• YAKHAK HOEJI
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• v.58 no.5
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• pp.287-293
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• 2014

Alzheimer's disease (AD), most common form of dementia is characterized that memory deficit and loss of cognitive function. This study was evaluated cognitive enhancing effect of water and ethanol extracts of Codonopsis lanceolata and compared using Morris water maze and passive avoidance test. The water and 70% ethanol extracts (100, 300 and 500 mg/kg) were administered to mice. The neuroprotective effect on glutamate-induced cell death in HT22 cells was additionally investigated using MTT assay. Results showed 70% ethanol extract of Codonopsis lanceolata enhanced cognitive function than water extract, as shown by decrease in escape latency time in Morris water maze test. In passive avoidance test, 70% ethanol extract also increased the latency time compared to the water extract. Furthermore, 70% ethanol extract significantly protected neuronal cell against glutamate cytotoxicity and showed higher than neuroprotective effect of water extract. These results indicate that 70% ethanol extract more improve spatial cognitive ability and protected neuronal cells than water extract.

• Journal of the Korean Society of Earth Science Education
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• v.8 no.3
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• pp.332-345
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• 2015

Earth science is the study to explore the planet in which we live. Among these earth science geology of the area it can be the most critical and important study. However, because of the size and scope is too broad temporal spatial eurona covered in geology is true that many students find difficult about the geology field. In this study, in conjunction with landscape formation of geologic time for the concept to be among the core areas of Geology examined the concept and recognize it as the destination for high school students. Is a test tool for the analysis was adapted for use by Jolley (2010) has developed LIFT (The Landscape Identification and Formation Test). Currently we fix the strip to match the country through a validity check of the curriculum. Results of the study were as follows: First, the ability to check the landscape and formation is expected to estimate the time and the liberal arts students was higher than the natural science students. The reason for this seems to be the influence of learning geographical subjects. Second, the concept of geological time was found to lack both natural science and liberal arts students. The reason is that the students in the previous process because it deals with the concept of geologic time from the top of Earth Science Education II seems to be because there was no chance of learning about geological time. Third, the results confirm the confidence of the students surveyed in the landscape formation time natural science students was higher than liberal arts students. The research measured gender boys higher than girls. Fourth, the students on the landscape and geological time was found to have a number of misconceptions. This appears to be due to the students to feel difficulty in thinking of the concept because the need to understand the abstract geologic time. Therefore, it is necessary just to hold misconceptions about the concept of geology students have through the study of the landscape and geological time.

• Journal of the Korean Geographical Society
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• v.32 no.1
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• pp.113-124
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• 1997

The purpose of this article is to analyze some problems of the present curriculum of social studies education and develop a newer hierarchical curriculum system for the 7th Curriculum Reformation in the primary and secondary school of Korea. Most of the major problems of social studies education come from the mixture of different subject matters without reasonable education logic. Most of teachers feel some difficulties in teaching the social studies for the lack of other subject knowledges. For the better teaching, it is needed to control the integrating level according to the learner's intellectual ability from the elementary school to high school. So, it is necessary to enhance students' thinking skills by their own ability of restructuring knowledges from all subject matters in more advanced curriculum. Also, it is required to develop a new hierarchical system of curriculum concerning the geographical view of the world. Students can have many kinds of geographical view points if teachers can well organize learning activities logically for the students to enhance their understanding of geography by adjusting scale of regional unit, geographical theme, and resolution level of interpretation. And then, in the elementary school curriculum, the students are required to understand the spatial variation of places, and various environments in the world, scale. In the junior high school, students have to understand the relationship between man and nature in the context of large scale environments. The high school curriculum needs to be focused on the student's understanding of the spatial contexts of places by theoretical application in the smaller scale region different from elementary and junior high school curriculums.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.4
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• pp.825-840
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• 2015

Adaptive bitrate (ABR) streaming technology has become an important and prevalent feature in many multimedia delivery systems, with content providers such as Netflix and Amazon using ABR streaming to increase bandwidth efficiency and provide the maximum user experience when channel conditions are not ideal. Where such systems could see improvement is in the delivery of live video with a closed loop cognitive control of video encoding. In this paper, we present streaming camera system which provides spatially and temporally adaptive video streams, learning the user's preferences in order to make intelligent scaling decisions. The system employs a hardware based H.264/AVC encoder for video compression. The encoding parameters can be configured by the user or by the cognitive system on behalf of the user when the bandwidth changes. A cognitive video client developed in this study learns the user's preferences(i.e. video size over frame rate) over time and intelligently adapts encoding parameters when the channel conditions change. It has been demonstrated that the cognitive decision system developed has the ability to control video bandwidth by altering the spatial and temporal resolution, as well as the ability to make scaling decisions.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.469-481
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• 2018

DL (Deep Learning) is getting popular in various fields to implement artificial intelligence that resembles human learning and cognition. DL based on complicate structure of the ANN (Artificial Neural Network) requires computing power and computation cost. Variety of DL models with improved performance have been developed with powerful computer specification. The main purpose of this paper is to detect buildings from aerial images and evaluate performance of Mask R-CNN (Region-based Convolutional Neural Network) developed by FAIR (Facebook AI Research) team recently. Mask R-CNN is a R-CNN that is evaluated to be one of the best ANN models in terms of performance for semantic segmentation with pixel-level accuracy. The performance of the DL models is determined by training ability as well as architecture of the ANN. In this paper, we characteristics of the Mask R-CNN with various types of the images and evaluate possibility of the generalization which is the ultimate goal of the DL. As for future study, it is expected that reliability and generalization of DL will be improved by using a variety of spatial information data for training of the DL models.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.77-82
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• 2023

The Ministry of Agriculture, Food and Rural Affairs established the FarmMap, an digital map of agricultural land. In this study, using deep learning, we suggest the application of farm map reading to farmland such as paddy fields, fields, ginseng, fruit trees, facilities, and uncultivated land. The farm map is used as spatial information for planting status and drone operation by digitizing agricultural land in the real world using aerial and satellite images. A reading manual has been prepared and updated every year by demarcating the boundaries of agricultural land and reading the attributes. Human reading of agricultural land differs depending on reading ability and experience, and reading errors are difficult to verify in reality because of budget limitations. The farmmap has location information and class information of the corresponding object in the image of 5 types of farmland properties, so the suitable AI technique was tested with ResNet50, an instance segmentation model. The results of attribute reading of agricultural land using deep learning and attribute reading by humans were compared. If technology is developed by focusing on attribute reading that shows different results in the future, it is expected that it will play a big role in reducing attribute errors and improving the accuracy of digital map of agricultural land.

• Journal of the Korean Society for information Management
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• v.33 no.2
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• pp.227-256
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• 2016

This study was carried out for the university library to find out a strategy to stand tall as an institution to lead the university, by reflecting the university environment having with drastic environmental changes and reflecting the evolution of information technology. As a result, first, university librarians responded that big issues related to the university library is the University Library Promotion Act, University Library evaluation and assessment indicators, the value of university libraries at the university, and changing spatial composition and functions of the university library. Second, university librarians responded that changes of the university environment, government policy on universities, various national projects, and various university reform policy significantly affect to the university library. Third, about what you think would be helpful to the crisis in their universities as changing role of the library, they responded that they can contribute in terms of improving students' information and technology literacy, improving students' reading skills, improving research capacity, and improve students' learning ability. Fourth, they responded that services that users demand the highest in the university library will be expansion of e-books and information resource.

• Applied Microscopy
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• v.51
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• pp.4.1-4.12
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• 2021

Fluorescence in situ hybridization (FISH) is a technique to visualize specific DNA/RNA sequences within the cell nuclei and provide the presence, location and structural integrity of genes on chromosomes. A confocal Whole Slide Imaging (WSI) scanner technology has superior depth resolution compared to wide-field fluorescence imaging. Confocal WSI has the ability to perform serial optical sections with specimen imaging, which is critical for 3D tissue reconstruction for volumetric spatial analysis. The standard clinical manual scoring for FISH is labor-intensive, time-consuming and subjective. Application of multi-gene FISH analysis alongside 3D imaging, significantly increase the level of complexity required for an accurate 3D analysis. Therefore, the purpose of this study is to establish automated 3D FISH scoring for z-stack images from confocal WSI scanner. The algorithm and the application we developed, SHIMARIS PAFQ, successfully employs 3D calculations for clear individual cell nuclei segmentation, gene signals detection and distribution of break-apart probes signal patterns, including standard break-apart, and variant patterns due to truncation, and deletion, etc. The analysis was accurate and precise when compared with ground truth clinical manual counting and scoring reported in ten lymphoma and solid tumors cases. The algorithm and the application we developed, SHIMARIS PAFQ, is objective and more efficient than the conventional procedure. It enables the automated counting of more nuclei, precisely detecting additional abnormal signal variations in nuclei patterns and analyzes gigabyte multi-layer stacking imaging data of tissue samples from patients. Currently, we are developing a deep learning algorithm for automated tumor area detection to be integrated with SHIMARIS PAFQ.

• Journal of Science Education
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• v.33 no.2
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• pp.193-206
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• 2009

The purpose of this study was to examine the effect of the consistent presentation of illustrations about the aligning direction of the Axis on the middle school students' acquisition and retention of astronomical concepts. This study was taken using the nonequivalent control-group pretest-posttest design on 116 7th middle school subjects. The same teaching and learning activities were given to both the experimental (n=59) and control groups (n=57) through three lessons. The experimental group was given a consistent presentation of the illustrations about the aligning direction of the Axis, while the control group was given an inconsistent presentation of the same illustrations about aligning direction. Two days after the three lessons, the 1st posttest was administered to compare the statistical difference of mean of both groups, using ANCOVA test. The result of ANCOVA test implicated that the consistent presentation of the illustrations about the aligning direction of the Axis had a positive influence on the experimental group's acquisition of the concepts. The 2nd posttest result for retention effect was given two month later by one-paired t-Test in each group and showed that the method had a positive effect on the experimental group, compared with control group. The results of this study implicated that paying careful attention to using the consistent illustration is highly beneficial for students' meaningful learning on astronomical concepts.

• Nutrition Research and Practice
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• v.12 no.3
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• pp.191-198
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• 2018

BACKGROUD/OBJECTIVES: Neuroinflammation plays critical role in neurodegenerative disorders, such as Alzheimer's disease (AD). We investigated the effect of three licorice varieties, Glycyrhiza uralensis, G. glabra, and Shinwongam (SW) on a mouse model of inflammation-induced memory and cognitive deficit. MATERIALS/METHODS: C57BL/6 mice were injected with lipopolysaccharide (LPS; 2.5 mg/kg, intraperitoneally) and orally administrated G. uralensis, G. glabra, and SW extract (150 mg/kg/day). SW, a new species of licorice in Korea, was combined with G. uralensis and G. glabra. Behavioral tests, including the T-maze, novel object recognition and Morris water maze, were carried out to assess learning and memory. In addition, the expressions of inflammation-related proteins in brain tissue were measured by western blotting. RESULTS: There was a significant decrease in spatial and objective recognition memory in LPS-induced cognitive impairment group, as measured by the T-maze and novel object recognition test; however, the administration of licorice ameliorated these deficits. In addition, licorice-treated groups exhibited improved learning and memory ability in the Morris water maze. Furthermore, LPS-injected mice had up-regulated pro-inflammatory proteins, such as inducible nitric oxide synthase (iNOS), cyclooxygenase-2, interleukin-6, via activation of toll like receptor 4 (TLR4) and nuclear factor-kappa B ($NF{\kappa}B$) pathways in the brain. However, these were attenuated by following administration of the three licorice varieties. Interestingly, the SW-administered group showed greater inhibition of iNOS and TLR4 when compared with the other licorice varieties. Furthermore, there was a significant increase in the expression of brain-derived neurotrophic factor (BDNF) in the brain of LPS-induced cognitively impaired mice that were administered licorice, with the greatest effect following SW treatment. CONCLUSIONS: The three licorice varieties ameliorated the inflammation-induced cognitive dysfunction by down-regulating inflammatory proteins and up-regulating BDNF. These results suggest that licorice, in particular SW, could be potential therapeutic agents against cognitive impairment.