• Title/Summary/Keyword: Real-time data pipeline system

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3D game animation production pipeline and application instance proposal (3D게임 애니메이션 제작 파이프라인 및 적용 사례 제안)

  • Han, Dong Hoon;Ryu, Seuc-Ho;Lee, Dong-Lyeor;Che, Te-June;Lee, Hung-Woo
    • Proceedings of the Korea Contents Association Conference
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    • 2007.11a
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    • pp.644-646
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    • 2007
  • On-line game industry had accomplished much growths and development. One in pain of the game enterprises according to quality of on-line comes to be short Game production pipeline and it is suitable in quick production schedule and to be easy to the standard research of form by of 3D game character animations which are various the game production at the time of application is possible, operation by and type by in necessity. Element by model classification of the digital base game character which is used in game it set from the research which it sees and research it analyzed and the fundamental data which is necessary to 3D game character animation productions escape it tried. And the digital motioncapture it applies a cap department system and real picture of the character animation which is various at real-time the control research moving and it advances at the time when the effectiveness is short highly in game industry and digital contents industry application the character animation production process which is possible and production pipeline escape the reporter to do it does.

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Application and performance evaluation of mass balance method for real-time pipe burst detection in supply pipeline (도수관로 실시간 관파손감지를 위한 물수지 분석 방법 적용 및 성능평가)

  • Eunher Shin;Gimoon Jeong;Kyoungpil Kim;Taeho Choi;Seon-ha Chae;Yong Woo Cho
    • Journal of Korean Society of Water and Wastewater
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    • v.37 no.6
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    • pp.347-361
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    • 2023
  • Water utilities are making various efforts to reduce water losses from water networks, and an essential part of them is to recognize the moment when a pipe burst occurs during operation quickly. Several physics-based methods and data-driven analysis are applied using real-time flow and pressure data measured through a SCADA system or smart meters, and methodologies based on machining learning are currently widely studied. Water utilities should apply various approaches together to increase pipe burst detection. The most intuitive and explainable water balance method and its procedure were presented in this study, and the applicability and detection performance were evaluated by applying this approach to water supply pipelines. Based on these results, water utilities can establish a mass balance-based pipe burst detection system, give a guideline for installing new flow meters, and set the detection parameters with expected performance. The performance of the water balance analysis method is affected by the water network operation conditions, the characteristics of the installed flow meter, and event data, so there is a limit to the general use of the results in all sites. Therefore, water utilities should accumulate experience by applying the water balance method in more fields.

Design and Verification of Algorithms for the Motion Detection of Vehicles using Hierarchical Motion Estimation and Parallel Processing (계층화 모션 추정법과 병렬처리 기반의 차량 움직임 측정 알고리즘 개발 및 검증1))

  • 강경훈;심현진;이은숙;정성태;남궁문;금기정;이상설
    • Proceedings of the IEEK Conference
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    • 2002.06d
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    • pp.21-24
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    • 2002
  • This paper presents a new method for the motion detection of vehicles using hierarchical motion estimation and parallel processing. It captures the road image by using a CMOS sensor. It divides the captured image into small blocks and detects the motion of each block by using a block-matching method which is based on a hierarchical motion estimation and parallel processing for the real-time processing. The parallelism is achieved by using the pipeline and the data flow technique. The proposed method has been implemented with an embedded system. Experimental results show that the proposed method detects the motion of vehicles in real-time.

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Two-dimensional DCT arcitecture for imprecise computation model (중간 결과값 연산 모델을 위한 2차원 DCT 구조)

  • 임강빈;정진군;신준호;최경희;정기현
    • Journal of the Korean Institute of Telematics and Electronics C
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    • v.34C no.9
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    • pp.22-32
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    • 1997
  • This paper proposes an imprecise compuitation model for DCT considering QOS of images and a two dimensional DCT architecture for imprecise computations. In case that many processes are scheduling in a hard real time system, the system resources are shared among them. Thus all processes can not be allocated enough system resources (such as processing power and communication bandwidth). The imprecise computtion model can be used to provide scheduling flexibility and various QOS(quality of service)levels, to enhance fault tolerance, and to ensure service continuity in rela time systems. The DCT(discrete cosine transform) is known as one of popular image data compression techniques and adopted in JPEG and MPEG algorithms since the DCT can remove the spatial redundancy of 2-D image data efficiently. Even though many commercial data compression VLSI chips include the DCST hardware, the DCT computation is still a very time-consuming process and a lot of hardware resources are required for the DCT implementation. In this paper the DCT procedure is re-analyzed to fit to imprecise computation model. The test image is simulated on teh base of this model, and the computation time and the quality of restored image are studied. The row-column algorithm is used ot fit the proposed imprecise computation DCT which supports pipeline operatiions by pixel unit, various QOS levels and low speed stroage devices. The architecture has reduced I/O bandwidth which could make its implementation feasible in VLSI. The architecture is proved using a VHDL simulator in architecture level.

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Real-time estimation of break sizes during LOCA in nuclear power plants using NARX neural network

  • Saghafi, Mahdi;Ghofrani, Mohammad B.
    • Nuclear Engineering and Technology
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    • v.51 no.3
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    • pp.702-708
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    • 2019
  • This paper deals with break size estimation of loss of coolant accidents (LOCA) using a nonlinear autoregressive with exogenous inputs (NARX) neural network. Previous studies used static approaches, requiring time-integrated parameters and independent firing algorithms. NARX neural network is able to directly deal with time-dependent signals for dynamic estimation of break sizes in real-time. The case studied is a LOCA in the primary system of Bushehr nuclear power plant (NPP). In this study, number of hidden layers, neurons, feedbacks, inputs, and training duration of transients are selected by performing parametric studies to determine the network architecture with minimum error. The developed NARX neural network is trained by error back propagation algorithm with different break sizes, covering 5% -100% of main coolant pipeline area. This database of LOCA scenarios is developed using RELAP5 thermal-hydraulic code. The results are satisfactory and indicate feasibility of implementing NARX neural network for break size estimation in NPPs. It is able to find a general solution for break size estimation problem in real-time, using a limited number of training data sets. This study has been performed in the framework of a research project, aiming to develop an appropriate accident management support tool for Bushehr NPP.

IoT Based Real-Time Indoor Air Quality Monitoring Platform for a Ventilation System (청정환기장치 최적제어를 위한 IoT 기반 실시간 공기질 모니터링 플랫폼 구현)

  • Uprety, Sudan Prasad;Kim, Yoosin
    • Journal of Internet Computing and Services
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    • v.21 no.6
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    • pp.95-104
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    • 2020
  • In this paper, we propose the real time indoor air quality monitoring and controlling platform on cloud using IoT sensor data such as PM10, PM2.5, CO2, VOCs, temperature, and humidity which has direct or indirect impact to indoor air quality. The system is connected to air ventilator to manage and optimize the indoor air quality. The proposed system has three main parts; First, IoT data collection service to measure, and collect indoor air quality in real time from IoT sensor network, Second, Big data processing pipeline to process and store the collected data on cloud platform and Finally, Big data analysis and visualization service to give real time insight of indoor air quality on mobile and web application. For the implication of the proposed system, IoT sensor kits are installed on three different public day care center where the indoor pollution can cause serious impact to the health and education of growing kids. Analyzed results are visualized on mobile and web application. The impact of ventilation system to indoor air quality is tested statistically and the result shows the proper optimization of indoor air quality.

City Gas Pipeline Pressure Prediction Model (도시가스 배관압력 예측모델)

  • Chung, Won Hee;Park, Giljoo;Gu, Yeong Hyeon;Kim, Sunghyun;Yoo, Seong Joon;Jo, Young-do
    • The Journal of Society for e-Business Studies
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    • v.23 no.2
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    • pp.33-47
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    • 2018
  • City gas pipelines are buried underground. Because of this, pipeline is hard to manage, and can be easily damaged. This research proposes a real time prediction system that helps experts can make decision about pressure anomalies. The gas pipline pressure data of Jungbu City Gas Company, which is one of the domestic city gas suppliers, time variables and environment variables are analysed. In this research, regression models that predicts pipeline pressure in minutes are proposed. Random forest, support vector regression (SVR), long-short term memory (LSTM) algorithms are used to build pressure prediction models. A comparison of pressure prediction models' preformances shows that the LSTM model was the best. LSTM model for Asan-si have root mean square error (RMSE) 0.011, mean absolute percentage error (MAPE) 0.494. LSTM model for Cheonan-si have RMSE 0.015, MAPE 0.668.

Real-time 3D Converting System using Stereoscopic Video (스테레오 비디오를 이용한 실시간 3차원 입체 변환 시스템)

  • Seo, Young-Ho;Choi, Hyun-Jun;Kim, Dong-Wook
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.33 no.10C
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    • pp.813-819
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    • 2008
  • In this paper, we implemented a real-time system which displays 3-dimensional (3D) stereoscopic image with stereo camera. The system consists of a set of stereo camera, FPGA board, and 3D stereoscopic LCD. Two CMOS image sensor were used for the stereo camera. FPGA which processes video data was designed with Verilog-HDL, and it can accommodate various resolutional videos. The stereoscopic image is configured by two methods which are side-by-side and up-down image configuration. After the left and right images are converted to the type for the stereoscopic display, they are stored into SDRAM. When the next frame is inputted into FPGA from two CMOS image sensors, the previous video data is output to the DA converter for displaying it. From this pipeline operation, the real-time operation is possible. After the proposed system was implemented into hardware, we verified that it operated exactly.

An Automated High Throughput Proteolysis and Desalting Platform for Quantitative Proteomic Analysis

  • Arul, Albert-Baskar;Han, Na-Young;Lee, Hookeun
    • Mass Spectrometry Letters
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    • v.4 no.2
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    • pp.25-29
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    • 2013
  • Proteomics for biomarker validation needs high throughput instrumentation to analyze huge set of clinical samples for quantitative and reproducible analysis at a minimum time without manual experimental errors. Sample preparation, a vital step in proteomics plays a major role in identification and quantification of proteins from biological samples. Tryptic digestion a major check point in sample preparation for mass spectrometry based proteomics needs to be more accurate with rapid processing time. The present study focuses on establishing a high throughput automated online system for proteolytic digestion and desalting of proteins from biological samples quantitatively and qualitatively in a reproducible manner. The present study compares online protein digestion and desalting of BSA with conventional off-line (in-solution) method and validated for real time sample for reproducibility. Proteins were identified using SEQUEST data base search engine and the data were quantified using IDEALQ software. The present study shows that the online system capable of handling high throughput samples in 96 well formats carries out protein digestion and peptide desalting efficiently in a reproducible and quantitative manner. Label free quantification showed clear increase of peptide quantities with increase in concentration with much linearity compared to off line method. Hence we would like to suggest that inclusion of this online system in proteomic pipeline will be effective in quantification of proteins in comparative proteomics were the quantification is really very crucial.

The Propose of Optimal Flow Data Acquisition by Error Rate Analysis of Flow Data (유량 데이터 오차율 분석을 통한 최적의 유량데이터 취득방안 제안)

  • Kim, Yunha;Choi, Hyunju
    • Journal of Korean Society of Water and Wastewater
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    • v.31 no.3
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    • pp.249-256
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    • 2017
  • Recently, application areas based on M2M (Machine-to-Machine communications) and IoT (Internet of Things) technologies are expanding rapidly. Accordingly, water flow and water quality management improvements are being pursued by applying this technology to water and sewage facilities. Especially, water management will collect and store accurate data based on various ICT technologies, and then will expand its service range to remote meter-reading service using smart metering system. For this, the error in flow rate data transmitting should be minimized to obtain credibility on related additional service system such as real time water flow rate analysis and billing. In this study, we have identified the structural problems in transmitting process and protocol to minimize errors in flow rate data transmission and its handling process which is essential to water supply pipeline management. The result confirmed that data acquisition via communication system is better than via analogue current values and pulse, and for communication method case, applying the industrial standard protocol is better for minimizing errors during data acquisition versus applying user assigned method.