• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.3
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• pp.323-334
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• 2008

According to the delivery condition, the breakage of a product occurs when it is delivered to the customers. Therefore product's makers evaluate the durability under the delivery process by accelerated life testing. In order to conduct this accelerated life testing accurately, it is very important to identify the acceleration-factor exactly between on-road and accelerated life test condition. In this paper, the acceleration-factor is identified by applying linear damage summation law, rain-flow cycle counting and Dirlik theory under the conditions of the random vibration. And approximated FEM model of the connecting-pipe to the compressor is developed for fatigue analysis. This model is finally verified by comparing the experiment results to the numerical analysis results.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.66 no.3
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• pp.123-128
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• 2017

Electric utilities has been considered the necessity to introduce AM(asset management) of electric power facilities in order to reduce maintenance cost of existing facilities and to maximize profit. In order to make decisions in terms of repairs and replacements for power transformers, not only measuring by counting parts and labor costs, but comprehensive comparison including reliability and cost is needed. Therefore, this study is modeling input cost for power transformer during its entire life and also the life cycle cost (LCC) technique is applied. In particular, this paper presents an application of heuristic harmony search(HS) optimization algorithm to the convergence and the validity of economic life assessment of power transformer from LCC technique. This recently developed HS algorithm is conceptualized using the musical process of searching for a perfect state of harmony. It uses a stochastic random search instead of a gradient search so that derivative information is unnecessary. The effectiveness of the proposed identification method has been demonstrated through an economic life assessment simulation of power transformer using HS optimization algorithm.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.23 no.7 s.166
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• pp.1164-1172
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• 1999

In this study, to investigate the fatigue crack retardation behavior and the variability of retardation cycles, fatigue crack growth tests were conducted on 7075-T6 aluminum alloy under single tensile overload. A retardation coefficient, D was introduced to describe fatigue crack retardation behavior and a random variable, Z to describe the variability of fatigue crack growth. The retardation coefficient was separately formulated according to retardation behavior which is composed of delayed retardation part and retardation part. The random variable, Z was evaluated from experimental data which was obtained from fatigue crack growth tests under constant amplitude load. Using these variables, a probabilistic model was developed on the basis of the modified Forman's equation, and retardation behavior and cycles were predicted under certain overload condition. The predicted retardation curve well agrees with the trend of experimental crack retardation behavior. And this model well predicts the scatter of experimental retardation cycles.

• Journal of Ecology and Environment
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• v.36 no.3
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• pp.205-210
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• 2013

Cicuta virosa L. (Apiaceae) is a perennial emergent plant designated as an endangered species in South Korea. According to the former records, only four natural habitats remain in South Korea. A former study suggested that three of four populations (Pyeongchang: PC, Hoengseong: HS, Gunsan: GS) would be classified as different ecotypes based on their different morphological characteristics and life cycle under different environmental conditions. To evaluate this suggestion, we estimated genetic diversity in each population and distance among three populations by random amplification of polymorphic DNA. Seven random primers generated a total of 61 different banding positions, 36 (59%) of them were polymorphic. Nei's gene diversity and the Shannon diversity index increased in the order of PC < HS < GS, which is the same order of population size. In the two-dimensional (2D) plot of first two principal components in principal component analysis with the presence of 61 loci, individuals could be grouped as three populations easily (proportion of variance = 0.6125). Nei's genetic distance for the three populations showed the same tendency with the geographical distance within three populations. And it is also similar to the result of discriminant analysis with the morphological or life-cycle factors from the previous study. From the results, we concluded that three different populations of C. virosa should be classified as ecotypes based on not only morphology and phenology but genetic differences in terms of diversity and distance as well.

• International Journal of Aeronautical and Space Sciences
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• v.5 no.2
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• pp.1-8
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• 2004

Real-Time Kinematic GPS positioning is widely used for many applications.Resolving ambiguities is the key to precise positioning. Integer ambiguity resolution isthe process of resolving the unknown cycle ambiguities of double difference carrierphase data as integers. Two important issues of resolving are efficiency andreliability. In the conventional search techniques, we generally used chi-squarerandom variables for decision variables. Mathematically, a chi-square random variableis the sum of mutually independent, squared zero-mean unit-variance normal(Gaussian) random variables. With this base knowledge, we can separate decisionvariables to several normal random variables. We showed it with related equationsand conceptual diagrams. With this separation, we can improve the computationalefficiency of the process without losing the needed performance. If we averageseparated normal random variables sequentially, averaged values are also normalrandom variables. So we can use them as decision variables, which prevent from asudden increase of some decision variable. With the method using averaged decisionvalues, we can get the solution more quicklv and more reliably.To verify the performance of our proposed algorithm, we conducted simulations.We used some visual diagrams that are useful for intuitional approach. We analyzedthe performance of the proposed algorithm and compared it to the conventionalmethods.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.134-134
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• 2021

Precipitation is a crucial component of water cycle and play a key role in hydrological processes. Traditionally, gauge-based precipitation is the main method to achieve high accuracy of rainfall estimation, but its distribution is sparsely in mountainous areas. Recently, satellite-based precipitation products (SPPs) provide grid-based precipitation with spatio-temporal variability, but SPPs contain a lot of uncertainty in estimated precipitation, and the spatial resolution quite coarse. To overcome these limitations, this study aims to generate new grid-based daily precipitation using Automatic weather system (AWS) in Korea and multiple SPPs(i.e. CHIRPSv2, CMORPH, GSMaP, TRMMv7) during the period of 2003-2017. And this study used a machine learning based Random Forest (RF) model for generating new merging precipitation. In addition, several statistical linear merging methods are used to compare with the results of the RF model. In order to investigate the efficiency of RF, observed data from 64 observed Automated Synoptic Observation System (ASOS) were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the random forest model showed higher accuracy than each satellite rainfall product and spatio-temporal variability was better reflected than other statistical merging methods. Therefore, a random forest-based ensemble satellite precipitation product can be efficiently used for hydrological simulations in ungauged basins such as the Mekong River.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.4
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• pp.355-361
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• 2011

The power control of the existing heating element has been using the On-Off control, phase control, and PWM control. In case of controlling power PTC heating element developed recently with the existing method, the temperature is unable to be precisely controlled or the harmful electromagnetic wave to human body is generated. In this paper, We suggest the power control of PTC heating cable using variable AC Cycles. This regards the AC cycle of N as the unit of the power control. It determines On-Off for each cycle. It is the AC power control method in which it arranges the on-cycle in N cycles in the random and it supplies the current continuously. At this time. the minimal electric power amount becomes 1/N. The maximum current amount becomes 1 and sets up the number of on cycles according to the set value and can control the electric power with the step of N consistently. In the PTC heating system, we show that proposed power control method is superior in the EMI and temperature control property using MATLAB simulation, experiments and measurements.

• Journal of Computing Science and Engineering
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• v.2 no.3
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• pp.249-273
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• 2008

Epidemic protocols have two fundamental assumptions. One is the availability of a mechanism that provides each node with a set of log(N) (fanout) nodes to gossip with at each cycle. The other is that the network size N is known to all member nodes. While it may be trivial to support these assumptions in small systems, it is a challenge to realize them in large open dynamic systems, such as peer-to-peer (P2P) systems. Technically, since the most fundamental parameter of epidemic protocols is log(N), without knowing the system size, the protocols will be limited. Further, since the network churn, frequently observed in P2P systems, causes rapid membership changes, providing a different set of log(N) at each cycle is a difficult problem. In order to support the assumptions, the fanout nodes should be selected randomly and uniformly from the entire membership. This paper investigates one possible solution which addresses both problems; providing at each cycle a different set of log(N) nodes selected randomly and uniformly from the entire network under churn, and estimating the dynamic network size in the number of nodes. This solution improves the previously developed distributed algorithm called Shuffle to deal with churn, and utilizes the Shuffle infrastructure to estimate the dynamic network size. The effectiveness of the proposed solution is evaluated by simulation. According to the simulation results, the proposed algorithms successfully handle network churn in providing random log(N0 fanout nodes, and practically and accurately estimate the network size. Overall, this work provides insights in designing epidemic protocols for large scale open dynamic systems, where the protocols behave autonomically.

• Asian-Australasian Journal of Animal Sciences
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• v.23 no.2
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• pp.169-174
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• 2010

A meta-analysis was conducted to summarize the results of studies which have described the profiles of hormones during the oestrous cycle in buffalo using a fixed effect model and a random effect model. Plasma progesterone concentrations were lowest (0.30${\pm}$0.06 ng/ml) during the peri-oestrous phase and increased (p = 0.067) through the early luteal phase to a maximum concentration (1.94${\pm}$0.03 ng/ml) during the mid-luteal phase. Circulating plasma inhibin and estradiol concentrations were lowest (0.31${\pm}$0.01 and 11.04${\pm}$0.13 ng/ml) during the mid-luteal phase, increased through the late luteal phase to maximum concentrations (0.44${\pm}$0.02 and 22.48${\pm}$0.32 ng/ml) during the peri-oestrous phase. Plasma FSH concentrations were lowest during the early luteal phase and increased through the mid-luteal phase to a maximum concentration during the peri-oestrous phase. Peripheral prolactin concentrations were lowest during the late luteal phase and increased to a maximum concentration during the peri-oestrous phase which then declined (p = 0.716) during the early luteal phase. Peripheral plasma cortisol concentrations decreased from 2.68${\pm}$0.14 ng/ml during the early luteal phase to 1.43${\pm}$0.27 ng/ml during the mid-luteal phase (p<0.001) which then increased to 2.06${\pm}$0.17 ng/ml during the late luteal phase. Plasma $T_{5}$ concentrations decreased from the late luteal phase to the peri-oestrous phase (p<0.001) which then increased during the early luteal phase. $T_{4}$ concentrations increased from the late luteal phase to the peri-oestrous phase which then decreased during the early luteal phase.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.1
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• pp.51-58
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• 2014

A LFSR is commonly used for various stream cryptography applications to generate random numbers. A Leap-ahead LFSR was presented to generate a multi-bits random number per cycle. It only requires a single LFSR and it has an advantages in hardware complexity. However, it suffers from the significant reduction of maximum period of the generated random numbers. This paper presents the new segmented Leap-ahead LFSR to solve this problem. It consists of two segmented LFSRs. We prove the efficiency of the proposed segmented architecture using the precise mathematical analysis. We also demonstrate the proposed comparison results with other counterparts using Xinilx Vertex5 FPGA. The proposed architecture can increase 2.5 times of the maximum period of generated random numbers compared to the typical Leap-ahead architecture.