• Title/Summary/Keyword: complex sensor data

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Concept Study of Mission Equipment Package Architecture for Korean Attack Helicopter (한국형 공격헬기 임무탑재장비 구조도 개념 연구)

  • Kim, Sung-Woo;Kim, Myung-Chin;Oh, Woo-Seop;Lee, Jong-Hoon;Yim, Jong-Bong
    • Journal of the Korea Institute of Military Science and Technology
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    • v.14 no.4
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    • pp.598-606
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    • 2011
  • The importance of avionics systems has increased to a significant level in modern aircraft development. Modern avionics system is a complex integrated system of state-of-art hardware and software technology. Specifying the avionics system architecture is the most important task throughout the avionics system design process. This paper reviews modern avionics system architectures and proposes an effective avionics architecture suitable for modern attack helicopters.

Temperature and Humidity Monitoring Using Ubiquitous Senor Network in Railway Cabin (철도차량 객실 온습도 USN 모니터링 기술)

  • Kwon, Soon-Bark;Cho, Young-Min;Park, Duck-Shin;Park, Eun-Young;Kim, Se-Young;Jung, Mi-Young
    • Proceedings of the KSR Conference
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    • 2008.06a
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    • pp.948-951
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    • 2008
  • Ubiquitous sensor network (USN) based on ZigBee communication protocol has been used in various application fields, such as home-network, intelligent building and machine, logistics, environmental monitoring, military field, security field and etc. The ZigBee is targeted at radio-frequency application that require a low data rate, long battery life and secure network. Especially, the USN system can be applied efficiently to building-indoor where the complex geometry is adopted. In this study, all 90 points of railway cabin indoor were monitored for temperature and humidity using USN technology. All sensors were pre/post-calibrated and the temperature/humidity change were analyzed in a railway cabin in real-time. The results would be useful to develop the cabin heating, ventilating and air conditing (HVAC) system to meet all passengers' thermal comfort regardless of their seat position.

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Analysis of Volatile Compounds using Electronic Nose and its Application in Food Industry (전자코를 이용한 휘발성분의 분석과 식품에의 이용)

  • Noh, Bong-Soo
    • Korean Journal of Food Science and Technology
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    • v.37 no.6
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    • pp.1048-1064
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    • 2005
  • Detection of specific compounds influencing food flavor quality is not easy. Electronic nose, comprised of electronic chemical sensors with partial specificity and appropriate pattern recognition system, is capable of recognizing simple and complex volatiles. It provides fast analysis with simple and straightforward results and is best suited for quality control and process monitoring of flavor in food industry. This review examines application of electronic nose in food analysis with brief explanation of its principle. Characteristics of different sensors and sensor drift. and solutions to related problems are reviewed. Applications of electronic nose in food industry include monitoring of fermentation process and lipid oxidation, prediction of shelf life, identification of irradiated volatile compounds, discrimination of food material origin, and quality control of food and processing by principal component analysis and neural network analysis. Electronic nose could be useful for quality control in food industry when correlating analytical instrumental data with sensory evaluation results.

A Study on Preprocessing Method in Deep Learning for ICS Cyber Attack Detection (ICS 사이버 공격 탐지를 위한 딥러닝 전처리 방법 연구)

  • Seonghwan Park;Minseok Kim;Eunseo Baek;Junghoon Park
    • Smart Media Journal
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    • v.12 no.11
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    • pp.36-47
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    • 2023
  • Industrial Control System(ICS), which controls facilities at major industrial sites, is increasingly connected to other systems through networks. With this integration and the development of intelligent attacks that can lead to a single external intrusion as a whole system paralysis, the risk and impact of security on industrial control systems are increasing. As a result, research on how to protect and detect cyber attacks is actively underway, and deep learning models in the form of unsupervised learning have achieved a lot, and many abnormal detection technologies based on deep learning are being introduced. In this study, we emphasize the application of preprocessing methodologies to enhance the anomaly detection performance of deep learning models on time series data. The results demonstrate the effectiveness of a Wavelet Transform (WT)-based noise reduction methodology as a preprocessing technique for deep learning-based anomaly detection. Particularly, by incorporating sensor characteristics through clustering, the differential application of the Dual-Tree Complex Wavelet Transform proves to be the most effective approach in improving the detection performance of cyber attacks.

A Study on forest fires Prediction and Detection Algorithm using Intelligent Context-awareness sensor (상황인지 센서를 활용한 지능형 산불 이동 예측 및 탐지 알고리즘에 관한 연구)

  • Kim, Hyeng-jun;Shin, Gyu-young;Woo, Byeong-hun;Koo, Nam-kyoung;Jang, Kyung-sik;Lee, Kang-whan
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.6
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    • pp.1506-1514
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    • 2015
  • In this paper, we proposed a forest fires prediction and detection system. It could provide a situation of fire prediction and detection methods using context awareness sensor. A fire occurs wide range of sensing a fire in a single camera sensor, it is difficult to detect the occurrence of a fire. In this paper, we propose an algorithm for real-time by using a temperature sensor, humidity, Co2, the flame presence information acquired and comparing the data based on multiple conditions, analyze and determine the weighting according to fire in complex situations. In addition, it is possible to differential management of intensive fire detection and prediction for required dividing the state of fire zone. Therefore we propose an algorithm to determine the prediction and detection from the fire parameters as an temperature, humidity, Co2 and the flame in real-time by using a context awareness sensor and also suggest algorithm that provide the path of fire diffusion and service the secure safety zone prediction.

Development of Ubiquitous Sensor Network Intelligent Bridge System (유비쿼터스 센서 네트워크 기반 지능형 교량 시스템 개발)

  • Jo, Byung Wan;Park, Jung Hoon;Yoon, Kwang Won;Kim, Heoun
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.16 no.1
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    • pp.120-130
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    • 2012
  • As long span and complex bridges are constructed often recently, safety estimation became a big issue. Various types of measuring instruments are installed in case of long span bridge. New wireless technologies for long span bridges such as sending information through a gateway at the field or sending it through cables by signal processing the sensing data are applied these days. However, The case of occurred accidents related to bridge in the world have been reported that serious accidents occur due to lack of real-time proactive, intelligent action based on recognition accidents. To solve this problem in this study, the idea of "communication among things", which is the basic method of RFID/USN technology, is applied to the bridge monitoring system. A sensor node module for USN based intelligent bridge system in which sensor are utilized on the bridge and communicates interactively to prevent accidents when it captures the alert signals and urgent events, sends RF wireless signal to the nearest traffic signal to block the traffic and prevent massive accidents, is designed and tested by performing TinyOS based middleware design and sensor test free Space trans-receiving distance.

Comparative Study of GPS-Integrated Concrete Supply Management using Discrete Event Simulation

  • Zekavat, Payam Rahnamayie;Mortaheb, Mohammad Mehdi;Han, Sangwon;Bernold, Leonhard
    • Journal of Construction Engineering and Project Management
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    • v.4 no.2
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    • pp.31-40
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    • 2014
  • The management of vehicular supply of "perishable" construction material, such as concrete mixes, faces a series of uncertainties such as weather, daily traffic patterns and accidents. Presented in this paper is a logistics control model for managing a hauling fleet with interrelated processes at both ends and queue capacities. Discrete event simulation is used to model the complex interactions of production units and the randomness of the real world. Two alternative strategies for ready mix concrete delivery, with and without an off-site waiting queue, are studied to compare supply performance. Secondly, the paper discusses the effect of an agent-based GPS tracking system providing real-time travel data that lessens the uncertainty of trucking time. The results show that the combination of GPS information with off-site queuing reduces productivity loss and process wastes of concrete placement as well as the idleness of supply trucks when crew or pump experience an unexpected stoppage.

Grinding robot system for car brazing bead

  • Kang, Hyo-Sik;Lee, Woo-Ho;Park, Jong-Oh;Lee, Gwang-Se;Shin, Hyoun-Oh
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10b
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    • pp.160-163
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    • 1993
  • In this paper, design of an automatic grinding robot system for car brazing bead is introduced. Car roof and side panels are joined using brazing, and then the brazing bead is processed so that the bead is invisible after painting. Up to now the grinding process is accomplished manually. The difficulties in automation of the grinding process are induced by variation of position and shape of the bead and non-uniformity of the grinding area due to surface deformation. For each car, the grinding area including the brazing bead is sensed and then modeled using a 2-D optical sensor system. Using these model data, the position and the direction of discrete points on the car, body surface are obtained to produce grinding path for a 6 degrees of freedom grinding robot. During the process, it is necessary to sense the reaction forces continuously to prepare for the unexpected circumstances. In addition, to meet the line cycle time it is necessary to reduce the required time in sensing, signal processing, modeling, path planning and data transfer by utilizing real-time communication of the information. The key technique in the communication and integration of the complex information is obtaining in-field reliability. This automatic grinding robot system may be regarded as a jump in the intelligent robot processing technique.

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Process and Location-aware Information Service System for the Disabled and the Elderly (장애인과 고령자를 위한 시공간 상황인식 기반의 정보서비스 제공 시스템)

  • Han, Man-Chul;Kim, Gun-Hee;Park, Hyun-Chul;Kim, Lae-Hyun;Ha, Sung-Do;Park, Se-Hyung
    • 한국HCI학회:학술대회논문집
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    • 2009.02a
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    • pp.295-300
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    • 2009
  • This paper presents a context-aware information service system in public places that have complex processes, for the disabled and the elderly. The system infers context of a user which is derived from the user's demand, then it informs to the user -what to do, where to go-according to the context. Our system gets user's context from sensor data and informations from the local information system. The system provides more suitable information with a knowledge model, which organizes location and process data coordinately. The information is provided personally to the user, with mobile devices.

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Fuzzy Logic Based Auto Navigation System Using Dual Rule Evaluation Structure for Improving Driving Ability of a Mobile Robot (모바일 로봇의 주행 능력 향상을 위한 이중 룰 평가 구조의 퍼지 기반 자율 주행 알고리즘)

  • Park, Kiwon
    • Journal of Korea Multimedia Society
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    • v.18 no.3
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    • pp.387-400
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    • 2015
  • A fuzzy logic based mobile robot navigation system was developed to improve the driving ability without trapping inside obstacles in complex terrains, which is one of the most concerns in robot navigation in unknown terrains. The navigation system utilizes the data from ultrasonic sensors to recognize the distances from obstacles and the position information from a GPS sensor. The fuzzy navigation system has two groups of behavior rules, and the robot chooses one of them based on the information from sensors while navigating for the targets. In plain terrains the robot with the proposed algorithm uses one rule group consisting of behavior rules for avoiding obstacle, target steering, and following edge of obstacle. Once trap is detected the robot uses the other rule group consisting of behavior rules strengthened for following edge of obstacle. The output signals from navigation system control the speed of two wheels of the robot through the fuzzy logic data process. The test was conducted in the Matlab based mobile robot simulator developed in this study, and the results show that escaping ability from obstacle is improved.