• Journal of Institute of Control, Robotics and Systems
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• v.5 no.6
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• pp.734-743
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• 1999

In this paper, a real-time communication method using a PICNET-NP(Plant instrumentation and Control Network for Nuclear Power plant) is proposed with an analysis of the control network requirements of DCS(Distributed Control System) in nuclear power plants. The method satisfies deadline in case of worst data traffics by considering aperiodic and periodic real-time data and others. In addition, the method was used to analyze the data characteristics of the DCS in existing nuclear power plant. The result shows that use of this method meets the response time requirement(100ms).

• ETRI Journal
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• v.43 no.1
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• pp.82-94
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• 2021

In this work, six voiced/unvoiced speech classifiers based on the autocorrelation function (ACF), average magnitude difference function (AMDF), cepstrum, weighted ACF (WACF), zero crossing rate and energy of the signal (ZCR-E), and neural networks (NNs) have been simulated and implemented in real time using the TMS320C6713 DSP starter kit. These speech classifiers have been integrated into a linear-predictive-coding-based speech analysis-synthesis system and their performance has been compared in terms of the percentage of the voiced/unvoiced classification accuracy, speech quality, and computation time. The results of the percentage of the voiced/unvoiced classification accuracy and speech quality show that the NN-based speech classifier performs better than the ACF-, AMDF-, cepstrum-, WACF- and ZCR-E-based speech classifiers for both clean and noisy environments. The computation time results show that the AMDF-based speech classifier is computationally simple, and thus its computation time is less than that of other speech classifiers, while that of the NN-based speech classifier is greater compared with other classifiers.

• Health Policy and Management
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• v.24 no.3
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• pp.254-260
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• 2014

Background: The purpose of this study is to assume appropriate outpatient consultation time for each clinical department on the basis of measured outpatient consultation time and satisfaction of outpatient. Methods: We surveyed the feeling and satisfactory outpatient consultation time, satisfaction, revisiting intention and recommendation to others to 1,105 patients of single general hospital in Gyeonggi-do and measured their real outpatient consultation time from October 28 to November 27 in 2013. On the basis of satisfaction, we estimated appropriate outpatient consultation time through area under the receiver operating characteristic curve in logistic regression model. Results: Feeling outpatient consultation time was 5.1 minutess, satisfactory outpatient consultation time which was suggested by patient was 6.3 minutes, and real outpatient consultation time was 4.2 minutes. Department which had longest real outpatient consultation time was infection (7 minutes) and department which had longest satisfactory outpatient consultation time was neurology (9.4 minutes). From the univariate and the multiple linear regression analysis, real outpatient consultation time was longer in pulmonology patient, new patient and afternoon patient, satisfactory outpatient consultation time was longer in infection, neurology, neuropsychiatry, neurosurgery, and rehabilitation patient. Appropriate real outpatient consultation time was suggested as 5.6 minutes which differentiated high and low satisfied patient group. However, we could not assume appropriate outpatient consultation time for each clinical department because the number of patient who had bad satisfaction was too low. Conclusion: To improve patient's satisfaction, we hope outpatient reservation system is operated as each patient's outpatient consultation time is at least 5.6 minutes.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.7
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• pp.720-725
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• 2008

This paper proposes a system architecture for USN with a service robot to provide more active assisted living services for elderly persons by monitoring their mental and physical well-being with USN environments at home, hospital, or silver town. Sensors embedded in USN are used to detect preventive measures for chronic disease. Logged data are transferred to main controller of a service robot via wireless channel in which the analysis of data is performed. For the purpose of handling emergency situations, it needs real-time processing on gathering variety sensor data, routing algorithms for sensor nodes to a moving sink node and processing of logged data. This paper realized multi-hop sensor network to detect user movements with biometric data transmission and performed algorithms on Xenomai, a real-time embedded Linux. To leverage active sensing, a mobile robot is used of which task was implemented with a priority to process urgent data came from the sink-node. This software architecture is anticipated to integrate sensing, communication and computing with real-time manner. In order to verify the usefulness of a proposed system, the performance of data transferring and processing on a real-time OS with non real-time OS is also evaluated.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.5
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• pp.89-108
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• 2023

This study provides a comprehensive analysis of recent studies conducted on the topic of nowcasting in order to enhance the accuracy and promptness of official statistical data. Furthermore, we propose an alternative approach involving the utilization of real-time data and its corresponding collection methods to effectively operate a real-time nowcasting model capable of accurately capturing the current economic condition. We explore high-frequency real-time data that can predict economic indicators in both the public and private sectors and propose a pipeline for data collection processing and modeling that is based on cloud platforms. Furthermore we validate the essential elements required for the implementation of real-time nowcasting, as well as their data management protocols to ensure the reliability and consistency needed for accurate forecasting of official statistical indicators.

• Journal of Food Hygiene and Safety
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• v.34 no.6
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• pp.557-561
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• 2019

This study investigated the efficacy of DNA extraction methods for real-time PCR detection of foodborne pathogenic bacteria in livestock manure composts. Livestock manure composts were inoculated with Escherichia coli O157:H7, Salmonella Typhimurium, Listeria monocytogenes, Bacillus cereus and incubated in enrichment broth. For DNA extraction, enriched samples were treated following boiling method, by chloroform, C₁₈ powder, and proteinase K. As a result, 4 species of bacteria were detected by real-time PCR when subjected to boiling for 30 min and treated with proteinase K. These results suggest that detection of foodborne pathogens by real-time PCR from livestock manure composts could be applicable using effective DNA extraction methodology such as the boiling method or proteinase K.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.165-166
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• 2017

It is demanding to receive information of data in real time anywhere and analyze it with meaningful data. Research on the platform for such analysis is actively underway. In this paper, we try to find out what are important factors in solving the problems of collecting and analyzing IoT data in real time. How much better than existing data collection methods and analytical methods can be the basis for judging the value of the data. It is important to accurately collect and store data more quickly and quickly from many sensors in real time in real time, and analytical methods that can derive values from the stored data. Therefore, an important requirement of the analysis platform in the IoT environment is to process large amount of data in real time and to centralize and manage it.

• Journal of the Earthquake Engineering Society of Korea
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• v.27 no.2
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• pp.77-82
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• 2023

The structural analysis module is an essential part of any integrated structural system. Diverse integrated systems today require, from the analysis module, efficient real-time responses to real-time input such as earthquake signals, extreme weather-related forces, and man-made accidents. An integrated system may also be for the entire life span of a civil structure conceived during the initial conception, developed throughout various design stages, effectively used in construction, and utilized during usage and maintenance. All these integrated systems' essential part is the structural analysis module, which must be automated and computationally efficient so that responses may be almost immediate. The finite element method is often used for structural analysis, and for automation, many effective finite element meshes must be automatically generated for a given analysis. A computationally efficient finite element mesh generation scheme based on the r-h method of mesh refinement using strain deviations from the values at the Gauss points as error estimates from the previous mesh is described. Shape factors are used to sort out overly distorted elements. A standard cantilever beam analyzed by four-node plane stress elements is used as an example to show the effectiveness of the automated algorithm for a time-domain dynamic analysis. Although recent developments in computer hardware and software have made many new applications in integrated structural systems possible, structural analysis still needs to be executed efficiently in real-time. The algorithm applies to diverse integrated systems, including nonlinear analyses and general dynamic problems in earthquake engineering.

• The Journal of Society for e-Business Studies
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• v.18 no.3
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• pp.159-175
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• 2013

Recently, as real-time availability of e-commerce data becomes possible, the requirement of real-time analysis of e-commerce increases significantly. In the real-time analysis of e-commerce data, it is very important to efficiently process continuous join queries between an e-commerce data stream and disk-based large relations. In this paper, we propose an efficient method for processing a continuous join query between an e-commerce data stream and multiple disk-based relations. The proposed method improves the service rate significantly, while reducing the amount of required memory substantially. Through analysis and various experiments, we show the efficiency of the proposed method compared with the previous one in terms of service rate and memory usage.

• Journal of Mechanical Science and Technology
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• v.19 no.6
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• pp.1243-1252
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• 2005

This paper describes a new digital signal processor (DSP) imbalance measurement system dedicated to real-time vibration analysis on rotating machine. To accomplish real-time analysis, the vibration signals are on-line acquired and processed to analyze the mass imbalance and phase position. This is achieved through the use of FFT and Lissajous diagram. The method followed to analyze the mass imbalance with the chosen hardware and software solutions are described in detail in this paper. Several experimental tests demonstrate the efficiency and accuracy in imbalance analysis performance of the DSP system.