• Journal of Sensor Science and Technology
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• v.23 no.1
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• pp.42-45
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• 2014

Recently, tremendous application utilizing electrospun nanofibers have been actively reported due to its several advantages, such as high surface to volume ratio, simple fabrication and high-throughput manufacturing. In this paper, we developed highly sensitive and consistent nanofiber humidity sensor by electrospinning. The humidity sensor was fabricated by rapid electrospinning (~2 sec) $TiO_2$/PVP/LiCl mixed solution on the micro-interdigitated electrode. In order to evaluate the humidity sensing performances, we measured current response using DC bias voltage under various relative humidity levels. The results show fast response / recovery time and marginal hysteresis as well as long-term stability. In addition, with the aid of micro-interdigitated electrode, we can reduce a total resistance of the sensor and increase the total reaction area of nanofibers across the electrodes resulting in high sensitivity and enhanced current level. Therefore, we expect that the electrospun nanofiber array for humidity sensor can be feasible and promising for diverse humidity sensing application.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.571-574
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• 2008

In this paper, we propose $256{\times}256$ pixel array fingerprint sensor with an advanced circuits for detecting. The pixel level simple detection circuit converts from a small and variable sensing current to binary voltage out effectively. We minimizes an electrostatic discharge(ESD) influence by applying an effective isolation structure. The sensor circuit blocks were designed and simulated in standard CMOS $0.35{\mu}m$ process. Full custom layout is performed in the unit sensor pixel and auto placement and routing is performed in the full chip.

• Journal of Sensor Science and Technology
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• v.17 no.4
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• pp.295-302
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• 2008

$TiO_2,\;ZrO_2$, and $SiO_2$ were added in the concentration of 1 - 3 wt.% to improve long-term stability for the $SnO2$ thick film gas sensor. Short-term sensor resistances up to 90 h were measured to investigate the stabilization time of initial resistance in air. Long-term resistance drifts in air and in gas to 5000 ppm methane for the sensors annealed at $750^{\circ}C$ for 1 h and continuously heated at an operating temperature of $400^{\circ}C$ were also measured up to 90 days at an interval of 1 day. The long-term drifts in methane sensitivity for the three metal oxide-doped $SnO2$ sensors are closely related to methane sensitivity level, catalytic activity, and long-term drift in sensor resistance in air. Those stabilities are mainly discussed in terms of oxidation state and catalytic activity.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.10
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• pp.2257-2264
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• 2011

Sensor nodes in Wireless sensor network have limited resources and consume almost all energy to the communication. For its traffic feature as a burst traffic type toward a sink node, it has high probability to network congestion. Network congestion causes packet drops and retransmission of dropped packets draws energy consumption. In particular, the loss of packet that is from the sensor node far away from a sink node requires additional energy consumption by frequent retransmission. This paper presents a traffic control mechanism that determines packet transfer by considering priority of packet and congestion level as well as hop count. Analysis of proposed mechanism by simulation demonstrated that it improved energy efficiency.

• Journal of Korea Society of Digital Industry and Information Management
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• v.4 no.2
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• pp.29-37
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• 2008

Clustering allows hierarchical structures to be built on the nodes and enables more efficient use of scarce resources, such as frequency spectrum, bandwidth, and energy in wireless sensor networks (WSNs). This paper proposes a hierarchical clustering algorithm called EEHC which is more energy efficient than existing algorithms for WSNs, It introduces region node selection as well as cluster head election based on the residual battery capacity of nodes to reduce the costs of managing sensor nodes and of the communication among them. The role of cluster heads or region nodes is rotated among nodes to achieve load balancing and extend the lifetime of every individual sensor node. To do this, EEHC clusters periodically to select cluster heads that are richer in residual energy level, compared to the other nodes, according to clustering policies from administrators. To prove the performance improvement of EEHC, the ns-2 simulator was used. The results show that it can reduce the energy and bandwidth consumption for organizing and managing WSNs comparing it with existing algorithms.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.5
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• pp.151-156
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• 2013

The experiment was done on cars travelling at the speeds of 20km/h, 60km/h and 100km/h using the performance testing mode for chassis dynamometer. In this experiment, the relativity between the secondary waveform coming from ignition coil and exhaust emissions were measured in case of cars with failures, in oxygen sensor, spark plugs. The following results obtained by analysis of the relativity between the secondary waveform and exhaust emissions. 1) When the oxygen sensor is failure, the average value of CO emission measured was 6.8 times higher than the standard CO emission value and the average value of HC emission measured was 2.3 times higher than the standard emission level. 2) When engine parts are in failure, more fuel enters the cylinder due to longer opening duration of injector, and it tended to make CO and HC emission values increase. 3) Combustion duration, the shape of flame propagation during spark line, and the size of the discharge-induced energy were the three main elements that directly cause variations in CO and HC emission values.

• Journal of Forest and Environmental Science
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• v.29 no.2
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• pp.131-137
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• 2013

This study attempts to classify forest species using hyperspectral data for supporting resources management. The primary dataset used was AISA sensor. The sensor was mounted onboard the NOMAD GAF-27 aircraft at 2,000 m altitude creating a 2 m spatial resolution on the ground. Pre-processing was carried out with CALIGEO software, which automatically corrects for both geometric and radiometric distortions of the raw image data. The radiance data set was then converted to at-sensor reflectance derived from the FODIS sensor. Spectral Angle Mapper (SAM) technique was used for image classification. The spectra libraries for tree species were established after confirming the appropriate match between field spectra and pixel spectra. Results showed that the highest spectral signature in NIR range were Kembang Semangkok (Scaphium macropodum), followed by Meranti Sarang Punai (Shorea parvifolia) and Chengal (Neobalanocarpus hemii). Meanwhile, the lowest spectral response were Kasai (Pometia pinnata), Kelat (Eugenia spp.) and Merawan (Hopea beccariana), respectively. The overall accuracy obtained was 79%. Although the accuracy of SAM techniques is below the expectation level, SAM classifier was able to classify tropical tree species. In future it is believe that the most effective way of ground data collection is to use the ground object that has the strongest response to sensor for more significant tree signatures.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.3
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• pp.531-536
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• 2009

In this paper, we propose $256{\times}256$ pixel array fingerprint sensor with an advanced circuits for detecting. The pixel level simple detection circuit converts from a small and variable sensing current to binary voltage out effectively. We minimizes an electrostatic discharge(ESD) influence by applying an effective isolation structure around the unit pixel. The sensor circuit blocks were designed and simulated in standard CMOS $0.35{\mu}m$ process. Full custom layout is performed in the unit sensor pixel and auto placement and routing is performed in the full chip.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.26 no.8
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• pp.351-356
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• 2014

Typical trouble patterns in solar thermal systems include working fluid leakage and freezing other than breakdown of pump. A fluid sensor for measuring electric resistance of fluid was developed and installed at the top of the collector piping in order to check the fault of solar system. Working fluid level in the pipe was determined by measuring electric resistance from a fluid sensor. On the base of this, it was confirmed that the fluid sensor diagnoses leakage of fluid. Electric resistance of propylene glycol aqueous solution was measured in the range of $0{\sim}70^{\circ}C$ and 0~40% of concentration. The response surface analysis was performed by using a central composite design, and the regression equation was derived from the relationship between electric resistance, temperature, and concentration. Through the experiment in a real solar system, we can estimate a concentration of working fluid when a pump is not operating and predict a possibility of freezing. Finally, an effective algorithm for trouble shooting was proposed to operate and maintain the solar system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.944-946
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• 2014

Localization of a sensor network node using machine learning has been recently studied. It is easy for Support vector machines algorithm to implement in high level language enabling parallelism. In this paper, we realized Support vector machine using python language and built a sensor network cluster with 5 Pi's. We also established a Hadoop software framework to employ MapReduce mechanism. We modified the existing Support vector machine algorithm to fit into the distributed hadoop architecture system for localization of a sensor node. In our experiment, we implemented the test sensor network with a variety of parameters and examined based on proficiency, resource evaluation, and processing time.