• Title/Summary/Keyword: Very large real-time data

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Use of Near Infrared Spectroscopy in the Meat Industry

  • Akselsen, Thorvald M.
    • Proceedings of the Korean Society for Food Science of Animal Resources Conference
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    • 2000.11a
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    • pp.1-14
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    • 2000
  • The Near Infrared region of the energy spectrum was first discovered by Hershel in the year 1800. The principles of NIR is based on light absorption of specific organic chemical bonds. The absorption at each wavelength is measured and a spectre is obtained. The spectre is then treated mathematically and with the absorption data is converted to absolute units via a calibration. In the last two decades it has developed dramatically. With the invention of computers and the ability to treat a large amount of data in a very short time the use of NIR for many different purposes has developed very fast. During the last decade with the aid of very powerful PC's the application of NIR technology has become even more widespread. Now or days development of very robust calibrations can be done in a relatively short time with a minimum of resources. The use of Near Infrared Spectroscopy (NIR) in the Meat industry is relatively new. The first installations were taken into operation in the 80ties. The Meat Industry in often referred to as rather conservative and slow to embrace new technologies, they stay with the old and proven methods. The first NIR instruments used by the Meat Industry, and most other industries, were multipurpose build, which means that the sample presentation was not well suited to this particular application, or many other applications for that sake. As the Meat Industry grows and develops to meet the demands of the modern markets, they realise the need for better control of processes and final products. From the early 90 ties and onward the demand for 'rear time' rapid results starts growing, and some suppliers of NIR instruments (and instruments based on other technologies, like X-ray) start to develop and manufacture instrumentation dedicated to the particular needs of the Meat Industry. Today it is estimated that there are approximately 2000 rapid instruments placed in the Meat industry world-wide. By far most of these are used as at-line or laboratory installations, but the trend and need is moving towards real on-line or in-line solutions. NIR is the most cost effective and reproducible analytical procedure available for the twenty first century.

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Air Pollution Changes of Jakarta, Banten, and West Java, Indonesia During the First Month of COVID-19 Pandemic

  • PRAMANA, Setia;PARAMARTHA, Dede Yoga;ADHINUGROHO, Yustiar;NURMALASARI, Mieke
    • Asian Journal of Business Environment
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    • v.10 no.4
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    • pp.15-19
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    • 2020
  • Purpose: This research aims to explore the level of air pollution in Jakarta, the epicenter of COVID-19 Pandemic in Indonesia and its surrounding provinces during the first month of the Pandemic. Research design, data and methodology: This study uses data, which have been obtained real time from API (Application Programming Interfaces) of air quality website. The measurements of Air Quality Index (AQI), temperature, humidity, and other factors from several cities and regencies in Indonesia were obtained eight times a day. The data collected have been analyzed using descriptive statistics and mapped using QGIS. Results: The finding of this study indicates that The Greater Jakarta Area experienced a decrease in pollutant levels, especially in the Bogor area. Nevertheless, some areas, such as the north Jakarta, have exhibited slow reduction. Furthermore, the regions with high COVID-19 confirmed cases have experienced a decline in AQI. Conclusions: The study concludes that the air quality of three provinces, Jakarta, Banten, and West Java, especially in cities located in the Jakarta Metropolitan Area during COVID-19 pandemic and large-scale social restrictions, is getting better. However, in some regions, the reduction of pollutant concentrations requires a longer time, as it was very high before the pandemic.

FMI based Real-time CPS Distributed Simulation Framework using OMG DDS middleware (OMG DDS 미들웨어를 이용한 FMI기반 실시간 CPS 분산 시뮬레이션 프레임워크)

  • Hong, Seokjoon;Joe, Inwhee;Kim, Wontae
    • Journal of IKEEE
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    • v.22 no.1
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    • pp.6-13
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    • 2018
  • To develop highly dependable CPS, M&S(modeling and simulation) is very important. It is not easy to model any CPS whole system in a single simulation tool because each simulation tool is optimized for modeling each different part of the CPS. The FMI is the standard for M&S between different simulation tools. The DDS is a communication middleware suitable for large-scale real-time data transmission. In this paper, we proposed FMI based CPS real-time distributed simulaton framework using DDS. To evaluate the performance of the proposed framework, we performed distributed simulation using IEEE HLA/RTI and OMG DDS middleware and measured and compared the execution time of the entire simulation. From the simulation results, we can confirm that the simulation execution time using DDS is at least 1.14 times faster compared to execution time using HLA/RTI.

A Study on System Identification of Active Magnetic Bearing Rotor System Considering Sensor and Actuator Dynamics (센서와 작동기를 고려한 자기베어링 시스템의 식별에 관한 연구)

  • Kim, Chan-Jung;Ahn, Hyeong-Joon;Han, Dong-Chul
    • Proceedings of the KSME Conference
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    • 2003.11a
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    • pp.1458-1463
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    • 2003
  • This paper presents an improved identification algorithm of active magnetic bearing rotor systems considering sensor and actuator dynamics. An AMB rotor system has both real and complex poles so that it is very hard to identify them together. In previous research, a linear transformation through a fictitious proportional feedback was used in order to shift the real poles close to the imaginary axis. However, the identification result highly depends on the fictitious feedback gain, and it is not easy to identify the additional dynamics including sensor and actuators at the same time. First, this paper discusses the necessity and a selection criterion of the fictitious feedback gain. An appropriate feedback gain minimizes dominant SVD(Singular Value Decomposition) error through maximizing rank deficiency. Second, more improvement in the identification is achieved through separating the common additional dynamics in all elements of frequency response matrix. The feasibility of the proposed identification algorithm is proved with two theoretical AMB rotor models. Finally, the proposed scheme is compared with previous identification methods using experimental data, and a great improvement in model quality and large amount of time saving can be achieved with the proposed method.

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Thermal creep behavior of CZ cladding under biaxial stress state

  • Jin, Xin;Lin, Yuyu;Zhang, Libin
    • Nuclear Engineering and Technology
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    • v.52 no.12
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    • pp.2901-2909
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    • 2020
  • Thermal creep is a key property of zircaloy cladding. CZ developed by CGN is a new zircaloy used as PWR fuel cladding. This research is devoted to investigating the thermal creep behavior of CZ and build the thermal creep model of CZ. Twenty internal pressure creep tests were conducted, and the ranges of temperature and Tresca stress were 320-430 ℃ and 70-300 MPa, respectively. Real-time creep data were analyzed by separating primary creep and steady-state creep. Based on Soderberg model and creep test data, CZ thermal creep model is derived. As a whole, the mean value and the standard deviation of P/M of CZ saturated primary creep strain are very close to these from steady-state creep rate, however, the predictive effect of primary creep is less satisfactory. Four conditions, where there exists large deviation between predicted values and test data, are 320 ℃ and 300 MPa, 350 ℃ and 190 MPa, 380 ℃ and 160 MPa, 380 ℃ and 190 MPa, respectively. As primary creep was much smaller than steady-state creep in long-time operation, the thermal creep model built can be applied to predict the thermal creep behavior of CZ cladding.

Dynamic Yield Improvement Model Using Neural Networks (신경망을 이용한 동적 수율 개선 모형)

  • Jung, Hyun-Chul;Kang, Chang-Wook;Kang, Hae-Woon
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.32 no.2
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    • pp.132-139
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    • 2009
  • Yield is a very important measure that can expresses simply for productivity and performance of company. So, yield is used widely in many industries nowadays. With the development of the information technology and online based real-time process monitoring technology, many industries operate the production lines that are developed into automation system. In these production lines, the product structures are very complexity and variety. So, there are many multi-variate processes that need to be monitored with many quality characteristics and associated process variables at the same time. These situations have made it possible to obtain super-large manufacturing process data sets. However, there are many difficulties with finding the cause of process variation or useful information in the high capacity database. In order to solve this problem, neural networks technique is a favorite technique that predicts the yield of process for process control. This paper uses a neural networks technique for improvement and maintenance of yield in manufacturing process. The purpose of this paper is to model the prediction of a sub process that has much effect to improve yields in total manufacturing process and the prediction of adjustment values of this sub process. These informations feedback into the process and the process is adjusted. Also, we show that the proposed model is useful to the manufacturing process through the case study.

A Study on the New Motion Estimation Algorithm of Binary Operation for Real Time Video Communication (실시간 비디오 통신에 적합한 새로운 이진 연산 움직임 추정 알고리즘에 관한 연구)

  • Lee, Wan-Bum;Shim, Byoung-Sup;Kim, Hwan-Yong
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.4
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    • pp.418-423
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    • 2004
  • The motion estimation algorithm based block matching is a widely used in the international standards related to video compression, such as the MPEG series and H.26x series. Full search algorithm(FA) ones of this block matching algorithms is usually impractical because of the large number of computations required for large search region. Fast search algorithms and conventional binary block matching algorithms reduce computational complexity and data processing time but this algorithms have disadvantages that is less performance than full search algorithm. This paper presents new Boolean matching algorithm, called BCBM(Bit Converted Boolean Matching). Proposed algorithm has performance closed to the FA by Boolean only block matching that may be very efficiently implemented in hardware for real time video communication. Simulation results show that the PSNR of the proposed algorithm is about 0.08㏈ loss than FA but is about 0.96∼2.02㏈ gain than fast search algorithm and conventional Boolean matching algorithm.

A Study on the New Binary Block Matching Algorithm for Motion Estimation of Real time Video Coding (실시간 비디오 압축의 움직임 추정을 위한 새로운 이진 블록 정합 알고리즘에 관한 연구)

  • 이완범;김환용
    • Journal of the Institute of Convergence Signal Processing
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    • v.5 no.2
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    • pp.126-131
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    • 2004
  • Full search algorithm(FA) provides the best performance but this is usually impractical because of the large number of computations required for large search region. Fast search and conventional Boolean matching algorithms reduce computational complexity and data processing time but this algorithms have disadvantages that is difficult of implementation of hardware because of high control overhead and that is less performance than FA. This paper presents new Boolean matching algorithm, called BCBM(Bit Converted Boolean Matching). Proposed algorithm has performance closed to the FA by Boolean only block matching that may be very efficiently implemented in hardware for real time video communication. Simulation results show that the PSNR of the proposed algorithm is about 0.08㏈ loss than FA but is about 0.96∼2.02㏈ gain than fast search algorithm and conventional Boolean matching algorithm.

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Compression Methods for Time Series Data using Discrete Cosine Transform with Varying Sample Size (가변 샘플 크기의 이산 코사인 변환을 활용한 시계열 데이터 압축 기법)

  • Moon, Byeongsun;Choi, Myungwhan
    • KIISE Transactions on Computing Practices
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    • v.22 no.5
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    • pp.201-208
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    • 2016
  • Collection and storing of multiple time series data in real time requires large memory space. To solve this problem, the usage of varying sample size is proposed in the compression scheme using discrete cosine transform technique. Time series data set has characteristics such that a higher compression ratio can be achieved with smaller amount of value changes and lower frequency of the value changes. The coefficient of variation and the variability of the differences between adjacent data elements (VDAD) are presumed to be very good measures to represent the characteristics of the time series data and used as key parameters to determine the varying sample size. Test results showed that both VDAD-based and the coefficient of variation-based scheme generate excellent compression ratios. However, the former scheme uses much simpler sample size decision mechanism and results in better compression performance than the latter scheme.

APPLICATION OF REMOTE SENSING FOR COASTAL HAZARD MONITORING IN TAM GIANG - CAU HAI LAGOON, VIETNAM

  • Dien, Tran Van;Lan, Tran Dinh;Huong, Do Thu
    • Proceedings of the KSRS Conference
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    • v.1
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    • pp.455-458
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    • 2006
  • Stretching on the coastline of 70 km, the Tam Giang - Cau Hai Lagoon plays a very important role for the coastal ecology and socio-economic development of Hue region where was Vietnam's Ancient Kingdom Capital and recognized as a World's Cultural Heritage. Recently, coastal hazard in the lagoon have occurred seriously such as inlet movement and fill up, coastal erosion, flood and inundation, etc. These hazards have impacted on lagoon environment, resources, ecosystems, socio-economic and sustainable development of this coastal area. This paper present a case study using remote sensing data in combination with ground survey for monitoring the coastal hazards in Tam Giang - Cau Hai lagoon in recent decades. Analysis results find that during its natural evolution, the lagoon has been being in three situations of only one, two and three inlets. When inlets opened or displaced, coastal erosion have occurred seriously toward new balance condition. Flood and inundation occurs every rainy season in lowland plain around lagoon. The historical flood happened in early of November 1999 with six days long, created very terrible damages for Thua Thien Hue province. Remote sensing data with capability of regular update, large area coverage is effective provide real-time and continuous information for coastal hazards monitoring.

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