• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1383-1386
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• 2003

In this paper, an ALU for Simultaneous Multi-Threading (SMT) microprocessors is designed. The SMT architecture improves notably performance and utilization of processes compared with conventional superscalar architectures by executing instructions from multiple threads at the same time. This ALU adopts data bypassing method to process multi-threads. And it can flush instructions in the same thread that generate exceptions such as branch misprediction. interrupt etc, performance of SMT microprocessors with data bypassing and exception handler can be improved.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.89.3-89
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• 2002

Plasma processing plays a crucial role in fabricating integrated circuits (ICs). Manufacturing ICs in a cost effective way, it is increasingly demanded a computer model that predicts plasma properties to unknown process inputs. Physical models are limited in the prediction accuracy since they are subject to many assumptions. Expensive computation time is another hindrance that prevents their widespread used in manufacturing site. To circumvent these difficulties inherent in physical models, neural networks have been used to learn nonlinear plasma data. A generalized regression neural network (GRNN) [I] is one of the architectures that have been widely used to analyze complex chemical data. I...

• Proceedings of the IEEK Conference
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• 2000.11b
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• pp.67-70
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• 2000

DSP is used for processing the digital data in such as the multimedia applications. Because the digital data of high rate is demanded more and more, high performance is increasingly required in DSP. In this paper, we discuss important issues for development of high performance DSP, analyze architectures of several commercial DSP chips, and propose a new architecture. Finally, we show that the new architecture has the highest performance.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 1995.11a
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• pp.79-88
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• 1995

Most works done so far have concentrated on developing data modeling techniques such as multi-level relation for data protection. These techniques, however, cannot be applied to practical area. This is because they require new queries or new architectures. In this paper, we propose a query processing technique for multi-level databases using horizontal partitioning and views, which does not need any change in database architecture and query language.

• Communications for Statistical Applications and Methods
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• v.30 no.3
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• pp.343-354
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• 2023

Recently, there have been many improvements in general language models using architectures such as GPT-3 proposed by Brown et al. (2020). Nevertheless, training complex models can hardly be done if the number of data is very small. Data augmentation that addressed this problem was more than normal success in image data. Image augmentation technology significantly improves model performance without any additional data or architectural changes (Perez and Wang, 2017). However, applying this technique to textual data has many challenges because the noise to be added is veiled. Thus, we have developed a novel method for performing data augmentation on text data. We divide the data into signals with positive or negative meaning and noise without them, and then perform data augmentation using k-doc augmentation to randomly combine signals and noises from all data to generate new data.

• The Transactions of the Korea Information Processing Society
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• v.4 no.6
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• pp.1589-1600
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• 1997

The construction of optical access network costs upper 40% in total installation cost of total optical network. Optimization of access network therefore is core in optical network. Advanced countries include EU, Japan and USA already have researched access network. This paper presents analysis of three broad-band fiber-optics subscriber loop architectures(HFC, ATM-PON, Super PON). The analyses focus on the specific demonstrated architectures and use component cost projections to estimate future network costs on a per-subscriber basis. We use TITAN(Tool for Introduction Scenarios and Techno-Economic Evaluation of The Access Network) model. We find that ATM-PON can deliver voice and ISDN data at installed first costs than the other architectures. This is due to the sharing bandwidth among a cluster of subscribers within Curb. This work intends to support establishing guidelines for strategic decisions regarding the development of the access network alternatives of different operators.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.8
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• pp.391-400
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• 2017

Software architecture plays a key role in satisfying non-functional requirement (NFR), i.e. quality requirements and constraints. Architecture design methods and tactics for conventional NFR are largely available in literatures. However, the methods for the target system-specific non-conventional NFRs are not readily available; rather architects should invent the design methods from their experiences and intuitions. Hence, the hardship to design architectures for non-conventional NFRs is quite high. In this paper, we provide a systematic architecture design methodology for non-conventional NFRs. We provide a five-step process, and detailed instructions for the steps. In the process, we treat the traceability among artifacts and seamlessness as essential values for supporting effective architecture design. We apply the methodology on designing architectures for a platform software system. We believe that the proposed methodology can be effectively utilized in designing high quality architectures for non-conventional NFRs.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.15 no.1
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• pp.97-105
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• 1997

In order to conserve architecture accurately as original feature, we need to get the data which is measured in detail about the information of size, position, type, shape, and other terms for architectures. Recently, we need to get data fast and correctly, to compose and to update the database of geographic information system, but using existing method. it is difficult to update the data effectively in the rapid development of information industry. In this study, therefore, It is measured precisely architecture using accurate close-range photogrammetry The aims of this study are real-measured plan by processing acquired image through multi-image matching method if photogrammetry, suggesting the method which is able to draw in detail front plane and plane of well-established architecture, and giving data to obtain accurate size and 3-D coordinate using analytical method.

• The KIPS Transactions:PartC
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• v.10C no.6
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• pp.809-814
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• 2003

The multicast transmitting the real-time data to groups may easily have many attacks from abnormal attacks because it has many links as compared to the unicast. The existing group key management architectures for preventing these problems are designed for protocols suitable for a large scale. Thus these architectures applied to a small scale routing protocols may have many overheads with key distribution and a constant core tree. Therefore this paper proposes a groups key management protocol for a secure multicast in PIM-SM multicast group communication. The proposed method divide multicast groups with RO(Rendezvous-Point), and subgroup key managers are established in each RP and can be transmitted groups keys between senders and receivers, so the security cannel is set up for secure data transfer, And this does not have needs of the data translation for group keys and the new key distribution for path change. As a result of this, the data transmission time can be reduced.

• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.807-817
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• 2019

Airborne Gamma Ray Spectrometry (AGRS) with its important applications such as gathering radiation information of ground surface, geochemistry measuring of the abundance of Potassium, Thorium and Uranium in outer earth layer, environmental and nuclear site surveillance has a key role in the field of nuclear science and human life. The Broyden-Fletcher-Goldfarb-Shanno (BFGS), with its advanced numerical unconstrained nonlinear optimization in collaboration with Artificial Neural Networks (ANNs) provides a noteworthy opportunity for modern AGRS. In this study a new AGRS system empowered by ANN-BFGS has been proposed and evaluated on available empirical AGRS data. To that effect different architectures of adaptive ANN-BFGS were implemented for a sort of published experimental AGRS outputs. The selected approach among of various training methods, with its low iteration cost and nondiagonal scaling allocation is a new powerful algorithm for AGRS data due to its inherent stochastic properties. Experiments were performed by different architectures and trainings, the selected scheme achieved the smallest number of epochs, the minimum Mean Square Error (MSE) and the maximum performance in compare with different types of optimization strategies and algorithms. The proposed method is capable to be implemented on a cost effective and minimum electronic equipment to present its real-time process, which will let it to be used on board a light Unmanned Aerial Vehicle (UAV). The advanced adaptation properties and models of neural network, the training of stochastic process and its implementation on DSP outstands an affordable, reliable and low cost AGRS design. The main outcome of the study shows this method increases the quality of curvature information of AGRS data while cost of the algorithm is reduced in each iteration so the proposed ANN-BFGS is a trustworthy appropriate model for Gamma-ray data reconstruction and analysis based on advanced novel artificial intelligence systems.