• Journal of the Korean Society for Library and Information Science
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• v.57 no.2
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• pp.5-30
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• 2023

At public elementary schools in areas where multicultural students are concentrated, they have difficulty understanding classes due to their lack of Korean proficiency. Multicultural teaching and learning materials produced by teachers have not been managed or reused and stored individually. To overcome this situation and increase students' learning effect, the study applied digital curation to multicultural teaching and learning materials and suggested to link the materials with a platform that can be stored, used, and shared. The study was based on B Elementary School in A City, a multicultural international innovation school under the Gyeonggi Provincial Office of Education. The process of applying digital curation to multicultural teaching and learning materials was analyzed by collecting, organizing/selecting teaching and learning materials, categorizing subject, classifying subtopic, and linking with platforms. Practical issues and policy suggestions in school settings were also proposed.

• Journal of the Korean Society for Library and Information Science
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• v.58 no.3
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• pp.65-89
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• 2024

This study developed a model to classify news articles into categories of topic, genre, and region using a Korean Pre-trained Language model. To achieve this, a new news article classification system was designed by referring to the classification systems of domestic media outlets. The topic and genre classification models were implemented as hierarchical classification models that link the main categories and subcategories, and their performance was compared with that of an integrated category model. The evaluation results showed that the hierarchical structure classification model had the advantage of providing more precise categorization in ambiguous or overlapping categories compared to the integrated category model. For regional classification of news articles, a model was built to classify into 18 categories, and for regional news articles, the regional characteristics were clearly reflected in the text, resulting in high performance. This study demonstrated the effectiveness of classifying news articles from multiple perspectives-topic, genre, and region-and emphasized the significance of suggesting the potential for a multi-dimensional news article classification service that meets user needs.

• Journal of Life Science
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• v.15 no.3 s.70
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• pp.415-422
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• 2005

library of the mutants was prepared by transposon mutagenesis of the Mycobacterium bovis BCG. We screened this library for the resistance to an anti-tuberculosis antibiotic, PA-824. Most of the mutants resistant to the PA-824 were not able to synthesize the coenzyme $F_{420}$ which is normally produced by the wild type M. bovis BCG strains. HPLC analysis of the cellular extract showed that one of those mutants which lost the ability to synthesize $F_{420}$ still produced F0. The insertion site of the transposon in this mutant was determined by an inverse PCR and the transposon was found to be inserted in the Rv2435c open reading frame (ORF). Rv2435c ORF is predicted to encode an 80.3 kDa protein. Rv2435c protein appears to be bound to the cytoplasmic membrane, its N-terminal present in the periplasm and C-terminal in the cytoplasm. The C-terminal portion of this protein is highly homologous with the adenylyl cyclases of both prokaryotes and eukaryotes. There are 15 ORFs which have homology with the class III AC proteins in the genome of the M. tuberculosis and M. bovis. Two of those, Rv1625c and Rv2435c, are highly homologous with the mammalian ACs. We cloned the cytoplasmic domain of the Rv2435c ORF and expressed it with six histidine residues attached on its C-terminal in Escherichia coli to find out if this protein is a genuine AC. Production of that protein in E. coli was proved by purifying the histidine-tagged protein by using the Ni-NTA resin. This protein, however, failed to complement the cya mutation in E. coli, indicating that this protein lacks the AC activity. All of the further attempts to convert this protein to a functional AC by a mutagenesis with UV or hydroxylamine, or construction of several different fusion proteins with Rv1625c failed. It is, therefore, possible that Rv2435c protein might affect the conversion of F0 to $F_{420}$ not by synthesizing cAMP but by some other way.

• The Journal of the Korea Contents Association
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• v.6 no.10
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• pp.134-142
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• 2006

In this paper, we investigate a Hausdorff distance, which is used for the measurement of image similarity, to see whether it is also effective for document retrieval. The proposed method uses a local crowdedness and a Hausdorff distance to locate text images by determining whether a pair of images scanned at different time comes from the same text or not. To reduce the processing time, which is one of the disadvantages of a Hausdorff distance algorithm, we adopt a local crowdedness for feature point extraction. We apply the proposed method to 190 pairs of the same class and 190 pairs of the different class collected from postal envelop images. The results show that the modified Hausdorff distance proposed in this paper performed well in locating the tort region and calculating the degree of similarity between two images. An improvement of accuracy by 2.7% and 9.0% has been obtained, compared to a binary correlation method and the original Hausdorff distance method, respectively.

• The Korean Journal of Food And Nutrition
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• v.27 no.4
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• pp.630-640
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• 2014

The purpose of this study was to use the Kano model to compare and analyze the educational service quality attributes of domestic and foreign culinary arts schools. For this purpose, a questionnaire-based survey was completed by 312 students who were studying in domestic and foreign culinary schools. The results of the study indicated that 23 of the total 25 attributes were significantly different between domestic and foreign culinary arts school.; the "minium 4 hour-kitchen class" and "mandatory internship program" were classified into "indifferent quality" for domestic schools and a "must-be quality" for foreign schools; "well-organized internship guidebook", "kitchen class limited to 20 students", "introducing the latest food or restaurant trends", "library with the latest publications related to major", "objective instructor's evaluation", "detailed instructor's evaluation", "instructor's field experience", and "decent communication skills on the part of the instructor" attributes were classified into "attractive quality" for domestic schools and "must-be quality" for foreign schools; and "kitchen classes operated by block system", and "foreign instructors for each ethnic cuisine" attributes were classified into "indifferent" and "attractive quality" for both domestic and foreign schools, respectively. Also, according to the Better and Worse quotient designed by Timko, there were more attributes for domestic school than for foreign school that scored over 0.5 in the Better category and fewer attributes for domestic than the foreign scored over 0.5 in the Worse category. The results also indicate that, students in foreign schools receive an educational service of better quality than students in a domestic school. As a result, this research suggests significant implications to develop culinary educational services.

• Journal of Microbiology and Biotechnology
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• v.21 no.7
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• pp.667-674
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• 2011

The gene for esterase (rEst1) was isolated from a new species of genus Rheinheimera by functional screening of E. coli cells transformed with the pSMART/HaeIII genomic library. E. coli cells harboring the esterase gene insert could grow and produce clear halo zones on tributyrin agar. The rEst1 ORF consisted of 1,029 bp, corresponding to 342 amino acid residues with a molecular mass of 37 kDa. The signal P program 3.0 revealed the presence of a signal peptide of 25 amino acids. Esterase activity, however, was associated with a homotrimeric form of molecular mass 95 kDa and not with the monomeric form. The deduced amino acid sequence showed only 54% sequence identity with the closest lipase from Cellvibrio japonicus strain Ueda 107. Conserved domain search and multiple sequence alignment revealed the presence of an esterase/ lipase conserved domain consisting of a GXSXG motif, HGGG motif (oxyanion hole) and HGF motif, typical of the class IV hormone sensitive lipase family. On the basis of the sequence comparison with known esterases/ lipases, REst1 represents a new esterase belonging to the class IV family. The purified enzyme worked optimally at $50^{\circ}C$ and pH 8, utilized pNP esters of short chain lengths, and showed best catalytic activity with p-nitrophenyl butyrate ($C_4$), indicating that it was an esterase. The enzyme was completely inhibited by PMSF and DEPC and showed moderate organotolerance.

• The KIPS Transactions:PartD
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• v.16D no.1
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• pp.83-92
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• 2009

Complicated business logic makes program complexity more complicated. It's inevitable that the program must undergo reengineering processes all the way of in its lifetime. Hot spot analysis that has diverse purposes is getting an important question more and more. As a rule, reengineering process is done by UML model-based approach to analyze the legacy system. The smallest fragment of targets to be analysed is unit, that is function or class. Today's software development is to deal with huge change of software product and huge class including heavy quantity of LOC(Lines Of Code). However, analysis of unit is not precise approach process for reliable reengineering consequence. In this paper, we propose very precise hot spot analysis approach using Aspect-Oriented Programming languages, such as AspectJ. Typically the consistency between UML and source is needed code to redefine the modified library or framework boundaries. But reengineering approach using AOP doesn't need to analyze UML and source code. This approach makes dynamic event log data that contains detailed program interaction information. This dynamic event log data makes it possible to analyze hot spot.

• The korean journal of orthodontics
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• v.52 no.2
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• pp.112-122
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• 2022

Objective: This study aimed to present and evaluate a new deep learning model for determining cervical vertebral maturation (CVM) degree and growth spurts by analyzing lateral cephalometric radiographs. Methods: The study sample included 890 cephalograms. The images were classified into six cervical stages independently by two orthodontists. The images were also categorized into three degrees on the basis of the growth spurt: pre-pubertal, growth spurt, and post-pubertal. Subsequently, the samples were fed to a transfer learning model implemented using the Python programming language and PyTorch library. In the last step, the test set of cephalograms was randomly coded and provided to two new orthodontists in order to compare their diagnosis to the artificial intelligence (AI) model's performance using weighted kappa and Cohen's kappa statistical analyses. Results: The model's validation and test accuracy for the six-class CVM diagnosis were 62.63% and 61.62%, respectively. Moreover, the model's validation and test accuracy for the three-class classification were 75.76% and 82.83%, respectively. Furthermore, substantial agreements were observed between the two orthodontists as well as one of them and the AI model. Conclusions: The newly developed AI model had reasonable accuracy in detecting the CVM stage and high reliability in detecting the pubertal stage. However, its accuracy was still less than that of human observers. With further improvements in data quality, this model should be able to provide practical assistance to practicing dentists in the future.

• Journal of The Korean Association of Information Education
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• v.6 no.1
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• pp.86-97
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• 2002

Reading education in elementary school is being performed without connection between the curriculums and is searching for a diversified method of reading education. There are other problems in reading education such as absence of several reading education programs lack of experts with field experiences and difficulties in practicing a continuous reading education due to the emotional and disconnection between school and home. We designed a web-based reading education support system as a supplement for the reading education in which an electronic library and information about each reading-related activity can be shared. This reading education support system based on internet can connect reading education to the students everyday life. The electronic library can activate reading education by providing book management, a bulletin about the impression of a book and the information on recommended books. In addition, this electronic library can develop various reading education programs and can strengthen the relationship between school and home. This system also can make knowledge and information related activities after reading books be commonly available to all schools through the realization module, according to school and class. Therefore, various material related to reading education can be shared and statistical works are possible with the system we developed in this study.

• Journal of the Korean Society for information Management
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• v.39 no.1
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• pp.91-117
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• 2022

The number of depressed patients in Korea and around the world is rapidly increasing every year. However, most of the mentally ill patients are not aware that they are suffering from the disease, so adequate treatment is not being performed. If depressive symptoms are neglected, it can lead to suicide, anxiety, and other psychological problems. Therefore, early detection and treatment of depression are very important in improving mental health. To improve this problem, this study presented a deep learning-based depression tendency model using Korean social media text. After collecting data from Naver KonwledgeiN, Naver Blog, Hidoc, and Twitter, DSM-5 major depressive disorder diagnosis criteria were used to classify and annotate classes according to the number of depressive symptoms. Afterwards, TF-IDF analysis and simultaneous word analysis were performed to examine the characteristics of each class of the corpus constructed. In addition, word embedding, dictionary-based sentiment analysis, and LDA topic modeling were performed to generate a depression tendency classification model using various text features. Through this, the embedded text, sentiment score, and topic number for each document were calculated and used as text features. As a result, it was confirmed that the highest accuracy rate of 83.28% was achieved when the depression tendency was classified based on the KorBERT algorithm by combining both the emotional score and the topic of the document with the embedded text. This study establishes a classification model for Korean depression trends with improved performance using various text features, and detects potential depressive patients early among Korean online community users, enabling rapid treatment and prevention, thereby enabling the mental health of Korean society. It is significant in that it can help in promotion.