• Title/Summary/Keyword: Low precision network

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OD matrix estimation using link use proportion sample data as additional information (표본링크이용비를 추가정보로 이용한 OD 행렬 추정)

  • 백승걸;김현명;신동호
    • Journal of Korean Society of Transportation
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    • v.20 no.4
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    • pp.83-93
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    • 2002
  • To improve the performance of estimation, the research that uses additional information addition to traffic count and target OD with additional survey cost have been studied. The purpose of this paper is to improve the performance of OD estimation by reducing the feasible solutions with cost-efficiently additional information addition to traffic counts and target OD. For this purpose, we Propose the OD estimation method with sample link use proportion as additional information. That is, we obtain the relationship between OD trip and link flow from sample link use proportion that is high reliable information with roadside survey, not from the traffic assignment of target OD. Therefore, this paper proposes OD estimation algorithm in which the conservation of link flow rule under the path-based non-equilibrium traffic assignment concept. Numerical result with test network shows that it is possible to improve the performance of OD estimation where the precision of additional data is low, since sample link use Proportion represented the information showing the relationship between OD trip and link flow. And this method shows the robust performance of estimation where traffic count or OD trip be changed, since this method did not largely affected by the error of target OD and the one of traffic count. In addition to, we also propose that we must set the level of data precision by considering the level of other information precision, because "precision problem between information" is generated when we use additional information like sample link use proportion etc. And we Propose that the method using traffic count as basic information must obtain the link flow to certain level in order to high the applicability of additional information. Finally, we propose that additional information on link have a optimal counting location problem. Expecially by Precision of information side it is possible that optimal survey location problem of sample link use proportion have a much impact on the performance of OD estimation rather than optimal counting location problem of link flow.

Vehicle Dynamics and Road Slope Estimation based on Cascade Extended Kalman Filter (Cascade Extended Kalman Filter 기반의 차량동특성 및 도로종단경사 추정)

  • Kim, Moon-Sik;Kim, Chang-Il;Lee, Kwang-Soo
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.9
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    • pp.208-214
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    • 2014
  • Vehicle dynamic states used in various advanced driving safety systems are influenced by road geometry. Among the road geometry information, the vehicle pitch angle influenced by road slope and acceleration-deceleration is essential parameter used in pose estimation including the navigation system, advanced adaptive cruise control and others on sag road. Although the road slope data is essential parameter, the method measuring the parameter is not commercialized. The digital map including the road geometry data and high-precision DGPS system such as DGPS(Differential Global Positioning System) based RTK(Real-Time Kinematics) are used unusually. In this paper, low-cost cascade extended Kalman filter(CEKF) based road slope estimation method is proposed. It use cascade two EKFs. The EKFs use several measured vehicle states such as yaw rate, longitudinal acceleration, lateral acceleration and wheel speed of the rear tires and 3 D.O.F(Degree Of Freedom) vehicle dynamics model. The performance of proposed estimation algorithm is evaluated by simulation based on Carsim dynamics tool and T-car based experiment.

Fundamental Experiment for the Development of Water Pipeline Locator (상수도관로 위치탐사 장비개발을 위한 기초실험)

  • Park, Sang-Bong;Kim, Jin-Won;Oh, Kyeong-Seok;Kim, Min-Cheol;Koo, Ja-yong
    • Journal of Korean Society of Water and Wastewater
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    • v.30 no.3
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    • pp.253-261
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    • 2016
  • A variety of methods for detecting the location of an underground water pipeline are being used across the world; the current main methods used in South Korea, however, have the problems of low precision and efficiency and the limitations in actual application. On this, this study developed locator capable of detecting the location of a water pipe by the use of an IMU sensor, and technology for using the extended karman filter to correct error in location detection and to plot the location on the coordinate system. This study carried out a tract test and a road test as basic experiments to measure the performance of the developed technology and equipment. As a result of the straight line, circular and ellipse track tests, the 1750 IMU sensor showed the average error of 0.08-0.11%; and thus it was found that the developed locator can detect a location precisely. As a result of the 859.6-m road test, it was found that the error was 0.31 m in case the moving rate of the sensor was 0.3-0.6 m/s; and thus it was judged that the equipment developed by this study can be applied to long-distance water pipes of over 1 km sufficiently. It is planned to evaluate its field applicability in the future through an actual pipe network pilot test, and it is expected that locator capable of detecting the location of a water pipe more precisely will be developed through research for the enhancement of accuracy in the algorithm of location detection.

Ground Tracking Support Condition Effect on Orbit Determination for Korea Pathfinder Lunar Orbiter (KPLO) in Lunar Orbit

  • Kim, Young-Rok;Song, Young-Joo;Park, Jae-ik;Lee, Donghun;Bae, Jonghee;Hong, SeungBum;Kim, Dae-Kwan;Lee, Sang-Ryool
    • Journal of Astronomy and Space Sciences
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    • v.37 no.4
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    • pp.237-247
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    • 2020
  • The ground tracking support is a critical factor for the navigation performance of spacecraft orbiting around the Moon. Because of the tracking limit of antennas, only a small number of facilities can support lunar missions. Therefore, case studies for various ground tracking support conditions are needed for lunar missions on the stage of preliminary mission analysis. This study analyzes the ground supporting condition effect on orbit determination (OD) of Korea Pathfinder Lunar Orbiter (KPLO) in the lunar orbit. For the assumption of ground support conditions, daily tracking frequency, cut-off angle for low elevation, tracking measurement accuracy, and tracking failure situations were considered. Two antennas of deep space network (DSN) and Korea Deep Space Antenna (KDSA) are utilized for various tracking conditions configuration. For the investigation of the daily tracking frequency effect, three cases (full support, DSN 4 pass/day and KDSA 4 pass/day, and DSN 2 pass/day and KDSA 2 pass/day) are prepared. For the elevation cut-off angle effect, two situations, which are 5 deg and 10 deg, are assumed. Three cases (0%, 30%, and 50% of degradation) were considered for the tracking measurement accuracy effect. Three cases such as no missing, 1-day KDSA missing, and 2-day KDSA missing are assumed for tracking failure effect. For OD, a sequential estimation algorithm was used, and for the OD performance evaluation, position uncertainty, position differences between true and estimated orbits, and orbit overlap precision according to various ground supporting conditions were investigated. Orbit prediction accuracy variations due to ground tracking conditions were also demonstrated. This study provides a guideline for selecting ground tracking support levels and preparing a backup plan for the KPLO lunar mission phase.

A study of communication-based protection coordination for networked distribution system (네트워크 배전계통용 통신기반 보호협조에 관한 연구)

  • Kim, WooHyun;Chae, WooKyu;Hwang, SungWook;Lee, HakJu
    • KEPCO Journal on Electric Power and Energy
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    • v.8 no.1
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    • pp.43-48
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    • 2022
  • Although the distribution system has been structured as complicated as a mesh in the past, the connection points for each line are always kept open, so that it is operated as a radial distribution system (RDS). For RDS, the line utilization rate is determined according to the maximum load on the line, and the utilization rate is usually kept low. In addition, when a fault occurs in the RDS, a power outage of about 3 to 5 minutes occurs until the fault section is separated, and the healthy section is transferred to another line. To improve the disadvantages of the RDS, research on the construction of a networked distribution system (NDS) that linking multiple lines is in progress. Compared to the RDS, the NDS has advantages such as increased facility utilization, load leveling, self-healing, increased capacity connected to distributed generator, and resolution of terminal voltage drop. However, when a fault occurs in the network distribution system, fault current can flow in from all connected lines, and the direction of fault current varies depending on the fault point, so a high-precision fault current direction determination method and high-speed communication are required. Therefore, in this paper, we propose an accurate fault current direction determination method by comparing the peak value polarity of the fault current in the event of a fault, and a communication-based protection coordination method using this method.

Fashion Category Oversampling Automation System

  • Minsun Yeu;Do Hyeok Yoo;SuJin Bak
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.1
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    • pp.31-40
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    • 2024
  • In the realm of domestic online fashion platform industry the manual registration of product information by individual business owners leads to inconvenience and reliability issues, especially when dealing with simultaneous registrations of numerous product groups. Moreover, bias is significantly heightened due to the low quality of product images and an imbalance in data quantity. Therefore, this study proposes a ResNet50 model aimed at minimizing data bias through oversampling techniques and conducting multiple classifications for 13 fashion categories. Transfer learning is employed to optimize resource utilization and reduce prolonged learning times. The results indicate improved discrimination of up to 33.4% for data augmentation in classes with insufficient data compared to the basic convolution neural network (CNN) model. The reliability of all outcomes is underscored by precision and affirmed by the recall curve. This study is suggested to advance the development of the domestic online fashion platform industry to a higher echelon.

CHANGING THE ANIMAL WORLD WITH NIR : SMALL STEPS OR GIANT LEAPS\ulcorner

  • Flinn, Peter C.
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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    • pp.1062-1062
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    • 2001
  • The concept of “precision agriculture” or “site-specific farming” is usually confined to the fields of soil science, crop science and agronomy. However, because plants grow in soil, animals eat plants, and humans eat animal products, it could be argued (perhaps with some poetic licence) that the fields of feed quality, animal nutrition and animal production should also be considered in this context. NIR spectroscopy has proved over the last 20 years that it can provide a firm foundation for quality measurement across all of these fields, and with the continuing developments in instrumentation, computer capacity and software, is now a major cog in the wheel of precision agriculture. There have been a few giant leaps and a lot of small steps in the impact of NIR on the animal world. These have not been confined to the amazing advances in hardware and software, although would not have occurred without them. Rapid testing of forages, grains and mixed feeds by NIR for nutritional value to livestock is now commonplace in commercial laboratories world-wide. This would never have been possible without the pioneering work done by the USDA NIR Forage Research Network in the 1980's, following the landmark paper of Norris et al. in 1976. The advent of calibration transfer between instruments, algorithms which utilize huge databases for calibration and prediction, and the ability to directly scan whole grains and fresh forages can also be considered as major steps, if not leaps. More adventurous NIR applications have emerged in animal nutrition, with emphasis on estimating the functional properties of feeds, such as in vivo digestibility, voluntary intake, protein degradability and in vitro assays to simulate starch digestion. The potential to monitor the diets of grazing animals by using faecal NIR spectra is also now being realized. NIR measurements on animal carcasses and even live animals have also been attempted, with varying degrees of success, The use of discriminant analysis in these fields is proving a useful tool. The latest giant leap is likely to be the advent of relatively low-cost, portable and ultra-fast diode array NIR instruments, which can be used “on-site” and also be fitted to forage or grain harvesters. The fodder and livestock industries are no longer satisfied with what we once thought was revolutionary: a 2-3 day laboratory turnaround for fred quality testing. This means that the instrument needs to be taken to the samples rather than vice versa. Considerable research is underway in this area, but the challenge of calibration transfer and maintenance of instrument networks of this type remains. The animal world is currently facing its biggest challenges ever; animal welfare, alleged effects of animal products on human health, environmental and economic issues are difficult enough, but the current calamities of BSE and foot and mouth disease are “the last straw” NIR will not of course solve all these problems, but is already proving useful in some of these areas and will continue to do so.

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PM10 β-ray attenuation samplers (β-ray absorption method) equivalence evaluation and comparatively observed study (PM10 연속자동측정기(β-ray) 등가성평가 및 비교관측 연구)

  • WonSeok Jung;Hee-Jung Ko;Wonick Seo;Jiyoung Jeong;Sang Min Oh;Kyung-On Boo
    • Particle and aerosol research
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    • v.19 no.1
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    • pp.13-20
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    • 2023
  • The Asian dust observation network operates β-ray attenuation samplers to measure PM10 concentrations. In addition, equivalence evaluation and accuracy inspection(Precision Tests) are conducted every year for the reliability of data. β-ray attenuation samplers(16 units) were comparatively observed from May to June 2020 and from July to December 2021. During the observation period, the average daily temperature was the lowest at 6.4℃ in December and the highest at 27.3℃ in August. The average daily humidity ranged from 60% to 100%, but the average daily humidity was over 75% from July to September. The minimum value of the PM10 Gravimetric method was 5.0 ㎍/m3, the maximum value was 53.4 ㎍/m3, and the average value was 17.8 ㎍/m3. The equivalence evaluation results of the PM10 Gravimetric method and β-ray attenuation samplers satisfied the criteria (slope: 1±0.1, intercept: 0±0.5). A relative error analysis between the PM10 Gravimetric method and β-ray attenuation samplers equipment showed that the relative error increased when the concentration was low and the temperature and humidity were high. In addition, in the β-ray attenuation samplers 5-minute interval observation data in May 2020, a relatively large Standard devication was shown as an average maximum ±23.4 ㎍/m3 and a minimum ±15.2 ㎍/m3. At standard deviations of 10% and 90%, equipment with high variability (deviation) was measured at 6 ㎍/m3and 61 ㎍/m3, and equipment with low variability was measured at 12 ㎍/m3 and 47 ㎍/m3. It was confirmed that concentration differences occurred due to differences in variability for each equipment.

Development of deep learning network based low-quality image enhancement techniques for improving foreign object detection performance (이물 객체 탐지 성능 개선을 위한 딥러닝 네트워크 기반 저품질 영상 개선 기법 개발)

  • Ki-Yeol Eom;Byeong-Seok Min
    • Journal of Internet Computing and Services
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    • v.25 no.1
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    • pp.99-107
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    • 2024
  • Along with economic growth and industrial development, there is an increasing demand for various electronic components and device production of semiconductor, SMT component, and electrical battery products. However, these products may contain foreign substances coming from manufacturing process such as iron, aluminum, plastic and so on, which could lead to serious problems or malfunctioning of the product, and fire on the electric vehicle. To solve these problems, it is necessary to determine whether there are foreign materials inside the product, and may tests have been done by means of non-destructive testing methodology such as ultrasound ot X-ray. Nevertheless, there are technical challenges and limitation in acquiring X-ray images and determining the presence of foreign materials. In particular Small-sized or low-density foreign materials may not be visible even when X-ray equipment is used, and noise can also make it difficult to detect foreign objects. Moreover, in order to meet the manufacturing speed requirement, the x-ray acquisition time should be reduced, which can result in the very low signal- to-noise ratio(SNR) lowering the foreign material detection accuracy. Therefore, in this paper, we propose a five-step approach to overcome the limitations of low resolution, which make it challenging to detect foreign substances. Firstly, global contrast of X-ray images are increased through histogram stretching methodology. Second, to strengthen the high frequency signal and local contrast, we applied local contrast enhancement technique. Third, to improve the edge clearness, Unsharp masking is applied to enhance edges, making objects more visible. Forth, the super-resolution method of the Residual Dense Block (RDB) is used for noise reduction and image enhancement. Last, the Yolov5 algorithm is employed to train and detect foreign objects after learning. Using the proposed method in this study, experimental results show an improvement of more than 10% in performance metrics such as precision compared to low-density images.

Transfer and Validation of NIRS Calibration Models for Evaluating Forage Quality in Italian Ryegrass Silages (이탈리안 라이그라스 사일리지의 품질평가를 위한 근적외선분광 (NIRS) 검량식의 이설 및 검증)

  • Cho, Kyu Chae;Park, Hyung Soo;Lee, Sang Hoon;Choi, Jin Hyeok;Seo, Sung;Choi, Gi Jun
    • Journal of Animal Environmental Science
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    • v.18 no.sup
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    • pp.81-90
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    • 2012
  • This study was evaluated high end research grade Near infrared spectrophotometer (NIRS) to low end popular field grade multiple Near infrared spectrophotometer (NIRS) for rapid analysis at forage quality at sight with 241 samples of Italian ryegrass silage during 3 years collected whole country for evaluate accuracy and precision between instruments. Firstly collected and build database high end research grade NIRS using with Unity Scientific Model 2500X (650 nm~2,500 nm) then trim and fit to low end popular field grade NIRS with Unity Scientific Model 1400 (1,400 nm~2,400 nm) then build and create calibration, transfer calibration with special transfer algorithm. The result between instruments was 0.000%~0.343% differences, rapidly analysis for chemical constituents, NDF, ADF, and crude protein, crude ash and fermentation parameter such as moisture, pH and lactic acid, finally forage quality parameter, TDN, DMI, RFV within 5 minutes at sight and the result equivalent with laboratory data. Nevertheless during 3 years collected samples for build calibration was organic samples that make differentiate by local or yearly bases etc. This strongly suggest population evaluation technique needed and constantly update calibration and maintenance calibration to proper handling database accumulation and spread out by knowledgable control laboratory analysis and reflect calibration update such as powerful control center needed for long lasting usage of forage analysis with NIRS at sight. Especially the agriculture products such as forage will continuously changes that made easily find out the changes and update routinely, if not near future NIRS was worthless due to those changes. Many research related NIRS was shortly study not long term study that made not well using NIRS, so the system needed check simple and instantly using with local language supported signal methods Global Distance (GD) and Neighbour Distance (ND) algorithm. Finally the multiple popular field grades instruments should be the same results not only between research grade instruments but also between multiple popular field grade instruments that needed easily transfer calibration and maintenance between instruments via internet networking techniques.