• Journal of the Korea Safety Management & Science
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• v.12 no.3
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• pp.257-262
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• 2010

The study investigates the various Acceptance Control Charts (ACCs) based on the factors that include process independence, data weighting scheme, subgrouping, and use of control charts. USL - LSL > $6{\sigma}$ that used in the good condition processes in the ACCs are designed by considering user's perspective, producer's perspective and both perspectives. ACCs developed from the research is efficiently applied by using the simple control limit unified with APL (Acceptable Process Level), RLP (Rejectable Process Level), Type I Error $\alpha$, and Type II Error $\beta$. Sampling interval of subgroup examines i.i.d. (Identically and Independent Distributed) or auto-correlated processes. Three types of weight schemes according to the reliability of data include Shewhart, Moving Average(MA) and Exponentially Weighted Moving Average (EWMA) which are considered when designing ACCs. Two types of control charts by the purpose of improvement are also presented. Overall, $\alpha$, $\beta$ and APL for nonconforming proportion and RPL of claim proportion can be designed by practioners who emphasize productivity and claim defense cost.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.76-78
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• 2014

Naive Bayes (NB, for shortly) learning is more popular, faster and effective supervised learning method to handle the labeled datasets especially in which have some noises, NB learning also has well performance. However, the conditional independent assumption of NB learning imposes some restriction on the property of handling data of real world. Some researchers proposed lots of methods to relax NB assumption, those methods also include attribute weighting, kernel density estimating. In this paper, we propose a novel approach called NB Based on Attribute Weighting in Kernel Density Estimation (NBAWKDE) to improve the NB learning classification ability via combining kernel density estimation and attribute weighting.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.3
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• pp.65-73
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• 2005

Because the geological features of Imha basin are composed of clay and shale layer, much soil particle flows into reservoir in shape of muddy water when it rains a lot. Therefore, turbidity data can be indirect-index to estimate the soil erosion of Imha basin. This study evaluated annual soil erosion using GIS-based soil erosion model and applied rainfall weighting value method by time-series rainfall data to estimate monthly soil erosion. In view of 2003 turbidity data, monthly soil erosion with rainfall weighting value is more efficient than monthly soil erosion with rainfall data.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.43-49
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• 2020

This paper proposes a lossless image compression method based on arithmetic coding using block-adaptive Context Tree Weighting. The CTW method predicts and compresses the input data bit by bit. Also, it can achieve a desirable coding distribution for tree sources with an unknown model and unknown parameters. This paper suggests the method to enhance the compression rate about image data, especially aerial and satellite images that require lossless compression. The value of aerial and satellite images is significant. Also, the size of their images is huger than common images. But, existed methods have difficulties to compress these data. For these reasons, this paper shows the experiment to prove a higher compression rate when using the CTW method with divided images than when using the same method with non-divided images. The experimental results indicate that the proposed method is more effective when compressing the divided images.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.70-74
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• 2005

Soil particles from rainfall flow into reservoir and give lots of influence In water quality because the geological conditions and landcover characteristics of imha basin have a weakness against soil loss. Especially, much soil particles induced to reservoir in shape of muddy water when it rains a lot because the geological characteristics of imha reservoir are composed of clay and shale layer. Therefore, field turbidity data can be Indirect-standards to estimate the soil erosion of imha basin. This study evaluated annual soil erosion using GIS-based RUSLE (Revised Universal Soil Loss Equation) and developed rainfall weighting value method using time-series rainfall data to estimate monthly soil erosion. In view of field turbidity data(2003 yr), we can find out monthly soil erosion with rainfall weighting value is more efficient than that with monthly rainfall data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.2
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• pp.514-522
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• 2017

Traffic offloading is a promising solution to solve the explosive growth of mobile traffic. One of offloading schemes, in LIPA/SIPTO(Local IP Access and Selected IP Traffic Offload) offloading, we can offload mobile traffic that can satisfy QoS requirement for application. In addition, it is necessary for traffic offloading using social context due to large traffic from SNS. Thus, we propose the LIPA/SIPTO offloading algorithm using social context. We define the application selection probability using social context, the application popularity. Then, we find the optimal offloading weighting factor to maximize the QoS(Quality of Service) of small cell users in term of effective data rate. Finally, we determine the offloading ratio by this application selection probability and optimal offloading weighting factor. By performance analysis, the effective data rate achievement ratio of the proposed algorithm is similar with the conventional one although the total offloading ratio of the proposed algorithm is about 46 percent of the conventional one.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5B
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• pp.529-537
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• 2006

This paper investigates the impacts of the drag-related weighting coefficients on mean velocity and turbulence structures. The transport equations for the Reynolds stress of vegetated open-channel flows are derived by using the temporal- and horizontal-averaging scheme. It is found that the total Reynolds stress of vegetated open channel flows consists of the Reynolds stress due to temporally fluctuating velocities and the Reynolds stress due to spatially fluctuating velocities. The drag-related weighting coefficient $C_{fk}$ for the total Reynolds stress component is found to be unit, while the coefficient for the Reynolds stress due to temporally fluctuating velocities can be negligible. This is the reason why very small weighting coefficients in previous studies yield very good agreements with measured data. In other words, the Reynolds stress due to spatially fluctuating velocities remains still unknown, especially due to the large number of measuring locations. Through a developed Reynolds stress model, vegetated open-channel flows are simulated and compared with measured data from the literature. Comparisons reveal that the computed mean flow and Reynolds stress structures are hardly affected by the drag-related weighting coefficients. However, the computed turbulence intensity profiles are significant different with the drag-related weighting coefficients. A budget analysis of the transport equations for the Reynolds stress component is carried to investigate why turbulence intensity is affected by the drag-related weighting coefficients.

• Journal of the Korean Data and Information Science Society
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• v.23 no.3
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• pp.579-585
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• 2012

Many different semi-supervised learning algorithms have been proposed for use wit unlabeled data. However, most of them focus on classification problems. In this paper we propose a semi-supervised regression algorithm called the semi-supervised local constant estimator (SSLCE), based on the local constant estimator (LCE), and reveal the asymptotic properties of SSLCE. We also show that the SSLCE has a faster convergence rate than that of the LCE when a well chosen weighting factor is employed. Our experiment with synthetic data shows that the SSLCE can improve performance with unlabeled data, and we recommend its use with the proper size of unlabeled data.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.3
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• pp.515-520
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• 2022

In context awareness using multiple sensors, when using sensor data detected and sent by each sensor, it is necessary to give different weights for each sensor. Even if the same type of sensor is configured for the same situation, sometimes it is necessary to assign different weights due to other secondary factors. It is inevitable to assign weights to events in the real world, and it can be said that a weighting method that can be used in a context awareness system using multiple sensors is necessary. In this study, we propose a weighting method for each sensor that reports to the host while the sensors continue to detect over time. In most IoT environments, the sensor continues the detection activity, and when the detected value shows a change pattern beyond a predetermined range, it is basically reported to the host. This can be called a kind of data stream environment. A weighting method was proposed for sensing data from multiple sensors in a data stream environment, and the new weighting method was to select and assign weights to data that indicates a context change in the stream.

• 한국해양학회지
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• v.30 no.6
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• pp.543-549
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• 1995

The inverse method has been used to estimate a surface velocity field from sequential AVHRR/SST data. In the model, equation system was composed of heat equation and horizontal divergence minimization and the velocity field contained in the advective term of the heat equation, which was linearized in grid system, was estimated. A constraint was the minimization of horizontal divergence with weighting factor and introduced to compensate the null space(Menke, 1984) of the velocity solutions for the heat equation. The experiments were carried out to set up the range of weighting factor and the matrix equation was solved by SVD(Singular Value Decomposion). In the experiment, the scales of horizontal temperature gradient and divergence of synthetic velocity field were approximated to those of real field. The neglected diffusive effect and the horizontal variation of heat flux in the heat equation were regarded as random temperature errors. According to the result of experiments, the minimum of relative error was more desirable than the minimum of misfit as the criteria of setting up the weighting factor and the error of estimated velocity field became small when the weighting factor was order of $10^{-1}$