• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.11
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• pp.2029-2036
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• 2017

Currently, the demand for multimedia services is increasing with the rapid development of the digital age. Image data is corrupted by various noises and typical noise is mainly AWGN, salt and pepper noise and the complex noise that these two noises are mixed. Therefore, in this paper, the noise is processed by classifying AWGN and salt and pepper noise through noise judgment. In the case of AWGN, the outputs of spatial weighted filter and pixel change weighted filter are composed and processed, and the composite weights are applied differently according to the standard deviation of the local mask. In the case of salt and pepper noise, cubic spline interpolation and local histogram weighted filters are composed and processed. This study suggested the multiple image restoration filter algorithm which is processed by applying different composite weights according to the salt and pepper noise density of the local mask.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.3
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• pp.97-103
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• 2020

Linux Cgroups takes a fundamental role for sharing system resources among multiple containers on container-based cloud computing environment. Especially for I/O resource, Linux Cgroups supports a mechanism for sharing I/O bandwidth in proportion to I/O weight. However, the current mechanism of Linux Cgroups using BFQ I/O scheduler seriously degrades the I/O performance with high bandwidth storage device such as NVMe SSDs. In this paper, we proposed a new feedback based I/O bandwidth sharing scheme for Linux Cgroups which allocates I/O credits to containers according to I/O weights and adjusts the amount of credits to performance fluctuation of NVMe SSDs. The proposed scheme is implemented on Linux kernel 5.3 and evaluated. The evaluation results show that it can share the I/O bandwidth among multiple containers proportionally to I/O weights while improving I/O performance more than twice as high as the existing scheme.

• Development and Reproduction
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• v.20 no.2
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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.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.19
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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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.7
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• pp.1749-1756
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• 2014

Knowledge about protein subcellular localization provides important information about protein function. This paper improves a label power-set multi-label classification for the accurate prediction of subcellular localization of proteins which simultaneously exist at multiple subcellular locations. Among multi-label classification methods, label power-set method can effectively model the correlation between subcellular locations of proteins performing certain biological function. With constrained optimization, this paper calculates combination weights which are used in the linear combination representation of a multi-label by other multi-labels. Using these weights, the prediction probabilities of multi-labels are combined to give final prediction results. Experimental results on human protein dataset show that the proposed method achieves higher performance than other prediction methods for protein subcellular localization. This shows that the proposed method can successfully enrich the prediction probability of multi-labels by exploiting the overlapping information between multi-labels.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.7 no.3
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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.

• Journal of Communications and Networks
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• v.18 no.2
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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.

• Industrial Engineering and Management Systems
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• v.1 no.1
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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.

• Journal of Positioning, Navigation, and Timing
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• v.7 no.4
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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.

• Journal of Information Processing Systems
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• v.15 no.5
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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.