• The Korean Journal of Applied Statistics
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• v.14 no.1
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• pp.59-70
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• 2001

이면교배 실험은 식물이나 동물의 교배를 통해 자식계통의 유전적인 성질을 조사하는데 중용한 역할을 한다. 이면교배에 관한 기존의 연구에서는 p개의 자식계통은 하나의 집합에 속하는 것으로 간주하였다. 이와 달리 새로 육성된 자식계통의 유전적 성질을 평가하고자 하는 경우에는, p개의 자식계통이 각각 p$_1$과 p$_2$개의 자식계통을 갖는 두 개의 집합으로 분리되는 형태의 교배실험을 사용한다(단, p=p$_1$+p$_2$). 이에 본 연구에서는 자식계통이 두 집단으로 분리된 경우에 대해서 Kempthorne의 합동식을 이용하여 두 군간 교배에 대한 블록디자인을 설계하고, 이에 대한 평균효율인자를 계산하는 방법을 제안하고자 한다.

• Journal of the Korean Mathematical Society
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• v.60 no.1
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• pp.91-113
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• 2023

The polytope of tristochastic tensors of degree three, the Latin polytope, has two kinds of extreme points. Those that are at a maximum distance from the barycenter of the polytope correspond to Latin squares. The remaining extreme points are said to be short. The aim of the paper is to determine the geometry of these short extreme points, as they relate to the Latin squares. The paper adapts the Latin square notion of an intercalate to yield the new concept of a cross-intercalate between two Latin squares. Cross-intercalates of pairs of orthogonal Latin squares of degree three are used to produce the short extreme points of the degree three Latin polytope. The pairs of orthogonal Latin squares fall into two classes, described as parallel and reversed, each forming an orbit under the isotopy group. In the inverse direction, we show that each short extreme point of the Latin polytope determines four pairs of orthogonal Latin squares, two parallel and two reversed.

• Language and Information
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• v.14 no.1
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• pp.165-196
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• 2010

The primary goal of this paper is to propose methods of enriching two heterogeneous ontologies: Sejong Semantic Classes (SJSC) and KorLexNoun 1.5 (KLN). In order to achieve this goal, this study introduces the pros and cons of two ontologies, and analyzes the error patterns found during the fine-grained manual mapping processes between them. Error patterns can be classified into four types: (1) structural defectives involved in node branching, (2) errors in assigning the semantic classes, (3) deficiency in providing linguistic information, and (4) lack of the lexical units representing specific concepts. According to these error patterns, we propose different solutions in order to correct the node branching defectives and the semantic class assignment, to complement the deficiency of linguistic information, and to increase the number of lexical units suitably allotted to their corresponding concepts. Using the results of this study, we can obtain more enriched ontologies by correcting the defects and errors in each ontology, which will lead to the enhancement of practicality for syntactic and semantic analysis.

• The Korean Journal of Applied Statistics
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• v.24 no.5
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• pp.847-859
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• 2011

cDNA microarray-based comparative genomic hybridization(CGH) data includes low-intensity spots and thus a statistical strategy is needed to detect subtle differences between different cancer classes. In this study, genes displaying a high frequency of alteration in one of the different classes were selected among the pre-selected genes that show relatively large variations between genes compared to total variations. Utilizing copy-number changes of the selected genes, this study suggests a statistical approach to predict patients' classes with increased performance by pre-classifying patients with similar genetic alteration scores. Two-stage logistic regression model(TLRM) was suggested to pre-classify homogeneous patients and predict patients' classes for cancer prediction; a decision tree(DT) was combined with logistic regression on the set of informative genes. TLRM was constructed in cDNA microarray-based CGH data from the Cancer Metastasis Research Center(CMRC) at Yonsei University; it predicted the patients' clinical diagnoses with perfect matches (except for one patient among the high-risk and low-risk classified patients where the performance of predictions is critical due to the high sensitivity and specificity requirements for clinical treatments. Accuracy validated by leave-one-out cross-validation(LOOCV) was 83.3% while other classification methods of CART and DT performed as comparisons showed worse performances than TLRM.

• Journal of Korean Physical Therapy Science
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• v.31 no.2
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• pp.90-104
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• 2024

Background: Hybrid learning is an educational approach that combines the teaching methods of online and lecture-style classes to compensate for each method's strengths and weaknesses. Compared to lecture-style classes, flipped learning improves overall class satisfaction and self-directed learning but is associated with lower learning motivation. It is necessary to determine whether hybrid flipped learning can solve the learning motivation problem of flipped learning by incorporating flipped learning into hybrid learning. The purpose of this study is to compare the effects of hybrid flipped learning and flipped learning on students' learning ability. Design: Cross-sectional study Methods: For students in the Department of Physical Therapy, classes were conducted using both flipped learning and hybrid flipped learning. In both learning methods, students took online classes first and participated in them every week. Flipped learning classes was conducted offline at school every week, while hybrid flipped learning alternated between live classes on YouTube and offline classes at school every other week. Results: Hybrid flipped learning resulted in significantly lower learning satisfaction and course evaluation than flipped learning, with no significant difference in grades. Conclusion: Hybrid flipped learning was able to cope with the situation well with the non-face-to-face teaching method caused by COVID-19, but it was difficult to improve learning ability because there were restrictions on activities that could interact with students. Flipped learning is a smooth offline activity that enables two-way activities between professors and students to improve learning ability, but the effect of improving test scores is still unclear.

• Education of Primary School Mathematics
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• v.4 no.2
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• pp.111-125
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• 2000

This paper presents cross-national perspectives on challenges in implementing current mathematics education reform ideals. This paper includes detailed qualitative descriptions of mathematics instruction from unevenly successful second-grade classrooms both in Koran and in the U. S with regared to reform recommendations. Despits dramatic differences in mathematics achivement between Korean and the U.S student. problems in both countries with regard to mathematics education are perceived to be very similar. The shared problems have a common origin in teacher-centered instruction. Educational leaders in both countries have persistently attempted to change the teacher-centered pedagogy to a student-centered approach. Many teachers report familiarity with and adherence to reform ideas, but their actual classroom teaching practices do not reflect the full implications of the reform ideals. Given the challenges in implementing reform, this study explored the breakdown that may occur between teachers adoption of reform objectives and their successful incorporation of reform ideals by comparing and contrasting two reform-oriented classrooms in both countries. This comparison and contrast provided a unique opportunity to reflect on possible subtle but crucial issues with regard to reform implementation. Thus, this study departed from past international comparisons in which the common objective has been to compare general social norma of typical mathematics classes across countries. This study was and exploratory, qualitative, comparative case study using grounded theory methodology based on constant comparative analysis for which the primary data sources were classroom video recordings and transcripts. The Korean portion of this study was conducted by the team of four researchers, including the author. The U.S portion of this study and a brief joint analysis were conducted by the author. This study compared and contrasted the classroom general social norms and sociomathematical norms of two Korean and two U.S second-grade teachers who aspired to implement reform. The two classrooms in each country were chosen because of their unequal success in activating the reform recommendation. Four mathematics lessons were videotaped from Korean classes, whereas fourteen lessons were videotaped from the U.S. classes. Intensive interviews were conducted with each teacher. The two classes within each country established similar participation patterns but very different sociomathematical norms. In both classes open-ended questioning, collaborative group work, and students own problem solving constituted the primary modes of classroom participation. However in one class mathematical significance was constituted as using standard algorithm with accuracy, whereas the other established a focus on providing reasonable and convincing arguments. Given these different mathematical foci, the students in the latter class had more opportunities to develop conceptual understanding than their counterparts. The similarities and differences to between the two teaching practices within each country clearly show that students learning opportunities do not arise social norms of a classroom community. Instead, they are closely related to its sociomathematical norms. Thus this study suggests that reform efforts highlight the importance of sociomathematical norms that established in the classroom microculture. This study also provides a more caution for the Korean reform movement than for its U.S. counterpart.

• The KIPS Transactions:PartB
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• v.13B no.5 s.108
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• pp.547-552
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• 2006

There have been various cohesion measurements studied considering reference relation among attributes and methods in a class. Generally, these cohesion measurement are camed out in one class. If the range of reference relation considered are extended from one class to two classes, we could find out the reference relation between two classes. Tn this paper, we proposed a neural network to determine the method location. Neural network is effective to predict output value from input data not to be included in training and generalize after training input and output pattern repeatedly. Learning vector is generated with 30-dimensional input vector and one target binary values of method location in a constraint that there are two classes which have less than or equal to 5 attributes and methods The result of the proposed neural network is about 95% in cross-validation and 88% in testing.

• Proceedings of the Korean Society for Cognitive Science Conference
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• 2005.05a
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• pp.163-167
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• 2005

Current theories of cross-language speech perception claim that patterns of perceptual assimilation of non-native segments to native categories predict relative difficulties in learning to perceive (and produce) non-native phones. Perceptual assimilation patterns by Japanese listeners of the three-way voicing distinction in Korean syllable-initial obstruent consonants were assessed directly. According to Speech Learning Model (SLM) and Perceptual Assimilation Model (PAM), the resulting perceptual assimilation pattern predicts relative difficulty in discrimination between lenis and aspirated consonants, and relative ease in the discrimination of fortis. This study compared the effects of two different training conditions on Japanese adults’perceptual categorization of Korean three-way distinction. In one condition, participants were trained to discriminate lenis and aspirated consonants which were predicted to be problematic, whereas in another condition participants were trained with all three classes of 'learnability' did not seem to depend lawfully on the perceived cross-language similarity of Korean and Japanese consonants.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.49-54
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• 2024

Data imbalance is a common issue encountered in classification problems, stemming from a significant disparity in the number of samples between classes within the dataset. Such data imbalance typically leads to problems in classification models, including overfitting, underfitting, and misinterpretation of performance metrics. Methods to address this issue include resampling, augmentation, regularization techniques, and adjustment of loss functions. In this paper, we focus on loss function adjustment, particularly comparing the performance of various configurations of loss functions (Cross Entropy, Balanced Cross Entropy, two settings of Focal Loss: 𝛼 = 1 and 𝛼 = Balanced, Asymmetric Loss) on Multi-Class black-box video data with imbalance issues. The comparison is conducted using the I3D, and R3D_18 models.

• Applied Biological Chemistry
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• v.32 no.1
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• pp.64-72
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• 1989

Near full length cDNA clones encoding the rice seed storage protein, prolamine, were isolated and divided into two homology classes based on cross-hybridization and DNA sequencing analysis. These cDNA clones contain a single open reading frame encoding a putative rice prolamine precursor(M.W.=17,200) possessing atypical 14 amino acid signal peptide. Clones of these two homology classes diverge mainly by insertions/deletions of short nucleotide stretches and point mutations. The deduced primary structures of both types of prolamine polypeptides are devoid of any major tandem repetitive sequences, a feature prevalent in other cereal prolamines. No significant homology teas detected between the rice prolamine and other cereal prolamines, indicating that the rice gene evolved from a different ancestor that gave rise to other cereal prolamine genes. Developing wheat and rice endosperms were examined using ultrathin sections prepared from tissues harvested at various days after flowering. By immunocytochemical localization techniques, wheat prolamines are localized within vesicles from Golgi apparatus and in homogeneous regions of protein bodies. The involvement of the goli apparatus in the packaging of wheat prolamines into protein bodies indicates a pathway which differs from the mode of other cereal prolamines and resembles the mechanism employed for the storage of rice glutelin and legume globulins.