• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.8
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• pp.838-848
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• 2014

We present a simulation study of an algorithm for the range and angle of arrival(AOA) estimation with an interferometric synthetic aperture radar(InSAR) altimeter using a real digital elevation model(DEM). We also illustrate a step-by-step procedure of generating raw InSAR data, as well as their range and azimuth compressed data, which is to be used for the subsequent altitude and angle estimation. The AOA is estimated using a deterministic maximum likelihood estimator(DMLE) applied to the first arrived point for each pulse in the compressed data obtained with three antennas. The range bin size and the pulse repetition interval(PRI) are much smaller than the cell size of the DEM used in this study. To make the DEM compatible to the radar parameters, we first generate a higher resolution DEM by linearly interpolating the given DEM. After a brief description of the principle of the InSAR altimeter, the algorithms for altitude and angle estimation are presented, and their performance is assessed through simulation.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.11
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• pp.1-11
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• 1998

We present somple block methods for blind maximal ratio combining (MRC) based on a maximum likelihood (ML) principle and finite alphabet properties (FAP) inherent in digital communication systems. The methods can provide accurate estimates of channel parameters even with a small subset of data, thus realizing nearly perfect combining. The channel parameters of diversity branches and the data sequence are estimated simultaneously by using an alternating projection technique. Two different methods, that is, (1) Joint combining and data sequence estimation(JC-DSE) method and (2) Pre-combining and blind phase estimation (PC-BPE) method are presented. Efficient initiallization schemes that can assure the convergence to the global optimum are also presented. Simulation results demonstrate the performance of two methods on the symbol error rate (SER) and the estimated accuracy of the channel parameters.

• Nutrition Research and Practice
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• v.9 no.3
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• pp.268-277
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• 2015

BACKGROUND/OBJECTIVES: Although it is crucial to identify those children likely to be treated in an appropriate nutrition rehabilitation programme and discharge them at the appropriate time, there is no golden standard for such identification. The current study examined the appropriateness of using Mid-Upper Arm Circumference for the identification, follow-up and discharge of malnourished children. We also assessed its discrepancy with the Weight-for-Height based diagnosis, the rate of recovery, and the discharge criteria of the children during nutrition rehabilitation. SUBJECTS/METHODS: The study present findings from 156 children (aged 6-59 months) attending a supplementary feeding programme at Makadara and Jericho Health Centres, Eastern District of Nairobi, Kenya. Records of age, weight, height and mid-upper arm circumference were selected at three stages of nutrition rehabilitation: admission, follow-up and discharge. The values obtained were then used to calculate z-scores as defined by WHO Anthro while estimating different diagnostic indices. RESULTS: Mid-upper arm circumference single cut-off (< 12.5 cm) was found to exhibit high values of sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio at both admission and discharge. Besides, children recorded higher rate of recovery at 86 days, an average increment of 0.98 cm at the rate of 0.14mm/day, and a weight gain of 13.49gm/day, albeit higher in female than their male counterparts. Nevertheless, children admitted on basis of low MUAC had a significantly higher MUAC gain than WH at 0.19mm/day and 0.13mm/day respectively. CONCLUSIONS: Mid-upper arm circumference can be an appropriate tool for identifying malnourished children for admission to nutrition rehabilitation programs. Our results confirm the appropriateness of this tool for monitoring recovery trends and discharging the children thereafter. In principle the tool has potential to minimize nutrition rehabilitation costs, particularly in community therapeutic centres in developing countries.

• Child Health Nursing Research
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• v.13 no.1
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• pp.13-20
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• 2007

Purpose: This investigation examined a model to predict body mass index in order to prevent later development of obesity among adolescents. The hypothesized model was developed based on the principle of Social Cognitive Theory that social influences predict perceptions of cognition as well as behavior. Method: The 5,770 adolescents, aged 14-18 who participated in this study came from 11 separate school districts in Busan and Kyungnam province of South Korea. The adolescent surveys were administered in a group setting at the participating school. Of the 5770 surveys, adolescents with more than 10 percent missing data in the entire survey were excluded. The final sample contained 4,527 cases. The adolescents were included 2,250 (49.7%) males and 2,277 (50.3%) females. Data was analyzed Pearson correlation coefficients using SPSS 12 program and structural equation model (SEM) using Maximum Likelihood estimation was employed using Amos 5.0. Results: Social support directly affects cognitive determinants. Cognitive determinants directly affect behavior determinants which directly affect BMI. Cognitive and behavioral factors mediated the relationship between social support and BMI (GFI= 0.984, CFI= 0.974, RMSEA=0.031). Conclusion: Social levels should be supportive to help adolescents have healthier behaviors. This support can be accomplished by providing frequent support to establish positive cognitive factors as the foundation of the solution to prevent overweight and obesity.

• Journal of Information Technology Services
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• v.15 no.2
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• pp.1-19
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• 2016

With various success stories of crowdfunding, government's establishment of crowdfunding act, and expected rapid growth of crowdfunding market, the potential ripple effect of crowdfunding on our society is anticipated to be enormous. This study investigates the influential factors and their impacts on the likelihood of project success in donation-based crowdfunding through the DonorsChoose case. The authors analyze the characteristics of project creator, characteristics of project, and behaviors of project participants in relation to the success or failure of the corresponding project. Consequently, the authors found that participants of donation-based crowdfunding exhibit altruistic behaviors and obtained the following specific results: First, donation participation and social capital of the project creator, and marginal help utility of receivers positively affect the success of project. Second, experience of past project creation of the project creator negatively affects the success of project. Third, past donations of the project creator to others' projects, when not appropriately signaled like on the DonorsChoose platform, may not exert a positive influence on the success of project and the reciprocity principle may not work.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.4
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• pp.1039-1049
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• 1994

The intermitternt and transient fuel spray have been investigated from the simultaneous measurement of droplet sizes and velocities by using Phase/Doppler Particle Analyzer(PDPA). Measurement have been done on the spray axis and at the edge of the spray near nozzle at various gas-to-liquid density ratios(.rho./sub g//.rho./sub l/) that ranges from those found in free atmospheric jets to conditions typical of diesel engines. Probability density distributions of the droplet size and velocity were obtained from raw data and mathematical probability density functions which can fit the experimental distribations were extracted using the principle of maximum likelihood. In the near nozzle region on the spray axis, droplet sizes ranged from the lower limit of the measurement system to the order of nozzle diameter for all (.rho./sub g/ /.rho./sub l/) and droplet sizes tended to be small on the spray edge. At the edge of spray, average droplet velocity peaked during needle opening and needle closing. The rms intensity is greatly incresed as the radial distance from the nozzle is increased. The probability density function which can best fit the physical breakage process such as breakup of fuel drops is exponecially decreasing log-hypebolic function with 4 parameters.

• The Korean Journal of Applied Statistics
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• v.27 no.5
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• pp.819-831
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• 2014

The Exact-EM algorithm can conventionally fit a mixture of multivariate skew distribution. However, it suffers from highly expensive computational costs to calculate the moments of multivariate truncated t-distribution in E-step. This paper proposes a new SPU-EM method that adopts the AECM algorithm principle proposed by Meng and van Dyk (1997)'s to circumvent the multi-dimensionality of the moments. This method offers a shorter execution time than a conventional Exact-EM algorithm. Some experments are provided to show its effectiveness.

• Journal of Korean Society for Atmospheric Environment
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• v.22 no.6
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• pp.940-953
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• 2006

The major source of carbon monoxide (CO) at the Earth's surface is the incomplete combustion of biomass and fossil fuels. Because the global lifetime of CO is about two months, it can be used as a tracer for pollution from anthropogenic activities and biomass hurtling. In this paper, we introduced the principle and algorithm of the Measurement of Pollution in the Troposphere (MOPITT) instrument for global CO monitoring. The MOPITT instrument, which was launched on the Satellite Terra in 1999, measures CO column and mixing ratio based on gas correlation radiometry. CO levels can be determined by a retrieval algorithm based on the maximum likelihood method minimizing the difference between observed and modeled radiances. MOPITT level 2 data (HDF format) can be downloaded through the Earth Observing System (EOS) data gateway of NASA. ASCII files of CO parameters can be extracted from HDF files, and then temporal and spatial distributions can be obtained. Finally, we showed an example of CO monitoring in April 2000. The locations of forest fires and distribution of MOPITT CO clearly indicated that not only anthropogenic emissions but also forest fires play an important role in CO levels and global CO distribution. Our introduction to MOPITT and the example of MOPITT data interpretation would be helpful for scientists who want to use the EOS data.

• School Mathematics
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• v.11 no.3
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• pp.389-413
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• 2009

This thesis assumes that the teaching objective of the Probability unit of the 8th grade textbook under the 7th National Curriculum is to enhance the ability to analyze and utilize informations. And we examine them if this point of view is fully reflected. Based on the analysis of the textbook analysis, followings are found. 1) It is necessary to emphasize more enumerating all possible cases and to induce formulae counting the number of possible cases through organizing them 2) The probability is to be decribed more clearly as a likelihood of events and to be introduced and followed through various students' experiences and the relative frequencies. Less emphasis on probability computations, while more emphasis on probability comparisons of events are recommended. 3) The term "influential events"(a kind of stochastic correlation) is ambiguous. It is necessary to make clear what it means at tile level of the 8th grade or to discard it for it is to be learned at the 10th grade again. Especially, contingency table has been introduced at the 9th grade under the 7th National Curriculum. 4) Uses of the likelihood principle in making a decision and in learning the reliability of it should be encouraged. And students are to team the hazard of transitive inferences in probability comparisons. As a consequence of above, we feel that textbook authors and related stakeholder are to be more serious about the behavioral changes of students that may come along with the didactics of specific contents of school mathematics.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.4
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• pp.75-88
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• 2008

This paper presents a spatial-level nonparametric multi-focus image fusion technique based on kernel estimates of input image blocks' underlying class-conditional probability density functions. Image fusion is approached as a classification task whose posterior class probabilities, P($wi{\mid}Bikl$), are calculated with likelihood density functions that are estimated from the training patterns. For each of the C input images Ii, the proposed method defines i classes wi and forms the fused image Z(k,l) from a decision map represented by a set of $P{\times}Q$ blocks Bikl whose features maximize the discriminant function based on the Bayesian decision principle. Performance of the proposed technique is evaluated in terms of RMSE and Mutual Information (MI) as the output quality measures. The width of the kernel functions, ${\sigma}$, were made to vary, and different kernels and block sizes were applied in performance evaluation. The proposed scheme is tested with C=2 and C=3 input images and results exhibited good performance.