• Journal of Korean Society of Coastal and Ocean Engineers
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• v.4 no.1
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• pp.34-44
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• 1992

A numerical model using Hybrid Element Method(HEM) is presented for the prediction of wave agitations in a harbor which are induced by the intrusion and transformation of incident short-period waves. A linear mild-slope equation including bottom friction is used as the governing equation and a partial absorbing boundary condition is used on solid boundaries. Functional derived in the present paper is based on the Chen and Mei(1974)'s concept which uses finite element net in the inner region and analytical solution of Helmholtz equation in the outer region. Final simultaneous equations are solved using the Gaussian Elimination Method. The model appears to be reasonably good from the comparison of numerical calculation with hydraulic experimental results of short-wave diffraction through a breakwater gap(Pos and Kilner, 1987). The problem of requring large computational memory could be overcome using 8-noded isoparametric elements.

• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.795-802
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• 2003

To live autonomously, intelligent agents such as robots or virtual characters need ability that recognizes given environment, and learns and chooses adaptive actions. So, we propose an action selection/learning mechanism in intelligent agents. The proposed mechanism employs a hybrid system which integrates a behavior-based method using the reinforcement learning and a cognitive-based method using the symbolic learning. The characteristics of our mechanism are as follows. First, because it learns adaptive actions about environment using reinforcement learning, our agents have flexibility about environmental changes. Second, because it learns environmental factors for the agent's goals using inductive machine learning and association rules, the agent learns and selects appropriate actions faster in given surrounding and more efficiently in extended surroundings. Third, in implementing the intelligent agents, we considers only the recognized states which are found by a state detector rather than by all states. Because this method consider only necessary states, we can reduce the space of memory. And because it represents and processes new states dynamically, we can cope with the change of environment spontaneously.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.12
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• pp.4997-5006
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• 2010

A flash-memory-based SSDs(Solid State Disks) are one of the best media to support portable and desktop computers' storage devices. Their features include non-volatility, low power consumption, and fast access time for read operations, which are sufficient to present flash memories as major database storage components for desktop and server computers. However, we need to improve traditional storage management schemes based on HDD(Hard Disk Drive) and RAID(Redundant array of independent disks) due to the relatively slow or freezing characteristics of write operations of SSDs, as compared to fast read operations. In order to achieve this goal, we propose a new storage management scheme called Hetero-Mirroring based on traditional HDD mirroring scheme. Hetero-Mirroring-based scheme improves RAID-1 operation performance by balancing write-workloads and delaying write operations to avoid SSD freezing. Our test results show that our scheme significantly reduces the write operation overheads and freezing overheads, and improves the performance of traditional SSD-RAID-1 scheme by 18 percent, and the response time of the scheme by 38 percent.

• Journal of Information Processing Systems
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• v.12 no.4
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• pp.688-710
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• 2016

Our approach permits to capitalize the expert's knowledge as business rules by using an agent-based platform. The objective of our approach is to allow experts to manage the daily evolutions of business domains without having to use a technician, and to allow them to be implied, and to participate in the development of the application to accomplish the daily tasks of their work. Therefore, the manipulation of an expert's knowledge generates the need for information security and other associated technologies. The notion of cryptography has emerged as a basic concept in business rules modeling. The purpose of this paper is to present a cryptographic algorithm based approach to integrate the security aspect in business rules modeling. We propose integrating an agent-based approach in the framework. This solution utilizes a security agent with domain ontology. This agent applies an encryption/decryption algorithm to allow for the confidentiality, authenticity, and integrity of the most important rules. To increase the security of these rules, we used hybrid cryptography in order to take advantage of symmetric and asymmetric algorithms. We performed some experiments to find the best encryption algorithm, which provides improvement in terms of response time, space memory, and security.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.393-405
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• 2023

Accurate prediction of wind speed and power is vital for enhancing the efficiency of wind energy systems. Numerous solutions have been implemented to date, demonstrating their potential to improve forecasting. Among these, deep learning is perceived as a revolutionary approach in the field. However, despite their effectiveness, the noise present in the collected data remains a significant challenge. This noise has the potential to diminish the performance of these algorithms, leading to inaccurate predictions. In response to this, this study explores a novel feature engineering approach. This approach involves altering the data input shape in both Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) and Autoregressive models for various forecasting horizons. The results reveal substantial enhancements in model resilience against noise resulting from step increases in data. The approach could achieve an impressive 83% accuracy in predicting unseen data up to the 24th steps. Furthermore, this method consistently provides high accuracy for short, mid, and long-term forecasts, outperforming the performance of individual models. These findings pave the way for further research on noise reduction strategies at different forecasting horizons through shape-wise feature engineering.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.08a
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• pp.114-114
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• 2012

Even though graphene was introduced with a great hope to replace silicon in future, small (or zero) band gap and poor stability have become major challenges in graphene electronics. Especially, rectification and amplification function which are the elemental functions of silicon device, is very difficult to implement without a bandgap. However, the graphene can still be used in many other device applications if the merits of graphene are creatively utilized. For example, graphene can be applied to almost any kind of substrate. Its conductivity can be varied in some degree using electric field, charge dipole, attached molecules, and many other ways. Recently, graphene stacked with ferroelectric materials or piezoelectric materials has been actively studied for various device applications. In this talk, various device applications of graphene using hybrid stack or novel device structure will be introduced and their prospect will be discussed.

• Journal of Computing Science and Engineering
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• v.5 no.2
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• pp.121-130
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• 2011

Recent research indicates that transient errors will increasingly become a critical concern in microprocessor design. As embedded processors are widely used in reliability-critical or noisy environments, it is necessary to develop cost-effective fault-tolerant techniques to protect processors against transient errors. The register file is one of the critical components that can significantly affect microprocessor system reliability, since registers are typically accessed very frequently, and transient errors in registers can be easily propagated to functional units or the memory system, leading to silent data error (SDC) or system crash. This paper focuses on investigating the impact of register file soft errors on system reliability and developing cost-effective techniques to improve the register file immunity to soft errors. This paper proposes the register vulnerability factor (RVF) concept to characterize the probability that register transient errors can escape the register file and thus potentially affect system reliability. We propose an approach to compute the RVF based on register access patterns. In this paper, we also propose two compiler-directed techniques and a hybrid approach to improve register file reliability cost-effectively by lowering the RVF value. Our experiments indicate that on average, RVF can be reduced to 9.1% and 9.5% by the hyperblock-based instruction re-scheduling and the reliability-oriented register assignment respectively, which can potentially lower the reliability cost significantly, without sacrificing the register value integrity.

• Earthquakes and Structures
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• v.25 no.5
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• pp.343-358
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• 2023

The superelastic viscous damper (SVD) is a hybrid passive control device comprising a viscoelastic damper and shape memory alloy (SMA) cables connected in series. The SVD is an innovative damper through which a large amount of seismic energy can dissipate. The current study assessed the seismic collapse induced by steel moment-resisting frames (SMRFs) equipped with SVDs and compared them with the performance of special MRFs and buckling restrained brace frames (BRBFs). For this purpose, nonlinear dynamic and incremental dynamic analysis (IDA) were conducted in OpenSees software. Both 5- and 9-story special MRFs, BRBFs, and MRFs equipped with the SVDs were examined. The results indicated that the annual exceedance rate for maximum residual drifts of 0.2% and 0.5% for the BRBFs and MRFs with SVDs, respectively, were considerably less than for SMRFs with reduced-beam section (RBS) connections and that the seismic performances of these structures were enhanced with the use of the BRB and SVD. The probability of collapse due to residual drift in the SVD, BRB, and RBS frames in the 9-story structure was 1.45, 1.75, and 1.05 times greater than for the 5-story frame.

• Wind and Structures
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• v.38 no.6
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• pp.461-475
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• 2024

A reliable wind speed forecasting method is crucial for the applications in wind engineering. In this study, the generalized S-transform (GST) is innovatively applied for wind speed forecasting to uncover the time-frequency characteristics in the non-stationary wind speed data. The improved grey wolf optimizer (IGWO) is employed to optimize the adjustable parameters of GST to obtain the best time-frequency resolution. Then a hybrid method based on IGWO-optimized GST is proposed to validate the effectiveness and superiority for multi-step non-stationary wind speed forecasting. The historical wind speed is chosen as the first input feature, while the dynamic time-frequency characteristics obtained by IGWO-optimized GST are chosen as the second input feature. Comparative experiment with six competitors is conducted to demonstrate the best performance of the proposed method in terms of prediction accuracy and stability. The superiority of the GST compared to other time-frequency analysis methods is also discussed by another experiment. It can be concluded that the introduction of IGWO-optimized GST can deeply exploit the time-frequency characteristics and effectively improving the prediction accuracy.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.253-256
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• 2009

This paper describes a core generator (FFT_Core_Gen) which generates Verilog HDL models of 8 different FFT/IFFT cores with $N=64{\times}2^k$($0{\leq}k{\leq}7$ for OFDM-based communication systems. The generated FFT/IFFT cores are based on in-place single memory architecture, and use a hybrid structure of radix-4 and radix-2 DIF algorithm to accommodate various FFT lengths. To achieve both memory reduction and the improved SQNR, a conditional scaling technique is adopted, which conditionally scales the intermediate results of each computational stage, and the internal data and twiddle factor has 14 bits. The generated FFT/IFFT cores have the SQNR of 58-dB for N=8,192 and 63-dB for N=64. The cores synthesized with a $0.35-{\mu}m$ CMOS standard cell library can operate with 75-MHz@3.3-V, and a 8,192-point FFT can be computed in $762.7-{\mu}s$, thus the cores satisfy the specifications of wireless LAN, DMB, and DVB systems.