• Structural Monitoring and Maintenance
• /
• v.10 no.3
• /
• pp.243-260
• /
• 2023

Indonesia has had seismic codes for earthquake-resistant structures designs since 1970 and has been updated five times to the latest in 2019. In updating the Indonesian seismic codes, seismic hazard maps for design also update, and there are changes to the Peak Ground Acceleration (PGA). Indonesian seismic design uses the concept of building performance levels consisting of Immediate occupancy (IO), Life Safety (LS), and Collapse Prevention (CP). Related to this performance level, cases still found that buildings were damaged more than their performance targets after the earthquake. Based on the above issues, this study aims to analyze the performance of base isolation design on existing target buildings and analyze the seismic fragility for a case study in Indonesia. The target building is a prototype design 8-story medium-rise residential building using the reinforced concrete moment frame structure. Seismic fragility analysis uses Incremental Dynamic Analysis (IDA) with Nonlinear Time History Analysis (NLTHA) and eleven selected ground motions based on soil classification, magnitude, fault distance, and earthquake source mechanism. The comparison result of IDA shows a trend of significant performance improvement, with the same performance level target and risk category, the base isolation structure can be used at 1.46-3.20 times higher PGA than the fixed base structure. Then the fragility analysis results show that the fixed base structure has a safety margin of 30% and a base isolation structure of 62.5% from the PGA design. This result is useful for assessing existing buildings or considering a new building's performance.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.27 no.6
• /
• pp.545-556
• /
• 2016

JPDAF is a method of updating target's state estimation by using posterior probability that measurements are originated from existing target in multi-target tracking. In this paper, we propose a multi-target tracking algorithm for falling cluster bombs separated from a mother bomb based on JPDAS method which is obtained by applying fixed-interval smoothing technique to JPDAF. The performance of JPDAF and JPDAS multi-target tracking algorithm is compared by observing the average of the difference between targets' state estimations obtained from 100 independent executions of two algorithms and targets' true states. Based on this, results of simulations for a radar tracking problem that show proposed JPDAS has better tracking performance than JPDAF is presented.

• Journal of Distribution Science
• /
• v.17 no.4
• /
• pp.77-85
• /
• 2019

Purpose - Statistics of Traditional Market is the only source of information on traditional markets, shopping street, and underground shopping street. The government conducts a survey of traditional market conditions every year to look at the current status of traditional markets and provide effective support. Therefore, this study examines the necessity and validity of updating about the Survey Population of Traditional Market Research design, data, and methodology - This study investigated the necessity of updating about the Survey Population of Traditional Market through literature review. Therefore this study examined the necessity of the current population based on the review of the population related to the sample design, methods, and the sampling frame. Next, we examined the change patterns of the population and the sample by dividing the population and sample of the current survey of the traditional market survey into the market unit, the store unit within the market, and finally the individual store unit. Results - As a result, the population of traditional market changes about 4~6%. Next, the analysis of the store unit in the market shows that the number of stores is very variable even though the market is continuously included in the survey target. Finally, as a result of examining the characteristics of individual stores, the stores with less than one year were more than 6% of the total surveyed stores based on the traditional market. These results are generally inconsistent with the idea that stores in traditional markets will operate for a long time in one place. Next, we proposed the establishment of a management system, applying Citizen Generated Data, and circulation survey. Additionally, this study proposes to change the stratification variables at the regional level rather than the market unit. Conclusions - Therefore, in this study, it is suggested that a current population of traditional market is needed updating, and that a population survey should be updated at least four years. In addition, a system for investigating traditional markets and districts was established and a circulation survey was proposed for efficient use of budgets. Based on these research results and policy suggestions, the future research directions are suggested.

• Korean Journal of Clinical Pharmacy
• /
• v.27 no.4
• /
• pp.276-283
• /
• 2017

Objective: Dyslipidemia is recognized as a prominent risk factor for cardiovascular and cerebrovascular diseases but it is manageable through therapeutic and lifestyle intervention. Interpreting the latest guidelines is essential for an application of recommendation from guidelines into clinical practice. Therefore, this study aimed to compare the most recent guidelines on dyslipidemia treatment recommendations in Korea and USA. Methods: This study analyzed and compared 2015 Korean guidelines for the management of dyslipidemia, 2013 American College of Cardiology/American Heart Association (ACC/AHA) guideline and 2016 supportive guidelines from ACC. Results: A comparison was made focused on the following: target patients based on cardiovascular risk assessment, target goal, and treatment strategies including statin and non-statin therapies. Four target patient groups by risk were suggested in 2015 Korean guideline and cardiovascular risk factors were also considered for initiation of lipid lowering therapy. Titrated statin regimen was recommended by Korean guideline to reach LDL cholesterol and non-HDL cholesterol target level. In 2013 ACC/AHA guideline, four statin benefit group was introduced considering ASCVD risk and high intensity statin or intermediate intensity statin use were recommended without dose titration. 2016 update was to support non-statin therapy based on updated evidence and new consideration of ezetimibe, PCSK9-inhibitor and bile acid sequestrant was brought up. Conclusion: Guidelines are continuously updating as new and important clinical data are constantly released along with the advent of newly approved drugs for lipid disorder. This article provides resources that facilitates uptake of these recommendations into clinical practice.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.40 no.4
• /
• pp.260-267
• /
• 2017

Quantum-inspired Genetic Algorithm (QGA) is a probabilistic search optimization method combined quantum computation and genetic algorithm. In QGA, the chromosomes are encoded by qubits and are updated by quantum rotation gates, which can achieve a genetic search. Asset-based weapon target assignment (WTA) problem can be described as an optimization problem in which the defenders assign the weapons to hostile targets in order to maximize the value of a group of surviving assets threatened by the targets. It has already been proven that the WTA problem is NP-complete. In this study, we propose a QGA and a hybrid-QGA to solve an asset-based WTA problem. In the proposed QGA, a set of probabilistic superposition of qubits are coded and collapsed into a target number. Q-gate updating strategy is also used for search guidance. The hybrid-QGA is generated by incorporating both the random search capability of QGA and the evolution capability of genetic algorithm (GA). To observe the performance of each algorithm, we construct three synthetic WTA problems and check how each algorithm works on them. Simulation results show that all of the algorithm have good quality of solutions. Since the difference among mean resulting value is within 2%, we run the nonparametric pairwise Wilcoxon rank sum test for testing the equality of the means among the results. The Wilcoxon test reveals that GA has better quality than the others. In contrast, the simulation results indicate that hybrid-QGA and QGA is much faster than GA for the production of the same number of generations.

• Journal of Korea Multimedia Society
• /
• v.21 no.10
• /
• pp.1195-1202
• /
• 2018

Artificial neural network is widely used for its excellent performance and implementability. However, traditional neural network needs to learn the system from scratch, with the addition of new input data, the variation of the observation environment, or the change in the form of input/output data. To resolve such a problem, the technique of transfer learning has been proposed. Transfer learning constructs a newly developed target system partially updating existing system and hence provides much more efficient learning process. Until now, transfer learning is mainly studied in the field of image processing and is not yet widely employed in acoustic data processing. In this paper, focusing on the scalability of transfer learning, we apply the concept of transfer learning to the problem of guitar chord classification and evaluate its performance. For this purpose, we build a target system of convolutional neutral network (CNN) based 48 guitar chords classification system by applying the concept of transfer learning to a source system of CNN based 24 guitar chords classification system. We show that the system with transfer learning has performance similar to that of conventional system, but it requires only half the learning time.

• Smart Structures and Systems
• /
• v.33 no.5
• /
• pp.325-332
• /
• 2024

This study proposes a novel long short-term memory (LSTM)-based approach for predicting carbonation depth, with the aim of enhancing the durability evaluation of concrete structures. Conventional carbonation depth prediction relies on statistical methodologies using carbonation influencing factors and in-situ carbonation depth data. However, applying in-situ data for predictive modeling faces challenges due to the lack of time-series data. To address this limitation, an LSTM-based carbonation depth prediction technique is proposed. First, training data are generated through random sampling from the distribution of carbonation velocity coefficients, which are calculated from in-situ carbonation depth data. Subsequently, a Bayesian theorem is applied to tailor the training data for each target bridge, which are depending on surrounding environmental conditions. Ultimately, the LSTM model predicts the time-dependent carbonation depth data for the target bridge. To examine the feasibility of this technique, a carbonation depth dataset from 3,960 in-situ bridges was used for training, and untrained time-series data from the Miho River bridge in the Republic of Korea were used for experimental validation. The results of the experimental validation demonstrate a significant reduction in prediction error from 8.19% to 1.75% compared with the conventional statistical method. Furthermore, the LSTM prediction result can be enhanced by sequentially updating the LSTM model using actual time-series measurement data.

• International Journal of Contents
• /
• v.8 no.2
• /
• pp.7-12
• /
• 2012

Imbalanced data sets are difficult to be classified since most classifiers are developed based on the assumption that class distributions are well-balanced. In order to improve the error back-propagation algorithm for the classification of imbalanced data sets, a new error function is proposed. The error function controls weight-updating with regards to the classes in which the training samples are. This has the effect that samples in the minority class have a greater chance to be classified but samples in the majority class have a less chance to be classified. The proposed method is compared with the two-phase, threshold-moving, and target node methods through simulations in a mammography data set and the proposed method attains the best results.

• Proceedings of the IEEK Conference
• /
• 1998.10a
• /
• pp.955-958
• /
• 1998

This paper describes the algorithm which extracts moving vehicles from sequential images and tracks those vehicles using Kalman filter. This work is composed of a motion segmentation stage which extracts moving objects from sequential images and gets features of objects, and a motion estimation stage which estimates the position and the motion of moving objects using Kalman filter. In the motion estimation stage, applying to affine motion model we divided the Kalman filter into position filter and velocity filter to employ linear Kalman filter. Multi-target tracking requires a data association component that decides which measurement to use for updating the state of which object. We use pattern recognition method to solve this problem.

• Journal of Mechanical Science and Technology
• /
• v.20 no.12
• /
• pp.2189-2196
• /
• 2006

The present work is concerned with the development of a procedure for adaptive computations of shear localization problems. The maximum jump of equivalent strain rates across element boundaries is proposed as a simple error indicator based on interpolation errors, and successfully implemented in the adaptive mesh refinement scheme. The time step is controlled by using a parameter related to the Lipschitz constant, and state variables in target elements for refinements are transferred by $L_2$-projection. Consistent tangent moduli with a proper updating scheme for state variables are used to improve the numerical stability in the formation of shear bands. It is observed that the present adaptive mesh refinement procedure shows an excellent performance in the simulation of shear localization problems.