• Food Science and Preservation
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• v.22 no.3
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• pp.303-313
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• 2015

This study investigates the physicochemical, microbiological and sensory characteristics of seasonal salted-Kimchi cabbages to provide basic data on its uniform quality. Generally, seasonal salted-Kimchi samples had different pH values at initial storage periods, but there was no difference in pH between the seasonal samples when stored for longer periods. The samples from the fall and winter seasons were relatively low in acid and high in solid soluble content compared to samples from other seasons. Salted-Kimchi cabbages in the summer showed the highest microbiological number compared to samples from other seasons. In the sensory evaluation, there were differences in the appearance, aroma, and taste, depending on seasonal samples at different storage periods. The correlation coefficient between the quality characteristics in the seasonal samples showed a positive or negative correlation between the quality characteristics at 1% significant level. In the principal component analysis, F1 and F2 were shown the 51.81% and 14.23% of the total variance (66.21%), respectively. In the PCA pattern of seasonal salted-Kimchi cabbages during storage periods, winter samples were distributed on the top of F2, spring samples were in the middle of F2, while the rest of the samples were distributed on the bottom of F2. According to increasing storage periods, initial storage samples were distributed at the left of F1, while other samples were located at the right of F2.

• Journal of Ecology and Environment
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• v.29 no.6
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• pp.551-558
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• 2006

Effects of Pb and $CO_2$ on soil microbial community associated with Pinus densiflora were investigated using community level physiological profiles (CLPP) and 16S rDNA PCR-denaturing gradient gel electrophoresis (DGGE) methods. Two-years pine trees were planted in Pb-contaminated soils and uncontaminated soils, and cultivated for 3 months in the growth chamber where $CO_2$ concentration was controlled at 380 or 760 ppmv. The structure of microbial community was analyzed in 6 kinds of soil samples (CA-0M : $CO_2$ 380 ppmv + Pb 0 mg/kg + initial, CB-0M : $CO_2$ 380 ppmv + Pb 500 mg/kg + initial, CA-3M : $CO_2$ 380 ppmv + Pb 0 mg/kg + after 3 months, CB-3M : $CO_2$ 380 ppmv + Pb 500 mglkg + after 3 months, EA-3M : $CO_2$ 760 ppmv + Pb 0 mg/kg + after 3 months, EB-3M : $CO_2$ 760 ppmv + Pb 500 mg/kg + after 3 months). After 3 months, the substrate utilization in the uncontaminated soil samples (CA-3M vs EA-3M) was not significantly influenced by $CO_2$ concentrations. However, the substrate utilization in the Pb-contaminated soil samples (CB-3M vs EB-3M) was enhanced by the elevated $CO_2$ concentrations. The results of principal component analysis based on substrate utilization activities showed that the structure of microbial community structure in each soil sample was grouped by Pb-contamination. The similarities of DGGE fingerprints were 56.3 % between the uncontaminated soil samples (CA-3M vs EA-3M), and 71.4% between the Pb-contaminated soil samples (CB-3M vs. EB-3M). The similarities between the soil samples under $CO_2$ 380 ppmv (CA-3M vs CB-3M) and $CO_2$, 760 ppmv (EA-3M vs EB-3M) were 53.3% and 35.8%, respectively. These results suggested that the structure of microbial community associated with Pinus densiflora were sensitively specialized by Pb-contamination rather than $CO_2$ concentration.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.53-65
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• 2019

Object tracking is one of important steps to achieve video-based surveillance systems. Object tracking is considered as an essential task similar to object detection and recognition. In order to perform object tracking, various machine learning methods (e.g., least-squares, perceptron and support vector machine) can be applied for different designs of tracking systems. In general, generative methods (e.g., principal component analysis) were utilized due to its simplicity and effectiveness. However, the generative methods were only focused on modeling the target object. Due to this limitation, discriminative methods (e.g., binary classification) were adopted to distinguish the target object and the background. Among the machine learning methods for binary classification, total error rate minimization can be used as one of successful machine learning methods for binary classification. The total error rate minimization can achieve a global minimum due to a quadratic approximation to a step function while other methods (e.g., support vector machine) seek local minima using nonlinear functions (e.g., hinge loss function). Due to this quadratic approximation, the total error rate minimization could obtain appropriate properties in solving optimization problems for binary classification. However, this total error rate minimization was based on a batch mode setting. The batch mode setting can be limited to several applications under offline learning. Due to limited computing resources, offline learning could not handle large scale data sets. Compared to offline learning, online learning can update its solution without storing all training samples in learning process. Due to increment of large scale data sets, online learning becomes one of essential properties for various applications. Since object tracking needs to handle data samples in real time, online learning based total error rate minimization methods are necessary to efficiently address object tracking problems. Due to the need of the online learning, an online learning based total error rate minimization method was developed. However, an approximately reweighted technique was developed. Although the approximation technique is utilized, this online version of the total error rate minimization could achieve good performances in biometric applications. However, this method is assumed that the total error rate minimization can be asymptotically achieved when only the number of training samples is infinite. Although there is the assumption to achieve the total error rate minimization, the approximation issue can continuously accumulate learning errors according to increment of training samples. Due to this reason, the approximated online learning solution can then lead a wrong solution. The wrong solution can make significant errors when it is applied to surveillance systems. In this paper, we propose an exactly reweighted technique to recursively update the solution of the total error rate minimization in online learning manner. Compared to the approximately reweighted online total error rate minimization, an exactly reweighted online total error rate minimization is achieved. The proposed exact online learning method based on the total error rate minimization is then applied to object tracking problems. In our object tracking system, particle filtering is adopted. In particle filtering, our observation model is consisted of both generative and discriminative methods to leverage the advantages between generative and discriminative properties. In our experiments, our proposed object tracking system achieves promising performances on 8 public video sequences over competing object tracking systems. The paired t-test is also reported to evaluate its quality of the results. Our proposed online learning method can be extended under the deep learning architecture which can cover the shallow and deep networks. Moreover, online learning methods, that need the exact reweighting process, can use our proposed reweighting technique. In addition to object tracking, the proposed online learning method can be easily applied to object detection and recognition. Therefore, our proposed methods can contribute to online learning community and object tracking, detection and recognition communities.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.562-569
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• 2019

Raman spectroscopy has been receiving increased attention as a standoff explosive detection technique. In addition, there is a growing need for a fast search method that can identify raman spectrum for measured chemical substances compared to known raman spectra in large database. By far the most simple and widely used method is to calculate and compare the Euclidean distance between the given spectrum and the spectra in a database. But it is non-trivial problem because of the inherent high dimensionality of the data. One of the most serious problems is the high computational complexity of searching for the closet spectra. To overcome this problem, we presented the MPS Sort with Sorted Variance+PDS method for the fast algorithm to search for the closet spectra in the last paper. the proposed algorithm uses two significant features of a vector, mean values and variance, to reject many unlikely spectra and save a great deal of computation time. In this paper, we present two new methods for the fast algorithm to search for the closet spectra. the PCA+PDS algorithm reduces the amount of computation by reducing the dimension of the data through PCA transformation with the same result as the distance calculation using the whole data. the Hierarchical Cluster Tree algorithm makes a binary hierarchical tree using PCA transformed spectra data. then it start searching from the clusters closest to the input spectrum and do not calculate many spectra that can not be candidates, which save a great deal of computation time. As the Experiment results, PCA+PDS shows about 60.06% performance improvement for the MPS Sort with Sorted Variance+PDS. also, Hierarchical Tree shows about 17.74% performance improvement for the PCA+PDS. The results obtained confirm the effectiveness of the proposed algorithm.

• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1165-1178
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• 2018

Collapse of an Antarctic ice shelf and its flow velocity changes has the potential to reduce the restraining stress to the seaward flow of the Antarctic Ice Sheet, which can cause sea level rising. In this study, variations in ice velocity from 2000 to 2017 for the Nansen Ice Shelf in East Antarctica that experienced a large-scale collapse in April 2016 were analyzed using Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and Landsat-8 Operational Land Imager (OLI) images. To extract ice velocity, image matching based on orientation correlation was applied to the image pairs of blue, green, red, near-infrared, panchromatic, and the first principal component image of the Landsat multispectral data, from which the results were combined. The Landsat multispectral image matching produced reliable ice velocities for at least 14% wider area on the Nansen Ice Shelf than for the case of using single band (i.e., panchromatic) image matching. The ice velocities derived from the Landsat multispectral image matching have the error of $2.1m\;a^{-1}$ compared to the in situ Global Positioning System (GPS) observation data. The region adjacent to the Drygalski Ice Tongue showed the fastest increase in ice velocity between 2000 and 2017. The ice velocity along the central flow line of the Nansen Ice Shelf was stable before 2010 (${\sim}228m\;a^{-1}$). In 2011-2012, when a rift began to develop near the ice front, the ice flow was accelerated (${\sim}255m\;a^{-1}$) but the velocity was only about 11% faster than 2010. Since 2014, the massive rift had been fully developed, and the ice velocity of the upper region of the rift slightly decreased (${\sim}225m\;a^{-1}$) and stabilized. This means that the development of the rift and the resulting collapse of the ice front had little effect on the ice velocity of the Nansen Ice Shelf.

• Korean Journal of Environmental Biology
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• v.37 no.1
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• pp.42-47
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• 2019

This experiment was conducted to investigate the effects of pH on the mineral nutrient uptake and growth of the four Chinese chives species. The Chinese chives species used in the experiment were the cultivated species grown in the farm (cultivated Allium tuberosum) and three wild species of wild Allium tuberosum, A. thunbergii and A. senescens. The pH levels of soil medium were set to be 4.5, 6.5, and 7.5. Fresh weight(FW) of cultivated A. tuberosum was highest at all pH levels. The increase of soil pH increased the FW of the wild A. tuberosum and A. thunbergii, but no difference was noted for the A. tuberosum and A. senescens. Plant height was higher in the order of wild A. tuberosum, A. thunbergii, and cultivated A. tuberosum and A. thunbergii. Notably plant height of the wild A. tuberosum increased significantly by the pH increase. The Zn content of the wild A. tuberosum was shown to be significantly higher than that of the other species and increased with the increase of soil pH. This indicates that there is a close relationship between the plant height and Zn content in Chinese chives plant. Principal component analysis for characterizing closely related A. species using the factors of plant growth and amounts of nutrients uptake showed that the cultivated A. and wild A. tuberosum were in the $4^{th}$ quadrant of the graph which are classified as the same species, while A. senescens and thunbergii was in $1^{st}$ and $3^{rd}$ quadrant indicating different species, respectively.

• Korean Journal of Breeding Science
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• v.50 no.4
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• pp.406-414
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• 2018

This study was conducted to develop environmental risk assessments and biosafety guides for insect-resistant genetically modified rice in an LMO (Living Modified Organism) isolation field. In the LMO quarantine area of Kyungpook National University, the species diversities and population densities of non-target insects found on insect-resistant genetically modified rice (Bt-T), rice resistant to Cnaphalocrocis medinalis, and non-GM rice (Dongjin-byeo and Ilmi-byeo) were investigated. The Bt-T plants were, therefore, evaluated under field conditions to detect possible impacts on above ground insects and spiders. In 2016 and 2017, the study compared transgenic rice and two non-GM reference rice, namely Dongjin-byeo and Ilmi-byeo, at Gunwi. A total of 9,552 individuals from 51 families and 11 orders were collected from the LMO isolation field. From the three types of rice fields, a total of 3,042; 3,212; and 3,297 individuals from the Bt-T, Dongjin-byeo, and Ilmi-byeo were collected, respectively. There was no difference between the population densities of the non-target insect pests, natural enemies, and other insects on the Bt-T compared to non-GM rice. The data on insect species population densities were subjected to principal component analysis (PCA) without distinguishing between the three varieties, namely GM, non-GM, and reference cultivar, in all cultivation years. However, the PCA clearly separated the samples based on the cultivation years. These results suggest that insect species diversities and population densities during plant cultivation are determined by environmental factors (growing condition and seasons) rather than by genetic factors.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.300-310
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• 2022

The objective of this experiment was to investigate the effect of drip irrigation volume on tomatoes (Solanum lycopersicum L.) grown in a greenhouse using perlite medium. Plants were treated by three different irrigation treatment I₀, I₂₅, and I₅₀ (where irrigation volume of I₂₅ and I₅₀ was 25% and 50% higher than I₀, having limited or no leaching). Growth characteristics of plants, yield and water use efficiency were measured. The result showed that plant height, leaf length and leaf width were lowest in the I₀ treated plants. However, these parameters were not statistically significant differences between the plants that were grown in the I₂₅ and I₅₀ treatment. Soluble solids content, acidity and dry matter of 111th, 132nd, and 143rd days harvested tomato were higher in the plants irrigated with lowest volume (I₀) than the higher volume (I₂₅ or I₅₀). In addition, water content was lower in the 111th and 132nd days of harvested tomatoes from the I₀ treatment. The number of big-size tomatoes (>180 g) was significantly higher in the I₂₅ irrigated plants. There was no significant difference in the total number of harvested fruits among the treatments. The average fruit weight and total yield of harvested tomatoes were lowest in the I₀ treated plants. The water consumption of tomato was not significantly different amongst the treatments but water use efficiency was lowest in the I₀ treatment. Principal component analysis revealed that total soluble solid and acidity of tomato showed a positive correlation between each other. These results suggest that I₂₅ was the optimum irrigation treatment for tomato based on its measured growth characteristics, yield and water use efficiency.

• Journal of Wetlands Research
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• v.25 no.3
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• pp.205-212
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• 2023

This study was attempted to find out how the ecological niche and interspecies relationship of Quercus aliena and Q. serrata, which are the main constituents of potential natural vegetation along the riverside of mountains in Korea, under climate change conditions. To this end, soil moisture and soil nutrients were treated with 4 grad ients under climate change conditions with elevated CO₂ and temperature, plants we re harvested at the end of the growing season, growth responses of traits were measured, ecological niche breadth and overlap were calculated, and it was compared with that of the control group(ambient condition). In addition, the relationship between the two species was analyzed by principal component analysis using trait values. As a result, the ecological niche breadth of Q. aliena was wider than that of Q. serrata under the moisture environment conditions under climate change. Under nutrient conditions, the ecological niche of the two species were similar. In addition, the ecological overlap for soil moisture of Q. aliena and Q. serrata was wider than the soil nutrient gradient under climate change. The species with traits in which the increase in ecological niche breadth due to climate change occurred more than the decrease was Q. aliena in both water and nutrient gradients. And in the responses of the population level, due to climate change, the adaptability of Q. aliena was higher than that of Q. serrata under the soil moisture condition, but the two species were similar under the nutrient condition. These results mean that the competition between the two species occurs more severely in the water environment under climate change conditions, and at that time, Q. aliena has higher adaptability than Q. serrata.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.6 no.1
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• pp.56-64
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• 1995

Family is a primary unit of the major socialization processing for children. Parents among the family members are one of the most important figures from whom the child and adolescent acquire a wide variety of behavior patterns, attitudes, values and norms. An organization of family members product family structural functioning. Abnormal family structure is one of the most important reference models in the learning of antisocial patterns of behavior. Therefore incest and child sexual abuse including spouse abuse, elderly abuse, and neglect occurs in the abnormal family structural setting. In particular, incest, a specific form of sexual abuse, was once thought to be a phenomenon of great rarity, but our clinical experiences, especially over the past decade, have made us aware that incest and child sexual abuse is not rare case and on the increasing trend. Therefore, the aim of this study was to determine the family problem and dynamics of incest family, and character pattern of post-incest adolescent victim in Korea. A total of 1,838 adolescents from middle and high school(1,237) and juvenile correctional institute(601) were studied, sampled from Korean student population and adolescent delinquent population confined in juvenile correctional institutes, using proportional stratified random sampling method. The subjects' ages ranged from 12 to 21 years. Data were collected through questionnaire survey. Data analysis was done by IBM PC of Behavior Science Center at the Korea university, using SAS program. Statistical methods employed were Chi-square, principal component analysis and t-test etc. The results of this study were as follows ; 1) Of 1,071 subjects, 40(3.7%) reported incest experiences(sibling incest : 1.6% ; another type of incest : 2.1%) in their family setting. 2) The character pattern of post-incest adolescent victim was more socially maladjusted, immature, impulsive, rigid, anxious and dependent than non-incest adolescent. Also they showed some problem in academic performance and their assertiveness. 3) The other family members of incest family revealed more psychological and behavioral problem such as depression, alcoholism, psychotic disorder and criminal act than the non-incest family, even though there is no evidence of the context between them. 4) The family dynamics of incest family tended to be dysfunctional trend, as compared with non-incest family. It showed that the psychological instability of family member, parental rejection toward their children, coldness and indifference among family member and marital discordance between the parents had significant correlation with incest.