• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.1
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• pp.183-188
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• 2008

Satellite DMB(Digital Multimedia Broadcasting) uses the Cap Filler(GF) that provides a service to the wave shade area of the satellite signal that is a non-line of sight area. The GF is the repeater and the Satellite DMB Systems certainly must construct the GF Network toguarantee the movement reception of the terminal. As the coverage of the GF is formed the Cell or Sector, when the multiple GF is established to be contiguous, the problem of the interference will be able to occur. This paper describes the Satellite DMB system and the GF, and it investigate the design fundamentals plan of the GF Network that it will be able to reduce this problem. As a result, in case of the distance that GF and terminal unit is above 4.6Km, service is not provided because of quality degradation according to mutual interference.

• Advances in materials Research
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• v.13 no.1
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• pp.63-86
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• 2024

Asphalt concrete (AC), is a mixture of bitumen and aggregates, which is very sensitive in the design of flexible pavement. In this study, the Marshall stability of the glass and carbon fiber bituminous concrete was predicted by using Artificial Neural Network (ANN), Support Vector Machine (SVM), Random Forest (RF), and M5P Tree machine learning algorithms. To predict the Marshall stability, nine inputs parameters i.e., Bitumen, Glass and Carbon fibers mixed in 100:0, 75:25, 50:50, 25:75, 0:100 percentage (designated as 100GF:0CF, 75GF:25CF, 50GF:50 CF, 25GF:75CF, 0GF:100CF), Bitumen grade (VG), Fiber length (FL), and Fiber diameter (FD) were utilized from the experimental and literary data. Seven statistical indices i.e., coefficient of correlation (CC), mean absolute error (MAE), root mean squared error (RMSE), relative absolute error (RAE), root relative squared error (RRSE), Scattering index (SI), and BIAS were applied to assess the effectiveness of the developed models. According to the performance evaluation results, Artificial neural network (ANN) was outperforming among other models with CC values as 0.9147 and 0.8648, MAE values as 1.3757 and 1.978, RMSE values as 1.843 and 2.6951, RAE values as 39.88 and 49.31, RRSE values as 40.62 and 50.50, SI values as 0.1379 and 0.2027 and BIAS value as -0.1 290 and -0.2357 in training and testing stage respectively. The Taylor diagram (testing stage) also confirmed that the ANN-based model outperforms the other models. Results of sensitivity analysis showed that the fiber length is the most influential in all nine input parameters whereas the fiber combination of 25GF:75CF was the most effective among all the fiber mixes in Marshall stability.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.9
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• pp.1786-1792
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• 2015

Random linear network coding (RLNC) is widely employed to enhance the reliability of wireless multicast. In RLNC encoding/decoding, Galois Filed (GF) arithmetic is typically used since all the operations can be performed with symbols of finite bits. Considering the architecture of commercial computers, the complexity of arithmetic operations is constant regardless of the dimension of GF m, if m is smaller than 32 and pre-calculated tables are used for multiplication/division. Based on this, we show that the complexity of RLNC inversely proportional to m. Considering additional overheads, i.e., the increase of header length and memory usage, we determine the practical value of m. We implement RLNC in a commercial computer and evaluate the codec throughput with respect to the type of the tables for multiplication/division and the number of original packets to encode with each other.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.414-426
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• 2022

Elliptic Curve Cryptography (ECC) is one of the finest cryptographic technique of recent time due to its lower key length and satisfactory performance with different hardware structures. In this paper, a High Throughput Multiplier architecture is introduced for Elliptic Cryptographic applications based on concurrent computations. With the aid of the concurrent computing approach, the High Throughput Concurrent Computation (HTCC) technology that was just presented improves the processing speed as well as the overall efficiency of the point-multiplier architecture. Here, first and second distinct group operation of point multiplier are combined together and synthesised concurrently. The synthesis of proposed HTCC technique is performed in Xilinx Virtex - 5 and Xilinx Virtex - 7 of Field-programmable gate array (FPGA) family. In terms of slices, flip flops, time delay, maximum frequency, and efficiency, the advantages of the proposed HTCC point multiplier architecture are outlined, and a comparison of these advantages with those of existing state-of-the-art point multiplier approaches is provided over GF(2¹⁶³), GF(2²³³) and GF(2²⁸³). The efficiency using proposed HTCC technique is enhanced by 30.22% and 75.31% for Xilinx Virtex-5 and by 25.13% and 47.75% for Xilinx Virtex-7 in comparison according to the LC design as well as the LL design, in their respective fashions. The experimental results for Virtex - 5 and Virtex - 7 over GF(2²³³) and GF(2²⁸³)are also very satisfactory.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2702-2704
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• 2003

본 논문은 전력선통신시스템 (Power Line Communications)을 위한 초고속 오류정정 부호화기 회로에 관한 설계방법론과 회로의 동작속도, 회로복잡성과 레이턴시에 직접적으로 기여하는 핵심 GF (Galois Field) 연산기들의 역할 및 이들의 설계결과에 관해 설명한다. 특히, 이러한 설계방법에 충실한 오류정정 부호화기회로는 입출력 병렬구조의 세미-시스톨릭 (Semi-systolic) 아키텍처를 갖는 고속의 내부 핵심 GF 연산기회로들을 채택함으로써 고속 연산을 가능토록 한다. 최적화된 GF곱셈연산기를 기반으로 설계되어진 리드-솔로몬 (Reed-Solomon) 오류정정 부호화기는 전력선 채널상에서 데이터를 전송 시 발생되는 연집오류들을 효과적으로 복원하도록 하는 대표적인 부호화기로 이미 존재하는 다른 회로들에 비해 동작속도, 회로의 복잡성, 및 레이턴시 측면에서 그 성능이 월등히 뛰어나므로, 실제 초고속 전력선 통신시스템의 설계 및 구현 시 효과적으로 이용될 수 있다.

• Herbal Formula Science
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• v.31 no.3
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• pp.145-156
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• 2023

Objectives : This study aimed to select candidate herbal medicines to be used in preclinical studies of cerebral infarction using the network pharmacology research method. Methods : Oral bioavailability (OB), drug likeness (DL), Caco-2, and blood-brain barrier (BBB) permeability were employed in this study's network pharmacology analysis method to choose compounds with potential efficacy. The following formulas were utilized for the values of each variable used in this study: OB ≥ 20%, DL ≥ 0.18, Caco-2 ≥ 0, and BBB ≥ -0.3. The relationships between target proteins and diseases that are assumed to be involved in the chosen bioavailable chemicals were built in a network manner using the aforementioned factors, and proteins thought to play a significant role were identified. Results : Sudan III was obtained as a result of selecting compounds related to ischemic stroke in consideration of pharmacokinetic characteristics such as digestion and absorption and practicality using the TCMSP database. Medicinal herbs Gardeniae Fructus (GF) contains sudan III, and it was confirmed that compounds in GF were highly related to brain diseases, and the mechanism involved through the KEGG pathway was confirmed. GF, which has sudan III related to ischemic stroke and is also involved in other neurological diseases, is expected to be used for ischemic stroke treatment. Conclusions : GF has been predicted to have potential for ischemic stroke treatment, and can be used for future preclinical studies.

• The KIPS Transactions:PartC
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• v.15C no.2
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• pp.133-140
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• 2008

In this paper, we propose a high performance elliptic curve cryptographic processor over $GF(2^{163})$. The proposed architecture is based on a modified Lopez-Dahab elliptic curve point multiplication algorithm and uses Gaussian normal basis for $GF(2^{163})$ field arithmetic. To achieve a high throughput rates, we design two new word-level arithmetic units over $GF(2^{163})$ and derive a parallelized elliptic curve point doubling and point addition algorithm with uniform addressing based on the Lopez-Dahab method. We implement our design using Xilinx XC4VLX80 FPGA device which uses 24,263 slices and has a maximum frequency of 143MHz. Our design is roughly 4.8 times faster with 2 times increased hardware complexity compared with the previous hardware implementation proposed by Shu. et. al. Therefore, the proposed elliptic curve cryptographic processor is well suited to elliptic curve cryptosystems requiring high throughput rates such as network processors and web servers.

• Advances in Computational Design
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• v.7 no.3
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• pp.253-279
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• 2022

This study investigated and predicted the Marshall stability of glass-fiber asphalt mix, carbon-fiber asphalt mix and glass-carbon-fiber asphalt (hybrid) mix by using machine learning techniques such as Artificial Neural Network (ANN), Support Vector Machine (SVM) and Random Forest(RF), The data was obtained from the experiments and the research articles. Assessment of results indicated that performance of the Artificial Neural Network (ANN) based model outperformed applied models in training and testing datasets with values of indices as; coefficient of correlation (CC) 0.8492 and 0.8234, mean absolute error (MAE) 2.0999 and 2.5408, root mean squared error (RMSE) 2.8541 and 3.3165, relative absolute error (RAE) 48.16% and 54.05%, relative squared error (RRSE) 53.14% and 57.39%, Willmott's index (WI) 0.7490 and 0.7011, Scattering index (SI) 0.4134 and 0.3702 and BIAS 0.3020 and 0.4300 for both training and testing stages respectively. The Taylor diagram also confirms that the ANN-based model outperforms the other models. Results of sensitivity analysis show that Carbon fiber has a major influence in predicting the Marshall stability. However, the carbon fiber (CF) followed by glass-carbon fiber (50GF:50CF) and the optimal combination CF + (50GF:50CF) are found to be most sensitive in predicting the Marshall stability of fibrous asphalt concrete.

• Journal of the Korean Society of Safety
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• v.17 no.1
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• pp.11-17
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• 2002

The purpose of this study was to present the method to choose the optimization machining condition for the wire electric machine. This was completed by examining the ever-changing quality of the material and by improving the function of the wire electric discharge machine. Precision metal mold products and the unmanned wire electric discharge machining system were used and then applied in industrial fields. This experiment uses the wire electric discharge machine with brass wire electrode of 0.25mm. To measure the precision of the machining surface, average values are obtained from 3 samples of measures of center-line average roughness by using a third dimension gauge and a stylus surface roughness gauge. In this experiment, we changed no-node voltage to 7 and 9, pulse-on-time to $6{\mu}s,\;8{\mu}s$ and $10{\mu}s$, pulse-off-time to $8{\mu}s,\;10{\mu}s$ and $13{\mu}s$, and experimented on wire tension at room temperature by 1000gf, 1200gf, and 1400gf, respectively.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.308-318
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• 2022

Noise is a serious issue. While sending images via electronic communication, Impulse noise, which is created by unsteady voltage, is one of the most common noises in digital communication. During the acquisition process, pictures were collected. It is possible to obtain accurate diagnosis images by removing these noises without affecting the edges and tiny features. The New Average High Noise Density Median Filter. (HNDMF) was proposed in this paper, and it operates in two steps for each pixel. Filter can decide whether the test pixels is degraded by SPN. In the first stage, a detector identifies corrupted pixels, in the second stage, an algorithm replaced by noise free processed pixel, the New average suggested Filter produced for this window. The paper examines the performance of Gaussian Filter (GF), Adaptive Median Filter (AMF), and PHDNF. In this paper the comparison of known image denoising is discussed and a new decision based weighted median filter used to remove impulse noise. Using Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), and Structure Similarity Index Method (SSIM) metrics, the paper examines the performance of Gaussian Filter (GF), Adaptive Median Filter (AMF), and PHDNF. A detailed simulation process is performed to ensure the betterment of the presented model on the Mini-MIAS dataset. The obtained experimental values stated that the HNDMF model has reached to a better performance with the maximum picture quality. images affected by various amounts of pretend salt and paper noise, as well as speckle noise, are calculated and provided as experimental results. According to quality metrics, the HNDMF Method produces a superior result than the existing filter method. Accurately detect and replace salt and pepper noise pixel values with mean and median value in images. The proposed method is to improve the median filter with a significant change.