• The Korean Journal of Applied Statistics
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• v.23 no.2
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• pp.335-344
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• 2010

Reliability of the estimation is usually damaged in the situation where a linear regression model without spatial dependencies is employed to the spatial data analysis. In this study, we considered the conditional autoregressive model in order to construct spatial association structures and estimate the parameters via the Bayesian approaches. Finally, we compared the performances of the models with spatial effects and the ones without spatial effects. We analyzed the yearly total crime count data measured from each of 25 districts in Seoul, South Korea in 2007.

• Asian-Australasian Journal of Animal Sciences
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• v.19 no.7
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• pp.943-952
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• 2006

The genetic variation in 10 indigenous Caucasian sheep breeds was studied with 14 micro-satellite loci in order to determine the genetic diversity among and between the breeds. Five breeds from Asia, five breeds from Europe and one breed from Africa, were included in order to study any relationships or influences they may have with the Caucasian sheep analyzed. A Karakul population from Uzbekistan was included in the study to see whether there was any Central Asian influence. All the 14 loci were found to be polymorphic in all the breeds, with the exception of ILST0056, which was monomorphic in Imeretian. A total of 231 alleles were generated from all the 688 individuals of the sheep analyzed. The mean number of alleles (MNA) at each locus was 16.5. The total number of alleles detected in all samples ranged from 13 in several loci to 23 in OarJMP029. Out of total 308 Hardy-Weinberg Equilibrium (HWE) tests, 85 gave significant results. After Bonferroni correction for multiple tests, 30 comparisons still remained significant to the experimental levels. The Gala population was the most diverse and Imeretian the least diverse with a MNA of 8.50 and 5.51, respectively. Gene diversity estimates exhibited the same trend and ranged from 0.803 in Gala and 0.623 in Imeretian, but generally there is higher diversity among the Caucasian breeds in comparison to other eference breeds. The closest breeds were Tushin and Bozakh with Da of 0.113 and most distant breeds were $Djallonk{\acute{e}}$ and North Rondalsy with Da of 0.445. Principal Component (PC) analyses were done. PC1 described 14% of the differences. PC2, which described 13% of the differences, further separated the Caucasian breeds from Asian breeds except Karakul and Awasi, and the two British breeds. PC3 described 10% of the differences, allowing better differentiation of the Caucasian breeds. A moderate degree of reliability was observed for individual-breed assignment from the 14 loci using different approaches among which the Bayesian method proved to be the most efficient. About 72% of individuals analyzed were correctly assigned to their respective breeds.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.6
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• pp.143-151
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• 2009

Extreme hydrologic events cause serious disaster, such as flood and drought. Many researchers have an effort to estimate design rainfalls or discharges. This study evaluated parameter estimation methods to estimate probability rainfalls with low uncertainty which will be used in design rainfalls. This study collected rainfall data from Incheon, Gangnueng, Gwangju, Busan, and Chupungryong gage station, and generated synthetic rainfall data using ARMA model. This study employed the maximum likelihood method and the Bayesian inference method for estimating parameters of the Gumbel and GEV distribution. Using a bootstrap resampling method, this study estimated the confidence intervals of estimated probability rainfalls. Based on the comparison of the confidence intervals, this study recommended a proper parameter estimation method for estimating probability rainfalls which have a low uncertainty.

• Journal of KIISE:Software and Applications
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• v.28 no.12
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• pp.875-884
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• 2001

Although the self organizing map (SOM) is widely utilized in such fields of data visualization and topology preserving mapping, since it should have the topology fixed before trained, it has some shortcomings that it is difficult to apply it to practical problems, and classification capability is quite low despite better clustering performance. To overcome these points this paper proposes the dynamic topology preserving self-organizing map(DTSOM) that dynamically splits the output nodes on the map and trains them, and attempts to improve the classification capability by combining multiple DTSOMs K-Winner method has been applied to combine DTSOMs which produces K outputs with winner node selection method. This produces even better performance than the conventional combining methods such as majority voting weighting, BKS Bayesian, Borda, Condorect and reliability sum. DTSOM remedies the shortcoming of determining the topology in advance, and the classification rate increases significantly by combing multiple maps trained with different features. Experimental results with handwritten digit recognition indicate that the proposed method works out to problems of conventional SOM effectively so to improve the classification rate to 98.1%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.4B
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• pp.354-361
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• 2011

Increasing interest and technological advances in smart home has led to active research on context-awareness service and prediction algorithms such as Bayesian Networks, Tree-Dimensional Structures and Genetic prediction algorithms. Context-awareness service presents that providing automatic customized service regarding individual user's pattern surely helps users improve the quality of life. However, it is difficult to implement context-awareness service because the problems are that handling coincidence with context information and exceptional cases have to consider. To overcome this problem, we proposes an Intelligent Sequential Matching Algorithm(ISMA), models context-awareness service using Timed Petri-net(TPN) which is petri-net to have time factor. The example scenario illustrates the effectiveness of the Timed Petri-net model and our proposed algorithm improves average 4~6% than traditional in the accuracy and reliability of prediction.

• Animal Bioscience
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• v.34 no.2
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• pp.163-171
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• 2021

Objective: Considering the importance of dairy farming and the negative effects of heat stress, more tolerant genotypes need to be identified. The objective of this study was to investigate the effect of heat stress via temperature-humidity index (THI) and diurnal temperature variation (DTV) in the genetic evaluations for daily milk yield of Holstein dairy cattle, using random regression models. Methods: The data comprised 94,549 test-day records of 11,294 first parity Holstein cows from Brazil, collected from 1997 to 2013, and bioclimatic data (THI and DTV) from 18 weather stations. Least square linear regression models were used to determine the THI and DTV thresholds for milk yield losses caused by heat stress. In addition to the standard model (SM, without bioclimatic variables), THI and DTV were combined in various ways and tested for different days, totaling 41 models. Results: The THI and DTV thresholds for milk yield losses was THI = 74 (-0.106 kg/d/THI) and DTV = 13 (-0.045 kg/d/DTV). The model that included THI and DTV as fixed effects, considering the two-day average, presented better fit (-2logL, Akaike information criterion, and Bayesian information criterion). The estimated breeding values (EBVs) and the reliabilities of the EBVs improved when using this model. Conclusion: Sires are re-ranking when heat stress indicators are included in the model. Genetic evaluation using the mean of two days of THI and DTV as fixed effect, improved EBVs and EBVs reliability.

• Geotechnical Engineering
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• v.11 no.1
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• pp.9-22
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• 1995

The purpose of this study is to propose safety factors of pile bearing capacity based on the reliability analysis. Each prediction method involves various degrees of uncertainties. To account for these uncertainties in a systematic way, the ratios of the measured bearing capacity from pile load tests to the predicted bearing capacity are represented in the form of a probability density function. The safety factor for each design method is obtained so that the probability of pile foundation failure is less than 10-3. The Bayesian theorem is applied in a way that the distribution using static formulae is assumed to be the A-prior and the distribution using dynamic formulae or wave equation based methods is assumed to be the likelihood, and these two are combined to obtain the posterior which has the reduced uncertainty. The results of this study show that static formulae of the pile bearing capacity using the 5.p.7. N-value as well as dynamic formulae are highly unreliable and have to have the safety factor more than 7.4 : the wave equation analysis using PDA(Pile Driving Analyzer) system the most reliable with the safety factor close to 2.7. The safety factor could be reduced certain amount by adoption the Bayes methodology in pile design.

• The Journal of Engineering Geology
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• v.26 no.4
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• pp.485-495
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• 2016

To reinforce and improve the soft ground under a breakwater while using materials efficiently, the replacement ratio and leaving periods of surcharge load are optimized probabilistically. The results of Bayesian updating of the random variables using prior information decrease uncertainty by up to 39.8%, and using prior information with more samples results in a sharp decrease in uncertainty. Replacement ratios of 15%-40% are analyzed using First Order Reliability Method and Monte Carlo simulation to optimize the replacement ratio. The results show that replacement ratios of 20% and 25% are acceptable at the column jet grouting area and the granular compaction pile area, respectively. Life cycle costs are also compared to optimize the replacement ratios within allowable ranges. The results show that a range of 20%-30% is the most economical during the total life cycle. This means that initial construction cost, maintenance cost and failure loss cost are minimized during total life cycle. Probabilistic analysis for leaving periods of shows that three months acceptable. Design optimization with respect to life cycle cost is important to minimize maintenance costs and retain the performance of the structures for the required period. Therefore, more case studies that consider the maintenance costs of soil structures are necessary to establish relevant design codes.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.10
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• pp.447-454
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• 2015

This paper proposes geographical name denoising by machine learning of event detection based on twitter. Recently, the increasing number of smart phone users are leading the growing user of SNS. Especially, the functions of short message (less than 140 words) and follow service make twitter has the power of conveying and diffusing the information more quickly. These characteristics and mobile optimised feature make twitter has fast information conveying speed, which can play a role of conveying disasters or events. Related research used the individuals of twitter user as the sensor of event detection to detect events that occur in reality. This research employed geographical name as the keyword by using the characteristic that an event occurs in a specific place. However, it ignored the denoising of relationship between geographical name and homograph, it became an important factor to lower the accuracy of event detection. In this paper, we used removing and forecasting, these two method to applied denoising technique. First after processing the filtering step by using noise related database building, we have determined the existence of geographical name by using the Naive Bayesian classification. Finally by using the experimental data, we earned the probability value of machine learning. On the basis of forecast technique which is proposed in this paper, the reliability of the need for denoising technique has turned out to be 89.6%.

• Journal of the Korean earth science society
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• v.42 no.6
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• pp.688-699
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• 2021

On September 23, 2020, at 1:39 a.m., a bright fireball above Seocheon was observed across the country. Two fireball explosions were identified in the images of the All-Sky Camera (ASC), and the shock waves were recorded at seismic and infrasound stations in the southwestern Korean Peninsula. The location of the explosion was estimated by a Bayesian-based location method using the arrival times of the fireball-associated seismic and infrasound signals at 17 stations. Realistic azimuth- and rang-dependent propagation speeds of sound waves were incorporated into the location method to increase the reliability of the results. The location of the sound source was found to be 36.050°N, 126.855°E at an altitude of 35 km, which was close to the location of the second fireball explosion. The two explosions were identified as sequential infrasound arrivals at local infrasound stations. Simulations of waveforms for long ranges explain the detection results at distant infrasound stations, up to ~266 km from the sound source. The dominant period of the signals recorded at five infrasound stations is about 0.4 s. A period-energy relation suggests the explosion energy was equivalent to ~0.3 ton of TNT.