• 한국측량학회지
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• 제35권2호
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• pp.103-112
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• 2017

Due to the large size and high complexity of modern buildings, the interest and the studies about indoor spatial information are increasing. Previous studies related to indoor spatial information were mostly about relevant technologies, and the application of indoor spatial information has been less studied. In the present study, the public administrative work areas where indoor spatial information may be applied were identified by using a modified delphi technique. And the indoor LOD (Level of Detail) and indoor positioning accuracy for indoor spatial information applications considering user requirements was established as standards for efficiently establishing and providing services. The required LOD and positioning accuracy for services was established by reestablishing indoor LOD and positioning accuracy and classifying services with reference to those. The indoor LOD was reestablished from LOD 0 to 4 by focusing on service utilization and general recognition, and the positioning accuracy was reestablished in three levels by considering the accuracy of the present positioning technology and service utilization status.

• 한국응급구조학회지
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• 제23권3호
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• pp.41-51
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• 2019

Purpose: This dissertation is a descriptive research study analyzing the accuracy and reliability of the cardiopulmonary resuscitation (CPR) application developed in Korea. Methods: Two faculty members from the emergency medical services department and the emergency medicine department searched applications from July 1 to July 10, 2019 and selected a total of 13 applications. Twelve questions were assessed for information accuracy and three were assessed for reliability. In accordance with application types, the number and mean ± standard deviation were analyzed. The t-test was used to compare the accuracy of CPR information in accordance with information sources. Results: The results revealed the following errors: 7 cases (53.8%) identified the chest center lining from the nipple center-line as the chest pressure point; 5 cases (38.5%) did not provide information on the depth of 6 cm that should not be exceeded; and 4 cases (30.8%) did not provide advise to check respiration. When the CPR information sources were included, the information accuracy score was high; a significant difference was observed (p=.035). Conclusion: In the case of applications providing medical information regarding CPR, it is necessary to provide at least authoritarian, sources of information, and author transparency as well as continuous effort and attention.

• Journal of the Korean Data and Information Science Society
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• 제25권6호
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• pp.1345-1352
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• 2014

데이터마이닝 기법 중에서 연관성 규칙은 연관성 평가 기준을 기반으로 하여 데이터베이스에 포함되어 있는 항목들 간의 관련성을 탐색하는 기법이다. 일반적인 연관성 규칙 기법과는 달리 역의 연관성 규칙은 하나의 항목집합이 발생하지 않으면 다른 항목집합도 발생하지 않는다는 규칙을 찾아내는 것이다. 이러한 역의 연관성 규칙을 일반적인 연관성 규칙과 함께 생성하면 기업체에서 특정 제품을 판매하기 위해서는 그 제품만의 마케팅뿐만 아니라 더 나아가 어떤 제품의 마케팅이 필요한 지에 대한 정보를 파악할 수 있다. 이를 위해 본 논문에서는 이러한 두 종류의 연관성 규칙에 적용 가능한 균형화된 기여 상대적 규칙 정확도를 연관성 평가 기준으로 제안하고자 한다. 또한 Piatetsky-Shapiro (1991)가 제안한 흥미도 측도가 가져야 할 조건들을 점검한 후, 예제를 통하여 제안된 측도와 연관성 규칙에 적용 가능한 의학진단분야의 평가 측도들의 유용성을 비교하였다. 그 결과, 기여 상대적 정확도와 역의 기여 상대적 정확도의 크기가 다르게 나타나면 연관성의 정도를 명확하게 설명하기가 어려우므로 이들 두 측도를 동시에 고려한 균형화된 기여 상대적 규칙 정확도를 이용하는 것이 가장 바람직하다는 사실을 확인하였다.

• 대한공간정보학회지
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• 제10권4호
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• pp.51-60
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• 2002

GIS의 사용이 확대되면서 사용자들은 데이터의 품질과 원자료에 대한 관심이 매우 증대되었다. 정확도는 전체 품질 중의 한 요소이며 또한 위치정확도는 정확도의 일부분이다. 정확도 측면에서 본다면 수작업 종래의 측량기술, GPS 또는 리모트센싱 등 무엇이든 간에 위치와 속성 정보에 대한 동시 수집방법은 위치와 속성이 정확하게 서로 관련되어 있는 것을 확인하는 가장 실질적인 방법이다. 본 연구는 도로기반시설물의 품질을 확보하고 지속적으로 유지관리하기 위해 고려할 사항으로서 위치정확도를 사용자측면과 공급자측면에서 분석하였다. 도로기반시설물의 위치정확도는 도로기반시설물 데이터베이스를 구축하는 과정에서 발생되는 기대 정확도, 실제 업무에 활용하는 과정에서 발생되는 사용자 요구정확도로 크게 나누어 분석할 수 있으며, 계획기관에서 데이터베이스 구축방법을 결정할 때에는 비용대비 기대효과 측면에서의 정확도를 고려하여야 한다.

• 디지털산업정보학회논문지
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• 제14권4호
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• pp.155-161
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• 2018

Recently, the development of sensor technology has led to an increase in research on unmanned aerial photogrammetry in various fields such as digital mapping, monitoring, cadastral survey, coastal survey, and topographic survey. However, existing studies are mainly limited experiments and analysis of specific application field, which is insufficient to demonstrate the validity of unmanned aerial photogrammetry for geospatial information construction. In this study, the studies related to the accuracy of unmanned aerial photogrammetry were investigated. The flight altitude and accuracy of horizontal direction is proportional to the GSD by analyzing the results of the individual studies conducted on the unmanned aerial photogrammetry within the last 5 years. In addition, the accuracy of the evaluation results varied widely according to the experimental conditions, and the problems of the previous studies that lacked the number of samples to evaluate the results were identified. A total accuracy analysis of 322 checkpoints yielded an accuracy of 0.028m in the horizontal direction and 0.044m in the vertical direction. In the future, the results of this study can be used as a basis for the validity of spatial information construction using unmanned aerial photogrammetry.

• 한국도로학회논문집
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• 제14권6호
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• pp.139-148
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• 2012

PURPOSES : The accuracy of travel time information is a key measure of effectiveness and reliability of advanced traveler information systems. This study aims at investigating drivers' perception on the acceptable level of information accuracy and their corresponding valuations. METHODS : A questionnaire survey was executed for collecting driver perception data to capture the expectation level of travel time information provided and their willingness to pay for the information. A Tobit model was adopted for exploring the relationship among the acceptable level, driver socioeconomic characteristics and travel attributes. Since drivers' willingness to pay for accurate travel time information can be different according to their travel lengths, a piecewise linear regression model was developed to capture the sensitivity of values of travel time information to travel length. RESULTS : The analysis results suggest that trip purpose and travel time are two dominant factors to determine drivers' acceptable level of travel time information. For business and short trips, drivers want more accurate information than for non-business and long trips. Drivers' willingness to pay for travel time information also varies depending on their incomes, trip purposes and travel lengths. The results also show that drivers' valuation of travel time information provided is sensitive to their travel length. For longer trips, drivers are less sensitive to travel time information and then put less value on the information provided. CONCLUSIONS : Censored nonlinear regression models are developed to estimate drivers' acceptable accuracy for travel time information and their valuation using questionnaire survey data. The findings on drivers perception to the required accuracy of travel time information and their corresponding willingness to pay can be used in the design and deployment of advanced traveler information system to improve its effectiveness and usefulness through high compliance.

• 한국측량학회지
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• 제31권6_1호
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• pp.493-502
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• 2013

GIS에서 필요로 하는 다양한 공간정보의 요구 정확도는 활용목적에 따라 다르게 정의될 수 있으며, 공간정보에 대한 정확도는 측량 원자료의 품질과 관계된다. 따라서 정밀한 공간정보를 유용하게 활용하기 위해서는 기본도인 수치지도가 정확하게 제작될 수 있도록 정확도 기준이 적절하게 설정되어야 할 것이다. 컴퓨터 매핑 및 GIS 기술이 존재하기 전에는 종이지도가 수작업으로 그려졌기 때문에 지도의 축척은 지도의 정확도를 바로 의미하는 것이었다. 이렇듯 과거에는 지도의 정확도가 지도가 그려질 축척을 결정하였지만, 최근 디지털시대의 경향에서는 정확도가 지도 제작사양이라기 보다는 오히려 수치지도에 포함되는 품질요소 중 하나로 취급되고 있다. 이에 본 논문은 오늘날 정밀한 공간정보의 구축 및 활용에 적합한 수치지도의 정확도 기준으로서 현재 우리나라 수치지도의 표현방식을 대신하는 새로운 기준설정 방안을 제시하는 데 목적을 두고 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권2호
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• pp.729-748
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• 2021

Vocal detection is one of the fundamental steps in musical information retrieval. Typically, the detection process consists of feature extraction and classification steps. Recently, neural networks are shown to outperform traditional classifiers. In this paper, we report our study on how to improve detection accuracy further by carefully choosing the parameters of the deep network model. Through experiments, we conclude that a feature-classifier model is still better than an end-to-end model. The recommended model uses a spectrogram as the input plane and the classifier is an 18-layer convolutional neural network (CNN). With this arrangement, when compared with existing literature, the proposed model improves the accuracy from 91.8% to 94.1% in Jamendo dataset. As the dataset has an accuracy of more than 90%, the improvement of 2.3% is difficult and valuable. If even higher accuracy is required, the ensemble learning may be used. The recommend setting is a majority vote with seven proposed models. Doing so, the accuracy increases by about 1.1% in Jamendo dataset.

• Journal of Information Processing Systems
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• 제16권4호
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• pp.809-819
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• 2020

Gender prediction accuracy increases as convolutional neural network (CNN) architecture evolves. This paper compares voting and ensemble schemes to utilize the already trained five CNN models to further improve gender prediction accuracy. The majority voting usually requires odd-numbered models while the proposed softmax-based voting can utilize any number of models to improve accuracy. The ensemble of CNN models combined with one more fully-connected layer requires further tuning or training of the models combined. With experiments, it is observed that the voting or ensemble of CNN models leads to further improvement of gender prediction accuracy and that especially softmax-based voters always show better gender prediction accuracy than majority voters. Also, compared with softmax-based voters, ensemble models show a slightly better or similar accuracy with added training of the combined CNN models. Softmax-based voting can be a fast and efficient way to get better accuracy without further training since the selection of the top accuracy models among available CNN pre-trained models usually leads to similar accuracy to that of the corresponding ensemble models.

• Journal of Information Processing Systems
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• 제17권6호
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• pp.1083-1096
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• 2021

Compressed sensing-based matching pursuit algorithms can estimate the sparse channel of massive multiple input multiple-output systems with short pilot sequences. Although they have the advantages of low computational complexity and low pilot overhead, their accuracy remains insufficient. Simply multiplying the weight value and the estimated channel obtained in different iterations can only improve the accuracy of channel estimation under conditions of low signal-to-noise ratio (SNR), whereas it degrades accuracy under conditions of high SNR. To address this issue, an improved weighted matching pursuit algorithm is proposed, which obtains a suitable weight value u_op by training the channel data. The step of the weight value increasing with successive iterations is calculated according to the sparsity of the channel and u_op. Adjusting the weight value adaptively over the iterations can further improve the accuracy of estimation. The results of simulations conducted to evaluate the proposed algorithm show that it exhibits improved performance in terms of accuracy compared to previous methods under conditions of both high and low SNR.