• 제목/요약/키워드: matching prediction

검색결과 201건 처리시간 0.028초

Performance Prediction of an OWC Wave Power Plant with 3-D Characteristics in Regular Waves

  • Hong, Do-Chun;Hong, Keyyong
    • 한국항해항만학회지
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    • 제36권9호
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    • pp.729-735
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    • 2012
  • The primary wave energy conversion by a three-dimensional bottom-mounted oscillating water column (OWC) wave power device in regular waves has been studied. The linear potential boundary value problem has been solved following the boundary matching method. The optimum shape parameters such as the chamber length and the depth of the front skirt of the OWC chamber obtained through two-dimensional numerical tests in the frequency domain have been applied in the design of the present OWC chamber. Time-mean wave power converted by the OWC device and the time-mean second-order wave forces on the OWC chamber structure have been presented for different wave incidence angles in the frequency-domain. It has been shown that the peak period of $P_m$ for the optimum damping parameter coincides with the peak period of the time.mean wave drift force when ${\gamma}=0$.

Group-affiliated Firms and Corporate Social Responsibility Activities

  • Lee, Woo Jae
    • The Journal of Asian Finance, Economics and Business
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    • 제5권4호
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    • pp.127-133
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    • 2018
  • Corporate social responsibility (CSR) is one of the strategies for managing firms' business activities but may have heterogeneity depending on ownership structures. This study investigates the association between group-affiliation and CSR activities. Drawing on a theory from the prior research, this study predicts that group-affiliated firms are less likely to invest on CSR activities. For instance, prior research finds that controlling shareholders expropriate the values of minority shareholders. As one of the motivations of investing on CSR activities is the harmonization among the stakeholders, it leads to the prediction that firms controlled by large shareholders are less likely to engage in CSR activities. Second, group-affiliated firms under poor financial performance benefit from other group members through sharing their financial resources. Thus, there is less incentive for managers of group-affiliated firms to increase their financial performance by conducting CSR. By leveraging firms listed in Korean stock market and CSR score from Korea Economic Justice Institute, the result shows that the group-affiliation is negatively related to CSR activities. The result is consistent in case of applying propensity score-matched sample. Based on the findings of this study, this paper contributes to the related literature by showing the significant association between group-affiliation and CSR decisions.

FRACTAL CODING OF VIDEO SEQUENCE USING CPM AND NCIM

  • Kim, Chang-Su;Kim, Rin-Chul;Lee, Sang-Uk
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 1996년도 Proceedings International Workshop on New Video Media Technology
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    • pp.72-76
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    • 1996
  • We propose a novel algorithm for fractal video sequence coding, based on the circular prediction mapping (CPM), in which each range block is approximated by a domain block in the circularly previous frame. In our approach, the size of the domain block is set to be same as that of the range block for exploiting the high temporal correlation between the adjacent frames, while most other fractal coders use the domain block larger than the range block. Therefore the domain-range mapping in the CPM is similar to the block matching algorithm in the motion compensation techniques, and the advantages of this similarity are discussed. Also we show that the CPM can be combined with non-contractive inter-frame mapping (NCIM), improving the performance of the fractal sequence coder further. The computer simulation results on real image sequences demonstrate that the proposed algorithm provides very promising performance at low bit-rate, ranging from 40 Kbps to 250 Kbps.

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간이단열온도로서 콘크리트의 단열온도 추정을 위한 연구 (Prediction of Adiabatic Temperature in Concrete as Semiadiabatic Temperature)

  • 문한영;문대중
    • 한국구조물진단유지관리공학회 논문집
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    • 제5권4호
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    • pp.121-129
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    • 2001
  • The semi-adiabatic temperature rise and the losses of temperature of cement paste, mortar and concrete were measured by an apparatus of semi-adiabatic temperature. Heat of hydration was measured by a conduction calorimeter and adiabatic temperature rise of concrete was measured by an adiabatic calorimeter. The derived equation which can assume the adiabatic temperature was proposed by measuring the semi-adiabatic temperature of concrete. The maximum adiabatic temperature rise of concrete obtained by the derived equation of adiabatic temperature, $T_{ad}(t)=T_{sad}(t)+T_{dis}(t)$, showed $55^{\circ}C$ approximately and it had good relation with the other one obtained by the heat of hydration of cement paste and with maximum value which was measured by the adiabatic calorimeter. The adiabatic temperature rise obtained by derived equation was a different information in comparison with the value obtained by adiabatic temperature rise equations by Hell and et. al. in early age, but it showed similar tendencies with the other one according to elapsed time. Adiabatic temperature rise of lich mix concrete with highly cement content was predicted. The adiabatic temperature rise of cement paste and mortar obtained by derived equation from us showed comparatively matching results to compared with that of obtained by adiabatic temperature equation from concrete standard specification.

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적응적 탐색 영역 예측을 이용한 고속 움직임 추정 (Fast Motion Estimation using Adaptive Search Region Prediction)

  • 류권열
    • 한국정보통신학회논문지
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    • 제12권7호
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    • pp.1187-1192
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    • 2008
  • 본 논문은 적응적 탐색 영역과 새로운 3단계 탐색을 이용하는 고속 움직임 추정을 제안한다. 제안한 방법은 이웃 블록의 모션벡터로부터 현재 블록의 움직임를 예측하고, 예측된 움직임 정보를 이용하여 탐색 영역을 적응적으로 설정함으로써 움직임 보상 영상의 화질이 $0.43dB{\sim}2.19dB$ 향상되었다. 또한 새로운 3단계 탐색 패턴을 적용하여 블록 당 계산량을 기존의 방법에 비해 $1.3%{\sim}1.9%$ 감소시킴으로써 고속 움직임 추정이 가능함을 알 수 있었다.

Audio Fingerprint Retrieval Method Based on Feature Dimension Reduction and Feature Combination

  • Zhang, Qiu-yu;Xu, Fu-jiu;Bai, Jian
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권2호
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    • pp.522-539
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    • 2021
  • In order to solve the problems of the existing audio fingerprint method when extracting audio fingerprints from long speech segments, such as too large fingerprint dimension, poor robustness, and low retrieval accuracy and efficiency, a robust audio fingerprint retrieval method based on feature dimension reduction and feature combination is proposed. Firstly, the Mel-frequency cepstral coefficient (MFCC) and linear prediction cepstrum coefficient (LPCC) of the original speech are extracted respectively, and the MFCC feature matrix and LPCC feature matrix are combined. Secondly, the feature dimension reduction method based on information entropy is used for column dimension reduction, and the feature matrix after dimension reduction is used for row dimension reduction based on energy feature dimension reduction method. Finally, the audio fingerprint is constructed by using the feature combination matrix after dimension reduction. When speech's user retrieval, the normalized Hamming distance algorithm is used for matching retrieval. Experiment results show that the proposed method has smaller audio fingerprint dimension and better robustness for long speech segments, and has higher retrieval efficiency while maintaining a higher recall rate and precision rate.

Analysis of Inter-satellite Ranging Precision for Gravity Recovery in a Satellite Gravimetry Mission

  • Kim, Pureum;Park, Sang-Young;Kang, Dae-Eun;Lee, Youngro
    • Journal of Astronomy and Space Sciences
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    • 제35권4호
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    • pp.243-252
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    • 2018
  • In a satellite gravimetry mission similar to GRACE, the precision of inter-satellite ranging is one of the key factors affecting the quality of gravity field recovery. In this paper, the impact of ranging precision on the accuracy of recovered geopotential coefficients is analyzed. Simulated precise orbit determination (POD) data and inter-satellite range data of formation-flying satellites containing white noise were generated, and geopotential coefficients were recovered from these simulated data sets using the crude acceleration approach. The accuracy of the recovered coefficients was quantitatively compared between data sets encompassing different ranging precisions. From this analysis, a rough prediction of the accuracy of geopotential coefficients could be obtained from the hypothetical mission. For a given POD precision, a ranging measurement precision that matches the POD precision was determined. Since the purpose of adopting inter-satellite ranging in a gravimetry mission is to overcome the imprecision of determining orbits, ranging measurements should be more precise than POD. For that reason, it can be concluded that this critical ranging precision matching the POD precision can serve as the minimum precision requirement for an on-board ranging device. Although the result obtained herein is about a very particular case, this methodology can also be applied in cases where different parameters are used.

Deep Learning Model on Gravitational Waves of Merger and Ringdown in Coalescence of Binary Black Holes

  • Lee, Joongoo;Cho, Gihyuk;Kim, Kyungmin;Oh, Sang Hoon;Oh, John J.;Son, Edwin J.
    • 천문학회보
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    • 제44권1호
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    • pp.46.2-46.2
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    • 2019
  • We propose a deep learning model that can generate a waveform of coalescing binary black holes in merging and ring-down phases in less than one second with a graphics processing unit (GPU) as an approximant of gravitational waveforms. Up to date, numerical relativity has been accepted as the most adequate tool for the accurate prediction of merger phase of waveform, but it is known that it typically requires huge amount of computational costs. We present our method can generate the waveform with ~98% matching to that of the status-of-the-art waveform approximant, effective-one-body model calibrated to numerical relativity simulation and the time for the generation of ~1500 waveforms takes O(1) seconds. The validity of our model is also tested through the recovery of signal-to-noise ratio and the recovery of waveform parameters by injecting the generated waveforms into a public open noise data produced by LIGO. Our model is readily extendable to incorporate additional physics such as higher harmonics modes of the ring-down phase and eccentric encounters, since it only requires sufficient number of training data from numerical relativity simulations.

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Novel Maritime Wireless Communication based on Mobile Technology for the Safety of Navigation: LTE-Maritime focusing on the Cell Planning and its Verification

  • Shim, Woo-Seong;Kim, Bu-Young;Park, Chan-Yong;Lee, Byeong-Hyeok
    • 한국항해항만학회지
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    • 제45권5호
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    • pp.231-237
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    • 2021
  • Enhancing the performance of maritime wireless communication has been highlighted by the issue of cell planning in the sea area because of lack of an appropriate Propagation Loss Model (PLM). To resolve the cell planning issue in vast sea areas, it was essential to develop the (PLM) matching the intended sea area. However, there were considerable gaps between the prediction of legacy PLMs and field measurement in propagation loss and there was a need to develop the adjusted PLM (A-PLM). Therefore, cell planning was performed on this adjusted model, including modification of the base station's location, altitude, and antenna azimuth to meet the quality objectives. Furthermore, in order to verify the availability of the cell planning, Communication Service Quality Monitoring System (CS-QMS) was developed in the LTE-Maritime project to collect LTE signal quality information from the onboard equipment at regular intervals and to ensure that the service quality was high enough to satisfy the goals in each designated grid. As a result of verification, the success rate of RSRP was 95.7% for the intensive management zone (IMZ) and 96.4% for the interested zone (IZ), respectively.

Improving Web Service Recommendation using Clustering with K-NN and SVD Algorithms

  • Weerasinghe, Amith M.;Rupasingha, Rupasingha A.H.M.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권5호
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    • pp.1708-1727
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    • 2021
  • In the advent of the twenty-first century, human beings began to closely interact with technology. Today, technology is developing, and as a result, the world wide web (www) has a very important place on the Internet and the significant task is fulfilled by Web services. A lot of Web services are available on the Internet and, therefore, it is difficult to find matching Web services among the available Web services. The recommendation systems can help in fixing this problem. In this paper, our observation was based on the recommended method such as the collaborative filtering (CF) technique which faces some failure from the data sparsity and the cold-start problems. To overcome these problems, we first applied an ontology-based clustering and then the k-nearest neighbor (KNN) algorithm for each separate cluster group that effectively increased the data density using the past user interests. Then, user ratings were predicted based on the model-based approach, such as singular value decomposition (SVD) and the predictions used for the recommendation. The evaluation results showed that our proposed approach has a less prediction error rate with high accuracy after analyzing the existing recommendation methods.