• Journal of Power Electronics
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• 제15권5호
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• pp.1318-1328
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• 2015

The photovoltaic (PV) power conditioning system for small-scale applications has gained significant interest in the past few decades. However, the standalone mode of operation has been rarely approached. This paper presents a two-stage multi-level micro-inverter topology that considers the different operation modes. A multi-output flyback converter provides both the DC-Link voltage balancing for the multi-level inverter side and maximum power point tracking control in grid connection mode in the PV stage. A modified H-bridge multi-level inverter topology is included for the AC output stage. The multi-level inverter lowers the total harmonic distortion and overall ratings of the power semiconductor switches. The proposed micro-inverter topology can help to decrease the size and cost of the PV system. Transient analysis and controller design of this micro-inverter have been proposed for stand-alone and grid-connected modes. Finally, the system performance was verified using a 120 W hardware prototype.

• ETRI Journal
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• 제46권1호
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• pp.82-95
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• 2024

As automated essay scoring (AES) has progressed from handcrafted techniques to deep learning, holistic scoring capabilities have merged. However, specific trait assessment remains a challenge because of the limited depth of earlier methods in modeling dual assessments for holistic and multi-trait tasks. To overcome this challenge, we explore providing comprehensive feedback while modeling the interconnections between holistic and trait representations. We introduce the DualBERT-Trans-CNN model, which combines transformer-based representations with a novel dual-scale bidirectional encoder representations from transformers (BERT) encoding approach at the document-level. By explicitly leveraging multi-trait representations in a multi-task learning (MTL) framework, our DualBERT-Trans-CNN emphasizes the interrelation between holistic and trait-based score predictions, aiming for improved accuracy. For validation, we conducted extensive tests on the ASAP++ and TOEFL11 datasets. Against models of the same MTL setting, ours showed a 2.0% increase in its holistic score. Additionally, compared with single-task learning (STL) models, ours demonstrated a 3.6% enhancement in average multi-trait performance on the ASAP++ dataset.

• 한국실천공학교육학회논문지
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• 제3권2호
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• pp.93-99
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• 2011

영상처리 기술을 이용한 PC정비사 자격증 취득을 돕기 위한 어플리케이션을 소개한다. 요즘 사람들은 컴퓨터의 마우스나, 키보드를 직접 이용하기 보다는 손의 제스쳐, 즉 흥미를 유발시켜 많은 사람들에게 이미지와 그래픽적인 부분을 추가시켜 소개한다. 요즘 화두가 되고 있는 멀티터치 테이블에 3D Maxs, C#을 이용해 각 부품의 Scale 및 Drag를 통해 카메라 뷰를 이동함으로써 효과적으로 자격증 취득을 돕는다. 또한 PC 정비사 국가 자격증에 출제되는 문제를 수록하고, 각 부품을 세부적으로 학습함으로써, 자격증 취득의 기틀을 마련한다. 이에, 본 논문에서는 멀티터치 테이블(MultiTouch-Table) 기반의 학습용 어플리케이션을 제안하고 그 성능을 시험하였다.

• 한국정보통신학회논문지
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• 제9권2호
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• pp.229-236
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• 2005

이 논문은 신호 f(t)의 실제적인 스케일 정보를 나타내는 웨이브렛 플랜을 중심으로 연속 웨이브렛 역변환의 특성에 대하여 논하였다. 웨이브렛 변환에 비해 역변환의 적용이 상대적으로 미비한 이유는 수치적인 연산의 복잡성에 기인한 것이며, 이 논문은 웨이브렛 역변환의 안정된 복원을 위한 방법에 대하여 연구하였다. 웨이브렛 역변환의 안정적인 구현은 신호 f(t)에 대한 실제적인 스케일 정보를 지니고 있는 웨이브렛 플랜이라는 새로운 "시간-스케일" 공간을 통하여 실현하였으며, 이는 완전한 멀티 필터 뱅크 시스템과 동일한 특성을 나타낸다. 즉 연속 웨이브렛 변환을 통해 신호 f(t)의 모든 스케일 성분을 독립적으로 주파수 전체 대역에 걸쳐 분산하고 다시 역변환을 통해 원래의 신호를 복원하는 과정은 필터뱅크이론의 분석과 합성과정과 일치한다 이 논문에서는 연속 웨이브렛 역변환을 이용하여 "시간-스케일" 필터를 통한 신호 f(t)의 스케일 분해와 웨이브렛 멀티 필터 뱅크이론에 대하여 논하였다.

• 대한공간정보학회지
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• 제18권4호
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• pp.101-107
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• 2010

본 연구의 목적은 벡터 도메인 안에 대규모 도로 선형 사상을 대상으로 실시간 데이터 변경, 관리가 가능한 네트워크의 다중 표현 데이터베이스 모델을 구축하는 것이다. 즉, 최상위 레벨의 네트워크 데이터로부터 이에 대응하는 하위 베이스 네트워크 데이터로 순차적으로 데이터 통합과 자동 매칭을 수행하는 상의하달 방식(top-down)을 기초로 하는 프레임워크를 제시하며, 이를 통해 변화 가능한 축척(variable-scale)의 지도를 생성하는 모델을 제안하였다. 구현된 MRDB(Multi-Resolution Database) 모델을 차량 항법 서비스에 적용하여 실제 동적 경로 안내 시스템에 활용 가능함을 확인할 수 있었다.

• Advances in nano research
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• 제3권4호
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• pp.193-206
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• 2015

The present paper investigate the elastic buckling of chiral double-walled carbon nanotubes (DWCNTs) under axial compression. Using the non-local elasticity theory, Timoshenko beam model has been implemented. According to the governing equations of non-local theory, the analytical solution is derived and the solution for non-local critical buckling loads is obtained. The numerical results show the influence of non-local small-scale coefficient, the vibrational mode number, the chirality of carbon nanotube and aspect ratio of the (DWCNTs) on non-local critical buckling loads of the (DWCNTs). The results indicate the dependence of non-local critical buckling loads on the chirality of single-walled carbon nanotube with increase the non-local small-scale coefficient, the vibrational mode number and aspect ratio of length to diameter.

• 한국초전도ㆍ저온공학회논문지
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• 제12권1호
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• pp.42-46
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• 2010

The HTS power cable is composed of 2 layers for transmission and 1 layer for shield. The superconducting tapes of transmission layers and shield layer are wound in a cylindrical shape with a winding pitch. The radius of cylinder and the number of superconducting tapes are decided considering to the transmission current capacity and the critical current of superconducting tapes. The increasement of transmission current capacity will increase in volume of HTS cable system. In this paper, the composition method of supercondcuting power cable using the multi-cable is presented. The coated conductor tape can be wound on the smaller cylinder because it has the smaller critical bending diameter than the BSCCO tape. A small-scale cable was composed using the coated conductor tapes and a multi-cable is composed using a small-scale cable considering to transmission current capacity. Even increase of transmission current capacity, this method has advantage that the HTS superconducting power cable can be composed easily. The 22.9 kV and 154 kV superconducting power cable was composed using the presented method.

• 한국소음진동공학회논문집
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• 제24권8호
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• pp.621-627
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• 2014

In this paper, a possibility of controlling the motion of a floating wind turbine with the tuned liquid damper(TLD) is numerically investigated. First, motion of the scale model of a floating wind turbine without the TLD is predicted and its results are compared to the measured data. There are reasonably good agreements between two results, which confirms validity of the present numerical methods. Then, the effect of TLD is quantitatively assessed by comparing the prediction results for the floating wind turbine with and without the TLD. It is shown that the motion of the scale model derived by external forces can be reduced by using the TLD. On a basis of this result, a multi-layer TLD is proposed to generate larger reaction force of the TLD at the fixed target frequency. The motions of the scale model with the multi-layer TLDs are computed and compared with that of the single-layer TLD. It is shown that the multi-layer TLD generate stronger reaction force and thus more reduce the motion of the floating body than the single-layer TLD.

• Journal of Information Processing Systems
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• 제16권5호
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• pp.1083-1094
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• 2020

Recognizing plant species based on leaf images is challenging because of the large inter-class variation and inter-class similarities among different plant species. The effective extraction of leaf descriptors constitutes the most important problem in plant leaf recognition. In this paper, a multi-scale angular description method is proposed for fast and accurate leaf recognition and retrieval tasks. The proposed method uses a novel scale-generation rule to develop an angular description of leaf contours. It is parameter-free and can capture leaf features from coarse to fine at multiple scales. A fast Fourier transform is used to make the descriptor compact and is effective in matching samples. Both support vector machine and k-nearest neighbors are used to classify leaves. Leaf recognition and retrieval experiments were conducted on three challenging datasets, namely Swedish leaf, Flavia leaf, and ImageCLEF2012 leaf. The results are evaluated with the widely used standard metrics and compared with several state-of-the-art methods. The results and comparisons show that the proposed method not only requires a low computational time, but also achieves good recognition and retrieval accuracies on challenging datasets.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권6호
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• pp.3037-3054
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• 2019

Public bicycle system (PBS) is a new emerging and popular mode of public transportation. PBS data can be adopted to analyze human movement patterns. Previous work usually focused on specific scales, and the relationships between different levels of hierarchies are ignored. In this paper, we introduce a multi-scale and interactive visual analytics system to investigate human cycling movement and PBS usage condition. The system supports level-of-detail explorative analysis of spatio-temporal characteristics in PBS. Visual views are designed from global, regional and microcosmic scales. For the regional scale, a bicycle network is constructed to model PBS data, and an flow-based community detection algorithm is applied on the bicycle network to determine station clusters. In contrast to the previous used Louvain algorithm, our method avoids producing super-communities and generates better results. We provide two cases to demonstrate how our system can help analysts explore the overall cycling condition in the city and spatio-temporal aggregation of stations.