• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.183-191
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• 2021

Non-intrusive load monitoring is a technology that can be used for predicting and classifying the type of appliances through real-time monitoring of user power consumption, and it has recently got interested as a means of energy-saving. In this paper, we propose a system for classifying appliances from user consumption data by combining GAF(Gramian angular field) technique that can be used for converting one-dimensional data to the two-dimensional matrix with convolutional neural networks. We use REDD(residential energy disaggregation dataset) that is the public appliances power data and confirm the classification accuracy of the GASF(Gramian angular summation field) and GADF(Gramian angular difference field). Simulation results show that both models showed 94% accuracy on appliances with binary-state(on/off) and that GASF showed 93.5% accuracy that is 3% higher than GADF on appliances with multi-state. In later studies, we plan to increase the dataset and optimize the model to improve accuracy and speed.

• Korean Journal of Remote Sensing
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• v.35 no.5_2
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• pp.841-850
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• 2019

The purpose of this study is to strengthen the capability of rapid mapping for disaster through improving the positioning accuracy of mapping and fusion of multi-sensing point cloud data derived from Unmanned Aerial Vehicles (UAVs) and disaster investigation vehicle. The positioning accuracy was evaluated for two procedures of drone mapping with Agisoft PhotoScan: 1) general geo-referencing by self-calibration, 2) proposed geo-referencing with optimized camera model by using fixed accurate Interior Orientation Parameters (IOPs) derived from indoor camera calibration test and bundle adjustment. The analysis result of positioning accuracy showed that positioning RMS error was improved 2~3 m to 0.11~0.28 m in horizontal and 2.85 m to 0.45 m in vertical accuracy, respectively. In addition, proposed data fusion approach of multi-sensing point cloud with the constraints of the height showed that the point matching error was greatly reduced under about 0.07 m. Accordingly, our proposed data fusion approach will enable us to generate effectively and timelinessly ortho-imagery and high-resolution three dimensional geographic data for national disaster management in the future.

• Journal of KIISE:Databases
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• v.31 no.6
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• pp.684-698
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• 2004

The Hippocratic database model recently proposed by Agrawal et al. incorporates privacy protection capabilities into relational databases. Since the Hippocratic database is based on the relational database, it needs extensions to be adapted for XML databases. In this paper, we propose the Hippocratic XML database model, an extension of the Hippocratic database model for XML databases and present an efficient access control mechanism under this model. In contrast to relational data, XML data have tree-like hierarchies. Thus, in order to manage these hierarchies of XML data, we extend and formally define such concepts presented in the Hippocratic database model as privacy preferences, privacy policies, privacy authorizations, and usage purposes of data records. Next, we present a new mechanism, which we call the authorization index, that is used in the access control mechanism. This authorization index, which is Implemented using a multi-dimensional index, allows us to efficiently search authorizations implied by the authorization granted on the nearest ancestor using the nearest neighbor search technique. Using synthetic and real data, we have performed extensive experiments comparing query processing time with those of existing access control mechanisms. The results show that the proposed access control mechanism improves the wall clock time by up to 13.6 times over the top-down access control strategy and by up to 20.3 times over the bottom-up access control strategy The major contributions of our paper are 1) extending the Hippocratic database model into the Hippocratic XML database model and 2) proposing an efficient across control mechanism that uses the authorization index and nearest neighbor search technique under this model.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.2
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• pp.80-98
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• 2023

This study explores the effectiveness of various data preprocessing algorithms for improving subseasonal to seasonal (S2S) climate predictions from six climate forecast models and their Multi-Model Ensemble (MME) using a deep learning-based postprocessing model. A pipeline of data transformation algorithms was constructed to convert raw S2S prediction data into the training data processed with several statistical distribution. A dimensionality reduction algorithm for selecting features through rankings of correlation coefficients between the observed and the input data. The training model in the study was designed with TimeDistributed wrapper applied to all convolutional layers of U-Net: The TimeDistributed wrapper allows a U-Net convolutional layer to be directly applied to 5-dimensional time series data while maintaining the time axis of data, but every input should be at least 3D in U-Net. We found that Robust and Standard transformation algorithms are most suitable for improving S2S predictions. The dimensionality reduction based on feature selections did not significantly improve predictions of daily precipitation for six climate models and even worsened predictions of daily maximum and minimum temperatures. While deep learning-based postprocessing was also improved MME S2S precipitation predictions, it did not have a significant effect on temperature predictions, particularly for the lead time of weeks 1 and 2. Further research is needed to develop an optimal deep learning model for improving S2S temperature predictions by testing various models and parameters.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6B
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• pp.597-603
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• 2006

The purpose of this study is to improve the short term rainfall forecast skill using neural network model that can deal with the non-linear behavior between satellite data and ground observation, and minimize the flood damage. To overcome the geographical limitation of Korean peninsula and get the long forecast lead time of 3 to 6 hour, the developed rainfall forecast model took satellite imageries and wide range AWS data. The architecture of neural network model is a multi-layer neural network which consists of one input layer, one hidden layer, and one output layer. Neural network is trained using a momentum back propagation algorithm. Flood was estimated using rainfall forecasts. We developed a dynamic flood inundation model which is associated with 1-dimensional flood routing model. Therefore the model can forecast flood aspect in a protected lowland by levee failure of river. In the case of multiple levee breaks at main stream and tributaries, the developed flood inundation model can estimate flood level in a river and inundation level and area in a protected lowland simultaneously.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.4
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• pp.165-175
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• 2006

The discussion about capacity development (CD) has been spotlighted as significant drivers for sustainable development in recent years. Multi-dimensional natures of capacities would lead to various definitions of CD in international institutes and organizations. CD is perceived as an endogeneous process to improve actionable learning and knowledge, but most of core capacities still remain abstract notion and might be unreliable in sustainable development (SD). The paper first explicates international perspectives of CD in association with SD. An agent-based model is especially proposed to portray more details of CD. It illuminates the role of assets (or capitals, resources) in agents to impact on ingredients of CDs that are drivers or enablers for improvement of SD. A definition of sustainable capacity development is firstly articulated in international society and its conceptual framework is also creatively designed to assist concerned international organizations. The paper concludes by proposing practical spatial asset mapping linking to agent-based organizational capacity as a tool for measuring sustainable capacity development.

• Journal of The Korean Association of Information Education
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• v.18 no.4
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• pp.529-540
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• 2014

We propose an efficient information science teaching-learning method to improve information-scientific creativity of mathematically and scientifically gifted students. The students are able to improve their creative problem solving and team-work abilities through team project work to resolve a variety of application problem in real world. In the pursuit of this purpose, we designed a new two-stage information science learning method consisted of the standard stage and the application stage, and a new systemic project process. Moreover, we applied small-scale cooperation learning strategies and a multi-dimensional assessment system. The analysis on our proposed model shows that there is a remarkable achievement of educational objectives on cognitive capability, social and affective ability of information science creativity.

• Journal of the Korean Society of Safety
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• v.20 no.2 s.70
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• pp.26-31
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• 2005

The strong continuous fiber reinforced metal matrix composites (MMCs) are recently used in aerospace and transportation applications as an advanced material due to its high strength and light weight. Unidirectional fiber-metal matrix composites have superior mechanical properties along the longitudinal direction. However, the applicability of continuous fiber reinforced MMCs is somewhat limited due to their relatively poor transverse properties. Therefore, the transverse properties of MMCs are significantly influenced by the properties of the fiber/matrix interface. In order to be able to utilize these MMCs effectively and with safety, it must be determined their elastic plastic behaviors at the interface. In this study, the interfacial stress states of transversely loaded unidirectional fiber reinforced metal matrix composites investigated by using elastic-plastic finite element analysis. Different fiber volume fractions $(5-60\%)$ were studied numerically. The interlace was treated as three thin layer (with different properties) with a finite thickness between the fiber and the matrix. The fiber is modeled as transversely isotropic linear-elastic, and the matrix as isotropic elastic-plastic material. Using proposed model, the effects of the interface region and fiber arrangement in MMCs on the distributions of stress and strain are evaluated. The stress distributions of a thin multi layer interface have much less changes compared with conventional perfect interface. The analyses were based on a two-dimensional generalized plane strain model of a cross-section of an unidirectional composite by the ANSYS finite element analysis code.

• Journal of Fashion Business
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• v.18 no.4
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• pp.80-96
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• 2014

The purpose of this study is to consider the expression of costume through the review of cinema costumes and to provide the model of cooperation between fashion and movie industry by analysis of collaboration with fashion brands in the movie . The subjects are the 1974 film directed by Jack Clayton and the 2013 version by Baz Luhrmann. Cinema Fashion was studied by analyzing the costumes of the two main characters, Gatsby and Daisy, in each scene. Gatsby's costume appeared as a model of traditional American classic suit, sensitive G-G look that symbolizes social success and traditional casual style that reflects upper-class life style. Daisy's costume expressed pastel toned luxury flapper look, oriental art deco style, and prestigious jewelry representing high class. The collaborations with fashion brands were carried out with Ralph Lauren and Cartier in 1974 film, and Brooks Brothers, Prada, and Tiffany in 2013. The value of prestige brands that matched the images of the movie was utilized, but marketing strategies for the promotion of fashion goods were not enough in 1974 version. On the other hand, in 2013 film, the effects of collaboration of the movie and fashion brands were forecasted sufficiently and marketing campaigns for promotion were performed in a various ways. The characteristics of collaborations were as follows: (1) the usage of prestige brands value, (2) collections planning and promotion using the stories of a movie, (3) the usage of multidirectional digital media, and (4) multi-dimensional promotion using entertainment factors. In collaborations with the movie, fashion brands could make cooperative relationship to produce the positive effects for promotion and prestige image strategies and draw attention of the people to the movie and fashion.

• Earthquakes and Structures
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• v.6 no.1
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• pp.71-87
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• 2014

Interaction between closely-spaced buildings subject to earthquake induced strong ground motions, termed in the literature as "seismic pounding", occurs commonly during major seismic events in contemporary congested urban environments. Seismic pounding is not taken into account by current codes of practice and is rarely considered in practice at the design stage of new buildings constructed "in contact" with existing ones. Thus far, limited research work has been devoted to quantify the influence of slab-to-slab pounding on the inelastic seismic demands at critical locations of structural members in adjacent structures that are not aligned in series. In this respect, this paper considers a typical case study of a "new" reinforced concrete (R/C) EC8-compliant, torsionally sensitive, 7-story corner building constructed within a block, in bi-lateral contact with two existing R/C 5-story structures with same height floors. A non-linear local plasticity numerical model is developed and a series of non-linear time-history analyses is undertaken considering the corner building "in isolation" from the existing ones (no-pounding case), and in combination with the existing ones (pounding case). Numerical results are reported in terms of averages of ratios of peak inelastic rotation demands at all structural elements (beams, columns, shear walls) at each storey. It is shown that seismic pounding reduces on average the inelastic demands of the structural members at the lower floors of the 7-story building. However, the discrepancy in structural response of the entire block due to torsion-induced, bi-directionally seismic pounding is substantial as a result of the complex nonlinear dynamics of the coupled building block system.