• Applied Biological Chemistry
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• v.25 no.4
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• pp.232-238
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• 1982

From ^{15}N$ labelled nitrogen experiments on 13 fields use efficiency by difference method was higher than that by labelling method in 80% of fields tested indicating augmentation of soil nitrogen uptake by fertilizer nitrogen. Both methods showed very similar trend among fields. Sulfur coated urea(SCU) and point application increased fertilization efficiency(yield increment per fertilizer nitrogen applied, Fe) to 23 from 15 of split application through the increase of fertilizer use efficiency from 29(Eu) to 50 but tended to decrease efficiency of absorbed fertilizer nitrogen(yield increment per nitrogen derived from fertilizer, Ef) from 50. to 46 High yielding capacity of Tongil line appears to be attributed to the higher Ef, translocation efficiency and soil nitrogen preference index(soil nitrogen increment in plant per the increment of fertilizer nitrogen in plant, PI). This studies confirmed that yield under fertilizer application system depends on Fe which is the multiplication of Eu and Ef and that the improvement of fertilizer management(form, application method and time) increases principally Eu, the limit of which is controlled by Ef that is attributed mainly to varietal characteristics.

• Journal of Ginseng Research
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• v.40 no.1
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• pp.28-37
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• 2016

Background: Panax ginseng cannot be cultivated on the same land consecutively for an extended period, and the underlying mechanism regarding microorganisms is still being explored. Methods: Polymerase chain reaction and denaturing gradient gel electrophoresis (PCR-DGGE) and BIO-LOG methods were used to evaluate the microbial genetic and functional diversity associated with the P. ginseng rhizosphere soil in various cultivation ages and modes. Results: The analysis of microbial diversity using PCR-DGGE showed that microbial communities were significantly variable in composition, of which six bacterial phyla and seven fungal classes were detected in P. ginseng soil. Among them, Proteobacteria and Hypocreales dominated. Fusarium oxysporum, a soilborne pathogen, was found in all P. ginseng soil samples except R0. The results from functional diversity suggested that the microbial metabolic diversity of fallow soil abandoned in 2003was the maximum and transplanted soil was higher than direct-seeding soil and the forest soil uncultivated P. ginseng, whereas the increase in cultivation ages in the same mode led to decreases in microbial diversity in P. ginseng soil. Carbohydrates, amino acids, and polymers were the main carbon sources utilized. Furthermore, the microbial diversity index and multivariate comparisons indicated that the augmentation of P. ginseng cultivation ages resulted in decreased bacterial diversity and increased fungal diversity, whereas microbial diversity was improved strikingly in transplanted soil and fallow soil abandoned for at least one decade. Conclusion: The key factors for discontinuous P. ginseng cultivation were the lack of balance in rhizosphere microbial communities and the outbreak of soilborne diseases caused by the accumulation of its root exudates.

• Journal of Pharmacopuncture
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• v.18 no.1
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• pp.79-85
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• 2015

Objectives: A vertebral compression fracture (VCF) is characterized by back pain and fracture of a vertebral body on spinal radiography. VCFs of the thoraco lumbar spine are common in the elderly. In general, appropriate analgesics should be prescribed to reduce pain and, thus, promote early mobilization. The ideal treatment approach for VCFs has not been determined. In Korea, acupuncture and herbal medication have been used to treat VCFs for many years. There is empirical evidence that acupuncture might benefit patients with a VCF. However, no randomized, controlled, clinical trials evaluating the efficacy and the safety of acupuncture for treating a VCF have been published. Therefore, we designed a randomized, controlled, pilot, clinical trial to obtain information for the design of a further full scale trial. Methods: A five week protocol for a randomized, controlled, pilot, clinical trial is presented. Fourteen patients will be recruited and randomly allocated to two groups: a control group receiving interlaminar epidural steroid injections once a week for three weeks, and an experimental group receiving interlaminar epidural steroid injections plus acupuncture treatment (three acupuncture sessions per week for three weeks, nine sessions in total). The primary outcomes will be the pain intensity (visual analogue scale and PainVision$^{TM}$ system). The secondary outcome measurements will be the answers on the short form McGill pain questionnaire and the oswestry disability index. Assessments will be made at baseline and at one, three, and five weeks. The last assessment (week five) will take place two weeks after treatment cessation. This study will provide both an indication of feasibility and a clinical foundation for a future large scale trial. The outcomes will provide additional resources for incorporating acupuncture into existing treatments, such as nonsteroidal anti-inflammatory medications, narcotics and vertebral augmentation. This article describes the protocol.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.1
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• pp.25-33
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• 2021

With the development of machine learning techniques, various types of data such as vibration, temperature, and flow rate can be used to detect and diagnose abnormalities in machine conditions. In particular, in the field of the state monitoring of rotating machines, the fault diagnosis of machines using vibration data has long been carried out, and the methods are also very diverse. In this study, an experiment was conducted to collect vibration data from normal and abnormal compressors by installing accelerometers directly on rotary compressors used in household air conditioners. Data segmentation was performed to solve the data shortage problem, and the main features for the fault classification model were extracted through the chi-square test after statistical and physical features were extracted from the vibration data in the time domain. The support vector machine (SVM) model was developed to classify the normal or abnormal conditions of compressors and improve the classification accuracy through the hyperparameter optimization of the SVM.

• Journal of Korean Neurosurgical Society
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• v.65 no.6
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• pp.825-833
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• 2022

Objective : ABM/P-15 (anorganic bone matrix/15-amino acid peptide fragment) is a commercially available synthetically manufactured P-15 collagen peptide fragment, that is adsorbed on ABM. This study was done to investigate the efficacy of ABM/P-15 in achieving fusion in the lumbar spine and comparing it with that of recombinant bone morphogenic protein-2 (rhBMP-2) and demineralized bone matrix (DBM). Methods : A retrospective observational study of prospectively collected data of 140 patients who underwent lumbar spinal fusion surgeries in a single specialty spine hospital between 2016 and 2020, with a minimum 6-month follow-up was conducted. Based on the material used for the augmentation of the bone graft at the fusion site, the patients were divided into three categories namely ABM/P-15, rhBMP-2, and DBM group. Results : ABM/P-15, rhBMP-2, and DBM were used in 46, 44, and 50 patients, respectively. Patient characteristics like age, gender, bone mineral density, smoking history, and presence of diabetes mellitus were comparable amongst the three groups. Average follow-up was 16.0±5.2, 17.9±9.8, and 26.2±14.9 months, respectively in ABM/P-15, rhBMP-2, and DBM groups. The fusion was achieved in 97.9%, 93.2%, and 98% patients while the average time-to-union was 4.05±2.01, 10±4.28, and 9.44±3.49 months (p<0.001), respectively for ABM/P-15, rhBMP-2, and DBM groups. The average pre-operative Visual analogue scale score was 6.93±2.42, 7.14±1.97, 7.01±2.14 (p=0.900) for ABM/P-15, rhBMP-2 and DBM groups, respectively, which reduced to 1.02±0.80, 1.21±0.96, and 0.54±0.70 (p=0.112), respectively at the last follow up. Pre-operative Oswestry disability index scores were 52.7±18.02, 55.4±16.8, and 53.56±19.6 (p=0.751) in ABM/P-15, rhBMP-2, and DBM groups, which post-operatively reduced to 33.77±15.52, 39.42±16.47, and 38.3±15.89 (p=0.412) and further to 15.74±8.3, 17.41±10.45, and 16.76±9.81 (p=0.603), respectively at the last follow-up. Conclusion : ABM/P-15 appears to achieve union significantly earlier than rhBMP-2 and DBM in lumbar spinal fusion cases while maintaining a comparable clinical and complication profile.

• Journal of radiological science and technology
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• v.46 no.4
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• pp.315-323
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• 2023

Post-mortem computed tomography (PMCT) is commonly employed in the field of forensic pathology. PMCT was mainly performed using a whole-body scan with a wide field of view (FOV), which lead to a decrease in spatial resolution due to the increased pixel size. This study aims to evaluate the potential for developing a super-resolution model based on conditional generative adversarial networks (CGAN) to enhance the image quality of CT. 1761 low-resolution images were obtained using a whole-body scan with a wide FOV of the head phantom, and 341 high-resolution images were obtained using the appropriate FOV for the head phantom. Of the 150 paired images in the total dataset, which were divided into training set (96 paired images) and validation set (54 paired images). Data augmentation was perform to improve the effectiveness of training by implementing rotations and flips. To evaluate the performance of the proposed model, we used the Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM) and Deep Image Structure and Texture Similarity (DISTS). Obtained the PSNR, SSIM, and DISTS values of the entire image and the Medial orbital wall, the zygomatic arch, and the temporal bone, where fractures often occur during head trauma. The proposed method demonstrated improvements in values of PSNR by 13.14%, SSIM by 13.10% and DISTS by 45.45% when compared to low-resolution images. The image quality of the three areas where fractures commonly occur during head trauma has also improved compared to low-resolution images.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1413-1425
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• 2023

The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.

• Atmosphere
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• v.12 no.4
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• pp.20-42
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• 2002

Based on the "Mid to Long Term Plan for Space Development", a project to launch COMeS (Communication, Oceanography, and Meteorological Satellite) into the geostationary orbit is undergoing. Accordingly, KMA (Korea Meteorological Administration) has defined the meteorological missions and prepared the user requirements to fulfill the missions. To make a realistic user requirements, we prepared a first draft based on the ideal meteorological products derivable from a geostationary platform and sent the RFI (request for information) to the sensor manufacturers. Based on the responses to the RFI and other considerations, we revised the user requirement to be a realistic plan for the 2008 launch of the satellite. This manuscript introduces the revised user requirements briefly. The major mission defined in the revised user requirement is the augmentation of the detection and prediction ability of the severe weather phenomena, especially around the Korean Peninsula. The required payload is an enhanced Imager, which includes the major observation channels of the current geostationary sounder. To derive the required meteorological products from the Imager, at least 12 channels are required with the optimum of 16 channels. The minimum 12 channels are 6 wavelength bands used for current geostationary satellite, and additional channels in two visible bands, a near infrared band, two water vapor bands and one ozone absorption band. From these enhanced channel observation, we are going to derive and utilize the information of water vapor, stability index, wind field, and analysis of special weather phenomena such as the yellow sand event in addition to the standard derived products from the current geostationary Imager data. For a better temporal coverage, the Imager is required to acquire the full disk data within 15 minutes and to have the rapid scan mode for the limited area coverage. The required thresholds of spatial resolutions are 1 km and 2 km for visible and infrared channels, respectively, while the target resolutions are 0.5 km and 1 km.

• Journal of the Korean Applied Science and Technology
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• v.37 no.4
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• pp.769-777
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• 2020

The purpose of this study was to investigate the effects of 8 weeks Self-Myofascial Release exercise on body composition, vascular and metabolic functions in obese female college students. The subjects were 19 obese female college students (n = 9) who were randomly assigned to an exercise group(n=9) and control group(n=9), with an exception of except 1 abandonment. The Self-Myofascial Release exercise group performed exercises twice a week for 8 weeks and for 40 minutes at one time using a foam roller, and the control group maintained normal life pattern for the same period. Body composition was measured by body weight, body fat percentage, vascular function was measured by pulse wave velocity(PWV), augmentation index(AIx), brachial artery vascular flow-mediated dilation(FMD), and metabolic function was measured by fasting glucose and triglyceride levels. The Self-Myofascial Release exercise with foam roller showed no significant effect on body weight and body fat percentage. The Self-Myofascial Release exercise with foam roller showed no significant effect on heart rate, FMD, PWV but, SBP, CSBP and AIx were significant decreased. The Self-Myofascial Release exercise with foam roller showed no significant effect on fasting glucose and triglyceride levels. In conclusion, 8-week Self-Myofascial Release exercise for obese female college students showed no significant effect on body composition and metabolic function, but improved SBP, CSBP and AIx levels significantly. Therefore, Self-Myofascial Release exercise will be an effective way to improve the vascular function of obese female college students.

• The Korean Journal of Archival Studies
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• no.79
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• pp.5-32
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• 2024

The Korean government ranked 3rd among 193 UN member countries in the UN's 2022 e-Government Development Index. Korea, which has consistently been evaluated as a top country, can clearly be said to be a leading country in the world of e-government. The lubricant of e-government is data. Data itself is neither information nor a record, but it is a source of information and records and a resource of knowledge. Since administrative actions through electronic systems have become widespread, the production and technology of data-based records have naturally expanded and evolved. Technology may seem value-neutral, but in fact, technology itself reflects a specific worldview. The digital order of new technologies, armed with hyper-connectivity and super-intelligence, not only has a profound influence on traditional power structures, but also has an a similar influence on existing information and knowledge transmission media. Moreover, new technologies and media, including data-based generative artificial intelligence, are by far the hot topic. It can be seen that the all-round growth and spread of digital technology has led to the augmentation of human capabilities and the outsourcing of thinking. This also involves a variety of problems, ranging from deep fakes and other fake images, auto profiling, AI lies hallucination that creates them as if they were real, and copyright infringement of machine learning data. Moreover, radical connectivity capabilities enable the instantaneous sharing of vast amounts of data and rely on the technological unconscious to generate actions without awareness. Another irony of the digital world and online network, which is based on immaterial distribution and logical existence, is that access and contact can only be made through physical tools. Digital information is a logical object, but digital resources cannot be read or utilized without some type of device to relay it. In that respect, machines in today's technological society have gone beyond the level of simple assistance, and there are points at which it is difficult to say that the entry of machines into human society is a natural change pattern due to advanced technological development. This is because perspectives on machines will change over time. Important is the social and cultural implications of changes in the way records are produced as a result of communication and actions through machines. Even in the archive field, what problems will a data-based archive society face due to technological changes toward a hyper-intelligence and hyper-connected society, and who will prove the continuous activity of records and data and what will be the main drivers of media change? It is time to research whether this will happen. This study began with the need to recognize that archives are not only records that are the result of actions, but also data as strategic assets. Through this, author considered how to expand traditional boundaries and achieves reterritorialization in a data-driven society.