• Journal of the Korean Society of Radiology
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• v.15 no.2
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• pp.153-158
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• 2021

X-ray image analysis is a very important field to improve the early diagnosis rate and prediction accuracy of periodontal disease. Research on the development and application of artificial intelligence-based algorithms to improve the quality of such dental X-ray images is being widely conducted worldwide. Thus, the aim of this study was to design a super-resolution algorithm for predicting periodontal disease and to evaluate its applicability in dental X-ray images. The super-resolution algorithm was constructed based on the convolution layer and ReLU, and an image obtained by up-sampling a low-resolution image by 2 times was used as an input data. Also, 1,500 dental X-ray data used for deep learning training were used. Quantitative evaluation of images used root mean square error and structural similarity, which are factors that can measure similarity through comparison of two images. In addition, the recently developed no-reference based natural image quality evaluator and blind/referenceless image spatial quality evaluator were additionally analyzed. According to the results, we confirmed that the average similarity and no-reference-based evaluation values were improved by 1.86 and 2.14 times, respectively, compared to the existing bicubic-based upsampling method when the proposed method was used. In conclusion, the super-resolution algorithm for predicting periodontal disease proved useful in dental X-ray images, and it is expected to be highly applicable in various fields in the future.

• Journal of Korea Water Resources Association
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• v.52 no.7
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• pp.463-473
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• 2019

This study compared the characteristics of the optimization technique and the water supply and demand forecast using K-WEAP (Korea-Water Evaluation and Planning System) model and MODSIM (Modified SIMYLD) model considering wtaer supply priority. Currently, The national water resources plan applied same priority for municipal, industrial and agricultural demand. the K-WEAP model performs the ratio allocation to satisfy the maximum satisfaction rate, whereas the MODSIM model should be applied to the water supply priority of demands. As a result of applying the priority, water shortage decreased by an average of $1,035,000m^3$ than same prioritized results. It is due to the increase of the return flow rate as the distribution of Municipal and industrial water increases. Comparing the analysis results of K-WEAP and MODSIM applying the priorities, the relative error was within 5.3% and the coefficient of determination ($R^2$) was 0.9999. In addition, if both models provide reasonable water balance analysis results, K-WEAP is superior to GUI convenience for model construction and data processing. However, MODSIM is more effective in simulation time efficiency. It is expected that it will be able to carry out analysis according to various scenarios using the model.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.1-9
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• 2019

In the recent marine sector, the development and standardization regarding S-100, which is the universal hydrographical data model standard for development of marine space information, was progressed, and for the effectiveness of marine chart production work and the multi-purpose use of water level data in S-100, S-102(Bathymetric Surface grid) standard development and various studies of BAG formats combined with water level and uncertainty, property information is being progressed. Since the water level information that is important in the operation of the ship is provided based on S-102, the calibration method of the location information when producing S-102 is an important factor in deciding the water level. In this study, the hydrographical surveying was conducted by piloting the standardized method for the production of S-102 in Korea, and have compared the accuracy of water level information according to the GNSS post treatment calibration method. As a result of comparing the water level in 2 places in the rocky terrain of the study area, the northern water level of Namu-do was shown as DL 0.79~0.83m, the eastern water level of Daeho-do was DL 12.63~12.91m, and the horizontal position errors of the intermittent sunshine water level were confirmed to be within 1m. As a result, the intermittent sunshine water level according to the location calibration method when producing the BAG was confirmed that it was in the available range for a ship's safe voyage. However, the accuracy verification for the location of the ship when conducting hydrographical surveying was judged that there is a need for a various additional study about regional characteristics and environment factor.

• Korean Chemical Engineering Research
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• v.57 no.5
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• pp.679-686
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• 2019

Characteristics of adsorption equilibrium, kinetic and thermodynamic of aniline blue onto activated carbon from aqueous solution were investigated as function of initial concentration, contact time and temperature. Adsorption isotherm of aniline blue was analyzed by Langmuir, Freundlich, Redlich-Peterson, Temkin and Dubinin-Radushkevich models. Langmuir isotherm model fit better with isothermal data than other isotherm models. Estmated Langmuir separation factors ($R_L=0.036{\sim}0.068$) indicated that adsorption process of aniline blue by activated carbon could be an effective treatment method. Adsorption kinetic data were fitted to pseudo first order model, pseudo second order model and intraparticle diffusion models. The kinetic results showed that the adsorption of aniline blue onto activated carbon well followed pseudo second-order model. Adsorption mechanism was evaluated in two steps, film diffusion and intraparticle diffusion, by intraparticle diffusion model. Thermodynamic parameters such as Gibbs free energy, enthalpy and entropy for adsorption process were estimated. Enthalpy change (48.49 kJ/mol) indicated that this adsorption process was physical adsorption and endothermic. Since Gibbs free energy decreased with increasing temperature, the adsorption reaction became more spontaneously with increasing temperature. The isosteric heat of adsorption indicated that there is interaction between the adsorbent and the adsorbate because the energy heterogeneity of the adsorbent surface.

• Journal of Applied Biological Chemistry
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• v.61 no.4
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• pp.397-403
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• 2018

The leaves of Spiraea prunifolia were extracted with 80% aqueous MeOH and the concentrates were partitioned into EtOAc, n-BuOH, and $H_2O$ fractions. The repeated $SiO_2$ or ODS column, and medium pressure liquid chromatographies for the n-BuOH fraction led to isolation of two phenolic glucosides. The chemical structures of these compounds were determined as isosalicin (1) and crenatin (2) based on spectroscopic analyses including Nuclear magnetic resonance and MS. Extracts were analyzed using UPLC-MS/MS providing a short analysis time within 5 min using MRM technique. The concentration of crenatin was higher as 9.53 mg/g and isosalicin was lower as 0.65 mg/g. Neuroprotective effects of these compounds against hydrogen peroxide ($H_2O_2$)-induced neurotoxicity were evaluated. The results showed that exposure to $H_2O_2$ induced morphological changes, cell death and neurotoxicity in SK-N-MC cells. However, pretreatment with crenatin resulted in inhibition of morphological change, reduction of loss of cell viability and attenuation of neuronal damage. These results suggested that neuroprotective effect of crenatin isolated from S. prunifolia can be a good candidate for the development of health beneficial foods which can ameliorate the degenerative neuronal disease caused by oxidative stress.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.353-365
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• 2019

The purpose of this research is to guide the development of the program for the Directive Individual Sand Box Play for the improvement of the self-esteem of children of the dissolved multicultural families. For quantitative analysis data, the scores from before and after the program were compared. The SPSS 18.0 Package was used for statistical analysis. For the qualitative analysis, the linguistic changes in B children during the session were collected and analyzed using the self-expression scale. The research period lasted for around 3 months from February 2017 to May 2017, for a total of 12 sessions which included individual activities, 1 session of group activities, and 1 night and 2 days of family camp activities featuring a total of 6 children. The main results of this research include quantitatively through the program of the Directive Individual Sand Box Play in relation to the social self-esteem capability at z=-2,200 on the level of p<.05, the significant difference was shown. Qualitatively, positive expression increased as sessions proceeded and negative expression reduced regarding the linguistic expressions by session of children B. This means that the method of the Directive Individual Sand Box which presents the topic and in addition, the process of visiting the house of a child which is the most secure environment had shown the effectiveness that increases the improvement of the self-esteem of the children of the dissolved multi-cultural families. According to the diverse special characteristics of clients, a preliminary basic framework for the mobile individual sand box program through the directive approach method will be prepared.

• Journal of Convergence for Information Technology
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• v.9 no.4
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• pp.1-7
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• 2019

The medical environment, combined with IT technology, is changing the paradigm for medical services from treatment to prevention. In particular, as ICT convergence digital healthcare technology is applied to hospital medical systems, infrastructure technologies such as big data, Internet of Things, and artificial intelligence are being used in conjunction with the cloud. In particular, as medical services are used with IT devices, the quality of medical services is increasingly improving to make them easier for users to access. Medical institutions seeking to incorporate IoT services into cloud health care environment services are trying to reduce hospital operating costs and improve service quality, but have not yet been fully supported. In this paper, a patient information collection model from hospital IoT system, which has established a cloud environment, is proposed. The proposed model prevents third parties from illegally eavesdropping and interfering with patients' biometric information through IoT devices attached to the patient's body at hospitals in cloud environments that have established hospital IoT systems. The proposed model allows clinicians to analyze patients' disease information so that they can collect and treat diseases associated with their eating habits through IoT devices. The analyzed disease information minimizes hospital work to facilitate the handling of prescriptions and care according to the patient's degree of illness.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.3
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• pp.229-235
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• 2019

The implementation of an in-band full-duplex wireless communication system is demonstrated in this study. In the analog/RF domain, the self-interference(SI) signal is reduced using a separate antenna for the transmitter and receiver paths, and most of the SI signal is canceled in the digital domain. A software defined radio(SDR) is used to implement the in-band full-duplex wireless communication system. The USRP X310 device uses transmitting and receiving antennas. By adjusting the gain of the transmitting and receiving ends of the SDR device, the magnitude of the SI signal entering the receiving antenna, and the size of the received signal from the outside, are both set to -64 dB. To verify the in-band full-duplex wireless communication performance, the source data is image and orthogonal frequency-division multiplexing is used for modulation. A WiFi standard frame with a carrier frequency of 2.67 GHz and bandwidth of 20 MHz is used. In the received signal, the SI signal is canceled by digital signal processing and the SI signal is attenuated by up to 34 dB. OFDM demodulation was impossible when the SI signal was not removed. However, the bit error rate is reduced to $2.63{\times}10^{-5}$ when the SI signal is attenuated by 34 dB, and no error is detected in the 100 Mbit data output as a result of passing through the Viterbi decoder.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.565-572
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• 2018

Recently, UAVs (Unmanned Aerial Vehicles) or drones have gained popularity for the engineering surveying and mapping because they enable the rapid data acquisition and processing as well as their operation cost is low. The applicable fields become much wider including the topographic monitoring, agriculture, and forestry. It is reported that the high geospatial accuracy is achievable with the drone photogrammetry for many applications. However most studies reported the best achievable mapping results using well-distributed ground control points though some studies investigated the impact of control points on the accuracy. In this study, we focused on the drone mapping of corridors such as roads and pipelines. The distribution and the number of control points along the corridor were diversified for the accuracy assessment. In addition, the effects of the camera self-calibration and the number of the image strips were also studied. The experimental results showed that the biased distribution of ground control points has more negative impact on the accuracy compared to the density of points. The prior camera calibration was favored than the on-the-fly self-calibration that may produce poor positional accuracy for the case of less or biased control points. In addition, increasing the number of strips along the corridor was not helpful to increase the positional accuracy.

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