• Korean Journal of Social Welfare Studies
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• v.41 no.2
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• pp.247-278
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• 2010

There are three main purposes of this study: (a) to investigate the developmental trajectories of psychological resilience, social resilience, and school resilience of adolescents in poverty, (b) to identify the longitudinal relationship of three resiliences and (c) to examine the protective factors that help adolescents to develop successfully in the face of poverty. Data were drawn from Korea Youth Panel Survey(KYPS), a longitudinal panel study on Middle school students in the second grade. Sample consists of 648 adolescents in poverty who particiipated in the KYPS. Latent Growth Curve Model(LGM) was used to analyze intraindividual changes in resiliences and interindividual differences in these changes. And AMOS 7.0 and SPSS 15.0 were used. In this study, it is concluded that the resilience of adolescents in poverty is the construct that has uni-dimensionality and multi-dimensionality at the same time. Therefore, in order to improve resilience of adolescents in poverty, protective factors associated with each resilience have to be increased. Those findings have provided various theoretical and practical implications for social workers and professionals helping adolescents in poverty.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1031-1040
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• 2023

Propagation characteristics in line-of-sight(LOS) paths in 3, 6, 10, and 17 GHz frequency bands were measured and analyzed in two different indoor corridors: second floors of Buildings D2 and E2. The measurement was designed to measure when the receiving antenna moved at 0.5 m intervals from 3 m to 30 m, while the transmission antenna was fixed. The analysis of the two indoor corridors was compared by applying basic transmission loss, root mean square (RMS) delay spread, and K-factor. For basic transmission loss, the loss coefficient of the floating intercept path loss model was higher in the indoor corridor of Building E2 than in that of Building D2. Similarly, the RMS delay spread in the time domain was greater in the indoor corridor of Building E2. However, the indoor corridor of Building D2 exhibited higher K-factor in the 3, 6, and 17 GHz bands with lower wave propagation in the 10 GHz band. Despite the 2 indoor corridors being identical, the propagation characteristics varied due to different internal structures and materials. The results provide measurement data for ITU-R Recommendations regarding various indoor environments.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.6
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• pp.307-317
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• 2002

In this paper we propose a new mesh reconstruction scheme that produces a displaced subdivision surface directly from unorganized points. The displaced subdivision surface is a new mesh representation that defines a detailed mesh with a displacement map over a smooth domain surface, but original displaced subdivision surface algorithm needs an explicit polygonal mesh since it is not a mesh reconstruction algorithm but a mesh conversion (remeshing) algorithm. The main idea of our approach is that we sample surface detail from unorganized points without any topological information. For this, we predict a virtual triangular face from unorganized points for each sampling ray from a parameteric domain surface. Direct displaced subdivision surface reconstruction from unorganized points has much importance since the output of this algorithm has several important properties: It has compact mesh representation since most vertices can be represented by only a scalar value. Underlying structure of it is piecewise regular so it ran be easily transformed into a multiresolution mesh. Smoothness after mesh deformation is automatically preserved. We avoid time-consuming global energy optimization by employing the input data dependant mesh smoothing, so we can get a good quality displaced subdivision surface quickly.

• Journal of Plant Biotechnology
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• v.43 no.3
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• pp.359-366
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• 2016

Tradescantia is a perennial plant in the family of Commelinaceae. It is known to be sensitive to radiation. In this study, Tradescantia BNL 4430 was irradiated with gamma radiation at doses of 50 to 1,000 mGy in a phytotron equipped with a $^{60}Co$ radiation source at Korea Atomic Energy Research Institute, Korea. At 13 days after irradiation, we extracted RNA from irradiated floral tissues for RNA-seq. Transcriptome assembly produced a total of 77, 326 unique transcripts. In plantlets exposed to 50, 250, 500, and 1000 mGy, the numbers of up-regulated genes with more than 2-fold of expression compared that in the control were 116, 222, 246, and 308, respectively. Most of the up-regulated genes induced by 50 mGy were heat shock proteins (HSPs) such as HSP 70, indicating that protein misfolding, aggregation, and translocation might have occurred during radiation stress. Similarly, highly up-regulated transcripts of the IQ-domain 6 were induced by 250 mGy, KAR-UP oxidoreductase 1 was induced by 500 mGy, and zinc transporter 1 precursor was induced by 1000 mGy. Reverse transcriptase (RT) PCR and quantitative real time PCR (qRT-PCR) further validated the increased mRNA expression levels of selected genes, consistent with DEG analysis results. However, 2.3 to 97- fold higher expression activities were induced by different doses of radiation based on qRT-PCR results. Results on the transcriptome of Tradescantia in response to radiation might provide unique identifiers to develop in situ monitoring kit for measuring radiation exposure around radiation facilities.

• Journal of Korean Society of Forest Science
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• v.94 no.6
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• pp.496-503
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• 2005

This study was conducted to investigate the influences of sapflow flux on soil water tensions and soil moisture content at the Abies holophylla plots in Gwangneung, Gyeonggido, from September to October 2004. The Abies holophylla had been planted in 1976 and thinning and pruning were carried out in 1996 and 2004. Sapflow flux was measured by the heat pulse method, and soil water tension was measured by tensiometer at hillslope and streamside. Time domain reflectometry probes (TDR) were positioned horizontally at the depth of 10, 30 and 50 cm to measure soil moisture content. All of data were recorded every 30 minutes with the dataloggers. The sapflow flux responded sensitively to rainfall, so little sapflow was detected in rainy days. The average daily sapflow flux of sample trees was 10.16l, a maximum was 15.09l, and a minimum was 0.0l. The sapflow flux's diurnal changes showed that sapflow flux increased from 9 am and up to 0.74 l/30 min. The highest sapflow flux maintained by 3 pm and decreased almost 0.0 l/30 mm after 7 pm. The average soil water tensions were low ($-141.3cmH_2O$, $-52.9cmH_2O$ and $-134.2cmH_2O$) at hillslope and high ($-6.1cmH_2O$, $-18.0cmH_2O$ and $-3.7cmH_2O$) at streamside. When the soil moisture content decreased after rainfall, the soil water tension at hillslope responded sensitively to the sapflow flux. The soil water tension decreased as the sapflow flux increased during the day time, whereas increased during the night time when the sapflow flux was not detected. On the other hand, there was no significant relationship between soil water tension and sapflow flux at streamside. Soil moisture content at hillslope decreased continuously after rain, and showed a negative correlation to sapflow flux like a soil water tension at hillslope. As considered results above, it was confirmed that the response of soil moisture tension to sapflow flux at hillslope and streamside were different.

• Investigative Magnetic Resonance Imaging
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• v.8 no.2
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• pp.94-99
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• 2004

Purpose : To investigate the signal enhancement ratio by NOE effect on in vivo $^{31}P$ MRS in human heart muscle and liver. we also evaluated the enhancement ratios of different phosphorus metabolites, which are important in 31P MRS for each organ. Materials and Methods : Ten normal subjects (M:F = 8:2, age range = 24-32 yrs) were included for in vivo $^{31}P$ MRS measurements on a 1.5 T whole-body MRI/MRS system using $^1H-^{31}P$ dual tuned surface coil. Two-dimensional Chemical Shift Imaging (2D CSI) pulse sequence for $^{31}P$ MRS was employed in all $^{31}P$ MRS measurements. First, $^{31}P$ MRS performed without NOE effect and then the same 2D CSI data acquisitions were repeated with NOE effect. After postprocessing the MRS raw data in the time domain, the signal enhancements in percent were estimated from the major metabolites. Results : The calculated NOE enhancement for liver $^{31}P$ MRS were $\alpha-ATP\;(7\%),\;\beta-ATP\;(9\%),\;\gamma-ATP\;(17\%),\;Pi\;(1\%),\;PDE\;(19\%)$ and $PME\;(31\%)$. Because there is no creatine kinase activity in liver, PCr signal is absent. For cardiac $^{31}P$ MRS, whole body coil gave better scout images and thus better localization than surface coil. In $^{31}P$cardiac multi-voxel spectra, DPG signal increased from left to right according to the amount of blood included. The calculated enhancement for cardiac $^{31}P$ MRS were : $\alpha-ATP\;(12\%),\;\beta-ATP\;(19\%),\;\gamma-ATP\;(30\%),\;PCr\;(34\%),\;Pi\;(20\%),\;(PDE)\;(51\%),\;and\;DPG\;(72\%)$. Conclusion : Our results revealed that the NOE effect was more pronounced in heart muscle than in liver with different coupling to 1H spin system and thus different heteronuclear cross-relaxation.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.43-61
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• 2019

Development of technologies in artificial intelligence has been rapidly increasing with the Fourth Industrial Revolution, and researches related to AI have been actively conducted in a variety of fields such as autonomous vehicles, natural language processing, and robotics. These researches have been focused on solving cognitive problems such as learning and problem solving related to human intelligence from the 1950s. The field of artificial intelligence has achieved more technological advance than ever, due to recent interest in technology and research on various algorithms. The knowledge-based system is a sub-domain of artificial intelligence, and it aims to enable artificial intelligence agents to make decisions by using machine-readable and processible knowledge constructed from complex and informal human knowledge and rules in various fields. A knowledge base is used to optimize information collection, organization, and retrieval, and recently it is used with statistical artificial intelligence such as machine learning. Recently, the purpose of the knowledge base is to express, publish, and share knowledge on the web by describing and connecting web resources such as pages and data. These knowledge bases are used for intelligent processing in various fields of artificial intelligence such as question answering system of the smart speaker. However, building a useful knowledge base is a time-consuming task and still requires a lot of effort of the experts. In recent years, many kinds of research and technologies of knowledge based artificial intelligence use DBpedia that is one of the biggest knowledge base aiming to extract structured content from the various information of Wikipedia. DBpedia contains various information extracted from Wikipedia such as a title, categories, and links, but the most useful knowledge is from infobox of Wikipedia that presents a summary of some unifying aspect created by users. These knowledge are created by the mapping rule between infobox structures and DBpedia ontology schema defined in DBpedia Extraction Framework. In this way, DBpedia can expect high reliability in terms of accuracy of knowledge by using the method of generating knowledge from semi-structured infobox data created by users. However, since only about 50% of all wiki pages contain infobox in Korean Wikipedia, DBpedia has limitations in term of knowledge scalability. This paper proposes a method to extract knowledge from text documents according to the ontology schema using machine learning. In order to demonstrate the appropriateness of this method, we explain a knowledge extraction model according to the DBpedia ontology schema by learning Wikipedia infoboxes. Our knowledge extraction model consists of three steps, document classification as ontology classes, proper sentence classification to extract triples, and value selection and transformation into RDF triple structure. The structure of Wikipedia infobox are defined as infobox templates that provide standardized information across related articles, and DBpedia ontology schema can be mapped these infobox templates. Based on these mapping relations, we classify the input document according to infobox categories which means ontology classes. After determining the classification of the input document, we classify the appropriate sentence according to attributes belonging to the classification. Finally, we extract knowledge from sentences that are classified as appropriate, and we convert knowledge into a form of triples. In order to train models, we generated training data set from Wikipedia dump using a method to add BIO tags to sentences, so we trained about 200 classes and about 2,500 relations for extracting knowledge. Furthermore, we evaluated comparative experiments of CRF and Bi-LSTM-CRF for the knowledge extraction process. Through this proposed process, it is possible to utilize structured knowledge by extracting knowledge according to the ontology schema from text documents. In addition, this methodology can significantly reduce the effort of the experts to construct instances according to the ontology schema.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.1
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• pp.67-83
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• 2023

The social venture start-up phenomenon is found from the perspectives of social enterprise and for-profit enterprise. This study aims to fundamentally explore the start-up phenomenon of social ventures from these two perspectives. Considering the lack of prior research that researched both social and commercial perspectives at the same time, this paper analyzed using grounded theory approach of Strauss & Corbin(1998), an inductive research method that analyzes based on prior research and interview data. In order to collect data for this study, eight corporate representatives currently operating social ventures were interviewed and data and phenomena were analyzed. This progressed to a theoretical saturation where no additional information was derived. The analysis results of this study using the grounded theory approach are as follows. As a result of open coding and axial coding, 147 concepts and 70 subcategories were derived, and 18 categories were derived through the final abstraction process. In the selective coding, 'expansion of social venture entry in the social domain' and 'expansion of social function of for-profit companies' were selected as key categories, and a story line was formed around this. In this study, we saw that it is necessary to conduct academic research and analysis on the competitive factors required for companies that pursue the values of two conflicting relationships, such as social ventures, to survive with competitiveness. In practice, concepts such as collaboration with for-profit companies, value combination, entrepreneurship competency and performance improvement, social value execution competency reinforcement, communication strategy, for-profit enterprise value investment, and entrepreneur management competency were derived. This study explains the social venture phenomenon for social enterprises, commercial enterprises, and entrepreneurs who want to enter the social venture field. It is expected to provide the implications necessary for successful social venture startups.

• Geophysics and Geophysical Exploration
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• v.14 no.1
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• pp.98-104
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• 2011

Numerical simulation in exploration geophysics provides important insights into subsurface wave propagation phenomena. Although elastic wave simulations take longer to compute than acoustic simulations, an elastic simulator can construct more realistic wavefields including shear components. Therefore, it is suitable for exploration of the responses of elastic bodies. To overcome the long duration of the calculations, we use a Graphic Processing Unit (GPU) to accelerate the elastic wave simulation. Because a GPU has many processors and a wide memory bandwidth, we can use it in a parallelised computing architecture. The GPU board used in this study is an NVIDIA Tesla C1060, which has 240 processors and a 102 GB/s memory bandwidth. Despite the availability of a parallel computing architecture (CUDA), developed by NVIDIA, we must optimise the usage of the different types of memory on the GPU device, and the sequence of calculations, to obtain a significant speedup of the computation. In this study, we simulate two- (2D) and threedimensional (3D) elastic wave propagation using the Finite-Difference Time-Domain (FDTD) method on GPUs. In the wave propagation simulation, we adopt the staggered-grid method, which is one of the conventional FD schemes, since this method can achieve sufficient accuracy for use in numerical modelling in geophysics. Our simulator optimises the usage of memory on the GPU device to reduce data access times, and uses faster memory as much as possible. This is a key factor in GPU computing. By using one GPU device and optimising its memory usage, we improved the computation time by more than 14 times in the 2D simulation, and over six times in the 3D simulation, compared with one CPU. Furthermore, by using three GPUs, we succeeded in accelerating the 3D simulation 10 times.

• Journal of Korea Soil Environment Society
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• v.2 no.2
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• pp.81-94
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• 1997

In many solute transport studies, either flux or resident concentration has been used. Choice of the concentration mode was dependent on the monitoring device in solute displacement experiments. It has been accepted that no priority exists in the selection of concentration mode in the study of solute transport. It would be questionable, however, to accept the equivalency in the solute transport parameters between flux and resident concentrations in structured soils exhibiting preferential movement of solute. In this study, we investigate how they differ in the monitored breakthrough curves (BTCs) and transport parameters for a given boundary and flow condition by performing solute displacement experiments on a number of undisturbed soil columns. Both flux and resident concentrations have been simultaneously obtained by monitoring the effluent and resistance of the horizontally-positioned TDR probes. Two different solute transport models namely, convection-dispersion equation (CDE) and convective lognormal transfer function (CLT) models, were fitted to the observed breakthrough data in order to quantify the difference between two concentration modes. The study reveals that soil columns having relatively high flux densities exhibited great differences in the degree of peak concentration and travel time of peak between flux and resident concentrations. The peak concentration in flux mode was several times higher than that in resident one. Accordingly, the estimated parameters of flux mode differed greatly from those of resident mode and the difference was more pronounced in CDE than CLT model. Especially in CDE model, the parameters of flux mode were much higher than those of resident mode. This was mainly due to the bypassing of solute through soil macropores and failure of the equilibrium CDE model to adequate description of solute transport in studied soils. In the domain of the relationship between the ratio of hydrodynamic dispersion to molecular diffusion and the peclet number, both concentrations fall on a zone of predominant mechanical dispersion. However, it appears that more molecular diffusion contributes to the solute spreading in the matrix region than the macropore region due to the nonliearity present in the pore water velocity and dispersion coefficient relationship.