• Journal of the Korean Society for information Management
• /
• v.35 no.4
• /
• pp.141-164
• /
• 2018

Recently, as the amount of academic literature has increased rapidly and complex researches have been actively conducted, researchers have difficulty in analyzing trends in previous research. In order to solve this problem, it is necessary to classify information in units of academic papers. However, in Korea, there is no academic database in which such information is provided. In this paper, we propose an automatic classification system that can classify domestic academic literature into multiple classes. To this end, first, academic documents in the technical science field described in Korean were collected and mapped according to class 600 of the DDC by using K-Means clustering technique to construct a learning set capable of multiple classification. As a result of the construction of the training set, 63,915 documents in the Korean technical science field were established except for the values in which metadata does not exist. Using this training set, we implemented and learned the automatic classification engine of academic documents based on deep learning. Experimental results obtained by hand-built experimental set-up showed 78.32% accuracy and 72.45% F1 performance for multiple classification.

• Journal of the Korean Society of Radiology
• /
• v.13 no.2
• /
• pp.185-192
• /
• 2019

DXA is the most commonly used BMD examination equipment with the best performance on reflecting the biological alteration with tiny change of bone density. In spite of the importance of the quality control to maintain the accuracy and precision of the examination, considerable number of hospitals are not conducting QC due to the difficulty and high cost of the phantom product. This study develops the cross revision phantom with 3D printer and the change of the degree of infilling filaments which can be readily secured, and provides the usefulness assessment of the developed phantom by comparing with existing products. The Hounsfield Units of ABS, TPU, PLA, 30% Cu-PLA, and 30% Al-PLA are assessed. The Hounsfield Units result at infilling rate 100% was $-149.74{\pm}2.36$, $-55.62{\pm}7.14$, $-7.68{\pm}3.82$, $87.53{\pm}1.07$, and $1795.20{\pm}16.15$. The L1, L2, L3 BMD of 3D printing phantom with linear regression model were $0.620{\pm}0.010g/cm^2$, $1.092{\pm}0.025g/cm^2$, $1.554{\pm}0.026g/cm^2$ which are statistically relevant to the existing phantom products. This result provides the base line data for various medical phantom produce and capability of proper quality control of DXA equipment.

• Journal of Advanced Navigation Technology
• /
• v.22 no.6
• /
• pp.530-536
• /
• 2018

Recently, many studies for interoperability of UAV in the NAS has been performed since the application range and demand of UAV are continuously increased. For the interoperation of UAV in the NAS, technical standards and certification system for UAV which is equivalent to the commercial aircraft are required and test and evaluation methodology must be presented by standards. In this paper, qualification test and evaluation methodology aboutfor the UAV navigation system is proposed. For the research, the mission profile and operation environment of UAV were analyzed. Thereafter the test criteria were derived and the test methodology were established. Finally, the simulation and demonstration using test-bed UAV were performed. As a result of the test, it was confirmed that the navigation system of test UAV has a position accuracy about 1.4 meters at 95% confidence level in the entire flight stage.

• Journal of the Korea Computer Graphics Society
• /
• v.25 no.3
• /
• pp.11-20
• /
• 2019

In this study, a novel virtual reality (VR) experience environment is proposed for enabling walking adaptation of visually impaired people. The core of proposed VR environment is based on immersive walking interactions and deep learning based braille blocks recognition. To provide a realistic walking experience from the perspective of visually impaired people, a tracker-based walking process is designed for determining the walking state by detecting marching in place, and a controller-based VR white cane is developed that serves as the walking assistance tool for visually impaired people. Additionally, a learning model is developed for conducting comprehensive decision-making by recognizing and responding to braille blocks situated on roads that are followed during the course of directions provided by the VR white cane. Based on the same, a VR application comprising an outdoor urban environment is designed for analyzing the VR walking environment experience. An experimental survey and performance analysis were also conducted for the participants. Obtained results corroborate that the proposed VR walking environment provides a presence of high-level walking experience from the perspective of visually impaired people. Furthermore, the results verify that the proposed learning algorithm and process can recognize braille blocks situated on sidewalks and roadways with high accuracy.

• Journal of IKEEE
• /
• v.23 no.2
• /
• pp.743-746
• /
• 2019

In this paper we proposed a new ocean radiation automatic monitoring system. The proposed system has the following characteristics: First, using NaI + PVT mixed detectors, the response speed is fast and precision analysis is possible. Second, the application of temperature compensation algorithm to scintillator-type sensors does not require additional cooling devices and enables stable operation in the changing ocean environment. Third, since cooling system is not needed, electricity consumption is low, and electricity can be supplied reliably by utilizing solar energy, which can be installed at the observation deck of ocean environment. Fourth, using GPS and wireless communications, accurate location information and real-time data transmission function for measurement areas enables immediate warning response in the event of nuclear accidents such as those involving neighboring countries. The results tested by the authorized testing agency to assess the performance of the proposed system were measured in the range of $5{\mu}Sv/h$ to 15mSv/h, which is the highest level in the world, and the accuracy was determined to be ${\pm}8.1%$, making normal operation below the international standard ${\pm}15%$. The internal environmental grade (waterproof) was achieved, and the rate of variation was measured within 5% at operating temperature of $-20^{\circ}C$ to $50^{\circ}C$ and stability was verified. Since the measured value change rate was measured within 10% after the vibration test, it was confirmed that there will be no change in the measured value due to vibration in the ocean environment caused by waves.

• Journal of Korean Society of Forest Science
• /
• v.108 no.3
• /
• pp.357-363
• /
• 2019

This study was conducted to develop a stem volume table for Quercus acutissima in Korea by using Kozak's stem taper equation. In total, 2700 tree samples were collected around the country, and growth performance was investigated through compiling data on diameters by stem height and stem analysis. In order to test the stem taper equation's fitness, the fitness index (FI), bias, and mean absolute deviation (MAD) were analyzed. The fitness of the equation was estimated at 97%, bias as 0.017, and MAD turned out to be 1.118, respectively. Furthermore, there was a statistically significant volume difference between the current volume table and the new volume table (p = 0.0008, <0.005). The result indicates that using the new volume table that reflects the actual forest will reduce the loss when assessing wood resources and will improve the accuracy of forest statistics for national and local governments. A stem volume table, the main result of this research, which is utilized in the estimated stem taper equation, will provide growth information for Quercus acutissima, one of the main broadleaf species in Korea, and will function as a management indicator for rational forest management.

• The Korean Journal of Applied Statistics
• /
• v.32 no.4
• /
• pp.543-559
• /
• 2019

Data often include missing values due to various reasons. If the missing data mechanism is not MCAR, analysis based on fully observed cases may an estimation cause bias and decrease the precision of the estimate since partially observed cases are excluded. Especially when data include many variables, missing values cause more serious problems. Many imputation techniques are suggested to overcome this difficulty. However, imputation methods using parametric models may not fit well with real data which do not satisfy model assumptions. In this study, we review imputation methods using nonlinear models such as kernel, resampling, and spline methods which are robust on model assumptions. In addition, we suggest utilizing imputation classes to improve imputation accuracy or adding random errors to correctly estimate the variance of the estimates in nonlinear imputation models. Performances of imputation methods using nonlinear models are compared under various simulated data settings. Simulation results indicate that the performances of imputation methods are different as data settings change. However, imputation based on the kernel regression or the penalized spline performs better in most situations. Utilizing imputation classes or adding random errors improves the performance of imputation methods using nonlinear models.

• The Journal of the Korea Contents Association
• /
• v.19 no.9
• /
• pp.666-673
• /
• 2019

In the immersive virtual reality environment, we can select and manipulate various virtual objects. in order to select a virtual object, we generally use Ray-casting method that fires a virtual line in user's view and selects an object when the line and the object match, or Cone-casting method that is widely used to select multiple objects at the same time. However, since the virtual objects used in CAD are composed of small and complex objects in detail, when selecting an object in the user's view by existing methods, there occurs a ambiguity problem that needs additional realignment operation even though an object is selected as a group. in this paper, even if a virtual object is composed of several small virtual objects, it calculates the spatial and logical relationship among objects and expands or shrinks desired objects, so that the user can quickly and accurately select a desired object. in order to evaluate the proposed method, performance comparison were performed using Our and Ray-Casting and Cone-Casting methods. Experimental results show that the proposed method has the fastest speed and the highest accuracy when selecting the desired objects.

• Food Science of Animal Resources
• /
• v.39 no.3
• /
• pp.371-378
• /
• 2019

The objective of this study was to develop mathematical models for describing the kinetic behavior of Staphylococcus aureus (S. aureus) in seasoned beef jerky. Seasoned beef jerky was cut into 10-g pieces. Next, 0.1 mL of S. aureus ATCC13565 was inoculated into the samples to obtain 3 Log CFU/g, and the samples were stored aerobically at $10^{\circ}C$, $20^{\circ}C$, $25^{\circ}C$, $30^{\circ}C$, and $35^{\circ}C$ for 600 h. S. aureus cell counts were enumerated on Baird Parker agar during storage. To develop a primary model, the Weibull model was fitted to the cell count data to calculate Delta (required time for the first decimal reduction) and ${\rho}$ (shape of curves). For secondary modeling, a polynomial model was fitted to the Delta values as a function of storage temperature. To evaluate the accuracy of the model prediction, the root mean square error (RMSE) was calculated by comparing the predicted data with the observed data. The surviving S. aureus cell counts were decreased at all storage temperatures. The Delta values were longer at $10^{\circ}C$, $20^{\circ}C$, and $25^{\circ}C$ than at $30^{\circ}C$ and $35^{\circ}C$. The secondary model well-described the temperature effect on Delta with an $R^2$ value of 0.920. In validation analysis, RMSE values of 0.325 suggested that the model performance was appropriate. S. aureus in beef jerky survives for a long period at low storage temperatures and that the model developed in this study is useful for describing the kinetic behavior of S. aureus in seasoned beef jerky.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.31 no.2
• /
• pp.62-72
• /
• 2019

Due to the difficulties in forecasting the intensity and the source location of tsunami the countermeasures prepared based on the deterministic approach fail to work properly. Thus, there is an increasing demand of the tsunami hazard analyses that consider the uncertainties of tsunami behavior in probabilistic approach. In this paper a fundamental study is conducted to perform the probabilistic tsunami hazard analysis (PTHA) for the tsunamis that caused the disaster to the east coast of Korea. A logic tree approach is employed to consider the uncertainties of the initial free surface displacement and the tsunami height distribution along the coast. The branches of the logic tree are constructed by reflecting characteristics of tsunamis that have attacked the east coast of Korea. The computational time is nonlinearly increasing if the number of branches increases in the process of extracting the fractile curves. Thus, an improved method valid even for the case of a huge number of branches is proposed to save the computational time. The performance of the discrete weight distribution method proposed first in this study is compared with those of the conventional sorting method and the Monte Carlo method. The present method is comparable to the conventional methods in its accuracy, and is efficient in the sense of computational time when compared with the conventional sorting method. The Monte Carlo method, however, is more efficient than the other two methods if the number of branches and the number of fault segments increase significantly.