• Title/Summary/Keyword: velocity information

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An Efficient Complex Event Processing Algorithm based on Multipattern Sharing for Massive Manufacturing Event Streams

  • Wang, Jianhua;Lan, Yubin;Lu, Shilei;Cheng, Lianglun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.3
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    • pp.1385-1402
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    • 2019
  • Quickly picking up some valuable information from massive manufacturing event stream usually faces with the problem of long detection time, high memory consumption and low detection efficiency due to its stream characteristics of large volume, high velocity, many variety and small value. Aiming to solve the problem above for the current complex event processing methods because of not sharing detection during the detecting process for massive manufacturing event streams, an efficient complex event processing method based on multipattern sharing is presented in this paper. The achievement of this paper lies that a multipattern sharing technology is successfully used to realize the quick detection of complex event for massive manufacturing event streams. Specially, in our scheme, we firstly use pattern sharing technology to merge all the same prefix, suffix, or subpattern that existed in single pattern complex event detection models into a multiple pattern complex event detection model, then we use the new detection model to realize the quick detection for complex events from massive manufacturing event streams, as a result, our scheme can effectively solve the problems above by reducing lots of redundant building, storing, searching and calculating operations with pattern sharing technology. At the end of this paper, we use some simulation experiments to prove that our proposed multiple pattern processing scheme outperforms some general processing methods in current as a whole.

Boundary-RRT* Algorithm for Drone Collision Avoidance and Interleaved Path Re-planning

  • Park, Je-Kwan;Chung, Tai-Myoung
    • Journal of Information Processing Systems
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    • v.16 no.6
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    • pp.1324-1342
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    • 2020
  • Various modified algorithms of rapidly-exploring random tree (RRT) have been previously proposed. However, compared to the RRT algorithm for collision avoidance with global and static obstacles, it is not easy to find a collision avoidance and local path re-planning algorithm for dynamic obstacles based on the RRT algorithm. In this study, we propose boundary-RRT*, a novel-algorithm that can be applied to aerial vehicles for collision avoidance and path re-planning in a three-dimensional environment. The algorithm not only bounds the configuration space, but it also includes an implicit bias for the bounded configuration space. Therefore, it can create a path with a natural curvature without defining a bias function. Furthermore, the exploring space is reduced to a half-torus by combining it with simple right-of-way rules. When defining the distance as a cost, the proposed algorithm through numerical analysis shows that the standard deviation (σ) approaches 0 as the number of samples per unit time increases and the length of epsilon ε (maximum length of an edge in the tree) decreases. This means that a stable waypoint list can be generated using the proposed algorithm. Therefore, by increasing real-time performance through simple calculation and the boundary of the configuration space, the algorithm proved to be suitable for collision avoidance of aerial vehicles and replanning of local paths.

Correction of Time and Coordinate Systems for Interoperability of Multi-GNSS

  • Kim, Lawoo;Lee, Yu Dam;Lee, Hyung Keun
    • Journal of Positioning, Navigation, and Timing
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    • v.10 no.4
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    • pp.279-289
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    • 2021
  • GNSS receivers capable of tracking multiple Global Navigation Systems (GNSSs) simultaneously are widely used. In order to estimate accurate user position and velocity, it is necessary to consider the key elements that contribute to the interoperability of the different GNSSs. Typical examples are the time system and the coordinate system. Each GNSS is operated based on its own reference time system depending on when the system was developed and whether the leap seconds are applied. In addition, each GNSS is designed based on its own coordinate system based on earth model constant values. This paper addresses the interoperability issues from the viewpoint of Single Point Positioning (SPP) users utilizing multiple GNSS signals from GPS, GLONASS, BeiDou, and Galileo. Since the broadcast ephemerides of each GNSS are based on their own time and coordinate systems, the time and the coordinate systems should be unified for any user algorithm. For this purpose, this paper proposes a method of converting each GNSS coordinate system into the reference coordinate system through Helmert transformation. The error of the broadcast ephemerides was calculated with the precise ephemerides provided by the International GNSS Service (IGS). The effectiveness of the proposed multi-GNSS correction and transformation method is verified using the Multi-GNSS Experiment (MGEX) station data.

Vehicle Reference Dynamics Estimation by Speed and Heading Information Sensed from a Distant Point

  • Yun, Jeonghyeon;Kim, Gyeongmin;Cho, Minhyoung;Park, Byungwoon;Seo, Howon;Kim, Jinsung
    • Journal of Positioning, Navigation, and Timing
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    • v.11 no.3
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    • pp.209-215
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    • 2022
  • As intelligent autonomous driving vehicle development has become a big topic around the world, accurate reference dynamics estimation has been more important than before. Current systems generally use speed and heading information sensed from a distant point as a vehicle reference dynamic, however, the dynamics between different points are not same especially during rotating motions. In order to estimate properly estimate the reference dynamics from the information such as velocity and heading sensed at a point distant from the reference point such as center of gravity, this study proposes estimating reference dynamics from any location in the vehicle by combining the Bicycle and Ackermann models. A test system was constructed by implementing multiple GNSS/INS equipment on an Robot Operating System (ROS) and an actual car. Angle and speed errors of 10° and 0.2 m/s have been reduced to 0.2° and 0.06 m/s after applying the suggested method.

A new experimental protocol to quantitatively assess the motor control capability of low-back pain patinents during dynamic trunk movement

  • Kim, J.Y.
    • Proceedings of the ESK Conference
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    • 1995.10a
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    • pp.156-163
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    • 1995
  • An experimental protocol was developed and tested in this study in order to quantify the motor control capability of the trunk movement for both healthy subjects and low-back pain (LBP) patients. Information processing capacity (bits/second) (Fitts, 1954) and dynamic motor perfor- mance such as flexion/extension velocity and acceleration were measured as motor control parameters under the controlled range of motion (ROM). In this study, the original experimental propocol (Kim et al., 1993, 1994) was re-designed to reduce the length of the test via a series of statistical analyses for clinical application. The accuracy of the shortened protocol was statistically examined and indicated no difference conpared to the original protocol in terms of evaluating information processing capacity. This protocol was also tested among ten healthy subjects and ten LBP patients for validation purpose. The results showed that the information processing capacity was not significantly diffenent between two groups due to the large variation although there was an apparent mean difference. Average movement time showed a significant increase in LBP patients com- pared to healthy subjects. In conclusion, it was found that the new short experimental protocol could quantify the motor control capability of neuromuscular system of the trunk and also showed the applicability to patient population.

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A motion control of robot manipulator by hand glove gesture (손동작 인식 로봇 동작 제어)

  • An, Hyo-min;Lee, Yong-Gyu;Kim, Hyung-Jong;Hyun, Woong-Keun
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.10a
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    • pp.566-569
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    • 2022
  • In this paper, the algorithm was developed to recognize hand golve gesture and implemented a system to remotely control the robot. The system consists of a camera and a controller that controls robot motion by hand position gesture. The camera recognizes the specific color of the glove and outputs the recognized range and position by including the color area of the glove. We recognize the velocity vector of robot motion and control the robot by the output data of the position and the detected rectangle. Through the several experiments, it was confirmed that the robot motion control was successfully performed.

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Methodology for Evaluating Big Data Platforms Performance in the Domestic Electronic Power Industry (국내 전력산업에서의 빅데이터 플랫폼 성과 평가 방법론)

  • Cho, Chisun;Lee, Nangyu;Hahm, Yukun
    • The Journal of Bigdata
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    • v.5 no.1
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    • pp.97-108
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    • 2020
  • As the domestic electric power industry becomes a smart grid, big data platforms for demand management, facility management, and customer service have been deployed. However, due to the nature of the big data project, big data platforms take time to realize their value in the business processes. Therefore, it is not easy to evaluate the performance of the initial big data platforms using the known or theoretical evaluation methods. In this paper, we propose a methodology of big data platform performance evaluation based on specific information quality such as information completeness/sufficiency, information reliability, information relevancy, information comparability, information unbiasedness, timeliness of information, related to the volume, diversity, and velocity of big data.

An Artificial Intelligence Method for the Prediction of Near- and Off-Shore Fish Catch Using Satellite and Numerical Model Data

  • Yoon, You-Jeong;Cho, Subin;Kim, Seoyeon;Kim, Nari;Lee, Soo-Jin;Ahn, Jihye;Lee, Eunjeong;Joh, Seongeok;Lee, Yang-Won
    • Korean Journal of Remote Sensing
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    • v.36 no.1
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    • pp.41-53
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    • 2020
  • The production of near- and off-shore fisheries in South Korea is decreasing due to rapid changes in the fishing environment, particularly including higher sea temperature in recent years. To improve the competitiveness of the fisheries, it is necessary to provide fish catch information that changes spatiotemporally according to the sea state. In this study, artificial intelligence models that predict the CPUE (catch per unit effort) of mackerel, anchovies, and squid (Todarodes pacificus), which are three major fish species in the near- and off-shore areas of South Korea, on a 15-km grid and daily basis were developed. The models were trained and validated using the sea surface temperature, rainfall, relative humidity, pressure,sea surface wind velocity, significant wave height, and salinity as input data, and the fish catch statistics of Suhyup (National Federation of Fisheries Cooperatives) as observed data. The 10-fold blind test results showed that the developed artificial intelligence models exhibited accuracy with a corresponding correlation coefficient of 0.86. It is expected that the fish catch models can be actually operated with high accuracy under various sea conditions if high-quality large-volume data are available.

Onset Time Estimation of P- and S-waves at Gyeongsan Seismic Station Using Akaike Information Criterion (AIC) (Akaike Information Criterion (AIC)를 이용한 경산 지진관측소 P파와 S파 도착시간 자동추정)

  • Kwon, Joa;Kang, Su Young;Kim, Kwang-Hee
    • Journal of the Korean earth science society
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    • v.39 no.6
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    • pp.593-599
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    • 2018
  • The onset times of P- and S-waves are important information to have reliable earthquake locations, 1D or 3D subsurface velocity structures, and other related studies in seismology. As the number of seismic stations increases significantly in recent years, it becomes a formidable task for network operators to pick phase arrivals manually. This study used a simple method to estimate additional P- and S-wave arrival times for local earthquakes when a priori information (event location and time) is available using the Akaike Information Criterion (AIC). We applied the AIC program to the earthquake data recorded at the seismic station located in Gyeongsan (DAG2). The comparisons of automatically estimated phase arrival times with manually picked onset times showed that 95.1% and 93.7% of P-wave and S-wave arrival time estimations, respectively, are less than 0.1 second difference. The higher percentage of agreement presented the method which can be successfully applied to large data sets recorded by high-density seismic arrays.

A Real-Time Stereoscopic Image Conversion Method Based on A Single Frame (단일 프레임 기반의 실시간 입체 영상 변환 방법)

  • Jung Jae-Sung;Cho Hwa-Hyun;Choi Myung-Ryul
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.43 no.1 s.307
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    • pp.45-52
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    • 2006
  • In this paper, a real-time stereoscopic image conversion method using a single frame from a 2-D image is proposed. The Stereoscopic image is generated by creating depth map using vortical position information and parallax processing. For a real-time processing of stereoscopic conversion and reduction of hardware complexity, it uses image sampling, object segmentation by standardizing luminance and depth map generation by boundary scan. The proposed method offers realistic 3-D effect regardless of the direction, velocity and scene conversion of the 2-D image. It offers effective stereoscopic conversion using images suitable conditions assumed in this paper such as recorded image at long distance, landscape and panorama photo because it creates different depth sense using vertical position information from a single frame. The proposed method can be applied to still image because it uses a single frame from a 2-D image. The proposed method has been evaluated using visual test and APD for comparing the stereoscopic image of the proposed method with that of MTD. It is confirmed that stereoscopic images conversed by the proposed method offers 3-D effect regardless of the direction and velocity of the 2-D image.