• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.7
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• pp.36-46
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• 2017

The turbo code, an error correction code, needs a long decoding time since the same decoding process must be repeated several times in order to obtain a good BER performance. Thus, parallel processing may be used to reduce the decoding time, in which case there may be a memory contention that requires additional buffers. The QPP interleaving has been proposed to avoid such case, but there is still a possibility of memory contention when a decoder is constructed using the so-called double flow technique. In this paper, we propose an even-odd cross mapping technique to avoid memory conflicts even in decoding using the double-flow technique. This method uses the address generation characteristic of the QPP interleaving and can be used to implement the interleaving circuit between the decoding blocks and the LLR memory blocks. When the decoder implemented by applying the double flow and the proposed methods is compared with the decoder by the conventional MDF techniques, the decoding time is reduced by up to 32% with the total area increase by 8%.

• Anxiety and mood
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• v.10 no.2
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• pp.143-150
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• 2014

Objective : The subgenual cingulate cortex, a part of default-mode network, has been known to playa key role in the pathophysiology of depression. The previous studies have reported abnormal functional connectivity between the subgenual cingulate cortex and other brain regions in the patients with depression. The goal of this shldy was to explore the resting-state functional connectivity of the subgenual cingulate cortex between the patients with depression and healthy subjects. Methods : Twenty patients with major depression and age- and sex-matched 20 healthy subjects underwent 5-minute resting state fMRI scans. The functional connectivity map in each subject was acquired using seed-based correlation analysis with the seed located in the subgenual cingulate cortex (Talairach coordinates; x=-10, y=5, z=-10). The functional connectivity maps were calculated using AFNI and compared between the patient and healthy subject group via two-sample T-test using 3dttest++ in AFNI package. Results : Functional connectivity was decreased between the subgenual cingulate cortex and both sides of fusiform gyrus in depressed subjects. Connectivity was also decreased between the subgenual cingulate cortex and the left cerebellum in the patient group. There was no correlation between the severity of depression and the degree of functional connectivity between the subgenual cingulate cortex and the regions showing decreased functional connectivity. Conclusion : Decreased resting-state functional connectivity between the subgenual cingulate cortex and both sides of fusiform gyrus, and decreased connectivity between the subgenual cingulate cortex and the left cerebellum found in the patients with major depression in comparison to the healthy subjects might be related to abnormal emotional and cognitive processing of depressed patients.

• Journal of Korean Tunnelling and Underground Space Association
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• v.5 no.1
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• pp.13-21
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• 2003

To investigate the safety and stability of a concrete lining, numerous studies have been conducted over the years and several methods have been developed. Most signal processing techniques of NDT have been based on Fourier analysis. However, the application of Fourier analysis to analyze recorded vibrational signal shows results in the frequency domain only, and it is not enough to analyze transient waves precisely. In this study, Wavelet theory was employed for the analysis of non-stationary wave induced by mechanical impact on tunnel concrete lining. The Wavelet transform of transient signals provides a method for mapping the frequency spectrum as a function of time. To verify the availability of Wavelet transform as a time-frequency analysis tool, model experiments have been conducted and the thickness of the concrete lining was estimated based on the proposed theory. From this study, it was found that the contour map by Wavelet transform provides more distinct results than the power spectrum by Fourier transform and it was also found that Wavelet transform was also an effective tool for the analysis of dispersive waves in tunnel concrete linings.

• Journal of Korean Society for Geospatial Information Science
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• v.6 no.2 s.12
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• pp.21-34
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• 1998

SAR is an active imaging sensor emitting its own energy source and can be operated in all weather conditions. Thus SAR provides data which can not be obtained by an optical sensor. In this study, the potentials and problems of the techniques for DEM extraction from the SAR imagery were evaluated through theoretical researches and practical experiments. And then the accuracy was tested by RMS error between the digitized map contour and the results from this experiment. Here, two types of DEM extraction method were evaluated. One was an analytical photogrammetric technique, and the other was a SAR interferometric processing. From the experiment, we found that the photogrammetric technique is currently the most suitable method considering topographic conditions of Korea. In the SAR interferometry technique, we also conclude that the problems caused by decorrelations due to the temporal reasons and due to the scattering effects from vegetation should be solved.

• Journal of Korean Society for Geospatial Information Science
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• v.6 no.2 s.12
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• pp.81-90
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• 1998

With the high demand for Geographic Information System and the diversification of Spatial Information, it has been required a rapid and accurate input system, updating system and an efficient field survey system to organize database for thematic mapping. Following the purpose, several indispensable modules have to be Invented to build a GPS Lap-top Computer System using low cost GPS receivers. These modules include such as an interface module between GPS receivers and lap-top computers, a data processing module for standalone GPS or Real-time Differential GPS, a module to input or amend digital map and to transfer three-dimensional coordinates in real-time, and finially a module to enter attribute value and feature code based on standard specification of digital maps for controlling position and attribute data. In this paper, it Is presented the efficiency of method to acquire and to input or to amend spatial information using a GPS Lap-top Computer System.

• Journal of Korea Multimedia Society
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• v.14 no.8
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• pp.1094-1107
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• 2011

We can use panorama systems or image based modeling systems when we want to make 3D space model and look around result. Panorama systems make 3D model to stitch images and map cylinder or cube. The structure of 3D model, made by panorama system, is not same as structure of a real room, so user can't infer a real structure. Typically, Image based modeling systems work on a desktop computer. That makes it difficult to reconstruct 3D model in real time and take long time for processing. In this paper, we propose a 3D panorama modeling system that uses images on a mobile device. This system reconstructs a 3D space model, similar with a real room in real time, from multiple images captured part of rooms. Using this system, user can reconstruct various shape of space and look around a 3D space model.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.3
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• pp.587-594
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• 2005

In the paper, after we propose a viterbi decoder which has multiple buffering and parallel processing decoding scheme through expanding time-divided imput signal, and map a FPGA, we implement a channel coding system together with PC-based software. Continuous input signal is buffered as order of decoding length and is parallel decoded using a high speed cell for viterbi decoding. Output data rate increases linearly with the cell formed the viterbi decoder, and flexible operation can be satisfied by programming controller and modifying input buffer. The tell for viterbi decoder consists of HD block for calculating hamming distance, CM block for calculating value in each state, TB block for trace-back operation, and LIFO. The implemented cell of viterbi decoder used 351 LAB(Logic Arrary Block) and stably operated in maximum 139MHz in APEX20KC EP20K600CB652-7 FPGA of ALTERA. The whole viterbi decoder including viterbi decoding cells, input/output buffers, and a controller occupied the hardware resource of $23\%$ and has the output data rate of 1Gbps.

• The KIPS Transactions:PartD
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• v.9D no.6
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• pp.1119-1126
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• 2002

In this paper, we propose two predictive spatial data mining based on spatial statistics and apply for predicting the forest fire hazardous area. These are conditional probability and likelihood ratio methods. In these approaches, the prediction models and estimation procedures are depending un the basic quantitative relationships of spatial data sets relevant forest fire with respect to selected the past forest fire ignition areas. To make forest fire hazardous area prediction map using the two proposed methods and evaluate the performance of prediction power, we applied a FHR (Forest Fire Hazard Rate) and a PRC (Prediction Rate Curve) respectively. In comparison of the prediction power of the two proposed prediction model, the likelihood ratio method is mort powerful than conditional probability method. The proposed model for prediction of forest fire hazardous area would be helpful to increase the efficiency of forest fire management such as prevention of forest fire occurrence and effective placement of forest fire monitoring equipment and manpower.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.12
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• pp.1950-1958
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• 2016

Today, technique for precisely positioning vehicles is very important in C-ITS(Cooperative Intelligent Transport System), Self-Driving Car and other information technology relating to transportation. Though the most popular technology for vehicle positioning is the GPS, its accuracy is not reliable because of large delay caused by multipath effect, which is very bad for realtime traffic application. Therefore, in this paper, we proposed the Vision-Based High Accuracy Vehicle Positioning Technology. At the first step of proposed algorithm, the ROI is set up for road area and the vehicles detection. Then, center and four corners points of found vehicles on the road are determined. Lastly, these points are converted into aerial view map using homography matrix. By analyzing performance of algorithm, we find out that this technique has high accuracy with average error of result is less than about 20cm and the maximum value is not exceed 44.72cm. In addition, it is confirmed that the process of this algorithm is fast enough for real-time positioning at the $22-25_{FPS}$.

• Journal of KIISE
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• v.45 no.1
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• pp.94-98
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• 2018

We propose Wide Inception ResNet (WIR Net) an optimized neural network architecture as a real-time semantic segmentation method for autonomous driving. The neural network architecture consists of an encoder that extracts features by applying a residual connection and inception module, and a decoder that increases the resolution by using transposed convolution and a low layer feature map. We also improved the performance by applying an ELU activation function and optimized the neural network by reducing the number of layers and increasing the number of filters. The performance evaluations used an NVIDIA Geforce GTX 1080 and TX1 boards to assess the class and category IoU for cityscapes data in the driving environment. The experimental results show that the accuracy of class IoU 53.4, category IoU 81.8 and the execution speed of $640{\times}360$, $720{\times}480$ resolution image processing 17.8fps and 13.0fps on TX1 board.