• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.870-872
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• 2007

Sensor networks have been widely applied for data collection. Due to the energy limitation of the sensor nodes and the most energy consuming data transmission, we should allocate as much work as possible to the sensors, such as data compression and aggregation, to reduce data transmission and save energy. Querying extreme values is a general query type in wireless sensor networks. In this paper, we propose a novel querying method called Two-Level Filter (TLF) for querying extreme values in wireless sensor networks. We first divide the whole sensor network into domains using the Distributed Data Aggregation Model (DDAM). The sensor nodes report their data to the cluster heads using push method. The advantages of two-level filter lie in two aspects. When querying extreme values, the number of pull operations has the lower boundary. And the query results are less affected by the topology changes of the wireless sensor network. Through this method, the sensors preprocess the data to share the burden of the base station and it combines push and pull to be more energy efficient.

• Journal of Digital Contents Society
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• v.15 no.2
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• pp.167-172
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• 2014

As there are few documents about how to design and implement a sensor network with Z-Stack, developers can get information from developer's community on Internet. That takes longer time to develop the network. This paper presents how to design and implement a range measuring sensor network with Z-Stack's Generic application and ultrasonic sensors based on CC2530, and then show experimental results through the implemented network. This work will make less time for a developer to implement a sensor network with Z-Stack.

• Journal of Sensor Science and Technology
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• v.3 no.2
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• pp.24-32
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• 1994

A force sensor of 30 MN capacity using build-up technique in which three load cells of 10 MN capacity are arranged in parallel was fabricated. A column spring element was adopted as a shape of a strain gage type load cell. Temperature compensation circuits were used to reduce the error of a load cell. It was estimated that the total error of the fabricated force sensor is less than 0.1 %. The force sensor may be used to calibrate or test material testing machines above 4.5 MN capacity in industries.

• Journal of the Korean Society for Precision Engineering
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• v.9 no.1
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• pp.29-33
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• 1992

A non-contact torque sensor was developed using amorphous alloy. The change of maixmum magnetic induction of C0-based amorphous alloy under the tensile and compressive stress was proportional to applied torque. For the construction of the torque sensor, a glass fiber reinforced-epoxy rod was used as shaft. The amorphous strips were attached on the epoxy shaft in the direction of $+45^{\circ}$and $-45^{\circ}$. The magnetizing coil and 2 sensing coil was installed. The static and dynamic test was carried out. The linearity and sensor hysteresis of the torque sensor was less than 1%.

• The KSFM Journal of Fluid Machinery
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• v.13 no.2
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• pp.54-58
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• 2010

The most recent, Vacuum Pipeline for Waste Collecting System, to collect MSW(Municipal Solid Waste) efficiently, is used environmental preservative, to emit less air pollution, in New City. However, it is difficult to monitor broken pipe and filled mass of Waste, because Vacuum Pipeline is laid underground. Therefore, FBG, optical fiber sensor, is used to inspect the temperature change and longitudinal strain to take proper action for unusual situation. I have need to accumlate sensor data of district control. I hope to be used Vacuum Pipeline more than 30 years in New City.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2002.10a
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• pp.161-164
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• 2002

Optical fiber vibrations sensors (OFVSs) and extrinsic Fabry-Perot interferometer (EFPI) were used in damage monitoring of fiber-metal laminates(FML). The optical fiber vibration sensor and EFPI were applied in order to detect and evaluate the strain, damage and failure of FML. Damages in composites, such as matrix cracks, delamination and fiber breakage may occur as a result of excessive load, fatigue and low-velocity impacts. Tensile test was performed with the measurement of optical signal and acoustic emission (AE). The signals of the optical fiber vibration sensor due to damages were quantitatively evaluated by wavelet transform. EFPI was less sensible to the damage signals compared with the optical fiber vibration sensor. It was found that damage information of comparable in quality to acoustic emission data could be obtained from the optical fiber vibration sensor signals.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2003.10a
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• pp.154-157
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• 2003

Precision displacement of less than a few nm resolution was measured in real-time using fiber optic EFPI sensor. The novel method for real-time processing of analyzing EFPI output signal was developed and verified. Linearity in the mean values of interferometric light intensity among adjacent fringes was shown, and the sinusoidal approximation algorithm that estimates past and coming fringe values was verified through the linearity. Real-time signal processing program was developed, and the intensity signal of the EFPI sensor was transformed to the phase shift with this program. The resolution below 0.4 ~ 10 nm in the displacement range of $0 ~ 300\mu\textrm{m}$ was obtained by reducing the photodetector noise using low-pass filter and signal averaging. The nano-translation stage with a Piezo-electric actuator and the EFPI sensor system was designed and tested. This stage successfully reached to the desired destination in $15\mu\textrm{m}$ range within 1 nm accuracy.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.99-101
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• 2006

Auto-Cross Correlated time series (ACTS) model was constructed by using the backpropagation neural network. The performance of ACTS model was evaluated with sensor information collected from a large volume, industrial plasma-enhanced chemical vapor deposition system. A total of 18 sensor information were collected. The effect of inclusion of past and future information were examined. For all but three sensor information with a large data variance demonstrated a prediction error less than 3%. By integrating ACTS model into equipment software, process quality can be more stringently monitored while improving device throughput.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.102-104
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• 2006

Auto-Correlated time series (ATS) model was constructed by using the backpropagation neural network. The performance of ATS model was evaluated with sensor information collected from a large volume, industrial plasma-enhanced chemical vapor deposition system. A total of 18 sensor information were collected. The effect of inclusion of past and future information were examined. For all but three sensor information with a large data variance demonstrated a prediction error less than 4%. By integrating ATS model into equipment software, process quality can be more stringently monitored while improving device throughput.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.433-435
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• 2007

Geographic wireless sensor networks use position information for Greedy routing. Greedy routing works well in dense network where as in sparse network it may fail and require the use of recovery algorithms. Recovery algorithms help the packet to get out of the communication void. However, these algorithms are generally costlier for resource constrained position based wireless sensor type networks. In the present work, we propose a Void Avoidance Algorithm (VAA); a novel idea based on virtual distance upgrading that allows wireless sensor nodes to remove all stuck nodes by transforming the routing graph and forward packet using greedy routing only without recovery algorithm. In VAA, the stuck node upgrades distance unless it finds next hop node which is closer to the destination than itself. VAA guarantees the packet delivery if there is a topologically valid path exists. NS-2 is used to evaluate the performance and correctness of VAA and compared the performance with GPSR. Simulation results show that our proposed algorithm achieves higher delivery ratio, lower energy consumption and efficient path.