• 무역학회지
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• 제44권5호
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• pp.17-28
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• 2019

Although brand love is a major interest in global business, very little is known about how the effects of brand love are affected by relevant constructs. This study examines how the brand love-loyalty link is moderated by shopping value (hedonic vs. utilitarian) and how the moderated moderation effect of gender difference influences the consumer-brand relationship. Based on a unique dataset of 254 Chinese consumers of Korean cosmetic brands in China, we tested our proposed hypotheses using Regression PROCESS macro (model = 3). One of our novel findings is that brand love has a positive influence on brand loyalty. However, this relationship is sensitive to moderators. Regarding the brand love-loyalty linkage, consumers who seek hedonic shopping value is higher than consumers who seek utilitarian shopping value. In particular, female consumers are more passionate and loyal than male consumers. Finally, male consumers seeking hedonic shopping value feature greater brand love-loyal linkage than other consumers; however, this effect is very limited.

• 로봇학회논문지
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• 제16권3호
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• pp.238-244
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• 2021

Image mosaicking is a common and useful technique to visualize a global map by stitching a large number of local images obtained from visual surveys in underwater environments. In particular, visual inspection of underwater structures using underwater robots can be a potential application for image mosaicking. Feature-based pairwise image registration is a commonly employed process in most image mosaicking algorithms to estimate visual odometry information between compared images. However, visual features are not always uniformly distributed on the surface of underwater structures, and thus the performance of image registration can vary significantly, which results in unnecessary computations in image matching for poor-conditioned image pairs. This study proposes a pairwise registrability measure to select informative image pairs and to improve the overall computational efficiency of underwater image mosaicking algorithms. The validity and effectiveness of the image mosaicking algorithm considering the pairwise registrability are demonstrated using an experimental dataset obtained with a full-scale ship in a real sea environment.

• Journal of Information Processing Systems
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• 제18권5호
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• pp.711-718
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• 2022

In this paper, an accurate segmentation algorithm of video dynamic background image (VDBI) based on improved wavelet transform is proposed. Based on the smooth processing of VDBI, the traditional wavelet transform process is improved, and the two-layer decomposition of dynamic image is realized by using two-dimensional wavelet transform. On the basis of decomposition results and information enhancement processing, image features are detected, feature points are extracted, and quantum ant colony algorithm is adopted to complete accurate segmentation of the image. The maximum SNR of the output results of the proposed algorithm can reach 73.67 dB, the maximum time of the segmentation process is only 7 seconds, the segmentation accuracy shows a trend of decreasing first and then increasing, and the global maximum value can reach 97%, indicating that the proposed algorithm effectively achieves the design expectation.

• ETRI Journal
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• 제44권6호
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• pp.915-924
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• 2022

In this paper, we present a two-stage scalable channel estimator (TSCE), a deep learning (DL)-based scalable, and robust channel estimator for wireless cellular networks, which is made up of two DL networks to efficiently support different resource allocation sizes and reference signal configurations. Both networks use the transformer, one of cutting-edge neural network architecture, as a backbone for accurate estimation. For computation-efficient global feature extractions, we propose using window and window averaging-based self-attentions. Our results show that TSCE learns wireless propagation channels correctly and outperforms both traditional estimators and baseline DL-based estimators. Additionally, scalability and robustness evaluations are performed, revealing that TSCE is more robust in various environments than the baseline DL-based estimators.

• Journal of Forest and Environmental Science
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• 제26권3호
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• pp.181-192
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• 2010

Water erosion is progressing in the Loess Plateau, especially in gullies, and the sediment runoff to the Yellow River amounts to 975 million tons every year. Natural factors for water erosion include climate, soil, geological feature, terrain and vegetation. Many development projects due to the increasing population reduced the forest coverage ratio to 10%, and 200 million people in the downstream area are suffering from the damage during intense rainfall. Accordingly, the Chinese government is continuously trying to efficiently prevent the erosion by establishing measures for water erosion, including fish-scale pits, terrace technique, and check dams.

• 대한융합한의학회지
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• 제1권1호
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• pp.5-15
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• 2021

Objectives: To review the concept of Moebius syndrome. Methods: Literature search was done to study definition, epidemiology, pathophysiology, clinical feature, and treatment of Moebius syndrome. Pubmed, RISS, Google scholarship and uptodate scholastic were used in the research. Search words were 'Moebius syndrome', 'treatment of Moebius syndrome'. Only English and Korean studies were assessed. Results: Moebius syndrome is rare disease characterized by nonprogressive congenital uni- or bi-lateral facial (VII cranial nerve) and abducens (VI cranial nerve) palsy. This facial palsy is found across the world, and its incidence is approximately 1 per 250,000. Moebius is diagnosed by clinical features. Facial palsy, eye abduction problem, limb deformities, global cerebral nerve impairment can be shown. Rehabilitation, smile surgery, and acupuncture can be used to treat this. Conclusion: Moebius syndrome's epidemiology, pathogenesis, treatment is still not fully revealed. It is known to be a congenital disease which didn't have exact treatment except surgery. But, it needs further study about exact treatment, diagnosis, and pathogenesis.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2022년도 제66차 하계학술대회논문집 30권2호
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• pp.563-566
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• 2022

본 논문에서는 증강현실에서 객체 증강 시, 특징점과 GPS를 이용하여 증강 위치를 효율적으로 보간할 수 있는 ICP(Iterative closest point) 매칭 기법을 제안한다. 다양한 환경에서 제한받지 않고 객체를 증강하기 위해 일반적으로 마커리스(Markerless) 방식을 사용하며, 대표적으로 평면 검출과 페이스 검출을 사용한다. 이는 현실과 자연스러운 동기화를 위한 것으로 계산은 작지만, 인식의 범위가 넓기 때문에 증강 위치에 대한 오차가 존재한다. 이러한 작은 오차는 특정 산업에서는 치명적일 수 있으며, 특히 건설이나 의료시설에서 발생하면 큰 사고로 이어진다. 객체를 증강 시킬 때 해당 환경에 대한 점 구름(Point cloud)을 수집하여 데이터베이스에 저장한다. 본 논문에서는 관측되는 점 구름과의 오차를 줄이기 위해 ICP 매칭 기법을 사용하며, 실린더 기반의 각도 보간을 이용하여 계산량을 줄인다. 결과적으로 특징점과 GPS를 이용하여 ICP 매칭 기법을 통해 효율적으로 처리함으로써, 증강 위치에 대한 정확도가 개선된 증강 방식을 보여준다.

• ETRI Journal
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• 제46권3호
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• pp.513-525
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• 2024

Deep neural networks trained on labeled medical data face major challenges owing to the economic costs of data acquisition through expensive medical imaging devices, expert labor for data annotation, and large datasets to achieve optimal model performance. The heterogeneity of diseases, such as Alzheimer's disease, further complicates deep learning because the test cases may substantially differ from the training data, possibly increasing the rate of false positives. We propose a reconstruction-based self-supervised anomaly detection model to overcome these challenges. It has a dual-subnetwork encoder that enhances feature encoding augmented by skip connections to the decoder for improving the gradient flow. The novel encoder captures local and global features to improve image reconstruction. In addition, we introduce an entropy-based image conversion method. Extensive evaluations show that the proposed model outperforms benchmark models in anomaly detection and classification using an encoder. The supervised and unsupervised models show improved performances when trained with data preprocessed using the proposed image conversion method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.174-179
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• 2003

Through the simultaneous localization and map building (SLAM) technique, a robot can create maps about its unknown environment while it continuously localizes its position. Grid maps and feature maps have been widely used for SLAM together with application of probability methods and POMDP (partially observed Markov decision process). But this approach based on grid maps suffers from enormous computational burden. Topological maps, however, have drawn more attention these days because they are compact, provide natural interfaces, and are easily applicable to path planning in comparison with grid maps. Some topological SLAM techniques like GVG (generalized Voronoi diagram) were introduced, but it enables the robot to decide only whether the current position is part of GVG branch or not in the GVG algorithm. In this paper, therefore, to overcome these problems, we present a method for updating a global topological map from the local topological maps. These local topological maps are created through a labeled Voronoi diagram algorithm from the local grid map built based on the sensor information at the current robot position. And the nodes of a local topological map can be utilized as the features of the environment because it is robust in light of visibility problem. The geometric information of the feature is applied to the extended Kalman filter and the SLAM in the indoor environment is accomplished. A series of simulations have been conducted using a two-wheeled mobile robot equipped with a laser scanner. It is shown that the proposed scheme can be applied relatively well.