• The KIPS Transactions:PartC
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• v.11C no.7 s.96
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• pp.923-930
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• 2004

Wireless sensor networks is a core technology of ubiquitous computing which enables the network to aware the different kind of context by integrating exiting wired/wireless infranet with various sensor devices and connecting collected environmental data with applications. However it needs an energy-efficient approach in network layer to maintain the dynamic ad hoc network and to maximize the network lifetime by using energy constrained node. Cluster-based data aggregation and routing are energy-efficient solution judging from architecture of sensor networks and characteristics of data. In this paper. we propose a new distributed clustering algorithm in using distance from the sink. This algorithm shows that it can balance energy dissipation among nodes while minimizing the overhead. We verify that our clustering is more en-ergy-efficient and thus prolongs the network lifetime in comparing our proposed clustering to existing probabilistic clustering for sensor network via simulation.

• Journal of KIISE:Software and Applications
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• v.34 no.10
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• pp.910-917
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• 2007

Of the possible interactions between human and robot, touch is an important means of providing human beings with emotional relief. However, most previous studies have focused on interactions based on voice and images. In this paper. a method of recognizing human touching behaviors is proposed for developing a robot that can naturally interact with humans through touch. In this method, the recognition process is divided into pre-process and recognition Phases. In the Pre-Process Phase, recognizable characteristics are calculated from the data generated by the touch detector which was fabricated using force sensors. The force sensor used an FSR (force sensing register). The recognition phase classifies human touching behaviors using a multi-layer perceptron which is a neural network model. Experimental data was generated by six men employing three types of human touching behaviors including 'hitting', 'stroking' and 'tickling'. As the experimental result of a recognizer being generated for each user and being evaluated as cross-validation, the average recognition rate was 82.9% while the result of a single recognizer for all users showed a 74.5% average recognition rate.

• Journal of the Korean Vacuum Society
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• v.9 no.4
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• pp.406-410
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• 2000

Using the hot-wall epitaxy method, we grew a $Hg_{1-x}Cd_xTe$ (MCT) thin film in-situ after growing (111) CdTe of 9 $mu \textrm{m}$ as a buffer layer. The value of FWHM of double crystal x-ray diffraction rocking curve was 125 arcsec and the surface morphology was clean with a small roughness of 10 nm. From measuring the photocurrent of the grown MCT thin film, the maximum peak wavelength and the cut-off wavelength were 1.1050 $\mu\textrm{m}$ (1.1220 eV) and 1.2632 $\mu\textrm{m}$ (0.9815 eV), respectively. This peak wavelength corresponds to the peak of the band gap due to the intrinsic transition of the photoconductor. Therefore, the MCT thin film could be used as the photoconducting detector sensing a near-IR wavelength band from 1.0 to 1.6 $\mu\textrm{m}$.

• Journal of Sensor Science and Technology
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• v.5 no.1
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• pp.23-29
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• 1996

Thick film type gas sensors with parallel Pt heaters were fabricated by screen printing process and investigated sensitivities for methane gas. The TR7905 was selected as Pt paste for heater by characterization the properties of TCRs and thick film microstructures. The average resistance of parallel Pt heaters was $1.8{\Omega}$, and the best TCR obtained was $3685\;ppm/^{\circ}C$. On the top of the Pt heaters, a sensing layer added with Pt and Pd as catalyst paste was screen printed and heat treated. The sensitivity of the sensor was 4.3mV/1000ppm for methane. The power consumption of the sensors was 2.12watts.

• Journal of Korean Society for Geospatial Information Science
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• v.1 no.1 s.1
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• pp.171-180
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• 1993

Concern about nonpoint source pollution associated with urban storm water has led to the development of new tools for better water quality planning. This paper presents an application of a geographic information system (GIS) for urban water quality study. The GIS was used to manage land use data for nonpoint source pollution modeling and to aggregate pollutant loadings within various types of geographic units. An empirical water quality model was used to estimate pollutant loadings based primarily on land use. A land use coverage was created by updating an old coverage through interpretation of recent photography. This land use coverage was also used to record all pollutant loadings for each land use polygon. Storm sewer maps were digitized and interpreted to create a coverage of storm sewer basins and sub-basins. By overlaying pollutant loadings with the sewer sub-basin layer, aggregated pollutant loadings for major sewer outfalls were calculated. Based on the loading information, critical areas of excessive pollutant loadings were located and the effectiveness of Best Management Practices (BMPs) to control pollutant loadings were evaluated.

• The Journal of the Acoustical Society of Korea
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• v.16 no.2
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• pp.10-15
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• 1997

The hydrophones is mounted in many applications on a vibrating surface and functions as an underwater acoustic signal receiver without sensing the vibrations from the mounting surface. However, their performance is usually degraded by the interference of exterior noises such as acoustic cavitation in water stream, host structural vibration in the hull, and propeller motions. This paper describes the design and evaluation of a self noise suppressing hydrophones which shows very poor sensitivity to the external noises, first, effects of the external noise on the its receiver performance is simulated with finite element method(FEM). Second, the geometrical variations are implemented on the original structure that include additional air pockets and acoustic walls which work as acoustic shied or scatter of the noises. The results show that the effect of the external noise is the most significant when it is applied near to the bottom of the side wall of the hydrophones. The transverse noise induced by the outside water flow is isolated most effectively when a thin compliant (damping) layer combined with two air pockets is inserted to the circumference of the nose. Noise level is reduced about fifty nine percent of that of the original structure.

• Journal of Sensor Science and Technology
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• v.5 no.3
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• pp.41-48
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• 1996

We developed SAW gas sensor for monitoring SOx gas with high sensitivity. It was fabricated as a microsensor for detecting SOx gas by depositing sensing material on SAW device. As a detecting layer material, CdS was selected. Deposition of CdS in the form of thin films was carried out by the ultrasonic spray pyrolysis method using ultrasonic spray nozzle. Thin films with the uniform and large surface area for sensors were deposited. The stable pyrolysis environment provided by uniform and fine droplets formed by spray nozzle made it possible to obtain thin films with excellent quality. The minimum grain size of the CdS thin films was about 50 nm when deposited at $300^{\circ}C$. SAW gas sensors showed reasonable sensitivity and reproducibility. Further studies are required to investigate the interference of other gases to SOx gas detection.

• Geomechanics and Engineering
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• v.13 no.6
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• pp.893-906
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• 2017

Automatic large scale soil model generation is very critical stage for earthquake hazard simulation of urban areas. Manual model development may cause some data losses and may not be effective when there are too many data from different soil observations in a wide area. Geographic information systems (GIS) for storing and analyzing spatial data help scientists to generate better models automatically. Although the original soil observations were limited to soil profile data, the recent developments in mapping technology, interpolation methods, and remote sensing have provided advanced soil model developments. Together with advanced computational technology, it is possible to handle much larger volumes of data. The scientists may solve difficult problems of describing the spatial variation of soil. In this study, an algorithm is proposed for automatic three dimensional soil and velocity model development of southern part of the European side of Istanbul next to Sea of Marmara based on GIS data. In the proposed algorithm, firstly bedrock surface is generated from integration of geological and geophysical measurements. Then, layer surface contacts are integrated with data gathered in vertical borings, and interpolations are interpreted on sections between the borings automatically. Three dimensional underground geology model is prepared using boring data, geologic cross sections and formation base contours drawn in the light of these data. During the preparation of the model, classification studies are made based on formation models. Then, 3D velocity models are developed by using geophysical measurements such as refraction-microtremor, array microtremor and PS logging. The soil and velocity models are integrated and final soil model is obtained. All stages of this algorithm are carried out automatically in the selected urban area. The system directly reads the GIS soil data in the selected part of urban area and 3D soil model is automatically developed for large scale earthquake hazard simulation studies.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.8
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• pp.1493-1499
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• 2007

Real-time applications in a wireless sensor network environment require real-time transmissions from sensing nodes to sink nodes. Existing congestion control mechanisms have treated congestion problems in sensor networks, but they only adjust the reporting frequency or the sending rate in intermediate nodes. They were not suitable for real-time applications from the transmission delays point of view. In this paper, we suggest a new mechanism that can reduce the transmission delay and can increase the throughput for real-time applications in sensor network. This mechanism classifies data on the real-time characteristics, processes the data maintaining the real-time characteristics prior to the other data such as the non real-time data or the data lost the real-time characteristics. A modified frame format is also proposed in order to apply the mechanism to IEEE 802.15.4 MAC layer. The simulation based on ns-2 is accomplished in order to verify the performance of the suggested scheme from transmission delay and throughput standpoints. The simulation results show that the proposed algorithm has a better performance specifically when It applies to the real-time applications in sensor networks.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1081-1088
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• 2020

In this paper, the method of detecting sea fog through CCTV image is proposed based on convolutional neural networks. The study data randomly extracted 1,0004 images, sea-fog and not sea-fog, from a total of 11 ports or beaches (Busan Port, Busan New Port, Pyeongtaek Port, Incheon Port, Gunsan Port, Daesan Port, Mokpo Port, Yeosu Gwangyang Port, Ulsan Port, Pohang Port, and Haeundae Beach) based on 1km of visibility. 80% of the total 1,0004 datasets were extracted and used for learning the convolutional neural network model. The model has 16 convolutional layers and 3 fully connected layers, and a convolutional neural network that performs Softmax classification in the last fully connected layer is used. Model accuracy evaluation was performed using the remaining 20%, and the accuracy evaluation result showed a classification accuracy of about 96%.