• Korean Journal of Remote Sensing
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• v.35 no.6_3
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• pp.1209-1219
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• 2019

For consistent vegetation monitoring, it is necessary to generate time-series vegetation index datasets at fine temporal and spatial scales by fusing the complementary characteristics between temporal and spatial scales of multiple satellite data. In this study, we quantitatively and qualitatively analyzed the prediction accuracy of time-series change information extracted from spatio-temporal fusion models of multiple satellite data for vegetation monitoring. As for the spatio-temporal fusion models, we applied two models that have been widely employed to vegetation monitoring, including a Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) and an Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM). To quantitatively evaluate the prediction accuracy, we first generated simulated data sets from MODIS data with fine temporal scales and then used them as inputs for the spatio-temporal fusion models. We observed from the comparative experiment that ESTARFM showed better prediction performance than STARFM, but the prediction performance for the two models became degraded as the difference between the prediction date and the simultaneous acquisition date of the input data increased. This result indicates that multiple data acquired close to the prediction date should be used to improve the prediction accuracy. When considering the limited availability of optical images, it is necessary to develop an advanced spatio-temporal model that can reflect the suggestions of this study for vegetation monitoring.

• Journal of Korean Dental Science
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• v.15 no.1
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• pp.1-8
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• 2022

Purpose: Intraoral scanners, desktop scanners, and cone-beam computed tomography (CBCT) are being used in a complementary way for diagnosis and treatment planning. Limited patient-based results are available about dimensional reproducibility among different three-dimensional imaging systems. This study aimed to evaluate dimensional reproducibility among patient-derived digital models created from an intraoral scanner, desktop scanner, and two CBCT systems. Materials and Methods: Twenty-nine arches from sixteen patients who were candidates for implant treatments were enrolled. Different types of CBCT systems (KCT and VCT) were used before and after the surgery. Polyvinylsiloxane impressions were taken on the enrolled arches after the healing period. Gypsum casts were fabricated and scanned with an intraoral scanner (CIOS) and desktop scanner (MDS). Four test groups of digital models, each from CIOS, MDS, KCT, and VCT, respectively, were compared to the reference gypsum cast group. For comparison of linear measurements, intercanine and intermolar widths and left and right canine to molar lengths were measured on individual gypsum cast and digital models. All measurements were triplicated, and the averages were used for statistics. Bland-Altman plots were drawn to assess the degree of agreement between each test group with the reference gypsum cast group. A linear mixed model was used to analyze the fixed effect of the test groups compared to the reference group (α=0.05). Result: The Bland-Altman plots showed that the bias of each test group was -0.07 mm for CIOS, -0.07 mm for MDS, -0.21 mm for VCT, and -0.25 mm for KCT. The linear mixed model did not show significant differences between the test and reference groups (P>0.05). Conclusion: The linear distances measured on the digital models created from CIOS, MDS, and two CBCT systems showed slightly larger than the references but clinically acceptable reproducibility for diagnosis and treatment planning.

• Structural Engineering and Mechanics
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• v.87 no.3
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• pp.283-296
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• 2023

Free-vibration and buckling analyses of plate problems are investigated with the aid of the strain gradient notation finite element method (SGN-FEM). As SGN-FEM employs physically interpretable polynomials in developing finite elements, parasitic shear sources, which are the cause of shear locking, can be precisely identified and subsequently eliminated. This allows two mutually complementary objectives to be defined in this work, namely, evaluate the efficiency of free-vibration and buckling results provided by corrected models, and study the severity of parasitic shear effects on plate models performance. Parasitic shear are flexural terms erroneously present in shear strain polynomials. It is reviewed here that six parasitic shear terms arise during the formulation of the four-node Mindlin plate element. Two parasitic shear terms have been identified in the in-plane shear strain polynomial while other two have been identified in each of the transverse shear strain polynomials. The element is corrected a-priori, i.e., during development, by simply removing the spurious terms from the shear strain polynomials. The computational implementation of the element in its two versions, namely, containing the parasitic shear terms (PS) and corrected for parasitic shear (SG), allows for assessments of the accuracy of results and of the deleterious effects of parasitic shear in free vibration and buckling analyses. This assessment of the parasitic shear effects is a novelty of this work. Validation of the SG model is done comparing its results with analytical results and results provided by other numerical procedures. Analyses are performed for square plates with different thickness-to-length ratios and boundary conditions. Results for thin plates provided by the PS model do not converge to the correct solutions, which indicates that parasitic shear must be eliminated. That is, analysts should not rely on refinement alone. For thick plates, PS model results can be considered acceptable as deleterious effects are really critical in thin plates. On the other hand, results provided by the SG model converge well for both thin and thick plates. The effectiveness of the SG model is established via high-accuracy results obtained in several examples. It is concluded that corrected SGN-FEM models are efficient alternatives for free-vibration and buckling analysis of Mindlin plate problems, and that precise elimination of parasitic shear is a requirement for sound analyses.

• The Mathematical Education
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• v.39 no.2
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• pp.151-166
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• 2000

The purpose of this study is to understand what two models of SOLO taxonomy and van Hiele theory suggest and find out what relation there is between the category system of the SOLO taxonomy and the thinking level of the van Hiele theory. The van Hiele theory describes in line of ranking level so that it may increase the teaching effects by putting together a class, which takes into consideration the students thoughts. The SOLO taxonomy focused on the response mode of the students rather than the thinking level or the developmental stage of them to pursuit the method that can describe the students understanding in depth quality-wise. Although the SOLO taxonomy and the van Hiele model seem to have different form and character from outside in terms of their goals, a closer examination reveals that the two stances have much in common and that the models are complementary. Although the van Hiele placed more focus on the thoughts, because the conclusion was based on the students responses, the van Hiele theory can be interpreted within the structure identified in the SOLO model. In this study, we have tried to understand how the response structure form the SOLO taxonomy and the thinking level of the van Hiele theory are related, based on the studies of Pegg and Davery1998). If you briefly look at them, there are following corresponding relation between the SOLO taxonomy and the van Hiele theory. a) The relational level(R) in iconic moe is van Hiele level 1. b) The multisturctural level(M$_2$) in the second cycle of concrete-symbolic mode is van Hiel level 2. c) The relation level(R$_2$) in the second cycle of concrete-symbolic mode is van Hiele level 3. d) The unistructural level(U$_2$) in the second cycle of formal mode is van Hiele level 4. e) The postformal mode is van Hiele levle 5. Though it would be difficult to conclude that these correspondences were perfectly done, if you look at their relation, you can see that the learning process of the students were not carried out uniformly. Therefore, by studying the students response structure, using the SOLO taxonomy, and identifying the learning cycle and understand the geometrical concept more in depth.

• Journal of the Korea Concrete Institute
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• v.14 no.6
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• pp.1022-1031
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• 2002

This paper presents efficient models for bridge structures using CART-ANFIS (classification and regression tree-adaptive neuro fuzzy inference system). A fuzzy decision tree partitions the input space of a data set into mutually exclusive regions, each region is assigned a label, a value, or an action to characterize its data points. Fuzzy decision trees used for classification problems are often called fuzzy classification trees, and each terminal node contains a label that indicates the predicted class of a given feature vector. In the same vein, decision trees used for regression problems are often called fuzzy regression trees, and the terminal node labels may be constants or equations that specify the predicted output value of a given input vector. Note that CART can select relevant inputs and do tree partitioning of the input space, while ANFIS refines the regression and makes it continuous and smooth everywhere. Thus it can be seen that CART and ANFIS are complementary and their combination constitutes a solid approach to fuzzy modeling.

• The Korean Journal of Emergency Medical Services
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• v.19 no.2
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• pp.83-97
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• 2015

Purpose: Although appointed as a national competency standards (NCS) based reserves department, the department of emergency medical technology, an NCS-based emergency department, is mainly focused on subject deduction for a NCS-based curriculum. Methods: Job models were formed and verified by combining the competency unit of NCS and the duty of Developing a curriculum (DACUM) based on the development procedure indicated in the guidelines for a NCS-based curriculum. The mapping method of the subject was performed by deducting necessary competency units (duty) and competency unit elements (task) by connecting with the composition items of NCS and DACUM. Results: Job models combined with job analysis for the NCS and DACUM were reduced to 13 competency units (duty) and 79 competency unit elements (task). A modified method such as the 1:N method was mainly applied as a subject-matching method with consideration of the competency level and size of the competency unit. Conclusion: It would be a desirable direction to develop a NCS-based curriculum in the center of the practice subject in consideration of the size of the competency unit and competency level of the competency unit element. The existing curriculum should be promoted as a field-oriented curriculum at the complementary level.

• Molecules and Cells
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• v.42 no.2
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• pp.143-150
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• 2019

Chronic neuropathic pain is one of the primary causes of disability subsequent to spinal cord injury. Patients experiencing neuropathic pain after spinal cord injury suffer from poor quality of life, so complementary therapy is seriously needed. Dehydrocorybulbine is an alkaloid extracted from Corydalis yanhusuo. It effectively alleviates neuropathic pain. In the present study, we explored the effect of dehydrocorybulbine on neuropathic pain after spinal cord injury and delineated its possible mechanism. Experiments were performed in rats to evaluate the contribution of dehydrocorybulbine to P2X4 signaling in the modulation of pain-related behaviors and the levels of pronociceptive interleukins and proteins after spinal cord injury. In a rat contusion injury model, we confirmed that chronic neuropathic pain is present on day 7 after spinal cord injury and P2X4R expression is exacerbated after spinal cord injury. We also found that administration of dehydrocorybulbine by tail vein injection relieved pain behaviors in rat contusion injury models without affecting motor functions. The elevation in the levels of pronociceptive interleukins ($IL-1{\beta}$, IL-18, MMP-9) after spinal cord injury was mitigated by dehydrocorybulbine. Dehydrocorybulbine significantly mitigated the upregulation of P2X4 receptor and reduced ATP-evoked intracellular $Ca^{2+}$ concentration. Both P2XR and dopamine receptor2 agonists antagonized dehydrocorybulbine's antinociceptive effects. In conclusion, we propose that dehydrocorybulbine produces antinociceptive effects in spinal cord injury models by inhibiting P2X4R.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.635-644
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• 2020

Object recognition, detection and instance segmentation based on DL (Deep Learning) have being used in various practices, and mainly optical images are used as training data for DL models. The major objective of this paper is object segmentation and building detection by utilizing multimodal datasets as well as optical images for training Detectron2 model that is one of the improved R-CNN (Region-based Convolutional Neural Network). For the implementation, infrared aerial images, LiDAR data, and edges from the images, and Haralick features, that are representing statistical texture information, from LiDAR (Light Detection And Ranging) data were generated. The performance of the DL models depends on not only on the amount and characteristics of the training data, but also on the fusion method especially for the multimodal data. The results of segmenting objects and detecting buildings by applying hybrid fusion - which is a mixed method of early fusion and late fusion - results in a 32.65% improvement in building detection rate compared to training by optical image only. The experiments demonstrated complementary effect of the training multimodal data having unique characteristics and fusion strategy.

• Journal of Advanced Navigation Technology
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• v.28 no.2
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• pp.238-245
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• 2024

In this paper, we propose a framework for improving the performance of semantic segmentation of agricultural multispectral image using feature fusion techniques. Most of the semantic segmentation models being studied in the field of smart farms are trained on RGB images and focus on increasing the depth and complexity of the model to improve performance. In this study, we go beyond the conventional approach and optimize and design a model with multispectral and attention mechanisms. The proposed method fuses features from multiple channels collected from a UAV along with a single RGB image to increase feature extraction performance and recognize complementary features to increase the learning effect. We study the model structure to focus on feature fusion and compare its performance with other models by experimenting with favorable channels and combinations for crop images. The experimental results show that the model combining RGB and NDVI performs better than combinations with other channels.

• KIEAE Journal
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• v.12 no.5
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• pp.63-70
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• 2012

In order to set the direction of providing facility for the utilization of castle heritage, as well as to establish the method for securing access and determine installation criteria in consideration of preservation environment, an analysis was carried out on the cases of having secured access for people with disabilities in England for the advanced utilization of castle heritage. As the result of the analysis, the planning factors of the facility for people with disabilities in England for the utilization of castle heritage were deduced as follows: 1) The plan for facility was focused on the disabled using wheelchairs and visually impaired persons, rather than on services for hearing-impaired persons and people with learning disability. 2) As for audience movement line plan, regular route was used for audience movement line to lead them in a single direction. 3) As for the provision of prior access information, 3 stepwise access grades were established for the facility information plan of heritage. 4) As for information service by disability type, models were provided; and complementary explanation was provided by using text, drawing, picture, video and voice. 5) Rest spaces were secured where audience could look out upon castle heritage. For the utilization of castle heritage, it is necessary to develop planning factors of the facility design for people with disabilities according to its characteristics.