• Journal of Ubiquitous Convergence Technology
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• v.2 no.2
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• pp.78-87
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• 2008

Received signal strength indicator (RSSI) is used as one of the ranging techniques to locate dynamic sensor nodes in wireless sensor network. Before it can be used for position estimation, RSSI values must be converted to distances using path loss model. These distances among sensor nodes are combined using trilateration method to find position. This paper presents an idea which attempts to integrate both path loss model and trilateration as one algorithm without going through RSSI-distance conversion. This means it is not simply formulas combination but a whole new model was developed. Several advantages were found after integration: it is able to reduce processing load, and ensure that all values do not exceed the maximum range of 16-bit signed or unsigned numbers due to antilog operation in path loss model. The results also show that this method is able to reduce estimation error while inaccurate environmental parameters are used for RSSI-distance conversion.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.546-549
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• 2005

It is evident that advancement of ubiquitous technologies in the near future guarantees more convenient and plentiful living. With regarding to car life, we dream of an automatic driving without any effort of operation. This paper touches the realization issue, a convergence of wireless sensor network and Telematics specializing on an information routing mechanism between participating components in Telematics sensor communication network. We list up new requirements of wireless sensor network deployed for Telematics services. Then context-aware routing architecture is proposed in order to solve these constraints, in which a network topology for routing can be dynamically configured according to the combination of context models of network components.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.725-727
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• 2010

For simulation of Boat motion, pitch, motion element of roll and yaw direction could simulated. The combination of the marine use various multi sensor surveillance system technology with the development of servo motion control algorithm and gyro sensor in six freedom motion is implemented to analyze the movement response. The stabilization of the motion control is developed and Nano driving Precision Pan-Tilt/Gimbal system is obtained from the security positioning cameras with ultra high speed device is used to carry out the exact behavior of the device.

• 한국신재생에너지학회:학술대회논문집
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• 2010.06a
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• pp.51.3-51.3
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• 2010

Due to the recent public awareness of global warming and sustainable economic growth, there has been a growing interest in alternative clean energy sources. Hydrogen is considered as a clean fuel for the next generation. One of the technical challenges related to the use of hydrogen is safe monitoring of the hydrogen leak during separation, purification and transportation. For detecting various gases, chemiresistor-type gas sensors have been widely studied and used due to their well-established detection scheme and low cost. However, it is known that many of them have the limited sensitivity and slow response time, when used at low temperature conditions. In our work, a sensor based on Schottky barriers at the electrode/sensing material interface showed promising results that can be utilized for developing fast and highly sensitive gas sensors. Our hydrogen sensor was designed and fabricated based on indium oxide (In2O3)-doped tin oxide (SnO2) semiconductor nanoparticles with platinum (Pt) nanoclusters in combination with interdigitated electrodes. The sensor showed the sensitivity as high as $10^7%$ (Rair/Rgas) and the detection limit as low as 30 ppm. The sensor characteristics could be obtained via optimized materials synthesis route and sensor electrode design. Not only the contribution of electrical resistance from the film itself but also the interfacial effect was identified as an important factor that contribute significantly to the overall sensor characteristics. This promises the applicability of the developed sensor for monitoring hydrogen leak at room temperature.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.35 no.8
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• pp.123-130
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• 2019

Recently, it is required to develop a monitoring technology that combines an FBG sensor as a means for continuously monitoring whether reinforcing effect of FRP is maintained on FRP reinforced structural members. However, most existing researches focus on the insertion of FBG sensors into bar-shaped FRPs, and there is insufficient study on the details strip-type FRPs combined with FBG sensors. Therefore, in this paper, it is studied to develop a reinforcement in which a FBG sensor is combined with a FRP strip. Especially, combination of FRP and FBG sensor. For this, a series of experiments were performed to find the adhesive strength of fiber-FRP-epoxy joints, the tensile strength of FBG sensor part with reflection-lattice, and the performance depending on the connection method of FRF and FBG sensor. As a result of the study, it was found that a minimum strength of $216.15N/mm^2$ is required for incorporating FBG sensors in FRP using epoxy. It is considered that the adhesion length of epoxy joints should be more than 50mm. When the FBG sensor is attached to the FRP strip as an epoxy, it is considered appropriate to use the complete attachment and the sensor non-attachment method.

• Journal of Broadcast Engineering
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• v.17 no.3
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• pp.447-458
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• 2012

We present a method to recognize hand gestures using skeletal joint data obtained from Microsoft's Kinect sensor. We propose a combination feature of multi-angle histograms robust to orientation variations to represent the observation sequence of skeletons. The proposed feature efficiently represents the orientation variations of gestures that can be occurred according to person or environment by combining the multiple angle histograms with various angular-quantization levels. The gesture represented as combination of multi-angle histograms and random decision forest classifier improve the recognition performance. We conduct the experiments in hand gesture dataset obtained from a kinect sensor and show that our method outperforms the other methods by comparing the recognition performance.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1393-1395
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• 2003

In this research, we presented a data integration, which integrates ultra high resolution images and complementary data for 3D building reconstruction. In our method, as the ultra high resolution image, Three Line Sensor (TLS) images are used in combination with 2D digital maps, DSMs and both of them. Reconstructed 3D buildings, correctness rate and the accuracy of results were presented. As a result, optimized combination scheme of data sets , sensors and methods was proposed.

• The Journal of Korea Robotics Society
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• v.5 no.4
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• pp.294-301
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• 2010

In order to produce a convenient robot for the aged and the lower limb disabled, it is needed for the research detecting implicit walking intention and controlling robot by a user's intention. In this study, we developed sensor module system to control the walking- assist robot using FSR sensor and tilt sensor, and analyzed the signals being acquired from two sensors. The sensor module system consisted of the assist device control unit, communication unit by wire/wireless, information collection unit, information operation unit, and information processing PC which handles integrated processing of assist device control. The FSR sensors attached user's the palm and the soles of foot are sensing force/pressure signals from these areas and are used for detecting the walking intention and states. The tilt sensor acquires roll and pitch signal from area of vertebrae lumbales and reflects the pose of the upper limb. We could recognize the more detailed user's walking intention such as 'start walking', 'start of right or left foot forward', and 'stop walking' by the combination of FSR and tilt signals can recognize.

• Smart Structures and Systems
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• v.17 no.6
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• pp.1031-1053
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• 2016

The health conditions of in-service civil infrastructures can be evaluated by employing structural health monitoring technology. A reliable health evaluation result depends heavily on the quality of the data collected from the structural monitoring sensor network. Hence, the problem of sensor fault diagnosis has gained considerable attention in recent years. In this paper, an innovative sensor fault diagnosis method that focuses on fault detection and isolation stages has been proposed. The dynamic or auto-regressive characteristic is firstly utilized to build a multivariable statistical model that measures the correlations of the currently collected structural responses and the future possible ones in combination with the canonical correlation analysis. Two different fault detection statistics are then defined based on the above multivariable statistical model for deciding whether a fault or failure occurred in the sensor network. After that, two corresponding fault isolation indices are deduced through the contribution analysis methodology to identify the faulty sensor. Case studies, using a benchmark structure developed for bridge health monitoring, are considered in the research and demonstrate the superiority of the new proposed sensor fault diagnosis method over the traditional principal component analysis-based and the dynamic principal component analysis-based methods.

• ETRI Journal
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• v.45 no.4
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• pp.570-580
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• 2023

Sensor nodes are the most significant part of a wireless sensor network that offers a powerful combination of sensing, processing, and communication. One major challenge while designing a sensor node is power consumption, as sensor nodes are generally battery-operated. In this study, we proposed the design of a low-power, long range-based wireless sensor node with flexibility, a compact size, and energy efficiency. Furthermore, we improved power performance by adopting an efficient hardware design and proper component selection. The Nano Power Timer Integrated Circuit is used for power management, as it consumes nanoamps of current, resulting in improved battery life. The proposed design achieves an off-time current of 38.17309 nA, which is tiny compared with the design discussed in the existing literature. Battery life is estimated for spreading factors (SFs), ranging from SF7 to SF12. The achieved battery life is 2.54 years for SF12 and 3.94 years for SF7. We present the analysis of current consumption and battery life. Sensor data, received signal strength indicator, and signal-to-noise ratio are visualized using the ThingSpeak network.