• Title/Summary/Keyword: Performance, Simulation

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Doubly-robust Q-estimation in observational studies with high-dimensional covariates (고차원 관측자료에서의 Q-학습 모형에 대한 이중강건성 연구)

  • Lee, Hyobeen;Kim, Yeji;Cho, Hyungjun;Choi, Sangbum
    • The Korean Journal of Applied Statistics
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    • v.34 no.3
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    • pp.309-327
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    • 2021
  • Dynamic treatment regimes (DTRs) are decision-making rules designed to provide personalized treatment to individuals in multi-stage randomized trials. Unlike classical methods, in which all individuals are prescribed the same type of treatment, DTRs prescribe patient-tailored treatments which take into account individual characteristics that may change over time. The Q-learning method, one of regression-based algorithms to figure out optimal treatment rules, becomes more popular as it can be easily implemented. However, the performance of the Q-learning algorithm heavily relies on the correct specification of the Q-function for response, especially in observational studies. In this article, we examine a number of double-robust weighted least-squares estimating methods for Q-learning in high-dimensional settings, where treatment models for propensity score and penalization for sparse estimation are also investigated. We further consider flexible ensemble machine learning methods for the treatment model to achieve double-robustness, so that optimal decision rule can be correctly estimated as long as at least one of the outcome model or treatment model is correct. Extensive simulation studies show that the proposed methods work well with practical sample sizes. The practical utility of the proposed methods is proven with real data example.

CNN Based Spectrum Sensing Technique for Cognitive Radio Communications (인지 무선 통신을 위한 합성곱 신경망 기반 스펙트럼 센싱 기법)

  • Jung, Tae-Yun;Lee, Eui-Soo;Kim, Do-Kyoung;Oh, Ji-Myung;Noh, Woo-Young;Jeong, Eui-Rim
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.2
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    • pp.276-284
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    • 2020
  • This paper proposes a new convolutional neural network (CNN) based spectrum sensing technique for cognitive radio communications. The proposed technique determines the existence of the primary user (PU) by using energy detection without any prior knowledge of the PU's signal. In the proposed method, the received signal is high-rate sampled to sense the entire spectrum bands of interest. After that, fast Fourier transform (FFT) of the signal converts the time domain signal to frequency domain spectrum and by stacking those consecutive spectrums, a 2 dimensional signal is made. The 2 dimensional signal is cut by the sensing channel bandwidth and inputted to the CNN. The CNN determines the existence of the primary user. Since there are only two states (existence or non-existence), binary classification CNN is used. The performance of the proposed method is examined through computer simulation and indoor experiment. According to the results, the proposed method outperforms the conventional threshold-based method by over 2 dB.

Comparative Analysis of the Psychological State and Driving Safety for Driving within the Platoons of Trucks by Drivers Driving Performance (화물차 군집주행 간격에 따른 운전자의 운전수행능력별 심리상태 및 주행안전성 비교 연구)

  • Park, Hyun jin;Park, Jae beom;Lee, Ki young;Song, Chang jun
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.20 no.6
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    • pp.147-161
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    • 2021
  • The purpose of this study was to investigate the psychological state and driving safety of drivers driving around the truck platoon driving. Using the driving simulator, the experimental environment was constructed with the situation of changing lanes to the platoon and driving within the platoon. We tried to qualitatively and quantitatively analyze the driver's psychological state and driving safety through simulation driving experiments. As a result, in the case of the older driver group, there were many cases where they judged themselves to be driving safely, even though they were driving dangerously in the actual lane change to the platoon or driving within the platoon. In particular, this group showed that the narrower the distance between vehicles, the greater the misrecognition. The results of this study are expected to be useful in deriving the optimum interval when the interval between platooning of trucks needs to be temporarily extended.

Characteristic Analysis of Efficiency and Impedance With WPT Transmitter and Receiver Coil Distance (무선전력전송 송수신코일 거리에 따른 효율 및 임피던스 특성 해석)

  • Park, Dae Kil;Kim, Young Hyun;Koo, Kyung Heon
    • Journal of Advanced Navigation Technology
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    • v.26 no.3
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    • pp.160-165
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    • 2022
  • In this paper, we have proposed a magnetic resonant 6.78MHz WPT(wireless power transfer) technique which can be applied to a fixed transmitter and a receiver of varying relative distance and coil alignment, Power transmission characteristics are studied with the relative distance and misalignment ration of coil area between the transmitting and receiving coils. The coils are designed with the size of 60×80mm2 by direct feeding method, and the characteristics are derived with the maximum relative distance of 50mm and horizontal area misalignment state of 0-40mm misalignment of coil center axis in the XY plane. The power transmission characteristics are compared between the 3D EM simulation and the measured data, and the power transmission shows larger than -3dB performance with the vertical distance of up to 30mm and 50% area misalignmment ratio. This work showsthe transmission characteristics according to relative distance and misalignment state between the cols and that direct feeding has advantage for the short relative distance and small misalignment ratio.

Generation and Verification of Synthetic Wind Data With Seasonal Fluctuation Using Hidden Markov Model (은닉 마르코프 모델을 이용하여 계절의 변동을 동반한 인공 바람자료 생성 및 검증)

  • Park, Seok-Young;Ryu, Ki-Wahn
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.49 no.12
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    • pp.963-969
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    • 2021
  • The wind data measured from local meteorological masts is used to evaluate wind speed distribution and energy production in the specified site for wind farm However, wind data measured from meteorological masts often contain missing information or insufficient desired height or data length, making it difficult to perform wind turbine control and performance simulation. Therefore, long-term continuous wind data is very important to assess the annual energy production and the capacity factor for wind turbines or wind farms. In addition, if seasonal influences are distinct, such as on the Korean Peninsula, wind data with seasonal characteristics should be considered. This study presents methodologies for generating synthetic wind that take into account fluctuations in both wind speed and direction using the hidden Markov model, which is a statistical method. The wind data for statistical processing are measured at Maldo island in the Kokunnsan-gundo, Jeonbuk Province using the Automatic Weather System (AWS) of the Korea Meteorological Administration. The synthetic wind generated using the hidden Markov model will be validated by comparing statistical variables, wind energy density, seasonal mean speed, and prevailing wind direction with measurement data.

Evaluation of extreme rainfall estimation obtained from NSRP model based on the objective function with statistical third moment (통계적 3차 모멘트 기반의 목적함수를 이용한 NSRP 모형의 극치강우 재현능력 평가)

  • Cho, Hemie;Kim, Yong-Tak;Yu, Jae-Ung;Kwon, Hyun-Han
    • Journal of Korea Water Resources Association
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    • v.55 no.7
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    • pp.545-556
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    • 2022
  • It is recommended to use long-term hydrometeorological data for more than the service life of the hydraulic structures and water resource planning. For the purpose of expanding rainfall data, stochastic simulation models, such as Modified Bartlett-Lewis Rectangular Pulse (BLRP) and Neyman-Scott Rectangular Pulse (NSRP) models, have been widely used. The optimal parameters of the model can be estimated by repeatedly comparing the statistical moments defined through a combination of parameters of the probability distribution in the optimization context. However, parameter estimation using relatively small observed rainfall statistics corresponds to an ill-posed problem, leading to an increase in uncertainty in the parameter estimation process. In addition, as shown in previous studies, extreme values are underestimated because objective functions are typically defined by the first and second statistical moments (i.e., mean and variance). In this regard, this study estimated the parameters of the NSRP model using the objective function with the third moment and compared it with the existing approach based on the first and second moments in terms of estimation of extreme rainfall. It was found that the first and second moments did not show a significant difference depending on whether or not the skewness was considered in the objective function. However, the proposed model showed significantly improved performance in terms of estimation of design rainfalls.

Deep Learning-Based Prediction of the Quality of Multiple Concurrent Beams in mmWave Band (밀리미터파 대역 딥러닝 기반 다중빔 전송링크 성능 예측기법)

  • Choi, Jun-Hyeok;Kim, Mun-Suk
    • Journal of Internet Computing and Services
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    • v.23 no.3
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    • pp.13-20
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    • 2022
  • IEEE 802.11ay Wi-Fi is the next generation wireless technology and operates in mmWave band. It supports the MU-MIMO (Multiple User Multiple Input Multiple Output) transmission in which an AP (Access Point) can transmit multiple data streams simultaneously to multiple STAs (Stations). To this end, the AP should perform MU-MIMO beamforming training with the STAs. For efficient MU-MIMO beamforming training, it is important for the AP to estimate signal strength measured at each STA at which multiple beams are used simultaneously. Therefore, in the paper, we propose a deep learning-based link quality estimation scheme. Our proposed scheme estimates the signal strength with high accuracy by utilizing a deep learning model pre-trained for a certain indoor or outdoor propagation scenario. Specifically, to estimate the signal strength of the multiple concurrent beams, our scheme uses the signal strengths of the respective single beams, which can be obtained without additional signaling overhead, as the input of the deep learning model. For performance evaluation, we utilized a Q-D (Quasi-Deterministic) Channel Realization open source software and extensive channel measurement campaigns were conducted with NIST (National Institute of Standards and Technology) to implement the millimeter wave (mmWave) channel. Our simulation results demonstrate that our proposed scheme outperforms comparison schemes in terms of the accuracy of the signal strength estimation.

Research on the Creative Style of DreamWorks' Animated Film Script (드림웍스 애니메이션 영화 시나리오의 창작 스타일에 관한 연구)

  • Yan, Liu
    • Journal of Korea Entertainment Industry Association
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    • v.14 no.1
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    • pp.97-106
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    • 2020
  • The mainstream of cinema animated film in today's world is the animated film produced by film companies such as Disney, DreamWorks, and 20th Century Fox. These animated films are influenced by Hollywood blockbusters, high cost, and big-budget, which have brought a gorgeous and splendid audio-visual feast to the global audience. DreamWorks Studios founded in 1994 has become noted in just over ten years. It has produced many high-quality animated works which are well-known all over the world. This achievement is no doubt inseparable from its superior external animation industry environment, and benefited from the American animation industry which commercially operated for almost 100 years. However, in addition to these external environmental factors, DreamWorks' achievements have also come from the extraordinary and superior creation of the animated film scripts, strong narrative script ensures the logic and appeal of animated films. This article takes Kung Fu Panda series, Shrek series, The Prince of Egypt, The Croods, Chicken Run, Megamind and other representative films produced by DreamWorks as key analysis object, using Jean Baudrillard's simulation and imaging theory, Syd Field's screenwriting skills, and Hegel's aesthetic point of view, explores the Creative Style of DreamWorks' Animated Film Script which contains the following four aspects. The script is exaggerated and novel, and the subject matter is rich and targeted. The script creation is very imaginative and can fully express the visual beauty. The structure of the story is well controlled, the space comes from reality but full of imagination. The characters have distinctive personality and the dialogue is moderated but forceful.

Review of Adequacy for On-Site Application of Concrete Freeze-Thaw Damage Evaluation Method Using Surface Rebound Value (표면반발경도 활용 콘크리트 동해손상 판정법의 현장 적용 적정성 검토)

  • Ji-Sun, Park;Jong-Suk, Lee
    • Journal of the Korean Recycled Construction Resources Institute
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    • v.10 no.4
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    • pp.539-546
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    • 2022
  • The current 「Detailed guidelines for the safety and maintenance of facilities (performance Evaluation)」 prescribes that the durability of surface concrete is evaluated by comparing the measuring the surface rebound value between sound parts and non-sound parts that have surface damage due to winter rain or leakage on concrete. However, this evaluation method was proposed by analyzing the correlation with an experimental DB obtained under freeze-thaw simulation promoting the environment without reviewing on-site applicability. Therefore, this study reviewed on-site application appropriateness of the concrete freeze-thaw damage evaluation method for the 21 concrete bridges in Korea. From the results, it was clearly confirmed that there was a difference in the surface rebound value between the sound part and the non-sound on the concrete surface; the current evaluation method is considered appropriate for application at the site. In addition, the necessity of adding a specific method and a measurement position of surface rebound value were also analyzed, and the effectiveness of the current evaluation method was also analyzed when targeting the entire concrete bridge, not the evaluation of some sections.

An Extended ED-H Real-Time Scheduling Algorithm for Supporting an Intelligent PMU-Based Energy Harvesting System

  • Park, Sangsoo
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.12
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    • pp.17-27
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    • 2022
  • In this paper, ED-H algorithm, an optimal real-time scheduling algorithm dealing with the characteristics of the integrated energy harvester system with a capacitor, is extended to satisfy the time constraint under the blackout state which is a deliberate power-off state by an intelligent power management unit adopted in the system. If the power supply system does not have enough energy, it temporarily shuts off the power supply to protect the circuit and capacitor and resumes the supply again when the capacitor is fully charged, which may delay the task execution during these blackout states by calculating the time according to the occurrence of the events. To mitigate the problem, even if task execution is delayed by the original ED-H algorithm, the remaining time of the subsequent time units no longer can afford to delay the execution of the task is predicted in the extended algorithm and the task is forced to be scheduled to meet the time deadline. According to the simulation results, it is confirmed that the algorithm proposed in this paper has a high scheduling performance increase of 0.4% to 7.7% depending on the characteristics of the set of tasks compared to the ED-H.