• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.10
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• pp.1840-1848
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• 2017

Linear wireless sensor networks typically construct a network topology with a high reliability through sequential 1:1 mapping among sensor nodes, so that they are used in various surveillance applications of major national infrastructures. Most existing techniques for identifying sensor nodes in those networks are using GPS, AOA, and RSSI mechanisms. However, GPS or AOA based node identification techniques affect the size or production cost of the nodes so that it is not easy to construct practical sensor networks. RSSI based techniques may have a high deviation regrading location identification according to propagation environments and equipment quality so that complexity of error correction algorithm may increase. We propose a timestamps based sequential localization algorithm that uses transmit and receive timestamps in a message between sensor nodes without using GPS, AOA, and RSSI techniques. The algorithms for distance measurement between each node are expected to measure distance within up to 1 meter in case of an crystal oscillator of 300MHz or more.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.3
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• pp.139-146
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• 2018

Underwater acoustic communication can be applied to various area such as scientific, commercial and military survey using Autonomous Underwater Vehicles and Unmanned Underwater Vehicles. Underwater communication is studying very actively by advanced country like United States. But differ from wireless communication in the air, underwater acoustic communication has some difficult problems, ISI(Inter Symbol Interference) due to multipath and limit of transmission bandwidth due to slow propagation of sound wave. In this paper, SC-FDE and OFDM transmission system for the cancellation of ISI in conjunction with underwater acoustic channel modeling are applied to the underwater simulation of communication. The performance of these methods in the simulation guide to possibility of adopting in underwater acoustic communication algorithm. For this purpose, we compare SER performance of SC-FDE with that of OFDM for modelled underwater channel. Underwater channel is generated by Bellhop model. Simulation results show above 5dB SNR gain at 10-3 SER. And it demonstrate SC-FDE is efficient method for underwater acoustic communication.

• Journal of Biomedical Engineering Research
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• v.23 no.3
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• pp.197-205
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• 2002

The objectives of this Paper is to implement a diagnostic classifier of differential laryngeal diseases from acoustic signals acquired in a noisy room. For this Purpose, the voice signals of the vowel /a/ were collected from Patients in a soundproof chamber and got mixed with noise. Then, the acoustic Parameters were analyzed, and hierarchical neural networks were applied to the data classification. The classifier had a structure of five-step hierarchical neural networks. The first neural network classified the group into normal and benign or malign laryngeal disease cases. The second network classified the group into normal or benign laryngeal disease cases The following network distinguished polyp. nodule. Palsy from the benign laryngeal cases. Glottic cancer cases were discriminated into T1, T2. T3, T4 by the fourth and fifth networks All the neural networks were based on multilayer perceptron model which classified non-linear Patterns effectively and learned by an error back-propagation algorithm. We chose some acoustic Parameters for classification by investigating the distribution of laryngeal diseases and Pilot classification results of those Parameters derived from MDVP. The classifier was tested by using the chosen parameters to find the optimum ones. Then the networks were improved by including such Pre-Processing steps as linear and z-score transformation. Results showed that 90% of T1, 100% of T2-4 were correctly distinguished. On the other hand. 88.23% of vocal Polyps, 100% of normal cases. vocal nodules. and vocal cord Paralysis were classified from the data collected in a noisy room.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.4
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• pp.351-357
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• 2008

An aerial multi-looking camera system equips itself with five separate cameras which enables acquiring one vertical image and four oblique images at the same time. This provides diverse information about the site compared to aerial photographs vertically. The geometric relationship of oblique cameras and a vertical camera can be modelled by 6 exterior orientation parameters. Once the relationship between the vertical camera and each oblique camera is determined, the exterior orientation parameters of the oblique images can be calculated by the exterior orientation parameters of the vertical image. In order to examine the exterior orientation of both a vertical camera and each oblique cameras in the multi-looking camera relatively, calibration targets were installed in a lab and 14 images were taken from three image stations by tilting and rotating a non-metric digital camera. The interior orientation parameters of the camera and the exterior orientation parameters of the images were estimated. The exterior orientation parameters of the oblique image with respect to the vertical image were calculated relatively by the exterior orientation parameters of the images and error propagation of the orientation angles and the position of the projection center was examined.

• Journal of Korea Water Resources Association
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• v.39 no.10 s.171
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• pp.823-832
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• 2006

Precipitation is the most important component to the study of water and energy cycle in hydrology. In this study we investigate rainfall retrieval uncertainty from different sources of remotely sensed precipitation field and then probable error propagation in the simulation of hydrologic variables especially, runoff on different vegetation cover. Two remotely sensed rainfall retrievals (space-borne IR-only and ground radar rainfall) are explored and compared visually and statistically. Then, an offline Community Land Model (CLM) is forced with in situ meteorological data to simulate the amount of runoff and determine their impact on model predictions. A fundamental assumption made in this study is that CLM can adequately represent the physical land surface processes. Results show there are big differences between different sources of precipitation fields in terms of the magnitude and temporal variability. The study provides some intuitions on the uncertainty of hydrologic prediction via the interaction between the land surface and near atmosphere fluxes in the modelling approach. Eventually it will contribute to the understanding of water resources redistribution to the climate change in Korean Peninsula.

• Journal of Korea Water Resources Association
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• v.31 no.1
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• pp.13-25
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• 1998

It is necessary to develop methodologies for the application of artificial neural network into hydrologic rainfall-runoff process, although there is so much applicability by using the functions of associative memory based on recognition for the relationships between causes and effects and the excellent fitting capacity for the nonlinear phenomenon. In this study, some problems are presented in the application procedures of artificial neural networks and the simulation of runoff hydrograph experiences are reviewed with nonlinear functional approximator by artificial neural network for rainfall-runoff relationships in a watershed. which is regarded as hydrdologic black box model. The neural network models are constructed by organizing input and output patterns with the deserved rainfall and runoff data in Pyoungchang river basin under the assumption that the rainfall data is the input pattern and runoff hydrograph is the output patterns. Analyzed with the results. it is possible to simulate the runoff hydrograph with processing element of artificial neural network with any hydrologic concepts and the weight among processing elements are well-adapted as model parameters with the assumed model structure during learning process. Based upon these results. it is expected that neural network theory can be utilized as an efficient approach to simulate runoff hydrograph and identify the relationship between rainfall and runoff as hydrosystems which is necessary to develop and manage water resources.

• Korean Journal of Optics and Photonics
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• v.16 no.3
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• pp.248-253
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• 2005

We designed and fabricated a compact multi-mode interference (MMI) wavelength demultiplexer using the concept of 'Improved Quasi-State' modes. The output power and extinction ratio were improved by utilizing modal phase error which is specially occurred in low-index contrast. For a designed demultiplexer, the mode propagation analysis with effective index approximation shows significant improvement of extinction ratio to -25 dB for both $1.31{\mu}m\;and\;1.51{\mu}m$ wavelength region and the split-length was reduced about 1/5 of other MMI devices. The fabricated device shows successful characteristics for both 1.31 and $1.55{\mu}m$ wavelengths. These results demonstrate the potential of low-index materials system and the embossing process for photonic integrated circuits.

• Journal of Navigation and Port Research
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• v.34 no.3
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• pp.175-180
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• 2010

In the almost application parts, GNSS being used the primary navigation system on world-widely. However, some of nations attempt or deliberate to enhance current Loran system, as a backup to satellite navigation system because of the vulnerability to the disturbance signal. Loran interests in supplemental navigation system by the development and enhancement, which is called eLoran, and that consists of advancement of receiver and transmitter and of differential Loran in order to increase the accuracy of current Loran-C. A significant factor limiting the ranging accuracy of the eLoran signal is the ASF in the TOAs observed by the receiver. The ASF is mostly due to the fact that the ground-wave signal is likely to propagate over paths of varying conductivity and topography. This paper presents comparison results between the predicted ASF and the measured ASF in a southern east region of Korea. For predicting ASF, the Monteath model is used. Actual ASF is measured from the legacy Loran signal transmitted Pohang station in the GRI 9930 chain. The test results showed the repeatability of the measured ASF and the consistent characteristics between the predicted and the measured ASF values.

• The Transactions of the Korea Information Processing Society
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• v.4 no.2
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• pp.465-482
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• 1997

In this paper, we have studied on cinstructing code-recognition shstem by neural network according to a image process taking the DOT classification code stamped on tire surface.It happened to a few problems that characters distorted in edge by diffused reflection and two adjacent characters take the same label,even very sen- sitive to illumination ofr recognition the stamped them on tire.Thus,this paper would propose the algorithm for tire code under being cinscious of these properties and prove the algorithm drrciency with a simulation.Also,we have suggerted the MCBP network composing of multi-linked recognizers of dffcient identify the DOT code being tire classification code.The MCBP network extracts the projection balue for classifying each character's rdgion after taking out the prjection of each chracter's region on X,Y axis,processes each chracters by taking 7$\times$8 normalization.We have improved error rate 3% through the MCBP network and post-process comparing the DOT code Database. This approach has a accomplished that learming time get's improvenent at 60% and recognition rate has become to 95% from 90% than BckPropagation with including post- processing it has attained greate rates of entire of tire recoggnition at 98%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.8
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• pp.2010-2024
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• 1998

In video coding, it is important to improve the average picture quality as well as to maintain cosistent picture quality between consecutive pictures. In this paper, we propose a distortion-rate estimation method for MPEG-2 video and a forward rate control method, using the proposed estimation result, to be able to obtain the improved and consistent picture quality of CBR (Constant Bit Rate) encoded MPEG-2 video. The proposed distortion-rate estimation enable us to predict the distortion and the bits generated from an encoded picture at a given quantization step size and vice versa. The most attactive features of proposed distortion-rate estimation are its accuracy and low computational complexity enough to be applied to the practical video coding. In addition, the proposed rate control first determined a quantization parameter per frame by following procedure: distortion-rate estimation, target bit allocation, distortion constraint and VBV(Video Buffer Verification) constraint. And then this quantization parameter is applied to the encoding so that improved and consisten picture quality can be obtained. Furthermore the proposed rate control method can solve the error propagation problem caused by scene change or anchor picture degradation by using the B-picture skipping and the guarantee of the minimum bit allocation for the anchor picture. Experimental results, comparing the proposed forward rate control method with TM5 method, show that the proposed method makes more improed and consistent picture quality than TM5.