• Korean Journal of Remote Sensing
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• v.25 no.6
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• pp.547-557
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• 2009

LIDAR (LIght Detection And Ranging) is an active remote sensing technology which provides 3D coordinates of the Earth's surface by performing range measurements from the sensor. Early small footprint LIDAR systems recorded multiple discrete returns from the back-scattered energy. Recent advances in LIDAR hardware now make it possible to record full digital waveforms of the returned energy. LIDAR waveform decomposition involves separating the return waveform into a mixture of components which are then used to characterize the original data. The most common statistical mixture model used for this process is the Gaussian mixture. Waveform decomposition plays an important role in LIDAR waveform processing, since the resulting components are expected to represent reflection surfaces within waveform footprints. Hence the decomposition results ultimately affect the interpretation of LIDAR waveform data. Computational requirements in the waveform decomposition process result from two factors; (1) estimation of the number of components in a mixture and the resulting parameter estimates, which are inter-related and cannot be solved separately, and (2) parameter optimization does not have a closed form solution, and thus needs to be solved iteratively. The current state-of-the-art airborne LIDAR system acquires more than 50,000 waveforms per second, so decomposing the enormous number of waveforms is challenging using traditional single processor architecture. To tackle this issue, four parallel LIDAR waveform decomposition algorithms with different work load balancing schemes - (1) no weighting, (2) a decomposition results-based linear weighting, (3) a decomposition results-based squared weighting, and (4) a decomposition time-based linear weighting - were developed and tested with varying number of processors (8-256). The results were compared in terms of efficiency. Overall, the decomposition time-based linear weighting work load balancing approach yielded the best performance among four approaches.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1171-1173
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• 2003

There are two datasets to estimate the area-mean and time-mean precipitation rate. For one, an array of surface rain gauges represents a series of rods that have to the time axis of the volume. And another data is that of a remote sensing make periodic overpasses at a fixed interval such as radar. The problem of optimally combining data from surface rain gauge data and remote sensed data is considered. In order to combining remote sensed data with Automatic Weather Station (AWS), we use optimal weighting method, which is similar to the method of [2]. They had suggested optimal weights that minimized value of the mean square error. In this paper, optimal weight is evaluated for the cases such as Changma, summer Monsoon, Typhoon and orographic rain.

• Nuclear Engineering and Technology
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• v.17 no.2
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• pp.129-135
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• 1985

Effects of differences between fine- and broad-group structures and spectrum as a weighting function at the resonance energy region of iron on a neutron shielding calculation were analyzed with the ANISN code and ENDF/B-IV data. The problems analyzed are the broad-group effect, the effect for variation of iron thickness, and the effect of problem-dependent weighting spectrum. In order to verify the group data and method used, a calculational benchmark was performed with the continuous-energy Monte Carlo code VIM. The result was compared with the ANISN calculations using the fine- and broad-group data.

• The Journal of the Korea Contents Association
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• v.20 no.10
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• pp.45-56
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• 2020

This study is about the scale to evaluate the data of the countermeasures in the 'simulation based government exercise' (tentative name). The criteria and weighting of the scale is a standard for evaluating the data of each agency input. This maintains the objectivity and consistency of the evaluation, which complements the subjective evaluation of the observer. Therefore, the criteria should accommodate the purpose of the government exercise evaluation, the possibility of measurement in the simulation environment, the objectivity, no-duplication and causality between criteria, and the grade applying the evaluation results, and the weighting should be set. In this study, three major criteria of timeliness, accuracy, and appropriateness is set up for the evaluation scale and it consists of sub-criteria classified into three classes below respectively and the concept of it was defined. The weighting was calculated by AHP analysis considering the hierarchical structure of it. When this evaluation scale is applied to the 'simulation based government exercise' in the future, it will be possible to secure consistency and objectivity of the evaluation of measures by integrating the quantified evaluation into the observation evaluation and to conduct AAR by scientific techniques.

• Journal of KIISE:Software and Applications
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• v.29 no.4
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• pp.248-257
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• 2002

Clustering is a method for grouping objects with similar properties into a same cluster. SVD(Singular Value Decomposition) is known as an efficient preprocessing method for clustering because of dimension reduction and noise elimination for a high dimensional and sparse data set like E-Commerce data set. However, it is hard to evaluate the worth of original attributes because of information loss of a converted data set by SVD. This research proposes a cluster feature selection method, called ENTROPY-SVD, to find important attributes for each cluster based on entropy weighting and SVD. Using SVD, one can take advantage of the latent structures in the association of attributes with similar objects and, using entropy weighting one can find highly dense attributes for each cluster. This paper also proposes a model-based collaborative filtering recommendation system with ENTROPY-SVD, called CFS-CF and evaluates its efficiency and utilization.

• The Journal of the Acoustical Society of Korea
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• v.40 no.4
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• pp.359-369
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• 2021

In underwater communications, to compensate performance degradation induced from rapidly changing channel transfer characteristic, multi-band communication method which allocate the same data to different frequency bands is used. However, the multi-band configuration may have worse performance than the single-band one because performance degradation in a particular band affects the output from the entire bands. This problem can be solved through a receiving end that analyzes error rates of each band, sets threshold values and allocates lower weights to inferior bands. Therefore, this paper proposed a weighting algorithm based on estimated Bit Error Rate (BER) which analyzes reliability of received data based on the performance difference between demodulated and decoded data. Employing turbo codes with coding rate of 1/3, we evaluate the performance of the proposed weighted multi-band transmission model in real underwater environments based on optimal simulation parameters. Through the sea trial experiment, we confirmed error performance was improved by applying the proposed weighting algorithm.

• The Korean Journal of Applied Statistics
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• v.32 no.3
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• pp.375-389
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• 2019

Sample attrition according to a long-term tracking reduces the representativeness of the sample data in a panel study. Most panel surveys in South Korea and other countries have prepared response adjustment weights in order to solve problems regarding representativeness due to sample attrition. In this paper, we divided the panel data into continuous response group and non-continuous response group according to response patterns and considered a weighting adjustment method to reduce the bias of the non-continuous response group. A simulation indicated that the proposed composite estimation type weighting method, which reflected the characteristics of non-continuous response groups, could be more efficient than other weighting methods in terms of reducing non-response bias. As a case study, the proposed methods are applied to the Korean Longitudinal Study of Ageing (KLoSA) data of the Korea Employment Information Service.

• The Journal of Engineering Geology
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• v.16 no.1 s.47
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• pp.85-96
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• 2006

This study was conducted to suggest a method to determine weighting values of each parameter of the RMR system considered with geologic characteristics of a study area. This study reviewed the weighting values of the RMR system for the Cretaceous sedimentary rocks distributed in Ulsan area. Based on the data of field survey at the study area, a multiple regression analysis was used to set up an optimal weighting values of the RMR parameters. For the multiple regression analysis, each parameter of the RMR and the slope gradient were regarded as the independent variable and the dependent variable, respectively. The analysis result suggested a modified weighting values of the RMR parameters as follows; 30 for the intact strength of rock; 18 for RQD; 8 for spacing of discontinuities; 32 for the condition of discontinuities; and 12 for ground water.

• Journal of Communications and Networks
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• v.18 no.6
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• pp.892-901
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• 2016

In the multi-user multiple-input multiple-output (MIMO) system, orthogonal random beamforming (ORBF) scheme is proposed to serve multiple users simultaneously in order to achieve the multi-user diversity gain. The opportunistic space-division multiple access system (OSDMA-S) scheme performs multiple weighting matrices during the training phase and chooses the best weighting matrix to be used to broadcast data during the transmitting phase. The OSDMA-S scheme works better than the original ORBF by decreasing the inter-user interference during the transmitting phase. To save more time in the training phase, a partly random multiple weighting matrices selection scheme is proposed in this paper. In our proposed scheme, the Base Station does not need to use several unitary matrices to broadcast pilot symbol. Actually, only one broadcasting operation is needed. Each subscriber generates several virtual equivalent channels with a set of pre-saved unitary matrices and the channel status information gained from the broadcasting operation. The signal-to-interference and noise ratio (SINR) of each beam in each virtual equivalent channel is calculated and fed back to the base station for the weighting matrix selection and multi-user scheduling. According to the theoretical analysis, the proposed scheme relatively expands the transmitting phase and reduces the interactive complexity between the Base Station and subscribers. The asymptotic analysis and the simulation results show that the proposed scheme improves the throughput performance of the multi-user MIMO system.

• Journal of the Korean Society for information Management
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• v.4 no.1
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• pp.47-86
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• 1987

The purpose of this study is to present an effective automatic indexing method of Korean texts based on statistical criteria. Titles and abstracts of the 299 documents randomly selected from ETRI's DOCUMENT data base are used as the experimental data in this study the experimental data is divided into 4 word groups and these 4 word groups are respectively analyzed and evaluated by applying 3 automatic indexing methods including Transition Phenomena of Word Occurrence, Inverse Document Frequency Weighting Technique, and Term Discrimination Weighting Technique.