• The Korean Society of Law and Medicine
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• v.21 no.2
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• pp.75-103
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• 2020

There is a growing voice that medical information should be shared because it can prepare for genetic diseases or cancer by analyzing and utilizing medical information in big data or artificial intelligence to develop medical technology and improve patient care. The utilization and protection of patients' personal information are the same as two sides of the same coin. Medical institutions or medical personnel should take extra caution in handling personal information with high environmental distinct characteristics and sensitivity, which is different from general information processors. In general, the patient's personal information is processed by medical personnel or medical institutions through the processes of collection, creation, and destruction. Still, the use of terms related to personal information in the Medical Service Act is jumbled, or the scope of application is unclear, so it relies on the interpretation of precedents. For the medical personnel or the founder of the medical institution, in the case of infringement of Article 24(4), it cannot be regarded that it means only medical treatment information among personal information, whether or not it should be treated the same as the personal information under Article 23, because the sensitive information of patients is recorded, saved, and stored in electronic medical records. Although the prohibition of information leakage under Article 19 of the Medical Service Act has a revision; 'secret' that was learned in business was revised to 'information', but only the name was changed, and the benefit and protection of the law is the same as the 'secret' of the criminal law, such that the patient's right to self-determination of personal information is not protected. The Privacy Law and the Local Health Act consider the benefit and protection of the law in 'information learned in business' as the right to self-determination of personal information and stipulate the same penalties for personal information infringement such as leakage, forgery, alteration, and damage. The privacy regulations of the Medical Service Act require that the terms be adjusted uniformly because the jumbled use of terms can confuse information subjects, information processors, and shows certain limitations on the protection of personal information because the contents or scope of the regulations of the Medical Service Law for special corporations and the Privacy Law may cause confusion in interpretation. The patient's personal information is sensitive and must be safely protected in its use and processing. Personal information must be processed in accordance with the protection principle of Privacy Law, and the rights such as privacy, freedom, personal rights, and the right to self-determination of personal information of patients or guardians, the information subject, must be guaranteed.

• Korean Journal of Heritage: History & Science
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• v.51 no.2
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• pp.22-37
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• 2018

Unmanned aerial vehicles (UAV) have attracted considerable attention both at home and abroad. The UAV is equipped with a camera that shoots images, which is advantageous for access to areas where archaeological investigations are not possible. Moreover, it is possible to acquire three-dimensional spatial image information by modeling the terrain through aerial photographing, and it is possible to specify the interpretation of the terrain of the survey area. In addition, if we understand the change of the terrain through comparison with past aerial photographs, it will be very helpful to grasp the existence of the ruins. The terrain modeling for searching these remains can be divided into two parts. First, we acquire the aerial photographs of the current terrain using the drone. Then, using image registration and post-processing, we complete the image-joining and terrain-modeling using past aerial photographs. The completed modeled terrain can be used to derive several analytical results. In the present terrain modeling, terrain analysis such as DSM, DTM, and altitude analysis can be performed to roughly grasp the characteristics of the change in the form, quality, and micro-topography. Past terrain modeling of aerial photographs allows us to understand the shape of landforms and micro-topography in wetlands. When verified with actual findings and overlapping data on the modelling of each terrain, it is believed that changes in hill shapes and buried Microform can be identified as helpful when used in low-flying applications. Thus, modeling data using aerial photographs is useful for identifying the reasons for the inability to carry out archaeological surveys, the existence of terrain and ruins in a wide area, and to discuss the preservation process of the ruins. Furthermore, it is possible to provide various themes, such as cadastral maps and land use maps, through comparison of past and present topographical data. However, it is certain that it will function as a new investigation methodology for the exploration of ruins in order to discover archaeological cultural properties.

• Sleep Medicine and Psychophysiology
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• v.26 no.1
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• pp.44-48
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• 2019

Objectives: Insomnia is one of the most prevalent sleep disorders. Recent studies suggest that cognitive and physical arousal play an important role in the generation of primary insomnia. Studies have also shown that information processing disorders due to cortical hyperactivity might interfere with normal sleep onset and sleep continuity. Therefore, focusing on central nervous system arousal and normalizing the information process have become current topics of interest. It has been well known that neurofeedback can reduce the brain hyperarousal by modulating patients' brain waves during a sequence of behavior therapy. The purpose of this study was to investigate effects of neurofeedback therapy on electroencephalography (EEG) characteristics in patients with primary insomnia. Methods: Thirteen subjects who met the criteria for an insomnia diagnosis and 14 control subjects who were matched on sex and age were included. Neurofeedback and sham treatments were performed in a random order for 30 minutes, respectively. EEG spectral power analyses were performed to quantify effects of the neurofeedback therapy on brain wave forms. Results: In patients with primary insomnia, relative spectral theta and sigma power during a therapeutic neurofeedback session were significantly lower than during a sham session ($13.9{\pm}2.6$ vs. $12.2{\pm}3.8$ and $3.6{\pm}0.9$ vs. $3.2{\pm}1.0$ in %, respectively; p < 0.05). There were no statistically significant changes in other EEG spectral bands. Conclusion: For the first time in Korea, EEG spectral power in the theta band was found to increase when a neurofeedback session was applied to patients with insomnia. This outcome might provide some insight into new interventions for improving sleep onset. However, the treatment response of insomniacs was not precisely evaluated due to limitations of the current pilot study, which requires follow-up studies with larger samples in the future.

• Korean Journal of Heritage: History & Science
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• v.39
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• pp.219-242
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• 2006

Quantitative analysis and provenance interpretation of the raw materials for the jade (amazonite) excavated from the Asan Sijeonri site were studied. Geology of the Sijeonri site composed mainly of Precambrian metasedimentary rocks and the alluvium ranges extensively. In the site, amazonite jade was excavated in the Bronze Age No. 4 circular-shaped resident site. The jade has a comma-shaped and shows light green color with so much cracks. The jade is silicate mineral of columnar habits that is shown white streak, and has fine cleavages with vitreous luster. As the analytical results, this jade was identified as a feldspar-group mineral gemologically called amazonite that is mineralogically microcline formed to intergrowth of albite and orthoclase. Internal textures of the amazonite present Na-end member of albite coexisting with K-end member of orthoclase that are replaced each other along the cleavages and twin planes with several ${\mu}m$ scales. Therefore, the amazonite is one mineral phase combined with albite and orthoclase by substitution of $Na_2O$ and $K_2O$, respectively. The Danyang are is an unique producing site of amazonite in South Korea, and Gongju Janggimyeon was known as microcline provenance to the utmost area from the Sijeonri site. In the marginal area of southern coast in Korean Peninsula, Bronze Age amazonite has been excavated in several sites, where original provenance of the raw amazonite is not identified. The Sijeonri site does not show any facilities of producing and processing traces for amazonite jade. Also, only one jade was collected in the Sijeonri site. Therefore, there is not possibility that the provenance of raw jade is the Sijeonri area. To explain original provenance of the amazonite jade, migration path, manufacturing process and archaeological interpretation are required.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.6
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• pp.265-274
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• 2021

Outlier detection research in ocean data has traditionally been performed using statistical and distance-based machine learning algorithms. Recently, AI-based methods have received a lot of attention and so-called supervised learning methods that require classification information for data are mainly used. This supervised learning method requires a lot of time and costs because classification information (label) must be manually designated for all data required for learning. In this study, an autoencoder based on unsupervised learning was applied as an outlier detection to overcome this problem. For the experiment, two experiments were designed: one is univariate learning, in which only SST data was used among the observation data of Deokjeok Island and the other is multivariate learning, in which SST, air temperature, wind direction, wind speed, air pressure, and humidity were used. Period of data is 25 years from 1996 to 2020, and a pre-processing considering the characteristics of ocean data was applied to the data. An outlier detection of actual SST data was tried with a learned univariate and multivariate autoencoder. We tried to detect outliers in real SST data using trained univariate and multivariate autoencoders. To compare model performance, various outlier detection methods were applied to synthetic data with artificially inserted errors. As a result of quantitatively evaluating the performance of these methods, the multivariate/univariate accuracy was about 96%/91%, respectively, indicating that the multivariate autoencoder had better outlier detection performance. Outlier detection using an unsupervised learning-based autoencoder is expected to be used in various ways in that it can reduce subjective classification errors and cost and time required for data labeling.

• Journal of Food Hygiene and Safety
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• v.37 no.2
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• pp.97-106
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• 2022

Listeria monocytogenes (L. monocytogenes) is one of gram-positive foodborne pathogens with a very high fatality rate. Unlike most foodborne pathogens, L. monocytogenes is capable of growing at low temperatures, such as in refrigerated foods. Thus, various physical and chemical prevention methods are used in the manufacturing, processing and distribution of food. However, there are limitations to the methods such as possible changes to the food quality and the consumer awareness of synthetic preservatives. Thus, the aim of this study was to evaluate the anti-listeria activity of lactic acid bacteria (LAB) isolated from kimchi and characterize the bacteriocin produced by Lactococcuslactis which is one of isolated strains from kimchi. The analysis on the anti-listeria activity of a total of 36 species (Lactobacillus, Weissella, Lactobacillus, and Lactococcus) isolated from kimchi by the agar overlay method revealed that L. lactis NJ 1-10 and NJ 1-16 had the highest anti-listeria activity. For quantitatively analysis on the anti-listeria activity, NJ 1-10 and NJ 1-16 were co-cultured with L. monocytogenes in Brain Heat Infusion (BHI) broth, respectively. As a result, L. monocytogenes was reduced by 3.0 log CFU/mL in 20 h, lowering the number of bacteria to below the detection limit. Both LAB strains showed anti-listeria activity against 24 serotypes of L. monocytogenes, although the sizes of clear zone was slightly different. No clear zone was observed when the supernatants of both LAB cultures were treated with proteinase-K, indicating that their anti-listerial activities might be due to the production of bacteriocins. Heat stability of the partially purified bacteriocins of NJ 1-10 and NJ 1-16 was relatively stable at 60℃ and 80℃. Yet, their anti-listeria activities were completely lost by 60 min of treatment at 100℃ and 15 min of treatment at 121℃. The analysis on the pH stability showed that their anti-listeria activities were the most stable at pH 4.01, and decreased with the increasing pH value, yet, was not completely lost. Partially purified bacteriocins showed relatively stable anti-listeria activities in acetone, ethanol, and methanol, but their activities were reduced after chloroform treatment, yet was not completely lost. Conclusively, this study revealed that the bacteriocins produced by NJ 1-10 and NJ 1-16 effectively reduced L. monocytogenes, and that they were relatively stable against heat, pH, and organic solvents, therefore implying their potential as a natural antibacterial substance for controlling L. monocytogenes in food.

• Journal of Science Education
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• v.45 no.3
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• pp.292-303
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• 2021

This study identifies the terms frequently used together with energy in online science news articles and topics of the news reports to find out how the term energy is used in everyday life and to draw implications for science curriculum and instruction about energy. A total of 2,171 online news articles in science category published by 11 major newspaper companies in Korea for one year from March 1, 2018 were selected by using energy as a search term. As a result of natural language processing, a total of 51,224 sentences consisting of 507,901 words were compiled for analysis. Using the R program, term frequency analysis, semantic network analysis, and structural topic modeling were performed. The results show that the terms with exceptionally high frequencies were technology, research, and development, which reflected the characteristics of news articles that report new findings. On the other hand, terms used more than once per two articles were industry-related terms (industry, product, system, production, market) and terms that were sufficiently expected as energy-related terms such as 'electricity' and 'environment.' Meanwhile, 'sun', 'heat', 'temperature', and 'power generation', which are frequently used in energy-related science classes, also appeared as terms belonging to the highest frequency. From a network analysis, two clusters were found including terms related to industry and technology and terms related to basic science and research. From the analysis of terms paired with energy, it was also found that terms related to the use of energy such as 'energy efficiency,' 'energy saving,' and 'energy consumption' were the most frequently used. Out of 16 topics found, four contexts of energy were drawn including 'high-tech industry,' 'industry,' 'basic science,' and 'environment and health.' The results suggest that the introduction of the concept of energy degradation as a starting point for energy classes can be effective. It also shows the need to introduce high-tech industries or the context of environment and health into energy learning.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.1
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• pp.41-50
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• 2022

In this paper, a method to directly calculate the major elements of skin color such as melanin and hemoglobin from the RGB signal of the camera is proposed. The main elements of skin color typically measure spectral reflectance using specific equipment, and reconfigure the values at some wavelengths of the measured light. The values calculated by this method include such things as melanin index and erythema index, and require special equipment such as a spectral reflectance measuring device or a multi-spectral camera. It is difficult to find a direct calculation method for such component elements from a general digital camera, and a method of indirectly calculating the concentration of melanin and hemoglobin using independent component analysis has been proposed. This method targets a region of a certain RGB image, extracts characteristic vectors of melanin and hemoglobin, and calculates the concentration in a manner similar to that of Principal Component Analysis. The disadvantage of this method is that it is difficult to directly calculate the pixel unit because a group of pixels in a certain area is used as an input, and since the extracted feature vector is implemented by an optimization method, it tends to be calculated with a different value each time it is executed. The final calculation is determined in the form of an image representing the components of melanin and hemoglobin by converting it back to the RGB coordinate system without using the feature vector itself. In order to improve the disadvantages of this method, the proposed method is to calculate the component values of melanin and hemoglobin in a feature space rather than an RGB coordinate system using a feature vector, and calculate the spectral reflectance corresponding to the skin color using a general digital camera. Methods and methods of calculating detailed components constituting skin pigments such as melanin, oxidized hemoglobin, deoxidized hemoglobin, and carotenoid using spectral reflectance. The proposed method does not require special equipment such as a spectral reflectance measuring device or a multi-spectral camera, and unlike the existing method, direct calculation of the pixel unit is possible, and the same characteristics can be obtained even in repeated execution. The standard diviation of density for melanin and hemoglobin of proposed method was 15% compared to conventional and therefore gives 6 times stable.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.449-461
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• 2021

Analysis Ready Data (ARD) for optical satellite images represents a pre-processed product by applying spectral characteristics and viewing parameters for each sensor. The atmospheric correction is one of the fundamental and complicated topics, which helps to produce Top-of-Atmosphere (TOA) and Top-of-Canopy (TOC) reflectance from multi-spectral image sets. Most remote sensing software provides algorithms or processing schemes dedicated to those corrections of the Landsat-8 OLI sensors. Furthermore, Google Earth Engine (GEE), provides direct access to Landsat reflectance products, USGS-based ARD (USGS-ARD), on the cloud environment. We implemented the Orfeo ToolBox (OTB) atmospheric correction extension, an open-source remote sensing software for manipulating and analyzing high-resolution satellite images. This is the first tool because OTB has not provided calibration modules for any Landsat sensors. Using this extension software, we conducted the absolute atmospheric correction on the Landsat-8 OLI images of Railroad Valley, United States (RVUS) to validate their reflectance products using reflectance data sets of RVUS in the RadCalNet portal. The results showed that the reflectance products using the OTB extension for Landsat revealed a difference by less than 5% compared to RadCalNet RVUS data. In addition, we performed a comparative analysis with reflectance products obtained from other open-source tools such as a QGIS semi-automatic classification plugin and SAGA, besides USGS-ARD products. The reflectance products by the OTB extension showed a high consistency to those of USGS-ARD within the acceptable level in the measurement data range of the RadCalNet RVUS, compared to those of the other two open-source tools. In this study, the verification of the atmospheric calibration processor in OTB extension was carried out, and it proved the application possibility for other satellite sensors in the Compact Advanced Satellite (CAS)-500 or new optical satellites.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.27 no.3
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• pp.127-143
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• 2022

Recently, many attempts to run numerical ocean models in cloud computing environments have been tried actively. A cloud computing environment can be an effective means to implement numerical ocean models requiring a large-scale resource or quickly preparing modeling environment for global or large-scale grids. Many commercial and private cloud computing systems provide technologies such as virtualization, high-performance CPUs and instances, ether-net based high-performance-networking, and remote direct memory access for High Performance Computing (HPC). These new features facilitate ocean modeling experimentation on commercial cloud computing systems. Many scientists and engineers expect cloud computing to become mainstream in the near future. Analysis of the performance and features of commercial cloud services for numerical modeling is essential in order to select appropriate systems as this can help to minimize execution time and the amount of resources utilized. The effect of cache memory is large in the processing structure of the ocean numerical model, which processes input/output of data in a multidimensional array structure, and the speed of the network is important due to the communication characteristics through which a large amount of data moves. In this study, the performance of the Regional Ocean Modeling System (ROMS), the High Performance Linpack (HPL) benchmarking software package, and STREAM, the memory benchmark were evaluated and compared on commercial cloud systems to provide information for the transition of other ocean models into cloud computing. Through analysis of actual performance data and configuration settings obtained from virtualization-based commercial clouds, we evaluated the efficiency of the computer resources for the various model grid sizes in the virtualization-based cloud systems. We found that cache hierarchy and capacity are crucial in the performance of ROMS using huge memory. The memory latency time is also important in the performance. Increasing the number of cores to reduce the running time for numerical modeling is more effective with large grid sizes than with small grid sizes. Our analysis results will be helpful as a reference for constructing the best computing system in the cloud to minimize time and cost for numerical ocean modeling.