• Journal of Food Hygiene and Safety
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• v.35 no.6
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• pp.607-617
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• 2020

Human bio-monitoring (HBM) data is a very important resource for tracking total exposure and concentrations of a parent chemical or its metabolites in human biomarkers. However, until now, it was difficult to execute the integration of different types of HBM data due to incompatibility problems caused by gaps in study design, chemical description and coding system between different sources in Korea. In this study, we presented a standardized code system and HBM knowledge model (KM) based on relational database modeling methodology. For this purpose, we used 11 raw datasets collected from the Ministry of Food and Drug Safety (MFDS) between 2006 and 2018. We then constructed the HBM database (DB) using a total of 205,491 concentration-related data points for 18,870 participants and 86 chemicals. In addition, we developed a summary report-type statistical analysis program to verify the inputted HBM datasets. This study will contribute to promoting the sustainable creation and versatile utilization of big-data for HBM results at the MFDS.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.7
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• pp.892-903
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• 2020

The rapid and accurate prediction of storm-surge height during typhoon attacks is essential in responding to coastal disasters. Most methods used for predicting typhoon data are based on numerical modeling, but numerical modeling takes significant computing resources and time. Recently, various studies on the expeditious production of predictive data based on artificial intelligence have been conducted, and in this study, artificial intelligence-based storm-surge height prediction was performed. Several learning data were needed for artificial intelligence training. Because the number of previous typhoons was limited, many synthesized typhoons were created using the tropical cyclone risk model, and the storm-surge height was also generated using the storm surge model. The comparison of the storm-surge height predicted using artificial intelligence with the actual typhoon, showed that the root-mean-square error was 0.09 ~ 0.30 m, the correlation coefficient was 0.65 ~ 0.94, and the absolute relative error of the maximum height was 1.0 ~ 52.5%. Although errors appeared to be somewhat large at certain typhoons and points, future studies are expected to improve accuracy through learning-data optimization.

• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.566-572
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• 2020

In a wireless power transmitter, the characteristics and effects of wireless power transmission between two induction coils are investigated, and a power converter circuit and a battery charger/discharger circuit using wireless power transmission technology are proposed. The advantage of wireless power transmitters and wireless chargers is that, instead of the existing plug-in-mounted wired charger (OBC; on-board charger), the user can wirelessly charge the battery without connecting the power source when charging power to the battery. There is. In addition, the advantage of wireless charging can bring about an energy efficiency improvement effect by using the secondary side rectifier circuit and the receiving coil, but the large-capacity long-distance wireless charging method has a limitation on the transmission distance, so many studies are currently being conducted. The purpose of the study is to study the transmitter circuit and receiver circuit of a wireless power transmission device using a primary coil, a secondary coil, and a half bridge series resonance converter, which can transmit power of a non-contact type power transmitter. As a result, a new topology was applied to improve the power transmission distance of the wireless charging system, and through an experiment according to each distance, the maximum efficiency (95.8%) was confirmed at an output of 3 kW at an 8 cm transmission distance.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.32 no.2
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• pp.81-86
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• 2021

Background and Objectives Therapies have been reported to treat the glottal gap previously. However, these voice therapies showed the limits because many techniques focused only on one among breathing, resonance and phonation. In addition patients often have difficulties visiting hospital frequently. 'Gliding and humming' is vocal training technique that readjusts total vocal patterns such as breathing, resonance and phonation. This technique can be easily applied during short term sessions. The purpose of this study is to evaluate the efficiency of voice therapy with 'gliding and humming' for patients with glottic gap during short-term treatment sessions. Materials and Method Twenty-three patients with glottal gap were selected. Of all patients, 14 patients had sulcus vocalis and 12 patients had muscle tension dysphonia (MTD). Voice therapies were performed 1.9 sessions in average. GRBAS, jitter, shimmer, noise to harmonic ratio, semitone range, closed quotient_vowel and maximum phonation time were compared before and after the therapies. In addition, changes of glottal gap and MTD severity were evaluated. Results Statistically significant improvement was observed. MTD improvement was observed only among the patients with glottal gap improvement. Also sulcus vocalis group showed the statistically significant improvement. Conclusion 'Gliding and humming' was effective to the patients with glottic gap and sulcus vocalis. Also, among patients who have both glottic gap and MTD, the data suggests that voice therapy for glottic gap also makes improvement in MTD.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.2
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• pp.109-117
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• 2022

There has been an increasing number of studies on photovoltaic energy generation system in an offshore site with the largest energy generation efficiency, as increasing the researches and developments of renewable energies for use of offshore space and resources to replace existing fossil fuels and resolve environmental challenges. For installation and operation of floating photovoltaic systems in an offshore site with harsher environmental conditions, a stiffness of structural members comprising the total system must be reinforced to inland water spaces as dams, reservoirs etc., which have relatively weak condition. However, there are various limitations for the reinforcement of structural stiffness of the system, including producible size, total mass of the system, economic efficiency, etc. Thus, in this study, a floating breakwater is considered for reducing wave loads on the system and minimizing the reinforcement of the structural members. Wave reduction performances of floating breakwaters are evaluated, considering size and distance to the system. The wave loads on the system are evaluated using the higher-order boundary element method (HOBEM), considering the multi-body effect of buoys. Stresses on structural members are assessed by coupled analyses using the finite element method (FEM), considering the wave loads and hydrodynamic characteristics. As the maximum stresses on each of the cases are reviewed and compared, the effect of floating breakwater for floating photovoltaic system is checked, and it is confirmed that the size of breakwater has a significant effect on structural responses of the system.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.1
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• pp.141-152
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• 2022

As interest increases related to the development of eco-friendly energy, the offshore wind turbine market is growing at an increasing rate every year. In line with this, the demand for an installation vessel with large scaled capacity is also increasing rapidly. The wind turbine installation vessel (WTIV) is a fixed penetration of the spudcan in the sea-bed to install the wind turbine. At this time, a review of the spudcan is an important issue regarding structural safety in the entire structure system. In the study, we analyzed the current procedure suggested by classification of societies and new procedures reflect the new loading scenarios based on reasonable operating conditions; which is also verified through FE-analysis. The current procedure shows that the maximum stress is less than the allowable criteria because it does not consider the effect of the sea-bed slope, the leg bending moment, and the spudcan shape. However, results of some load conditions as defined by the new procedure confirm that it is necessary to reinforce the structure to required levels under actual pre-load conditions. Therefore, the new procedure considers additional actual operating conditions and the possible problems were verified through detailed FE-analysis.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.101-125
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• 2022

Recently, with the development of computing technology and the improvement of the cloud environment, deep learning technology has developed, and attempts to apply deep learning to various fields are increasing. A typical example is anomaly detection, which is a technique for identifying values or patterns that deviate from normal data. Among the representative types of anomaly detection, it is very difficult to detect a contextual anomaly that requires understanding of the overall situation. In general, detection of anomalies in image data is performed using a pre-trained model trained on large data. However, since this pre-trained model was created by focusing on object classification of images, there is a limit to be applied to anomaly detection that needs to understand complex situations created by various objects. Therefore, in this study, we newly propose a two-step pre-trained model for detecting abnormal situation. Our methodology performs additional learning from image captioning to understand not only mere objects but also the complicated situation created by them. Specifically, the proposed methodology transfers knowledge of the pre-trained model that has learned object classification with ImageNet data to the image captioning model, and uses the caption that describes the situation represented by the image. Afterwards, the weight obtained by learning the situational characteristics through images and captions is extracted and fine-tuning is performed to generate an anomaly detection model. To evaluate the performance of the proposed methodology, an anomaly detection experiment was performed on 400 situational images and the experimental results showed that the proposed methodology was superior in terms of anomaly detection accuracy and F1-score compared to the existing traditional pre-trained model.

• Tunnel and Underground Space
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• v.32 no.2
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• pp.120-130
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• 2022

In this study, the applicability of the microseismic monitoring system based on the underground mine communication system has been verified by operation test in the domestic underground mine. The microseismic data consists of wavelet data and meta-data for mine safety management, and both data should be transferred, stored, analyzed and managed with proper method according to the purpose and size of each data. In order to select the optimal communication system for the microseismic monitoring system considering the underground environment as well as properties of data, various types of communication system have been tested and compared during operation test after installing the optical cable communication system, 2.4 GHz and 900 MHz wireless communication system through the underground mine tunnel and overground area of the test site. The integrated microseismic monitoring software, which was developed to secure the stability of data management and ease of use, has been updated according to findings from operation test. Through the operation test of the microseismic monitoring system including the communication system and the monitoring software, the technical basis was established corresponding to various requirements of the domestic mine for adoption of the microseismic monitoring system.

• Journal of Broadcast Engineering
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• v.27 no.2
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• pp.185-197
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• 2022

Recently, deep learning networks with high performance for object recognition are emerging. In the case of object recognition using deep learning, it is important to build a training data set to improve performance. To build a data set, we need to collect and label the images. This process requires a lot of time and manpower. For this reason, open data sets are used. However, there are objects that do not have large open data sets. One of them is data required for license plate detection and recognition. Therefore, in this paper, we propose an artificial license plate generator system that can create large data sets by minimizing images. In addition, the detection rate according to the artificial license plate arrangement structure was analyzed. As a result of the analysis, the best layout structure was FVC_III and B, and the most suitable network was D2Det. Although the artificial data set performance was 2-3% lower than that of the actual data set, the time to build the artificial data was about 11 times faster than the time to build the actual data set, proving that it is a time-efficient data set building system.

• Journal of the Korean Orthopaedic Association
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• v.56 no.1
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• pp.14-25
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• 2021

Several factors need to be considered for a successful anterior cruciate ligament (ACL) reconstruction, such as preoperative planning, operation technique, and postoperative rehabilitation. Graft choice, fixation, preparation method, maturation, incorporation to host bone, and graft tension should also be considered to achieve a good outcome after an ACL reconstruction. Factors to consider when selecting a graft are the graft strength, graft fixation, fixation site healing, and donor site morbidity, as well as the effects of initial strength, size, surface area, and origin of the graft on its potential for weakening during healing. There are two types of graft for an ACL reconstruction, autograft or allograft. Several autografts have been introduced, including the bone-patellar tendon-bone, hamstring tendon, and quadriceps tendon-bone. On the other hand, each has its advantages and disadvantages. The recent increased use of allografts for an ACL reconstruction is the lack of donor site morbidity, decreased surgical time, diminished postoperative pain, and good availability of source. Despite this, there are no reports suggesting that an allograft may have a better long-term outcome than an autograft. Allografts have inherent disadvantages, including a longer and less complete course of incorporation, remodeling, biomechanically inferiority to autograft, the potential risk of an immunogenic reaction and disease transmission. Higher long-term failure rates and poorer graft maturation scores were reported for allografts compared to autografts. An autograft in an ACL reconstruction should remain the gold standard, although the allograft is a reasonable alternative. If adequate length and diameter of autograft can be obtained for an ACL reconstruction, an autograft with adequate graft fixation and postoperative rehabilitation should be chosen instead of an allograft to achieve better results.