• Korean Journal of Agricultural and Forest Meteorology
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• v.11 no.3
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• pp.111-117
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• 2009

Food and Agricultural Organization (FAO) Penman-Monteith (PM) equation is one of the most widely used equations for predicting evapotranspiration (ET) of crops. The ET rate and the base crop coefficients ($K_{cb}$) of the two different grape vines (i.e., Campbell Early and Kyoho) cultivated in Suwon were calculated by using the FAO PM equation. The ET rate of Campbell Early was $2.41\;mm\;day^{-1}$ and that of Kyoho was $2.22\;mm\;day^{-1}$ in August when the leaf area index was 2.2. During this period, the $K_{cb}$ of Campbell Early based on the FAO PM equation was on average 0.49 with the maximum value of 0.72. On the other hand, the $K_{cb}$ of Kyoho was averaged to be 0.45 with the maximum value of 0.64. The seasonal leaf area index for two grape cultivars was measured as 0.15 in April, 0.5 in May, 1.4 in June, 2.2 in July-September, and 1.5 in October. The $K_{cb}$ of Campbell Early showed a seasonal variation, changing from 0.03 in April to 0.11 in May, 0.31 in June, 0.49 in July-September, and 0.33 in October. The magnitudes and the seasonality of $K_{cb}$ of Kyoho were similar to those of Campbell Early.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.4
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• pp.280-292
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• 2017

Hail is not a frequently occurring weather event, and there are even fewer reports of hail damages to forest stands. Since the 2000s, an increase in hail incidence has been documented in Europe and the United States. In Korea, severe hails occurred in Jeollanam-do province on May 31 and in Gyeongsangbuk-do province on June 1, 2017. Hail size was ranged from 0.5 to 5.0 cm in diameter in Jeollanam-do, and from 1.5 to 3.0 cm in Gyeongsangbuk-do. This study was aimed to analyze the hail damages to forests by species and topography based on damage-categorized maps created by using drones and aerial photographs, and to analyze relationships of the damages with meteorological factors. The total damaged forest area was 1,163.1ha in Jeollanam-do, and 2,942.3ha in Gyeongsangbuk-do. Among the 'severe' damaged area 326.7ha, 91% was distributed in Jeollanam-do, and concentrated in the city of Hwasun which covers 57.2% of the total 'severe' damaged area. The most heavily damaged species was Korean red pine(Pinus densiflora S. & Z.) followed by P. rigida. Most broad-leaved trees species including oaks were recovered without any dead trees found. Liliodendron tulipifera was the most severely damaged in terms of the rate of 'severe' degree individuals which are needed to be checked whether they will die or be recovered. Cause of the death of pines was considered as the combination of physical damage caused by the hail and long-lasting drought with high air temperature that occurred before and after the hail event. No pathogens and insects were found which might have affected to tree deaths. We suggested a dieback mechanism of the pine trees damaged by hail and drought.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.4
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• pp.252-269
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• 2017

This study was carried out to examine the base temperature to flowering and the average days to flowering by accumulated hours of low temperature ($5.0^{\circ}C$) or changing temperature after bud breaking. Over-all, the prediction of flowering time in the commercial apple cultivars ('Fuji' and 'Tsugaru') and apple cultivars ('Chukwang', 'Gamhong', 'Hongan', 'Honggeum', 'Hongro', 'Hongso', 'Hwahong', 'Summer dream', 'Sunhong') bred in Korea at the Gunwi region for 4 years (from 2009 to 2012) was investigated. Also, this study estimated the flowering time when the air temperature of Gunwi region rises at $5.0^{\circ}C$ was investigated using the same data. The range of accumulated hours of low temperature (chilling requirement) was from 0 hour to 1,671 hours, and the range of high temperature (heat requirements) to flowering after low temperature treatment was from $5.0^{\circ}C$ to $29.0^{\circ}C$. The treatments of changing temperature after bud breaking were classified as constant temperature treatment (control) and $5.0{\sim}10.0^{\circ}C$ elevation or descent treatments. The results show that the average days to flowering was longer with shorter accumulated hours of low temperature, and the average days from bud breaking to flowering of 0 hour treatment was longer about 2~4 weeks than that of 1,335~1,503 hours treatments. In comparing to apple cultivars, the all cultivars were not flowered under $10.0^{\circ}C$ after bud breaking, and the cultivars with low chilling requirements needed low heat requirements for flowering. The average days to flowering of treatments that the air temperature after bud breaking was controlled about $15.0^{\circ}C$ was shorter about 1~3 weeks than that of treatments was controlled about $10.0^{\circ}C$. In the treatment of changing temperature after bud breaking, the average days from bud breaking to flowering of temperature elevation treatment was shorter than that of constant temperature treatment. By use of these results, the base temperature to flowering of main apple cultivars in Korea was seemed to $10.0^{\circ}C$, and if the air temperature of Gunwi region rises about $5.0^{\circ}C$ than that of current, the flowering time was estimated to be delayed by 1 week.

• The Journal of Korean Orthopaedic Ultrasound Society
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• v.7 no.1
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• pp.1-6
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• 2014

Purpose: In order to know the effectiveness of ultrasonographic examination in diagnosis and follow-up evaluation for the frozen shoulder, we compared those with contralateral side in initial and after steroid injection. Materials and Methods: For the 20 unilateral frozen shoulder from July 2012 to July 2013, ultrasonographic examination was tried using reference line 1 (CBT: distance from coracoid process to LHB tendon) and line 2 (CBG: distance from coracoid process to bicipital groove). We tried 1 time steroid injection and compared the improvement in gross motion and reference line with 2 month, 4 month, and 6 month's serial ultrasonographic examination. Results: The differences on CBT line between lesion side and normal side were -5.6 mm, -5.0 mm, and -4.3 mm in neutral (Neut), external rotation (ER) and internal rotation (IR), respectively. The differences on CBG line were -6.1 mm, -4.7 mm, and -5.0 mm respectively (p<0.05). The changes in the reference line after steroid injection were evaluated at 2 month (CBT: -4.8 mm, -3.5 mm, -2.6 mm / CBG: -4.7 mm, -4.0 mm, -3.6 mm), 4 month (CBT: -4.7 mm, -3.2 mm, -1.7 mm / CBG: -4.3 mm, -3.7 mm, -1.2 mm), and 6 month (CBT: -1.1 mm, -2.9 mm, -0.5 mm / CBG: -1.2 mm, -0.7 mm, -0.9 mm). The gross motion was improved at 4 month after injection, from elevation $108^{\circ}$, ER $32^{\circ}$, IR L5 in initial to $133^{\circ}$, $42^{\circ}$, L3 respectively (p<0.05). Pain improved from 7.5 in initial to 3.0 at 2 month on visual analog scale (VAS). Conclusion: The serial examination after steroid injection revealed that the delayed improvement on reference line (6 month) compared with pain (2 month) or gross motion (4 month). Dynamic ultrasonogram was useful in diagnosis and follow-up evaluation of frozen shoulder.

• Cartoon and Animation Studies
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• s.39
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• pp.233-259
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• 2015

Comics is a medium that characters lead a story as words are combined with pictures. Despite characters are simple and exaggerated fictive ones, readers empathize with personality of the character through outer appearance of face and clothes, expression, behavior lines etc. Personality of a character is established by the author or story writer of the comics. Basically, established personality must be maintained through the comics without being broken. To establish personality of a character, understanding of human personality is important. One method for the foregoing is to refer to the framework used for analyzing human personality. As for personality type by blood type, it is considered that there is a specific type of personality according to blood type, and human personality is analyzed by four blood types of A, B, AB and O. Personality type by blood type is convenient to access in the way that it is easy and simple without complexity. The process of establishing personality of a character may be easier by referring to the personality according to blood type. Kishimoto Masashi, the author of the comics is establishing blood types for each character. This study aims to analyze personality depending on the blood types and relations according to blood types among of main and surrounding characters appearing in . As for research methods, this study, first, analyzed how blood type is related to personality in 'the relation between blood type and personality'. Second, this study analyzed blood type and personality in 'personality by blood type of characters in comics '. Third, in the 'personality and relations according to the blood types of characters in the comics ', this study analyzed personality and relations according to the blood type by using a 'caring relationship' which is a like-minded relation according to the blood type. Relations that this study analyzed include '1) Relation between team manager and team member in a team Naruto is belonging', '2) Naruto's eternal triangle and family relations', '3) Naruto's teacher-pupil relations and team manager relation', '4) Main rivalries in ' and '5) change in Naruto and Sasuke's relationship from adversarial to cooperator relationship'. From the relations according to blood types between personality and character established by the author, it is possible to infer that the author referred to the personality of each blood type. Like this, establishing personality of characters and making relations among characters based on the personality type by blood type may be one of useful methods for creating a story.

• Microbiology and Biotechnology Letters
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• v.3 no.3
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• pp.123-134
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• 1975

Out of 96 yeast strains isolated from various natural habitats, five strains were screened based on their ability to ferment agricultural biproducts such as rice-, barley-and wheat-bran, and sawdust. These were identified as Hansenula anomala var anomala, Candide utilis, C. pelliculosa, Debaryomyces hansenii, and Irpex lacteus. Using these yeasts the above mentioned agricultural biproducts were fermented in various combinations. The fermented product was fed to 180 male Starcroses for eight weeks and obtained a body weight increase of 15.1g a day, while the unfermented control feed increased 10.5g a day.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.36 no.1
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• pp.11-17
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• 2003

As a pan of a study on effective use of seafood processing by-products, such as cuttle bone as a calcium source, we examined on the kind of organic acid (acetic acid and lactic acid), reaction concentration (mole ratio of calcium to mole of organic acid), reaction temperature $(20\~60^{\circ}C)$ and reaction time (6$\~$24 hours) as reaction conditions for the solubility improvement of cuttle bone powder. The high soluble cuttle bone powder was also prepared from the optimal reaction conditions and partially characterized. From the results on examination of reaction conditions, the high soluble cuttle bone powder was prepared with 0.4 in mole ratio of a calcium to mole of a acetic acid at room temperature for 12 hours, Judging from the patterns of IR and X-ray diffraction, the main component of the high soluble cuttle bone powder was presented as a form of calcium acetate, and a scanning electron micrograph showed an irregular form. The soluble calcium content in the high soluble cuttle bone powder was $5.3\%$ and it was improved about 1,380 times compared to a raw cuttle bone powder. For the effective use of the high soluble cuttle bone powder as a material for a functional improvement in processing, it should be used after the calcium treatment at room temperature for about 1 hour in tap water or distilled water. from these results, we concluded that it is possible to use the high soluble cut시e bone powder as a material for a functional improvement in processing.

• 대한공업교육학회지
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• v.31 no.2
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• pp.203-232
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• 2006

The purposes of this study are to examine the effects of learning, which was applied TRIZ's 40 inventive principles, on the improvement of learners' creativity and to offer basic information that would be necessary to study on Inventive Education in Technology Education. In order to achieve the purposes, objects were divided into two groups, experiment group(74 students) and control group(67 students), who were from B Middle school in Daejeon. Creativity Self-Assessment and Student Inventive Rating Scale were used as tools for research so that we could find the homogeneity in two groups. An applied design method was nonequivalent control group pretest-posttest design. This study was performed for 2 hours on the 1st and the 3rd Saturday in every month from the 3rd week of March, 2006 to the 3rd of July of 2006, and total researching period was 9 weeks. In that time, the students were required to learn 40 inventive principles. The results from this study are as below. (1) Applying TRIZ's 40 inventive principles had a positive effect on students' CQ(creative quotient), as influencing on the subordinate factors of creativity, such as, originality, germinal, trasformational, value, attraction, expressive power and organic systemicity. However it didn't have any effect on adequateness, properness, merit, complex and elegance. (2) Applying TRIZ's 40 inventive principles had a significant effect neither on CQ by sex, nor on the subordinate factors of creativity, except for originality and expressive power. Based on the results of the experiment, below suggestions were made to promote the application of TRIZ's 40 inventive principles to Technology Education. (1) Although this study was performed by using development activities, it is necessary to study more systemically to apply 40 inventive principles to regular subject in Technology Education. (2) As creativity was very important in Technology Education, there should be studies on the various types of inventive principles and techniques for Inventive Education in Technology Education.

• 대한공업교육학회지
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• v.33 no.1
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• pp.149-168
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• 2008

The purpose of this study is to verify the effect of PSpice instruction on academic achievement in 'Combination logic circuit' unit of 'Digital Logic Circuit' in industrial high school. Three kinds of null hypotheses were formulated. Two classes of the third grade of C technical high school in Gyeong-buk were divided into experimental group and control group in order to verify null hypotheses. In the experimental design, 'Non-equivalent control group pretest-posttest' model was utilized. This experiment was conducted for six classes, the experimental group was applied to PSpice instruction method before the circuit traning while the control group was applied to traditional lecture oriented method before the circuit traning. Window SPSS 10.0 korean language version program was used for the data analysis and independent sample t-test was used to identify the average of each group. Significance level was set to .05 level. The results obtained in this study were as follows; First, PSpice instruction had not an effect on academic achievement according to a group type. However, these instruction had an effect on the following sub-domains; the psychomotor domain. Second, PSpice instruction had not an effect on academic achievement according to a studies level. However, these instruction for middle and low level students had an effect on the cognitive and psychomotor domain, and for middle level students had an effect on the affective domain. Third, PSpice instruction had not an effect on shortening of a training requirement. However, this instruction for low level students had an effect on shortening of a training requirement. The study results of simulation instruction was chiefly efficient in the psychomotor domain. We could know that simulation instruction is efficient as went to a low level students than an upper level students. Thus, We may make the study effectiveness in various instruction method.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.119-142
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• 2015

With the explosive growth in the volume of information, Internet users are experiencing considerable difficulties in obtaining necessary information online. Against this backdrop, ever-greater importance is being placed on a recommender system that provides information catered to user preferences and tastes in an attempt to address issues associated with information overload. To this end, a number of techniques have been proposed, including content-based filtering (CBF), demographic filtering (DF) and collaborative filtering (CF). Among them, CBF and DF require external information and thus cannot be applied to a variety of domains. CF, on the other hand, is widely used since it is relatively free from the domain constraint. The CF technique is broadly classified into memory-based CF, model-based CF and hybrid CF. Model-based CF addresses the drawbacks of CF by considering the Bayesian model, clustering model or dependency network model. This filtering technique not only improves the sparsity and scalability issues but also boosts predictive performance. However, it involves expensive model-building and results in a tradeoff between performance and scalability. Such tradeoff is attributed to reduced coverage, which is a type of sparsity issues. In addition, expensive model-building may lead to performance instability since changes in the domain environment cannot be immediately incorporated into the model due to high costs involved. Cumulative changes in the domain environment that have failed to be reflected eventually undermine system performance. This study incorporates the Markov model of transition probabilities and the concept of fuzzy clustering with CBCF to propose predictive clustering-based CF (PCCF) that solves the issues of reduced coverage and of unstable performance. The method improves performance instability by tracking the changes in user preferences and bridging the gap between the static model and dynamic users. Furthermore, the issue of reduced coverage also improves by expanding the coverage based on transition probabilities and clustering probabilities. The proposed method consists of four processes. First, user preferences are normalized in preference clustering. Second, changes in user preferences are detected from review score entries during preference transition detection. Third, user propensities are normalized using patterns of changes (propensities) in user preferences in propensity clustering. Lastly, the preference prediction model is developed to predict user preferences for items during preference prediction. The proposed method has been validated by testing the robustness of performance instability and scalability-performance tradeoff. The initial test compared and analyzed the performance of individual recommender systems each enabled by IBCF, CBCF, ICFEC and PCCF under an environment where data sparsity had been minimized. The following test adjusted the optimal number of clusters in CBCF, ICFEC and PCCF for a comparative analysis of subsequent changes in the system performance. The test results revealed that the suggested method produced insignificant improvement in performance in comparison with the existing techniques. In addition, it failed to achieve significant improvement in the standard deviation that indicates the degree of data fluctuation. Notwithstanding, it resulted in marked improvement over the existing techniques in terms of range that indicates the level of performance fluctuation. The level of performance fluctuation before and after the model generation improved by 51.31% in the initial test. Then in the following test, there has been 36.05% improvement in the level of performance fluctuation driven by the changes in the number of clusters. This signifies that the proposed method, despite the slight performance improvement, clearly offers better performance stability compared to the existing techniques. Further research on this study will be directed toward enhancing the recommendation performance that failed to demonstrate significant improvement over the existing techniques. The future research will consider the introduction of a high-dimensional parameter-free clustering algorithm or deep learning-based model in order to improve performance in recommendations.