• Journal of the Korea Convergence Society
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• v.12 no.8
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• pp.229-243
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• 2021

As systematic information protection and management is recognized as an organization's core value, organizations are pursuing a shift from an individual-centered information management method to an organization-oriented information management method. The Enterprise content management system(ECMS) is a solution that supports document security and information sharing by insiders and is being introduced by many organizations due to recent technological developments. The purpose of this study is to present a method of improving performance through continuous use of the ECMS from the user's point of view and also suggest a method to improve the intention of continuous use through the expansion of the technology acceptance model. This study surveyed the employees of organizations that adopted the ECMS and verified the research hypothesis derived from previous studies through structural equation modeling. As a result of the analysis, usefulness, and ease of use affected on the intention of continuous use of the ECMS, and the knowledge sharing culture and the ECMS quality factors affected the technology acceptance model factors. The results of this study have academic and practical significance in terms of suggesting a plan to increase the usability of the ECMS from the user's point of view.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.53-67
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• 2021

According to statistics, the number of mobile payment users in China shows an increasing trend year by year. However, less than half of people over 60 years old use mobile payment. The purpose of this study is to explore the reasons for the low usage rate of mobile payment platforms among the elderly in China. Through literature research, questionnaires and interviews, the author found that the main obstacle for the elderly in China to use mobile payment platforms is acceptance barrier. Then, the user experience research method and technology acceptance model (TAM) were combined to construct a new research model and five hypotheses affecting acceptance behavior in the model were summarized. Finally, the Analysis of Covariance(ANCOVA) was used to test the hypotheses and found that satisfaction (SA), perceived usefulness (PU) and job relevance (JR) had significant coefficients of 0.001, 0.000 and 0.004 respectively, all of which were less than 0.05 and therefore had a significant effect on acceptability. The other two elements, perceived ease of use (PE) and self-efficacy (SE), did not have a significant effect on acceptability. Ultimately, a new user experience acceptability model was constructed to provide theoretical support for mobile payment platform developers and designers to develop products from the acceptability perspective, so as to develop more mobile payment methods suitable for elderly users and improve the acceptance of mobile payment by the elderly.

• Journal of the Korea Convergence Society
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• v.10 no.5
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• pp.359-367
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• 2019

This study was done to examine the effect of 'Zippy's friends' program based on stress coping model for early child. A nonequivalent control group was designed to conduct a pre-post test for this study. The participants for this study were 148 first grade elementary school students in G city(experimental group=72, control group=76). The experimental group received 'Zippy's friends program for 24 weeks (6 module, 24 hours). The control group did not receive any treatment. From April to December 2017 data were collected using self-report structured questionnaires, and were analyzed using the ${\chi}^2$-test, t-test, and ANCOVA with SPSS/WIN 20.0 Program. After the treatment, significant differences were found between the experimental group and control groups in terms of stress coping ability( F=22.77, p<.001),but not in level of emotional intelligence (t=-.37, p=.715). Results of this study indicate that Zippy's program can be used in school based practice as an effective mental health intervention for early child.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.10
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• pp.794-801
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• 2017

In this paper, we proposed airborne target recognition using multi-channel combining method in DTV-based passive radar. By combining multi-channel signals, we obtained the HRRP with sufficient range resolution. HRRP was obtained by AR method or zero-padding. From the obtained HRRP, we extracted scattering centers by CLEAN algorithm using the gradient descent. We extracted feature vectors and performed target recognition after training neural network using the extracted feature vectors. To verify performance of proposed methods, we assumed frequency bands of three broadcasting transmitters operated in Korea(Mt. Gwan-ak, Mt. Yong-moon, Kyeon-wol-ak) and used full scale 3D CAD model of four targets. Also we compared the target recognition performance of the proposed method with that of using only single-channel of three broadcasting transmitters. As a result, proposed methods showed better performance than using only single-channel at three broadcasting transmitters.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.6
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• pp.641-650
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• 2011

Airborne LIDAR system, utilized in various forest studies, provides efficiently spatial information about vertical structures of forest areas. The tree height is one of the most essential measurements to derive forest information such as biomass, which can be estimated from the forest terrain model. As the terrain model is generated by the interpolation of ground points extracted from LIDAR data, filtering methods with high reliability to classify reliably the ground points are required. In this paper, we applied three representative filtering methods to forest LIDAR data with diverse characteristics, measured the errors and performance of these methods, and analyzed the causes of the errors. Based on their complementary characteristics derived from the analysis results, we have attempted to combine the results and checked the performance improvement. In most test areas, the convergence method showed the satisfactory results, where the filtering performance were improved more than 10% in maximum. Also, we have generated DTM using the classified ground points and compared with the verification data. The DTM retains about 17cm RMSE, which can be sufficiently utilized for the derivation of forest information.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.9
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• pp.928-935
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• 2013

This paper proposed a combining technique of feature vectors which improves the performance of radar target recognition. The proposed method obtains more information than monostatic or bistatic case by combining extracted feature vectors from two receivers. For verifying the performance of the proposed method, we calculated monostatic and bistatic RCS(BRCS) of three full-scale fighters by changing the receiver position. Then, the scattering centers are extracted using 1-D FFT-based CLEAN from the calculated RCS data. Scattering centers are used as feature vectors for neural network classifier. The results show that our method has the better performance than the monostatic or bistatic case.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.424-424
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• 2018

인공신경망(Artificial Neural Network; ANN)은 뇌에 존재하는 생물학적 신경세포와 이들의 신호처리 과정을 수학적으로 묘사하여 뇌가 나타내는 지능적 형태의 반응을 구현한 것이다. 인공신경망은 학습(training)을 통해 입력과 출력으로 구성되는 하나의 시스템을 병렬적이고 비선형적으로 구축할 수 있으며, 유연한 모델링 특성으로 인하여 시스템 예측, 패턴인식, 분류 및 공정제어 등의 다양한 분야에서 활용되고 있다. 인공신경망에 대한 최초의 이론은 Muculloch and Pitts(1943)가 제안한 Perceptron에서 시작 되었으며, 기본적인 학습기법인 오차역전파 기법(back-propagation Algorithm) 이 1980년대에 들어 수학적으로 정립된 이후 여러 분야에서 활용되기 시작하였다). 본 연구에서는 하도추적, 구체적으로는 상류단의 복수의 수위관측을 이용하여 하류단의 수위를 예측하기 위하여 인공신경망 모델을 구성하였다. 대상하도는 금강유역의 용담댐과 대청댐 사이의 본류이며, 상류단 입력자료로써 본류에 있는 수통, 호탄 관측소 관측수위와 지류인 송천 관측소 관측수위를 고려하였다. 출력 값으로는 하류단의 옥천 관측소 수위를 3시간 및 6시간의 선행시간으로 예측하도록 인공신경망 모형을 구성하였다. 인공신경망의 학습(testing), 시험(testing), 검증(validation)을 위해 2000년부터 2012년까지 13년간의 시수위자료를 이용하여 학습을 진행하였으며, 2013년부터 2014년의 2년간의 수위자료를 이용한 시험을 통해 최적의 모형을 선정하였다. 또한 선정된 최적의 모형을 이용하여 2015년부터 2016년까지의 수위예측을 수행하였다.

• Journal of the Korea Convergence Society
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• v.10 no.9
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• pp.23-29
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• 2019

In this paper, the mood of images was classified into eight categories through a deep convolutional neural network and video was automatically generated using proper background music. Based on the collected image data, the classification model is learned using a multilayer perceptron (MLP). Using the MLP, a video is generated by using multi-class classification to predict image mood to be used for video generation, and by matching pre-classified music. As a result of 10-fold cross-validation and result of experiments on actual images, each 72.4% of accuracy and 64% of confusion matrix accuracy was achieved. In the case of misclassification, by classifying video into a similar mood, it was confirmed that the music from the video had no great mismatch with images.

• Journal of the Korea Society for Simulation
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• v.19 no.2
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• pp.137-145
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• 2010

This study presents an RTS(Real-time Traffic System) based on an LBS(Location Based Service) using 5.8~5.9GHz RSU(Road Side Unit). The proposed LBI(Location based Broadcast system on ITS) is a local information-based service supported by RSU for drivers, which has a feature of convergence between T-DMB system and ITS-based RTS. The convergence of local broadcasting station and ITS is realized by two-way communication and supports LBS(Location Based Service) by identifying of vehicle's location using RSU. Real-time information delivery and various services could be provided by information exchanges between LMM and local broadcasting stations. Furthermore, conventional technical limitations have been solved mutually such as transmission area limitation in RTS and one-way communication problem in T-DMB. This support real-time two-way communication to each driver. Therefore, it can be expected that traffic dispersion effects and services expansion for drivers by RTS and LBI. Finally, it is proposed to built and implement test-bed around institute.

• Korean Journal of Construction Engineering and Management
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• v.9 no.6
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• pp.129-136
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• 2008

There is a tremendous need for an effective indoor facility management since the building are tend to be built taller and bigger due to latest technology. Also, information that is continuously used and transferred during the design and construction phase is emerging due to 3D object-oriented CAD. Therefore, a system that will use such information for facility management should be developed. In this study, we have defined a process that will automatically create an spatial network model and also verified the usability by establishing an sample model. As a result, an effective spatial network has been generated and an evacuation path finder was found efficiently.