• Journal of Korea Society of Industrial Information Systems
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• v.13 no.1
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• pp.46-56
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• 2008

Double Patching is a multicasting technique for a VoD system which has been proposed to provide a true VoD service by making clients share a long patching stream as well as a regular stream For subsequent short patching streams, the technique always makes the long patching stream have extra data that will be played back during a double period of a patching window. In this paper, we propose a technique, using the start time of the latest short patching stream, optimizes Double Patching by deleting the useless data included in the long patching stream when the patching window of the long patching stream closes. The mean requirement for the server's bandwidth to provide the true VoD service is used as a performance metric, and the effect of the request inter-arrival time, the size of the client's local buffer and the video length on the mean bandwidth requirement is evaluated. Performance evaluation result shows that the proposed technique optimizes Double Patching in all cases.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.3
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• pp.495-504
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• 2012

This paper presents various speed optimization techniques for software implementation of the HIGHT block cipher on CPUs and GPUs. We considered 32-bit and 64-bit operating systems for CPU implementations. After we applied the bit-slicing and byte-slicing techniques to HIGHT, the encryption speed recorded 1.48Gbps over the intel core i7 920 CPU with a 64-bit operating system, which is up to 2.4 times faster than the previous implementation. We also implemented HIGHT on an NVIDIA GPU equipped with CUDA, and applied various optimization techniques, such as storing most frequently used data like subkeys and the F lookup table in the shared memory; and using coalesced access when reading data from the global memory. To our knowledge, this is the first result that implements and optimizes HIGHT on a GPU. We verified that the byte-slicing technique guarantees a speed-up of more than 20%, resulting a speed which is 31 times faster than that on a CPU.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10e
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• pp.397-399
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• 2002

유선망에 최적화되도록 진화해온 TCP는 무선망이 가지는 링크의 불안정함으로 인한 손실을 네트워크의 혼잡으로 인한 손실로 오해한다. 그 결과 혼잡 제어 메커니즘이 수행되어 전송율을 줄이므로 네트워크 성능이 저하되는 문제점을 초래한다. 이러한 이유로 최근 유ㆍ무선 혼합망에서 TCP의 성능을 향상시키기 위한 연구가 활발히 이루어지고 있다. 본 논문에서는 기존에 제안된 기법들 중 상대적으로 뛰어난 성능 향상을 보이는 snoop protocol이 유ㆍ무선 혼합망 특히 CDMA망에서 가지는 문제점을 분석하고 이를 보완하는 기법을 제안한다.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.615-619
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• 2021

This study focuses on memory systems that are optimized to increase performance and energy efficiency in many embedded systems such as IoT, cloud computing, and edge computing, and proposes a performance improvement technique. The proposed technique improves memory system performance based on machine learning algorithms that are widely used in many applications. The machine learning technique can be used for various applications through supervised learning, and can be applied to a data classification task used in improving memory system performance. Data classification based on highly accurate machine learning techniques enables data to be appropriately arranged according to data usage patterns, thereby improving overall system performance.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.3
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• pp.215-221
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• 2012

In this paper, we introduce an optimization method to improve pursuit performance of a pursuer in a pursuit-evasion game (PEG). Pursuers build a probability map and employ a hybrid pursuit policy which combines the merits of local-max and global-max pursuit policies to search and capture evaders as soon as possible in a 2-dimensional space. We propose an episodic parameter optimization (EPO) algorithm to learn good values for the weighting parameters of a hybrid pursuit policy. The EPO algorithm is performed while many episodes of the PEG are run repeatedly and the reward of each episode is accumulated using reinforcement learning, and the candidate weighting parameter is selected in a way that maximizes the total averaged reward by using the golden section search method. We found the best pursuit policy in various situations which are the different number of evaders and the different size of spaces and analyzed results.

• The Journal of the Acoustical Society of Korea
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• v.29 no.1
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• pp.56-61
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• 2010

This paper describes optimization methods of acoustic models in HMM-based continuous speech recognition. Most of the conventional speech recognition systems use the same number of Gaussian mixture components for each HMM state. However, since the number of data samples available for each state is different from each other, it is possible to reduce the overall number of model parameters and the computational cost at the decoding step by optimizing the number of Gaussian mixture components. In this study, we introduced the Gaussian mixture weight term at the merging stage of Gaussian components in the minimum description length (MDL) based acoustic modeling optimization. Experimental results showed that the proposed method can obtain better ASR accuracy than the previous optimization method which does not consider the Gaussian mixture weight term.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.217-217
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• 2023

상수도관망은 사용자에게 고품질의 물을 안정적으로 공급하는 것을 목적으로 하며, 이를 평가하기 위한 지표 중 하나로 압력을 활용한다. 최근 스마트 센서의 설치가 확장됨에 따라 기계학습기법을 이용한 실시간 데이터 기반의 분석이 활발하다. 따라서 어디에서 데이터를 수집하느냐에 대한 센서 위치 결정이 중요하다. 본 연구는 eXtreme Gradient Boosting(XGBoost) 모델을 활용하여 대규모 상수도관망 내 센서 위치를 최적화하는 방법론을 제안한다. XGBoost 모델은 여러 의사결정 나무(decision tree)를 활용하는 앙상블(ensemble) 모델이며, 오차에 따른 가중치를 부여하여 성능을 향상시키는 부스팅(boosting) 방식을 이용한다. 이는 분산 및 병렬 처리가 가능해 메모리리소스를 최적으로 사용하고, 학습 속도가 빠르며 결측치에 대한 전처리 과정을 모델 내에 포함하고 있다는 장점이 있다. 모델 구현을 위한 독립 변수 결정을 위해 압력 데이터의 변동성 및 평균압력 값을 고려하여 상수도관망을 대표하는 중요 절점(critical node)를 선정한다. 중요 절점의 압력 값을 예측하는 XGBoost 모델을 구축하고 모델의 성능과 요인 중요도(feature importance) 값을 고려하여 센서의 최적 위치를 선정한다. 이러한 방법론을 기반으로 상수도관망의 특성에 따른 경향성을 파악하기 위해 다양한 형태(예를 들어, 망형, 가지형)와 구성 절점의 수를 변화시키며 결과를 분석한다. 본 연구에서 구축한 XGBoost 모델은 추가적인 전처리 과정을 최소화하며 대규모 관망에 간편하게 사용할 수 있어 추후 다양한 입출력 데이터의 조합을 통해 센서 위치 외에도 상수도관망에서의 성능 최적화에 활용할 수 있을 것으로 기대한다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.8
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• pp.695-702
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• 2012

In this study, Multi-fidelity analysis is performed to improve the accuracy of analysis result during conceptual design stage. Multidisciplinary Design Optimization(MDO) method is also considered to satisfy the total system requirements. Low-fidelity analysis codes which are based on empirical equations are developed and validated for analyzing the Unmanned Aerial Vehicle(UAV) which have unconventional configurations. Analysis codes consist of initial sizing, aerodynamics, propulsion, mission, weight, performance, and stability modules. Design synthesis program which is composed of those modules is developed. To improve the accuracy of the design method for UAV, Vortex Lattice Method is used for the strategy of MFA. Multi-Disciplinary Feasible(MDF) method is used for MDO technique. To demonstrate the validity of presented method, the optimization results of both methods are compared. According to those results, the presented method is demonstrated to be applicable to improve the accuracy of the analyses during conceptual design stage.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.05a
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• pp.871-874
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• 2008

이동성을 제공하기 위한 프로토콜 중 오랜 기간 많은 연구로 표준화가 된 Mobile IPv6 (MIPv6)가 있다. MIPv6는 호스트 기반 이동성 제공 프로토콜로서 이동 단말이 이동성에 필요한 시그널링을 직접수행한다. 한편, 최근에 표준화 작업이 진행 중인 Proxy Mobile IPv6 (PMIPv6)는 네트워크 기반 이동성 제공 프로토콜로서 이동 단말이 아닌 네트워크 자체에서 이동성을 제공한다. PMIPv6는 MIPv6에서 Home Agent와 같은 역할을 하는 Local Mobility Anchor 와 이동 단말이 수행하던 시그널링을 대신하는 Mobile Access Gateway를 정의하여 이동성을 제공한다. PMIPv6의 기본 동작 과정에 대한 표준화가 진행됨에 따라 프로토콜의 최적화에 대한 이슈가 부각되고 있다. Route Optimization은 이러한 최적화 이슈 중 하나로서 패킷 전송 시 최적화 된 경로를 설정하고 발생할 수 있는 전송 지연을 최소화하는 기법이다. 본 논문에서는 PMIPv6에서의 Route Optimization을 적용하기 위해 Liebesch 인터넷 드래프트에서 제안 한 기법의 동작 과정을 살펴보고 PMIPv6의 기본 전송 과정과 비교하여 그 성능을 분석하였다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.9
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• pp.691-701
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• 2020

An actuator mixer design using convex optimization technique situation where the propulsion system of an electric VTOL UAV during vertical take-off and landing maneuvers is proposed. The attainable control set to analyze the impact from failure of each motor and propeller can be calculated and illustrated using the properties of the convex function. The control allocation can be defined as a convex function optimization problem to obtain an optimal solution in real time. The mixer is implemented using a convex optimization solver, and the performance of the control allocation methods is compared to the attainable control set. Finally, the proposed mixer is compared with other techniques with nonlinear sux degree-of-freedom simulation.