• 제목/요약/키워드: Real-time analysis system

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Plasma Impedance Monitoring with Real-time Cluster Analysis for RF Plasma Etching Endpoint Detection of Dielectric Layers

  • Jang, Hae-Gyu;Chae, Hui-Yeop
    • Proceedings of the Korean Vacuum Society Conference
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    • 2013.08a
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    • pp.123.2-123.2
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    • 2013
  • Etching endpoint detection with plasma impedance monitoring (PIM) is demonstrated for small area dielectric layers inductive coupled plasma etching. The endpoint is determined by the impedance harmonic signals variation from the I-V monitoring system. Measuring plasma impedance has been examined as a relatively simple method of detecting variations in plasma and surface conditions without contamination at low cost. Cluster analysis algorithm is modified and applied to real-time endpoint detection for sensitivity enhancement in this work. For verification, the detected endpoint by PIM and real-time cluster analysis is compared with widely used optical emission spectroscopy (OES) signals. The proposed technique shows clear improvement of sensitivity with significant noise reduction when it is compared with OES signals. This technique is expected to be applied to various plasma monitoring applications including fault detections as well as end point detection.

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Review of Internet of Things-Based Artificial Intelligence Analysis Method through Real-Time Indoor Air Quality and Health Effect Monitoring: Focusing on Indoor Air Pollution That Are Harmful to the Respiratory Organ

  • Eunmi Mun;Jaehyuk Cho
    • Tuberculosis and Respiratory Diseases
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    • v.86 no.1
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    • pp.23-32
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    • 2023
  • Everyone is aware that air and environmental pollutants are harmful to health. Among them, indoor air quality directly affects physical health, such as respiratory rather than outdoor air. However, studies that have examined the correlation between environmental and health information have been conducted with public data targeting large cohorts, and studies with real-time data analysis are insufficient. Therefore, this research explores the research with an indoor air quality monitoring (AQM) system based on developing environmental detection sensors and the internet of things to collect, monitor, and analyze environmental and health data from various data sources in real-time. It explores the usage of wearable devices for health monitoring systems. In addition, the availability of big data and artificial intelligence analysis and prediction has increased, investigating algorithmic studies for accurate prediction of hazardous environments and health impacts. Regarding health effects, techniques to prevent respiratory and related diseases were reviewed.

Analysis of Investment Time for a Residential Photovoltaic Power System in China and Thailand Applying a Real Option Model and SAM Data (Real Option 모형과 SAM데이터를 활용한 중국과 태국의 주거용 태양광 투자 시점 분석)

  • Moon, Yongma
    • The Journal of Society for e-Business Studies
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    • v.24 no.2
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    • pp.125-141
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    • 2019
  • This paper provides economic analysis for a residential photovoltaic (PV) power system of 5 districts in China and Thailand, using SAM (System Advisor Model) data. Unlike existing literature, the analysis is conducted from the investment timing perspective, as applying to a real option model which can incorporate the cost uncertainty of the PV system and a resident's option to delay the investment. This study shows that the gap of optimal investment times between a real option model and a generally used net present value model ranges from about 6 to 14 years. Also, we found a contracting result for a particular district that, while the investment is appropriate according to the net present value model, it is more reasonable to delay the PV system investment in terms of the real option model.

The Development of Seismic Monitoring for a Base-Isolated Building System (지진격리 구조물의 지진모니터링 시스템 개발)

  • 김성훈;조대승;박해동;김두훈
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2001.11a
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    • pp.247-251
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    • 2001
  • Nowadays, base isolation systems such as lead-rubber bearing, elastomer bearing and sliding bearing have been installed to the various structures to prevent the disaster from seismic. The performance of base isolation system have been well proved by model-scale experiments and numerical analysis. However. the seismic response data measured at real large base-isolated structures is still insufficient. This paper presents a seismic monitoring system, acquiring real-time acceleration signals up to 32 channels, displaying time history and spectrum of the signals, storing the acquired data at a PC hard disk, and replaying the saved data. Moreover, the system can be operated without any limitation for monitoring period by automatic management of stored data file. The developed system has been installed at a real base-isolated building using lead-rubber bearings and we expect its seismic response data with ground motion signal can be well licquired in case of earthquake occurrence.

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Real-time PCM Data Processing System Development for Flight Test Control (비행시험통제용 실시간 PCM 자료처리시스템 개발)

  • Park, In Hee
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.6
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    • pp.825-833
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    • 2021
  • In flight tests, aircraft moves in real time, so it is important that data from instrumentation/measurement equipment used to determine aircraft status are processed in necessary form and transmitted to flight control systems in real time. Therefore, through telemetry data processing time reduction and processing cycle improvement in flight test control computer data processing system, in order to provide faster slave-data and safety judgment information to radar/telemetry slave-data processing, flight safety analysis system, emergency destruction transmission system, etc., we developed a PCM processing system that can be operated independently by installing data processing software that can receive and process PCM data in current telemetry data processing system and radar information at the same time. In this paper, we explain classified software functions in detail, starting with overall structure of PCM data processing systems developed by supplementing existing systems. Additionally, PCM data processing system will be supplemented through system stabilization and test operation.

Research on OS fingerprinting Method for Real-time Traffic Analysis System (실시간 트래픽 분석을 위한 운영체제 판별 방법에 관한 연구)

  • Lee, Hyun-Shin;Kim, Myung-Sup
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.36 no.5B
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    • pp.443-450
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    • 2011
  • The Internet has become an essential part in our modern life by providing useful information. So, the volume of Internet traffic has been increasing rapidly, which emphasizes the importance of network traffic analysis for effective network operation and management. Signature based analysis have been commonly used, but it is shown that the increase of signatures due to the increase of applications causes the performance degradation of real-time traffic analysis on high-speed network links. In this paper, we propose OS fingerprinting method for real-time traffic analysis. The previous problems can be solved by utilizing the OS information. The OS fingerprinting method for real-time traffic analysis, proposed in this paper, conducts under passive mode, and improves the limitation of a previous method such as low completeness and accuracy. In this paper, we enlarged an input data to improve completeness, and used the User-Agent field in HTTP packet to extract various OS signatures. Also, we changed an input data from packet to flow to improve accuracy.

Data anomaly detection and Data fusion based on Incremental Principal Component Analysis in Fog Computing

  • Yu, Xue-Yong;Guo, Xin-Hui
    • 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.

Adaptive State Feedback Control for Nonlinear Rotary Inverted Pendulum System using Similarity Transformation Method: Implementation of Real-Time Experiment (유사변환기법을 이용한 비선형 회전식 역진자의 적응형 상태궤환 제어시스템: 실시간 실험 구현)

  • Cho, Hyun-Cheol;Lee, Young-Jin;Lee, Kwon-Soon;Koo, Kyung-Wan
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.58 no.2
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    • pp.130-135
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    • 2009
  • In recent years, researches on rotary inverted pendulum control systems have been significantly focused due their highly nonlinear dynamics and complicated geometric structures. This paper presents a novel control approach for such systems by means of similarity transformation theory. At first, we represent nonlinear system dynamics to the controllability-formed state space model including a time-varying parameter vector. We establish the state-feedback control configuration based on the transformed model and derive an adaptive control law for adjusting desired characteristic equation. Numerical analysis is achieved to evaluate our control method and demonstrate its superiority by comparing it to the traditional control strategy. Furthermore, real-time control experiment is carried out to test its practical reliability.

A Remote Trace Debugger for Multi-Task Programs in Qplus-T Embedded Internet System (Qplus-T내장형 인터넷 시스템에서 멀티 태스크 프로그램을 위한 원격 트레이스 디버거)

  • 이광용;김흥남
    • Journal of KIISE:Computing Practices and Letters
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    • v.9 no.2
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    • pp.166-181
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    • 2003
  • With the rapid growth of Internet, many devices such as Web TVs, PDAs and Web phones, begin to be directly connected to the Internet. These devices need real-time operating systems (RTOS) to support complex real-time applications running on them. Development of such real-time applications called embedded internet applications, is difficult due to the lack of adequate tools, especially debuggers. In this paper we present a new tracepoint debugging tool for the Qplus-T RTOS embedded system, which facilitates the instrumentations of the real-time software applications with timing trace-points. Compared with traditional breakpoint debugger, this trace-point debugger provides the ability to dynamically collect and record application data for on-line examination and for further off-line analysis. And, the trace-points can also provide the means for assigning new values to the running application's variables, without neither halting its execution nor interfering with its natural execution flow. Our trace-point debugger provides a highly efficient method for adding numerous monitoring trace-points within a real time target application such as Qplus-T internet applications, utilizing these trace-points to monitor and to analyze the application's behavior while it is running. And also, our trace debugger is different from previous one in that we can specify and detect the timing violations using its RTL (Real-Time Logic) trace experiments.

A New Distribution System Power Flow Method Using Symmetrical Components (대칭성분을 이용한 3상 배전계통 조류계산 기법)

  • Choe, Jeong-Hwan;Jeong, Seong-Il;Park, Je-Yeong;Kim, Gwang-Ho;Kim, Jae-Eon;Park, Jong-Geun
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.51 no.1
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    • pp.15-22
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    • 2002
  • This paper proposes a new power flow method for distribution system analysis by modifying the conventional back/forward sweep method using symmetrical components. Since the proposed method backward and forward sweeps with the variables expressed by symmetrical components, this method reduces computation time for matrix calculations; therefore, it is able to reduce the computational burden for real-time distribution network analysis. The proposed method was also developed to effectively analyze the unbalanced distribution system installing AVR(Auto Voltage Regulator), shunt capacitors. The proposed algorithm was compared with the conventional Back/forward Sweep method by applying both methods to three phase unbalanced distribution system of IEEE 123-bus model, and the test results showed that the proposed method would outperformed the conventional method in real-time distribution system analysis.