• 제목/요약/키워드: multiple weights

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복합잡음 제거를 위한 다중 필터에 관한 연구 (A Study on Multiple Filter for Mixed Noise Removal)

  • 권세익;김남호
    • 한국정보통신학회논문지
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    • 제21권11호
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    • pp.2029-2036
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    • 2017
  • 현재, 디지털 시대의 급속 발전과 함께 멀티미디어 서비스에 대한 수요가 증가되고 있다. 영상 데이터는 다양한 잡음에 의해 훼손되며, 주로 AWGN, salt and pepper 잡음, 이 두 잡음이 혼합된 복합잡음 등이 대표적이다. 따라서, 본 논문에서는 잡음 판단을 통해 AWGN 및 salt and pepper 잡음으로 분류하여 처리한다. AWGN인 경우, 공간 가중치 필터 및 화소 변화 가중치 필터의 출력을 합성하여 처리하며, 국부 마스크의 표준편차에 따라 합성 가중치를 다르게 적용한다. salt and pepper 잡음인 경우, 3차원 스플라인 보간법 및 국부 히스토그램 가중치 필터를 합성하여 처리하며, 국부 마스크의 salt and pepper 잡음 밀도에 따라 합성 가중치를 다르게 적용하여 처리하는 다중 영상복원 필터 알고리즘을 제안하였다.

클라우드 환경에서 고성능 저장장치를 위한 동적 대역폭 분배 기법 (Dynamic Bandwidth Distribution Method for High Performance Non-volatile Memory in Cloud Computing Environment)

  • 권필진;안성용
    • 한국인터넷방송통신학회논문지
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    • 제20권3호
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    • pp.97-103
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    • 2020
  • 리눅스 Cgroups은 컨테이너 기반 클라우드 서비스 구축에서 각 컨테이너 별 시스템 자원을 할당하기 위한 핵심적인 역할을 담당하고 있다. 특히 입출력 자원의 경우 리눅스 Cgroups은 컨테이너의 가중치에 따라 입출력 대역폭을 분배하는 기법을 지원하고 있다. 그러나 성능 분석 결과에 따르면 현재 리눅스 Cgroups의 입출력 대역폭 분배 기법은 NVMe SSD와 같은 고성능 저장장치를 사용할 경우 입출력 성능이 크게 저하된다는 한계점을 가지고 있다. 따라서 본 논문에서는 리눅스 Cgroups을 위한 새로운 피드백 기반의 동적 대역폭 분배 기법을 제안하고자 한다. 제안하는 기법은 가중치에 따라 입출력 크레딧을 분배하며 고성능 저장장치의 성능 변화를 동적으로 반영해 입출력 크레딧을 계산함으로써 저장장치의 성능 저하를 최소화한다. 제안된 기법은 리눅스 커널 5.3에 구현되었으며 성능 평가 결과 정확한 입출력 대역폭 분배를 수행할 뿐만 아니라 기존 기법에 비해 최대 2배 높은 입출력 성능을 보여주었다.

Effect of Lipopolysaccharide (LPS) Exposure on the Reproductive Organs of Immature Female Rats

  • Yoo, Da Kyung;Lee, Sung-Ho
    • 한국발생생물학회지:발생과생식
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    • 제20권2호
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    • pp.91-99
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    • 2016
  • Lipopolysaccharide (LPS), an endotoxin, elicits strong immune responses in mammals. Several lines of evidence demonstrate that LPS challenge profoundly affects female reproductive function. For example, LPS exposure affects steroidogenesis and folliculogenesis, resulting in delayed puberty onset. The present study was conducted to clarify the mechanism underlying the adverse effect of LPS on the delayed puberty in female rats. LPS was daily injected for 5 days ($50{\mu}g/kg$, PND 25-29) to treated animals and the date at VO was evaluated through daily visual examination. At PND 39, animals were sacrificed, and the tissues were immediately removed and weighed. Among the reproductive organs, the weights of the ovaries and oviduct from LPS-treated animals were significantly lower than those of control animals. There were no changes in the weights of uterus and vagina between the LPS-treated and their control animals. immunological challenge by LPS delayed VO. Multiple corpora lutea were found in the control ovaries, indicating ovulations were occurred. However, none of corpus luteum was present in the LPS-treated ovary. The transcription level of steroidogenic acute regulatory protein (StAR), CYP11A1, CYP17A1 and CYP19 were significantly increased by LPS treatment. On the other hand, the levels of $3{\beta}$-HSD, $17{\beta}$-HSD and LH receptor were not changed by LPS challenge. In conclusion, the present study demonstrated that the repeated LPS exposure during the prepubertal period could induce multiple alterations in the steroidogenic machinery in ovary, and in turn, delayed puberty onset. The prepubertal LPS challenge model used in our study is useful to understand the reciprocal regulation of immune (stress) - reproductive function in early life.

전남지역의 기상요인이 과맥의 생육 및 수량구성 요소에 미치는 영향 (Studies on Some Weather Factors in Chon-nam District on Plant Growth and Yield Components of Naked Barley)

  • 이돈길
    • 한국작물학회지
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    • 제19권
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    • pp.100-131
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    • 1975
  • To obtain basic information on the improvement of naked barley production. and to clarify the relation-ships between yield or yield components and some meteorogical factors for yield prediction were the objectives of this study. The basic data used in this study were obtained from the experiments carried out for 16 years from 1958 to 1974 at the Chon-nam Provincial Office of Rural development. The simple correlation coefficients and multiple regression coefficients among the yield or yield components and meteorogical factors were calculated for the study. Days to emergence ranged from 8 to 26 days were reduced under conditions of mean minimum air temperature were high. The early emergence contributed to increasing plant height and number of tillers as well as to earlier maximum tillering and heading date. The plant height before wintering showed positive correlations with the hours of sunshine. On the other hand, plant height measured on march 1st and March 20th showed positive correlation with the amount of precipitation and negative correlation with the hours of sunshine during the wintering or regrowth stage. Kernel weights were affected by the hours of sunshine and rainfall after heading, and kernel weights were less variable when the hours of sunshine were relatively long and rainfalls in May were around 80 to 10mm. It seemed that grain yields were mostly affected by the climatic condition in March. showing the negative correlation between yield and mean air temperature, minimum air temperature during the period. In the other hand, the yield was shown to have positive correlation with hours of sunshine. Some yield prediction equations were obtained from the data of mean air temperature, mean minimum temperature and accumulated air temperature in March. Yield prediction was also possible by using multiple regression equations, which were derived from yield data and the number of spikes and plant height as observed at May 20th.

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다중레이블 조합을 사용한 단백질 세포내 위치 예측 (Multi-Label Combination for Prediction of Protein Subcellular Localization)

  • 지상문
    • 한국정보통신학회논문지
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    • 제18권7호
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    • pp.1749-1756
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    • 2014
  • 단백질이 존재하는 세포내 위치에 대한 지식은 단백질의 기능과 관련된 중요한 정보이다. 본 논문은 개선된 레이블 멱집합 다중레이블 분류방법을 제안하여 단백질이 존재하는 세포내의 다중 위치를 예측한다. 다중레이블 분류 방법 중에서 레이블 멱집합 방법은 특정 생물학적 기능을 수행하는 단백질의 세포내 위치간의 연관 관계를 효과적으로 모델링할 수 있다. 본 논문은 다중레이블을 다른 다중레이블들의 선형조합으로 나타낼 때의 조합가중치를 제약조건이 있는 최적화를 통하여 구하고, 이를 사용하여 여러 다중레이블의 예측 확률들을 조합하여 최종적인 예측을 수행한다. 인간 단백질 자료에 대한 실험에서 제안한 방법이 다른 단백질 세포내 위치 예측 방법에 비하여 높은 성능을 보였다. 이는 제안한 방법이 레이블 멱집합 방법에서 사용되는 다중레이블들내에 존재하는 중복 정보를 이용하여 다중 레이블의 예측확률을 성공적으로 강화할 수 있기 때문이다.

3차원 조형장비 선정을 위한 복합 다요소 의사결정 구조 모델 개발에 관한 연구 (A decision making framework model for the selection of a RP using hybrid multiple attribute decision making techniques)

  • 변홍석
    • 한국기계가공학회지
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    • 제7권3호
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    • pp.87-95
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    • 2008
  • The purpose of this study is to provide a decision support to select an appropriate rapid prototyping(RP) machine that suits the application of a part. Selection factors include concept model, form/fit/functional model, pattern model for molding, material property, build time and part cost that greatly affect the performance of RP machines. However, the selection of a RP is not an easy decision because they are uncertain and vague. For this reason, the aim of this research is to propose hybrid multiple attribute decision making approaches to effectively evaluate RP machines. In addition, because subjective considerations are relevant to selection decision, a fuzzy logic approach is adopted. The proposed selection procedure consists of several steps. First, we identify RP machines that the users consider. After constructing the evaluation criteria, we calculate the weights of the criteria by applying the fuzzy Analytic Hierarchy Process(AHP) method. Finally, we construct the fuzzy Technique of Order Preference by Similarity to Ideal Solution(TOPSIS) method to achieve the ranking order of all machines providing the decision information for the selection of RP machines.

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Robust Transceiver Designs in Multiuser MISO Broadcasting with Simultaneous Wireless Information and Power Transmission

  • Zhu, Zhengyu;Wang, Zhongyong;Lee, Kyoung-Jae;Chu, Zheng;Lee, Inkyu
    • Journal of Communications and Networks
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    • 제18권2호
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    • pp.173-181
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    • 2016
  • In this paper, we address a new robust optimization problem in a multiuser multiple-input single-output broadcasting system with simultaneous wireless information and power transmission, where a multi-antenna base station (BS) sends energy and information simultaneously to multiple users equipped with a single antenna. Assuming that perfect channel-state information (CSI) for all channels is not available at the BS, the uncertainty of the CSI is modeled by an Euclidean ball-shaped uncertainty set. To optimally design transmit beamforming weights and receive power splitting, an average total transmit power minimization problem is investigated subject to the individual harvested power constraint and the received signal-to-interference-plus-noise ratio constraint at each user. Due to the channel uncertainty, the original problem becomes a homogeneous quadratically constrained quadratic problem, which is NP-hard. The original design problem is reformulated to a relaxed semidefinite program, and then two different approaches based on convex programming are proposed, which can be solved efficiently by the interior point algorithm. Numerical results are provided to validate the robustness of the proposed algorithms.

On a Multiple Data Handling Method under Online Parameter Estimation

  • Takeyasu, Kazuhiro;Amemiya, Takashi;Iino, Katsuhiro;Masuda, Shiro
    • Industrial Engineering and Management Systems
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    • 제1권1호
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    • pp.64-72
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    • 2002
  • In the field of plant maintenance, data that are gathered by sensors on multiple machines are handled and analyzed. Online or pseudo online data handling is required on such fields. When the data occurrence speed exceeds the data handling speed, multiple data should be handled at a time (batch data handling or pseudo online data handling). If l amount of data are received at one time following N amount of data, how to estimate the new parameters effectively is a great concern. A new simplified calculation method, which calculates the N data's weights, is introduced. Numerical examples show that this new method has a fairly god estimation accuracy and the calculation time is less than 1/10 compared with the case when the whole data are re-calculated. Even under the restriction calculation ability in the apparatus is limited, this proposed method makes the failure detection of equipments possible in early stages with a few new coming data. This method would be applicable in many data handling fields.

An Efficient Positioning Method for Multi-GNSS with Multi-SBAS

  • Park, Kwi Woo;Cho, MinGyou;Park, Chansik
    • Journal of Positioning, Navigation, and Timing
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    • 제7권4호
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    • pp.245-253
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    • 2018
  • The current SBAS service does not provide a method to integrate multiple SBAS corrections. This paper proposes a positioning method to effectively integrate multiple SBAS and multiple GNSS. In the method, the final position is obtained by the weighted sum of the positions obtained from the combination of GNSS and SBAS. Since each position is independently computed and combined using flexible weights, it has a simple structure that can easily cope with various environments. In order to verify the operation and performance of the proposed method, raw measurements of GNSS and SBAS were collected using commercial receivers. The experiments using real signals show that the combined use of two SBAS corrections was more accurate by 0.05~0.4m(2dRMS) than using only one SBAS correction. To improve the position accuracy, this paper considered the integration of multi-GNSS and multi-SBAS, which was not found in other existing studies. The proposed method is expected to be a core technology for designing multi-GNSS navigation receivers considering multi-SBAS corrections. The importance of the method will be increased as KPS and KASS also available in near future.

Learning-Based Multiple Pooling Fusion in Multi-View Convolutional Neural Network for 3D Model Classification and Retrieval

  • Zeng, Hui;Wang, Qi;Li, Chen;Song, Wei
    • Journal of Information Processing Systems
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    • 제15권5호
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    • pp.1179-1191
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    • 2019
  • We design an ingenious view-pooling method named learning-based multiple pooling fusion (LMPF), and apply it to multi-view convolutional neural network (MVCNN) for 3D model classification or retrieval. By this means, multi-view feature maps projected from a 3D model can be compiled as a simple and effective feature descriptor. The LMPF method fuses the max pooling method and the mean pooling method by learning a set of optimal weights. Compared with the hand-crafted approaches such as max pooling and mean pooling, the LMPF method can decrease the information loss effectively because of its "learning" ability. Experiments on ModelNet40 dataset and McGill dataset are presented and the results verify that LMPF can outperform those previous methods to a great extent.