• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.1
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• pp.199-204
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• 2017

Recently, the reagent in the laboratory can not only confirm the internal environment through the sensor but also check the status inside the reagent cabinet in real time. Also, if an abnormality occurs in the inside of the reagent cabinet, a serious accident may occur. To solve these problems, this paper proposes a reagent monitoring system that integrates reagent and ICT. The sensor data measured in real time is displayed to the user in real time through the monitor and stored in the database. In addition, by using the stored data, it is possible to inform the registered administrator in real time of the dangerous situation by informing the dangerous situation in case of danger, and to be able to check and control remotely. This can improve safety by making control and confirmation of the state of the inside of the reagent everywhere.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.4
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• pp.85-94
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• 2004

Object tracking in a real time image is one of interesting subjects in computer vision and many Practical application fields during the past couple of years. But sometimes existing systems cannot find all objects by recognizing background noise as object. This paper proposes a method of object detection and tracking using adaptive background image in real time. To detect object which is not influenced by illumination and to remove noise in background image, this system generates adaptive background image by real time background image updating. This system detects object using the difference between background image and input image from camera. After setting up Minimum Bounding Rectangle(MBR) using the internal point of detected object, the system tracks object through this MBR In addition, this paper evaluates the test result about performance of proposed method as compared with existing tracking algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.3989-4006
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• 2020

The intelligent agriculture monitoring is based on the perception and analysis of environmental data, which enables the monitoring of the production environment and the control of environmental regulation equipment. As the scale of the application continues to expand, a large amount of data will be generated from the perception layer and uploaded to the cloud service, which will bring challenges of insufficient bandwidth and processing capacity. A fog-based offline and real-time hybrid data analysis architecture was proposed in this paper, which combines offline and real-time analysis to enable real-time data processing on resource-constrained IoT devices. Furthermore, we propose a data process-ing algorithm based on the incremental principal component analysis, which can achieve data dimensionality reduction and update of principal components. We also introduce the concept of Squared Prediction Error (SPE) value and realize the abnormal detection of data through the combination of SPE value and data fusion algorithm. To ensure the accuracy and effectiveness of the algorithm, we design a regular-SPE hybrid model update strategy, which enables the principal component to be updated on demand when data anomalies are found. In addition, this strategy can significantly reduce resource consumption growth due to the data analysis architectures. Practical datasets-based simulations have confirmed that the proposed algorithm can perform data fusion and exception processing in real-time on resource-constrained devices; Our model update strategy can reduce the overall system resource consumption while ensuring the accuracy of the algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.12
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• pp.117-124
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• 2019

Vibrio cholerae is a very important pathogenic bacterium that has to be monitored in seafood and ships' ballast water. Various methods have been developed to identify this bacterium, yet these methods are time-consuming and have limitations for their sensitivity to detect contamination. The purpose of the present study was to develop a robust and reliable method for identifying V. cholerae. Peptide nucleic acid (PNA) probes were developed to use for PNA-based asymmetrical real-time PCR techniques. The toxigenic Cholera enterotoxin subunit B (ctxB) gene was selected as a target for detecting V. cholerae and the gene was synthesized as a positive template for conventional and real-time PCR. Real-time PCR primers and PNA probes were designed and standard curves were produced for the quantitative analysis. The selected PNA probes reacted specifically to V. cholerae without any ambiguity, even among closely related species, and the detection limit was 0.1 cfu/100 mL. Taken together, the PNA probes and asymmetrical qPCR methods developed in this present study could contribute to the rapid, accurate monitoring of V. cholerae in marine environments, and as well as in seafood and ships' ballast waters.

• Journal of Internet Computing and Services
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• v.6 no.6
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• pp.85-97
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• 2005

In this paper, we construct the traffic information database by using the acquired data from the traffic information devices installed in road network, and, by referring to this database, propose the intersection simulation system which can dynamically manage the real-time traffic flow for each section of road from the intersections, This system consists of hierarchical 3 parts, The lower layer is the physical layer where the traffic information is acquired on an actual road. The traffic flow control framework exists in the middle layer. The framework supports the grouping of intersection, the collection of real-time traffic flow information, and the remote monitoring and control by using the traffic information of the lower layer, This layer is designed by extending the distributed object group framework we developed. In upper layer, the intersection simulator applications controlling the traffic flow by grouping the intersections exist. The components of the intersection application in our system are composed of the implementing objects based on the Time-triggered Message-triggered Object(TMO) scheme, The intersection simulation system considers the each intersection on road as an application group, and can apply the control models of dynamic traffic flow by the road's status. At this time, we use the real-time traffic information collected through inter-communication among intersections. For constructing this system, we defined the system architecture and the interaction of components on the traffic flow control framework which supports the TMO scheme and the TMO Support Middleware(TMOSM), and designed the application simulator and the user interface to the monitoring and the controlling of traffic flow.

• Annual Conference of KIPS
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• 2021.11a
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• pp.700-703
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• 2021

Infrared cameras are widely used in recent research for automatic monitoring the abnormal behaviors of the pig. However, when deployed in real pig farms, infrared cameras always get polluted due to the harsh environment of pig farms which negatively affects the performance of pig monitoring. In this paper, we propose a real-time noise-robust infrared camera-based pig automatic monitoring system to improve the robustness of pigs' automatic monitoring in real pig farms. The proposed system first uses a preprocessor with a U-Net architecture that was trained as a GAN generator to transform the noisy images into clean images, then uses a YOLOv5-based detector to detect pigs. The experimental results show that with adding the preprocessing step, the average pig detection precision improved greatly from 0.639 to 0.759.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.59 no.1
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• pp.71-76
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• 2010

This paper is focused on implementing a real-time data acquisition system that checks power facility status by applying network based technology to Urban Transit substation power facilities and the results of its on-field tests. This system is composed of a sensor part, a measurement part, a transceiver part, a host computer, and a power source part. The system is designed to collect, save, analyze, and display the online state power facility AI (Analog Input). This system measures voltage and current from positive feeders and negative feeders where it is possible to check abnormalities of the substation‘s main power facilities. By monitoring abnormal data of the Urban Transit power facilities real-time and analyzing stored data, establishing procedures of optimized maintenance is possible.

• Proceedings of the KIEE Conference
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• 2006.07a
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• pp.141-142
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• 2006

In this paper, DSPOCS(Digital Switchgear Panel Operation and Control Solution) is designed, which is the intelligent inference operation and control solution of substation based on IED. DSPOCS is designed as a scheduled monitoring and control task and a real-time alarm inference task, and is interlinked with BRES in the required case. The intelligent alarm inference task consists of the alarm knowledge generation part and the real-time pattern matching part The alarm knowledge generation part generates automatically alarm knowledge from DB and saves it in alarm KB. On the other hand, the pattern matching part inferences the real-time event by comparing the real-time event information furnished from IEDs of substation with the patterns of the saved alarm knowledge base.

• Journal of Electrical Engineering and Technology
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• v.1 no.1
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• pp.23-27
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• 2006

In this paper a Hybrid Real Time HVDC Simulator fur both operator Training and Researching in the Cheju-Haenam HVDC System is proposed and its performance is studied by means of RTDS (Real Time Digital Simulator), EMTDC (Electro-Magnetic Transients system for DC), PSS/E (Power System Simulator for Engineering), and experienced scenarios. The objective of this paper is to represent the strategy in development for KEPCO's hybrid HVDC simulator for the Cheju-Haenam HVDC system. This simulator consists of two DC stations, DC cables, external digital/analog controllers, monitoring systems and control desk for education, and AC networks. Its suitability for operator's education is tested during startup/shutdown and normal state operations. Dynamic performances of it are also verified.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.415-419
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• 1997

The left ventricular relaxation rate is used as a golden standard which describes the left ventricular diastolic unction. So far, to get the rate of relaxation one should calculate the data after full recording, that is, off-line method. Therefore one cannot get the rate of relaxation in real-time while changing loading condition or infusing drug. But real time monitoring of the relaxation rate is necessary while changing loading condition or infusing drug to control the mechanics of heart and to get more information. We propose a new criterion to get the left ventricular relaxation rate and a real time algorithm. By comparison, it was turned out that our criterion outperforms others criterion.