• Journal of information and communication convergence engineering
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• v.19 no.4
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• pp.234-240
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• 2021

As the number of pet dog-related businesses is rising rapidly, there is an increasing need for reliable pet dog health information systems for casual pet owners, especially those caring for older dogs. Our goal is to implement a mobile pre-diagnosis system that can provide a first-hand pre-diagnosis and an appropriate coping strategy when the pet owner observes abnormal symptoms. Our previous attempt, which is based on the fuzzy C-means family in inference, performs well when only relevant symptoms are provided for the query, but this assumption is not realistic. Thus, in this paper, we propose a hybrid inference structure that combines fuzzy association memory and a double-layered fuzzy C-means algorithm to infer the probable disease with robustness, even when noisy symptoms are present in the query provided by the user. In the experiment, it is verified that our proposed system is more robust when noisy (irrelevant) input symptoms are provided and the inferred results (probable diseases) are more cohesive than those generated by the single-phase fuzzy C-means inference engine.

• Corrosion Science and Technology
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• v.21 no.4
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• pp.243-249
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• 2022

The objective of the present study was to perform failure analysis of double-layered bellow (expansion joint), a core part of stress reliever, used to relieve axial stresses induced by thermal expansion of heat-transport pipes in a district heating system. The bellow underwent tensile or compressive stresses due to its structure in terms of position. A leaked position sufferred a fatigue with a tensile component for decades. A cracked bellow contained a higher fraction of martensitic phase because of manufacturing and usage histories, which induced more brittleness on the component. Inclusions in the inner layer of the bellow acted as a site of stress concentration, from which cracks initiated and then propagated along the hoop direction from the inner surface of the inner layer under fatigue loading conditions. As the crack reached critical thickness, the crack propagated to the outer surface at a higher rate, resulting in leakage of the stress reliever.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.04a
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• pp.93-94
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• 2022

The presence of chloride (Cl-) ions in environments causes localized corrosion resulting decrease the durability of the structures. In this study, 5% Mg containing Al alloys (Al-5Mg) wire used vis-à-vis compared its corrosion resistance with pure Al in 3.5wt.% NaCl solution with exposure periods. Initially both wires exhibited identical open circuit potential (OCP) attributed to the presence of native oxide film on the surface but with the exposure periods it shifted towards active direction owing to the dissolution of oxide film. The pure Al continuously shifted the OCP towards active direction while Al-5Mg shows stabilization of OCP after 8 days of exposure. The OCP of Al-5Mg is slightly higher compared to pure Al wire owing to the activeness of Mg. The total impedance of the Al-5Mg alloy is almost three times greater than pure Al with exposure periods in 3.5 wt.% NaCl solution. It might be formation of Al-Mg LDH (layered double hydroxide) thin film onto the surface.

• Steel and Composite Structures
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• v.49 no.2
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• pp.231-244
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• 2023

Many of the recent investigations in the field of geotechnical engineering focused on the bearing capacity theories of multilayered soil. A number of factors affect the bearing capacity of the soil, such as soil properties, applied overburden stress, soil layer thickness beneath the footing, and type of design analysis. An extensive number of finite element model (FEM) simulation was performed on a prototype slope with various abovementioned terms. Furthermore, several non-linear artificial intelligence (AI) models are developed, and the best possible neural network system is presented. The data set is from 3443 measured full-scale finite element modeling (FEM) results of a circular shallow footing analysis placed on layered cohesionless soil. The result is used for both training (75% selected randomly) and testing (25% selected randomly) the models. The results from the predicted models are evaluated and compared using different statistical indices (R² and RMSE) and the most accurate model BBO (R²=0.9481, RMSE=4.71878 for training and R²=0.94355, RMSE=5.1338 for testing) and TLBO (R²=0.948, RMSE=4.70822 for training and R²=0.94341, RMSE=5.13991 for testing) are presented as a simple, applicable formula.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.93-107
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• 2014

In this paper, we report what we have observed with regard to user-perspective issue clustering based on multi-layered two-mode network analysis. This work is significant in the context of data collection by companies about customer needs. Most companies have failed to uncover such needs for products or services properly in terms of demographic data such as age, income levels, and purchase history. Because of excessive reliance on limited internal data, most recommendation systems do not provide decision makers with appropriate business information for current business circumstances. However, part of the problem is the increasing regulation of personal data gathering and privacy. This makes demographic or transaction data collection more difficult, and is a significant hurdle for traditional recommendation approaches because these systems demand a great deal of personal data or transaction logs. Our motivation for presenting this paper to academia is our strong belief, and evidence, that most customers' requirements for products can be effectively and efficiently analyzed from unstructured textual data such as Internet news text. In order to derive users' requirements from textual data obtained online, the proposed approach in this paper attempts to construct double two-mode networks, such as a user-news network and news-issue network, and to integrate these into one quasi-network as the input for issue clustering. One of the contributions of this research is the development of a methodology utilizing enormous amounts of unstructured textual data for user-oriented issue clustering by leveraging existing text mining and social network analysis. In order to build multi-layered two-mode networks of news logs, we need some tools such as text mining and topic analysis. We used not only SAS Enterprise Miner 12.1, which provides a text miner module and cluster module for textual data analysis, but also NetMiner 4 for network visualization and analysis. Our approach for user-perspective issue clustering is composed of six main phases: crawling, topic analysis, access pattern analysis, network merging, network conversion, and clustering. In the first phase, we collect visit logs for news sites by crawler. After gathering unstructured news article data, the topic analysis phase extracts issues from each news article in order to build an article-news network. For simplicity, 100 topics are extracted from 13,652 articles. In the third phase, a user-article network is constructed with access patterns derived from web transaction logs. The double two-mode networks are then merged into a quasi-network of user-issue. Finally, in the user-oriented issue-clustering phase, we classify issues through structural equivalence, and compare these with the clustering results from statistical tools and network analysis. An experiment with a large dataset was performed to build a multi-layer two-mode network. After that, we compared the results of issue clustering from SAS with that of network analysis. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The sample dataset contains 150 million transaction logs and 13,652 news articles of 5,000 panels over one year. User-article and article-issue networks are constructed and merged into a user-issue quasi-network using Netminer. Our issue-clustering results applied the Partitioning Around Medoids (PAM) algorithm and Multidimensional Scaling (MDS), and are consistent with the results from SAS clustering. In spite of extensive efforts to provide user information with recommendation systems, most projects are successful only when companies have sufficient data about users and transactions. Our proposed methodology, user-perspective issue clustering, can provide practical support to decision-making in companies because it enhances user-related data from unstructured textual data. To overcome the problem of insufficient data from traditional approaches, our methodology infers customers' real interests by utilizing web transaction logs. In addition, we suggest topic analysis and issue clustering as a practical means of issue identification.

• Journal of Digital Convergence
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• v.13 no.10
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• pp.271-278
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• 2015

Recently, bit data is difficult to easily collect the desired data because big data is collected via the Internet. Big data is higher than the rate at which the data type and the period of time for which data is collected depending on the size of data increases. In particular, since the data of all different by the intended use and the type of data processing accuracy and computational cost is one of the important items. In this paper, we propose data processing method using a dual-chain in a manner to minimize the computational cost of the data when data is correctly extracted at the same time a multi-layered process through the desired number of the user and different kinds of data on the Internet. The proposed scheme is classified into a hierarchical data in accordance with the intended use and method to extract various kinds of data. At this time, multi-processing and tie the data hash with the double chain to enhance the accuracy of the reading. In addition, the proposed method is to organize the data in the hash chain for easy access to the hierarchically classified data and reduced the cost of processing the data. Experimental results, the proposed method is the accuracy of the data on average 7.8% higher than conventional techniques, processing costs were reduced by 4.9% of the data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.55-63
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• 2020

Road traffic noise is a major complaint. Porous pavement (PP) has been proposed as an effective method for reducing road traffic noise, but it has not been applied much due to the lack of quantitative evaluation. In this study, the noise reduction of single-layer porous pavement (SLPP) and double-layer porous pavement (DLPP) was evaluated. The noise was measured using the CPX method, and the driving speed was measured every 10km/h from 50km/h to 80km/h. The differences in noise level between the two PPs were statistically significant. The driving speed had no significant effect on the difference in noise between the two PPs. The DLPP showed a 6.6dB(A) reduction in average and a 6.3dB(A) reduction at the 95% confidence level compared to the SLPP. Reducing noise by 5dB(A) is equivalent to reducing traffic to 1/3 or lowering the vehicle's speed to 1/2. Sensitively, it is possible to recognize a 3dB(A) and 5dB(A) difference. The DLPP and SLPP were very effective in reducing traffic noise.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.9
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• pp.92-102
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• 2020

Porous pavement (PP) has attracted attention as a new alternative measure against road traffic noise. PP refers to pavement that reduces the fines in the asphalt mixture to form voids. These voids can reduce traffic accidents and friction noise. For active application, verification of the noise reduction effect is required. In this study, the noise reduction of single-layer PP(SLPP) and double layer PP(DLPP) was analyzed. First, the Sejong section was selected, and traffic noise was measured using the SPB method on the roadside. The traffic volume, speed, and mixing ratio of large vehicles were measured. As a result, the DLPP was evaluated to be 7.95 dB(A) smaller on average and 7.57dB(A) smaller at the 95% reliability level than the SLPP. The traffic volume was more influential than the speed and the mixing rate of large vehicles. As the traffic volume increased, the noise increased, but the difference in noise between the two pavements decreased gradually. The results showed that the most effective way to reduce road traffic noise is to change the road pavement rather than reduce traffic speed, restrict traffic for heavy vehicles, or reduce traffic volume.

• Journal of the Korea institute for structural maintenance and inspection
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• v.19 no.5
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• pp.83-91
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• 2015

With varying conditions of concrete surface, induced chloride contents are changed and this is a key parameter for steel corrosion and service life in RC (Reinforced Concrete) structures. Many surface enhancement techniques using impregnation have been developed, however the evaluation techniques for chloride behavior through doubly layered media and time-dependent diffusion are rarely proposed. This paper presents an analysis technique considering double-layer concrete and time-dependent diffusion behavior, and the results are compared with those from the previous test results through reverse analysis. The chloride profiles from the surface-impregnated concrete exposed to atmospheric, tidal, submerged zone for 2 years are adopted. Furthermore surface chloride contents and diffusion coefficients are obtained, and are compared with those from Life365. Through consideration of time effect, the relative error decreases from 0.28 to 0.20 in atmospheric, 0.29 to 0.11 in tidal, and 0.54 to 0.40 in submerged zone, respectively, which shows more reasonable results. Utilizing the diffusion coefficients from Life365, relative errors increases and it needs deeper penetration depth (e) and lower diffusion coefficient ratio ($D_1/D_2$) due to higher diffusion coefficient.

• Journal of the Korean Geotechnical Society
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• v.25 no.9
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• pp.67-76
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• 2009

The problems of bearing capacity, settlement and shear deformation occur when constructing a structure such as harbor, airport and bridge on soft ground of marine clay, silty clay or sandy soil. Various ground improvement methods are applied to obtain preceding settlement of soft ground and strength increase. In this study, to analyze the applicability of PBD method in deep soft ground, the compound drainage capacity test was operated in comparison with SD. As a result of the test, a minimum drainage capacity of drain material was estimated to be more than $10\;cm^3/sec$ at a more than $400\;kN/m^2$ and less than $5\;cm^3/sec$ at a more than $500\;kN/m^2$ confining pressure in case of single core PBD. In case of double core PBD, it was estimated to be more than $10\;cm^3/sec$ at a more than $500\;kN/m^2$ confining pressure.