• Proceedings of the Korea Concrete Institute Conference
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• 2008.04a
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• pp.129-132
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• 2008

Coupled shear wall system is the primary seismic load resisting system of buildings. The coupling beam of these buildings must exhibit excellent ductility and energy dissipation capacity. To achieve better ductility and energy dissipation, the steel coupling beam embedded in the reinforced concrete walls is proposed. Performance of the steel coupling beam is mainly effected by embedment length. ACI equation and BS equation were examined with 23 previous test results. The statistical study uses the values of mean value, standard deviation, correlation coefficient, normal distribution curve, and error analysis. Through the analytical program, the evaluation of the 2 equations was established.

• Journal of Convergence for Information Technology
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• v.10 no.8
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• pp.35-39
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• 2020

DNN error is small compared to the conventional speech recognition system, DNN is difficult to parallel training, often the amount of calculations, and requires a large amount of data obtained. In this paper, we generate a phoneme unit to estimate the GMM parameters with each phoneme model parameters from the GMM to solve the problem efficiently. And it suggests ways to improve performance through clustering for a specific vocabulary to effectively apply them. To this end, using three types of word speech database was to have a DB build vocabulary model, the noise processing to extract feature with Warner filters were used in the speech recognition experiments. Results using the proposed method showed a 97.9% recognition rate in speech recognition. In this paper, additional studies are needed to improve the problems of improved over fitting.

• Journal of Digital Convergence
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• v.17 no.12
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• pp.197-202
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• 2019

In line with the era of the 4th Industrial Revolution, 5G technology has become common technology, and 5G technology is evaluated as a technology that minimizes the speed and response speed compared to 4G using technologies such as network slicing and ultra-multiple access. 5G NR stands for 5G mobile communication standard, and network slicing cuts the network into parallel connections to optimize the network. In addition, the risk of hacking is increasing as data is processed in the base station unit. In addition, since the number of accessible devices per unit area increases exponentially, there is a possibility of base station attack after hacking a large number of devices in the unit area. To solve this problem, this study proposes the introduction of quantum cryptography and 5G security standardization.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.9A
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• pp.1359-1367
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• 2000

A new coherent detection scheme with data based channel estimation (DBCE) for CDMA/BP(staggered burst pilot in parallel) channel structure is proposed. Because the pilot burst initiates DBCE operation periodically it is shown to be remarkably stable to Gaussian noise and Doppler shift with proper parameter settings. In our own system parameter setting, there is a negligible loss(0.068 dB) in $E_{b}/N_{o}$ by the introduction of the burst pilot. When compared with an ideal coherent detection, the required $E_{b}/N_{o}$ on Doppler shift corresponding to the speed of 160Km/H is degraded less that 2.0 dB. the burst pilot can be implemented without complexity even though some extra correlators are needed for DBCE. This improvement is superior to the previously coherent CDMA detectors with external or internal pilot.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.10
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• pp.573-581
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• 2002

In this paper, we propose a mediaprocessor of dual-cache architecture which is composed of the multimedia data cache and the general-purpose data cache to prevent performance degradation caused by memory delay. In the proposed processor architecture, multimedia data that are written in subword instructions are loaded in the multimedia data cache and the remaining data are loaded in the general-purpose data cache. Also, Ive use multi-block prefetching scheme that fetches two consecutive data blocks into a cache at a time to exploit the locality of multimedia data. Experimental results on MPEG and JPEG benchmark programs show that the proposed processor architecture results in better performance than the processor equipped with single data cache.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.4
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• pp.300-308
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• 2019

For drones to be used for industrial or agricultural applications, it is necessary to increase the payload and endurance. Currently, the payload and endurance are limited by the battery technology for electric powered drones. In addition, charging or replacing the batteries may not be a practical solution at the field that requires near continuous operation. In this paper, a procedure to optimize the power system of an electric hybrid drone that consists of an internal combustion engine, a generator, a battery, and electric motors is presented. The example drone for crop dusting is sized for easy transportation with a maximum takeoff weight of 200 kg. The two main rotors that are mechanically connected to the internal combustion engine provides most of the lift. The drone is controled by four electric motors that are driven by the generator. By analyzing the flow of the energy, a methodology to select the optimum propeller and motor among the commercially available models is described. Then, a procedure of finding the optimum operational condition along with the proper gear reduction ratios for the internal combustion engine based on the test data is presented.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.11
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• pp.1318-1332
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• 1999

본 논문에서는 입출력 응용을 위해 collective I/O 기법을 기반으로 한 실행시간 시스템의 설계, 구현 그리고 그 성능평가를 기술한다. 여기서는 모든 프로세서가 동시에 I/O 요구에 따라 스케쥴링하며 I/O를 수행하는 collective I/O 방안과 프로세서들이 여러 그룹으로 묶이어, 다음 그룹이 데이터를 재배열하는 통신을 수행하는 동안 오직 한 그룹만이 동시에 I/O를 수행하는 pipelined collective I/O 등의 두 가지 설계방안을 살펴본다. Pipelined collective I/O의 전체 과정은 I/O 노드 충돌을 동적으로 줄이기 위해 파이프라인된다. 이상의 설계 부분에서는 동적으로 충돌 관리를 위한 지원을 제공한다. 본 논문에서는 다른 노드의 메모리 영역에 이미 존재하는 데이터를 재 사용하여 I/O 비용을 줄이기 위해 collective I/O 방안에서의 소프트웨어 캐슁 방안과 두 가지 모형에서의 chunking과 온라인 압축방안을 기술한다. 그리고 이상에서 기술한 방안들이 입출력을 위해 높은 성능을 보임을 기술하는데, 이 성능결과는 Intel Paragon과 ASCI/Red teraflops 기계 상에서 실험한 것이다. 그 결과 응용 레벨에서의 bandwidth는 peak point가 55%까지 측정되었다.Abstract In this paper we present the design, implementation and evaluation of a runtime system based on collective I/O techniques for irregular applications. We present two designs, namely, "Collective I/O" and "Pipelined Collective I/O". In the first scheme, all processors participate in the I/O simultaneously, making scheduling of I/O requests simpler but creating a possibility of contention at the I/O nodes. In the second approach, processors are grouped into several groups, so that only one group performs I/O simultaneously, while the next group performs communication to rearrange data, and this entire process is pipelined to reduce I/O node contention dynamically. In other words, the design provides support for dynamic contention management. Then we present a software caching method using collective I/O to reduce I/O cost by reusing data already present in the memory of other nodes. Finally, chunking and on-line compression mechanisms are included in both models. We demonstrate that we can obtain significantly high-performance for I/O above what has been possible so far. The performance results are presented on an Intel Paragon and on the ASCI/Red teraflops machine. Application level I/O bandwidth up to 55% of the peak is observed.he peak is observed.

• Journal of KIISE:Software and Applications
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• v.34 no.12
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• pp.1045-1055
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• 2007

Latent topic models are statistical models which automatically captures salient patterns or correlation among features underlying a data collection in a probabilistic way. They are gaining an increased popularity as an effective tool in the application of automatic semantic feature extraction from text corpus, multimedia data analysis including image data, and bioinformatics. Among the important issues for the effectiveness in the application of latent topic models to the massive data set is the efficient learning of the model. The paper proposes an accelerated learning technique for PLSA model, one of the popular latent topic models, by an incremental EM algorithm instead of conventional EM algorithm. The incremental EM algorithm can be characterized by the employment of a series of partial E-steps that are performed on the corresponding subsets of the entire data collection, unlike in the conventional EM algorithm where one batch E-step is done for the whole data set. By the replacement of a single batch E-M step with a series of partial E-steps and M-steps, the inference result for the previous data subset can be directly reflected to the next inference process, which can enhance the learning speed for the entire data set. The algorithm is advantageous also in that it is guaranteed to converge to a local maximum solution and can be easily implemented just with slight modification of the existing algorithm based on the conventional EM. We present the basic application of the incremental EM algorithm to the learning of PLSA and empirically evaluate the acceleration performance with several possible data partitioning methods for the practical application. The experimental results on a real-world news data set show that the proposed approach can accomplish a meaningful enhancement of the convergence rate in the learning of latent topic model. Additionally, we present an interesting result which supports a possible synergistic effect of the combination of incremental EM algorithm with parallel computing.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.16 no.12 s.103
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• pp.1229-1238
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• 2005

OFDM(Orthogonal Frequency Division Multiplexing) communications system is very attractive for the high data rate wireless transmission. However, it may be distorted in the nonlinear HPA(High Power Amplifier) since OFDM signal has hish PAPR(Peak-to-Average Power Ratio). In this paper, a new method using control tone is studied for reducing the PAPR and we call it PCT(PAPR Control Tone) method. This proposed PCT method is to assign control tones for PAPR reduction at the predefined sub-carriers. After IFFT(Inverse Fast Fourier Transform) and PAPR calculation, the OFDM data signal of the lowest PAPR is selected to transmit. Unlike the conventional method, it can cut down the computational complexity because it does not require the transmission and demodulation process of side information about the phase rotation. Furthermore, if this method is made up in parallel configuration, it can solve the time delay problem so that it can be processed in real time processing. This proposed method is compared with the conventional selected mapping(SLM) technique. We find out the PAPR reduction performance and BER when the number of control tone is 6 and nonlinear HPA is considered.

• Tunnel and Underground Space
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• v.31 no.1
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• pp.10-24
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• 2021

Rock mass classification for construction of underground facilities is essential to secure their stabilities. Therefore, the reliable values for rock mass classification from the precise information on rock discontinuities are most important factors, because rock mass discontinuities can affect exclusively on the physical and mechanical properties of rock mass. The conventional classification operation for rock mass has been usually performed by hand mapping. However, there have been many issues for its precision and reliability; for instance, in large-scale survey area for regional geological survey, or rock mass classification operation by non-professional engineers. For these reasons, automated rock mass classification using LiDAR becomes popular for obtaining the quick and precise information. But there are several suggested algorithms for analyzing the rock mass discontinuities from point cloud data by LiDAR scanning, and it is known that the different algorithm gives usually different solution. Also, it is not simple to obtain the exact same value to hand mapping. In this paper, several discontinuity extract algorithms have been explained, and their processes for extracting rock mass discontinuities have been simulated for real rock bench. The application process for several algorithms is anticipated to be a good reference for future researches on extracting rock mass discontinuities from digital point cloud data by laser scanner, such as LiDAR.