• 방송공학회논문지
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• 제12권2호
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• pp.112-119
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• 2007

Reversible data embedding theory has marked a new epoch for data hiding and information security. Being reversible, the original data and the embedded data as well should be completely restored. Difference expansion transform is a remarkable breakthrough in reversible data hiding scheme. The difference expansion method achieves high embedding capacity and keeps the distortion low. This paper shows that the difference expansion method with simplified location map, and new expandability and changeability can achieve more embedding capacity while keeping the distortion almost the same as the original expansion method.

• 한국환경복원기술학회지
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• 제23권6호
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• pp.125-135
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• 2020

The uncontrolled urban expansion causes various social, economic problems and natural/environmental problems. Therefore, it is necessary to forecast urban expansion by identifying various factors related to urban expansion. This study aims to forecast it using a decision tree that is widely used in various areas. The study used geographic data such as the area of use, geographical data like elevation and slope, the environmental conservation value assessment map, and population density data for 2006 and 2018. It extracted the new urban expansion areas by comparing the residential, industrial, and commercial zones of the zoning in 2006 and 2018 and derived a decision tree using the 2006 data as independent variables. It is intended to forecast urban expansion in 2030 by applying the data for 2018 to the derived decision tree. The analysis result confirmed that the distance from the green area, the elevation, the grade of the environmental conservation value assessment map, and the distance from the industrial area were important factors in forecasting the urban area expansion. The AUC of 0.95051 showed excellent explanatory power in the ROC analysis performed to verify the accuracy. However, the forecast of the urban area expansion for 2018 using the decision tree was 15,459.98㎢, which was significantly different from the actual urban area of 4,144.93㎢ for 2018. Since many regions use decision tree to forecast urban expansion, they can be useful for identifying which factors affect urban expansion, although they are not suitable for forecasting the expansion of urban region in detail. Identifying such important factors for urban expansion is expected to provide information that can be used in future land, urban, and environmental planning.

• 한국안전학회지
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• 제33권6호
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• pp.42-49
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• 2018

In this study, we have developed a prediction model for expansion and contraction behaviors of expansion joint in Gwangan Bridge using machine learning techniques and bridge monitoring data. In the development of the prediction model, two famous machine learning techniques, multiple regression analysis (MRA) and artificial neural network (ANN), were employed. Structural monitoring data obtained from bridge monitoring system of Gwangan Bridge were used to train and validate the developed models. From the results, it was found that the expansion and contraction behaviors predicted by the developed models are matched well with actual expansion and contraction behaviors of Gwangan Bridge. Therefore, it can be concluded that both MRA and ANN models can be used to predict the expansion and contraction behaviors of Gwangan Bridge without actual measurements of those behaviors.

• 동력기계공학회지
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• 제2권3호
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• pp.34-40
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• 1998

Performance characteristics of a refrigeration systems with various expansion valves and superheat changes were investigated experimentally. Experimental data have been taken utilizing three different devices; a thermostatic expansion valve, a linear type electronic expansion valve and a solenoid type electronic expansion valve. The data taken from tile three types of expansion valves were discussed with the temperature distribution of each zone in the evaporator and the superheat changes of the evaporator outlet In each zone temperature distribution fluctuated larger with the thermostatic expansion valve than with the electronic expansion valves. The optimum superheat ranged from $5^{\circ}C\;to\;15^{\circ}C$, and the superheat with the thermostatic expansion valve showed hunting phenomenon, which affected the evaporating and condensing temperature.

• International Journal of Advanced Culture Technology
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• 제6권3호
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• pp.173-177
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• 2018

Masks are generated by adding different fonts of learning data characters in pixel unit, and pixel values belonging to each of the masks are divided into 3 groups. Using the directional expansion operators, we expand the text area of the test data character into 4 diagonal directions in order to create the boundary areas to distinguish it from the background area. A mask with a minimum average discordance is selected as the final recognition result by calculating the degree of discordance between the expanded test data and the masks. Image comparison using directional expansion operations more accurately recognizes test data through 4 subdivided recognition processes. It is also possible to expand the ranges of 3 groups of pixel values of masks more evenly such that new fonts can easily be added to the given learning data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권5호
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• pp.2588-2609
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• 2019

Speech homomorphic encryption has become one of the key components in secure speech storing in the public cloud computing. The major problem of speech homomorphic encryption is the huge data expansion of speech cipher-text. To address the issue, this paper presents a speech homomorphic encryption scheme with less data expansion, which is a probabilistic statistics and addition homomorphic cryptosystem. In the proposed scheme, the original digital speech with some random numbers selected is firstly grouped to form a series of speech matrix. Then, a proposed matrix encryption method is employed to encrypt that speech matrix. After that, mutual information in sample speech cipher-texts is reduced to limit the data expansion. Performance analysis and experimental results show that the proposed scheme is addition homomorphic, and it not only resists statistical analysis attacks but also eliminates some signal characteristics of original speech. In addition, comparing with Paillier homomorphic cryptosystem, the proposed scheme has less data expansion and lower computational complexity. Furthermore, the time consumption of the proposed scheme is almost the same on the smartphone and the PC. Thus, the proposed scheme is extremely suitable for secure speech storing in public cloud computing.

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.1559-1563
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• 2009

Despite the serious lack of parking lots, studies on parking lot expansion are insufficient; research on users' satisfaction following parking lot expansion is practically nonexistent. Therefore, this study sought to provide basic data for the parking lot expansion of old apartments by comparatively analyzing users' satisfaction before and after the parking lot expansion through a questionnaire survey that targeted residents benefiting from the expanded parking lot. Results revealed a low post-occupancy satisfaction with the parking lot expansion despite the parking lot expansion and improvement of the parking lot environment. This was because the parking lot was not expanded up to the second basement floor due to the lack of appropriate parking space. Other factors included the construction cost burden and lack of connectivity of the basement parking lot with elevators. The results actually raise the need for the establishment of an optimally suitable expansion plan and development of method and technology requiring lower cost and shorter construction period in the design and construction processes for parking lot expansion. Through post-occupancy evaluation (POE) after parking lot expansion, this study quantitatively identified the problems associated with the parking lots of old apartments and ensuing expansion effects. The findings in this study can be used as basic data to seek a suitable diagnosis and evaluation method for the parking lots of old apartments.

• Smart Structures and Systems
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• 제10권4_5호
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• pp.485-499
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• 2012

Mode shape expansion is useful in structural dynamic studies such as vibration based structural health monitoring; however most existing expansion methods can not consider the modelling errors in the finite element model and the measurement uncertainty in the modal properties identified from vibration data. This paper presents a reliable approach for expanding mode shapes with consideration of both the errors in analytical model and noise in measured modal data. The proposed approach takes the perturbed force as an unknown vector that contains the discrepancies in structural parameters between the analytical model and tested structure. A regularisation algorithm based on the Tikhonov solution incorporating the L-curve criterion is adopted to reduce the influence of measurement uncertainties and to produce smooth and optimised expansion estimates in the least squares sense. The Canton Tower benchmark problem established by the Hong Kong Polytechnic University is then utilised to demonstrate the applicability of the proposed expansion approach to the actual structure. The results from the benchmark problem studies show that the proposed approach can provide reliable predictions of mode shape expansion using only limited information on the operational modal data identified from the recorded ambient vibration measurements.

• International journal of advanced smart convergence
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• 제13권3호
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• pp.306-311
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• 2024

In today's globalized economy, franchise companies are strategically preparing to expand beyond domestic markets into international markets. When expanding overseas, it is crucial that the brand identity of a franchise company is well established. Through marketing activities, the brand's value must be enhanced to build a positive image of the brand, and all these activities are referred to as brand management. This study aimed to analyze the relationship between brand management and international expansion, utilizing big data analysis techniques with Textom. A total of 31,564 pieces of data were collected for the period from January 1, 2024, to May 1, 2024, and analyzed after undergoing a refinement process. The analysis results showed that brand management is an essential element in the strategic process of international expansion, and subsequent studies should focus on qualitative research

• 한국구조물진단유지관리공학회 논문집
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• 제28권2호
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• pp.1-8
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• 2024

신축이음 장치는 교량 상부구조의 신축량을 수용할 목적으로 설치되며 공용중 충분한 유간을 확보하여야 한다. 안전점검 및 정밀안전진단 수행 시 유간부족 및 유간과다에 대한 손상을 명시하고 있으나, 유간에 따른 교량의 이상 거동을 판별하기 위한 기준이 미흡하다. 본 연구에서는 동일 신축이음부의 유간 데이터를 지속적으로 추적하여 데이터 기반의 유지관리 방안을 제시하였다. 689개소의 신축이음 장치에서 계절별 영향을 고려하여 총 2,756개의 유간 데이터를 수집하였다. 동일 위치에서 4개 이상의 데이터를 통해 신축거동을 분석할 수 있는 유간 변화 평가 방안을 마련하였으며, 신축거동에 영향을 미치는 인자를 분류하고 딥러닝과 설명 가능한 AI를 통해 각 인자의 영향도를 분석하였다. 유간 평가 그래프를 통해 교량 상부구조의 이상 거동을 협착 및 기능 고장으로 분류하였다. 이론적 거동을 보이고 있다하더라도 협착 가능성이 나타날 수 있는 사례 및 하절기 협착 가능성이 매우 높게 나타난 사례가 도출되었다. 협착 가능성은 낮으나 교량 상부구조에 기능상 문제점이 발생했을 가능성이 높은 사례와 시공오류에 따라 신축이음 장치가 재시공된 사례도 도출되었다. 딥러닝 및 설명 가능한 AI를 통한 영향인자 분석은 기존의 신축유간 계산식 및 교량 설계에 따른 결과로 설명 가능하여 신뢰 가능한 수준으로 판단되어 추후 모델의 개선을 통해 유지관리를 위한 가이드를 제시할 수 있을 것이라 판단된다.