• Title/Summary/Keyword: data expansion

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New reversible data hiding algorithm based on difference expansion method

  • Kim, Hyoung-Joong;Sachnev, Vasiliy;Kim, Dong-Hoi
    • Journal of Broadcast Engineering
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    • v.12 no.2
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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.

Urban Sprawl prediction in 2030 using decision tree (의사결정나무를 활용한 2030년 도시 확장 예측)

  • Kim, Geun-Han;Choi, Hee-Sun;Kim, Dong-Beom;Jung, Yee-Rim;Jin, Dae-Yong
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.23 no.6
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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.

Modeling on Expansion Behavior of Gwangan Bridge using Machine Learning Techniques and Structural Monitoring Data (머신러닝 기법과 계측 모니터링 데이터를 이용한 광안대교 신축거동 모델링)

  • Park, Ji Hyun;Shin, Sung Woo;Kim, Soo Yong
    • Journal of the Korean Society of Safety
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    • v.33 no.6
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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.

Expansion Valves Characteristics for Development of Control System on Air Conditioning and Refrigeration Systems (공조.냉동장치의 제어시스템 개발을 위한 팽창밸브 특성)

  • Kim, J.D.;Jang, J.E.;Yoon, J.I.
    • Journal of Power System Engineering
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    • v.2 no.3
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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.

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Image Comparison Using Directional Expansion Operation

  • Yoo, Suk Won
    • International Journal of Advanced Culture Technology
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    • v.6 no.3
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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.

A Speech Homomorphic Encryption Scheme with Less Data Expansion in Cloud Computing

  • Shi, Canghong;Wang, Hongxia;Hu, Yi;Qian, Qing;Zhao, Hong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.5
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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.

POST-OCCUPANCY EVALUATION (POE) AFTER THE EXPANSION OF AN APARTMENT PARKING LOT

  • Park, Jin-Gu;Oh, Kyung-Taek;Ryu, Gyu-Seok;Jung, In-Su;Lee, Chan-Sik
    • International conference on construction engineering and project management
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    • 2009.05a
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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.

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Mode shape expansion with consideration of analytical modelling errors and modal measurement uncertainty

  • Chen, Hua-Peng;Tee, Kong Fah;Ni, Yi-Qing
    • Smart Structures and Systems
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    • v.10 no.4_5
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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.

Analysis of the Relationship between Brand Management and International Expansion of Franchise Companies Using Big Data

  • Munyeong Yun;Yang-Ja Bae;Gi-Hwan Ryu
    • International journal of advanced smart convergence
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    • v.13 no.3
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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

Evaluation of Data-based Expansion Joint-gap for Digital Maintenance (디지털 유지관리를 위한 데이터 기반 교량 신축이음 유간 평가 )

  • Jongho Park;Yooseong Shin
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.28 no.2
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    • pp.1-8
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    • 2024
  • The expansion joint is installed to offset the expansion of the superstructure and must ensure sufficient gap during its service life. In detailed guideline of safety inspection and precise safety diagnosis for bridge, damage due to lack or excessive gap is specified, but there are insufficient standards for determining the abnormal behavior of superstructures. In this study, a data-based maintenance was proposed by continuously monitoring the expansion-gap data of the same expansion joint. A total of 2,756 data were collected from 689 expansion joint, taking into account the effects of season. We have developed a method to evaluate changes in the expansion joint-gap that can analyze the thermal movement through four or more data at the same location, and classified the factors that affect the superstructure behavior and analyze the influence of each factor through deep learning and explainable artificial intelligence(AI). Abnormal behavior of the superstructure was classified into narrowing and functional failure through the expansion joint-gap evaluation graph. The influence factor analysis using deep learning and explainable AI is considered to be reliable because the results can be explained by the existing expansion gap calculation formula and bridge design.