• The Korean Journal of Applied Statistics
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• v.35 no.1
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• pp.63-75
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• 2022

This paper proposes the so-called MOSUM-based sparse projection method for change points detection in high-dimensional time series. Our method is inspired by Wang and Samworth (2018), however, our method improves their method in two ways. One is to find change points all at once, so it minimizes sequential error. The other is localized so that more robust to the mean changes offsetting each other. We also propose data-driven threshold selection using block wild bootstrap. A comprehensive simulation study shows that our method performs reasonably well in finite samples. We also illustrate our method to stock prices consisting of S&P 500 index, and found four change points in recent 6 years.

• The Journal of Korea Robotics Society
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• v.17 no.1
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• pp.76-85
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• 2022

One of the most fundamental challenges when designing controllers for dynamic systems is the adjustment of controller parameters. Usually the system model is used to get the initial controller, but eventually the controller parameters must be manually adjusted in the real system to achieve the best performance. To avoid this manual tuning step, data-driven methods such as machine learning were used. Recently, reinforcement learning became one alternative of this problem to be considered as an agent learns policies in large state space with trial-and-error Markov Decision Process (MDP) which is widely used in the field of robotics. However, on initial training step, as an agent tries to explore to the new state space with random action and acts directly on the controller parameters in real systems, MDP can lead the system safety-critical system failures. Therefore, the issue of 'safe exploration' became important. In this paper we meet 'safe exploration' condition with Control Barrier Function (CBF) which converts direct constraints on the state space to the implicit constraint of the control inputs. Given an initial low-performance controller, it automatically optimizes the parameters of the control law while ensuring safety by the CBF so that the agent can learn how to predict and control unknown and often stochastic environments. Simulation results on a quadrotor UAV indicate that the proposed method can safely optimize controller parameters quickly and automatically.

• The Transactions of the Korea Information Processing Society
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• v.3 no.1
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• pp.118-126
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• 1996

Memory hierarchy is a useful mechanism for improving the memory access speed and making the program space larger by layering the memories and separating program spaces from memory spaces. However, it needs at least two memory accesses for each data reference : a TLB(Translation Lookaside Buffer) access for the address translation and a data cache access for the desired data. If the cache size increases to the multiplication of page size and the cache associativity, it is difficult to access the TLB with the cache in parallel, thereby making longer the critical timing path in the processor. To achieve such parallel accesses, we present the hybrid mapped TLB which combines a direct mapped TLB with a very small fully-associative mapped TLB. The former can reduce the TLB access time. while the latter removes the conflict misses from the former. The trace-driven simulation shows that under given workloads the proposed TLB is effective even when a fully-associative mapped TLB with only four entries is added because the effects of its increased misses are offset by its speed benefits.

• Journal of the Institute of Convergence Signal Processing
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• v.17 no.1
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• pp.46-52
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• 2016

LTE-Advanced system consisting of the number of cells in the cellular environment because it is built to allow efficient use of limited frequency resources of adjacent cell interference avoidance should be considered. Transition services in accordance with the development of the mobile communication technology, wireless multimedia content from voice-centric mobile communications services and causing a lot of mobile data traffic, such as smart phones and tablet terminals spread of a data-driven surge in mobile data traffic base stations in urban areas by increasing became a reality that can not be prevented. In this paper, we propose a new Hybrid resource allocation technique for improving the performance of the cell boundary and analyzed the performance of the proposed new techniques to perform the simulation using LTE-Advanced system level simulator based on 19cell of cellular system model.

• Journal of the Korea Computer Graphics Society
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• v.29 no.4
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• pp.7-16
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• 2023

For decades, creating a desired locomotive motion in a goal-oriented manner has been a challenge in character animation. Data-driven methods using generative models have demonstrated efficient ways of predicting long sequences of motions without the need for explicit conditioning. While these methods produce high-quality long-term motions, they can be limited when it comes to synthesizing motion for challenging novel scenarios, such as punching a random target. A state-of-the-art solution to overcome this limitation is by using a GAN Discriminator to imitate motion data clips and incorporating reinforcement learning to compose goal-oriented motions. In this paper, our research aims to create characters performing combat sports such as boxing, using a novel reward design in conjunction with existing GAN-based approaches. We experimentally demonstrate that both the Adversarial Motion Prior [3] and Adversarial Skill Embeddings [4] methods are capable of generating viable motions for a character punching a random target, even in the absence of mocap data that specifically captures the transition between punching and locomotion. Also, with a single learned policy, multiple task controllers can be constructed through the TimeChamber framework.

• Smart Structures and Systems
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• v.32 no.5
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• pp.319-338
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• 2023

The study presents a new hybrid data-driven method by combining radial basis functions neural networks (RBF-NN) with the Jaya algorithm (JA) to provide effective structural health monitoring of arch dams. The novelty of this approach lies in that only one user-defined parameter is required and thus can increase its effectiveness and efficiency, as compared to other machine learning techniques that often require processing a large amount of training and testing model parameters and hyper-parameters, with high time-consuming. This approach seeks rapid damage detection in arch dams under dynamic conditions, to prevent potential disasters, by utilizing the RBF-NNN to seamlessly integrate the dynamic elastic modulus (DEM) and modal parameters (such as natural frequency and mode shape) as damage indicators. To determine the dynamic characteristics of the arch dam, the JA sequentially optimizes an objective function rooted in vibration-based data sets. Two case studies of hyperbolic concrete arch dams were carefully designed using finite element simulation to demonstrate the effectiveness of the RBF-NN model, in conjunction with the Jaya algorithm. The testing results demonstrated that the proposed methods could exhibit significant computational time-savings, while effectively detecting damage in arch dam structures with complex nonlinearities. Furthermore, despite training data contaminated with a high level of noise, the RBF-NN and JA fusion remained the robustness, with high accuracy.

• Convergence Security Journal
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• v.23 no.5
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• pp.45-55
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• 2023

With the widespread use of digital devices, anonymous communication technologies such as the dark web and deep web are becoming increasingly popular for criminal activity. Because these technologies leave little local data on the device, they are difficult to track using conventional crime investigation techniques. The United States and the United Kingdom have enacted laws and developed systems to address this issue, but South Korea has not yet taken any significant steps. This paper proposes a new blockchain-based crime investigation method that uses physical memory data analysis to track the behavior of anonymous network users. The proposed method minimizes infringement of basic rights by only collecting physical memory data from the device of the suspected user and storing the tracking information on a blockchain, which is tamper-proof and transparent. The paper evaluates the effectiveness of the proposed method using a simulation environment and finds that it can track the behavior of dark website users with a residual rate of 77.2%.

• Journal of The Korean Astronomical Society
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• v.37 no.5
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• pp.427-431
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• 2004

We use simulations of large-scale structure formation to study the build-up of magnetic fields (MFs) in the intergalactic medium. Our basic assumption is that cosmological MFs grow in a magnetohy-drodynamical (MHD) amplification process driven by structure formation out of a magnetic seed field present at high redshift. This approach is motivated by previous simulations of the MFs in galaxy clusters which, under the same hypothesis that we adopt here, succeeded in reproducing Faraday rotation measurements (RMs) in clusters of galaxies. Our ACDM initial conditions for the dark matter density fluctuations have been statistically constrained by the observed large-scale density field within a sphere of 110 Mpc around the Milky Way, based on the IRAS 1.2-Jy all-sky redshift survey. As a result, the positions and masses of prominent galaxy clusters in our simulation coincide closely with their real counterparts in the Local Universe. We find excellent agreement between RMs of our simulated galaxy clusters and observational data. The improved numerical resolution of our simulations compared to previous work also allows us to study the MF in large-scale filaments, sheets and voids. By tracing the propagation of ultra high energy (UHE) protons in the simulated MF we construct full-sky maps of expected deflection angles of protons with arrival energies $E = 10^{20}\;eV$ and $4 {\times} 10^{19}\;eV$, respectively. Accounting only for the structures within 110 Mpc, we find that strong deflections are only produced if UHE protons cross galaxy clusters. The total area on the sky covered by these structures is however very small. Over still larger distances, multiple crossings of sheets and filaments may give rise to noticeable deflections over a significant fraction of the sky; the exact amount and angular distribution depends on the model adopted for the magnetic seed field. Based on our results we argue that over a large fraction of the sky the deflections are likely to remain smaller than the present experimental angular sensitivity. Therefore, we conclude that forthcoming air shower experiments should be able to locate sources of UHE protons and shed more light on the nature of cosmological MFs.

• Journal of The Korean Society of Agricultural Engineers
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• v.52 no.3
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• pp.97-104
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• 2010

The purpose of this study is to evaluate sediment yield reduction under various field slope conditions with rice straw mat. The Vegetative Filter Strip Model-W (VFSMOD-W) and Soil and Water Assessment Tool (SWAT) were used for simulation of sediment yield reduction effect of rice straw mat. The Universe Soil Loss Equation Practice factor (USLE P factor), being able to reflect simulation of rice straw mat in the agricultural field, were estimated for each slope with VFSMOD-W and measured soil erosion values under 5, 10, and 20 % slopes. Then with the regression equation for slopes, USLE P factor was derived and used as input data for each Hydrological Response Unit (HRU) in the SWAT model. The SWAT Spatially Distributed-HRU (SD-HRU) pre-processor module was utilized, moreover, in order to consider spatial location and topographic features (measured topographic features by field survey) of all HRU within each subwatershed in the study watershed. Result of monthly sediment yield without rice straw mat (Jan. 2000 - Aug. 2007) was 814.72 ton/month, and with rice straw mat (Jan. 2000 - Aug. 2007) was 526.75 ton/month, which was reduced as 35.35 % compared without it. Also, during the rainy season (from Jun. to Sep. 2000 - 2007), when without vs. with rice straw mat, monthly sediment indicated 2,109.54 ton and 1,358.61 ton respectively. It showed about 35.60 % was reduced depending on rice straw mat. As shown in this study, if rice straw mat is used as a Best Management Practice (BMP) in the sloping fields, rainfall-driven sediment yield will be reduced effectively.

• Nuclear Engineering and Technology
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• v.56 no.4
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• pp.1310-1319
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• 2024

The reactor cavity cooling system (RCCS) is a passive reactor safety system commonly present in the designs of High-Temperature Gas-cooled Reactors (HTGR) that removes heat from the reactor pressure vessel by means of natural convection and radiation. It is one of the factors responsible for ensuring that the reactor does not melt down under any plausible accident scenario. For the simulation of accident scenarios, which are transient phenomena unfolding over a span of up to several days, intermediate fidelity methods and system codes must be employed to limit the models' execution time. These models can quantify radiation heat transfer well, but heat transfer caused by natural convection must be quantified with the use of correlations for the heat transfer coefficient. It is difficult to obtain reliable correlations for HTGR RCCS heat transfer coefficients experimentally due to such a system's size. They could, however, be obtained from high-fidelity steady-state simulations of RCCSs. The Rayleigh number in RCCSs is too high for using a Direct Numerical Simulation (DNS) technique; thus, a Reynolds-Averaged Navier-Stokes (RANS) approach must be employed. There are many RANS models, each performing best under different geometry and fluid flow conditions. To find the most suitable one for simulating an RCCS, the RANS models need to be validated. This work benchmarks various RANS models against three experiments performed on the HTTR RCCS Mockup by the Japanese Atomic Energy Agency (JAEA) in 1993. This facility is a 1/6 scale model of a vessel cooling system (VCS) for the High Temperature Engineering Test Reactor (HTTR), which is operated by JAEA. Multiple RANS models were evaluated on a simplified 2d-axisymmetric geometry. They were found to reproduce the experimental temperature profiles with errors of up to 22% for the lowest temperature benchmark and 15% for the higher temperature benchmarks. The results highlight that the pragmatic turbulence models need to be validated for high Rayleigh natural convection-driven flows and improved accordingly, more publicly available experimental data of RCCS resembling experiments is needed and indicate that a 2d-axisymmetric geometry approximation is likely insufficient to capture all the relevant phenomena in RCCS simulations.