• Journal of Korean Orthopaedic Sports Medicine
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• v.7 no.2
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• pp.128-134
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• 2008

Purpose: We prospectively evaluated the clinical usefulness of the patellar inferior pole (PIP) as a landmark of the anteromedial (AM) portal for the arthroscopic surgery of the medial mensiscus posterior horn (MMPH). Materials and Methods: Group 1 (50 normal left knees of adults), Group 2 (10 normal knees under anesthesia), and Group 3 (50 consecutive knees undergoing elective arthroscopic surgery for relatively simple intraarticular pathologies, or diagnostic arthroscopy) were included. In Group 1 and 2, the true lateral (A) and valgus stress lateral radiographs (B) on $30^{\circ}$ flexion were obtained, and the lines (AM portal line) passing through the PIP and distal-most medial femoral condyle (MFC) were drawn under the condition without considering the thickness of articular cartilage of MFC (1, 2-A, B group), and considering it as 2.5mm on B (1, 2-C group). Then, we investigated the meeting point of the AM portal line with medial tibial plateau (C-D percentage), and measured the distance between the PIP and the anterior joint line (E-length), and medial tibial-femoral joint space (F-length). In Group 3, the AM portal was made at the PIP level and clinical usefulness of the approach to the MMPH and body of the lateral meniscus (LM) was analyzed. Results: The average C-D percentage came out as 85.8, 101.3, 69.1% for each Group 1-A, B, C, and 102.4, 144.6, 116.8% for each Group 2-A, B, C. Measured E-length was an average of 15.1 (Group 1-A), 15.5 (Group 1-B, C), 13.1 (Group 2-A), and 12.9 mm (Group 2-B, C) and the change by valgus stress had no statistical significance. The F-length increased about 1.2 (Group 1) and 3.6 mm (Group 2) when valgus stress was applied, which had statistical significance (p<0.001, p<0.001). In Group 3, 49, 48 knees were classified as good for the MMPH, and the body of LM in aspect of the clinical usefulness of AM portal made on the PIP level. Conclusion: We identified the clinical usefulness of the PIP as a skin landmark of AM portal for the arthroscopic surgery of the MMPH.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.6
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• pp.601-609
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• 2010

This paper measured EMF strength of the duty measurement radio station(77 station) and the non-duty measurement radio station(41 station) of mobile communication base station in Jeonbuk region. As the result of measurement, it generally reveals that EMF is highly low level compare to the human protection guideline. And It is regarded as level that the national people who live close to the mobile communication base station don't have to worry about electromagnetic wave. This paper provides comparative analyses categorized by the duty measurement station and the non-duty measurement station. The results reveals that the average value and the maximum value of the non-duty measurement station preferably was higher than all the duty measurement station. It is thought that the EMF exposure strength of the national people is caused by approach of station antenna rather than antenna power. Consequently this paper suggests that standard of the antenna power(exceed 30 W), standard of antenna height(exceed 10 m) specified by Radio Regulation Act enforcement ordinance, legal basis for mobile communication base station have to be changed.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.12
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• pp.1729-1735
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• 2015

This study was conducted to evaluate the effect of medicinal plant by-products (MPB) supplementation to a total mixed ration (TMR) on growth, carcass characteristics and economic efficacy in the late fattening period of Hanwoo steers. Twenty seven steers (body weight [BW], $573{\pm}57kg$) were assigned to 3 treatment groups so that each treatment based on BW contained 9 animals. All groups received ad libitum TMR throughout the feeding trial until slaughter (from 24 to 30 months of age) and treatments were as follows: control, 1,000 g/kg TMR; treatment 1 (T1), 970 g/kg TMR and 30 g/kg MPB; treatment 2 (T2), 950 g/kg TMR and 50 g/kg MPB. Initial and final BW were not different among treatments. Resultant data were analyzed using general linear models of SAS. Average daily gain and feed efficiency were higher (p<0.05) for T1 than control, but there was no difference between control and T2. Plasma albumin showed low-, intermediate- and high-level (p<0.05) for control, T1 and T2, whereas non-esterified fatty acid was high-, intermediate- and high-level (p<0.05) for control, T1 and T2, respectively. Carcass weight, carcass rate, backfat thickness and rib eye muscle area were not affected by MPB supplementation, whereas quality and yield grades were highest (p<0.05) for T1 and T2, respectively. Daily feed costs were decreased by 0.5% and 0.8% and carcass prices were increased by 18.1% and 7.6% for T1 and T2 compared to control, resulting from substituting TMR with 30 and 50 g/kg MPB, respectively. In conclusion, the substituting TMR by 30 g/kg MPB may be a potential feed supplement approach to improve economic efficacy in the late fattening period of Hanwoo steers.

• Journal of Microbiology and Biotechnology
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• v.28 no.4
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• pp.551-560
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• 2018

Bellflower root (Platycodon grandiflorum), which belongs to the Campanulaceae family, is a perennial grass that grows naturally in Korea, northeastern China, and Japan. Bellflower is widely consumed as both food and medicine owing to its high nutritional value and potential therapeutic effects. Since foodborne disease outbreaks often come from vegetables, understanding the public health risk of microorganisms on fresh vegetables is pivotal to predict and prevent foodborne disease outbreaks. We investigated the microbial communities on the bellflower root (n = 10). 16S rRNA gene amplicon sequencing targeting the V6-V9 regions of 16S rRNA genes was conducted via the 454-Titanium platform. The sequence quality was checked and phylogenetic assessments were performed using the RDP classifier implemented in QIIME with a bootstrap cutoff of 80%. Principal coordinate analysis was performed using the weighted Fast UniFrac distance. The average number of sequence reads generated per sample was 67,192 sequences. At the phylum level, bacterial communities from the bellflower root were composed primarily of Proteobacteria, Firmicutes, and Actinobacteria in March and September samples. Genera Serratia, Pseudomonas, and Pantoea comprised more than 54% of the total bellflower root bacteria. Principal coordinate analysis plots demonstrated that the microbial community of bellflower root in March samples was different from those in September samples. Potential pathogenic genera, such as Pantoea, were detected in bellflower root samples. Even though further studies will be required to determine if these species are associated with foodborne illness, our results indicate that the 16S rRNA gene-based sequencing approach can be used to detect pathogenic bacteria on fresh vegetables.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.3 s.357
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• pp.33-40
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• 2007

In this paper, low-rate TCP attack as one of shrew attacks is considered and the scaling based dynamic time warping (S-DTW) algorithm is introduced. The low-rate TCP attack can not be detected by the detection method for the previous flooding DoS/DDoS (Denial of Service/Distirbuted Denial of Service) attacks due to its low average traffic rate. It, however, is a periodic short burst that exploits the homogeneity of the minimum retransmission timeout (RTO) of TCP flows and then some pattern matching mechanisms have been proposed to detect it among legitimate input flows. A DTW mechanism as one of detection approaches has proposed to detect attack input stream consisting of many legitimate or attack flows, and shown a depending method as well. This approach, however, has a problem that legitimate input stream may be caught as an attack one. In addition, it is difficult to decide a threshold for separation between the legitimate and the malicious. Thus, the causes of this problem are analyzed through simulation and the scaling by maximum auto-correlation value is executed before computing the DTW. We also discuss the results on applying various scaling approaches and using standard deviation of input streams monitored.

• Journal of Energy Engineering
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• v.24 no.2
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• pp.167-173
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• 2015

This paper attempts to estimate the electricity demand function in Korea with quarterly data of average temperature, GDP and electricity price over the period 2005-2013. We apply lagged dependent variable model and ordinary least square method as a robust approach to estimating the parameters of the electricity demand function. The results show that short-run price and income elasticities of the electricity demand are estimated to be -0.569 and 0.631, respectively. They are statistically significant at the 1% level. Moreover, long-run income and price elasticities are estimated to be 1.589 and -1.433, respectively Both of results reveal that the demand for electricity is price- and income-elastic in the long-run. The relationship between electricity consumption and temperature is supported by many of references as a U-shaped relationship, and the base temperature of electricity demand is about $15.2^{\circ}C$. It is shown that power of explanation and goodness-of-fit statistics are improved in the use of the lagged dependent variable model rather than conventional model.

• Journal of Life Science
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• v.31 no.4
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• pp.410-417
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• 2021

Next-generation sequencing (NGS) is a high-throughput technique for sequencing large numbers of DNA fragments that are prepared from a genome. This sequencing technique has been used to elucidate whole genome sequences of living organisms and to analyze complementary DNA (cDNA) or chromatin immunoprecipitated DNA (ChIPed DNA) at the genome level. After NGS, the use of proper tools is important for processing and analyzing data with reasonable parameters. However, handling large-scale sequencing data and programing for data analysis can be difficult. The Galaxy platform, a public web service system, provides many different tools for NGS data analysis, and it allows researchers to analyze their data on a web browser with no deep knowledge about bioinformatics and/or programing. In this study, we explain the procedure for preparing chromatin immunoprecipitation-sequencing (ChIP-seq) libraries and steps for analyzing ChIP-seq data using the Galaxy platform. The data analysis steps include the NGS data upload to Galaxy, quality check of the NGS data, premapping processes, read mapping, the post-mapping process, peak-calling and visualization by window view, heatmaps, average profile, and correlation analysis. Analysis of our histone H3K4me1 ChIP-seq data in K562 cells shows that it correlates with public data. Thus, NGS data analysis using the Galaxy platform can provide an easy approach to bioinformatics.

• Journal of Climate Change Research
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• v.4 no.1
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• pp.11-26
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• 2013

This study examined the applicability of robust decision making (RDM) over standard decision making (SDM) by comparing each result of water supply planning under climate change uncertainties for a Korean dam case. RDM determines the rank of alternatives using the regret criterion which derives less fluctuating alternatives under the risk level regardless of scenarios. RDM and SDM methods were applied to assess hypothetic scenarios of water supply planning for the Andong dam and Imha dam basins. After generating various climate change scenarios and six assumed alternatives, the rank of alternatives was estimated by RDM and SDM respectively. As a result, the average difference in the rank of alternatives between RDM and SDM methods is 0.33~1.33 even though the same scenarios and alternatives were used to be ranked by both of RDM and SDM. This study has significance in terms of an attempt to assess a new approach to decision making for responding to climate change uncertainties in Korea. The effectiveness of RDM under more various conditions should be verified in the future.

• Journal of IKEEE
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• v.28 no.2
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• pp.150-157
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• 2024

In this paper, we propose a novel algorithm for predicting the number of apples on an apple tree using a deep learning-based object detection model and a polynomial regression model. Measuring the number of apples on an apple tree can be used to predict apple yield and to assess losses for determining agricultural disaster insurance payouts. To measure apple fruit load, we photographed the front and back sides of apple trees. We manually labeled the apples in the captured images to construct a dataset, which was then used to train a one-stage object detection CNN model. However, when apples on an apple tree are obscured by leaves, branches, or other parts of the tree, they may not be captured in images. Consequently, it becomes difficult for image recognition-based deep learning models to detect or infer the presence of these apples. To address this issue, we propose a two-stage inference process. In the first stage, we utilize an image-based deep learning model to count the number of apples in photos taken from both sides of the apple tree. In the second stage, we conduct a polynomial regression analysis, using the total apple count from the deep learning model as the independent variable, and the actual number of apples manually counted during an on-site visit to the orchard as the dependent variable. The performance evaluation of the two-stage inference system proposed in this paper showed an average accuracy of 90.98% in counting the number of apples on each apple tree. Therefore, the proposed method can significantly reduce the time and cost associated with manually counting apples. Furthermore, this approach has the potential to be widely adopted as a new foundational technology for fruit load estimation in related fields using deep learning.

• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1373-1387
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• 2021

Forest fire poses a significant threat to the environment and society, affecting carbon cycle and surface energy balance, and resulting in socioeconomic losses. Widely used multi-spectral satellite image-based approaches for burned area detection have a problem in that they do not work under cloudy conditions. Therefore, in this study, Sentinel-1 Synthetic Aperture Radar (SAR) data from Europe Space Agency, which can be collected in all weather conditions, were used to identify forest fire damaged area based on a series of processes including Principal Component Analysis (PCA) and K-means clustering. Four forest fire cases, which occurred in Gangneung·Donghae and Goseong·Sokcho in Gangwon-do of South Korea and two areas in North Korea on April 4, 2019, were examined. The estimated burned areas were evaluated using fire reference data provided by the National Institute of Forest Science (NIFOS) for two forest fire cases in South Korea, and differenced normalized burn ratio (dNBR) for all four cases. The average accuracy using the NIFOS reference data was 86% for the Gangneung·Donghae and Goseong·Sokcho fires. Evaluation using dNBR showed an average accuracy of 84% for all four forest fire cases. It was also confirmed that the stronger the burned intensity, the higher detection the accuracy, and vice versa. Given the advantage of SAR remote sensing, the proposed statistical processing and K-means clustering-based approach can be used to quickly identify forest fire damaged area across the Korean Peninsula, where a cloud cover rate is high and small-scale forest fires frequently occur.