• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.147-149
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• 2022

This paper proposes a state machine design methodology in which an interactive robot that mimics discrete trial training (DTT protocol) can support social interaction training for children with autism. The robot applied to social interaction training uses the response to the provided training stimulus as a quantitative indicator by processing the data received from the sensors measuring the behavioral response of the child. In this process, the state machine is used as information that classifies the state of the acquired data and provides the subsequent stimulus for DTT protocol. Through the joint attentional training, it can be used as evidence-based treatment information by quantitatively classifying the data on the number of sustainable and DTT protocol and the child's response, as well as the current reaction status of the child to the observer performing remote monitoring. At the same time, it was confirmed that it is possible to properly respond to misrecognition situations.

• Smart Structures and Systems
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• v.32 no.1
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• pp.23-35
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• 2023

Steel bolted joint is an important part of steel structure, and its damage directly affects the bearing capacity and durability of steel structure. Currently, the existing research mainly focuses on the identification of corroded bolts and corroded bolts respectively, and there are few studies on multiple states. A detection framework of corroded and loosened bolts is proposed in this study, and the innovations can be summarized as follows: (i) Vision Transformer (ViT) is introduced to replace the third and fourth C3 module of you-only-look-once version 5s (YOLOv5s) algorithm, which increases the attention weights of feature channels and the feature extraction capability. (ii) Three states of the steel bolts are considered, including corroded bolt, bolt missing and clean bolt. (iii) Line segment detector (LSD) is introduced for bolt rotation angle calculation, which realizes bolt looseness detection. The improved YOLOv5s model was validated on the dataset, and the mean average precision (mAP) was increased from 0.902 to 0.952. In terms of a lab-scale joint, the performance of the LSD algorithm and the Hough transform was compared from different perspective angles. The error value of bolt loosening angle of the LSD algorithm is controlled within 1.09%, less than 8.91% of the Hough transform. Furthermore, the proposed framework was applied to fullscale joints of a steel bridge in China. Synthetic images of loosened bolts were successfully identified and the multiple states were well detected. Therefore, the proposed framework can be alternative of monitoring steel bolted joints for management department.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1A
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• pp.147-154
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• 2008

The purpose of this study is to critically evaluate the structural performance of an innovative new shear resistance connecting structure of precast member. Joints such as shear resistance connecting structure require special attention when designing and constructing precast segmental structures. An experimental and analytical study was conducted to quantify performance measures and examine one aspect of detailing for developed shear resistance connecting structure. A computer program, named RCAHEST (Reinforced Concrete Analysis in Higher Evaluation System Technology), for the analysis of reinforced concrete structures was used. A joint element is used to predict the inelastic behavior of the joints between segmental members. Future work by the authors will do a model test of precast segmental prestressed concrete bridge columns with this shear resistance connecting structure, and examined both the structural behavior and seismic performance.

• Korean Journal of Child Education & Care
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• v.17 no.1
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• pp.1-28
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• 2017

This is a case study on how infants' behaviors change after their child care teachers use Responsive Interactions to them. The participants are five infants and five child care teachers from five employer-supported child care centers run and managed by H foundation. This study analyzes the changes in infants' pivotal developmental behaviors based on interactions between an infant and a child care teacher in video recordings, anecdotal records, Reflective Journal written by the teachers, and data on in-depth interviews with the child care teachers. The results show that Responsive Interactions have brought positive changes to infants' pivotal developmental behaviors(Attention to Activity, Problem Solving Persistence, Involvement, Cooperation, Initiation, Joint Attention and Affect). It suggests that child care teachers who are in charge of taking care of infants should realize and practice the importance of Responsive Interaction Strategy in order to help the infants develop their pivotal behaviors.

• The Journal of the Korea Contents Association
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• v.15 no.2
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• pp.529-541
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• 2015

Collaborative learning of collective intelligence-based model is also ideal in higher education did not yet consensus still in the theoretical level. To become collective intelligence-based collaborative learning is to mobilize the competence of the various members should be promoted as much as possible with their own services designed to actively participate in and contribute to the goals of the joint. Is still based collaborative learning model of collective intelligence, which does the actual model is not developed in education is a key program in creative fusion judge called talent. The evolution of the main features of the house just in shaping the content of a modern lecture geureohagi need to check from time to time to see and pay attention. As part of this study, attempts were associated with the tvN planning and attention to trying connector Executive Lecture show "Creative Club 199" content. Well oriented intention to converge the needs of the times, but it is even more compelling naeeotda implement the collective intelligence based on 'how' the reality is that together with the participants.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3729-3749
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• 2021

At present, deep convolution network-based salient object detection (SOD) has achieved impressive performance. However, it is still a challenging problem to make full use of the multi-scale information of the extracted features and which appropriate feature fusion method is adopted to process feature mapping. In this paper, we propose a new adjacency auxiliary network (AANet) based on multi-scale feature fusion for SOD. Firstly, we design the parallel connection feature enhancement module (PFEM) for each layer of feature extraction, which improves the feature density by connecting different dilated convolution branches in parallel, and add channel attention flow to fully extract the context information of features. Then the adjacent layer features with close degree of abstraction but different characteristic properties are fused through the adjacent auxiliary module (AAM) to eliminate the ambiguity and noise of the features. Besides, in order to refine the features effectively to get more accurate object boundaries, we design adjacency decoder (AAM_D) based on adjacency auxiliary module (AAM), which concatenates the features of adjacent layers, extracts their spatial attention, and then combines them with the output of AAM. The outputs of AAM_D features with semantic information and spatial detail obtained from each feature are used as salient prediction maps for multi-level feature joint supervising. Experiment results on six benchmark SOD datasets demonstrate that the proposed method outperforms similar previous methods.

• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.1-9
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• 2022

In this paper, we propose the Deep Learning-Based Companion Animal Abnormal Behavior Detection Service, which using video and sensor data. Due to the recent increase in households with companion animals, the pet tech industry with artificial intelligence is growing in the existing food and medical-oriented companion animal market. In this study, companion animal behavior was classified and abnormal behavior was detected based on a deep learning model using various data for health management of companion animals through artificial intelligence. Video data and sensor data of companion animals are collected using CCTV and the manufactured pet wearable device, and used as input data for the model. Image data was processed by combining the YOLO(You Only Look Once) model and DeepLabCut for extracting joint coordinates to detect companion animal objects for behavior classification. Also, in order to process sensor data, GAT(Graph Attention Network), which can identify the correlation and characteristics of each sensor, was used.

• Journal of Information Management
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• v.41 no.2
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• pp.47-69
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• 2010

Open innovation is a phenomenon that has been widely accepted by both practice and theory over the last few years. On the contrary, partner relationships have attracted little attention while the open innovation could not be emerged without the link to partners. This paper identifies and evaluates a framework for the partner relationships and open innovation processes. Based on the literatures regarding open innovation and partner relationships, we propose the framework of matrix type. We present results based on 352 open innovation cases reported during 2002-2009, and each case is classified into 5 different categories of the framework. JV-C(Joint Venture relationship & Coupled process) archetype has dominated the cases with 178 cases(50.6%) where JV-O(Joint Venture relationship & Outside-In process) follows JV-C with 124 cases(35.2%). No significant change has been found in the number of cases after 2003 when open innovation firstly suggested. However, the number sharply increases in 2009 by boom in JV-C and JV-O. These results show the importance of partner relationships and preference toward Joint Venture relationship in open innovation, while the conventional approaches has just focused on value-chain partnership. We find remarkable collaboration cases contributed by universities and government invested research centers, so the role of non-profit R&D organizations has also been discussed.

• Journal of Industrial Convergence
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• v.21 no.6
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• pp.1-11
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• 2023

The purpose of this study is to verify the factors affecting corporate bankruptcy by using non-financial information of companies invested by credit guarantee institutions. In this study, 594 companies (525 normal companies, 69 insolvent companies) invested in by the Korea Credit Guarantee Fund from March 2014 to the end of December 2022 were selected as samples. Non-financial information of companies was divided into founder characteristics information, company characteristics information, and corporate investment information, and cross-analysis and logistic regression analysis were conducted. As a result of the cross-analysis, personal credit rating, industry, and joint investment were selected as significant variables, and logistic regression analysis was conducted for those variables, and two variables, personal credit rating and joint investment, were selected as important factors for bankruptcy. In business management, the founder's personal credit and the importance of joint investment in investment support were found out. It will help to minimize bankruptcy if institutions that support investment in SMEs reflect these results in their screening and systematically build cooperative relationships with private investment institutions. It is hoped that this study will provide an opportunity to pay more attention to the factors that affect the bankruptcy of companies that receive direct investment from public institutions.

• Journal of the HCI Society of Korea
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• v.9 no.2
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• pp.61-68
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• 2014

Tabletop games have been applied to improve the ability of social collaboration based on the characteristics that more than two people simultaneously interact on the tabletop. Especially, the tabletop games can be used as an educational tool for children with autism when it is implemented by considering educational and psychological models for children's behavioral characteristics. However, the previous collaborative games were designed for only disabled children so that it is hard to reflect cognitive and humanistic effects in inclusive education, where disabled children and non-disabled children interact in a same spatiotemporal environment. In this paper, therefore, we design a collaborative game on a multi-touch tabletop to enable spontaneous communication between disabled children and non-disabled children. Through user study, we evaluate the improvement in terms of the positive interaction and the degree of attention by comparing with a conventional collaborative game(e.g., a board game). We found that negative interaction including disabled children's abnormal behavior decreased and positive interaction such as body gestures and verbal communications increased. In addition, the tabletop game supported high immersiveness to all children by deriving equal level of attention time including individual and joint attention. We anticipate that the proposed game design can be utilized to develop collaborative contents for people with differences on sociality and cognitive ability.