Adipocyte-Specific Deficiency of De Novo Sphingolipid Biosynthesis Leads to Lipodystrophy and Insulin Resistance

Lee, Su-Yeon,Lee, Hui-Young,Song, Jae-Hwi,Kim, Goon-Tae,Jeon, Suwon,Song, Yoo-Jeong,Lee, Jae Sung,Hur, Jang-Ho,Oh, Hyun Hee,Park, Shi-Young,Shim, Soon-Mi,Yoo, Hyun Joo,Lee, Byung Cheon,Jiang, Xian-Che American Diabetes Association 2017 Diabetes Vol.66 No.10

<P>Sphingolipids have been implicated in the etiology of chronic metabolic diseases. Here, we investigated whether sphingolipid biosynthesis is associated with the development of adipose tissues and metabolic diseases. SPTLC2, a subunit of serine palmitoyltransferase, was transcriptionally upregulated in the adipose tissues of obese mice and in differentiating adipocytes. Adipocyte-specific SPTLC2-deficient (aSPTLC2 KO) mice had markedly reduced adipose tissue mass. Fatty acids that were destined for the adipose tissue were instead shunted to liver and caused hepatosteatosis. This impaired fat distribution caused systemic insulin resistance and hyperglycemia, indicating severe lipodystrophy. Mechanistically, sphingosine 1-phosphate (S1P) was reduced in the adipose tissues of aSPTLC2 KO mice, and this inhibited adipocyte proliferation and differentiation via the downregulation of S1P receptor 1 and decreased activity of the peroxisome proliferator-activator receptor gamma. In addition, downregulation of SREBP (sterol regulatory element-binding protein)-1c prevented adipogenesis of aSPTLC2 KO adipocytes. Collectively, our observations suggest that the tight regulation of de novo sphingolipid biosynthesis and S1P signaling plays an important role in adipogenesis and hepatosteatosis.</P>

SAL 탐색기를 장착한 비례항법 기반 유도탄의 초기발사 영역 산출 연구

이수원(Suwon Lee),이석원(Seokwon Lee),이영준(Youngjun Lee),김유단(Youdan Kim),한용수(Yongsu Han) 한국항공우주학회 2020 한국항공우주학회 학술발표회 논문집 Vol.2020 No.7

Bag-of-binary-features for fast image representation

Suwon Lee,Choi, SuGil,Yang, Hyun S. IET 2015 Electronics letters Vol.51 No.7

<P>The possibility of integrating binary features into the bag-of-features (BoFs) model is explored. The set of binary features extracted from an image are packed into a single vector form, to yield the bag-of-binary-features (BoBFs). The efficient BoBF feature extraction and quantisation provide fast image representation. The trade-off between accuracy and efficiency in BoBF compared with BoF is investigated through image retrieval tasks. Experimental results demonstrate that BoBF is a competitive alternative to BoF when the run-time efficiency is critical.</P>

Sleep Mode Detection for Smart TV using Face and Motion Detection

( Suwon Lee ),( Yong-ho Seo ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.7

Sleep mode detection is a significant power management and green computing feature. However, it is difficult for televisions and smart TVs to detect deactivation events because we can use these devices without the assistance of an input device. In this paper, we propose a robust method for smart TVs to detect deactivation events based on a visual combination of face and motion detection. The results of experiments conducted indicate that the proposed method significantly reduces incorrect face detection and human absence by means of motion detection. The results also show that the proposed method is robust and effective for smart TVs to reduce power consumption.

Single-View Reconstruction of a Manhattan World from Line Segments

Lee, Suwon,Seo, Yong-Ho The Institute of Internet 2022 International journal of advanced smart convergenc Vol.11 No.1

Single-view reconstruction (SVR) is a fundamental method in computer vision. Often used for reconstructing human-made environments, the Manhattan world assumption presumes that planes in the real world exist in mutually orthogonal directions. Accordingly, this paper addresses an automatic SVR algorithm for Manhattan worlds. A method for estimating the directions of planes using graph-cut optimization is proposed. After segmenting an image from extracted line segments, the data cost function and smoothness cost function for graph-cut optimization are defined by considering the directions of the line segments and neighborhood segments. Furthermore, segments with the same depths are grouped during a depth-estimation step using a minimum spanning tree algorithm with the proposed weights. Experimental results demonstrate that, unlike previous methods, the proposed method can identify complex Manhattan structures of indoor and outdoor scenes and provide the exact boundaries and intersections of planes.

Quaternion-based 3D Attitude Tracking Algorithm Using Virtual Roll Angle for Missile Systems

Suwon Lee 제어·로봇·시스템학회 2023 International Journal of Control, Automation, and Vol.21 No.10

In this paper, a new type of three-dimensional attitude tracking algorithm for missiles is derived. A virtual roll angleis adopted to obtain additional control availability. The proposed attitude tracking algorithm is analyzed in a four-dimensional quaternion space. Based on the proposed algorithm, the attitude tracking algorithm can be designed more efficiently than in the existing control systems. A nonlinear attitude tracking algorithm is designed for the proposed control system, and an adaptation law for uncertainty is also designed. It is verified through numerical simulations that the proposed control system and tracking algorithm can successfully perform attitude tracking.

Real-time Object Recognition with Pose Initialization for Large-scale Standalone Mobile Augmented Reality

( Suwon Lee ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.10

Mobile devices such as smartphones are very attractive targets for augmented reality (AR) services, but their limited resources make it difficult to increase the number of objects to be recognized. When the recognition process is scaled to a large number of objects, it typically requires significant computation time and memory. Therefore, most large-scale mobile AR systems rely on a server to outsource recognition process to a high-performance PC, but this limits the scenarios available in the AR services. As a part of realizing large-scale standalone mobile AR, this paper presents a solution to the problem of accuracy, memory, and speed for large-scale object recognition. To this end, we design our own basic feature and realize spatial locality, selective feature extraction, rough pose estimation, and selective feature matching. Experiments are performed to verify the appropriateness of the proposed method for realizing large-scale standalone mobile AR in terms of efficiency and accuracy.

Face representation using multiple codebook learning

Suwon Lee ICT플랫폼학회 2017 JOURNAL OF PLATFORM TECHNOLOGY Vol.5 No.4

초등학교 블렌디드 러닝에서 맞춤형 학습을 위한 학습자 군집 탐색

이수원 ( Suwon Lee ),한예진 ( Ye Jin Han ),이승민 ( Seungmin Lee ),조영환 ( Young Hoan Cho ) 한국교육공학회 2022 교육공학연구 Vol.38 No.1

최근 코로나19 팬데믹으로 서로 다른 수업방법과 교육매체를 통합하는 블렌디드 러닝(blended learning)의 중요성이 초등학교에서 증가하고 있다. 블렌디드 러닝에 대한 관심이 증가하고 있지만, 교사가 학습자의 온라인 활동을 관찰하기 어렵고 학습자의 다양한 특성을 종합적으로 판단하기 어렵다는 제한점이 있다. 교사가 학습자의 요구를 쉽게 파악하고 맞춤형 학습지원을 효과적으로 제공할 수 있도록 학습자를 군집으로 구분하고 각 군집에 필요한 학습자료와 스캐폴딩을 제공할 필요가 있다. 본 연구는 블렌디드 러닝에서 온라인과 면대면 학습 데이터를 활용하여 초등학생의 군집을 탐색하고 군집 간 차이점을 비교하였다. 한 달 동안 초등학교 4학년 학생들(n=70)의 수학학습 데이터를 수집하였으며, 블렌디드 러닝에서 활용된 학습관리시스템에서 온라인 학습 데이터를 수집하고, 면대면 수업에서 수학 성취도 평가 점수와 동기, 성취정서, 자기효능감, 자기조절학습에 대한 설문조사 자료를 수집하였다. 수집된 데이터에 대한 군집분석을 실시한 결과, (1) 통합 지원이 필요한 군집, (2) 온라인 학습참여와 성적이 높은 군집, (3) 긍정정서를 가지고 있으며 자기조절학습 능력이 높은 군집으로 구분되었다. 그리고 담임교사 4명을 대상으로 학습자 군집의 유용성에 대한 면담을 실시하였다. 교사들은 군집분석 결과가 자신이 인지하지 못한 학습자들의 특성을 보여주고 학습자를 종합적으로 이해하는 것을 돕기 때문에 블렌디드 러닝에서 맞춤형 학습을 지원하는 데 유용하다고 인식했다. 향후 우리나라 학습자들의 고유한 특성을 다각도로 이해하고 다양한 학습자를 위한 맞춤형 학습환경을 개발하기 위해 군집분석을 체계적으로 실시할 필요가 있다. During the COVID-19 pandemic, teachers have emphasized the importance of blended learning in elementary schools by integrating different instructional methods and educational media. Despite the growing interest in blended learning, teachers have difficulties in observing online learning activities and understanding students’ characteristics comprehensively. To identify students’ needs easily and provide effective personalized learning support, it is essential for teachers to identify a few clusters of learners and provide learning materials and necessary support for each cluster. In this study, clusters of elementary school students were explored by employing blended learning data of achievements, affective characteristics, self-regulated learning skills, and online learning participation. We collected fourth graders’ mathematics learning data (n=70) for a month. The data included online learning data collected from a learning management system and face-to-face learning data such as assessment scores and surveys of motivation, achievement emotion, self-efficacy, and self-regulated learning. Cluster analysis revealed three clusters of elementary school students: (1) those who needed integrated support, (2) those with positive affective characteristics and high-level self-regulated learning skills, and (3) those with high-level online learning participation and achievement. Interviews with four homeroom teachers revealed that the clusters may be beneficial in understanding learners comprehensively and supporting personalized learning in blended learning. It is recommended that future research should conduct cluster analysis to explore Korean learners’ unique characteristics and develop personalized learning environments for a diverse group of students.

글라이더 비행체의 벡터 기반 비행속력 제어 유도기법

이수원(Suwon Lee),김유단(Youdan Kim) 한국항공우주학회 2018 한국항공우주학회 학술발표회 논문집 Vol.2018 No.11