• Title/Summary/Keyword: model perturbation

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Detecting the Baryon Acoustic Oscillations in the N-point Spatial Statistics of SDSS Galaxies

  • Hwang, Se Yeon;Kim, Sumi;Sabiu, Cristiano G.;Park, In Kyu
    • The Bulletin of The Korean Astronomical Society
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    • v.46 no.2
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    • pp.72.3-73
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    • 2021
  • Baryon Acoustic Oscillations (BAO) are caused by acoustic density waves in the early universe and act as a standard ruler in the clustering pattern of galaxies in the late Universe. Measuring the BAO feature in the 2-point correlation function of a sample of galaxies allows us to estimate cosmological distances to the galaxies mean redshift, , which is important for testing and constraining the cosmology model. The BAO feature is also expected to appear in the higher order statistics. In this work we measure the generalized spatial N-point point correlation functions up to 4th order. We made measurements of the 2, 3, and 4-point correlation functions in the SDSS-III DR12 CMASS data, comprising of 777,202 galaxies. The errors and covariances matrices were estimated from 500 mock catalogues. We created a theoretical model for these statistics by measuring the N-point functions in halo catalogues produced by the approximate Lagrangian perturbation theory based simulation code, PINOCCHIO. We created simulations using initial conditions with and without the BAO feature. We find that the BAO is detected to high significance up to the 4-point correlation function.

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Query-Efficient Black-Box Adversarial Attack Methods on Face Recognition Model (얼굴 인식 모델에 대한 질의 효율적인 블랙박스 적대적 공격 방법)

  • Seo, Seong-gwan;Son, Baehoon;Yun, Joobeom
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.32 no.6
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    • pp.1081-1090
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    • 2022
  • The face recognition model is used for identity recognition of smartphones, providing convenience to many users. As a result, the security review of the DNN model is becoming important, with adversarial attacks present as a well-known vulnerability of the DNN model. Adversarial attacks have evolved to decision-based attack techniques that use only the recognition results of deep learning models to perform attacks. However, existing decision-based attack technique[14] have a problem that requires a large number of queries when generating adversarial examples. In particular, it takes a large number of queries to approximate the gradient. Therefore, in this paper, we propose a method of generating adversarial examples using orthogonal space sampling and dimensionality reduction sampling to avoid wasting queries that are consumed to approximate the gradient of existing decision-based attack technique[14]. Experiments show that our method can reduce the perturbation size of adversarial examples by about 2.4 compared to existing attack technique[14] and increase the attack success rate by 14% compared to existing attack technique[14]. Experimental results demonstrate that the adversarial example generation method proposed in this paper has superior attack performance.

Improving Adversarial Robustness via Attention (Attention 기법에 기반한 적대적 공격의 강건성 향상 연구)

  • Jaeuk Kim;Myung Gyo Oh;Leo Hyun Park;Taekyoung Kwon
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.33 no.4
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    • pp.621-631
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    • 2023
  • Adversarial training improves the robustness of deep neural networks for adversarial examples. However, the previous adversarial training method focuses only on the adversarial loss function, ignoring that even a small perturbation of the input layer causes a significant change in the hidden layer features. Consequently, the accuracy of a defended model is reduced for various untrained situations such as clean samples or other attack techniques. Therefore, an architectural perspective is necessary to improve feature representation power to solve this problem. In this paper, we apply an attention module that generates an attention map of an input image to a general model and performs PGD adversarial training upon the augmented model. In our experiments on the CIFAR-10 dataset, the attention augmented model showed higher accuracy than the general model regardless of the network structure. In particular, the robust accuracy of our approach was consistently higher for various attacks such as PGD, FGSM, and BIM and more powerful adversaries. By visualizing the attention map, we further confirmed that the attention module extracts features of the correct class even for adversarial examples.

AN ORBIT PROPAGATION SOFTWARE FOR MARS ORBITING SPACECRAFT (화성 근접 탐사를 위한 우주선의 궤도전파 소프트웨어)

  • Song, Young-Joo;Park, Eun-Seo;Yoo, Sung-Moon;Park, Sang-Young;Choi, Kyu-Hong;Yoon, Jae-Cheol;Yim, Jo-Ryeong;Kim, Han-Dol;Choi, Jun-Min;Kim, Hak-Jung;Kim, Byung-Kyo
    • Journal of Astronomy and Space Sciences
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    • v.21 no.4
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    • pp.351-360
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    • 2004
  • An orbit propagation software for the Mars orbiting spacecraft has been developed and verified in preparations for the future Korean Mars missions. Dynamic model for Mars orbiting spacecraft has been studied, and Mars centered coordinate systems are utilized to express spacecraft state vectors. Coordinate corrections to the Mars centered coordinate system have been made to adjust the effects caused by Mars precession and nutation. After spacecraft enters Sphere of Influence (SOI) of the Mars, the spacecraft experiences various perturbation effects as it approaches to Mars. Every possible perturbation effect is considered during integrations of spacecraft state vectors. The Mars50c gravity field model and the Mars-GRAM 2001 model are used to compute perturbation effects due to Mars gravity field and Mars atmospheric drag, respectively. To compute exact locations of other planets, JPL's DE405 ephemerides are used. Phobos and Deimos's ephemeris are computed using analytical method because their informations are not released with DE405. Mars Global Surveyor's mapping orbital data are used to verify the developed propagator performances. After one Martian day propagation (12 orbital periods), the results show about maximum ${\pm}5$ meter errors, in every position state components(radial, cross-track and along-track), when compared to these from the Astrogator propagation in the Satellite Tool Kit. This result shows high reliability of the developed software which can be used to design near Mars missions for Korea, in future.

Impact of a Convectively Forced Gravity Wave Drag Parameterization in Global Data Assimilation and Prediction System (GDAPS) (대류가 유도하는 중력파 항력의 모수화가 GDAPS에 미치는 영향)

  • Kim, So-Young;Chun, Hye-Yeong;Park, Byoung-Kwon;Lee, Hae-Jin
    • Atmosphere
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    • v.16 no.4
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    • pp.303-318
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    • 2006
  • A parameterization of gravity wave drag induced by cumulus convection (GWDC) proposed by Chun and Baik is implemented in the KMA operational global NWP model (GDAPS), and effects of the GWDC on the forecast for July 2005 by GDAPS are investigated. The forecast result is compared with NCEP final analyses data (FNL) and model's own analysis data. Cloud-top gravity wave stresses are concentrated in the tropical region, and the resultant forcing by the GWDC is strong in the tropical upper troposphere and lower stratosphere. Nevertheless, the effect of the GWDC is strong in the mid- to high latitudes of Southern Hemisphere and high latitudes of Northern Hemisphere. By examining the effect of the GWDC on the amplitude of the geopotential height perturbation with zonal wavenumbers 1-3, it is found that impact of the GWDC is extended to the high latitudes through the change of planetary wave activity, which is maximum in the winter hemisphere. The GWDC reduces the amplitude of zonal wavenumber 1 but increases wavenumber 2 in the winter hemisphere. This change alleviates model biases in the zonal wind not only in the lower stratosphere where the GWDC is imposed, but also in the whole troposphere, especially in the mid- to high latitudes of Southern Hemisphere. By examining root mean square error, it is found that the GWDC parameterization improves GDAPS forecast skill in the Southern Hemisphere before 7 days and partially in the Northern Hemisphere after about 5 days.

Development of Tools for calculating Forecast Sensitivities to the Initial Condition in the Korea Meteorological Administration (KMA) Unified Model (UM) (통합모델의 초기 자료에 대한 예측 민감도 산출 도구 개발)

  • Kim, Sung-Min;Kim, Hyun Mee;Joo, Sang-Won;Shin, Hyun-Cheol;Won, DukJin
    • Atmosphere
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    • v.21 no.2
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    • pp.163-172
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    • 2011
  • Numerical forecasting depends on the initial condition error strongly because numerical model is a chaotic system. To calculate the sensitivity of some forecast aspects to the initial condition in the Korea Meteorological Administration (KMA) Unified Model (UM) which is originated from United Kingdom (UK) Meteorological Office (MO), an algorithm to calculate adjoint sensitivities is developed by modifying the adjoint perturbation forecast model in the KMA UM. Then the new algorithm is used to calculate adjoint sensitivity distributions for typhoon DIANMU (201004). Major initial adjoint sensitivities calculated for the 48 h forecast error are located horizontally in the rear right quadrant relative to the typhoon motion, which is related with the inflow regions of the environmental flow into the typhoon, similar to the sensitive structures in the previous studies. Because of the upward wave energy propagation, the major sensitivities at the initial time located in the low to mid- troposphere propagate upward to the upper troposphere where the maximum of the forecast error is located. The kinetic energy is dominant for both the initial adjoint sensitivity and forecast error of the typhoon DIANMU. The horizontal and vertical energy distributions of the adjoint sensitivity for the typhoon DIANMU are consistent with those for other typhoons using other models, indicating that the tools for calculating the adjoint sensitivity in the KMA UM is credible.

Origin of Dark-Energy and Accelerating Universe

  • Keum, Yong-Yeon
    • Bulletin of the Korean Space Science Society
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    • 2009.10a
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    • pp.34.1-34.1
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    • 2009
  • After SNIa and WMAP observations during the last decade, the discovery of the accelerated expansion of the universe is a major challenge to particle physics and cosmology. There are currently three candidates for the dark energy which results in this accelerated expansion: $\cdot$ a non-zero cosmological constant, $\cdot$ a dynamical cosmological constant (quintessence scalar field), $\cdot$ modifications of Einstein's theory of gravity. The scalar field model like quintessence is a simple model with time-dependent w, which is generally larger than -w1. Because the different w lead to a different expansion history of the universe, the geometrical measurements of cosmic expansion through observations of SNIa, CMB and baryon acoustic oscillations (BAO) can give us tight constraints on w. One of the interesting ways to study the scalar field dark-energy models is to investigate the coupling between the dark energy and the other matter fields. In fact, a number of models which realize the interaction between dark energy and dark matter, or even visible matter, have been proposed so far. Observations of the effects of these interactions will offer an unique opportunity to detect a cosmological scalar field. In this talk, after briefly reviewing the main idea of the three possible candidates for dark energy and their cosmological phenomena, we discuss the interactinng dark-energy model, paying particular attention to the interacting mechanism between dark energy with a hot dark matter (neutrinos). In this so-called mass-varying neutrino (MVN) model, we calculate explicitly the cosmic microwave background (CMB) radiation and large-scale structure (LSS) within cosmological perturbation theory. The evolution of the mass of neutrinos is determined by the quintessence scalar field, which is responsible for the cosmic acceleration today.

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Model for Maximum Power Point Tracking Using Artificial Neural Network and Fuzzy (인공 신경망과 퍼지를 이용한 최대 전력점 추적을 위한 모델)

  • Kim, Tae-Oh;Ha, Eun-Gyu;Kim, Chang-Bok
    • The Journal of Korean Institute of Information Technology
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    • v.17 no.9
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    • pp.19-30
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    • 2019
  • Photovoltaic power generation requires MPPT algorithm to track stable and efficient maximum power output power point according to external changes such as solar radiation and temperature. This study implemented a model that could track MPP more quickly than original MPPT algorithm using artificial neural network. The proposed model finds the current and voltage of MPP using the original MPPT algorithm for various combinations of insolation and temperature for training data of artificial neural networks. The acquired MPP data was learned using the input node as insolation and temperature and the output node as the current and voltage. The Experiment results show tracking time of the original algorithms P&O, InC and Fuzzy were respectively 0.428t, 0.49t and 0.4076t for the 0t~0.3t range, and MPP tracking time of the proposed model was 0.32511t and it is 0.1t faster than the original algorithms.

Self-excited Variability of the East Korea Warm Current: A Quasi-Geostyophic Model Study

  • Lee, Sang-Ki
    • Journal of the korean society of oceanography
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    • v.34 no.1
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    • pp.1-21
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    • 1999
  • A two-layer quasi-geostrophic numerical model is used to investigate the temporal variability of the East Korea Warm Current (EKWC), especially the separation from the Korean coast and the generation of warm eddies. An attention is given on the active role of the nonlinear boundary layer process. For this, an idealized flat bottom model of the East Sea is forced with the annual mean wind curl and with the inflow-outflow specified at the Korea (Tsushima) and Tsugaru Straits. Two types of separation mechanisms are identified. The first one is influenced by the westward movement of the recirculating leg of the EKWC (externally driven separation),the second one is solely driven by the boundary layer dynamics (internally driven separation). However, these two processes are not independent, and usually coexist. It is hypothesized that 'internally driven separation' arises as the result of relative vorticity production at the wall, its subsequent advection via the EKWC, and its accumulation up to a critical level characterized by the separation of the boundary flow from the coast. It is found that the sharp southeastern corner of the Korean peninsula provides a favorable condition for the accumulation of relative vorticity. The separation of the EKWC usually accompanies the generation of a warm eddy with a diameter of about 120 km. The warm eddy has a typical layer-averaged velocity of 0.3 m/s and its lifespan is up to a year. In general, the characteristics of the simulated warm eddy are compatible with observations. A conclusion is therefore drawn that the variability of the EKWC is at least partially self-excited, not being influenced by any sources of perturbation in the forcing field, and that the likely source of the variability is the barotropic instability although the extent of contribution from the baroclinic instability remains unknown. The effects of the seasonal wind curl and inflow-outflow strength are also investigated.

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Synthesis and 3D-QSARs Analyses of Herbicidal O,O-Dialkyl-1-phenoxyacetoxy-1-methylphosphonate Analogues as a New Class of Potent Inhibitors of Pyruvate Dehydrogenase

  • Soung, Min-Gyu;Hwang, Tae-Yeon;Sung, Nack-Do
    • Bulletin of the Korean Chemical Society
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    • v.31 no.5
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    • pp.1361-1367
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    • 2010
  • A series of O,O-dialkyl-1-phenoxyacetoxy-1-methylphosphonate analogues (1~22) as a new class of potent inhibitors of pyruvate dehydrogenase were synthesized and 3D-QSARs (three dimensional qantitative structure-activity relationships) models on the pre-emergency herbicidal activity against the seed of cucumber (Cucumus Sativa L.) were derived and discussed quantitatively using comparative molecular field analysis (CoMFA) and comparative molecular similarity indeces analysis (CoMSIA) methods. The statistical values of CoMSIA models were better predictability and fitness than those of CoMFA models. The inhibitory activities according to the optimized CoMSIA model I were dependent on the electrostatic field (41.4%), the H-bond acceptor field (26.0%), the hydrophobic field (20.8%) and the steric field (11.7%). And also, it was found that the optimized CoMSIA model I with the sensitivity to the perturbation ($d_q{^{2'}}/dr^2{_{yy'}}$ = 0.830) and the prediction ($q^2$ = 0.503) produced by a progressive scrambling analyses were not dependent on chance correlation. From the results of graphical analyses on the contour maps with the optimized CoMSIA model I, it is expected that the structural distinctions and descriptors that subscribe to herbicidal activities will be able to apply new an herbicide design.