• Composites Research
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• v.36 no.1
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• pp.53-58
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• 2023

The PIC design method is assigning different stacking sequences for each shell element through the preliminary FE analysis. In previous study, machine learning was applied to the PIC design method in order to assign the region efficiently, and the training data is labeled by dividing each region into tension, compression, and shear through the preliminary FE analysis results value. However, since buckling is not considered, when buckling occurs, it can't be divided into appropriate loading type. In the present study, it was proposed PIC-NTL (PIC design using novel technique for analyzing load type) which is method for applying a novel technique for analyzing load type considering buckling to the conventional PIC design. The stress triaxiality for each ply were analyzed for buckling analysis, and the representative loading type was designated through the determined loading type within decision area divided into two regions of the same size in the thickness direction of the elements. The input value of the training data and label consisted in coordination of element and representative loading type of each decision area, respectively. A machine learning model was trained through the training data, and the hyperparameters that affect the performance of the machine learning model were tuned to optimal values through Bayesian algorithm. Among the tuned machine learning models, the SVM model showed the highest performance. Most effective stacking sequence were mapped into PIC tube based on trained SVM model. FE analysis results show the design method proposed in this study has superior external loading resistance and energy absorption compared to previous study.

• Information Systems Review
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• v.10 no.2
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• pp.137-158
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• 2008

Rapid development of various information technologies creates new opportunities in online and offline markets. In this changing market environment, customers have various demands on new products and services. Therefore, their power and influence on the markets grow stronger each year. Companies have paid great attention to customer relationship management. Especially, personalized product recommendation systems, which recommend products and services based on customer's private information or purchasing behaviors in stores, is an important asset to most companies. CRM is one of the important business processes where reliable information is mined from customer database. Data mining techniques such as artificial intelligence are popular tools used to extract useful information and knowledge from these customer databases. In this research, we propose a recommendation system that predicts customer's purchase intention. Then, customer's purchasing intention of specific product is predicted by using data mining techniques using receipt data set. The performance of this suggested method is compared with that of other data mining technologies.

• 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.

• Journal of Korean Society of Transportation
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• v.18 no.4
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• pp.117-126
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• 2000

Conventional methods for collecting origin-destination trips have been mainly relied on the surveys of home or roadside interview. However, the methods tend to be costly, labor intensive and time disruptive to the trip makers, thus the methods are not considered suitable for Planning applications such as routing guidance, arterial management and information Provision, as the parts of deployments in Intelligent Transport Systems Motivated by the problems, more economic ways to estimate origin-destination trip tables have been studied since the late 1970s. Some of them, which have been estimating O-D table from link traffic counts are generally Entropy maximizing, Maximum likelihood, Generalized least squares(GLS), and Bayesian inference estimation etc. In the Paper, with user equilibrium constraint we formulate GLS problem for estimating O-D trips and develop a solution a1gorithm by using Genetic Algorithm, which has been known as a g1oba1 searching technique. For the purpose of evaluating the method, we apply it to Seoul inner ringroad and compare it with gradient method proposed by Spiess(1990). From the resu1ts we fond that the method developed in the Paper is superior to other.

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.287-296
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• 2003

There has been much research focused on collaborative filtering technique in Recommender System. However, these studies have shown the First-Rater Problem and the Sparsity Problem. The main purpose of this Paper is to solve these Problems. In this Paper, we suggest the user's predicting preference method using Bayesian estimated value and the associative user clustering for the recalculation of preference. In addition to this method, to complement a shortcoming, which doesn't regard the attribution of item, we use Representative Attribute-Neighborhood method that is used for the prediction when we find the similar neighborhood through extracting the representative attribution, which most affect the preference. We improved the efficiency by using the associative user's clustering analysis in order to calculate the preference of specific item within the cluster item vector to the collaborative filtering algorithm. Besides, for the problem of the Sparsity and First-Rater, through using Association Rule Hypergraph Partitioning algorithm associative users are clustered according to the genre. New users are classified into one of these genres by Naive Bayes classifier. In addition, in order to get the similarity value between users belonged to the classified genre and new users, and this paper allows the different estimated value to item which user evaluated through Naive Bayes learning. As applying the preference granted the estimated value to Pearson correlation coefficient, it can make the higher accuracy because the errors that cause the missing value come less. We evaluate our method on a large collaborative filtering database of user rating and it significantly outperforms previous proposed method.

• Journal of Korean Society of Transportation
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• v.30 no.6
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• pp.37-46
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• 2012

The number of traffic accidents caused by elderly drivers over the age of 65 has surged over the past ten years from 37,000 to 274,000 cases. The proportion of elderly drivers' accidents has jumped 3.1 times from 1.2% to 3.7% out of all traffic accidents, and traffic safety organizations are pursuing diverse measures to address the situation. Above all, connecting safety measures with an in-depth research on behavioral and physical characteristics of elderly drivers will prove vital. This study conducted an empirical research linking the driving characteristics and traffic accidents by elderly drivers based on the Driving Aptitude Test items and traffic accident data, which enabled the measurement of behavioral characteristics of elderly drivers. In developing the Influence Model, we applied the zero-inflated Poisson (ZIP) regression model and selected an accident prediction model based on the Bayesian Influence in regards to the ZIP regression model and the zero-inflated negative binomial (ZINB) regression model. According to the results of the AAE analysis, the ZIP regression model was more appropriate and it was found that three variables? prediction of velocity, diversion, and cognitive ability? had a relation of influence with traffic accidents caused by elderly drivers.

• Korean Journal of Microbiology
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• v.54 no.3
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• pp.254-265
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• 2018

Avian influenza recently damaged the poultry industry, which suffered a huge economic loss reaching billions of U.S. dollars in South Korea. Transmission routes of the pathogens would help plan to control and limit the spread of the devastating biological tragedy. Phylogenetic analyses of pathogen's DNA sequences could sketch transmission trees relating hosts with directed edges. The last decade has seen the methodological development of inferring transmission trees using epidemiological as well as genetic data. Here, I reanalyzed the DNA sequence data that had originated in the highly pathogenic avian influenza H5N8 outbreak of South Korea in 2014. The H5N8 viruses spread geographically contiguously from the origin of the outbreak, Jeonbuk. The Jeonbuk origin viruses were known to spread to four provinces neighboring Jeonbuk. I estimated the transmission tree of the host domestic and migratory wild birds after combining multiple runs of Markov chain Monte Carlo using a Bayesian method for inferring transmission trees. The estimated transmission tree, albeit with a rather large uncertainty in the directed edges, showed that the viruses spread from Jeonbuk through Chungnam to Gyeonggi. Domestic birds of breeder or broiler ducks were estimated to appear to be at the terminal nodes of the transmission tree. This observation confirmed that migratory wild birds played an important role as one of the main infection mediators in the avian influenza H5N8 outbreak of South Korea in 2014.

• Journal of Conservation Science
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• v.34 no.6
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• pp.481-492
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• 2018

We conducted TL/OSL dating for the earthenware kilns in the Bongsan-ri archaeological site, Osong, which was occupied from the late nineteenth to the late twentieth century. With the SAR-TL/OSL method, paleodose was determined from the equivalent dose during the burial period($ED_{burial}$), the background dose($ED_{BG}$), the fading correction factor(f), and the overestimation correction factor(C). The annual dose rates and their provenance were evaluated from the measurement of natural radionuclides $^{238}U$, $^{232}Th$, and $^{40}K$. Because the comprehensive absolute age was provided by combining the resulting TL/OSL and radiocarbon data, we concluded that, for the absolute chronology of a modern archaeological site, TL/OSL dating and radiocarbon dating must be carried out together and summed. The construction and occupation of earthenware kilns in the Bongsan-ri site had changed from stage I (No.5, 6 kilns), to stage II (No.1, 2, 3 kilns), to stage III (No.4) in chronological order. When Bayesian statistics were applied, we found that the absolute ages of occupation for stages I, II, and III correspond to AD $1910{\pm}23$, AD $1970{\pm}10$, and AD $1987{\pm}4$. These results were in good agreement with the archaeological context or chronology.

• Journal of the Society of Disaster Information
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• v.19 no.1
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• pp.161-172
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• 2023

Safety education delivered to construction workers in a lecture manner has limitations in concentration and immersion, so delivery power and interest are low. In order to improve unstable behavior through education and prevent safety accidents, it is necessary to change the paradigm to hands-on education. Purpose: Experiential safety education aims to contribute to preventing accidents for construction workers by quickly recognizing risks, improving emergency response skills, and verifying the effectiveness of pre- and post-learning. Method: Based on a survey of workers who experienced the same work environment as the actual construction site, an opinion survey on the pre- and post-safety experience education and a variable measurement tool were planned, and a research hypothesis was established. Results: The Bayesian theory and MC simulation analysis were used to analyze the structural equation model, and the change in construction worker behavior was confirmed through the intended safety (A), non-experiential education in the sub-area of anxiety (B), average, standard deviation, and minimum and maximum values. Conclusion: The effect of education and industrial accidents are reduced only when construction workers are motivated to participate.

• Korean Journal of Ecology and Environment
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• v.56 no.2
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• pp.140-150
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• 2023

The Hangang River^* is necessary to manage the water environment of severe pollution due to the high density of residential areas, parks, and agriculture and the large population concentrated there. Benthic macroinvertebrates, such as chironomids larvae, are bioindicator species that reflect environmental changes and are crucial for water quality monitoring. In this study, we investigated morphological characteristics and molecular analysis of the chironomids larvae inhabiting the Hangang River area for water environment surveys. For this research, 20 rivers, lakes, and urban area in the Hangang River basin were selected. Chironomids larvae were collected from July to September 2022, and their appearance and characteristics were identified through morphological identification. In addition, phylogenetic analysis was performed based on the mtCOI gene sequences of the collected chironomids larvae, and identification at the genus level was confirmed. As a result, 32 species and 18 genera of 3 subfamilies of Chironomidae larvae were identified, and Stictochironomus sp. dominated most sites(6 sites). The morphological characteristics of the identified chironomids larvae, such as the mentum, ventromental plate, and antenna, were organized into table and pictorial keys, and a Bayesian inference molecular phylogeny was presented. These results provide basic morphological information for genus-level identification and can be used as fundamental information for water quality management.