluated using Pearson's correlation coefficients with the new general self-efficacy scale. Internal consistency reliability and test-retest were examined for reliability. Results: The Korean version of HIV-SE (K-HIV-SE) comprises 33 items across six domains: "managing depression/mood," "managing medications," "managing symptoms," "communicating with a healthcare provider," "getting support/help," and "managing fatigue." The fitness of the modified model was acceptable (minimum value of the discrepancy function/degree of freedom = 2.49, root mean square error of approximation = .08, goodness-of-fit index = .76, adjusted goodness-of-fit index = .71, Tucker-Lewis index = .84, and comparative fit index = .86). The internal consistency reliability (Cronbach's α = .91) and test-retest reliability (intraclass correlation coefficient = .73) were good. The criterion validity of the K-HIV-SE was .59 (p < .001). Conclusion: This study suggests that the K-HIV-SE is useful for efficiently assessing self-efficacy for HIV disease management.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6C
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• pp.367-377
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• 2008

As part of study to develop LRFD (Load and Resistance Factor Design) codes for foundation structures in Korea, resistance factors for static bearing capacity of driven steel pipe piles were calibrated in the framework of reliability theory. The 57 data sets of static load tests and soil property tests conducted in the whole domestic area were collected and these load test piles were sorted into two cases: SPT N at pile tip less than 50, SPT N at pile tip equal to or more than 50. The static bearing capacity formula and the Meyerhof method using N values were applied to calculate the expected design bearing capacities of the piles. The resistance bias factors were evaluated for the two static design methods by comparing the representative measured bearing capacities with the expected design values. Reliability analysis was performed by two types of advanced methods: the First Order Reliability Method (FORM), and the Monte Carlo Simulation (MCS) method using resistance bias factor statistics. The target reliability indices are selected as 2.0 and 2.33 for group pile case and 2.5 for single pile case, in consideration of the reliability level of the current design practice, redundancy of pile group, acceptable risk level, construction quality control, and significance of individual structure. Resistance factors of driven steel pipe piles were recommended based on the results derived from the First Order Reliability Method and the Monte Carlo Simulation method.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1C
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• pp.19-29
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• 2008

As a part of study to develop LRFD (Load and Resistance Factor Design) codes for foundation structures in Korea, reliability analyses for driven steel pipe piles are performed and the target reliability indices are selected carefully. The 58 data sets of static load tests and soil property tests conducted in the whole domestic area were collected and analyzed to determine the representative bearing capacities of the piles. The static bearing capacity formula and the Meyerhof method using N values are applied to calculate the expected design bearing capacity of the piles. The resistance bias factors were evaluated for the two static design methods by comparing the representative bearing capacities with the design values. Reliability analysis was performed by two types of advanced methods: First Order Reliability Method (FORM), and Monte Carlo Simulation (MCS) method using resistance bias factor statistics. The static bearing capacity formula exhibited relatively small variation, whereas the Meyerhof method showed relatively high inherent conservatism in the resistance bias factors. Reliability indices for safety factors in the range of 3 to 5 were evaluated respectively as 1.50~2.89 and 1.61~2.72 for both of the static bearing capacity formula and the Meyerhof method. The target reliability indices are selected as 2.0 and 2.33 for group pile case and 2.5 for single pile case, based on the reliability level of the current design practice and considering redundancy of pile group, acceptable risk level, construction quality control, and significance of individual structure.

• Korean Journal of Radiology
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• v.23 no.8
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• pp.811-820
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• 2022

Objective: To develop a model incorporating radiomic features and clinical factors to accurately predict acute ischemic stroke (AIS) outcomes. Materials and Methods: Data from 522 AIS patients (382 male [73.2%]; mean age ± standard deviation, 58.9 ± 11.5 years) were randomly divided into the training (n = 311) and validation cohorts (n = 211). According to the modified Rankin Scale (mRS) at 6 months after hospital discharge, prognosis was dichotomized into good (mRS ≤ 2) and poor (mRS > 2); 1310 radiomics features were extracted from diffusion-weighted imaging and apparent diffusion coefficient maps. The minimum redundancy maximum relevance algorithm and the least absolute shrinkage and selection operator logistic regression method were implemented to select the features and establish a radiomics model. Univariable and multivariable logistic regression analyses were performed to identify the clinical factors and construct a clinical model. Ultimately, a multivariable logistic regression analysis incorporating independent clinical factors and radiomics score was implemented to establish the final combined prediction model using a backward step-down selection procedure, and a clinical-radiomics nomogram was developed. The models were evaluated using calibration, receiver operating characteristic (ROC), and decision curve analyses. Results: Age, sex, stroke history, diabetes, baseline mRS, baseline National Institutes of Health Stroke Scale score, and radiomics score were independent predictors of AIS outcomes. The area under the ROC curve of the clinical-radiomics model was 0.868 (95% confidence interval, 0.825-0.910) in the training cohort and 0.890 (0.844-0.936) in the validation cohort, which was significantly larger than that of the clinical or radiomics models. The clinical radiomics nomogram was well calibrated (p > 0.05). The decision curve analysis indicated its clinical usefulness. Conclusion: The clinical-radiomics model outperformed individual clinical or radiomics models and achieved satisfactory performance in predicting AIS outcomes.

• Journal of KIISE:Databases
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• v.30 no.4
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• pp.381-396
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• 2003

Subsequence matching is an operation that finds subsequences whose changing patterns are similar to a given query sequence from time-series databases. This paper points out the performance bottleneck in subsequence matching, and then proposes an effective method that improves the performance of entire subsequence matching significantly by resolving the performance bottleneck. First, we analyze the disk access and CPU processing times required during the index searching and post processing steps through preliminary experiments. Based on their results, we show that the post processing step is the main performance bottleneck in subsequence matching, and them claim that its optimization is a crucial issue overlooked in previous approaches. In order to resolve the performance bottleneck, we propose a simple but quite effective method that processes the post processing step in the optimal way. By rearranging the order of candidate subsequences to be compared with a query sequence, our method completely eliminates the redundancy of disk accesses and CPU processing occurred in the post processing step. We formally prove that our method is optimal and also does not incur any false dismissal. We show the effectiveness of our method by extensive experiments. The results show that our method achieves significant speed-up in the post processing step 3.91 to 9.42 times when using a data set of real-world stock sequences and 4.97 to 5.61 times when using data sets of a large volume of synthetic sequences. Also, the results show that our method reduces the weight of the post processing step in entire subsequence matching from about 90% to less than 70%. This implies that our method successfully resolves th performance bottleneck in subsequence matching. As a result, our method provides excellent performance in entire subsequence matching. The experimental results reveal that it is 3.05 to 5.60 times faster when using a data set of real-world stock sequences and 3.68 to 4.21 times faster when using data sets of a large volume of synthetic sequences compared with the previous one.