• Journal of Internet Computing and Services
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• v.17 no.4
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• pp.35-42
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• 2016

Recently many researches have been focused on the use of the markerless augmented reality system using face, foot, and hand of user's body to alleviate many disadvantages of the marker based augmented reality system. In addition, most existing augmented reality systems have been utilized rigid objects since they just desire to insert and to basic interaction with virtual object in the augmented reality system. In this paper, unlike restricted marker based augmented reality system with rigid objects that is based in display, we designed and implemented the markerless augmented reality system using deformable objects to apply various fields for interactive situations with a user. Generally, deformable objects can be implemented with mass-spring modeling and the finite element modeling. Mass-spring model can provide a real time simulation and finite element model can achieve more accurate simulation result in physical and mathematical view. In this paper, the proposed markerless augmented reality system utilize the mass-spring model using tetraheadron structure to provide real-time simulation result. To provide plausible simulated interaction result with deformable objects, the proposed method detects and tracks users hand with Kinect SDK and calculates the external force which is applied to the object on hand based on the position change of hand. Based on these force, 4th order Runge-Kutta Integration is applied to compute the next position of the deformable object. In addition, to prevent the generation of excessive external force by hand movement that can provide the natural behavior of deformable object, we set up the threshold value and applied this value when the hand movement is over this threshold. Each experimental test has been repeated 5 times and we analyzed the experimental result based on the computational cost of simulation. We believe that the proposed markerless augmented reality system with deformable objects can overcome the weakness of traditional marker based augmented reality system with rigid object that are not suitable to apply to other various fields including healthcare and education area.

• The Korean Journal of Nuclear Medicine
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• v.37 no.5
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• pp.288-300
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• 2003

Purpose: To obtain regional blood flow and tissue-blood partition coefficient with time-activity curves from ${H_2}^{15}O$ PET, fitting of some parameters in the Kety model is conventionally accomplished by nonlinear least squares (NLS) analysis. However, NLS requires considerable compuation time then is impractical for pixel-by-pixel analysis to generate parametric images of these parameters. In this study, we investigated several fast parameter estimation methods for the parametric image generation and compared their statistical reliability and computational efficiency. Materials and Methods: These methods included linear least squres (LLS), linear weighted least squares (LWLS), linear generalized least squares (GLS), linear generalized weighted least squares (GWLS), weighted Integration (WI), and model-based clustering method (CAKS). ${H_2}^{15}O$ dynamic brain PET with Poisson noise component was simulated using numerical Zubal brain phantom. Error and bias in the estimation of rCBF and partition coefficient, and computation time in various noise environments was estimated and compared. In audition, parametric images from ${H_2}^{15}O$ dynamic brain PET data peformed on 16 healthy volunteers under various physiological conditions was compared to examine the utility of these methods for real human data. Results: These fast algorithms produced parametric images with similar image qualify and statistical reliability. When CAKS and LLS methods were used combinedly, computation time was significantly reduced and less than 30 seconds for $128{\times}128{\times}46$ images on Pentium III processor. Conclusion: Parametric images of rCBF and partition coefficient with good statistical properties can be generated with short computation time which is acceptable in clinical situation.

• Journal of Nutrition and Health
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• v.51 no.4
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• pp.340-356
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• 2018

Purpose: This study was conducted to develop a nutrition quotient (NQ) to assess overall dietary quality and food behaviors of Korean adults. Methods: The NQ was developed in three steps: item generation, item reduction, and validation. Candidate items of the NQ checklist were derived from a systematic literature review, expert in-depth interviews, statistical analyses of the Korea National Health and Nutrition Examination Survey (2010 ~ 2013) data, and national nutrition policies and recommendations. A total of 368 adults (19 ~ 64 years) participated in a one-day dietary record survey and responded to 43 items in the food behavior checklist. Pearson's correlation coefficients between responses to the checklist items and nutritional intake status of the adults were calculated. Item reduction was performed, and 24 items were selected for a nationwide survey. A total of 1,053 nationwide adult subjects completed the checklist questionnaires. Exploratory and confirmatory factor analyses were performed to develop a final NQ model. Results: The 21 checklist items were used as final items for NQ. Checklist items were composed of four factors: nutrition balance (seven items), food diversity (three items), moderation for the amount of food intake (six items), and dietary behavior (five items). The four-factor structure accounted for 41.8% of the total variance. Indicator tests of the NQ model suggested an adequate model fit (GRI = 0.9693, adjusted GFI = 0.9617, RMR = 0.0054, SRMR = 0.0897, p < 0.05), and item loadings were significant for all subscales. Standardized path coefficients were used as weights of the items. The NQ and four-factor scores were calculated according to the obtained weights of the questionnaire items. Conclusion: NQ for adults would be a useful tool for assessing adult dietary quality and food behavior. Further investigations of adult NQ are needed to reflect changes in their food behavior, environment, and prevalence of chronic diseases.

• Korean Journal of Environmental Biology
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• v.37 no.4
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• pp.568-578
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• 2019

The nymphal development of the potato aphid, Macrosiphum euphorbiae (Thomas), was studied at seven constant temperatures (12.5, 15.0, 17.5, 20.0, 22.5, 25.0, and 27.5±1℃), 65±5% relative humidity (RH), and 16:8 h light/dark photoperiods. The developmental investigation of M. euphorbiae was separated into two steps, the 1^st through 2^nd and the 3^rd through 4^th stages. The mortality was under 10% at six temperatures. However, it was 53.0% at 27.5℃. The developmental time of the entire nymph stage was 15.5 days at 15.0℃, 6.7 days at 25.0℃, and 9.7 days at 27.5℃. In the immature stage, the lower threshold temperature of the larvae was 2.6℃ and the thermal constant was 144.5 DD. In our analysis of the temperature-development experiment, the Logan-6 model equation was most appropriate for the non-linear regression models (r²=0.99). When the distribution completion model of each development stage of M. euphorbiae larvae was applied to the 2-parameter and 3-parameter Weibull functions, each of the model's goodness of fit was very similar (r²=0.92 and 0.93, respectively). The adult longevity decreased as the temperature increased but the total fecundity of the females at each temperature was highest at 20℃. The life table parameters were calculated using the whole lifespan periods of M. euphorbiae at the above six temperatures. The net reproduction rate (R₀) was highest at 20.0℃(63.2). The intrinsic rate of increase (r_m) was highest at 25℃(1.393). The finite rate of doubling time (D_t) was the shortest at 25.0℃(2.091). The finite rate of increase (λ) was also the highest at 25.0℃(1.393). The mean generation time(T) was the shortest at 25.0℃(9.929).

• Korean Journal of Agricultural and Forest Meteorology
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• v.2 no.2
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• pp.47-61
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• 2000

Agroclimatic zoning was done for paddy rice culture in North Korea based on a simulation experiment. Daily weather data for the experiment were generated by 3 steps consisting of spatial interpolation based on topoclimatological relationships, zonal summarization of grid cell values, and conversion of monthly climate data to daily weather data. Regression models for monthly climatological temperature estimation were derived from a statistical procedure using monthly averages of 51 standard weather stations in South and North Korea (1981-1994) and their spatial variables such as latitude, altitude, distance from the coast, sloping angle, and aspect-dependent field of view (openness). Selected models (0.4 to 1.6$^{\circ}C$ RMSE) were applied to the generation of monthly temperature surface over the entire North Korean territory on 1 km$\times$l km grid spacing. Monthly precipitation data were prepared by a procedure described in Yun (2000). Solar radiation data for 27 North Korean stations were reproduced by applying a relationship found in South Korea ([Solar Radiation, MJ m$^{-2}$ day$^{-1}$ ] =0.344 + 0.4756 [Extraterrestrial Solar Irradiance) + 0.0299 [Openness toward south, 0 - 255) - 1.307 [Cloud amount, 0 - 10) - 0.01 [Relative humidity, %), $r^2$=0.92, RMSE = 0.95 ). Monthly solar irradiance data of 27 points calculated from the reproduced data set were converted to 1 km$\times$1 km grid data by inverse distance weighted interpolation. The grid cell values of monthly temperature, solar radiation, and precipitation were summed up to represent corresponding county, which will serve as a land unit for the growth simulation. Finally, we randomly generated daily maximum and minimum temperature, solar irradiance and precipitation data for 30 years from the monthly climatic data for each county based on a statistical method suggested by Pickering et a1. (1994). CERES-rice, a rice growth simulation model, was tuned to accommodate agronomic characteristics of major North Korean cultivars based on observed phenological and yield data at two sites in South Korea during 1995~1998. Daily weather data were fed into the model to simulate the crop status at 183 counties in North Korea for 30 years. Results were analyzed with respect to spatial and temporal variation in yield and maturity, and used to score the suitability of the county for paddy rice culture.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2002.06a
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• pp.148-155
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• 2002

Multithreaded models improve the efficiency of parallel systems by combining inner parallelism, asynchronous data availability and the locality of von Neumann model. This model executes thread code which is generated by compiler and of which quality is given by the method of generation. But multithreaded models have the demerit that execution model is restricted to a specific platform. On the contrary, Java has the platform independency, so if we can translate from threads code to Java bytecode, we can use the advantages of multithreaded models in many platforms. Java executes Java bytecode which is intermediate language format for Java virtual machine. Java bytecode plays a role of an intermediate language in translator and Java virtual machine work as back-end in translator. But, Java bytecode which is translated from multithreaded models have the demerit that it is not secure. This paper, multhithread code whose feature of platform independent can execute in java virtual machine. We design and implement translator which translate from thread code of multithreaded code to Java bytecode and which check secure problems from Java bytecode.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.3
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• pp.237-246
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• 2020

Recently, as high resolution satellites data have been serviced, frequent DSM (Digital Surface Model) generation over urban areas has been possible. In addition, it is possible to detect changes using a high-resolution DSM at building level such that various methods of building change detection using DSM have been studied. In order to detect building changes using DSM, we need to generate a DSM using a stereo satellite image. The change detection method using D-DSM (Differential DSM) uses the elevation difference between two DSMs of different dates. The D-DSM method has difficulty in applying a precise vertical threshold, because between the two DSMs may have elevation errors. In this study, we focus on the urban structure change detection using D-nDSM (Differential nDSM) based on nDSM (Normalized DSM) that expresses only the height of the structures or buildings without terrain elevation. In addition, we attempted to reduce noise using a morphological filtering. Also, in order to improve the roadside buildings extraction precision, we exploited the urban road network extraction from nDSM. Experiments were conducted for high-resolution stereo satellite images of two periods. The experimental results were compared for D-DSM, D-nDSM, and D-nDSM with road extraction methods. The D-DSM method showed the accuracy of about 30% to 55% depending on the vertical threshold and the D-nDSM approaches achieved 59% and 77.9% without and with the morphological filtering, respectively. Finally, the D-nDSM with the road extraction method showed 87.2% of change detection accuracy.

• Ultrasonography
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• v.32 no.2
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• pp.132-142
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• 2013

Purpose: The purpose of this study is to investigate the correlations of various kinetic parameters derived from the time intensity curve in a xenograft mouse model injected with a prostate cancer model (PC-3 and LNCaP) using an ultrasound contrast agent with histopathologic parameters. Materials and Methods: Twenty nude mice were injected with human prostate cancer cells (15 PC-3 and five LNCaP) on their hind limbs. A bolus of $500{\mu}L$ ($1{\times}10^8$ microbubbles) of second-generation US contrast agent (SonoVue) was injected into the retroorbital vein. The region of interest was drawn over the entire tumor. The time intensity curve was acquired and then fitted to a gamma variate function. The maximal intensity (A), time to peak (Tp), maximal wash-in rate (washin), washout rate (washout), area under the curve up to 50 sec ($AUC_{50}$), area under the ascending slope ($AUC_{in}$), and area under the descending slope ($AUC_{out}$) were derived from the parameters of the gamma variate fit. Immunohistochemical staining for VEGF and CD31 was performed. Tumor volume, the area percentage of VEGF stained in a field, and the count of CD31 (microvessel density, MVD) positive vessels showed correlation with the parameters from the time intensity curve. Results: No significant differences were observed between the kinetic and histopathological parameters from each group. MVD showed positive correlation with A (r=0.625, p=0.003), washin (r=0.462, p=0.040), $AUC_{50}$ (r=0.604, p=0.005), and $AUC_{out}$ (r=0.587, p=0.007). Positive correlations were also observed between tumor volume and $AUC_{50}$ (r=0.481, p=0.032), washin (r=0.662, p=0.001), and $AUC_{out}$ (r=0.547, p=0.012). Washout showed negative correlations with MVD (r=-0.454, p=0.044) and tumor volume (r=-0.464, p=0.039). The area percentage of VEGF did not show any correlation with calculated data from the curve. Conclusion: MVD showed correlations with several of the kinetic parameters. CEUS has the potential for prediction of tumor vascularity in a prostate cancer animal model.

• Korean journal of applied entomology
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• v.58 no.2
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• pp.111-120
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• 2019

Riptortus pedestris (Fabricius) (Hemiptera: Alydidae) is an economically important insect pest of soybean and fruit trees. We investigated the temperature effects on the adult fecundity and longevity, and determined the parameters of oviposition models and life table at different constant temperatures 15.8, 19.7, 24.0, 27.8, 32.6, 34.0, and $35.5^{\circ}C$. R. pedestris females reproduced successfully from 19.7 to $35.5^{\circ}C$ except $15.8^{\circ}C$. The longevity of R. pedestris was longest at $15.8^{\circ}C$ and it decreased with increasing temperature (76.6 days at $19.7^{\circ}C$ and 20.6 days at $35.5^{\circ}C$). The number of total eggs and viable eggs was highest at $24.0^{\circ}C$ (193.5 and 151.2). Egg hatchability was highest at $27.8^{\circ}C$ (84.0%). We compared the results of oviposition models and life table parameters using both total eggs and viable eggs. The parameter value (c: the maximum reproductive capacity) (190 eggs) of temperature dependent total fecundity model using total eggs was higher than that of the model using viable eggs. When we analyzed the life table parameter the values of net reproductive rate and mean generation time using viable eggs were lower than those using total eggs. The oviposition models and life table analysis using viable eggs will be helpful to understand the real population transition of R. pedestris in agricultural system.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.707-723
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• 2022

Although satellite-based sea surface temperature (SST) is advantageous for monitoring large areas, spatiotemporal data gaps frequently occur due to various environmental or mechanical causes. Thus, it is crucial to fill in the gaps to maximize its usability. In this study, daily SST composite fields with a resolution of 4 km were produced through a two-step machine learning approach using polar-orbiting and geostationary satellite SST data. The first step was SST reconstruction based on Data Interpolate Convolutional AutoEncoder (DINCAE) using multi-satellite-derived SST data. The second step improved the reconstructed SST targeting in situ measurements based on light gradient boosting machine (LGBM) to finally produce daily SST composite fields. The DINCAE model was validated using random masks for 50 days, whereas the LGBM model was evaluated using leave-one-year-out cross-validation (LOYOCV). The SST reconstruction accuracy was high, resulting in R² of 0.98, and a root-mean-square-error (RMSE) of 0.97℃. The accuracy increase by the second step was also high when compared to in situ measurements, resulting in an RMSE decrease of 0.21-0.29℃ and an MAE decrease of 0.17-0.24℃. The SST composite fields generated using all in situ data in this study were comparable with the existing data assimilated SST composite fields. In addition, the LGBM model in the second step greatly reduced the overfitting, which was reported as a limitation in the previous study that used random forest. The spatial distribution of the corrected SST was similar to those of existing high resolution SST composite fields, revealing that spatial details of oceanic phenomena such as fronts, eddies and SST gradients were well simulated. This research demonstrated the potential to produce high resolution seamless SST composite fields using multi-satellite data and artificial intelligence.