• Title/Summary/Keyword: Single Sensor

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Parallel Computing on Intensity Offset Tracking Using Synthetic Aperture Radar for Retrieval of Glacier Velocity

  • Hong, Sang-Hoon
    • Korean Journal of Remote Sensing
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    • v.35 no.1
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    • pp.29-37
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    • 2019
  • Synthetic Aperture Radar (SAR) observations are powerful tools to monitor surface's displacement very accurately, induced by earthquake, volcano, ground subsidence, glacier movement, etc. Especially, radar interferometry (InSAR) which utilizes phase information related to distance from sensor to target, can generate displacement map in line-of-sight direction with accuracy of a few cm or mm. Due to decorrelation effect, however, degradation of coherence in the InSAR application often prohibit from construction of differential interferogram. Offset tracking method is an alternative approach to make a two-dimensional displacement map using intensity information instead of the phase. However, there is limitation in that the offset tracking requires very intensive computation power and time. In this paper, efficiency of parallel computing has been investigated using high performance computer for estimation of glacier velocity. Two TanDEM-X SAR observations which were acquired on September 15, 2013 and September 26, 2013 over the Narsap Sermia in Southwestern Greenland were collected. Atotal of 56 of 2.4 GHz Intel Xeon processors(28 physical processors with hyperthreading) by operating with linux environment were utilized. The Gamma software was used for application of offset tracking by adjustment of the number of processors for the OpenMP parallel computing. The processing times of the offset tracking at the 256 by 256 pixels of window patch size at single and 56 cores are; 26,344 sec and 2,055 sec, respectively. It is impressive that the processing time could be reduced significantly about thirteen times (12.81) at the 56 cores usage. However, the parallel computing using all the processors prevent other background operations or functions. Except the offset tracking processing, optimum number of processors need to be evaluated for computing efficiency.

The Analysis of the Collimator & Radiation Shield for the Radiation Sensor for the 3Dimension Radiation Detection (3차원 방사선 탐지장치용 검출센서의 차폐체 및 Collimator 구조 분석 연구)

  • Hwang, Young-Gwan;Lee, Nam-Ho;Park, Sumg-Hun;Jeong, Sang-Hun;Kim, Jong-Ryul;Choi, Myung-Jin
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2014.05a
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    • pp.707-709
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    • 2014
  • The radiation sources leaked from large-scale radiation leak accident like the Fukushima nuclear power plant accident or nuclear explosions can cause to the very large damage for us. So that the damage can be minimized, we have being developed a detector that can providing information about the location of the source to remove dangerous substances quickly than the conventional single detector. In this paper, we designed and implemented the radiation shield and the collimator for the development of the stereo radiation detector to detect contamination things using MCNP Simulation. And we analysed the test results of the radiation shield and collimator using the radiation source. The results of this paper will be used as the basis for improving the efficiency of the stereo radiation detector being studied currently.

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A Method to Provide Context from Massive Data Processing in Context-Aware System (상황인지 시스템에서 대용량의 데이터 처리결과를 컨텍스트 정보로 제공하기 위한 방법)

  • Park, Yoo Sang;Choi, Jong Sun;Choi, Jae Young
    • KIPS Transactions on Software and Data Engineering
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    • v.8 no.4
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    • pp.145-152
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    • 2019
  • Unlike a single value from a sensor device, a massive data set has characteristics for various processing aspects; input data may be formed in a different format, the size of input data varies, and the processing time of analyzing input data is not predictable. Therefore, context aware systems may contain complex modules, and these modules can be implemented and used in different ways. In order to solve these problems, we propose a method to handle context information from the result of analyzing massive data. The proposed method considers analysis work as a different type of abstracting context and suggests the way of representing context information. In experiment, we demonstrate how the context processing engine works properly in a couple of steps with healthcare services.

Detection and Identification of CMG Faults based on the Gyro Sensor Data (자이로 센서 정보 기반 CMG 고장 진단 및 식별)

  • Lee, Jung-Hyung;Lee, Hun-Jo;Lee, Jun-Yong;Oh, Hwa-Suk;Song, Tae-Seong;Kang, Jeong-min;Song, Deok-ki;Seo, Joong-bo
    • Journal of Aerospace System Engineering
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    • v.13 no.2
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    • pp.26-33
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    • 2019
  • Control moment gyro (CMG) employed as satellite actuators, generates a large torque through the steering of its gimbals. Although each gimbal holds a high-speed rotating wheel, the wheel imbalances induces disturbance and degrades the satellite control quality. Therefore, the disturbances ought to be detected and identified as a precaution against actuator faults. Among the method used in detecting disturbances is the state observers. In this paper, we apply a continuous second order sliding mode observer to detect single disturbances/faults in CMGs. Verification of the algorithm is also done on the hardware satellite simulator where four CMGs are installed.

The Principle and Trends of CRISPR/Cas Diagnosis (CRISPR/Cas 진단의 원리와 현황)

  • Park, Jeewoong;Kang, Bong Keun;Shin, Hwa Hui;Shin, Jun Geun
    • Journal of Biomedical Engineering Research
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    • v.42 no.3
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    • pp.125-142
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    • 2021
  • The POCT (point-of-care test) sensing that has been a fast-developing field is expected to be a next generation technology in health care. The POCT sensors for the detection of proteins, small molecules and especially nucleic acids have lately attracted considerable attention. According to the World Health Organization (WHO), the POCT methods are required to follow the ASSURED guidelines (Affordable, Sensitive, Specific, User- friendly, Robust and rapid, Equipment-free, Deliverable to all people who need the test). Recently, several CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) based diagnostic techniques using the sensitive gene recognition function of CRISPR have been reported. CRISPR/Cas (Cas, CRISPR associated protein) systems based detection technology is the most innovative gene analysis technology that is following the ASSURED guidelines. It is being re-emerged as a powerful diagnostic tool that can detect nucleic acids due to its characteristics that enable rapid, sensitive and specific analyses of nucleic acid. The first CRISPR-based diagnosis begins with the discovery of the additional function of Cas13a. The enzymatic cleavage occurs when the conjugate of Cas protein and CRISPR RNA (crRNA) detect a specific complementary sequence of the target sequence. Enzymatic cleavage occurs on not only the target sequence, but also all surrounding non-target single-stranded RNAs. This discovery was immediately utilized as a biosensor, and numerous sensor studies using CRISPR have been reported since then. In this review, the concept of CRISPR, the characteristics of the Cas protein required for CRISPR diagnosis, the current research trends of CRISPR diagnostic technology, and some aspects to be improved in the future are covered.

Closed-form based 3D Localization for Multiple Signal Sources (다중 신호원에 대한 닫힌 형태 기반 3차원 위치 추정)

  • Ko, Yo-han;Bu, Sung-chun;Lee, Chul-soo;Lim, Jae-wook;Chae, Ju-hui
    • Journal of Advanced Navigation Technology
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    • v.26 no.2
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    • pp.78-84
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    • 2022
  • In this paper, we propose a closed-form based 3D localization method in the presence of multiple signal sources. General localization methods such as TDOA, AOA, and FDOA can estimate a location when a single signal source exists. When there are multiple unknown signal sources, there is a limit in estimating the location. The proposed method calculates a cross-correlation vector of signals received by sensors having an array antenna, and estimates TDOA and AOA values from the cross-correlation values. Then, the coordinate transformation is performed using the position of the reference sensor. Then, the coordinate rotation is performed using the estimated AOA value for the transformed coordinates, and then the three-dimensional position of each emitter is estimated. The proposed method verifies its performance through computer simulation.

Development of Long-perimeter Intrusion Detection System Aided by deep Learning-based Distributed Fiber-optic Acoustic·vibration Sensing Technology (딥러닝 기반 광섬유 분포 음향·진동 계측기술을 활용한 장거리 외곽 침입감지 시스템 개발)

  • Kim, Huioon;Lee, Joo-young;Jung, Hyoyoung;Kim, Young Ho;Kwon, Jun Hyuk;Ki, Song Do;Kim, Myoung Jin
    • Journal of Sensor Science and Technology
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    • v.31 no.1
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    • pp.24-30
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    • 2022
  • Distributed fiber-optic acoustic·vibration sensing technology is becoming increasingly popular in many industrial and academic areas such as in securing large edifices, exploring underground seismic activity, monitoring oil well/reservoir, etc. Long-range perimeter intrusion detection exemplifies an application that not only detects intrusion, but also pinpoints where it happens and recognizes kinds of threats made along the perimeter where a single fiber cable was installed. In this study, we developed a distributed fiber-optic sensing device that measures a distributed acoustic·vibration signature (pattern) for intrusion detection. In addition, we demontrate the proposed deep learning algorithm and how it classifies various intrusion events. We evaluated the sensing device and deep learning algorithm in a practical testbed setup. The evaluation results confirm that the developed system is a promising intrusion detection system for long-distance and seamless recognition requirements.

Method for predicting the diagnosis of mastitis in cows using multivariate data and Recurrent Neural Network (다변량 데이터와 순환 신경망을 이용한 젖소의 유방염 진단예측 방법)

  • Park, Gicheol;Lee, Seonghun;Park, Jaehwa
    • Journal of Software Assessment and Valuation
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    • v.17 no.1
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    • pp.75-82
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    • 2021
  • Mastitis in cows is a major factor that hinders dairy productivity of farms, and many attempts have been made to solve it. However, research on mastitis has been limited to diagnosis rather than prediction, and even this is mostly using a single sensor. In this study, a predictive model was developed using multivariate data including biometric data and environmental data. The data used for the analysis were collected from robot milking machines and sensors installed in farmhouses in Chungcheongnam-do, South Korea. The recurrent neural network model using three weeks of data predicts whether or not mastitis is diagnosed the next day. As a result, mastitis was predicted with an accuracy of 82.9%. The superiority of the model was confirmed by comparing the performance of various data collection periods and various models.

Exploring precise deposition and influence mechanism for micro-scale serpentine structure fiber

  • Wang, Han;Ou, Weicheng;Zhong, Huiyu;He, Jingfan;Wang, Zuyong;Cai, Nian;Chen, XinDu;Xue, Zengxi;Liao, Jianxiang;Zhan, Daohua;Yao, Jingsong;Wu, Peixuan
    • Advances in nano research
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    • v.12 no.2
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    • pp.151-165
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    • 2022
  • Micro-scale serpentine structure fibers are widely used as flexible sensor in the manufacturing of micro-nano flexible electronic devices because of their outstanding non-linear mechanical properties and organizational flexibility. The use of melt electrowriting (MEW) technology, combined with the axial bending effect of the Taylor cone jet in the process, can achieve the micro-scale serpentine structure fibers. Due to the interference of the process parameters, it is still challenging to achieve the precise deposition of micro-scale and high-consistency serpentine structure fibers. In this paper, the micro-scale serpentine structure fiber is produced by MEW combined with axial bending effect. Based on the controlled deposition of MEW, applied voltage, collector speed, nozzle height and nozzle diameter are adjusted to achieve the precise deposition of micro-scale serpentine structure fibers with different morphologies in a single motion dimension. Finally, the influence mechanism of the above four parameters on the precise deposition of micro-scale serpentine fibers is explored.

Development of Automatic Peach Grading System using NIR Spectroscopy

  • Lee, Kang-J.;Choi, Kyu H.;Choi, Dong S.
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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    • pp.1267-1267
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    • 2001
  • The existing fruit sorter has the method of tilting tray and extracting fruits by the action of solenoid or springs. In peaches, the most sort processing is supported by man because the sorter make fatal damage to peaches. In order to sustain commodity and quality of peach non-destructive, non-contact and real time based sorter was needed. This study was performed to develop peach sorter using near-infrared spectroscopy in real time and nondestructively. The prototype was developed to decrease internal and external damage of peach caused by the sorter, which had a way of extracting tray with it. To decrease positioning error of measuring sugar contents in peaches, fiber optic with two direction diverged was developed and attached to the prototype. The program for sorting and operating the prototype was developed using visual basic 6.0 language to measure several quality index such as chlorophyll, some defect, sugar contents. The all sorting result was saved to return farmers for being index of good quality production. Using the prototype, program and MLR(multiple linear regression) model, it was possible to estimate sugar content of peaches with the determination coefficient of 0.71 and SEC of 0.42bx using 16 wavelengths. The developed MLR model had determination coefficient of 0.69, and SEP of 0.49bx, it was better result than single point measurement of 1999's. The peach sweetness grading system based on NIR reflectance method, which consists of photodiode-array sensor, quartz-halogen lamp and fiber optic diverged two bundles for transmitting the light and detecting the reflected light, was developed and evaluated. It was possible to predict the soluble solid contents of peaches in real time and nondestructively using the system which had the accuracy of 91 percentage and the capacity of 7,200 peaches per an hour for grading 2 classes by sugar contents. Draining is one of important factors for production peaches having good qualities. The reason why one farm's product belows others could be estimated for bad draining, over-much nitrogen fertilizer, soil characteristics, etc. After this, the report saved by the peach grading system will have to be good materials to farmers for production high quality peaches. They could share the result or compare with others and diagnose their cultural practice.

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