• Title/Summary/Keyword: location detection

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Display of Irradiation Location of Ultrasonic Beauty Device Using AR Scheme (증강현실 기법을 이용한 초음파 미용기의 조사 위치 표시)

  • Kang, Moon-Ho
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.9
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    • pp.25-31
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    • 2020
  • In this study, for the safe use of a portable ultrasonic skin-beauty device, an android app was developed to show the irradiation locations of focused ultrasound to a user through augmented reality (AR) and enable stable self-surgery. The utility of the app was assessed through testing. While the user is making a facial treatment with the beauty device, the user's face and the ultrasonic irradiation location on the face are detected in real-time with a smart-phone camera. The irradiation location is then indicated on the face image and shown to the user so that excessive ultrasound is not irradiated to the same area during treatment. To this end, ML-Kit is used to detect the user's face landmarks in real-time, and they are compared with a reference face model to estimate the pose of the face, such as rotation and movement. After mounting a LED on the ultrasonic irradiation part of the device and operating the LED during irradiation, the LED light was searched to find the position of the ultrasonic irradiation on the smart-phone screen, and the irradiation position was registered and displayed on the face image based on the estimated face pose. Each task performed in the app was implemented through the thread and the timer, and all tasks were executed within 75 ms. The test results showed that the time taken to register and display 120 ultrasound irradiation positions was less than 25ms, and the display accuracy was within 20mm when the face did not rotate significantly.

Analysis of the under Pavement Cavity Growth Rate using Multi-Channel GPR Equipment (멀티채널 GPR 장비를 이용한 도로하부 공동의 크기 변화 분석)

  • Park, Jeong Jun;Kim, In Dae
    • Journal of the Society of Disaster Information
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    • v.16 no.1
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    • pp.60-69
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    • 2020
  • Purpose: Cavity growth process monitoring is to periodically monitor changes in common size and topography for general and observational grades to predict the rate of common growth. The purpose of this study is to establish a systematic cavity management plan by evaluating the general and observational class community in a non-destructive method. Method: Using GPR exploration equipment, the acquired surface image and the surrounding status image are analyzed in the GPR probe radargram in depth, profile, and cross section of the location. The exact location is selected using the distance and surrounding markings shown on the road surface of the initial detection cavity, and the test cavity is analyzed by calling the radar at the corresponding location. Result: As a result of monitoring tests conducted at a cavity 30 sites of general and observation grade, nine sites have been recovered. Changes in scale were seen in 21 cavity locations, and changes in size and grade occurred in 13 locations. Conclusion: The under road cavity is caused by various causes such as damage to the burial site, poor construction, soil leakage caused by groundwater leakage, waste and ground vibration. Among them, indirect factors could infer the effects of groundwater and localized rainfall.

A RSS-Based Localization for Multiple Modes using Bayesian Compressive Sensing with Path-Loss Estimation (전력 손실 지수 추정 기법과 베이지안 압축 센싱을 이용하는 수신신호 세기 기반의 위치 추정 기법)

  • Ahn, Tae-Joon;Koo, In-Soo
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.12 no.1
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    • pp.29-36
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    • 2012
  • In Wireless Sensor Network(WSN)s, the detection of precise location of each node is essential for utilizing sensing data acquired from sensor nodes effectively. Among various location methods, the received signal strength(RSS) based localization scheme is mostly preferable in many applications because it can be easily implemented without any additional hardware cost. Since a RSS-based localization scheme is mainly affected by radio channel or obstacles such as building and mountain between two nodes, the localization error can be inevitable. To enhance the accuracy of localization in RSS-based localization scheme, a number of RSS measurements are needed, which results in the energy consumption. In this paper, a RSS based localization using Bayesian Compressive Sensing(BSS) with path-loss exponent estimation is proposed to improve the accuracy of localization in the energy-efficient way. In the propose scheme, we can increase the adaptative, reliability and accuracy of localization by estimating the path-loss exponents between nodes, and further we can enhance the energy efficiency by the compressive sensing. Through the simulation, it is shown that the proposed scheme can enhance the location accuracy of multiple unknown nodes with fewer RSS measurements and is robust against the channel variation.

Positive Random Forest based Robust Object Tracking (Positive Random Forest 기반의 강건한 객체 추적)

  • Cho, Yunsub;Jeong, Soowoong;Lee, Sangkeun
    • Journal of the Institute of Electronics and Information Engineers
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    • v.52 no.6
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    • pp.107-116
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    • 2015
  • In compliance with digital device growth, the proliferation of high-tech computers, the availability of high quality and inexpensive video cameras, the demands for automated video analysis is increasing, especially in field of intelligent monitor system, video compression and robot vision. That is why object tracking of computer vision comes into the spotlight. Tracking is the process of locating a moving object over time using a camera. The consideration of object's scale, rotation and shape deformation is the most important thing in robust object tracking. In this paper, we propose a robust object tracking scheme using Random Forest. Specifically, an object detection scheme based on region covariance and ZNCC(zeros mean normalized cross correlation) is adopted for estimating accurate object location. Next, the detected region will be divided into five regions for random forest-based learning. The five regions are verified by random forest. The verified regions are put into the model pool. Finally, the input model is updated for the object location correction when the region does not contain the object. The experiments shows that the proposed method produces better accurate performance with respect to object location than the existing methods.

Speeding Detection and Time by Time Visualization based on Vehicle Trajectory Data

  • Onuean, Athita;Jung, Hanmin
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2018.10a
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    • pp.593-596
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    • 2018
  • The speed of vehicles has remained a significant factor that influences the severity of accidents and traffic accident rate in many parts of the world including South Korea. This behavior where drivers drive at speeds which exceed a posted safe threshold is known as 'speeding'. Over the past twenty years, the Korean National Police Agency (NPA) has become aware of an increased frequency of drivers who are speeding. Therefore, fixed-type ASE systems [1] have been installed on hazardous road sections of many highways. These system monitor vehicle speeds using a camera. However, the use of ASE systems has changed the behavior of the drivers. Specifically, drivers reduce speed or avoid the route where the cameras are mounted. It is not practical to install cameras at every possible location. Therefore, it is challenging to thoroughly explore the location where speeding occurs. In view of these problems, the author of this paper designed and implemented a prototype visualization system in which point and color are used to show vehicle location and associated over-speed information. All of this information was used to create a comprehensive visualization application to show information about vehicle driving. In this paper, we present an approach detecting vehicles moving at speeds which exceed a threshold and visualizing the points those violations occur on a map. This was done using vehicle trajectory data collected in Daegu city. We propose steps for exploring the data collected from those sensors. The resulting mapping has two layers. The first layer contains the dynamic vehicle trajectory data. The second underlying layer contains the static road networks. This allows comparing the speed of vehicles on roads with the known maximum safe speed of those roads, and presents the results with a visualization tool. We also compared data about people who drive over threshold safe speeds on each road on days and weekends based on vehicle trajectories. Finally, our study suggests improved times and locations where law enforcement should use monitoring with speed cameras, and where they should be stricter with traffic law enforcement. We learned that people will drive over the speed limit at midnight more than 1.9 times as often when compared with rush hour traffic at 8 o'clock in the morning, and 4.5 times as often when compared with traffic at 7 o'clock in the evening. Our study can benefit the government by helping them select better locations for installation of speed cameras. This would ultimately reduce police labor in traffic speed enforcement, and also has the potential to improve traffic safety in Daegu city.

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Image Based Damage Detection Method for Composite Panel With Guided Elastic Wave Technique Part I. Damage Localization Algorithm (복합재 패널에서 유도 탄성파를 이용한 이미지 기반 손상탐지 기법 개발 Part I. 손상위치 탐지 알고리즘)

  • Kim, Changsik;Jeon, Yongun;Park, Jungsun;Cho, Jin Yeon
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.49 no.1
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    • pp.1-12
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    • 2021
  • In this paper, a new algorithm is proposed to estimate the damage location in the composite panel by extracting the elastic wave signal reflected from the damaged area. The guided elastic wave is generated by a piezoelectric actuator and sensed by a piezoelectric sensor. The proposed algorithm adopts a diagnostic approach. It compares the non-damaged signal with the damaged signal, and extract damage information along with sensor network and lamb wave group velocity estimated by signal correlation. However, it is difficult to clearly distinguish the damage location due to the nonlinear properties of lamb wave and complex information composed of various signals. To overcome this difficulty, the cumulative summation feature vector algorithm(CSFV) and a visualization technique are newly proposed in this paper. CSFV algorithm finds the center position of the damage by converting the signals reflected from the damage to the area of distance at which signals reach, and visualization technique is applied that expresses feature vectors by multiplying damage indexes. Experiments are performed for a composite panel and comparative study with the existing algorithms is carried out. From the results, it is confirmed that the damage location can be detected by the proposed algorithm with more reliable accuracy.

Onset Date of Forest Canopy Detected from MODIS Leaf Area Index

  • Kim, So-Hee;Kang, Sin-Kyu;Lim, Jong-Hwan
    • Journal of Ecology and Environment
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    • v.31 no.2
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    • pp.153-159
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    • 2008
  • The timing of the canopy phenology onset (CPO hereafter) indicates the initiation of the growing season, with rapid increases in exchange rates of carbon dioxide and water vapor between vegetation and atmosphere. The CPO is regarded as a potential indicator of ecosystem responses to global warming, but the CPO shows considerable spatial variation depending on the species composition and local temperature regime. at a given geographic location. In this study, we evaluated the utility of satellite observation data for detection of the timing of the CPO. Leaf area indices (LAI) obtained from the Moderate Resolution Imaging Spectrora-diometer (MODIS) were utilized to detect and map the onset dates from 2001 to 2006. The reliability of MODIS-based onset dates was evaluated with ground measured cherry blossom flowering data from national weather stations. The MODIS onset dates preceded the observed flowering dates by 8 days and were linearly related with a correlation coefficient of 0.58 (p < 0.05). In spite of the coarse spatial (1 km) and temporal (8 days) resolutions of MODIS LAI, the MODIS-based onset dates showed reasonable ability to predict flowering dates.

A Study on the Signal Propagation Characteristics of Generator Windings (발전기 권선에서의 신호전송 특성에 관한 연구)

  • Hwang, Don-Ha;Kim, Jin-Bong;Kim, Yong-Joo;Park, Myong-Soo;Kim, Taek-Soo
    • Proceedings of the KIEE Conference
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    • 1995.07c
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    • pp.1299-1303
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    • 1995
  • The detection and measurement of partial discharge activity prevalent in the solid insulating systems of high-voltage generator stator windings has, for many years, been a recognized method of assessing the insulation condition of such systems. Partial discharge activity occurs at sites of degradation within, or at the surface of, stator's insulation systems under high voltage stressing. However, partial discharge pulses suffer from attenuation and distortion when transmitted along windings, because of the complex L-C network between windings. The mode of transmission varies with the signal frequency and is dependant on the geometrical configurations of windings. This paper reports the investigated results of the signal propagation characteristics along the windings when both sinusoidal signals and simulated partial discharge pulses are injected at the various positions of stator windings within the 25 MVA, 11 kV hydro generator. The on-line identification technique of partial discharge location in generator windings is also proposed in this study.

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The Development of Vehicle Counting System at Intersection Using Mean Shift (Mean Shift를 이용한 교차로 교통량 측정 시스템 개발)

  • Chun, In-Gook
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.7 no.3
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    • pp.38-47
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    • 2008
  • A vehicle counting system at intersection is designed and implemented using analyzing a video stream from a camera. To separate foreground image from background, we compare three different methods, among which Li's method is chosen. Blobs are extracted from the foreground image using connected component analysis and the blobs are tracked by a blob tracker, frame by frame. The primary tracker use only the size and location of blob in foreground image. If there is a collision between blobs, the mean-shift tracking algorithm based on color distribution of blob is used. The proposed system is tested using real video data at intersection. If some huristics is applied, the system shows a good detection rate and a low error rate.

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Performance Analysis of Hybrid Decode-and-Forward Schemes for 2-hop Wireless Network (2-홉 무선 네트워크를 위한 하이브리드 복호 후 전달 기법의 성능 분석)

  • Kong, Hyung-Yun
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.12A
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    • pp.949-961
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    • 2009
  • This paper analyses BER (Bit Error Rate) performance of 2-hop wireless communications networks with hybrid decode-and-forward (HDF) relays. The conventional HDF method is usually based on the receive signal-to-noise ratio (SNR) for the relay to decide whether to forward the decoded data in order to obviate the erroneous detection at the relay. In contrast, we propose a new solution of using log-likelihood ratio (LLR) as an efficient alternative to SNR. The approximate BER expressions of different HDF schemes are also derived and verified by Monte-Carlo simulations. In addition, we compute the optimum thresholds for HDF schemes. A variety of numerical results demonstrate that the new LLR-based HDF significantly outperforms the SNR-based HDF for any threshold level and relay location under flat Rayleigh fading channel plus AWGN (Additive White Gaussian Noise).