• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.2
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• pp.102-110
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• 2015

The main source of noise in computed tomography (CT) images is a quantum noise, which results from statistical fluctuations of X-ray quanta reaching the detector. This paper proposes a neural network (NN) based hybrid filter for removing quantum noise. The proposed filter consists of bilateral filters (BFs), a single or multiple neural edge enhancer(s) (NEE), and a neural filter (NF) to combine them. The BFs take into account the difference in value from the neighbors, to preserve edges while smoothing. The NEE is used to clearly enhance the desired edges from noisy images. The NF acts like a fusion operator, and attempts to construct an enhanced output image. Several measurements are used to evaluate the image quality, like the root mean square error (RMSE), the improvement in signal to noise ratio (ISNR), the standard deviation ratio (MSR), and the contrast to noise ratio (CNR). Also, the modulation transfer function (MTF) is used as a means of determining how well the edge structure is preserved. In terms of all those measurements and means, the proposed filter shows better performance than the guided filter, and the nonlocal means (NLM) filter. In addition, there is no severe restriction to select the number of inputs for the fusion operator differently from the neuro-fuzzy system. Therefore, without concerning too much about the filter selection for fusion, one could apply the proposed hybrid filter to various images with different modalities, once the corresponding noise characteristics are explored.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.93-113
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• 2020

According to information theory, non-orthogonal transmission can achieve the multiple-user channel capacity with an onion-peeling like successive interference cancellation (SIC) based detection followed by a capacity approaching channel code. However, in multiple antenna system, due to the unideal characteristic of the SIC detector, the residual interference propagated to the next detection stage will significantly degrade the detection performance of spatial data layers. To overcome this problem, we proposed a modified power-domain non-orthogonal multiple access (P-NOMA) scheme joint designed with space-time coding for multiple input multiple output (MIMO) NOMA system. First, with proper power allocation for each user, inter-user signals can be separated from each other for NOMA detection. Second, a well-designed quasi-orthogonal space-time block code (QO-STBC) was employed to facilitate the SIC-based MIMO detection of spatial data layers within each user. Last, we proposed an optimization algorithm to assign channel coding rates to balance the bit error rate (BER) performance of those spatial data layers for each user. Link-level performance simulation results demonstrate that the proposed time-space-power domain joint transmission scheme performs better than the traditional P-NOMA scheme. Furthermore, the proposed algorithm is of low complexity and easy to implement.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.1
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• pp.49-58
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• 2012

Buildings become complex and diverse with time. It is difficult to extract individual buildings using only an optical image, because they have similar spectral characteristics to objects such as vegetation and roads. In this study, we propose a method to extract building area and boundary through integrating airborne Light Detection and Ranging(LiDAR) data and aerial images. Firstly, a binary edge map was generated using Edison edge detector after applying Adaptive dynamic range linear stretching radiometric enhancement algorithm to the aerial image. Secondly, building objects on airborne LiDAR data were extracted from normalized Digital Surface Model and aerial image. Then, a temporary building areas were extracted by overlaying the binary edge map and building objects extracted from LiDAR data. Finally, some building boundaries were additionally refined considering positional accuracy between LiDAR data and aerial image. The proposed method was applied to two experimental sites for validation. Through error matrix, F-measure, Jaccard coefficient, Yule coefficient, and Overall accuracy were calculated, and the values had a higher accuracy than 0.85.

• Korean Journal of Remote Sensing
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• v.30 no.6
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• pp.787-795
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• 2014

This paper presents an image registration using Triangulation-based Local Transformation (TLT) applied to the remaining matched points after elimination of the matched points with gross error. The corners extracted using geometric mean-based corner detector are matched using Pearson's correlation coefficient and then accepted as initial matched points only when they satisfy the Left-Right Consistency (LRC) check. We finally accept the remaining matched points whose RANdom SAmple Consensus (RANSAC)-based global transformation (RGT) errors are smaller than a predefined outlier threshold. After Delaunay triangulated irregular networks (TINs) are created using the final matched points on reference and sensed images, respectively, affine transformation is applied to every corresponding triangle and then all the inner pixels of the triangles on the sensed image are transformed to the reference image coordinate. The proposed algorithm was tested using KOMPSAT-2 images and the results showed higher image registration accuracy than the RANSAC-based global transformation.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1528-1528
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• 2001

Ginseng cultivated in different country or growing condition has generally different components such as saponin and protein, and it relates to efficacy and action. Protein content assumes by nitrogen content in ginseng radix. Nitrogen content could be determined by chemical analysis such as kjeldahl or extraction methods. However, these methods require long analysis time and result environmental pollution and sample damage. In this work we investigated possibility of non-destructive determination of nitrogen content in ginseng radix using near-infrared spectroscopy. Ginseng radix, root of Panax ginseng C. A. Meyer, was studied. Total 120 samples were used in this study and it was consisted of 6 sample sets, 4, 5 and 6-year-old Korea ginseng and 7, 8 and 9-year-old China ginseng, respectively. Each sample set has 20 sample. Nigrogen content was measured by electronic analysis. NIR reflectance spectra were collected over the 1100 to 2500 nm spectral region with a InfraAlyzer 500C (Bran+Luebbe, Germany) equipped with a halogen lapmp and PbS detector and data were collected every 2 nm data point intervals. The calibration models were carried out by multiple linear regression (MLR) and partial least squares (PLS) analysis using IDAS and SESAME software. Result of electronic analysis, Korean ginseng were different mean value in nitrogen content of China ginseng. Ginseng tend to generally decrease the nitrogen content according as cultivation year is over 6 years. The MLR calibration model with 8 wavelengths using IDAS software accurately predicted nitrogen contents with correlation coefficient (R) and standard error of prediction of 0.985 and 0.855%, respectively. In case of SESAME software, the MLR calibration with 9 wavelength was selected the best calibration, R and SEP were 0.972 and 0.596%, respectively. The PLSR calibration model result in 0.969 of R and 0.630 of RMSEP. This study shows the NIR spectroscopy could be applied to determine the nitrogen content in ginseng radix with high accuracy.

• Journal of the Korean Institute of Gas
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• v.11 no.1 s.34
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• pp.40-45
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• 2007

This paper describes NDIR $CO_{2}$ gas sensor that shows the characteristics of temperature compensation. It consists of novel optical cavity that has two elliptical mirrors and a thermopile that includes ASIC chip in the same metal package for the amplification of detector output voltage and temperature sensor. The newly developed sensor module shows high accuracy ($less\;than {\pm}40\;ppm$) throughout the measuring concentration of $CO_{2}$ gas from 0 ppm to 2,000 ppm. After implementing the calculation methods of gas concentration, which is based upon the experimental results, the sensor module shows high accuracy less than ${\pm}5\;ppm$ error throughout the measuring temperature range ($15^{\circ}C\;to\;35$^{\circ}C$) and gas concentrations with self-temperature compensation.

• The KIPS Transactions:PartA
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• v.11A no.1
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• pp.81-88
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• 2004

In this paper, we designed the outer encoder/decoder for the terrestrial DMB that is an advanced digital broadcasting standard, implemented, and verified by using ALTERA FPGA. In the encoder part, it was created the parity bytes (16 bytes) from the input packet (188by1e) of MPEG-2 TS and the encoded data was distributed output by the convolutional interleaver for Preventing burst errors. In the decoder part, It was proposed the algorithm that detects synchronous character suitable to DMB in transmitted data from the encoder. The circuit complexity in RS decoder was reduced by applying a modified Euclid's algorithm. This system has a capability to correct error of the maximum 8 bytes in a packet. After the outer encoder/decoder algorithm was verified by using C language, described in VHDL and implemented in the ALTERA FPGA chips.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.1
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• pp.677-682
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• 2015

In this paper, we investigated the effect of light on the performance of the receiver system noise and external noise added from the ever-present influence in general optical system. And calculated the reception sensitivity of the receiver at the time of off-keying transmission - from the optical transmission system in consideration of the case that the photo detector has a quantum yield of less than one-one. Not less than 50 it was confirmed that it is possible to configure the low power system is calculated and compared with the case where less than 300 the receiver sensitivity of the optical system to maintain the standard error probability. However, even if these values were considered, and the preamplifier in the receiver, considering a case of using a low-output light source, so that a heavy burden in the value less than the actual system installation, using the light source having less than the output, as shown in Figure 3, the results that were obtained also may be used.

• Progress in Medical Physics
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• v.28 no.4
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• pp.164-170
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• 2017

One of the methods to consider the effect of respiratory motion of a tumor target in radiotherapy is to establish a treatment plan with the internal target volume (ITV) created based on an accurate analysis of the target motion displacement. When this method is applied to intensity modulated radiotherapy (IMRT), it is expected to yield a different treatment dose distribution under the motion condition according to the IMRT method. In this study, we prepared ITV-based IMRT plans with conventional IMRT using fixed gantry angle beams, RapidArc using volumetric modulated arc therapy, and tomotherapy using helical therapy. Then, the variation in dose distribution caused by the target motion was analyzed by the dose measurement in the actual motion condition. A delivery quality assurance plan was prepared for the established IMRT plan and the dose distribution in the actual motion condition was measured and analyzed using a two-dimensional diode detector placed on a moving phantom capable of simulating breathing movements. The dose measurement was performed considering only a uniform target shape and motion in the superior-inferior (SI) direction. In this condition, it was confirmed that the error of the dose distribution due to the target motion is minimum in tomotherapy. This is thought to be due to the characteristic of tomotherapy that treats the target sequentially by dividing it into several slices. When the target shape is uniform and the main target motion direction is SI, it is considered that tomotherapy for the ITV-based IMRT method has a characteristic which can reduce the dose difference compared with the plan dose under the target motion condition.

• Journal of Satellite, Information and Communications
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• v.11 no.3
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• pp.119-122
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• 2016

Feature detection is recognized as an accurate spectrum sensing approach when the information of the desired signal is partly known at the receiver. This type of detection was proposed to overcome large noise environment. Cyclostationary detection is an example of feature detection in spectrum sensing technique in cognitive radio. However, the cyclostationary process calculation requires a lot of processing time and information about the designed signals. On the other hand, energy detection spectrum sensing is widely known as a simple and compact spectrum sensing technique. However, energy detection is highly affected by large noise and lead to high detection error probability. In this paper, the combination of energy detection and cyclostationary is proposed in order to increase the accuracy and decrease the calculation and processing time. The two-layer threshold is utilized in order to reduce the complexity of computation and processing time in cyclostationary which can lead to the improved throughput of the system. The simulation result shows that the implementation of energy-based cyclostationary detector can help to improve the performance of the system while it can considerably reduce the required time for signal detection.