• Journal of Forest and Environmental Science
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• v.31 no.3
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• pp.164-176
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• 2015

Cyathea gigantea is a tree fern distributed throughout humid tropical regions of northeast India and other parts of the country. However, wild populations of this species are largely affected by various natural and anthropogenic activities. Therefore, an attempt was made to study the population structure and regeneration status of C. gigantea in and around greater Itanagar area of Papum Pare district, Arunachal Pradesh. Altogether 45 patches, ranging from 19.63 to $260m^2$ of area, were randomly sampled to study population structure and regeneration status of the species. Population study showed highest number of youngs in the height class of 0.50-0.75 m while, immatures were recorded highest in the height class of 2.0 to 2.5 m. Majority of the matures belonged to 6-9 m height class while it was recorded maximum in the diameter class of 10-15 cm. Average density of C. gigantea was $0.07individuals\;ha^{-1}$ which varied greatly among different patches with a range of 2 to 14. Significant correlations were found between patch size and density of youngs, immatures, matures and total density. Maximum concentration of youngs was observed in patch size $60-140m^2$, while for immatures, it was highest in patch size $20-160m^2$. Similarly, highest concentration of matures was observed in patch size $20-80m^2$ and $80-180m^2$. Population structure of the total population exhibited inverted pyramid shaped distribution. Population structure consisting of youngs, immatures, matures showed that around 60% patches lack of regenerating individuals which depict very poor natural regeneration of the species. Effective conservation strategies are therefore to be formulated to save C. gigantea from the threat of extinction in near future.

• Journal of the Korea Society of Computer and Information
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• v.17 no.7
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• pp.45-52
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• 2012

In this paper, an crowd density in elevator estimation method based on multi-class Adaboost classifier is proposed. The SOM (Self-Organizing Map) based conventional methods have shown insufficient performance in practical scenarios and have weakness for low reproducibility. The proposed method estimates the crowd density using multi-class Adaboost classifier with texture features, namely, GLDM(Grey-Level Dependency Matrix) or GGDM(Grey-Gradient Dependency Matrix). In order to classify into multi-label, weak classifier which have better performance is generated by modifying a weight update equation of general Adaboost algorithm. The crowd density is classified into four categories depending on the number of persons in the crowd, which can be 0 person, 1-2 people, 3-4 people, and 5 or more people. The experimental results under indoor environment show the proposed method improves detection rate by about 20% compared to that of the conventional method.

• Journal of Engineering Education Research
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• v.15 no.3
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• pp.47-58
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• 2012

The purpose of this paper is to verify the education effects of program for engineering students and extract the essential components to be included in the learning contents. For this, we investigated the lecture contents critically and analyzed the evaluation result of questionnaire to examine the students' learning satisfaction and learners' needs concerning the effectiveness of course. The survey using two types of questionnaires was conducted with 210 junior and senior students taking lectures of ${\ll}$Presentation and Debate Skills${\gg}$ in the college of engineering at Pusan National University. According to the evaluation result, students experienced various speech education's effects concerning (1) verbal components, (2) non-verbal components, (3) problem solving competence, (4) teamwork skills, etc. On the other side there have been pointed out as problems in the ${\ll}$Presentation and Debate Skills${\gg}$ class, such as (1) a large number of assignments, (2) insufficiency of more refined evaluation method for the individuals and (3) a well-balanced arrangement between 'theory' and 'practice' was needed. However more importantly, the individual students can not do practice sufficiently owing to the large scale of class. Therefore the various and effective ways to help students improve their communicative competence have to be developed further. Finally, there have been extracted several essential components to be included in the class and implications for ameliorating the class were discussed and suggested in detail.

• The Korean Journal of Ecology
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• v.27 no.2
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• pp.115-120
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• 2004

Coarse woody debris (CWD, $\ge$ 5 cm in maximum diameter) is an important functional component, especially to nutrient cycling in forest ecosystems. To compare mass and nutrient dynamics of CWD in natural oak forests, a two-year study was conducted at Quercus serrata and Q. variabilis stands in Yangpyeong, Kyonggi Province. Total CWD (snag, stump, log and large branch) and annual decomposition mass (Mg/ha) were 1.9 and 0.4 for the Q. serrata stand and 7.5 and 0.5 for the Q. variabilis stand, respectively. Snags covered 72% of total CWD mass for the Q. variabilis stand and 42% for the Q. serrata stand. Most of CWD was classified into decay class 1 for both stands. CWD N and P concentrations for the Q. variabilis stand significantly increased along decay class and sampling time, except for P concentration in 2002. There were no differences in CWD N concentration for the Q. serrata stand along decay class and sampling time. However, CWD P concentration decreased along sampling time. CWD N and P contents (kg/ha) ranged from 3.5∼4.7 and 0.8∼1.3 for the Q. serrata stand to 22.8∼23.6 and 3.7∼4.7 for the Q. variabilis stand. Nitrogen and P inputs (kg/ha/yr) into mineral soil through the CWD decomposition were 0.7 and 0.3 for the Q. serrata stand and 1.6 and 0.3 for the Q. variabilis stand, respectively. The number of CWD and decay rate were main factors influencing the difference in CWD mass and nutrient dynamics between both stands.

• ALGAE
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• v.31 no.2
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• pp.155-165
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• 2016

Green microalgae from the class Chlorophyceae represent a major biodiversity component of eukaryotic algae in continental water. Identification and classification of this group through morphology is a hard task, since it may present cryptic species and phenotypic plasticity. Despite the increasing use of molecular methods for identification of microorganisms, no single standard barcode marker is yet established for this important group of green microalgae. Some available studies present results with a limited number of chlorophycean genera or using markers that require many different primers for different groups within the class. Thus, we aimed to find a single marker easily amplified and with wide coverage within Chlorophyceae using only one pair of primers. Here, we tested the universality of primers for different genes (tufA, ITS, rbcL, and UCP4) in 22 strains, comprising 18 different species from different orders of Chlorophyceae. The ITS primers sequenced only 3 strains and the UCP primer failed to amplify any strain. We tested two pairs of primers for rbcL and the best pair provided sequences for 10 strains whereas the second one provided sequences for only 7 strains. The pair of primers for the tufA gene presented good results for Chlorophyceae, successfully sequencing 21 strains and recovering the expected phylogeny relationships within the class. Thus, the tufA marker stands out as a good choice to be used as molecular marker for the class.

• Asian-Australasian Journal of Animal Sciences
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• v.21 no.1
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• pp.35-41
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• 2008

This study was undertaken to investigate the distribution of major histocompatibility complex class II positive (MHC II+) (HLA-DP-like) cells in the cow uterus (cervix, corpus and cornu uteri) and to compare these cells between the estrus and diestrus phases of the estrous cycle. Twenty-nine multiparous cows were used. Tissue samples from the middle of the cervix, the corpus and the right cornu were taken immediately after slaughter at the estrus or diestrus phase. Streptavidin-biotin peroxidase complex staining was used to detect MHC II+ cells. The number of MHC II+ cells per unit area of tissue was counted using image analysis software under a light microscope. Numerous MHC II+ cells were found in the endometrium (cervix, corpus and cornu uteri) in both estrus and diestrus. MHC II+ cells were found in the surface epithelium of the cervix uteri in diestrus, but in the corpus uteri in both estrus and diestrus and in the cornu uteri in estrus. MHC II+ cells were also found freely in the lumen of the glands and between the gland epithelia of the corpus and cornu uteri in both estrus and diestrus. There were also MHC II+ cells in the connective tissue of the myometrium and perimetrium (outside the endometrium) and around the blood vessels. Endothelial cells were frequently positive for MHC II staining. More MHC II+ cells were found in the endometrium than outside the endometrium in both estrus and diestrus (p<0.001). However, there was no difference in the numbers of positive cells between estrus and diestrus either in the endometrium or outside it. These results are the first evidence for HLA-DP-like MHC II+ cells in the bovine uterus. They indicate that antigen presentation by HLA-DP-like MHC II+ cells of the uterus is not influenced by hormonal status.

• Journal of Distribution Science
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• v.14 no.10
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• pp.127-136
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• 2016

Purpose - This study investigated the effects of lectures in the English medium (EML) on understanding and learning outcomes. Sixty percent of EML lectures in Korea also use Korean for further support. Thus, this situation needs to clearly distinguish the specific impacts of the EML classes on learning outcomes. Here, we use the same English materials, including PowerPoint slides and video content, given in the Korean and English lectures. The difference between the lectures becomes only whether the lecture is delivered in Korean or English. Thus, we can clearly identify whether the language difference makes any difference in learning outcomes. Research design, data, and methodology - Our sample consisted of 91 students taking an international business course the spring of 2015. All course materials, including textbooks, PowerPoint slides, exams, video, and support content, were presented in English. Survey data and exam results were used. Students filled out their student identification number and name, so we could match the surveys against the exam results. Results - First, results show that whether the lecture was delivered in English or Korean was an important factor when students chose the class. Second, English proficiency related to international business and general English levels were higher in the English class than in the Korean class. However, the understanding of key concepts and reading abilities of international business newspapers were the same for students in both classes. Third, teaching materials and lectures were the most important material for the understanding of key concepts in the business major. Fourth, the exam results showed no difference in performance of the students in the English versus the Korean class. This shows that EML classes were not necessarily detrimental to the understanding of major concepts of the lecture. Thus, it is important that researchers carefully design empirical settings to study the effectiveness of EML. Conclusions - The English lecture can be as helpful for enhancing knowledge in the business major as the Korean lecture. For further research, various English lecture forms can be considered to distinguish the effects of the English lecture.

• Journal of KIISE:Software and Applications
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• v.33 no.10
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• pp.886-895
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• 2006

Fingerprint classification reduces the number of matches required in automated fingerprint identification systems by categorizing fingerprints into a predefined class. Support vector machines (SVMs), widely used in pattern classification, have produced a high accuracy rate when performing fingerprint classification. In order to effectively apply SVMs to multi-class fingerprint classification systems, we propose a novel method in which SVMs are generated with the one-vs-all (OVA) scheme and dynamically ordered with $na{\ddot{i}}ve$ Bayes classifiers. More specifically, it uses representative fingerprint features such as the FingerCode, singularities and pseudo ridges to train the OVA SVMs and $na{\ddot{i}}ve$ Bayes classifiers. The proposed method has been validated on the NIST-4 database and produced a classification accuracy of 90.8% for 5-class classification. Especially, it has effectively managed tie problems usually occurred in applying OVA SVMs to multi-class classification.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.147-153
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• 2017

The mortality rate in industrial accidents in South Korea was 11 per 100,000 workers in 2015. It's five times higher than the OECD average. Economic losses due to industrial accidents continue to grow, reaching 19 trillion won much more than natural disaster losses equivalent to 1.1 trillion won. It requires fundamental changes according to industrial safety management. In this study, We classified the risk of accidents in industrial complex of Ulju-gun using spatial analytics and data mining. We collected 119 data on accident data, factory characteristics data, company information such as sales amount, capital stock, building information, weather information, official land price, etc. Through the pre-processing and data convergence process, the analysis dataset was constructed. Then we conducted geographically weighted regression with spatial factors affecting fire incidents and calculated the risk of fire accidents with analytical model for combining Boosting and CART (Classification and Regression Tree). We drew the main factors that affect the fire accident. The drawn main factors are deterioration of buildings, capital stock, employee number, officially assessed land price and height of building. Finally the predicted accident rates were divided into four class (risk category-alert, hazard, caution, and attention) with Jenks Natural Breaks Classification. It is divided by seeking to minimize each class's average deviation from the class mean, while maximizing each class's deviation from the means of the other groups. As the analysis results were also visualized on maps, the danger zone can be intuitively checked. It is judged to be available in different policy decisions for different types, such as those used by different types of risk ratings.

• Progress in Medical Physics
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• v.23 no.4
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• pp.303-308
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• 2012

The Geant4 based Monte Carlo code for the application of stereotactic radiosurgery was developed. The probability density function and cumulative density function to determine the incident photon energy were calculated from pre-calculated energy spectrum for the linac by multiplying the weighting factors corresponding to the energy bins. The messenger class to transfer the various MLC fields generated by the planning system was used. The rotation matrix of rotateX and rotateY were used for simulating gantry and table rotation respectively. We construct accelerator world and phantom world in the main world coordinate to rotate accelerator and phantom world independently. We used dicomHandler class object to convert from the dicom binary file to the text file which contains the matrix number, pixel size, pixel's HU, bit size, padding value and high bits order. We reconstruct this class object to work fine. We also reconstruct the PrimaryGeneratorAction class to speed up the calculation time. because of the huge calculation time we discard search process of the ThitsMap and used direct access method from the first to the last element to produce the result files.