• 제목/요약/키워드: sensing time

검색결과 2,598건 처리시간 0.032초

Change Detection in Land-Cover Pattern Using Region Growing Segmentation and Fuzzy Classification

  • Lee Sang-Hoon
    • 대한원격탐사학회지
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    • 제21권1호
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    • pp.83-89
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    • 2005
  • This study utilized a spatial region growing segmentation and a classification using fuzzy membership vectors to detect the changes in the images observed at different dates. Consider two co-registered images of the same scene, and one image is supposed to have the class map of the scene at the observation time. The method performs the unsupervised segmentation and the fuzzy classification for the other image, and then detects the changes in the scene by examining the changes in the fuzzy membership vectors of the segmented regions in the classification procedure. The algorithm was evaluated with simulated images and then applied to a real scene of the Korean Peninsula using the KOMPSAT-l EOC images. In the expertments, the proposed method showed a great performance for detecting changes in land-cover.

Detection of Moving Direction using PIR Sensors and Deep Learning Algorithm

  • Woo, Jiyoung;Yun, Jaeseok
    • 한국컴퓨터정보학회논문지
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    • 제24권3호
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    • pp.11-17
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    • 2019
  • In this paper, we propose a method to recognize the moving direction in the indoor environment by using the sensing system equipped with passive infrared (PIR) sensors and a deep learning algorithm. A PIR sensor generates a signal that can be distinguished according to the direction of movement of the user. A sensing system with four PIR sensors deployed by $45^{\circ}$ increments is developed and installed in the ceiling of the room. The PIR sensor signals from 6 users with 10-time experiments for 8 directions were collected. We extracted the raw data sets and performed experiments varying the number of sensors fed into the deep learning algorithm. The proposed sensing system using deep learning algorithm can recognize the users' moving direction by 99.2 %. In addition, with only one PIR senor, the recognition accuracy reaches 98.4%.

Cloud computing for handling data from traffic sensing technologies and on-board diagnostics

  • Nkenyereye, Lionel;Jang, Jong-wook
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2014년도 추계학술대회
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    • pp.488-491
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    • 2014
  • Based on a complete understanding research in Information and Communication Technologies (ICT), the Intelligent Transport Systems rapidly build up innovative applications to ensure real time attainment as well remote management of driven information, provide a huge range of services and involve many actors in automotive ecosystem. In this paper, we present an intelligent cloud computing for handling data received from traffic sensing technologies. Transportations technologies applied in ITS have played a great role in collecting data from devices deployed in vehicles and highway infrastructures utilizing broadband wireless technologies to the Cloud. In order to facilitate the interested in automotive industry to use data collected and afford services to the car's owner, a scalable acquisition, access to computing resources and offered services are the primary goal of the proposed cloud computing.

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자율주행 셔틀버스의 통신 정보 융합 기반 충돌 위험 판단 알고리즘 개발 (Development of I2V Communication-based Collision Risk Decision Algorithm for Autonomous Shuttle Bus)

  • 이승민;이창형;박만복
    • 자동차안전학회지
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    • 제11권3호
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    • pp.19-29
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    • 2019
  • Recently, autonomous vehicles have been studied actively. Autonomous vehicles can detect objects around them using their on board sensors, estimate collision probability and maneuver to avoid colliding with objects. Many algorithms are suggested to prevent collision avoidance. However there are limitations of complex and diverse environments because algorithm uses only the information of attached environmental sensors and mainly depends on TTC (time-to-Collision) parameter. In this paper, autonomous driving algorithm using I2V communication-based cooperative sensing information is developed to cope with complex and diverse environments through sensor fusion of objects information from infrastructure camera and object information from equipped sensors. The cooperative sensing based autonomous driving algorithm is implemented in autonomous shuttle bus and the proposed algorithm proved to be able to improve the autonomous navigation technology effectively.

Periodic Biometric Information Collection Interface Method for Wearable Vulnerable Users

  • Lee, Taegyu
    • International journal of advanced smart convergence
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    • 제10권3호
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    • pp.33-40
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    • 2021
  • Recently, wearable computers equipped with various biosensors such as smart watches, smart bands, and smart patches that support daily health management of users as well as patients have been released. Users of wearable computers such as smart watches face various difficulties in performing biometric information processes such as data sensing, collection, transmission, real-time analysis, and feedback in a weak wireless and mobile biometric information service environment. In particular, the biometric information collection interface is an important basic process that determines the quality and performance of the entire biometric information service. So far, research has focused on sensing hardware and logic. This study intensively considers the interface method for effectively sensing and collecting raw biometric information. In particular, the process of collecting biometric information is designed and analyzed from the perspective of periodicity. Therefore, we propose an efficient and stable periodic collection method.

Flexible biosensors based on field-effect transistors and multi-electrode arrays: a review

  • Kim, Ju-Hwan;Park, Je-Won;Han, Dong-Jun;Park, Dong-Wook
    • Journal of Semiconductor Engineering
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    • 제1권3호
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    • pp.88-98
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    • 2020
  • As biosensors are widely used in the medical field, flexible devices compatible with live animals have aroused great interest. Especially, significant research has been carried out to develop implantable or skin-attachable devices for real-time bio-signal sensing. From the device point of view, various biosensor types such as field-effect transistors (FETs) and multi-electrode arrays (MEAs) have been reported as diverse sensing strategies. In particular, the flexible FETs and MEAs allow semiconductor engineering to expand its application, which had been impossible with stiff devices and materials. This review summarizes the state-of-the-art research on flexible FET and MEA biosensors focusing on their materials, structures, sensing targets, and methods.

온도감응형 인광물질을 이용한 온도장 및 열변형 동시 계측 기법 개발 (Development of a multi-sensing technique for temperature and strain field of high-temperature using thermographic phosphors)

  • 임유진;염은섭
    • 한국가시화정보학회지
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    • 제19권3호
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    • pp.77-83
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    • 2021
  • Solid oxide fuel cell (SOFC) operates at high temperatures in range of 600-800℃. Since layers of SOFC are composed of different substances, different thermal expansion in SOFC can result in defects under high temperature conditions. For understanding relation between temperature field and the thermal deformation in SOFC, temperature and strain field were simultaneously estimated using thermographic phosphors by optical measurement. Temperature fields were obtained by the life-time method, and the temperature differences of one specimen was checked with thermocouple. The thermal deformation was estimated by digital image correlation (DIC) method with extracted phosphorescence images. To investigate the deformation accuracy of DIC measurement, thermographic phosphors were coated with and without grid pattern on aluminum surface. Simultaneous measurement of temperature fields and thermal deformation were carried out for YSZ. This study will be helpful to multi-sensing of temperature field and thermal deformation on SOFC cells.

5(6)-Carboxyflurescein을 담지한 인지질 리포좀의 제조 및 박테리아 센싱 능력 평가에 대한 연구 (A Study on the Preparation of 5(6)-Carboxyflurescein-supported Phospholipid Liposomes and Evaluation of Bacterial Sensing Ability)

  • 한민호;전재우;이준영;신은숙;김우진;김삼수
    • 한국염색가공학회지
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    • 제33권4호
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    • pp.338-347
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    • 2021
  • In the case of occlusive dressings currently used in dressings for burn treatment, it is impossible to confirm the replacement time, so replacement is delayed, resulting in additional infection. To solve this problem, liposomes capable of bacterial sensing were prepared using 5(6)-Carboxyfluorescein, Phosphatidylcholine, 1,2-Dipalmitoyl-sn-glycero-3-phosphocholine, Cholesterol, and 10,12-Tricosadiynoic acid. In this study, evaluation of changes in drug encapsulation rate in liposomes according to changes in three types of phosphatidylcholine phospholipids during liposome production, high-performance phosphatidylcholine phospholipids selected through vesicle size analysis, low and high temperature stability evaluation, bacterial sensitization ability evaluation, animals cell responses were assessed.

자동 절단과 부하 감응 제어 기술을 적용한 양날 도로절단기 개발 (Development of a Double-blades Road Cutter with Automatic Cutting and Load Sensing Control Technology)

  • 서명국;강명철;박종호;김영진
    • 드라이브 ㆍ 컨트롤
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    • 제21권1호
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    • pp.53-58
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    • 2024
  • With the recent development of intelligence and automation technologies for construction machinery, the demand for safety and efficiency of road-cutting operations has continued to increase. In response to this, a double-blade road cutter has been developed that can automatically cut roads. However, a double-blade road cutter has a load difference between the two blades due to the ground and wear conditions of the cutting blades. The difference in load between the two blades distorts the direction of travel of the cutter. In this study, a vision sensor-based driving guide technology was developed to correct the driving path of road cutters. In addition, we developed a load-sensing technology that detects blade loads in real-time and controls driving speed in the event of overload.

도시 빅데이터: 모바일 센싱 데이터를 활용한 도시 계획을 위한 사회 비용 분석 (Urban Big Data: Social Costs Analysis for Urban Planning with Crowd-sourced Mobile Sensing Data)

  • 신동윤
    • 한국BIM학회 논문집
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    • 제13권4호
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    • pp.106-114
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    • 2023
  • In this study, we developed a method to quantify urban social costs using mobile sensing data, providing a novel approach to urban planning. By collecting and analyzing extensive mobile data over time, we transformed travel patterns into measurable social costs. Our findings highlight the effectiveness of big data in urban planning, revealing key correlations between transportation modes and their associated social costs. This research not only advances the use of mobile data in urban planning but also suggests new directions for future studies to enhance data collection and analysis methods.