• KIPS Transactions on Software and Data Engineering
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• 제11권5호
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• pp.221-228
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• 2022

With the application of artificial intelligence technology, robots can provide efficient services in real life. Unlike industrial manipulators that do simple repetitive work, this study presented design methods of 6 degree of freedom robot arm and intelligent object search and movement methods for use alone or in collaboration with no place restrictions in the service robot field and verified performance. Using a depth camera and deep learning in the ROS environment of the embedded board included in the robot arm, the robot arm detects objects and moves to the object area through inverse kinematics analysis. In addition, when contacting an object, it was possible to accurately hold and move the object through the analysis of the force sensor value. To verify the performance of the manufactured robot arm, experiments were conducted on accurate positioning of objects through deep learning and image processing, motor control, and object separation, and finally robot arm was tested to separate various cups commonly used in cafes to check whether they actually operate.

• The Journal of the Convergence on Culture Technology
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• 제7권2호
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• pp.427-436
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• 2021

The purpose of this study is to implement a machine learning language model that learns literary texts. Literary texts have an important characteristic that pairs of question-and-answer are not frequently clearly distinguished. Also, literary texts consist of pronouns, figurative expressions, soliloquies, etc. They hinder the necessity of machine learning using literary texts by making it difficult to learn algorithms. Algorithms that learn literary texts can show more human-friendly interactions than algorithms that learn general sentences. For this goal, this paper proposes three text correction tasks that must be preceded in researches using literary texts for machine learning language model: pronoun processing, dialogue pair expansion, and data amplification. Learning data for artificial intelligence should have clear meanings to facilitate machine learning and to ensure high effectiveness. The introduction of special genres of texts such as literature into natural language processing research is expected not only to expand the learning area of machine learning, but to show a new language learning method.

• The Journal of the Korea institute of electronic communication sciences
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• 제18권4호
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• pp.601-608
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• 2023

Mobile robots are widely used in industries because mobile robots perform tasks in various environments. In order to carry out tasks, determining the precise location of the robot in real-time is important due to the need for path generation and obstacle detection. In particular, when mobile robots autonomously navigate in indoor environments and carry out assigned tasks within pre-determined areas, highly precise positioning performance is required. However, mobile robots frequently experience data missing in wireless communication environments. The robots need to rely on predictive techniques to autonomously determine the mobile robot positions and continue performing mobile robot tasks. In this paper, we propose an extended Kalman filter-based algorithm to enhance the accuracy of mobile robot localization and address the issue of data missing. Trilateration algorithm relies on measurements taken at that moment, resulting in inaccurate localization performance. In contrast, the proposed algorithm uses residual values of predicted measurements in data missing environments, making precise mobile robot position estimation. We conducted simulations in terms of data missing to verify the superior performance of the proposed algorithm.

• Journal of Korea Entertainment Industry Association
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• 제13권3호
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• pp.203-211
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• 2019

The purpose of this study was to investigate the relations between sensory processing and sleep disturbances and to investigate the effect of sensory processing on sleep disorder in preschool children with developmental disorder. This study was conducted for 110 children with developmental disorder in developmental clinic and rehabilitation hospital in Gwang Ju from June to August, 2017. The final 109 data were analyzed. Sensory processing and Sleep disturbances were measured using the Shortened sensory profile(SSP) and Korean-the Children's Sleep Habits Questionnaire(K-CSHQ). Statistical analysis was performed using descriptive analysis, Pearson correlation analysis, and multiple regression analysis were performed. Children with developmental disorder had problems with sensory processing and sleep habits. Sensory processing was related to sleep habit and most important factors of sensory processing influencing sleep was taste/olfactory sensitivity, auditory filtering. Conclusion: In order to help children with developmental disorder with sleep problem, it is necessary to consider the sensory processing especially taste/olfactory sensitivity, auditory filtering.

• Journal of the Korea Society of Computer and Information
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• 제14권2호
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• pp.111-118
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• 2009

Against Anomaly of GPS, there are several projects of independent satellite navigation systems like Galileo of Europe and QZSS of Japan and modernization of terrestrial navigation system like Loran. In domestic, the need of independent navigation system was proposed and DGPS signal was nominated as the possible substitute. The DGPS signal uses medium frequency, which travels through the surface and cause the additional delay rather than the speed of light according to Conductivities and elevations of the irregular terrain. The similar approach is Locan-C. Loran-C has been widely used as the maritime location system. Loran-C uses the ASF estimation method and provides more precise positioning. However there was rarely research on this area in Korea Therefore, we introduce the legacy guaranteed model of additional delay(ASF) and present the results of implementation. With the comparison of the original Monteath results and BALOR results respectively, we guarantee that the implementation is absolutely perfect. For further works, we're going to apply the ASF estimation model to Korean DGPS system with the Korean terrain data.

• 한국체육학회지인문사회과학편
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• 제55권4호
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• pp.343-350
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• 2016

The purpose of this study is to phenomenological analyze the fun experience of G-Golf Tour players. A total of 3 male and 3 female professional golfers who are currently participate in G-Golf Tour are selected by snow-ball sampling. Data was collected from interviews and participant observation, With this data, coding was done as first step and group categorization was done as second step in order to achieve the right result from meaningful analyzing. In order to approve the adequate of this study, the peer review was done by one qualitative research specialist and two candidates of Ph.D. The motivation of G-Tour participation, the notification changing of G-Tour, the addiction of G-Tour, the fun factor of G-Tour were drawn as the results, and the media exposure, personal relations, and skill improvement were drawn as the sub-factors of fun experience of G-Tour.

• Journal of the Korea Institute of Building Construction
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• 제23권4호
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• pp.477-484
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• 2023

Human error, a leading cause of construction accidents, emphasizes the need for minimization to reduce such incidents. However, due to the nature of the construction industry, workers operate within the collective environment of a construction site. Therefore, this study investigates the influence of safety awareness levels within construction sites on the human errors committed by construction workers, from an organizational perspective. The analysis revealed that human errors directly impact construction accidents and that safety awareness levels within construction sites influence the human errors committed by construction workers. Specifically, a strong correlation was observed between slip errors(unintentional actions or oversights) and safety awareness levels in nearly all domains of construction site safety. This study highlights that by elevating safety awareness levels within construction sites, the likelihood of construction worker slips - and by extension, construction accidents - can be significantly reduced.

• The Journal of the Acoustical Society of Korea
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• 제42권4호
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• pp.370-376
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• 2023

In the underwater image, it is not clear to distinguish the shape of the target due to underwater noise and low resolution. In addition, as an input of deep learning, underwater images require pre-processing and segmentation must be preceded. Even after pre-processing, the target is not clear, and the performance of detection and identification by deep learning may not be high. Therefore, it is necessary to distinguish and clarify the target. In this study, the importance of target shadows is confirmed in underwater images, object detection and target area acquisition by shadows, and data containing only the shape of targets and shadows without underwater background are generated. We present the process of converting the shadow image into a 3-mode image in which the target is white, the shadow is black, and the background is gray. Through this, it is possible to provide an image that is clearly pre-processed and easily discriminated as an input of deep learning. In addition, if the image processing code using Open Source Computer Vision (OpenCV)Library was used for processing, the processing speed was also suitable for real-time processing.

• The Journal of the Convergence on Culture Technology
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• 제9권2호
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• pp.575-580
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• 2023

This study was prevent the decrease in crop output by insect pests and spraying by application uniformity. A flight level 4 m height and 4-5 m/sec. speed are difficult to maintain with a agricultural drone for aerial application, which has been affected by the methods or environmental factors, such as changes in the wind. Therefore, which can allow a controlled application width and spray rate automatically and verified experimentally using drone. The sprayed particles began to decrease from about 3.75 m on the left and right sides of the spray nozzle. According to the number of particles, the effective spraying width was observed to be about 7.5 m, and it was verified that the proposed spraying system was effective in uniform control system.

• Proceedings of the Korea Water Resources Association Conference
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• 한국수자원학회 2022년도 학술발표회
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• pp.6-6
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• 2022

최근 수재해에 대응하기 위한 물관리 환경은 기후변화에 따른 홍수 피해 심화와 댐과 하천 시설의 노후화 점증, 하천관리일원화 등 정책적 변화, 그리고 포스트코로나 디지털 혁신 등 복합적 대전환 시대 진입에 따라 복잡다단한 양상을 보이고 있다. 디지털 트윈은 디지털 대전환(digital transformation) 시대 다양한 산업 영역에서 지능화와 생산성 향상을 목적으로 도입되고 있다. 본 국가 시범사업에서는 170 km에 달하는 섬진강 유역 전체를 대상으로 홍수에 대응하기 위한 디지털 트윈 플랫폼(K-Twin SJ)을 구축하고 있다. 본 플랫폼은 국가 인프라 지능정보화 사업의 일환으로 시작되었으며, 공간정보와 시설물 모델링, 홍수 분석 등 수재해에 대응하기 위한 수자원 분야의 다학제적인 강소기업들과 K-water에서 컨소시엄을 구성하여 추진하고 있다. 본 사업의 내용은 섬진강 댐-하천 유역에 대하여 고정밀도 3D 공간정보화, 실시간 물관리 데이터 연계, 홍수 분석 시뮬레이션, AI 댐 운영 최적화, AI 사면 정보 생성, 하천 제방 안전성 평가, AI 지능형 CCTV 영상분석, 간이 침수피해 예측, 드론 제약사항 조사 체계 개발을 포함하고 있다. 물관리 데이터와 하천 시설정보를 트윈 플랫폼 상에서 위치기반으로 시각화 표출하기 위해서는 유역의 공간정보를 3차원으로 구축하는 과정이 필수적이다. 따라서 GIS 기반의 섬진강 하천 중심 공간정보 구축을 위해 유역의 국가 정사영상과 5m 수치표고모형(DEM)은 최신성과를 협조 받아 적용하였으며, 홍수 분석을 위한 하천 중심 공간정보는 신규 헬기에 LiDAR 매핑을 수행하여 0.5m 급 DEM을 신규 구축하였다. 또한 하천 시설물 중 섬진강댐과 79개 주요 하천 횡단 교량과 3개 보 시설을 지상기준점 측량과 드론 매핑, 패턴 방식의 경량화 작업을 통해 트윈에 탑재할 수 있는 시설물 3D 객체 모델을 제작하였다. 홍수 분석을 위해서는 섬진강 유역에 대해 K-Drum, K-River, K-Flood 모델을 구축하였으며, AI 하천 수위 예측 학습 모델을 개발하였다. 섬진강 디지털 트윈 유역 물관리 플랫폼을 통해 데이터 기반의 똑똑한 물관리를 구현하고자 한다.