• Journal of The Korean Association For Science Education
• /
• v.30 no.4
• /
• pp.487-497
• /
• 2010

The purpose of this study was to investigate how a teaching approach influences student's ability of classification at the brain level. Twenty four healthy and right-handed college students participated in this study, which investigated a brain plasticity associated with category-generation and -understanding in classification learning. The participants were divided into one of two groups, one each for category-generation and -understanding learning programs, which were composed of twelve topics taught over a twelve-week period. To measure the change in student competence and brain activations, a paper and pencil test and an fMRI scanning session were administered before and after the training programs. Unlike the understanding group, the generation group showed significant changes in classification ability quotients and learning-related brain activations (cerebral cortex and basal ganglia were increased and prefrontal cortex and parahippocampal gyrus were decreased). Nevertheless, the understanding group showed an increased activation in the cerebral cortex and parahippocampal gyrus and a decreased activation in the right prefrontal cortex and cerebellum. Therefore, it can be concluded that teaching styles could influence students' brain activation patterns and classification ability. The results might also be used to develop a brain-compatible science education curriculum.

• ETRI Journal
• /
• v.29 no.4
• /
• pp.527-529
• /
• 2007

In this paper, a decision-tree-based Markov model for phrase break prediction is proposed. The model takes advantage of the non-homogeneous-features-based classification ability of decision tree and temporal break sequence modeling based on the Markov process. For this experiment, a text corpus tagged with parts-of-speech and three break strength levels is prepared and evaluated. The complex feature set, textual conditions, and prior knowledge are utilized; and chunking rules are applied to the search results. The proposed model shows an error reduction rate of about 11.6% compared to the conventional classification model.

• Journal of Biomedical Engineering Research
• /
• v.5 no.2
• /
• pp.121-126
• /
• 1984

A new approach to texture classification for quantitative ultrasound liver diagnosis using run difference matrix was developed. The run difference matrix comprised the gray level difference along with a distances. From this run difference matrix, we defined several vectors and parameters such as DOD, DGD, DAD vector, SHP, SMO, SMG, LDE, LDEL etc.Each parameter values calculated in fatty, cirrhotic, normal and chronic hepatitic liver images were plotted in a plane and we found that RDM method was more sensitive to small structural changes than the conventional run length method and showed improved classification ability between the diseases.

• The Journal of the Korea Contents Association
• /
• v.9 no.7
• /
• pp.248-256
• /
• 2009

The purpose of this study was to investigate the relationship among functional evaluation systems, the Manual Ability Classification System (MACS), the Gross Motor Function Classification System (GMFCS), and the functional status (WeeFIM) in children with spastic cerebral palsy and to provide the foundation data about MACS for evaluation system of hand function in children with spastic cerebral palsy. For this, sixty children with spastic cerebral palsy were employed in this study. The sixty children were evaluated by using the MACS for their hand function and by using the GMFCS for their motor function. The functional status were assessed by using the Functional Independence Measure of Children (WeeFIM). There were a significant correlation between the MACS and the GMFCS (r =.659, p <.05). The good correlation between the MACS and WeeFIM was found (r = -.576, p <.05). The functional status according to the hand function level evaluated by using the MACS were different significantly (p <.05). The MACS in practice will provide usefulness for assessment of hand function in children with spastic cerebral palsy.

• Journal of the Korean Society of Earth Science Education
• /
• v.3 no.3
• /
• pp.209-218
• /
• 2010

In this study, we investigate the effects of instruction using science magic program on the scientific attitude and scientific inquiry ability in elementary students. For this study, it was chosen two classes of the forth grades J elementary school in Seoul. Instruction using science magic program was applied to the experimental group for 8 weeks during the school hours. The results of this study were as follows : 1. Science tasks applied science magic had influence on elementary learners' scientific attitude in positive way. 2. Science tasks applied science magic had valuable significance to observation, classification, data intepretation ability. However it had no valuable significance to scientific integrated inquiry.

• Proceedings of the KSRS Conference
• /
• 2002.10a
• /
• pp.388-393
• /
• 2002

Remote sensing data is collected and analyzed to enhance understanding of the terrestrial surface. Since Landsat satellite was launched in 1972, many researches using multispectral data has been achieved. Recently, with the availability of airborne and satellite hyperspectral data, the study on hyperspectral data are being increased. It is known that as the number of spectral bands of high-spectral resolution data increases, the ability to detect more detailed cases should also increase, and the classification accuracy should increase as well. In this paper, we classified the hyperspectral and multispectral data and tested the classification accuracy. The MASTER(MODIS/ASTER Airborne Simulator, 50channels, 0.4~13$\mu$m) and Landsat TM(7channels) imagery including Yeong-Gwang area were used and we adjusted the classification items in several cases and tested their classification accuracy through statistical comparison. As a result of this study, it is shown that hyperspectral data offer more information than multispectral data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2016.10a
• /
• pp.798-799
• /
• 2016

Reagent Cabinet of existing that management does not classify the reagents by characteristics it has a problem that can result dangerous situations. Also, the situation impossible the ability to control the reagent cabinet from outside in the event of dangerous situations. In this paper, design a system for managing reagents it can be classified according to the characteristics and the reagent cabinet management on a mobile device. Utilizing the characteristics classification from first to sixth classification management to fit the classification of each reagent. The mobile device transmits the sensor control, reagent and sensor data monitoring, dangerous situation occurs when the alarm message. Accordingly, it is expected through the characteristics classification reduce accidents in the laboratory if the dangerous situation will be a prompt action from the outside.

• Korean Journal of Remote Sensing
• /
• v.40 no.1
• /
• pp.57-69
• /
• 2024

Crop classification plays a vitalrole in monitoring agricultural landscapes and enhancing food production. In this study, we explore the effectiveness of Long Short-Term Memory (LSTM) models for crop classification, focusing on distinguishing between apple and rice crops. The aim wasto overcome the challenges associatedwith finding phenology-based classification thresholds by utilizing LSTM to capture the entire Normalized Difference Vegetation Index (NDVI)trend. Our methodology involvestraining the LSTM model using a reference site and applying it to three separate three test sites. Firstly, we generated 25 NDVI imagesfrom the Sentinel-2A data. Aftersegmenting study areas, we calculated the mean NDVI values for each segment. For the reference area, employed a training approach utilizing the NDVI trend line. This trend line served as the basis for training our crop classification model. Following the training phase, we applied the trained model to three separate test sites. The results demonstrated a high overall accuracy of 0.92 and a kappa coefficient of 0.85 for the reference site. The overall accuracies for the test sites were also favorable, ranging from 0.88 to 0.92, indicating successful classification outcomes. We also found that certain phenological metrics can be less effective in crop classification therefore limitations of relying solely on phenological map thresholds and emphasizes the challenges in detecting phenology in real-time, particularly in the early stages of crops. Our study demonstrates the potential of LSTM models in crop classification tasks, showcasing their ability to capture temporal dependencies and analyze timeseriesremote sensing data.While limitations exist in capturing specific phenological events, the integration of alternative approaches holds promise for enhancing classification accuracy. By leveraging advanced techniques and considering the specific challenges of agricultural landscapes, we can continue to refine crop classification models and support agricultural management practices.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.12 no.12
• /
• pp.5709-5714
• /
• 2011

The purpose of this study was to investigate the utility of function classification system in children with cerebral palsy (CP). For this, relationship among the Manual Ability Classification System (MACS), the Gross Motor Function Classification System (GMFCS), and the functional status (WeeFIM) in children with cerebral palsy form September 2008 to August 2010. The participants was 217 children with CP in this study. The 217 children were evaluated by using the MACS for their hand function and by using the GMFCS for their motor function. The functional status were assessed by using the Functional Independence Measure of Children (WeeFIM). The GMFCS have a significant correlation with total score and domains of WeeFIM (p<.05) There were a significant correlation with total score and domains of WeeFIM (p<.05) except no significancy with communication domain in dyskinesia type. The highest number of participants were in level 1 (20.3) and level 5 (40.6%) for GMFCS. For MACS, the highest number of participants were level 2 (48.8%) and level 5 (16.6%). The function classification of GMFCS and MACS in practice will provide usefulness for assessment of function in children with CP.

• Journal of the Korea Fashion and Costume Design Association
• /
• v.11 no.3
• /
• pp.87-99
• /
• 2009

The purpose of this study was to find out criteria for classifying fashion brand from the consumer point of view. This was compared with the viewpoint of fashion business practice in order to develop strategy of fashion brands and to manage brand effectively and systematically, and to suggest theoretical frame for application of these criteria. This study was researched as the succeeding study of a model of criteria for classifying fashion brands from the viewpoint of fashion business practice. Survey was used as a research method. The subjects were 422 women who were 20-30 years old and living in and near Seoul. Questionnaires were developed based on 37 fashion brands' classification criteria by means of pre-survey, and SPSS package and LISREL program were used to analyze the data. As a result of factor analysis considering 37 classification criteria, 8 factors were identified as classification criteria. They were as follows; the level of brand form, the level of product concept, the level of management item, the level of brand sales ability, the level of customer management, the level of brand advertising and awareness, the level of brand value, and the level of product lead ability. All of criteria were correlated to each other. The effective method to classify fashion brands was proposed by establishing the model of the relationship of the values of 7 criteria and by proving it with the structure equation model analysis. The model of criteria for classifying fashion brands that was suggested on this study was proved by the structure equation model analysis. In this study, from a consumer's point of view we suggested a theoretical framework describing which criteria would be selected to classify and utilize fashion brand market. This model can be used to select the most efficient classification criteria and classify them hierarchically instead of selecting only one among some factors that complex and interactional and classifying.