• Radiation Oncology Journal
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• v.24 no.1
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• pp.30-36
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• 2006

Purpose: It is well known from clinical experience that acute complications of chemoradiation therapy vary from patients to patients. However, there are no known factors to predict these acute complications before treatment starts. The human XRCC1 gene is known as a DNA base excision repair gene. We investigated the possibilities of XRCC1 gene polymorphisms as a predictor for the acute complications of chemoradiation therapy in colorectal cancer patients. Materials and Methods: From July 1997 to June 2003, 86 colorectal cancer patients (71 rectal cancer, 13 sigmoid colon cancer and 2 colon cancer patients) were treated with chemoradiation therapy at the Department of Radiation Oncology, Inha University Hospital. Twenty-two patients were in stage B, 50 were in stage C, 8 were in stage D and 6 patients were unresectable cases. External radiation therapy was delivered with 10MV X-ray at a 1.8 Gy fraction per day for a total dose of radiation of $30.6{\sim}59.4 Gy$ (median: 54 Gy). All the patients received 5-FU based chemotherapy regimen. We analyzed the acute complications of upper and lower gastrointestinal tract based on the RTOG complication scale. The initial and lowest WBC and platelet count were recorded during both the RT period and the whole treatment period. Allelic variants of the XRCC1 gene at codons 194, 280 and 399 were analyzed in the lymphocyte DNA by performing PCR-RFLP. Statistical analyses were carried out with the SAS (version 6.12) statistical package. Results: When all the variables were assessed on the multivariate analysis, recurrent disease revealed the factors that significantly correlated with upper gastrointestinal acute complications. Arg399Gln polymorph isms of the XRCC1 gene, the radiation dose and the frequencies of chemotherapy during radiation therapy were significantly correlated with lower gastrointestinal complications. Arg399Gln polymorph isms also affected the decrease of the WBC and platelet count during radiation therapy. Conclusion: Although the present sample size was too small for fully evaluating this hypothesis, this study suggests that Arg399Gln polymorph isms of the XRCC1 genes may be used as one of the predictors for acute complications of chemoradiation therapy in colorectal cancer patients.

• The Journal of Korean Academy of Sensory Integration
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• v.17 no.2
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• pp.31-40
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• 2019

Purpose : The purpose of this study was to compare the difference between preterm infants and toddlers (PT) and full-term infant and toddler (FT) of sensory processing ability, feeding as well as investigate the correlation of sensory processing ability with feeding of preterm infants and toddlers. Methods : The subjects of a study were 107 including 51 PT and 56 FT. Infant/Toddler Sensory Profile 2 (ITSP 2) was used to assess sensory processing ability. The Behavioral Pediatrics Feeding Assessment (BPFAS) was used to assess feeding behavior. The collected data were analyzed by using SPSS 21.0. Independent sample t-test was used in order to compare the difference between PT group and FT group. Pearson correlation analysis was used in order to investigate the correlation of sensory processing ability with feeding of preterm infants and toddlers. Results : There was a significant difference in sensory sensitivity and oral sensory processing between with PT group and FT group (p<0.05). There was a significant difference in feeding behavior between with PT group and FT group (p<.05). In PT group, there are positive correlations of sensory avoidance (r=.443) and sensory sensitivity (r=.374) with feeding frequency. General behavior (r=.390) and oral sensory processing (r=.513) showed a positive correlation with feeding frequency. In addition, oral sensory processing (r=.529) showed a positive correlation with feeding problem. Conclusion : It is proved that the interrelationship of sensory processing ability with feeding and of preterm infants and toddlers. And it is meaningful to recognize significance of sensory processing characteristics to comprehend feeding and of preterm infants and toddlers.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.239-251
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• 2019

Statistical methods such as moving averages, Kalman filtering, exponential smoothing, regression analysis, and ARIMA (autoregressive integrated moving average) have been used for stock market predictions. However, these statistical methods have not produced superior performances. In recent years, machine learning techniques have been widely used in stock market predictions, including artificial neural network, SVM, and genetic algorithm. In particular, a case-based reasoning method, known as k-nearest neighbor is also widely used for stock price prediction. Case based reasoning retrieves several similar cases from previous cases when a new problem occurs, and combines the class labels of similar cases to create a classification for the new problem. However, case based reasoning has some problems. First, case based reasoning has a tendency to search for a fixed number of neighbors in the observation space and always selects the same number of neighbors rather than the best similar neighbors for the target case. So, case based reasoning may have to take into account more cases even when there are fewer cases applicable depending on the subject. Second, case based reasoning may select neighbors that are far away from the target case. Thus, case based reasoning does not guarantee an optimal pseudo-neighborhood for various target cases, and the predictability can be degraded due to a deviation from the desired similar neighbor. This paper examines how the size of learning data affects stock price predictability through k-nearest neighbor and compares the predictability of k-nearest neighbor with the random walk model according to the size of the learning data and the number of neighbors. In this study, Samsung electronics stock prices were predicted by dividing the learning dataset into two types. For the prediction of next day's closing price, we used four variables: opening value, daily high, daily low, and daily close. In the first experiment, data from January 1, 2000 to December 31, 2017 were used for the learning process. In the second experiment, data from January 1, 2015 to December 31, 2017 were used for the learning process. The test data is from January 1, 2018 to August 31, 2018 for both experiments. We compared the performance of k-NN with the random walk model using the two learning dataset. The mean absolute percentage error (MAPE) was 1.3497 for the random walk model and 1.3570 for the k-NN for the first experiment when the learning data was small. However, the mean absolute percentage error (MAPE) for the random walk model was 1.3497 and the k-NN was 1.2928 for the second experiment when the learning data was large. These results show that the prediction power when more learning data are used is higher than when less learning data are used. Also, this paper shows that k-NN generally produces a better predictive power than random walk model for larger learning datasets and does not when the learning dataset is relatively small. Future studies need to consider macroeconomic variables related to stock price forecasting including opening price, low price, high price, and closing price. Also, to produce better results, it is recommended that the k-nearest neighbor needs to find nearest neighbors using the second step filtering method considering fundamental economic variables as well as a sufficient amount of learning data.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.1
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• pp.15-33
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• 2021

In this study, the possibility of discriminating Fire blight (FB) infection tested using the hyperspectral imagery. The reflectance of healthy and infected leaves and branches was acquired with 5 nm of full width at high maximum (FWHM) and then it was standardized to 10 nm, 25 nm, 50 nm, and 80 nm of FWHM. The standardized samples were divided into training and test sets at ratios of 7:3, 5:5 and 3:7 to find the optimal bands of FWHM by the decision tree analysis. Classification accuracy was evaluated using overall accuracy (OA) and kappa coefficient (KC). The hyperspectral reflectance of infected leaves and branches was significantly lower than those of healthy green, red-edge (RE) and near infrared (NIR) regions. The bands selected for the first node were generally 750 and 800 nm; these were used to identify the infection of leaves and branches, respectively. The accuracy of the classifier was higher in the 7:3 ratio. Four bands with 50 nm of FWHM (450, 650, 750, and 950 nm) might be reasonable because the difference in the recalculated accuracy between 8 bands with 10 nm of FWHM (440, 580, 640, 660, 680, 710, 730, and 740 nm) and 4 bands was only 1.8% for OA and 4.1% for KC, respectively. Finally, adding two bands (550 nm and 800 nm with 25 nm of FWHM) in four bands with 50 nm of FWHM have been proposed to improve the usability of multispectral image sensors with performing various roles in agriculture as well as detecting FB with other combinations of spectral bands.

• Journal of fish pathology
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• v.33 no.2
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• pp.111-118
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• 2020

The genus Edwardsiella belonging to the family Enterobacteriaceae is a member of Gram-negative rod-shaped bacteria that cause disease in diverse aquatic organisms such as fish, amphibians and reptiles as well as avians and mammals including human throughout the world. This genus had been composed of three species, E. hoshinae, E. ictaluri and E. tarda, but recent researches erected two novel species, E. anguillarum and E. piscicida that were conventionally identified as E. tarda. In this study, we isolated seven strains belonging to the genus Edwardsiella from freshwater fishes that had been reared at inland fish farms in South Korea and investigated their biochemical characteristics and molecular phylogenetic relationships. The seven strains showed typical characteristics of four Edwardsiella species, E. anguillarum, E. ictaluri, E. piscicida and E. tarda, by biochemical analyses of Gram staining, indole and hydrogen sulfide (H2S) production, and API (Analytic Profile Index) 20E test. Molecular phylogenetic analyses inferred from DNA sequence data of both 16S ribosomal RNA (rRNA) and DNA gyrase subunit B (gyrB) genes were congruent with the biochemical characteristics. As a result, both biochemical and molecular phylogenetic analyses identified four strains isolated from three Anguilla species as E. anguillarum, E. piscicida and E. tarda, two strains from Pelteobagrus fulvidraco and Silurus asotus as E. ictaluri, and one strain from Moroco oxycephalus as E. piscicida. In this study, we isolated and successfully identified recently newly erected species, E. anguillarum and E. piscicida in addition to historically notorious pathogenic species, E. ictaluri and E. tarda. In the future study, systematic and comprehensive monitoring of the four Edwardsiella species are required for studying differences in pathogenicity among freshwater fishes.

• Journal of the Korean Geotechnical Society
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• v.38 no.7
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• pp.5-24
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• 2022

The current performance evaluation of slope anchors qualitatively determines the physical bonding between the anchor head and ground as well as cracks or breakage of the anchor head. However, such performance evaluation does not measure these primary factors quantitatively. Therefore, the time-dependent management of the anchors is almost impossible. This study is an evaluation of the 3D numerical model by SfM which combines UAS images with terrestrial LiDAR to collect numerical data on the damage factors. It also utilizes the data for the quantitative maintenance of the anchor system once it is installed on slopes. The UAS 3D model, which often shows relatively low precision in the z-coordinate for vertical objects such as slopes, is combined with terrestrial LiDAR scan data to improve the accuracy of the z-coordinate measurement. After validating the system, a field test is conducted with ten anchors installed on a slope with arbitrarily damaged heads. The damages (such as cracks, breakages, and rotational displacements) are detected and numerically evaluated through the orthogonal projection of the measurement system. The results show that the introduced system at the resolution of 8K can detect cracks less than 0.3 mm in any aperture with an error range of 0.05 mm. Also, the system can successfully detect the volume of the damaged part, showing that the maximum damage area of the anchor head was within 3% of the original design guideline. Originally, the ground adhesion to the anchor head, where the z-coordinate is highly relevant, was almost impossible to measure with the UAS 3D numerical model alone because of its blind spots. However, by applying the combined system, elevation differences between the anchor bottom and the irregular ground surface was identified so that the average value at 20 various locations was calculated for the ground adhesion. Additionally, rotation angle and displacement of the anchor head less than 1" were detected. From the observations, the validity of the 3D numerical model can obtain quantitative data on anchor damage. Such data collection can potentially create a database that could be used as a fundamental resource for quantitative anchor damage evaluation in the future.

• Journal of the Korean Geotechnical Society
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• v.25 no.4
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• pp.91-103
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• 2009

Slope failure depends upon the climatic features related to related rainfall, structural geology and geomorphological features as well as the variation of the mechanical behaviors of soil constituting a slope. In this paper, among many variables, effects of soil layer thickness on the slope failure process, and variations of matric suction and volumetric water content were observed. When the soil layer is relatively thick, the descending wetting front decreases matric suction and the observed matric suction reaches to "0" value. When the wetting front reaches to the impermeable boundary, the bottom surface of steel soil box, ascending wetting front was observed. This observation can be postulated to be the effects of various sizes of pores. When macro size pores exist, the capillary effects can be reduced and infilling of pore will be limited. The partially filled pores would be filled with water during the ascending of the wetting front, which bounces from the impermeable boundary. This assumption has been assured from the observation of variation of the volumetric water contents at different depth. When the soil layer is thick (thickness = 20 cm), for granular material, erosion is a cause triggering the slope failure. It has been found that the initiation of erosion occurs when the top soil is fully saturated. Meanwhile, when the soil layer is shallow (thickness = 10 cm), slope slides as en mass. The slope failure for this condition occurs when the wetting front reaches to the interface between the soil layer and steel soil box. As the wetting front approaches to the bottom of soil layer, reduction of shear resistance along the boundary and increase of the unit weight due to the infiltration occur and these produce complex effects on the slope failure processes.

• Journal of the Korean Applied Science and Technology
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• v.40 no.4
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• pp.685-698
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• 2023

This study aimed to identify binge-eating behavior and food addiction in Korean population and to determine their associations with obesity, eating behaviors, mental health and cognitive characteristics. We collected clinical questionnaire scores related to eating problems (e.g. binge eating, food addiction, food cravings), mental health (e.g. depression), and cognitive functions (e.g. impulsivity, emotion regulation) in 257 Korean adults in the normal and the obese weight ranges. Binge-eating and food addiction were most frequent in obese women (binge-eating: 46.6%, food addiction: 29.3%) when we divided the participants into 4 groups depending on gender and obesity status. The independence test using the data with propensity score matching confirmed that binge-eating and food addiction were more prevalent in obese individuals. Finally, we constructed the logistic regression models using forward selection method to evaluate the influence of various clinical questionnaire scores on binge-eating and food addiction respectively. Binge-eating was significantly associated with the clinical scales of eating disorders, food craving, state anxiety, and emotion regulation (cognitive reappraisal) as well as food addiction. Food addiction demonstrated the significant effect of food craving, binge-eating, the interaction of obesity and age, and years of education. In conclusion, we found that binge-eating and food addiction are much more frequent in females and obese individuals. Both binge-eating and food addiction commonly involved eating problems (e.g. food craving), but there was difference in mental health and cognitive risk factors. Therefore, it is required to distinguish food addiction from binge-eating and investigate intrinsic and environmental risk factors for each pathology.

• The Korean Journal of Air & Space Law and Policy
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• v.25 no.2
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• pp.139-162
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• 2010

In terms of the international air transport, the open skies policy implies freedom in the sky or opening the sky. In the normative respect, the open skies policy is a kind of open-door policy which gives various forms of traffic right to other countries, but on the other hand it is a policy of free competition in the international air transport. Since the Airline Deregulation Act of 1978, the United States has signed an open skies agreement with many countries, starting with the Netherlands, so that competitive large airlines can compete in the international air transport market where there exist a lot of business opportunities. South Korea now has an open skies agreement with more than 20 countries. The frequent flyer program (FFP) is part of a broad-based marketing alliance which has been used as an airfare strategy since the U.S. government's airline deregulation. The membership-based program is an incentive plan that provides mileage points to customers for using airline services and rewards customer loyalty in tangible forms based on their accumulated points. In its early stages, the frequent flyer program was focused on marketing efforts to attract customers, but now in the environment of intense competition among airlines, the program is used as an important strategic marketing tool for enhancing business performance. Therefore, airline companies agree that they need to identify customer needs in order to secure loyal customers more effectively. The outcomes from an airline's frequent flyer program can have a variety of effects on international competition. First, the airline can obtain a more dominant position in the air flight market by expanding its air route networks. Second, the availability of flight products for customers can be improved with an increase in flight frequency. Third, the airline can preferentially expand into new markets and thus gain advantages over its competitors. However, there are few empirical studies on the airline frequent flyer program. Accordingly, this study aims to explore the effects of the program on international competition, after reviewing the types of strategic alliance between airlines. Making strategic airline alliances is a worldwide trend resulting from the open skies policy. South Korea also needs to be making open skies agreements more realistic to promote the growth and competition of domestic airlines. The present study is about the performance of the airline frequent flyer program and international competition under the open skies policy. With a sample of five global alliance groups (Star, Oneworld, Wings, Qualiflyer and Skyteam), the study was attempted as an empirical study of the effects that the resource structures and levels of information technology held by airlines in each group have on the type of alliance, and one-way analysis of variance and regression analysis were used to test hypotheses. The findings of this study suggest that both large airline companies and small/medium-size airlines in an alliance group with global networks and organizations are able to achieve high performance and secure international competitiveness. Airline passengers earn mileage points by using non-flight services through an alliance network with hotels, car-rental services, duty-free shops, travel agents and more and show high interests in and preferences for related service benefits. Therefore, Korean airline companies should develop more aggressive marketing programs based on multilateral alliances with other services including hotels, as well as with other airlines.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.29-44
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• 2017

In Internet commerce, consumers are heavily influenced by product reviews written by other users who have already purchased the product. However, as the product reviews accumulate, it takes a lot of time and effort for consumers to individually check the massive number of product reviews. Moreover, product reviews that are written carelessly actually inconvenience consumers. Thus many online vendors provide mechanisms to identify reviews that customers perceive as most helpful (Cao et al. 2011; Mudambi and Schuff 2010). For example, some online retailers, such as Amazon.com and TripAdvisor, allow users to rate the helpfulness of each review, and use this feedback information to rank and re-order them. However, many reviews have only a few feedbacks or no feedback at all, thus making it hard to identify their helpfulness. Also, it takes time to accumulate feedbacks, thus the newly authored reviews do not have enough ones. For example, only 20% of the reviews in Amazon Review Dataset (Mcauley and Leskovec, 2013) have more than 5 reviews (Yan et al, 2014). The purpose of this study is to analyze the factors affecting the usefulness of online product reviews and to derive a forecasting model that selectively provides product reviews that can be helpful to consumers. In order to do this, we extracted the various linguistic, psychological, and perceptual elements included in product reviews by using text-mining techniques and identifying the determinants among these elements that affect the usability of product reviews. In particular, considering that the characteristics of the product reviews and determinants of usability for apparel products (which are experiential products) and electronic products (which are search goods) can differ, the characteristics of the product reviews were compared within each product group and the determinants were established for each. This study used 7,498 apparel product reviews and 106,962 electronic product reviews from Amazon.com. In order to understand a review text, we first extract linguistic and psychological characteristics from review texts such as a word count, the level of emotional tone and analytical thinking embedded in review text using widely adopted text analysis software LIWC (Linguistic Inquiry and Word Count). After then, we explore the descriptive statistics of review text for each category and statistically compare their differences using t-test. Lastly, we regression analysis using the data mining software RapidMiner to find out determinant factors. As a result of comparing and analyzing product review characteristics of electronic products and apparel products, it was found that reviewers used more words as well as longer sentences when writing product reviews for electronic products. As for the content characteristics of the product reviews, it was found that these reviews included many analytic words, carried more clout, and related to the cognitive processes (CogProc) more so than the apparel product reviews, in addition to including many words expressing negative emotions (NegEmo). On the other hand, the apparel product reviews included more personal, authentic, positive emotions (PosEmo) and perceptual processes (Percept) compared to the electronic product reviews. Next, we analyzed the determinants toward the usefulness of the product reviews between the two product groups. As a result, it was found that product reviews with high product ratings from reviewers in both product groups that were perceived as being useful contained a larger number of total words, many expressions involving perceptual processes, and fewer negative emotions. In addition, apparel product reviews with a large number of comparative expressions, a low expertise index, and concise content with fewer words in each sentence were perceived to be useful. In the case of electronic product reviews, those that were analytical with a high expertise index, along with containing many authentic expressions, cognitive processes, and positive emotions (PosEmo) were perceived to be useful. These findings are expected to help consumers effectively identify useful product reviews in the future.