• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.499-500
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• 2007

The existing digital protection relay is continuously growing with an improvement in technology. In this paper, we propose the development of the digital protection relay which displays the trip area in real time. In most of the digital protection relays monitor whether analog signal enters into the pre-determined trip area, but those aren't provide the trip area information for a operator in real time. Therefore, if the digital protection relay continuously displays the trip area in real time, the operator analysis power system status easily. This paper particularly introduces selective ground protective relay and differential protective relay with trip area and presents a method of providing the trip area information to operator in real time.

• Journal of Korea Multimedia Society
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• v.24 no.12
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• pp.1682-1692
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• 2021

Digital Twin, one of the core technologies of the Fourth Industrial Revolution, is attracting attention as a very suitable technology for disaster monitoring such as fires and earthquakes. In this paper, we implement a system equipped with UWB RTLS(Ultra-Wideband Real Time Location System), real-time remote control, and video streaming, which are element technologies for disaster monitoring digital twin. Since the proposed system structure is based on a cloud server, the actual location of the UWB indoor positioning-based client is transmitted to the user device in real time and stored on the cloud server for statistical and data analysis. In addition, we demonstrate through experiments that outliers occurs when the value of RSSI(Received Signal Strength Indicator) decreases due to communication collisions between UWB Tags, and propose an RSSI outlier correction algorithm to solve this problem.

• Journal of Advanced Information Technology and Convergence
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• v.10 no.2
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• pp.177-197
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• 2020

Colleges have been forced to take non-face-to-face classes this year due to the COVID-19, and the situation is expected to continue unless the development of treatments and vaccines is carried out as soon as possible. In the situation where non-face-to-face classes are required under compulsion, two methodologies have been suggested as most representative alternatives to face-to-face classes: online real-time classes and on-demand contents classes. The purpose of this study is to compare the perceived convenience, self-fidelity, and preference of students between online real-time and on-demand contents classes by gender, school year grade, mostly using class media, and number of courses taken. Comparative results between online real-time and on-demand contents classes were statistically analyzed by surveying students at a university.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.1
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• pp.80-88
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• 2001

The existed approaches to analyzing real-time schedulability take place exponential time and space complexity of this methods, since these uses a fixed priority scheduling and/or traverse all possible state spaces. This paper judges whether it is satisfied a given deadlines for real-time processes regarding a minimum execution time of process, periodic, deadline and a synchronizion time of processes by using the transaction rules of process algebra, and proposes a retrieval algorithm for unschedulable processes based on GUI environment. And we implement and evaluate the scheduling state analyzer that displays visually the result of schedulabiliy analysis for real-time processes.

• Journal of Life Science
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• v.20 no.8
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• pp.1201-1206
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• 2010

We performed a comparative analysis using a Real-time PCR (Polymerase Chain Reaction) and LC/MS (Liquid-Chromatograph/Mass Spectrometer) method in order to detect microcystin in environmental sources. Among the three different primer sets tested for microcystin using three positive strains of Microcystis aeruginosa by Real-time PCR assay, only TOX2P/TOX2M primer pairs were able to detect Microcystis aeruginosa. According to the results of a survey carried out from June 2009 to September 2009, 11 out of 11 (100%) raw water samples were were found to have microcystin when the Real-Time PCR and LC/MS method was used, with total microcystin concentration ranging from 5.98~219.0 ${\mu}g/l$. A microcystin removal treatment process was used to ensure entire removal, by passing it through a BAC filtration step. It was concluded that real-time PCR assay can be used to estimate micrucystin detection more rapidly and easily than the LC/MS method.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.3_4
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• pp.170-186
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• 2004

Recently, for real-time applications such as multimedia and signal processing, it becomes increasingly important to provide a probabilistic guarantee that each task in the application meets its deadline with a given probability. To provide the probabilistic guarantee, an analysis method is needed that can accurately predict the deadline miss probability for each task in a given system. This paper proposes a stochastic analysis method for real-time systems that use priority-driven scheduling, such as Rate Monotonic and Earliest Deadline First, in order to accurately compute the deadline miss probability of each task in the system. The proposed method accurately computes the response time distributions for tasks with arbitrary execution time distributions, and thus makes it possible to determine the deadline miss probability of individual tasks. In the paper. through experiments, we show that the proposed method is highly accurate and outperforms exisiting methods proposed in the literature.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.6
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• pp.569-578
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• 2016

With the recent advancement of surveying and technology, the spatial data acquisition rates and precision have been improved continually. As the updates of spatial data are rapid, and the size of data increases in line with the advancing technology, the LOD (Level of Detail) algorithm has been adopted to process data expressions in real time in a streaming format with spatial data divided precisely into separate steps. The existing GRID analysis utilizes the single DEM, as it is, in examining and analyzing all data outside the analysis area as well, which results in extending the analysis time in proportion to the quantity of data. Hence, this study suggests a method to reduce analysis time and data throughput by acquiring and analyzing DEM data necessary for GRID analysis in real time based on the area of analysis and the level of precision, specifically for streaming DEM data, which is utilized mostly for 3D geographic information service.

• The KIPS Transactions:PartA
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• v.12A no.1 s.91
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• pp.53-58
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• 2005

The use of computers for control and monitoring of industrial process has expanded greatly in recent years. The computer used in such applications is shared between a certain number of time-critical control and monitor function and non time-critical batch processing job stream. Embedded systems encompass a variety of hardware and software components which perform specific function in host computer. Many embedded system must respond to external events under certain timing constraints. Failure to respond to certain events on time may either seriously degrade system performance or even result in a catastrophe. In the design of real-time embedded system, decisions made at the architectural design phase greatly affect the final implementation and performance of the system. Flexibility indicates how well a particular system architecture can tolerate with respect to satisfying real-time requirements. The degree of flexibility of real-time system architecture indicates the capability of the system to tolerate perturbations in timing related specifications. Given degree of flexibility, one may compare and rank different implementations. A system with a higher degree of flexibility is more desirable. Flexibility is also an important factor in the trade-off studies between cost and performance. In this paper, it is identified the need for flexibility function and shows that the existing real-time analysis result can be effective. This paper motivated the need for a flexibility for the efficient analysis of potential design candidates in the architectural design exploration or real time embedded system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.1
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• pp.209-221
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• 1999

Several approaches to anlayzing real-time schedulability have been presented, but since these used a fixed priority scheduling scheme and/or traverse all possible state spaces, there take place exponential time and space complexity of these methods. Therefore it is necessary to reduce the state space and detect schedulability at earlier time. This paper proposes and implements an advanced schedulability analysis algorithm to determine that is satisfied a given deadlines for real-time processes. These use a minimum execution time of process, periodic, deadline, and a synchronization time of processes to detect schedulability at earlier time and dynamic scheduling scheme to reduce state space using the transition rules of process algebra. From a result of implementation, we demonstrated the effective performance to determine schedulability analysis.

• Korea Real Estate Review
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• v.27 no.3
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• pp.71-86
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• 2017

The purpose of this study was to apply the deep running method to real estate price index predicting and to compare it with the time series analysis method to test the possibility of its application to real estate market forecasting. Various real estate price indices were predicted using the DNN (deep neural networks) and LSTM (long short term memory networks) models, both of which draw on the deep learning method, and the ARIMA (autoregressive integrated moving average) model, which is based on the time seies analysis method. The results of the study showed the following. First, the predictive power of the deep learning method is superior to that of the time series analysis method. Second, among the deep learning models, the predictability of the DNN model is slightly superior to that of the LSTM model. Third, the deep learning method and the ARIMA model are the least reliable tools for predicting the housing sales prices index among the real estate price indices. Drawing on the deep learning method, it is hoped that this study will help enhance the accuracy in predicting the real estate market dynamics.