• Journal of Korea Multimedia Society
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• v.15 no.1
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• pp.87-92
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• 2012

Wireless sensor network is a technology that collects the information about object in real-time. Sensor data has a characteristic that is generated an unprecedented volume data in short time. Analysis is essential to define the relationship between the data, including more of the data from a large volume data stream which is acquired from the sensor. In order to effectively handle the sensor data stream, in this paper, using ECA rules to organize data in a meaningful and more practical real-time monitoring systems is proposed.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.473-473
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• 2010

Plasma is widely used in various commercial etchers and chemical vapor deposition. Unfortunately, real-time plasma process monitoring is still difficult. Some methods of plasma diagnosis is improved, however, it is possible for real-time plasma diagnosis to use non-intrusive probe only. In this research, the object is to investigate the suitability of using impedance analysis and optical emission spectroscopy (OES) for real-time plasma process monitoring. It is assumed that plasma system is a equivalent circuit. Therefore, V-I probe is used for measuring impedance, which can be a new non-intrusive probe for plasma diagnosis. From impedance data, we tried to analyse physical properties of plasma. And OES, the other method of plasma diagnosis, is a typical non-intrusive probe for analyzing chemical properties. The amount of the OES data is typically large, so this poses a difficulty in extracting relevant information. To solve this problem, principal component analysis (PCA) can be used. For fundamental information, Ar plasma and $O_2$ plasma are used in this experiment. This method can be applied to real-time endpoint and fault detections.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.104-108
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• 2023

This paper deals with research on innovative systems using Python-based artificial intelligence technology in the field of plant growth monitoring. The importance of monitoring and analyzing the health status and growth environment of plants in real time contributes to improving the efficiency and quality of crop production. This paper proposes a method of processing and analyzing plant image data using computer vision and deep learning technologies. The system was implemented using Python language and the main deep learning framework, TensorFlow, PyTorch. A camera system that monitors plants in real time acquires image data and provides it as input to a deep neural network model. This model was used to determine the growth state of plants, the presence of pests, and nutritional status. The proposed system provides users with information on plant state changes in real time by providing monitoring results in the form of visual or notification. In addition, it is also used to predict future growth conditions or anomalies by building data analysis and prediction models based on the collected data. This paper is about the design and implementation of Python-based plant growth monitoring systems, data processing and analysis methods, and is expected to contribute to important research areas for improving plant production efficiency and reducing resource consumption.

• Journal of Electrical Engineering and Technology
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• v.5 no.1
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• pp.16-20
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• 2010

Recently, the smart grid has become a hot issue and interest in related power sources have increased accordingly. The implementation of a smart grid can enable many generation resources to be linked to the power system, including small-scale reactors for the purpose of co-generation. Research on small-scale reactors is being carried out all over the world. Similarly, Korea is also conducting research on multi-purpose regional energy systems using nuclear energy. This paper proposes a real-time data acquisition and analysis system for small-scale reactors, and is known as the REX-10 (Regional Energy rX 10 MVA). This analysis requires real-time simulations for the power system since it needs data communication with a remote REX-10. A RTDS (Real Time Digital Simulator) has been used for the simulation, and a SCADA/HMI system interfaced with the RTDS is proposed for the purpose of monitoring and control of the regional energy system.

• Fourth Industrial Review
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• v.3 no.1
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• pp.13-20
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• 2023

Purpose - By designing a PEF(Personalized Education Feedback) system for real-time prediction of learning achievement and motivation through real-time EEG analysis of learners, this system provides some modules of a personalized adaptive learning system. By applying these modules to e-learning and offline learning, they motivate learners and improve the quality of learning progress and effective learning outcomes can be achieved for immersive self-directed learning Research design, data, and methodology - EEG data were collected simultaneously as the English test was given to the experimenters, and the correlation between the correct answer result and the EEG data was learned with a machine learning algorithm and the predictive model was evaluated.. Result - In model performance evaluation, both artificial neural networks(ANNs) and support vector machines(SVMs) showed high accuracy of more than 91%. Conclusion - This research provides some modules of personalized adaptive learning systems that can more efficiently complete by designing a PEF system for real-time learning achievement prediction and learning motivation through an adaptive learning system based on real-time EEG analysis of learners. The implication of this initial research is to verify hypothetical situations for the development of an adaptive learning system through EEG analysis-based learning achievement prediction.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.547-549
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• 2021

In Artificial Intelligence analysis, the process of creating a model and verifying it is a task that requires computational processing time because it is Batch Processing performed with already generated data. We need to model, validate, and predict real-time data, such as stocks and defense information, with data generated directly in front of us. As a solution to this, we solve it by applying techniques to segment the data required for artificial intelligence modeling tasks in order of time processing and distribute the data across multiple processes.

• Spatial Information Research
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• v.11 no.1
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• pp.41-60
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• 2003

It is noted that the paper mapping system for University Building Facility has many limitations in terms of data maintenance, real-time GIS data acquisition, and economic efficiency. The aim of this research was to evaluate an operational potential of an on site real-time mobile GIS technique to resolve the problem faced in the university. The idea is based upon the recent trends in the field of 'Telecommunication and Information Technology' that uses a PDA (personal Digital Assistants), wireless network computing, mobile computing, etc. A real time mobile GIS approach has been adopted, in which a PDA is linked to a wireless internet and field workers record data on the computer at the site and analyse data on site. While there should be a considerable number and variety of factors associated with real-time mobile GIS quality, this research focuses on three criteria that are identified as fundamental to customer requirements; (1) data quarry (2) spatial analysis (3) real-time GIS database building. 'Art--empirical study for a case study facility has been conducted to confirm the validity for the system. The system has been checked experimentally, enabled the field users to quarry the data required simply and execute spatial analysis (buffer, overlay etc.,) accommodating versatile alternatives on the site. Detailed visual maps can be generated over large areas quickly and easily. The PDA interface, in particular, were ideally suited for field users to interactively displaying positional information with attribute data. This system has shown to be quite convenient to maintaining a highly reliable database since it could playa crucial role in documenting at real-time basis temporal and spatial changes occurred in the facilities. It is anticipated that this research output will greatly serve to introduce the reliable and cost-effective facility mapping system in the university by overcoming serious constraints suffered from the past non-real time mobile GIS approach.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.11
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• pp.2080-2085
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• 2008

KEPCO's AMR (Automatic Meter Reading) is a system that performs the real-time inspection and management of the 15-minute load profile of electric power consumption through a wired and/or wireless network such as CDMA. It has been utilized widely for real-time collection and data analysis. So far, KEPCO has focused on establishing wireless networks using CDMA and collecting data in real time but failed to consider sufficiently performances that can improve the quality of the original data required in terms of data utilization as well as establish the summary information. In this paper, we are going to show the functions that improve data quality by recording the final renewal time of any erroneous data and maintaining such data lists to use them in the rebuilding of summary information. The goals are to reduce any load applied mainly on the DBMS (Database Management System) of AMR, to enable the real-time performance of establishment in the summary information, and to obtain high-quality inspection data. The performance evaluation result has revealed a 10-fold improvement compared to the traditional disk-based DBMS system when the summary information is established.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.2
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• pp.317-322
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• 2019

This study is based on big big data base for real-time collection/analysis/processing of data, creative analysis of data assets, and intelligent processing system based on IoT, which can measure distribution phase in real time. The mobile terminal uses the SDK of the provided device to measure the data information on the consumption of specific seafood production and distribution. We use the oneM2M protocol to store various kinds of information needed for seafood production, and implement a DB Server and a system that allows the administrator to manage the system using the UI.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.338-341
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• 2005

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).