• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.5
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• pp.230-239
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• 1999

A virtual prototyping seeks to virtual environment where the development of vehicle models can be flecible as well as rapid and the experiments can be executed effectively concerning kinematics, controls, and behavior aspects of the models. This paper explains a virtual environment used for virtual prototyping of a vehicle. Ut has been developed using the dVISE environment thar provides actions, events, sounds, and light features. A vehicle model including detailed informations about a real-size vehicle. A human model is introduced for odjective visual evaluations of the developed, and then results are illustrated in order to demonstrate the applicability of developed models.

• Geophysics and Geophysical Exploration
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• v.7 no.1
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• pp.33-40
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• 2004

Numerical and laboratory studies have been conducted to test the ability of Electrical Resistance Tomography-a technique used to map the electrical resistivity of the subsurface-to delineate contaminant plumes. Two-dimensional numerical models were created to investigate survey design and resolution. Optimal survey design consisted of both downhole and surface electrode sites. Resolution models revealed that while the bulk fluid flow could be outlined, small-scale fingering effects could not be delineated. Laboratory experiments were conducted in a narrow glass tank to validate theoretical models. A visual comparison of fluid flow with ERT images also showed that, while the bulk fluid flow could be seen in most instances, fine-scale effects were indeterminate.

• The Mathematical Education
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• v.40 no.1
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• pp.93-102
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• 2001

The world we live in is called the age of information. Thus communication and computers are doing the central role in it. When one studies the mathematical problem, the use of tools such as computers, calculators and technology is available for all students, and then students are actively engaged in reasoning, communicating, problem solving, and making connections with mathematics, between mathematics and other disciplines. The use of technology extends to include computer algebra systems, spreadsheets, dynamic geometry software and the Internet and help active learning of students by analyzing data and realizing mathematical models visually. In this paper, we explain concepts of transformation, linear transformation, congruence transformation and homothety, and introduce interesting, meaningful and visual models for teaching of a plane transformation geomeoy which are obtained by using Mathematica. Moreover, this study will show how to visualize linear transformation for student's better understanding in teaching a plane transformation geometry in classroom. New development of these kinds of teaching-learning methods can simulate student's curiosity about mathematics and their interest. Therefore these models will give teachers the active teaching and also give students the successful loaming for obtaining the concept of linear transformation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.6
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• pp.973-980
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• 2017

The purpose of this study is to develop VDFT (Visual Basic based Density-coupled Flow and Transport), a numerical modeling code used to simulate density coupled flow equations used to simulate seawater intrusion in a two dimensional finite difference method. The VDFT code has the advantage of being intuitive and simple to use and has the advantage of utilizing the EXCEL Visual Basic platform, which is widely used for general business purposes. Generally, code developed for numerical simulation can be verified through representative example models called benchmark problem. In this study, we verified the VDFT code using benchmark problem called Henry Problem and Modified Henry Problem as well as two laboratory test data. The results of this study are analyzed the importance of each benchmark problems, validated VDFT code compared to those problems. In conclusion, the possibility of using VDFT code is diagnosed and the direction of future research is suggested.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.2938-2956
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• 2020

Objective image quality assessment (IQA) models have been developed by effective features to imitate the characteristics of human visual system (HVS). Actually, HVS is extremely sensitive to color degradation and complex texture changes. In this paper, we firstly reveal that many existing full reference image quality assessment (FR-IQA) methods can hardly measure the image quality with contrast and masking texture changes. To solve this problem, considering texture masking effect, we proposed a novel FR-IQA method, called Texture and Color Quality Index (TCQI). The proposed method considers both in the masking effect texture and color visual perceptual threshold, which adopts three kinds of features to reflect masking texture, color difference and structural information. Furthermore, random forest (RF) is used to address the drawbacks of existing pooling technologies. Compared with other traditional learning-based tools (support vector regression and neural network), RF can achieve the better prediction performance. Experiments conducted on five large-scale databases demonstrate that our approach is highly consistent with subjective perception, outperforms twelve the state-of-the-art IQA models in terms of prediction accuracy and keeps a moderate computational complexity. The cross database validation also validates our approach achieves the ability to maintain high robustness.

• Journal of the Korean Institute of Educational Facilities
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• v.6 no.2
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• pp.13-23
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• 1999

This paper seeks to find out the policies of management and layout of middle school rooms for the community people's use. This paper surveys community's needs with respect to both the use of school rooms before, during, and after classes and preferences of use of school rooms. This paper adopts two experimental case studies to find out the models. It uses t-test analysis of the statistics to find out community people's preferences for the use of school rooms between two communities in an urban area, and uses simple and multiple regression analyses to develop models concerning community people's uses of school rooms before, during, and after classes. It also uses cluster analysis to find out the cluster among community people's preference of school rooms. It found, first, that community people's use of school rooms after class can be influenced by the uses of a play ground, a music classroom, an audio visual classroom, and a gymnasium. The use during regular classes is related to the uses of the fine arts classroom, a general classroom, a home economics classroom, a gymnasium, and a playground. The use before class is affected by the uses of a fine arts classroom, a playground, and a library. It also found that, with respect to community people's preferential use of school rooms, the rooms can be clustered as a cluster of laboratories such as a general classroom, a music room, a fine arts classroom, a science classroom, a home economics classroom, and a technique classroom, a cluster of athletic areas such as a gymnasium and a playground, and a cluster of supporting facilities such as a library, an audio visual classroom, and a computer classroom. Those clusters can also be clustered in more detail, i. e., that both a general classroom and playground can be apart from a cluster of laboratories or a cluster of supporting facilities; that an audio visual classroom can be fostered into a cluster with a home economics affairs classroom and a technique classroom. Finally this paper suggests policies of management and layout of school rooms.

• Korean Journal of Ophthalmology
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• v.32 no.6
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• pp.470-477
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• 2018

Purpose: To investigate the relationship between the progression of visual field (VF) loss and changes in lamina cribrosa depth (LCD) as determined by spectral-domain optical coherence tomography (SD-OCT) enhanced depth imaging in patients with primary open angle glaucoma (POAG). Methods: Data from 60 POAG patients (mean follow-up, $3.5{\pm}0.7$ years) were included in this retrospective study. The LCD was measured in the optic disc image using SD-OCT enhanced depth imaging scanning at each visit. Change in the LCD was considered to either 'increase' or 'decrease' when the differences between baseline and the latest two consecutive follow-up visits were greater than the corresponding reproducibility coefficient value ($23.08{\mu}m$, as determined in a preliminary reproducibility study). All participants were divided into three groups: increased LCD (ILCD), decreased LCD (DLCD), and no LCD change (NLCD). The Early Manifest Glaucoma Trial criteria were used to define VF deterioration. Kaplan-Meier survival analysis and Cox's proportional hazard models were performed to explore the relationship between VF progression and LCD change. Results: Of the 60 eyes examined, 35.0% (21 eyes), 28.3% (17 eyes), and 36.7% (22 eyes) were classified as the ILCD, DLCD, and NLCD groups, respectively. Kaplan-Meier survival analysis showed a greater cumulative probability of VF progression in the ILCD group than in the NLCD (p < 0.001) or DLCD groups (p = 0.018). Increased LCD was identified as the only risk factor for VF progression in the Cox proportional hazard models (hazard ratio, 1.008; 95% confidence interval, 1.000 to 1.015; p = 0.047). Conclusions: Increased LCD was associated with a greater possibility of VF progression. The quantitative measurement of LCD changes, determined by SD-OCT, is a potential biomarker for the prediction of VF deterioration in patients with POAG.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.175-181
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• 2022

COVID-19 is an acute respiratory syndrome that affects the host's breathing and respiratory system. The novel disease's first case was reported in 2019 and has created a state of emergency in the whole world and declared a global pandemic within months after the first case. The disease created elements of socioeconomic crisis globally. The emergency has made it imperative for professionals to take the necessary measures to make early diagnoses of the disease. The conventional diagnosis for COVID-19 is through Polymerase Chain Reaction (PCR) testing. However, in a lot of rural societies, these tests are not available or take a lot of time to provide results. Hence, we propose a COVID-19 classification system by means of machine learning and transfer learning models. The proposed approach identifies individuals with COVID-19 and distinguishes them from those who are healthy with the help of Deep Visual Embeddings (DVE). Five state-of-the-art models: VGG-19, ResNet50, Inceptionv3, MobileNetv3, and EfficientNetB7, were used in this study along with five different pooling schemes to perform deep feature extraction. In addition, the features are normalized using standard scaling, and 4-fold cross-validation is used to validate the performance over multiple versions of the validation data. The best results of 88.86% UAR, 88.27% Specificity, 89.44% Sensitivity, 88.62% Accuracy, 89.06% Precision, and 87.52% F1-score were obtained using ResNet-50 with Average Pooling and Logistic regression with class weight as the classifier.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.12
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• pp.3383-3397
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• 2023

Scene graphs serve as semantic abstractions of images and play a crucial role in enhancing visual comprehension and reasoning. However, the performance of Scene Graph Generation is often compromised when working with biased data in real-world situations. While many existing systems focus on a single stage of learning for both feature extraction and classification, some employ Class-Balancing strategies, such as Re-weighting, Data Resampling, and Transfer Learning from head to tail. In this paper, we propose a novel approach that decouples the feature extraction and classification phases of the scene graph generation process. For feature extraction, we leverage a transformer-based architecture and design an adaptive calibration function specifically for predicate classification. This function enables us to dynamically adjust the classification scores for each predicate category. Additionally, we introduce a Distribution Alignment technique that effectively balances the class distribution after the feature extraction phase reaches a stable state, thereby facilitating the retraining of the classification head. Importantly, our Distribution Alignment strategy is model-independent and does not require additional supervision, making it applicable to a wide range of SGG models. Using the scene graph diagnostic toolkit on Visual Genome and several popular models, we achieved significant improvements over the previous state-of-the-art methods with our model. Compared to the TDE model, our model improved mR@100 by 70.5% for PredCls, by 84.0% for SGCls, and by 97.6% for SGDet tasks.

• Korean Journal of Cognitive Science
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• v.35 no.1
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• pp.1-21
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• 2024

This study investigates the characteristics of visual working memory (VWM) representations by examining two theoretical models: the integrated-object and the parallel-independent feature storage models. Experiment I involved a change detection task where participants memorized arrays of either orientation bars, colored squares, or both. In the one-feature condition, the memory array consisted of one feature (either orientations or colors), whereas the two-feature condition included both. We found no differences in change detection performance between the conditions, favoring the integrated object model over the parallel-independent feature storage model. Experiment II employed a recall task with memory arrays of isosceles triangles' orientations, colored squares, or both, and one-feature and two-feature conditions were compared for their recall performance. We found again no clear difference in recall accuracy between the conditions, but the results of analyses for memory precision and guessing responses indicated the weak object model over the strong object model. For ongoing debates surrounding VWM's representational characteristics, these findings highlight the dominance of the integrated object model over the parallel independent feature storage model.