• Smart Structures and Systems
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• v.33 no.4
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• pp.263-279
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• 2024

With the increasing diversity of internet media, available video data have become more convenient and abundant. Related video data-based research has advanced rapidly in recent years owing to advantages such as noncontact, low-cost data acquisition, high spatial resolution, and simultaneity. Additionally, structural nonlinearity extraction has attracted increasing attention as a tool for damage evaluation. This review paper aims to summarize the research experience with the recent developments and applications of video data-based technology for structural nonlinearity extraction and damage evaluation. The most regularly used object detection images and video databases are first summarized, followed by suggestions for obtaining video data on structural nonlinear damage events. Technologies for linear and nonlinear system identification based on video data are then discussed. In addition, common nonlinear damage types in disaster events and prevalent processing algorithms are reviewed in the section on structural damage evaluation using video data uploaded on online platform. Finally, a discussion regarding some potential research directions is proposed to address the weaknesses of the current nonlinear extraction technology based on video data, such as the use of uni-dimensional time-series data as leverage to further achieve nonlinear extraction and the difficulty of real-time detection, including the fields of nonlinear extraction for spatial data, real-time detection, and visualization.

• Journal of the Ergonomics Society of Korea
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• v.20 no.1
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• pp.31-43
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• 2001

The present study the feasibility of the new subjective assessment devise; Real-Time Subjective Assessment Digitizer (RTSAD). The subjects were instructed to evaluate their sensibility during the presentation of the positive and the negative visual stimuli using RTSAD. After the presentation of each of the stimulus, a questionnaire was used for comparing the results with those from RTSAD. It was argued that the biggest utility of the RTSAD is the capability of measuring and figuring out the trends of the subjective assessment in real time. The results from the questionnaires unlike the results from RTSAD, reflects only the averaged human sensibility for the entire time of the presentation of the stimulus.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.03a
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• pp.1139-1146
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• 2009

Collapse of cut slope includes many uncertainties in view of the reason and time. So, in the past, risky cut slopes have been dealt after they've been collapsed through post-management measures. But recently, advanced disaster prevention system is required, and as a part of that RTMS(Real-Time Monitoring System) was developed. In this study, stability of risky cut slope was evaluated by site investigation. To grasp deformation behavior characteristics of slope, numerical analysis based on FEM was performed and using results of that, specific standards for installation of Real-Time Monitoring System were suggested.

• Journal of Computing Science and Engineering
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• v.6 no.1
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• pp.26-38
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• 2012

Java has been increasingly used in programming for real-time systems. However, some of Java's features such as automatic memory management and dynamic compilation are harmful to time predictability. If these problems are not solved properly then it can fundamentally limit the usage of Java for real-time systems, especially for hard real-time systems that require very high time predictability. In this paper, we propose to exploit multicore computing in order to reduce the timing unpredictability that is caused by dynamic compilation and adaptive optimization. Our goal is to retain high performance comparable to that of traditional dynamic compilation, while at the same time, obtain better time predictability for Java virtual machine (JVM). We have studied pre-compilation techniques to utilize another core more efficiently, preoptimization on another core (PoAC) scheme to replace the adaptive optimization system (AOS) in Jikes JVM and the counter based optimization (CBO). Our evaluation reveals that the proposed approaches are able to attain high performance while greatly reducing the variation of the execution time for Java applications.

• Korean Journal of Food Science and Technology
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• v.42 no.3
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• pp.355-360
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• 2010

Vibrio parahaemolyticus (V. parahaemolyticus), which is commonly found in raw seafood, causes gastroenteritis in humans. Rapid and effective methods have been developed as culture methods require up to 5-7 days. In this study, real-time PCR was compared with the standard culture method for detecting V. parahaemolyticus in seafood and radish sprout samples. Five hundred grams of the samples were artificially contaminated with V. parahaemolyticus then divided into 20 samples. The samples were incubated in alkaline peptone water and then streaked onto thiosulfate-citrate-bile saltssucrose agar. Biochemical tests for suspicious colonies were performed using the API 20NE strip. In parallel, real-time PCR was performed targeting the toxR gene using the enrichment broth. The real-time PCR was sensitive in discriminating V. parahaemolyticus from other foodborne pathogens. The detection limit of the real-time PCR was $10^3\;CFU/mL$ in phosphate-buffered saline. Although the real-time PCR detected more positive samples (76 out of 180, 42%) than the culture method (66 out of 180, 37%), there was no significant statistical difference (p>0.05) between the two methods. In conclusion, real-time PCR assays could be an alternative to the standard culture method for detecting V. parahaemolyticus in seafood and radish sprouts, which has many advantages in terms of detection time, labor, and sensitivity.

• Journal of Food Hygiene and Safety
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• v.29 no.4
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• pp.340-346
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• 2014

In this study, the detection method was developed using real-time PCR to distinguish 4 species (bovine, porcine, horse, and chicken) of raw meats. The genes for distinction of species about meats targeted at 12S rRNA and 16S rRNA parts in mitochondrial DNA. Probes were designed to have a 5' FAM and a TAMRA at the 3' end. This study is to develop 4 species-specific primer and probes about raw materials and real-time PCR on 10 strains to observe the products of non-specific signal for similar species. As a result, any non-specific signal were not detected among each other. Real-time PCR method was developed for quantitation and identification of intentional and unintentional mixture in ground mixed meat (The difference of $C_T$ value between intentional mixture and 100% meat: $${\leq_-}$$ cycles, The difference of $C_T$ value between unintentional mixture and 100% meat: $${\geq_-}$$ cycles). The detection and differentiation of intentional and unintentional mixture in this study would be applied to food safety management for eradication of adulterated food distribution and protection of consumer's right.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.1
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• pp.55-63
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• 2019

This paper develops an algorithm to determine the batch size of the batch process in real time for improving production and efficient control of production system with multiple processes and batch processes. It is so important to find the batch size of the batch process, because the variability arising from the batch process in the production system affects the capacity of the production. Specifically, batch size could change system efficiency such as throughput, WIP (Work In Process) in production system, batch formation time and so on. In order to improve the system variability and productivity, real time batch size determined by considering the preparation time and batch formation time according to the number of operation of the batch process. The purpose of the study is to control the WIP by applying CONWIP production system method in the production line and implements an algorithm for a real time batch size decision in a batch process that requires long work preparation time and affects system efficiency. In order to verify the efficiency of the developed algorithm that determine the batch size in a real time, an existed production system with fixed the batch size will be implemented first and determines that batch size in real time considering WIP in queue and average lead time in the current system. To comparing the efficiency of a system with a fixed batch size and a system that determines a batch size in real time, the results are analyzed using three evaluation indexes of lead time, throughput, and average WIP of the queue.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.4
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• pp.472-476
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• 2010

Nowadays, as the indices of the major search engines grow to a tremendous proportion, vertical search services can help customers to find what they need. Real time search is valuable because it lets you know what's happening right now on any given topic. In this paper, we designed a new architecture to implement a high performance real time search system. Based on the real time search's characters, we divided the whole system to two parts which are collection system and search system. The evaluation results showed that our design has the potential to provide the real time search transparent scalability while maintaining the replication overhead costs in check.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.2
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• pp.113-119
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• 2000

In this paper, we design and implement a query processor of real-time main memory database systems, which reflect the characteristics of main memory database systems and satisfy timing constraints. The proposed query processor manages real-time data that has timing constraint by exploiting meta database. It supports CLI in order to make application programs. It also supports extended CLI and stored CLI. The former can be expressed the Information on real-time transaction. The latter is designed to support frequently processed transaction. The proposed query processor is implemented as query processor of real-time database management systems. We Present performance evaluation results that illustrate ratio of transaction, which satisfy deadline are increased by the query processing ability of system and the efficient management of real-time data.

• Korean Journal of Artificial Intelligence
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• v.11 no.4
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• pp.21-27
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• 2023

This paper discusses a deep learning-based road surface analysis system that collects data by installing vibration sensors on the 4-axis wheel bearings of a vehicle, analyzes the data, and appropriately classifies the characteristics of the current driving road surface for use in the vehicle's control system. The data used for road surface analysis is real-time large-capacity data, with 48K samples per second, and the A2B protocol, which is used for large-capacity real-time data communication in modern vehicles, was used to collect the data. CAN and CAN-FD commonly used in vehicle communication, are unable to perform real-time road surface analysis due to bandwidth limitations. By using A2B communication, data was collected at a maximum bandwidth for real-time analysis, requiring a minimum of 24K samples/sec for evaluation. Based on the data collected for real-time analysis, performance was assessed using deep learning models such as LSTM, GRU, and RNN. The results showed similar road surface classification performance across all models. It was also observed that the quality of data used during the training process had an impact on the performance of each model.