• The Journal of Korean Physical Therapy
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• v.30 no.5
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• pp.193-198
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• 2018

Purpose: The purpose of this study was to analysis of effectiveness between cognitive function assessment scores and gaming cognitive rehabilitation system in children with intellectual impairment. Methods: Five children (male=5, $age=10.00{\pm}0.80$) with intellectual impairment participated in this study and were randomly assigned to the experiment that played (received) gaming cognitive rehabilitation system (Neuroworld). The children were applied 2 times a week for 30 minutes during 3 months. The children were assessed K-WSIC-VI (Korean-Wechsler intelligence scale for children-fourth edition) and recorded that gained score in gaming cognitive rehabilitation system before and after intervention. K-WSIC-VI contained five primary index scores: verbal comprehension index, visual spatial index, fluid reasoning index, working memory index, and processing speed index. Gaming cognitive rehabilitation system scoring was composed visual recall, target recall, sequence recall, selective attention, continuous attention, and exploration. Results: In the intelligence quotient (IQ) of K-WSIC-VI, there were significant increased in all children. The visual recall item was highest effective in all children. However, sequential recall showed the lowest improvement in all children. The performance speed of selective attention item was decreased, this means that children's skills have improved. Also, their ability to explore has improved significantly. Conclusion: In conclusion, gaming cognitive rehabilitation system was significant effectiveness in cognitive function in some categories for children with intellectual impairment. However, the visual recall and performance speed don't represent of all cognitive function. Therefore, further studies will need to verify by applying more subject and longer duration.

• Korean Journal of Child Studies
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• v.37 no.6
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• pp.107-117
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• 2016

Objective: This study examined the construct validity of K-WPPSI-IV. Factor structures of the structures of the K-WPPSI-IV full scale as well as primary index scales for two age ranges (2 years, 6 months to 3 years, 11 months; 4 years to 7 years, 7 months) were examined. Methods: Data were collected from 1,700 children aged 2 years, 6 months to 7 years, 7 months during the K-WPPSI-IV standardization. Confirmatory factor analyses were conducted using the K-WPPSI-IV subtest performances with maximum likelihood estimation using Amos 18. Results: First, the three-factor model (verbal comprehension, visual spatial, and working memory) fitted best for the younger age range. However, the five-factor model (verbal comprehension, visual spatial, fluid reasoning, working memory, and processing speed) fitted best for the older age range. Residuals suggest the presence of two nested subfactors within the verbal comprehension factor (broad/expressive and focused/simple). Second, the confirmatory factor analysis on primary index subtests identified factors that account for the intercorrelations among the reduced sets of primary index subtests. Conclusion: The findings showed that the theoretical structures of WPPSI-IV subtests were confirmed within K-WPPSI-IV.

• Research in Community and Public Health Nursing
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• v.28 no.2
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• pp.107-117
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• 2017

Purpose: The purpose of this study is to examine the cognitive function in the elderly and to identify the influencing factors. Methods: The design of this study was descriptive research design. A total of 139 elderly people (aged 65 years and over) visiting the electroencephalogram (EEG) center in Seoul, Korea were evaluated. Data were assessed by self-administered questionnaires and CNS Vital Signs (CNSVS). Data were analyzed using SPSS Statistics 23.0 for Windows. Results: There were significant differences in the Korean Mini-Mental State Examination (K-MMSE), executive functions and reasoning according to education level. K-MMSE, visual memory and executive functions were different depending on the jobs. Age was highly correlated with cognitive function. In addition, stepwise multiple regression analyses showed that the factor significantly associated with reaction time and visual memory was depression. Depression and Trait-Anxiety had significant impacts on executive functions and K-MMSE. Conclusion: CNSVS enabled the accurate and objective measurement of cognitive function. Therefore, this study provides useful data to improve cognitive function of the community-dwelling elderly. The results suggested that there is need for comprehensive interventional programs that manage cognitive impairment.

• The Journal of Korean Association of Computer Education
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• v.4 no.1
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• pp.99-107
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• 2001

One of the main objects of geometry in mathematics education is to improve students' geometric intuition capability and logical reasoning capability based on them. A visual element related to intuition plays an important role in teaching and learning of geometry. Therefore, in this research, we focus on the development of multimedia title available to dynamic operation about visual elements and verify of effect of its application. This title for the learning of "the Pythagorean theorem and its practical use" in the third grade of middle school is designed and implemented by an authoring tool, Toolbook. And it enables learners to study mathematics individually and can be applied to the educational field, too. And we taught two groups, the applied group and the compared one of the second grade of middle school and surveyed Questions and evaluated study achievement. We calculated study achievement of two groups on t-test using SPSS. As the result, we knew that the applied group is higher than the compared one in the study achievement and provision of dynamic operation possibility on visual elements make students know very high learning effect and help improvement of intelligent capability.

• 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 Management Science Review
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• v.15 no.1
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• pp.137-148
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• 1998

We proposed a framework for computer-supported credit evaluation systems for the effective management of credit risks in Korean commercial banks. Especially for medium and small sized companies, credit evaluators used to depend much on past experience rather than formalized principles and rules. Therefore, we applied case-based reasoning. The credit grade of a company is roughly determined by searching for alreadygraded similar companies in terms of usually accepted evaluation items. And then the grade is refined and adjusted by considering additional information about exceptional facts or by reflecting other evaluation results from different methods or techniques. Booch's object-oriented analysis and design method, Visual Basic 5.0 and MS Access 97 are used for the development of this prototype system.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.731-736
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• 2007

Ubiquitous computing is a model of computing in which computer functions are integrated into everyday life, providing services and information in anywhere and anytime fashion. Augmented Reality is one of ubiquitous computing technologies to provide new paradigm utilized to interact between human and computer. By adding computer-generated non-visual information to real information and their interaction. user can get the improved and more knowledgeable information about real world. The purpose of this paper is the integration of AR and knowledge-base reasoning technology in ubiquitous computing. Through the introduced concept, it is enable to provide adequate knowledge in the process of ship design and manufacturing easily (Knowledge Everywhere). That is, this is a basic research to construct knowledge-based ubiquitous environment (KAD/KAM) in shipbuilding industry.

• 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.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.03a
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• pp.107-111
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• 1998

This paper presents a now approach to the design of intelligent contorl system for track vehicle system using fuzzy logic based on neural network. The proposed control scheme uses a Gaussian function as a unit function in the neural network-fuzzy, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. Moreover, We develop a Windows 95 version dynamic simulator which can simulate a track vehicle model in 3D graphics space. It is proposed a learning controller consisting of two neural network-fuzzy based of independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The dynamic simulator for track vehicle is developed by Microsoft Visual C++. Graphic libraries, OpenGL, by Silicon Graphics, Inc. were utilized for 3D Graphics. The performance of the proposed controller is illustrated by simulation for trajectory tracking of track vehicle speed.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.994-997
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• 2019

영상 기반 상식 추론(VCR) 문제는 기존의 영상 기반 질문-응답(VQA) 문제들과는 달리, 영상에 포함된 사물들 간의 관계 파악과 답변 근거 제시 등 별도의 상식 추론이 요구되는 새로운 지능 문제이다. 본 논문에서는 입력 데이터(영상, 자연어 질문, 응답 리스트)에서 사물들 간의 관계와 맥락 정보를 추출해내는 모듈들 외에, 별도로 ConceptNet과 같은 외부 지식 베이스로부터 관련 상식들을 직접 가져다 GCN 기반의 지식 그래프 임베딩 과정을 거쳐 추가적으로 활용할 수 있는 모듈들을 포함한 새로운 심층 신경망 모델인 KG_VCR을 제안한다. 제안 모델인 KG_VCR의 세부 설계사항들을 소개하고, VCR 벤치마크 데이터 집합을 이용한 다양한 실험들을 통해 제안 모델의 성능을 입증한다.