• Journal of Radiation Industry
• /
• v.5 no.1
• /
• pp.47-54
• /
• 2011

In this study, we investigated to evaluate differential expression of genes encoding lipid transfer proteins (LTP) by acute and chronic gamma irradiation in rice. After acute and chronic gamma irradiation by 100 Gy and 400 Gy to rice plant, necrotic lesion was observed in the leaf blade and anthocyanin contents were increased. We isolated a total of 21 rice lipid transfer protein (LTP) genes in the TIGR database, and these genes were divided into four different groups on the basis of nucleotide sequences. The LTP genes also were classified as different four classes according to expression pattern using RT-PCR. Group A, B contained genes with increased expression and decreased expression in acute and chronic, respectively. Group C contained genes with contrasted expression pattern. Group D wasn't a regular pattern. But the specific affinity was not obtained between two grouping.

• Journal of The Korean Association of Information Education
• /
• v.24 no.6
• /
• pp.551-562
• /
• 2020

The purpose of this study is to investigate the effects of Data Science Education classes using PBL-based App Inventor on elementary student Computational Thinking and Creativity. Based on the results of the pre-requisite analysis by Rossett's demand analysis model, PBL-based Data Science Education class was designed according to the procedure of ADDIE model which is 42 hours of classroom instruction for elementary student. As a result of the Paired t-test, it was proved that the Computational Thinking was statistically significantly improved in the post-test. In addition, as a result of the Paired t-test and Wilcoxon's signed rank test, it was found that the sub-factors of Creativity were 'Originality', 'Fluency', 'Closure', 'Average', and 'Index'. Therefore, it was confirmed that the PBL-based Data Science Education class using App Inventor is effective in improving Computational Thinking and Creativity of elementary student.

• Journal of the Korea Institute of Building Construction
• /
• v.22 no.5
• /
• pp.451-462
• /
• 2022

The objective of the study is to establish a BIM modeling of precast concrete(PC) shear wall with various wall-to-base connections. The family library of PC shear wall was established in BIM program using component function in a IFC(Industry foundation classes) file format and SketchUp program. From the BIM program, the amounts of concrete, reinforcing bars and steel materials as well as the interference of arranged reinforcing bars can be accurately evaluated in the PC shear walls with spliced sleeves, bolt, or welding plate connection methods. Although the additional metallic materials such as steel plates, bolts, and nuts were used in the PC shear walls with welding plate connection method, their amounts of materials, economic efficiency, and environmental impact were similar to those with spliced sleeve connection. Consequently, the bolt or welding connection is a highly applicable method as wall-to-base connection of PC shear walls, and it was a more useful method than spliced sleeve method, particularly considering the constructability.

• International Journal of Computer Science & Network Security
• /
• v.22 no.9
• /
• pp.334-342
• /
• 2022

Nowadays, as we can notice on social media, most users choose to use more than one language in their online postings. Thus, social media analytics needs reviewing as code-switching analytics instead of traditional analytics. This paper aims to present evidence comparable to the accuracy of code-switching analytics techniques in analysing the mood state of social media users. We conducted a systematic literature review (SLR) to study the social media analytics that examined the effectiveness of code-switching analytics techniques. One primary question and three sub-questions have been raised for this purpose. The study investigates the computational models used to detect and measures emotional well-being. The study primarily focuses on online postings text, including the extended text analysis, analysing and predicting using past experiences, and classifying the mood upon analysis. We used thirty-two (32) papers for our evidence synthesis and identified four main task classifications that can be used potentially in code-switching analytics. The tasks include determining analytics algorithms, classification techniques, mood classes, and analytics flow. Results showed that CNN-BiLSTM was the machine learning algorithm that affected code-switching analytics accuracy the most with 83.21%. In addition, the analytics accuracy when using the code-mixing emotion corpus could enhance by about 20% compared to when performing with one language. Our meta-analyses showed that code-mixing emotion corpus was effective in improving the mood analytics accuracy level. This SLR result has pointed to two apparent gaps in the research field: i) lack of studies that focus on Malay-English code-mixing analytics and ii) lack of studies investigating various mood classes via the code-mixing approach.

• Journal of Information Science Theory and Practice
• /
• v.12 no.2
• /
• pp.22-35
• /
• 2024

There has been a growing interest in halal-related ontology research in recent years, as ontology has gained recognition in the halal industry. This paper discusses the development of a flavouring ontology that will assist halal management auditors in predicting the halal status of flavours in order to process food producers' applications for halal certification. The development of a flavouring ontology is based on multiple references, because the auditors of halal management divisions must consult a variety of sources independently in order to determine the halal status of flavourings. The process includes 1) determining the ontology goal and scope, 2) building ontologies, and 3) evaluating the ontologies. The researcher used Protégé to design the ontologies, and Phyton was used to develop a prototype based on flavouring ontology. The developed ontology consists of four classes, nine sub-classes, and 11 relationships. The evaluation of the ontology using the prototype revealed that the majority of experts were satisfied with the information generated by the ontology in the prototype, particularly in relation to synonyms and the hierarchical structure of a flavour. However, the experts suggest improvements in terms of flavour metadata, especially on raw materials and natural occurrence data, so that the flavour information retrieved is comprehensive and accurate.

• Journal of the Korean Chemical Society
• /
• v.54 no.6
• /
• pp.771-780
• /
• 2010

The purpose of this study is to examine the effects of PBL (Problem-based Learning) strategy applied to the "Inorganic Chemistry Laboratory" class. Especially, the changes in 'self-directed learning ability' and 'attitudes toward science' of undergraduate students were examined. In addition, perception on PBL problem and the PBL classes were investigated. The results of this study were as follows: First, after the course, 'self-directed learning ability' and 'attitude toward science' of students were significantly improved (p < .05). There were significant improvements in every sub-categories except 'self-confidence as a learner' for 'self directed learning ability' and every sub-categories except 'usefulness of science' for 'attitude toward science'. Second, the students expressed that PBL strategy provided opportunities to learn self-directively and responsibly, but the process of defining the problem was difficult. Finally on the survey toward PBL strategy, the students responded that PBL problems were authentic and helpful to learn problem solving ability. In conclusion, PBL laboratory course is effective for developing self-directed learning ability and positive attitude toward science.

• Korean Journal of Childcare and Education
• /
• v.10 no.2
• /
• pp.21-41
• /
• 2014

The purpose of his study was to explore the effect of crossover musical activities applying the traditional Korean Jang-dan on the multicultural perception of young children. The subjects of this study were one class of 21 5-year-old children(experimental group) in J kindergarten and two classes of 5-year-old children (20 children in comparative group and 20 children in control group) in S kindergarten located in Y city, totaling 61 children (31 male children and 30 female children). Twenty sessions of Crossover musical activities applying the traditional Korean Jang-dan (rhythmic patterns) developed by the author were applied to the experimental group, musical activities focusing on traditional Korean music to the comparative group and musical classes from Nuri curriculum for 5-year-olds to the control group, respectively. The result of this study showed the following, among the sub-factors of multi-cultural perception, the scores of post-cultural openness and post-cultural acceptability showed a significantly higher level in statistical terms in the experimental group, for which crossover musical activities applying the traditional Korean Jang-dan were conducted, than those in the comparative group and the control group. The comparative group which participated in musical activities of traditional Korean music exhibited a significantly higher level of post-cultural respectfulness statistically (than other groups). The result of this study implies that crossover musical activities applying the traditional Korean Jang-dan have the effect of enhancing the perception of cultural openness and cultural acceptability which are the sub-factors of young children's multi-cultural perception.

• Korean Journal of Remote Sensing
• /
• v.22 no.6
• /
• pp.553-563
• /
• 2006

This study aims to produce land-cover maps of Korean peninsula using multi-temporal MODIS (Moderate Resolution Imaging Spectroradiometer) imagery. To solve the low spatial resolution of MODIS data and enhance classification accuracy, Linear Spectral Mixture Analysis (LSMA) was employed. LSMA allowed to determine the fraction of each surface type in a pixel and develop vegetation, soil and water fraction images. To eliminate clouds, MVC (Maximum Value Composite) was utilized for vegetation fraction and MinVC (Minimum Value Composite) for soil fraction image respectively. With these images, using ISODATA unsupervised classifier, southern part of Korean peninsula was classified to low and mid level land-cover classes. The results showed that vegetation and soil fraction images reflected phenological characteristics of Korean peninsula. Paddy fields and forest could be easily detected in spring and summer data of the entire peninsula and arable land in North Korea. Secondly, in low level land-cover classification, overall accuracy was 79.94% and Kappa value was 0.70. Classification accuracy of forest (88.12%) and paddy field (85.45%) was higher than that of barren land (60.71%) and grassland (57.14%). In midlevel classification, forest class was sub-divided into deciduous and conifers and field class was sub-divided into paddy and field classes. In mid level, overall accuracy was 82.02% and Kappa value was 0.6986. Classification accuracy of deciduous (86.96%) and paddy (85.38%) were higher than that of conifers (62.50%) and field (77.08%).

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.8
• /
• pp.49-59
• /
• 2022

In this paper, we designed a new enzyme function prediction model PSCREM based on a study that compared and evaluated CNN and LSTM/GRU models, which are the most widely used deep learning models in the field of predicting functions and structures using protein sequences in 2020, under the same conditions. Sequence evolution information was used to preserve detailed patterns which would miss in CNN convolution, and the relationship information between amino acids with functional significance was extracted through overlapping RNNs. It was referenced to feature map production. The RNN family of algorithms used in small CNN-RNN models are LSTM algorithms and GRU algorithms, which are usually stacked two to three times over 100 units, but in this paper, small RNNs consisting of 10 and 20 units are overlapped. The model used the PSSM profile, which is transformed from protein sequence data. The experiment proved 86.4% the performance for the problem of predicting the main classes of enzyme number, and it was confirmed that the performance was 84.4% accurate up to the sub-sub classes of enzyme number. Thus, PSCREM better identifies unique patterns related to protein function through overlapped RNN, and Overlapped RNN is proposed as a novel methodology for protein function and structure prediction extraction.

• Journal of Korean Elementary Science Education
• /
• v.43 no.3
• /
• pp.365-384
• /
• 2024

The purpose of this study was to determine the effect of grit on the resilience of elementary science gifted and general students in their daily lives, and to identify the differences between science gifted students in university gifted centers and elementary school gifted classes and normal students. The grit and resilience test was administered to 154 scientifically gifted students and 98 non-gifted students. Based on the collected data, descriptive statistical analysis, measurement model analysis, and multigroup structural model analysis were conducted. The results of the study were as follows: First, across all sub-factors of grit and resilience, the gifted students showed significantly higher levels of resilience than non-gifted students. Second, the path from making perseverance of effort in grit to resilience showed a positive effect, while the path from consistency of interest in grit to resilience showed a negative effect. Third, in all groups, including regular classes, the school for gifted, and the university-affiliated gifted students, the perseverance of effort in grit exhibited a positive effect on resilience, and the consistency of interest in grit showed a negative effect on interpersonal relationship skills in resilience for both the non-gifted and the gifted students. Lastly, gifted students showed a significant difference in the path from perseverance of effort in grit to the sub-factors of resilience, whereas non-gifted students did not.