• Korean Journal of Remote Sensing
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• v.21 no.3
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• pp.173-188
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• 2005

The present study aims to derive and compare narrow and broad bandwidths of ocean color sensor’s algorithms for the study of monitoring highly dynamic coastal oceanic environmental parameters using high-resolution imagery acquired from Multi-spectral Camera (MSC) on KOMPSAT-2. These algorithms are derived based on a large data set of remote sensing reflectances ($R_{rs}$) generated by using numerical model that relates $b_b/(a + b_b)$ to $R_{rs}$ as functions of inherent optical properties, such as absorption and backscattering coefficients of six water components including water, phytoplankton (chl), dissolved organic matter (DOM), suspended sediment (SS) concentration, heterotropic organism (he) and an unknown component, possibly represented by bubbles or other particulates unrelated to the first five components. The modeled $R_{rs}$ spectra appear to be consistent with in-situ spectra collected from Korean waters. As Kompsat-2 MSC has similar spectral characteristics with Landsat-5 Thematic Mapper (TM), the model generated $R_{rs}$ values at 2 ㎚ interval are converted to the equivalent remote sensing reflectances at MSC and TM bands. The empirical relationships between the spectral ratios of modeled $R_{rs}$ and chlorophyll concentrations are established in order to derive algorithms for both TM and MSC. Similarly, algorithms are obtained by relating a single band reflectance (band 2) to the suspended sediment concentrations. These algorithms derived by taking into account the narrow and broad spectral bandwidths are compared and assessed. Findings suggest that there was less difference between the broad and narrow band relationships, and the determination coefficient $(r^2)$ for log-transformed data [ N = 500] was interestingly found to be $(r^2)$ = 0.90 for both TM and MSC. Similarly, the determination coefficient for log-transformed data [ N = 500] was 0.93 and 0.92 for TM and MSC respectively. The algorithms presented here are expected to make significant contribution to the enhanced understanding of coastal oceanic environmental parameters using Multi-spectral Camera.

• The Journal of Korean Obstetrics and Gynecology
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• v.34 no.4
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• pp.46-61
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• 2021

Objectives: The purpose of this review is to overview the studies of traditional herbal medicine for chronic pelvic inflammatory disease. Methods: We searched relevant studies using seven databases (The Journal of Korean obstetrics & gynecology, National Digital Science Library (NDSL), Research Information Sharing Service (RISS), Oriental Medicine Advanced Searching Integrated System (OASIS), Pubmed, Cochrane, Chinese National Knowledge Infrastructure (CNKI)). Data retrieval was carried out on April 5, 2021 and the papers published from January 1, 2015 to March 31, 2021 were included. The risk of bias was assessed by using Cochrane's risk of bias tool. Results: 524 studies were searched in domestic and foreign databases, and 7 studies were finally selected. In all studies, the treatment group was treated with oral traditional herbal medicine and the control group was treated with western medicine. Although the evaluation index was slightly different for each study, all studies used total efficacy rate index. In all 7 studies, the treatment group was more effective than the control group. Conclusions: Traditional herbal medicine can be an effective option in treating chronic pelvic inflammatory disease. Further high quality studies which include large number should be carried out to confirm the evidence and safety of traditional herbal medicine treatment.

• Journal of the Korea Convergence Society
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• v.12 no.4
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• pp.23-30
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• 2021

An Automated Industry and Occupation Coding System assigns statistical classification code to the enormous amount of natural language data collected from people who write about their industry and occupation. Unlike previous studies that applied information retrieval, we propose a system that does not need an index database and gives proper code regardless of the level of classification. Also, we show our model, which utilized KoBERT that achieves high performance in natural language downstream tasks with deep learning, outperforms baseline. Our method achieves 95.65%, 91.51%, and 97.66% in Occupation/Industry Code Classification of Population and Housing Census, and Industry Code Classification of Census on Basic Characteristics of Establishments. Moreover, we also demonstrate future improvements through error analysis in the respect of data and modeling.

• The Journal of the Acoustical Society of Korea
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• v.40 no.2
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• pp.169-175
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• 2021

Recently, an ultrasound hologram and its applications have gained attention in the ultrasound research field. However, the determination technique of transmit signal phases, which generate a hologram, has not been significantly advanced from the previous algorithms which are time-consuming iterative methods. Thus, we applied the deep learning technique, which has been previously adopted to generate an optical hologram, to generate an ultrasound hologram. We further examined the Deep learning-based Holographic Ultrasound Generation algorithm (Deep-HUG). We implement the U-Net-based algorithm and examine its generalizability by training on a dataset, which consists of randomly distributed disks, and testing on the alphabets (A-Z). Furthermore, we compare the Deep-HUG with the previous algorithm in terms of computation time, accuracy, and uniformity. It was found that the accuracy and uniformity of the Deep-HUG are somewhat lower than those of the previous algorithm whereas the computation time is 190 times faster than that of the previous algorithm, demonstrating that Deep-HUG has potential as a useful technique to rapidly generate an ultrasound hologram for various applications.

• Clinical and Experimental Reproductive Medicine
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• v.48 no.2
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• pp.163-173
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• 2021

Objective: This study aimed to characterize a validated model for predicting oocyte retrieval in controlled ovarian stimulation (COS) and to construct model-based nomograms for assistance in clinical decision-making regarding the gonadotropin protocol and dose. Methods: This observational, retrospective, cohort study included 636 women with primary unexplained infertility and a normal menstrual cycle who were attempting assisted reproductive therapy for the first time. The enrolled women were split into an index group (n=497) for model building and a validation group (n=139). The primary outcome was absolute oocyte count. The dose-response relationship was tested using modified Poisson, negative binomial, hybrid Poisson-E_max, and linear models. The validation group was similarly analyzed, and its results were compared to that of the index group. Results: The Poisson model with the log-link function demonstrated superior predictive performance and precision (Akaike information criterion, 2,704; λ=8.27; relative standard error (λ)=2.02%). The covariate analysis included women's age (p<0.001), antral follicle count (p<0.001), basal follicle-stimulating hormone level (p<0.001), gonadotropin dose (p=0.042), and protocol type (p=0.002 and p<0.001 for short and antagonist protocols, respectively). The estimates from 500 bootstrap samples were close to those of the original model. The validation group showed model assessment metrics comparable to the index model. Based on the fitted model, a static nomogram was built to improve visualization. In addition, a dynamic electronic tool was created for convenience of use. Conclusion: Based on our validated model, nomograms were constructed to help clinicians individualize the stimulation protocol and gonadotropin doses in COS cycles.

• The Journal of Churna Manual Medicine for Spine and Nerves
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• v.15 no.2
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• pp.9-18
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• 2020

Objectives This study verified the clinical effectiveness of Qigong exercise therapy for individuals with hypertension. Methods Ten electronic databases were used for information retrieval. Only randomized controlled trials (RCTs) using Qigong exercise therapy as a treatment for hypertension were included in this study. Cochrane risk of bias tool was used to assess the methodological quality of each RCT. Results After a thorough review, six RCTs were deemed eligible. These studies were divided into two groups: Qigong vs. no intervention and Qigong plus anti-hypertensive drug vs. anti-hypertensive drug alone. Among the six RCTs, four studies were Qigong vs. no intervention, and two studies were Qigong plus anti-hypertensive drug vs. anti-hypertensive drug alone. The meta-analysis demonstrated that adding Qigong exercise to anti-hypertensive drug treatment lowers diastolic blood pressure more than the anti-hypertensive drug alone. Conclusions Although Qigong exercise is not widely used in the Korean medical field, the results of this study demonstrated the necessity of exercise while controlling hypertension. However, the number of included studies was small, with their high risk of bias. In conclusion, although it is difficult to determine whether Qigong exercise lowers blood pressure in hypertensive patients, exercise including Qigong must be parallel with the intake of anti-hypertensive drugs.

• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.11-22
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• 2022

Recently, research and development using various Artificial Intelligence (AI) technologies are being conducted in the field of education. Among the AI in Education (AIEd), conversational agents are not limited by time and space, and can learn more effectively by combining them with various AI technologies such as voice recognition and translation. This paper conducted a trend analysis on platforms that have a large number of users and used conversational agents for English learning among commercialized application. Currently commercialized educational platforms using conversational agent through trend analysis has several limitations and problems. To analyze specific problems and limitations, a comparative experiment was conducted with the latest pre-trained large-capacity dialogue model. Sensibleness and Specificity Average (SSA) human evaluation was conducted to evaluate conversational human-likeness. Based on the experiment, this paper propose the need for trained with large-capacity parameters dialogue models, educational data, and information retrieval functions for effective English conversation learning.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.1
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• pp.35-40
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• 2022

In this paper, we propose a method of constructing clinical knowledge with clinical concept relations and predicting diseases based on a deep learning model to support clinical decision-making. Clinical terms in UMLS(Unified Medical Language System) and cancer-related medical knowledge are classified into five categories. Medical related documents in Wikipedia are extracted using the classified clinical terms. Clinical concept relations are established by matching the extracted medical related documents with the extracted clinical terms. After deep learning using clinical knowledge, a disease is predicted based on medical terms expressed in a query. Thereafter, medical terms related to the predicted disease are selected as an extended query for clinical document retrieval. To validate our method, we have experimented on TREC Clinical Decision Support (CDS) and TREC Precision Medicine (PM) test collections.

• Journal of the Korea Society for Simulation
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• v.18 no.3
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• pp.1-11
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• 2009

This paper illustrates a case study of PLC logic simulation in a car manufacturing system. It was developed to simulate and verify PLC control program for automobile panel AS/RS. Because car models become varied, the complexity of supply problem is increasing in the car manufacturing system. To cope with this problem, companies use the AS (automated storage) and RS (retrieval system) but it has logical complexity. Industrial automated process uses PLC code to control the AS/RS, however control information and control codes (PLC code) are difficult to understand. This paper suggests a PLC simulation environment, using 3D models and PLC code with realistic data. Data used in this simulation is based on realistic 3D model and I/O model, using actual size and PLC signals, respectively. The environment is similar to a real factory; users can verify and test the PLC code using this simulation before the implementation of AS/RS. Proposed simulation environment can be used for test run of AS/RS to reduce implementation time and cost.

• Journal of Digital Convergence
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• v.20 no.1
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• pp.179-184
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• 2022

With the development of information and communication technology, the production and distribution of digital contents is rapidly increasing, and the distribution of illegally copied contents also increases, causing various problems. In order to prevent illegal distribution of contents, a DRM (Digital Rights Management)-based approach can be used, but in a situation where the contents are already copied and distributed, a method of searching and detecting the duplicated contents is required. In this paper, a duplication detection method based on the contents of video content is proposed. The proposed method divides the video into scene units using the visual rhythm extracted from the video, and hierarchically applies the playback time and color feature values of each divided scene to quickly and efficiently detect duplicate videos in a large database. Through experiments, it was shown that the proposed method can reliably detect various replication modifications.