• Title/Summary/Keyword: location detection

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A study of Web map investigation for the risk recognition (위험 인지를 위한 웹 지도 탐색 연구)

  • Park, Sangjoon;Lee, Jongchan
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2019.05a
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    • pp.171-172
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    • 2019
  • In this paper, we consider the dynamic method for the searching development of Web map to the monitoring object in the risk environments. It is to recognize the real-time detection to the risk situation based on the location monitoring mechanism of management to the object movement.

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Characteristic features of fungus ball in the maxillary sinus and the location of intralesional calcifications on computed tomographic images: A report of 2 cases

  • Lee, Jae-Hoon;Lee, Byung-Do
    • Imaging Science in Dentistry
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    • v.50 no.4
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    • pp.377-384
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    • 2020
  • This report presents 2 cases of sinus fungus ball and describes the characteristic radiographic features of fungus ball in the maxillary sinus. Two female patients, aged 62 and 40 years, sought consultations at a dental hospital for the treatment of dental implants and tooth pain, respectively. Panoramic radiography and small field-of-view(FOV) cone-beam computed tomography (CBCT) did not provide detailed information for the radiographic diagnosis of fungus ball due to the limited images of the maxillary sinus. Additional paranasal sinus computed tomographic images showed the characteristic features of fungus ball, such as heterogeneous opacification and intralesional calcification of the maxillary sinus. The calcified materials of the fungus balls were located in the middle and superior regions of the maxillary sinus. It is necessary to use large-FOV CBCT for the detection of calcified materials in the upper maxillary sinus to confirm the diagnosis of fungus ball.

Fast and Precise: How to Measure Meiotic Crossovers in Arabidopsis

  • Kim, Heejin;Choi, Kyuha
    • Molecules and Cells
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    • v.45 no.5
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    • pp.273-283
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    • 2022
  • During meiosis, homologous chromosomes (homologs) pair and undergo genetic recombination via assembly and disassembly of the synaptonemal complex. Meiotic recombination is initiated by excess formation of DNA double-strand breaks (DSBs), among which a subset are repaired by reciprocal genetic exchange, called crossovers (COs). COs generate genetic variations across generations, profoundly affecting genetic diversity and breeding. At least one CO between homologs is essential for the first meiotic chromosome segregation, but generally only one and fewer than three inter-homolog COs occur in plants. CO frequency and distribution are biased along chromosomes, suppressed in centromeres, and controlled by pro-CO, anti-CO, and epigenetic factors. Accurate and high-throughput detection of COs is important for our understanding of CO formation and chromosome behavior. Here, we review advanced approaches that enable precise measurement of the location, frequency, and genomic landscapes of COs in plants, with a focus on Arabidopsis thaliana.

Structural damage detection based on changes of wavelet transform coefficients of correlation functions

  • Sadeghian, Mohsen;Esfandiari, Akbar;Fadavie Manochehr
    • Structural Monitoring and Maintenance
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    • v.9 no.2
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    • pp.157-177
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    • 2022
  • In this paper, an innovative finite element updating method is presented based on the variation wavelet transform coefficients of Auto/cross-correlations function (WTCF). The Quasi-linear sensitivity of the wavelet coefficients of the WTCF concerning the structural parameters is evaluated based on incomplete measured structural responses. The proposed algorithm is used to estimate the structural parameters of truss and plate models. By the solution of the sensitivity equation through the least-squares method, the finite element model of the structure is updated for estimation of the location and severity of structural damages simultaneously. Several damage scenarios have been considered for the studied structure. The parameter estimation results prove the high accuracy of the method considering measurement and mass modeling errors.

A Study on the Human Detection and Location Estimation for ATV Type Search Robot Based on Variable Wheel (가변형 휠 기반의 ATV형 수색 로봇을 위한 얼굴 검출과 위치 추정에 관한 연구)

  • Park, Sung-Hyun;Jung, Hye-Won;Yoo, Hye-Bin;Park, Myeong-Suk;Kim, Sang-Hoon
    • Annual Conference of KIPS
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    • 2020.11a
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    • pp.1060-1063
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    • 2020
  • 본 논문은 가변형 휠을 이용한 이동방식과 로봇 내부에서의 얼굴 검출과 위치 추정에 관한 연구이다. 임베디드 시스템에서 딥러닝을 이용한 얼굴 검출을 구현하기 위해 SSD에 기반을 둔 객체 검출 알고리즘을 사용하였으며, 로봇이 이동하면서 PID 제어를 통해 주행을 제어하고 이를 기반으로 상대적 위치 추정을 수행한다. 본 로봇은 수색 작업뿐만 아니라 더 나아가 구조 및 정찰의 용도로 발전할 수 있을 것으로 예상한다.

Estimation of a Gaze Point in 3D Coordinates using Human Head Pose (휴먼 헤드포즈 정보를 이용한 3차원 공간 내 응시점 추정)

  • Shin, Chae-Rim;Yun, Sang-Seok
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.177-179
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    • 2021
  • This paper proposes a method of estimating location of a target point at which an interactive robot gazes in an indoor space. RGB images are extracted from low-cost web-cams, user head pose is obtained from the face detection (Openface) module, and geometric configurations are applied to estimate the user's gaze direction in the 3D space. The coordinates of the target point at which the user stares are finally measured through the correlation between the estimated gaze direction and the plane on the table plane.

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Structural Damage Localization for Visual Inspection Using Unmanned Aerial Vehicle with Building Information Modeling Information (UAV와 BIM 정보를 활용한 시설물 외관 손상의 위치 측정 방법)

  • Lee, Yong-Ju;Park, Man-Woo
    • Journal of KIBIM
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    • v.13 no.4
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    • pp.64-73
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    • 2023
  • This study introduces a method of estimating the 3D coordinates of structural damage from the detection results of visual inspection provided in 2D image coordinates using sensing data of UAV and 3D shape information of BIM. This estimation process takes place in a virtual space and utilizes the BIM model, so it is possible to immediately identify which member of the structure the estimated location corresponds to. Difference from conventional structural damage localization methods that require 3D scanning or additional sensor attachment, it is a method that can be applied locally and rapidly. Measurement accuracy was calculated through the distance difference between the measured position measured by TLS (Terrestrial Laser Scanner) and the estimated position calculated by the method proposed in this study, which can determine the applicability of this study and the direction of future research.

A Comparison of Deep Learning Models for IQ Fingerprint Map Based Indoor Positioning in Ship Environments

  • Yootae Shin;Qianfeng Lin;Jooyoung Son
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.4
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    • pp.1122-1140
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    • 2024
  • The importance of indoor positioning has grown in numerous application areas such as emergency response, logistics, and industrial automation. In ships, indoor positioning is also needed to provide services to passengers on board. Due to the complex structure and dynamic nature of ship environments, conventional positioning techniques have limitations in providing accurate positions. Compared to other indoor positioning technologies, Bluetooth 5.1-based indoor positioning technology is highly suitable for ship environments. Bluetooth 5.1 attains centimeter-level positioning accuracy by collecting In-phase and Quadrature (IQ) samples from wireless signals. However, distorted IQ samples can lead to significant errors in the final estimated position. Therefore, we propose an indoor positioning method for ships that utilizes a Deep Neural Network (DNN) combined with IQ fingerprint maps to overcome the challenges associated with accurate location detection within the ship. The results indicate that the accuracy of our proposed method can reach up to 97.76%.

Voronoi Diagram-based USBL Outlier Rejection for AUV Localization

  • Hyeonmin Sim;Hangil Joe
    • Journal of Ocean Engineering and Technology
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    • v.38 no.3
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    • pp.115-123
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    • 2024
  • USBL systems are essential for providing accurate positions of autonomous underwater vehicles (AUVs). On the other hand, the accuracy can be degraded by outliers because of the environmental conditions. A failure to address these outliers can significantly impact the reliability of underwater localization and navigation systems. This paper proposes a novel outlier rejection algorithm for AUV localization using Voronoi diagrams and query point calculation. The Voronoi diagram divides data space into Voronoi cells that center on ultra-short baseline (USBL) data, and the calculated query point determines if the corresponding USBL data is an inlier. This study conducted experiments acquiring GPS and USBL data simultaneously and optimized the algorithm empirically based on the acquired data. In addition, the proposed method was applied to a sensor fusion algorithm to verify its effectiveness, resulting in improved pose estimations. The proposed method can be applied to various sensor fusion algorithms as a preprocess and could be used for outlier rejection for other 2D-based location sensors.

Worker Accountability in Computer Vision for Construction Productivity Measurement: A Systematic Review

  • Mik Wanul KHOSIIN;Jacob J. LIN;Chuin-Shan CHEN
    • International conference on construction engineering and project management
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    • 2024.07a
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    • pp.775-782
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    • 2024
  • This systematic review comprehensively analyzes the application of computer vision in construction productivity measurement and emphasizes the importance of worker accountability in construction sites. It identifies a significant gap in the connection level between input (resources) and output data (products or progress) of productivity monitoring, a factor not adequately addressed in prior research. The review highlights three fundamental groups: input, output, and connection groups. Object detection, tracking, pose, and activity recognition, as the input stage, are essential for identifying characteristics and worker movements. The output phase will mostly focus on progress monitoring, and understanding the interaction of workers with other entities will be discussed in the connection groups. This study offers four research future research directions for the worker accountability monitoring process, such as human-object interaction (HOI), generative AI, location-based management systems (LBMS), and robotic technologies. The successful accountability monitoring will secure the accuracy of productivity measurement and elevate the competitiveness of the construction industry.