• 한국콘텐츠학회논문지
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• 제22권4호
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• pp.519-534
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• 2022

본 연구는 어린이집 교사의 2019 개정 누리과정 놀이중심 교육 경험의 실제와 인식을 구체적으로 파악하여 유아교육 현장의 현실적 지원 정책을 마련하고자 하였다. 이를 위해 현 누리과정 교육 경험이 있는 서울 및 경기도 소재 어린이집 교사를 대상으로 개별 심층면담을 실시하였으며, 수집한 자료는 Hatch(2002)의 유형적 분석과 해석적 분석 그리고 Seidman(2006)의 면담 자료분석을 사용하여 시사점을 도출하였다. 본 연구 결과 첫째, 유치원과 어린이집은 동일한 통합 개정 누리과정을 적용하고 있지만, 어린이집은 보육적 관점과 안전을 더 고려한 교육을 지향하고 있다. 둘째, 교사들은 유아들이 주체가 되는 자기주도적인 열린 놀이활동 연계과정에서 교육적 매칭에 어려움이 존재하였다. 셋째, 교사들의 놀이활동에 대한 교육적 이해와 가치 파악 능력은 유아 상호작용 및 유대관계 성장에 기여한다. 결론적으로 현 누리과정의 효과적인 교육 시행을 위한 교사교육과 교류지원 그리고 유아비율 조정의 국가적 정책 방안이 시급하다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권11호
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• pp.3991-4010
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• 2021

The Question Similarity Measurement of Chinese Crop Diseases and Insect Pests (QSM-CCD&IP) aims to judge the user's tendency to ask questions regarding input problems. The measurement is the basis of the Agricultural Knowledge Question and Answering (Q & A) system, information retrieval, and other tasks. However, the corpus and measurement methods available in this field have some deficiencies. In addition, error propagation may occur when the word boundary features and local context information are ignored when the general method embeds sentences. Hence, these factors make the task challenging. To solve the above problems and tackle the Question Similarity Measurement task in this work, a corpus on Chinese crop diseases and insect pests(CCDIP), which contains 13 categories, was established. Then, taking the CCDIP as the research object, this study proposes a Chinese agricultural text similarity matching model, namely, the AgrCQS. This model is based on mixed information extraction. Specifically, the hybrid embedding layer can enrich character information and improve the recognition ability of the model on the word boundary. The multi-scale local information can be extracted by multi-core convolutional neural network based on multi-weight (MM-CNN). The self-attention mechanism can enhance the fusion ability of the model on global information. In this research, the performance of the AgrCQS on the CCDIP is verified, and three benchmark datasets, namely, AFQMC, LCQMC, and BQ, are used. The accuracy rates are 93.92%, 74.42%, 86.35%, and 83.05%, respectively, which are higher than that of baseline systems without using any external knowledge. Additionally, the proposed method module can be extracted separately and applied to other models, thus providing reference for related research.

• 한국인터넷방송통신학회논문지
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• 제22권3호
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• pp.37-42
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• 2022

본 논문에서는 낮은 삽입 손실을 가지는 광대역 마이크로스트립-도파관 전이구조를 제안하였다. 제안하는 전이구조는 자연스러운 전계분포의 필드 변환과 마이크로스트립 선로와 fin-line 사이의 임피던스 정합의 관점에서 설계되었다. Offset DSPSL (double-sided parallel stripline)을 이용한 fin-line 테이퍼로 전이구조의 길이 및 그 구조를 결정할 수 있도록 하였다. 제작된 전이구조의 특성은 전이구조 당 85 ~ 108 GHz의 대역에서 0.67 dB 이하의 낮은 삽입 손실을 가지고 있으며, 83 ~ 110 GHz 이상의 대역에서 1 dB 이하의 삽입 손실을 가짐을 확인하였다. 본 논문에서 제시한 전이구조를 이용하여 W-대역의 초소형 레이다 및 다양한 응용 분야에 적용 가능하리라 예상된다.

• 패션비즈니스
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• 제26권4호
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• pp.64-82
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• 2022

This study aimed to explore fashion technologies for small-scale designer brands and reveal the priorities of the derived fashion technologies. Interviews were conducted with owners of 15 designer brands to explore fashion technologies needed in the field based on the business operation stage (study 1), and an online survey of owners of 61 designer brands was conducted to verify their priorities (study 2). A total of 12 fashion technologies were derived from study 1, including 2 market analysis stages, 6 season planning stages, and 4 product operation stages. In study 2, importance and satisfaction were measured with 12 fashion techniques derived from study 1, and importance-performance analysis (IPA) was performed. The technologies of product management with image tagging and sales channel matching were considered to be the fashion technologies that should be developed first. Second, in the case of maintenance, demand prediction and price determination were applicable. Third, over-effort avoidance was revealed through market analysis and design generation. Finally, in automatic product detail page creation and digital marketing, development was the lowest priority. The results of this study are expected to provide insight into priority areas for fashion technology developers and policy departments providing emerging brand support.

• 한국해양공학회지
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• 제36권5호
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• pp.340-352
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• 2022

This article presents a modeling method for the uncorrelated measurement error of the ultra-short baseline (USBL) acoustic positioning system for aiding navigation of underwater vehicles. The Mahalanobis distance (MD) and principal component analysis are applied to decorrelate the errors of USBL measurements, which are correlated in the x- and y-directions and vary according to the relative direction and distance between a reference station and the underwater vehicles. The proposed method can decouple the radial-direction error and angular direction error from each USBL measurement, where the former and latter are independent and dependent, respectively, of the distance between the reference station and the vehicle. With the decorrelation of the USBL errors along the trajectory of the vehicles in every time step, the proposed method can reduce the threshold of the outlier decision level. To demonstrate the effectiveness of the proposed method, simulation studies were performed with motion data obtained from a field experiment involving an autonomous underwater vehicle and USBL signals generated numerically by matching the specifications of a specific USBL with the data of a global positioning system. The simulations indicated that the navigation system is more robust in rejecting outliers of the USBL measurements than conventional ones. In addition, it was shown that the erroneous estimation of the navigation system after a long USBL blackout can converge to the true states using the MD of the USBL measurements. The navigation systems using the uncorrelated error model of the USBL, therefore, can effectively eliminate USBL outliers without loss of uncontaminated signals.

• Journal of Korea Trade
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• 제27권3호
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• pp.179-198
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• 2023

Purpose - There is a paucity of literature dealing with exporters' compliance issues in e-commerce exports. This study aims to fill this gap in the literature by exploring customs initiatives to facilitate the e-commerce exports of small and medium-sized enterprises (SMEs) in the changed compliance environment. The central question of this study was divided into five subquestions: first regarding the pros and cons of trade facilitation measures for Korean e-commerce export clearance; second and third questions about risk and compliance management for facilitation fourth about instruments, the changes in Korean SME compliance burden in e-commerce exports, and ways to improve trade facilitation for e-commerce exports. Design/methodology - This study adopts a qualitative approach using a case study method to understand the SME experience in Korean e-commerce export compliance procedures. A qualitative method was selected to answer research questions requiring an in-depth understanding of the regulatory procedures of customs administration and exporters' compliance burden. Because this study addresses the changing compliance environment for which statistical data is insufficient, a quantitative method is considered inappropriate. Based on the approach, data were collected using multiple sources, including an extensive literature review, interviews, and field observations. Thematic pattern matching was applied to interpret the data. Findings - This study examined ways to support SMEs in the changed e-commerce export compliance environment. Facilitation measures for e-commerce exports have contributed to SME access to global markets, simplifying export clearance procedures, and saving exporters' compliance costs. However, such instruments are limited in promoting SME compliance capabilities to cope with intensified competition and strengthened controls over foreign exporters in cross-border e-commerce. Therefore, this study highlights the importance of reshaping facilitation measures for e-commerce exports based on risk and compliance management theories to a system encouraging exporters' voluntary compliance. Originality/value - This study's academic significance derives from verifying the relationship between trade facilitation instruments and risk and compliance management procedures using an actual case in Korea. It is also of practical importance in navigating the directions for improving facilitation measures for e-commerce exports in a changed compliance environment.

• 한국지형학회지
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• 제27권3호
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• pp.87-103
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• 2020

The purpose of this study is to evaluate the risk of cropland and man-made infrastructures in a landslide-prone area using a GIS-based method. To achieve this goal, a landslide inventory map was prepared based on aerial photograph analysis as well as field observations. A total of 550 landslides have been counted in the entire study area. For model analysis and validation, extracted landslides were randomly selected and divided into two groups. The landslide causative factors such as slope, aspect, curvature, topographic wetness index, elevation, forest type, forest crown density, geology, land-use, soil drainage, and soil texture were used in the analysis. Moreover, to identify the correlation between landslides and causative factors, pixels were divided into several classes and frequency ratio was also extracted. A landslide susceptibility map was constructed using a bayesian predictive model (BPM) based on the entire events. In the cross validation process, the landslide susceptibility map as well as observation data were plotted with a receiver operating characteristic (ROC) curve then the area under the curve (AUC) was calculated and tried to extract a success rate curve. The results showed that, the BPM produced 85.8% accuracy. We believed that the model was acceptable for the landslide susceptibility analysis of the study area. In addition, for risk assessment, monetary value (local) and vulnerability scale were added for each social thematic data layers, which were then converted into US dollar considering landslide occurrence time. Moreover, the total number of the study area pixels and predictive landslide affected pixels were considered for making a probability table. Matching with the affected number, 5,000 landslide pixels were assumed to run for final calculation. Based on the result, cropland showed the estimated total risk as US $ 35.4 million and man-made infrastructure risk amounted to US $ 39.3 million.

• 한국전자통신학회논문지
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• 제18권6호
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• pp.1307-1312
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• 2023

본 논문에서는 자율주행 인지 기술의 핵심 요소인 객체 인식과 거리 측정을 위해 서로 다른 초점거리를 가진 다시점 카메라와 라이다(LiDAR) 센서를 결합한 복합형 카메라 시스템을 제안한다. 제안한 복합형 카메라 시스템을 이용해 장면 안의 객체를 추출하고, 추출한 객체의 정확한 위치와 거리 정보를 생성한다. 빠른 계산 속도와 높은 정확도, 실시간 처리가 가능하다는 장점 때문에 자율주행 분야에서 많이 사용하고 있는 YOLO7 알고리즘을 이용해 장면 안의 객체를 추출한다. 그리고 객체의 위치와 거리 정보를 생성하기 위해 다시점 카메라를 이용해 깊이맵을 생성한다. 마지막으로 거리 정확도를 향상시키기 위해 라이다 센서에서 획득한 3차원 거리 정보와 생성한 깊이맵을 하나로 결합한다. 본 논문에서는 제안한 복합형 카메라 시스템을 기반으로 주행중인 주변 환경을 더욱 정확하게 인식함과 동시에 3차원 공간상의 정확한 위치와 거리 정보까지 생성할 수 있는 자율주행 차량 플랫폼을 제안하였으며, 이를 통해 자율주행 차량의 안전성과 효율성을 향상시킬 수 있을 것으로 기대한다.

• 한국BIM학회 논문집
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• 제13권4호
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• pp.96-105
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• 2023

This study focuses on developing a building object recognition technology for efficient use in the remodeling of buildings constructed without drawings. In the era of the 4th industrial revolution, smart technologies are being developed. This research contributes to the architectural field by introducing a deep learning-based method for automatic object classification and recognition, utilizing point cloud data. We use a TD3D network with voxels, optimizing its performance through adjustments in voxel size and number of blocks. This technology enables the classification of building objects such as walls, floors, and roofs from 3D scanning data, labeling them in polygonal forms to minimize boundary ambiguities. However, challenges in object boundary classifications were observed. The model facilitates the automatic classification of non-building objects, thereby reducing manual effort in data matching processes. It also distinguishes between elements to be demolished or retained during remodeling. The study minimized data set loss space by labeling using the extremities of the x, y, and z coordinates. The research aims to enhance the efficiency of building object classification and improve the quality of architectural plans by reducing manpower and time during remodeling. The study aligns with its goal of developing an efficient classification technology. Future work can extend to creating classified objects using parametric tools with polygon-labeled datasets, offering meaningful numerical analysis for remodeling processes. Continued research in this direction is anticipated to significantly advance the efficiency of building remodeling techniques.

• Computers and Concrete
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• 제33권5호
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• pp.535-544
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• 2024

In the rapidly advancing landscape of computer vision (CV) technology, there is a burgeoning interest in its integration with the construction industry. Camera calibration is the process of deriving intrinsic and extrinsic parameters that affect when the coordinates of the 3D real world are projected onto the 2D plane, where the intrinsic parameters are internal factors of the camera, and extrinsic parameters are external factors such as the position and rotation of the camera. Camera pose estimation or extrinsic calibration, which estimates extrinsic parameters, is essential information for CV application at construction since it can be used for indoor navigation of construction robots and field monitoring by restoring depth information. Traditionally, camera pose estimation methods for cameras relied on target objects such as markers or patterns. However, these methods, which are marker- or pattern-based, are often time-consuming due to the requirement of installing a target object for estimation. As a solution to this challenge, this study introduces a novel framework that facilitates camera pose estimation using standardized materials found commonly in construction sites, such as concrete forms. The proposed framework obtains 3D real-world coordinates by referring to construction materials with certain specifications, extracts the 2D coordinates of the corresponding image plane through keypoint detection, and derives the camera's coordinate through the perspective-n-point (PnP) method which derives the extrinsic parameters by matching 3D and 2D coordinate pairs. This framework presents a substantial advancement as it streamlines the extrinsic calibration process, thereby potentially enhancing the efficiency of CV technology application and data collection at construction sites. This approach holds promise for expediting and optimizing various construction-related tasks by automating and simplifying the calibration procedure.