• Title/Summary/Keyword: precise monitoring

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Use of an Optical Scanning Device to Monitor the Progress of Noninvasive Treatments for Chest Wall Deformity: A Pilot Study

  • Kelly, Robert E. Jr.;Obermeyer, Robert J.;Kuhn, M. Ann;Frantz, Frazier W.;Obeid, Mohammad F.;Kidane, Nahom;McKenzie, Frederic D.
    • Journal of Chest Surgery
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    • v.51 no.6
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    • pp.390-394
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    • 2018
  • Background: The nonsurgical treatment of chest wall deformity by a vacuum bell or external brace is gradual, with correction taking place over months. Monitoring the progress of nonsurgical treatment of chest wall deformity has relied on the ancient methods of measuring the depth of the excavatum and the protrusion of the carinatum. Patients, who are often adolescent, may become discouraged and abandon treatment. Methods: Optical scanning was utilized before and after the intervention to assess the effectiveness of treatment. The device measured the change in chest shape at each visit. In this pilot study, patients were included if they were willing to undergo scanning before and after treatment. Both surgical and nonsurgical treatment results were assessed. Results: Scanning was successful in 7 patients. Optical scanning allowed a visually clear, precise assessment of treatment, whether by operation, vacuum bell (for pectus excavatum), or external compression brace (for pectus carinatum). Millimeter-scale differences were identified and presented graphically to patients and families. Conclusion: Optical scanning with the digital subtraction of images obtained months apart allows a comparison of chest shape before and after treatment. For nonsurgical, gradual methods, this allows the patient to more easily appreciate progress. We speculate that this will increase adherence to these methods in adolescent patients.

Liquid Biopsy: Current Status and Future Perspective in Gastric Cancer and Helicobacter Infection (액체 생검(Liquid Biopsy): 위암 및 헬리코박터 감염증에서 적응과 전망)

  • Kang, Eun A;Han, Young Min;Park, Jong Min;Yoo, In Kyung;Hong, Sung Pyo;Hahm, Ki Baik
    • The Korean journal of helicobacter and upper gastrointestinal research
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    • v.18 no.3
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    • pp.150-156
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    • 2018
  • Precision medicine stands for 4Ps - precise, preventive, participatory, and personal; in which "precision" is important because the current modern medicine starts from "trial and error," and "one does not fit all". Current targeted therapies for cancer have changed treatment approaches and led the precision medicine; however, clinical use of liquid biopsy, using blood or other liquid specimens to characterize circulating tumor cells (CTC) or tumor genes instead of biopsies of tumor tissues, still awaits availability of more information regarding non-invasive cancer detection and characterization, prediction of treatment response, monitoring the disease course and relapse possibilities, identification of mechanisms of drug resistance, and newer pathogenesis. In this review, we will introduce the basic concept of CTC, circulating cell free DNA, and exosomes and their possible application for gastric cancer relevant with Helicobacter pylori infection.

Design and Implementation of OPC-Based Intelligent Precision Servo Control Power Forming Press System (OPC 기반의 지능형 정밀 서보제어 분말성형 프레스 시스템의 설계 및 구현)

  • Yoo, Nam-Hyun
    • The Journal of the Korea institute of electronic communication sciences
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    • v.13 no.6
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    • pp.1243-1248
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    • 2018
  • Metal Powder Metallurgy is a manufacturing technology that makes unique model parts or a certain type of product by using a hardening phenomenon when a powder of metal or metal oxide is put it into a mold and compression-molded by a press and then heated and sintered at a high temperature. Powder metallurgical press equipment is mainly used to make the parts of automobile, electronic parts and so on, and most of them are manufactured using precise servo motor. The intelligent precision servo control powder molding press system which is designed and implemented in this paper has advantages of lowering the price and maintaining the precision by using the mechanical camshaft for the upper ram part and precisely controlling the lower ram part using the high precision servo system. In addition, OPC-based monitoring and process data collection systems are designed and implemented to provide scalability that can be applied to smart manufacturing management systems that utilize Big Data in the future.

Multi-constellation Local-area Differential GNSS for Unmanned Explorations in the Polar Regions

  • Kim, Dongwoo;Kim, Minchan;Lee, Jinsil;Lee, Jiyun
    • Journal of Positioning, Navigation, and Timing
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    • v.8 no.2
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    • pp.79-85
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    • 2019
  • The mission tasks of polar exploration utilizing unmanned systems such as glacier monitoring, ecosystem research, and inland exploration have been expanded. To facilitate unmanned exploration mission tasks, precise and robust navigation systems are required. However, limitations on the utilization of satellite navigation system are present due to satellite orbital characteristics at the polar region located in a high latitude. The orbital inclination of global positioning system (GPS), which was developed to be utilized in mid-latitude sites, was designed at $55^{\circ}$. This means that as the user is located in higher latitudes, the satellite visibility and vertical precision become worse. In addition, the use of satellite-based wide-area augmentation system (SBAS) is also limited in higher latitude regions than the maximum latitude of signal reception by stationary satellites, which is $70^{\circ}$. This study proposes a local-area augmentation system that additionally utilizes Global Navigation Satellite System (GLONASS) considering satellite navigation system environment in Polar Regions. The orbital inclination of GLONASS is $64.8^{\circ}$, which is suitable in order to ensure satellite visibility in high-latitude regions. In contrast, GLONASS has different system operation elements such as configuration elements of navigation message and update cycle and has a statistically different signal error level around 4 m, which is larger than that of GPS. Thus, such system characteristics must be taken into consideration to ensure data integrity and monitor GLONASS signal fault. This study took GLONASS system characteristics and performance into consideration to improve previously developed fault detection algorithm in the local-area augmentation system based on GPS. In addition, real GNSS observation data were acquired from the receivers installed at the Antarctic King Sejong Station to analyze positioning accuracy and calculate test statistics of the fault monitors. Finally, this study analyzed the satellite visibility of GPS/GLONASS-based local-area augmentation system in Polar Regions and conducted performance evaluations through simulations.

Detection of Levee Displacement and Estimation of Vulnerability of Levee Using Remote Sening (원격탐사를 이용한 하천 제방 변위량 측정과 취약지점 선별)

  • Bang, Young Jun;Jung, Hyo Jun;Lee, Seung Oh
    • Journal of Korean Society of Disaster and Security
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    • v.14 no.1
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    • pp.41-50
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    • 2021
  • As a method of predicting the displacement of river levee in advance, Differential Interferometry (D-InSAR) kind of InSAR techniques was used to identify weak points in the area of the levee collapes near Gumgok Bridge (Somjin River) in Namwon City, which occurred in the summer of 2020. As a result of analyzing the displacement using five images each in the spring and summer of 2020, the Variation Index (V) of area where the collapse occurred was larger than that of the other areas, so the prognostic sysmptoms was detected. If the levee monitoring system is realized by analyzing the correlations with displacement results and hydrometeorological factors, it will overcome the existing limitations of system and advance ultra-precise, automated river levee maintenance technology and improve national disaster management.

Characterizing Spatiotemporal Variations and Mass Balance of CO2 in a Stratified Reservoir using CE-QUAL-W2 (CE-QUAL-W2를 이용한 성층 저수지에서 CO2의 시공간적 분포 및 물질수지 분석)

  • Park, Hyungseok;Chung, Sewoong
    • Journal of Korean Society on Water Environment
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    • v.36 no.6
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    • pp.508-520
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    • 2020
  • Dam reservoirs have been reported to contribute significantly to global carbon emissions, but unlike natural lakes, there is considerable uncertainty in calculating carbon emissions due to the complex of emission pathways. In particular, the method of calculating carbon dioxide (CO2) net atmospheric flux (NAF) based on a simple gas exchange theory from sporadic data has limitations in explaining the spatiotemporal variations in the CO2 flux in stratified reservoirs. This study was aimed to analyze the spatial and temporal CO2 distribution and mass balance in Daecheong Reservoir, located in the mid-latitude monsoon climate zone, by applying a two-dimensional hydrodynamic and water quality model (CE-QUAL-W2). Simulation results showed that the Daecheong Reservoir is a heterotrophic system in which CO2 is supersaturated as a whole and releases CO2 to the atmosphere. Spatially, CO2 emissions were greater in the lacustrine zone than in the riverine and transition zones. In terms of time, CO2 emissions changed dynamically according to the temporal stratification structure of the reservoir and temporal variations of algae biomass. CO2 emissions were greater at night than during the day and were seasonally greatest in winter. The CO2 NAF calculated by the CE-QUAL-W2 model and the gas exchange theory showed a similar range, but there was a difference in the point of occurrence of the peak value. The findings provide useful information to improve the quantification of CO2 emissions from reservoirs. In order to reduce the uncertainty in the estimation of reservoir carbon emissions, more precise monitoring in time and space is required.

A Study on the Development of a Infusion Pump based on an Active Muscle Pump (능동형 근육펌프 구조의 수액 주입 펌프 개발에 관한 연구)

  • Lee, Jeong-Whan;Lee, Sang-Yeob;Lee, Jung-Eun;Ahn, Ihn-Seok
    • Journal of the Korean Society of Industry Convergence
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    • v.25 no.3
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    • pp.443-449
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    • 2022
  • In this study, in order to improve the disadvantages of the environmental error of the infusion set that performs infusion therapy in the existing clinical practice and to maximize the user's convenience by miniaturizing the existing infusion pump system, the structure of the muscle pump of the human vein was imitated. As a double check valve method, a method for preventing the backflow of fluid and discharging a constant fluid in one direction by external pressure was proposed. The proposed bio-mimic muscle pump uses a check valve that controls the flow of fluid in one direction and a silicone tube with elasticity, and a chamber is constructed. A peristaltic pump for applying intermittent pressure to the tube chamber was constructed using a multi-cam structure roller. In order to verify the performance of the proposed pump, optimization was performed while changing the number of multi-cam rollers and adjusting the speed of the roller driving motor, and the reproducibility of the instantaneous discharge amount and the continuous discharge amount of the pump was compared and tested. The performance of the muscle pump proposed in this study was verified through experiments that it can inject up to 1L of fluid within 12 hours, and that it is possible to inject the fluid with an accuracy of ±0.1ml. Real-time monitoring of the fluid injection volume through the bio-mimic muscle pump proposed in this study not only increases the convenience of the administrator, but also provides a precise fluid administration environment to more patients at a low cost, and additionally applies bubble detection and occlusion detection technology If so, it is believed that a safer medical environment can be provided to patients.

Automated Water Surface Extraction in Satellite Images Using a Comprehensive Water Database Collection and Water Index Analysis

  • Anisa Nur Utami;Taejung Kim
    • Korean Journal of Remote Sensing
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    • v.39 no.4
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    • pp.425-440
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    • 2023
  • Monitoring water surface has become one of the most prominent areas of research in addressing environmental challenges.Accurate and automated detection of watersurface in remote sensing imagesis crucial for disaster prevention, urban planning, and water resource management, particularly for a country where water plays a vital role in human life. However, achieving precise detection poses challenges. Previous studies have explored different approaches,such as analyzing water indexes, like normalized difference water index (NDWI) derived from satellite imagery's visible or infrared bands and using k-means clustering analysis to identify land cover patterns and segment regions based on similar attributes. Nonetheless, challenges persist, notably distinguishing between waterspectralsignatures and cloud shadow or terrain shadow. In thisstudy, our objective is to enhance the precision of water surface detection by constructing a comprehensive water database (DB) using existing digital and land cover maps. This database serves as an initial assumption for automated water index analysis. We utilized 1:5,000 and 1:25,000 digital maps of Korea to extract water surface, specifically rivers, lakes, and reservoirs. Additionally, the 1:50,000 and 1:5,000 land cover maps of Korea aided in the extraction process. Our research demonstrates the effectiveness of utilizing a water DB product as our first approach for efficient water surface extraction from satellite images, complemented by our second and third approachesinvolving NDWI analysis and k-means analysis. The image segmentation and binary mask methods were employed for image analysis during the water extraction process. To evaluate the accuracy of our approach, we conducted two assessments using reference and ground truth data that we made during this research. Visual interpretation involved comparing our results with the global surface water (GSW) mask 60 m resolution, revealing significant improvements in quality and resolution. Additionally, accuracy assessment measures, including an overall accuracy of 90% and kappa values exceeding 0.8, further support the efficacy of our methodology. In conclusion, thisstudy'sresults demonstrate enhanced extraction quality and resolution. Through comprehensive assessment, our approach proves effective in achieving high accuracy in delineating watersurfaces from satellite images.

AprilTag and Stereo Visual Inertial Odometry (A-SVIO) based Mobile Assets Localization at Indoor Construction Sites

  • Khalid, Rabia;Khan, Muhammad;Anjum, Sharjeel;Park, Junsung;Lee, Doyeop;Park, Chansik
    • International conference on construction engineering and project management
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    • 2022.06a
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    • pp.344-352
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    • 2022
  • Accurate indoor localization of construction workers and mobile assets is essential in safety management. Existing positioning methods based on GPS, wireless, vision, or sensor based RTLS are erroneous or expensive in large-scale indoor environments. Tightly coupled sensor fusion mitigates these limitations. This research paper proposes a state-of-the-art positioning methodology, addressing the existing limitations, by integrating Stereo Visual Inertial Odometry (SVIO) with fiducial landmarks called AprilTags. SVIO determines the relative position of the moving assets or workers from the initial starting point. This relative position is transformed to an absolute position when AprilTag placed at various entry points is decoded. The proposed solution is tested on the NVIDIA ISAAC SIM virtual environment, where the trajectory of the indoor moving forklift is estimated. The results show accurate localization of the moving asset within any indoor or underground environment. The system can be utilized in various use cases to increase productivity and improve safety at construction sites, contributing towards 1) indoor monitoring of man machinery coactivity for collision avoidance and 2) precise real-time knowledge of who is doing what and where.

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Assessing Stream Vegetation Dynamics and Revetment Impact Using Time-Series RGB UAV Images and ResNeXt101 CNNs

  • Seung-Hwan Go;Kyeong-Soo Jeong;Jong-Hwa Park
    • Korean Journal of Remote Sensing
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    • v.40 no.1
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    • pp.9-18
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    • 2024
  • Small streams, despite their rich ecosystems, face challenges in vegetation assessment due to the limitations of traditional, time-consuming methods. This study presents a groundbreaking approach, combining unmanned aerial vehicles(UAVs), convolutional neural networks(CNNs), and the vegetation differential vegetation index (VDVI), to revolutionize both assessment and management of stream vegetation. Focusing on Idong Stream in South Korea (2.7 km long, 2.34 km2 basin area)with eight diverse revetment methods, we leveraged high-resolution RGB images captured by UAVs across five dates (July-December). These images trained a ResNeXt101 CNN model, achieving an impressive 89% accuracy in classifying vegetation cover(soil,water, and vegetation). This enabled detailed spatial and temporal analysis of vegetation distribution. Further, VDVI calculations on classified vegetation areas allowed assessment of vegetation vitality. Our key findings showcase the power of this approach:(a) TheCNN model generated highly accurate cover maps, facilitating precise monitoring of vegetation changes overtime and space. (b) August displayed the highest average VDVI(0.24), indicating peak vegetation growth crucial for stabilizing streambanks and resisting flow. (c) Different revetment methods impacted vegetation vitality. Fieldstone sections exhibited initial high vitality followed by decline due to leaf browning. Block-type sections and the control group showed a gradual decline after peak growth. Interestingly, the "H environment block" exhibited minimal change, suggesting potential benefits for specific ecological functions.(d) Despite initial differences, all sections converged in vegetation distribution trends after 15 years due to the influence of surrounding vegetation. This study demonstrates the immense potential of UAV-based remote sensing and CNNs for revolutionizing small-stream vegetation assessment and management. By providing high-resolution, temporally detailed data, this approach offers distinct advantages over traditional methods, ultimately benefiting both the environment and surrounding communities through informed decision-making for improved stream health and ecological conservation.