• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.960-965
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• 2006

Privacy and security are latent problems in pervasive healthcare system. For the sake of protecting health monitoring information, it is necessary to classify and categorize the various contexts in terms of obfuscation. In this paper, we propose the physiological context categorization and specification methodology by exploiting data fusion network for automatic context alignment. In addition, we introduce the methodologies for making various level of physiological context on the context aware application model, which is wear-UCAM. This physiological context has several layers of context according to the level of abstraction such as user-friendly level or parametric level. This mechanism facilitates a user to restrict access to his/her monitoring results based on the level of details in context.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2008.04c
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• pp.98-102
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• 2008

Methods and analysis of a simple wireless sensor concept for detecting and locating faults as well as for load monitoring are presented. The concept is based on distributed wireless sensors that are attached to the incoming and outgoing power lines of secondary substations. A sensor measures only phase current characteristics of the wire it is attached to, is not synchronized to other sensors and does not need configuration of triggering levels. The main novelty of the concept is in detecting and locating faults by combining power distribution network characteristics on system level with low power sampling methods for individual sensors. This concept enables the sensor design to be simple, energy efficient and thus applicable in new installations and for retrofit purposes in both overhead and underground electrical distribution systems.

• Proceedings of the Korean Society of Crop Science Conference
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• 2006.04a
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• pp.40-54
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• 2006

It's not easy to detect the high quality and functional compounds for control quality of food materials. The electronic nose was an instrument, which comprised of an array of electronic chemical sensors with partial specificity and an appropriate pattern recognition system, capable of recognizing simple or complex odors. It can conduct fast analysis and provide simple and straightforward results and is best suited for quality control and process monitoring in the field of functional foods. Numbers of applications of an electronic nose in the functional food industry include discrimination of habitats for medicinal food materials, monitoring storage process, lipid oxidation, and quality control of food and/or processing with principal component analysis, neural network analysis and the electronic nose based on GC-SAW sensor. The electronic nose would be possibly useful for a wide variety of quality control in the functional food and plant cultivation when correlating traditional analytical instrumental data with sensory evaluation results or electronic nose data.

• Annual Conference of KIPS
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• 2005.05a
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• pp.1409-1412
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• 2005

무선 센서 네트워크는 교량 안전진단(Structural Health Monitoring, SHM)을 위한 효율성, 신뢰성 등의 특징들을 제공한다. 그러나 현재 교량 안전진단은 아날로그 센서를 이용하여 데이터를 수집하고, 유선망을 사용하여 관리프로그램으로 전송하고 있다. 본 논문에서는 무선망에서 동작하는 센서 네트워크를 이용하여 교량 및 노면을 모니터링하기 위한 안전진단 시스템을 구현하였다.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.6
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• pp.1089-1096
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• 2019

Recently, small-scale IoT services using a small amount of information through low-performance computing have been spread. It requires low cost, low-power, and long-distance communication technologies with wide communication radius, relatively low power consumption. This paper proposes a MAC layer and routing protocol that supports multi-hop transmission in small-scale IoT environment distributed over a large area based on LoRa communication and delivering a small amount of sensing data. The terminal node is mobile and the communication type provides bidirectional transmission between the terminal node and the network application server. By applying the proposed protocol, a production line monitoring system for smart factory was implemented. It was confirmed that the basic monitoring functions are normally performed.

• The Journal of the Acoustical Society of Korea
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• v.42 no.5
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• pp.395-401
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• 2023

Sound Event Detection (SED) aims to identify not only sound category but also time interval for target sounds in an audio waveform. It is a critical technique in field of acoustic surveillance system and monitoring system. Recently, various models have introduced through Detection and Classification of Acoustic Scenes and Events (DCASE) Task 4. This paper explored how to design optimal parameters of DenseNet based model, which has led to outstanding performance in other recognition system. In experiment, DenseRNN as an SED model consists of DensNet-BC and bi-directional Gated Recurrent Units (GRU). This model is trained with Mean teacher model. With an event-based f-score, evaluation is performed depending on parameters, related to model architecture as well as model training, under the assessment protocol of DCASE task4. Experimental result shows that the performance goes up and has been saturated to near the best. Also, DenseRNN would be trained more effectively without dropout technique.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.11
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• pp.2736-2744
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• 2013

In this paper, we present a Smart Water Treatment Plant using Zigbee USN devices and a real-time monitoring system in K-water Flow Meter Calibration Center Building. For verification, the data of vertical type WTP such as flow rate, pressure, water level and water temperature are obtained by the Zigbee USN devices, operating in 2.45 GHz band, and be wirelessly surveilled by the real-time monitoring system. The received data from the sensor is transmitted to the data processing device, and then the processed data can be monitored on a smart phone. Consequently, the pilot plant based on the low-cost and high-efficiency USN has been developed with the performance analysis for the communication network and remote monitoring system on mobile devices.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.364-366
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• 2017

Unlike general ships, offshore plants require high reliability due to their long operating time at fixed positions when they are operated. Sensor-based status information is required for user and maintenance worker to ensure safety. In this paper, we propose a monitoring system for safety diagnosis and inspection of cargo lift for offshore plant. It consists of a sensor unit mounted on the cargo Lift, an embedded system measurement unit, and a monitoring unit for real-time data verification. It is based on the ship standard network IEC 61162-450 for the exchange of operating information and sensor measurement information in accordance with the upgrading and integration of equipment in maritime.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.9
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• pp.2087-2092
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• 2015

Recently, use of the heat transferring machine and systems has been increasing in various industrial fields. A key technique for constructing such process is basically to measuring temperature directly to objects established on industrial plants. Particularly, a non-contact temperature measurement is very important to realize advanced heat transferring systems. This paper presents a new measurement methodology for temperature by using USN(ubiquitous sensor networks) technique including the microprocessor unit based ZigBee communication systems. This proposed system is made to be applied in monitoring systems for non-contact temperature measurement. We designed firmware based measurement systems whose main function is to save s series of temperature data sets and send it to main monitoring systems.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.16-21
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• 2008

Aero-engine, as one kind of rotating machinery with complex structure and high rotating speed, has complicated vibration faults. Therefore, condition monitoring and fault diagnosis system is very important for airplane security. In this paper, a vibration data acquisition and intelligent fault diagnosis system is introduced. First, the vibration data acquisition part is described in detail. This part consists of hardware acquisition modules and software analysis modules which can realize real-time data acquisition and analysis, off-line data analysis, trend analysis, fault simulation and graphical result display. The acquisition vibration data are prepared for the following intelligent fault diagnosis. Secondly, two advanced artificial intelligent(AI) methods, mapping-based and rule-based, are discussed. One is artificial neural network(ANN) which is an ideal tool for aero-engine fault diagnosis and has strong ability to learn complex nonlinear functions. The other is data mining, another AI method, has advantages of discovering knowledge from massive data and automatically extracting diagnostic rules. Thirdly, lots of historical data are used for training the ANN and extracting rules by data mining. Then, real-time data are input into the trained ANN for mapping-based fault diagnosis. At the same time, extracted rules are revised by expert experience and used for rule-based fault diagnosis. From the results of the experiments, the conclusion is obvious that both the two AI methods are effective on aero-engine vibration fault diagnosis, while each of them has its individual quality. The whole system can be developed in local vibration monitoring and real-time fault diagnosis for aero-engine.