• Journal of information and communication convergence engineering
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• v.6 no.4
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• pp.454-458
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• 2008

It can improve human being's life quality that all people can have more convenient medical service under pervasive computing environment. For a pervasive health care application for diabetes patient, we've implemented a health care system, which is composed of three parts. Various sensors monitor both outer and inner environment of human such as temperature, blood pressure, pulse, and glycemic index, etc. These sensors form zigbee based sensor network. And medical information server accumulates sensing values and performs back-end processing. To simply transfer these sensing values to a medical team is a low level's medical service. So, we've designed a new service model based on back propagation neural network for more improved medical service. Our experiments show that a proposed healthcare system can give high level's medical service because it can recognize human's context more concretely.

• Journal of Power System Engineering
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• v.13 no.1
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• pp.65-71
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• 2009

To address the need for new intelligent sensing, this paper introduces nano sensors made of carbon nanotube (CNT) composites and presents their preliminary experiments. Having smart material properties such as piezoresistivity, chemical and bio selectivity, the nano composite can be used as smart electrodes of the nano sensors. The nano composite sensor can detect structural deterioration, chemical contamination and bio signal by means of its impedance measurement (resistance and capacitance). For a structural application, the change of impedance shows specific patterns depending on the structural deterioration and this characteristic is available for an in-situ multi-functional sensor, which can simultaneously detect multi symptoms of the structure. This study is anticipated to develop a new nano sensor detecting multiple symptoms in structural, chemical and bio applications with simple electric circuits.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.560-564
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• 1999

Burr sensing for burr size measurement and deburring process control is one of the essential elements in an automated deburring procedure. This paper presents the implementation of capacitance sensing and acoustic emission (AE) to deburring. The first application is the "on-line" measurement of burrs using a capacitance sensor. A non-contact capacitance gauging sensor is attached to an ultra precision milling machine which was used as a positioning system. The setup is used to measure burr profiles along machined workpiece edges. The proposed scheme is shown to be accurate, easy to setup, and with minor modifications, readily applicable to automatic deburring processes. As the second example, AE signals were sampled and analyzed for the sensor feedback of a precision deburring process - laser deburring -. The results, such as the sensitivity of AE signals to burr shapes and edge detection capability show a clear correlation between physical process parameters and the AE signals. A subsequent control strategy for deburring automation is also briefly discussed.

• Journal of Multimedia Information System
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• v.2 no.4
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• pp.327-332
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• 2015

Recently, as microcomputers and sensors have been miniaturized due to dropdown of their market rates, this lead to a favorable environment for implementing the Internet of Things. Smart clothing refers to a system which can be wearable or portable, and allows people to communicate or conduct sensing. Applying the Internet of things, the role of the server computer is to receive and process data obtained from the sensor. An ordinary PC can act as a server but during the implementation of IoT, a PC has limited application due to a large size and the inconvenient portability. This study proposes a model that allows a variety of functions while implementation with the server from the sensing using the Arduino and Raspberry Pi. If we apply this proposed model, everyone can easily and inexpensively experience mobile IoT system.

• Journal of information and communication convergence engineering
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• v.7 no.3
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• pp.412-417
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• 2009

With ubiquitous computing aid, it can improve human being's life quality if all people have more convenient medical service under pervasive computing environment. In this paper, for a pervasive health care application for diabetes patient, we've implemented a health care system, which is composed of three parts. Various sensors monitor both outer and inner environment of human such as temperature, blood pressure, pulse, and glycemic index, etc. These sensors form zigbee-based sensor network. And as a backend, medical information server accumulates sensing data and performs back-end processing. To simply transfer these sensing values to a medical team may be a low level's medical service. So, we've designed a model with context awareness for more improved medical service which is based on ART(adaptive resonance theory) neural network. Our experiments show that a proposed healthcare system can provide improved medical service because it can recognize current context of patient more concretely.

• Korean Journal of Remote Sensing
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• v.31 no.4
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• pp.331-336
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• 2015

In this study, a numerical model developed for sunshine duration based on GIS data was used. This model considers blocking caused by topography and buildings and it is properly applicable to evaluation of sunshine duration environment in urban areas. The model reasonably well predicted the solar altitude and azimuth angels, compared to those provided by Korea Astronomy and Space Science Institute (KASI). The developed model was applied to evaluation of sunshine duration environment around the Seonleung Park located near a building-congested area in Seoul. The model well reproduced shadow caused by buildings and/or topography in the numerical domain at 09:00 on August 1, 2015. In addition, the model was applied to finding a suitable measurement sites for pyrheliometer around the Seonleung Park. The model was also usefully applied to finding a suitable site for pyrheliometer in an urban area.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.4
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• pp.53-58
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• 2009

In recently years, the research and application for sensor has increased in each field. In this paper, the system which can perceive and detect using 3-axis accelerometer sensor and serial communication is proposed. Also, the user has GUI environment for monitor in real-time. In order to reduce unstable data and error defect of electronic rechargeable liquid tilt sensor used digital 3-axis accelerometer sensor which has AD convertor. Therefore, this system provide exact data and a problem of objects for user more easier.

• Korean Journal of Remote Sensing
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• v.16 no.2
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• pp.135-143
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• 2000

Ocean Scanning Multispectral Imager (OSMI) is a payload on the Korean Multi-Purpose SATellite (KOMPSAT) to perform global ocean color monitoring for the study of biological oceanography. HOMPSAT was launched 21 December 1999. The radiometric performance of OSMI is analyzed for various gain settings in the viewpoint of the instrument developer for OSMI calibration and application based on its ground performance data measured before launch. The radiometric response linearity and dynamic range are analyzed and the dynamic range is compared with the nominal input radiance for the ocean and the land. The noise equivalent radiance (NER) corresponding to the instrument radiometric noise is compared with the radiometric resolution of signal digitization (1-count equivalent radiance). The best gain setting of OSMI for ocean monitoring is recommended. This analysis is considered to be useful for the OSMI mission and operation planning, the OSMI image data calibration, and users' understanding about OSMI image quality.

• Korean Journal of Remote Sensing
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• v.23 no.5
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• pp.365-373
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• 2007

Car navigation system is a key application in geographic information system and telematics. A recent trend of car navigation system is using real video captured by camera equipped on the vehicle, because video has more representation power about real world than conventional map. In this paper, we suggest a visual car navigation system that visually represents route guidance. It can improve drivers' understanding about real world by capturing real-time video and displaying navigation information overlaid directly on the video. The system integrates real-time data acquisition, conventional route finding and guidance, computer vision, and augmented reality display. We also designed visual navigation controller, which controls other modules and dynamically determines visual representation methods of navigation information according to current location and driving circumstances. We briefly show implementation of the system.

• Korean Journal of Remote Sensing
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• v.22 no.3
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• pp.211-219
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• 2006

A random forests classifier is applied to multi-sensor data fusion for supervised land-cover classification in order to account for the importance of variable. The random forests approach is a non-parametric ensemble classifier based on CART-like trees. The distinguished feature is that the importance of variable can be estimated by randomly permuting the variable of interest in all the out-of-bag samples for each classifier. Two different multi-sensor data sets for supervised classification were used to illustrate the applicability of random forests: one with optical and polarimetric SAR data and the other with multi-temporal Radarsat-l and ENVISAT ASAR data sets. From the experimental results, the random forests approach could extract important variables or bands for land-cover discrimination and showed reasonably good performance in terms of classification accuracy.