• Title/Summary/Keyword: hybrid filtering

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직렬형 하이브리드 버스에서 보조동력장치의 고효율 작동을 위한 제어 알고리즘 (A Control Algorithm for Highly Efficient Operation of Auxiliary Power Unit in a Series Hybrid Electric Bus)

  • 함윤영;송승호;민병문;노태수;이재왕;이현동;김철수
    • 한국자동차공학회논문집
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    • 제11권5호
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    • pp.170-175
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    • 2003
  • A control algorithm is developed for highly efficient operation of auxiliary power unit (APU) that consists of a diesel engine and a directly coupled induction generator in series hybrid electric Bus (SHEB). In a series hybrid configuration the APU supplies the electric power needed for maintaining the state of charge (SOC) of the battery unit in various conditions of vehicle operation. As the rotational speed of generator does not depend on the vehicle speed, an optimized operation of engine-generator unit based on the efficiency map of each component can be achieved. The output torque of diesel engine can be controlled by the amount of fuel injection, and the power converted from mechanical to electrical energy can be adjusted by generate control unit (GCU) using the decoupling vector control of torque and flux. As for the given reference of the generating power, the multiply of speed and torque, many combinations of operating speed and torque are possible. The algorithm decides the new operating point based on the engine efficiency map and generator characteristic curve. During the transition of operating points, the speed controller saturation is avoided using variable limit and filtering of generator torque reference. A test rig and SHEB consist of a 1.5L diesel engine and a 30kw induction generator are constructed by Hyundai Motor Company.

Hybrid Fungal Genome Annotation Pipeline Combining ab initio, Evidence-, and Homology-based gene model evaluation

  • Min, Byoungnam;Choi, In-Geol
    • 한국균학회소식:학술대회논문집
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    • 한국균학회 2018년도 춘계학술대회 및 임시총회
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    • pp.22-22
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    • 2018
  • Fungal genome sequencing and assembly have been trivial in these days. Genome analysis relies on high quality of gene prediction and annotation. Automatic fungal genome annotation pipeline is essential for handling genomic sequence data accumulated exponentially. However, building an automatic annotation procedure for fungal genomes is not an easy task. FunGAP (Fungal Genome Annotation Pipeline) is developed for precise and accurate prediction of gene models from any fungal genome assembly. To make high-quality gene models, this pipeline employs multiple gene prediction programs encompassing ab initio, evidence-, and homology-based evaluation. FunGAP aims to evaluate all predicted genes by filtering gene models. To make a successful filtering guide for removal of false-positive genes, we used a scoring function that seeks for a consensus by estimating each gene model based on homology to the known proteins or domains. FunGAP is freely available for non-commercial users at the GitHub site (https://github.com/CompSynBioLab-KoreaUniv/FunGAP).

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리뷰 데이터 마이닝을 이용한 하이브리드 추천시스템 개발: Amazon Kindle Store 데이터 분석사례 (Development of Hybrid Recommender System Using Review Data Mining: Kindle Store Data Analysis Case)

  • 장예화;이청용;최일영;김재경
    • 경영정보학연구
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    • 제23권1호
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    • pp.155-172
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    • 2021
  • 최근 온라인 상품 구매의 증가로 인해 사용자의 선호에 맞는 상품을 추천해주는 시스템이 지속적으로 연구되고 있다. 추천 시스템은 사용자들에게 개인화된 상품 추천 서비스를 제공하는 시스템으로 사용자가 상품에 남긴 평점을 이용한 협업 필터링(Collaborative Filtering)이 가장 널리 쓰이는 추천 방법이다. 협업 필터링에서 상품 간의 유사도 계산은 시간이 많이 소요되는데, 특히 리뷰 데이터와 같은 빅데이터를 사용할 경우 더욱 많은 시간을 소요한다. 그래서 본 연구에서는 리뷰 데이터 마이닝을 이용하여 상품 간의 유사도 계산을 빠르게 수행할 수 있으면서 정확도를 높일 있도록 2단계(2-Phase) 방법을 이용한 하이브리드 추천시스템 방식을 제안한다. 이를 위해 온라인 전자책 상거래 상점인 아마존 킨들 스토어(Amazon Kindle Store)의 약 98만 개의 온라인 소비자 평점과 리뷰 데이터를 수집하였다. 실험 결과 본 연구에서 제안한 사용자의 평점과 리뷰를 단계적으로 반영한 하이브리드 추천 방식이 전통적인 추천 방식과 비교하여 추천 시간은 비슷하였으나 높은 정확도를 나타내는 것을 확인하였다. 따라서 제안한 방법을 사용하면 사용자가 선호하는 상품을 빠르고 정확하게 추천함으로써 고객의 만족을 높여서 기업의 매출 증대에 기여할수 있을 것으로 기대된다.

순차적 추천에서의 RNN, CNN 및 GAN 모델 비교 연구 (A Comparison Study of RNN, CNN, and GAN Models in Sequential Recommendation)

  • 윤지형;정재원;장백철
    • 인터넷정보학회논문지
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    • 제23권4호
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    • pp.21-33
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    • 2022
  • 최근 추천 시스템은 영화, 음악, 온라인 쇼핑 및 SNS 등 다양한 분야들에서 광범위하게 활용되고 있으며, 추천 시스템 분야에서 1세대 모델이라고 할수 있는 Apriori 모델을 통한 연관분석부터 최근 많은 주목을 받는 딥러닝 기반 모델들까지 많은 모델들이 제안되어왔다. 추천 시스템에서 기본 모델들은 협업 필터링(Collaborative filtering) 방법, 콘텐츠 기반 필터링(Content-based filtering) 방법, 그리고 이 두 방법을 통합적으로 사용하는 하이브리드 필터링(Hybrid filtering) 방법으로 분류될 수 있다. 하지만 이러한 모델들은 최근 점점 빠르게 변화하는 사용자-아이템 간의 상호관계와 빅데이터의 발전과 같은 내외 변화 요인들에 적응하지 못하면서 점점 분야 내 방법론으로써의 지위를 잃어가고 있다. 반면, 추천 시스템 내에서 딥러닝 기반 모델들은 비선형 변환, 표현학습, 순차적 모델링, 그리고 유연성과 같은 장점들 때문에 그 비중이 높아지고 있는 추세이다. 본 논문에서는 딥러닝 기반 추천 모델들 중에서도 사용자-아이템 간의 상호작용에 대해 보다 정확하고, 유연성 있게 분석이 가능한 순차적 모델링에 적합한 순환 신경망, 합성곱 신경망, 그리고 생성적 적대 신경망 중심 기반 모델로 분류하여 비교 및 분석한다.

A Nonlinear Information Filter for Tracking Maneuvering Vehicles in an Adaptive Cruise Control Environment

  • Kim, Yong-Shik;Hong, Keum-Shik
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2004년도 ICCAS
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    • pp.1669-1674
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    • 2004
  • In this paper, a nonlinear information filter (IF) for curvilinear motions in an interacting multiple model (IMM) algorithm to track a maneuvering vehicle on a road is investigated. Driving patterns of vehicles on a road are modeled as stochastic hybrid systems. In order to track the maneuvering vehicles, two kinematic models are derived: A constant velocity model for linear motions and a constant-speed turn model for curvilinear motions. For the constant-speed turn model, a nonlinear IF is used in place of the extended Kalman filter in nonlinear systems. The suggested algorithm reduces the root mean squares error for linear motions and rapidly detects possible turning motions.

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Multi-level Scheduling Algorithm Based on Storm

  • Wang, Jie;Hang, Siguang;Liu, Jiwei;Chen, Weihao;Hou, Gang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권3호
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    • pp.1091-1110
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    • 2016
  • Hybrid deployment under current cloud data centers is a combination of online and offline services, which improves the utilization of the cluster resources. However, the performance of the cluster is often affected by the online services in the hybrid deployment environment. To improve the response time of online service (e.g. search engine), an effective scheduling algorithm based on Storm is proposed. At the component level, the algorithm dispatches the component with more influence to the optimal performance node. Inside the component, a reasonable resource allocation strategy is used. By searching the compressed index first and then filtering the complete index, the execution speed of the component is improved with similar accuracy. Experiments show that our algorithm can guarantee search accuracy of 95.94%, while increasing the response speed by 68.03%.

A Novel Hybrid Active Power Filter with a High-Voltage Rank

  • Li, Yan;Li, Gang
    • Journal of Power Electronics
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    • 제13권4호
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    • pp.719-728
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    • 2013
  • A novel hybrid active power filter (NHAPF) that can be adopted in high-voltage systems is proposed in this paper. The topological structure and filtering principle of the compensating system is provided and analyzed, respectively. Different controlling strategies are also presented to select the suitable strategy for the compensation system. Based on the selected strategy, the harmonic suppression function is used to analyze the influence of system parameters on the compensating system with MATLAB. Moreover, parameters in the injection branch are designed and analyzed. The performance of the proposed NHAPF in harmonic suppression and reactive power compensation is simulated with PSim. Thereafter, the overall control method is proposed. Simulation analysis and real experiments show that the proposed NHAPF exhibits good harmonic suppression and reactive power compensation. The proposed compensated system is based on the three-phase four-switch inverter, which is inexpensive, and the control method is verified for validity and effectiveness.

이동로봇의 물체인식 기반 전역적 자기위치 추정 (Object Recognition-based Global Localization for Mobile Robots)

  • 박순용;박민용;박성기
    • 로봇학회논문지
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    • 제3권1호
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    • pp.33-41
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    • 2008
  • Based on object recognition technology, we present a new global localization method for robot navigation. For doing this, we model any indoor environment using the following visual cues with a stereo camera; view-based image features for object recognition and those 3D positions for object pose estimation. Also, we use the depth information at the horizontal centerline in image where optical axis passes through, which is similar to the data of the 2D laser range finder. Therefore, we can build a hybrid local node for a topological map that is composed of an indoor environment metric map and an object location map. Based on such modeling, we suggest a coarse-to-fine strategy for estimating the global localization of a mobile robot. The coarse pose is obtained by means of object recognition and SVD based least-squares fitting, and then its refined pose is estimated with a particle filtering algorithm. With real experiments, we show that the proposed method can be an effective vision- based global localization algorithm.

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순서 통계형-적응 가중평균 혼성필터를 이용한 잡음화된 영상열의 향상 (Enhancement of noisy image sequence using order statistic-adaptive weighted average hybrid filters)

  • 박순영
    • 한국통신학회논문지
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    • 제22권1호
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    • pp.193-204
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    • 1997
  • In this research we propose the design of the Order Statistic-Adaptive Weighted Average Hybrid(OS-AWAH) filter which can suppress noise from the corrupted image sequence effectively while preserving the image structure. The proposed filter combines the desirable properties of the order static based spatial filter which can preserve the image structure while reducing noise and the adaptive weighted average based temporal filter which can adapt the filtering weights according to the amount of motion without motion estimation. Performance characteristics of the OS-AWAH filter in noisy sequences containing moving step edges are investigated throuth computer simulations and compared with the median based filters such as 3-D WM(weighted median) filter, MMF (multistage median filter), ADCWM(adaptive directional center weighted median) filter. The visual evaluations are also carried out by applyin gthe filters to the real images. The statistical analysis and experimental reslts show that the OS-AWAH filter is effective in preserving image structures while suppressing noise effectively without motion compensation preprocessing.

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An IMM Algorithm for Tracking Maneuvering Vehicles in an Adaptive Cruise Control Environment

  • Kim, Yong-Shik;Hong, Keum-Shik
    • International Journal of Control, Automation, and Systems
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    • 제2권3호
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    • pp.310-318
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    • 2004
  • In this paper, an unscented Kalman filter (UKF) for curvilinear motions in an interacting multiple model (IMM) algorithm to track a maneuvering vehicle on a road is investigated. Driving patterns of vehicles on a road are modeled as stochastic hybrid systems. In order to track the maneuvering vehicles, two kinematic models are derived: A constant velocity model for linear motions and a constant-speed turn model for curvilinear motions. For the constant-speed turn model, an UKF is used because of the drawbacks of the extended Kalman filter in nonlinear systems. The suggested algorithm reduces the root mean squares error for linear motions and rapidly detects possible turning motions.