• Title/Summary/Keyword: 예측성능 개선

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외부창호의 차음성능 향상방안

  • 김성완;김하근;김명준
    • Journal of KSNVE
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    • v.3 no.3
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    • pp.209-219
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    • 1993
  • 본 글에서는 아파트단지의 교통소음도 예측프로그램인 "TRANOIS-93"을 통하여 교통량, 도로, 방음벽, 수림대 등 각종 영향요인을 검토하여 1차적으로 소음저감대책 수립을 위한 시뮬레이션을 수행하고, 이를 분석하여 외부창호에 의해서 소음을 차단하지 않으면 안되는 경우에 대해서도 효과적인 대책을 수립할 수 있도록 창호의 차음설계자료를 제시하고자 한다. 이를 위해 창호의 기밀성, 유리의 두께, 이중창 사이의 공간층에 설치된 흡음재, 이중창에서 바깥창과 안쪽창과의 간격, 유리창의 크기 등의 요인에 대해서 실험을 통하여 차음개선량을 파악하고 이를 분석함으로서 창호제작 및 설계업무에 활용될 참고자료를 소개하고자 한다. 소개하고자 한다.

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A Self-Organizing Fuzzy Logic Controller with Hybrid Structure (하이브리드 구조의 자기구성 퍼지제어기)

  • 이평기;박상배
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.03a
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    • pp.31-34
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    • 1998
  • 본 논문에서는 하이브리드 구조를 가지는 자기구성 퍼지제어기를 제안한다. 제안한 방법은 FARMA 제어기에 비해 다음과 같은 장점을 가진다. 하이브리드 구조를 자기구성 퍼지논리 제어기에 도입하므로써 예측출력값을 구할 때 까지의 입축력정보의 부재로 인한 나쁜 응답성능을 개선할 수 있다. 또한 이 방법은 Yager의 t-norm을 이용하여 계산상의 복잡성을 피하고 규칙들의 가중치를 구하기 위해 필요한 Dmax선정의 어려움을 해결한다.

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A local search algorithm for predicting epistatic interactions of SNPs (복합 질환 관련 SNP 상호작용 예측을 위한 국소탐색 알고리즘)

  • Hong, Won-Pyo;Wee, Kyubum
    • Annual Conference of KIPS
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    • 2010.11a
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    • pp.1395-1398
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    • 2010
  • 최근 GWAS(Genome-wide association study)로 인해 수십만 개의 SNP들이 사용 가능하게 되었다. 그러나 SNP 정보의 양이 방대하여 모든 SNP 조합을 검토하는 방식은 계산 비용이 클 뿐 아니라 오버피팅의 위험이 따른다. 본 논문에서는 필터링 기반 알고리즘인 SNPHarvester의 속도를 개선하고 평가함수를 상호정보량으로 대체하여 실험한다. 기존 SNPHarvester와 비교해 속도면에서 50%가 향상되었고 평가함수 면에서는 기존 SNPHarvester와 동일한 성능을 보였다.

SIEM System Performance Enhancement Mechanism Using Active Model Improvement Feedback Technology (능동형 모델 개선 피드백 기술을 활용한 보안관제 시스템 성능 개선 방안)

  • Shin, Youn-Sup;Jo, In-June
    • The Journal of the Korea Contents Association
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    • v.21 no.12
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    • pp.896-905
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    • 2021
  • In the field of SIEM(Security information and event management), many studies try to use a feedback system to solve lack of completeness of training data and false positives of new attack events that occur in the actual operation. However, the current feedback system requires too much human inputs to improve the running model and even so, those feedback from inexperienced analysts can affect the model performance negatively. Therefore, we propose "active model improving feedback technology" to solve the shortage of security analyst manpower, increasing false positive rates and degrading model performance. First, we cluster similar predicted events during the operation, calculate feedback priorities for those clusters and select and provide representative events from those highly prioritized clusters using XAI (eXplainable AI)-based event visualization. Once these events are feedbacked, we exclude less analogous events and then propagate the feedback throughout the clusters. Finally, these events are incrementally trained by an existing model. To verify the effectiveness of our proposal, we compared three distinct scenarios using PKDD2007 and CSIC2012. As a result, our proposal confirmed a 30% higher performance in all indicators compared to that of the model with no feedback and the current feedback system.

Intra Block Copy Analysis to Improve Coding Efficiency for HEVC Screen Content Coding (HEVC 스크린 콘텐츠 코딩 성능 향상을 위한 화면 내 블록 카피 기술 분석)

  • Ma, Jonghyun;Ahn, Yong-Jo;Sim, Donggyu
    • Journal of Broadcast Engineering
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    • v.20 no.1
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    • pp.57-67
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    • 2015
  • This paper describes and analyzes IBC (intra block copy) in HEVC (high efficiency video coding) SCC (screen content coding) to improve the coding efficiency of IBC. HEVC SCC reference software SCM 2 is employed to analyze the selection ratio of IBC which is newly adopted in HEVC SCC, and the tools for IBC such as the block vector prediction and block vector coding method are evaluated. Experimental results show the average IBC selection ratio is 31.08% and 0.33% in I-Slice and B-Slice, respectively. Based on this results, the coding efficiency of IBC could be improved by utilizing IBC selectively. In addition, analysis tests of block vector prediction and the block vector coding method show the current methods are not efficient to screen content videos, and the analysis results are presented to improve these methods.

Performance Comparison of Fast Distributed Video Decoding Methods Using Correlation between LDPCA Frames (LDPCA 프레임간 상관성을 이용한 고속 분산 비디오 복호화 기법의 성능 비교)

  • Kim, Man-Jae;Kim, Jin-Soo
    • The Journal of the Korea Contents Association
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    • v.12 no.4
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    • pp.31-39
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    • 2012
  • DVC(Distributed Video Coding) techniques have been attracting a lot of research works since these enable us to implement the light-weight video encoder and to provide good coding efficiency by introducing the feedback channel. However, the feedback channel causes the decoder to increase the decoding complexity and requires very high decoding latency because of numerous iterative decoding processes. So, in order to reduce the decoding delay and then to implement in a real-time environment, this paper proposes several parity bit estimation methods which are based on the temporal correlation, spatial correlation and spatio-temporal correlations between LDPCA frames on each bit plane in the consecutive video frames in pixel-domain Wyner-Ziv video coding scheme and then the performances of these methods are compared in fast DVC scheme. Through computer simulations, it is shown that the adaptive spatio-temporal correlation-based estimation method and the temporal correlation-based estimation method outperform others for the video frames with the highly active contents and the low active contents, respectively. By using these results, the proposed estimation schemes will be able to be effectively used in a variety of different applications.

Channel Prediction based Adaptive Channel Tracking cheme in MIMO-OFDM Systems with Null Sub-carriers (Null 부반송파를 갖는 MIMO-OFDM에서 채널 예측 기반적응 채널 추적 방식)

  • Jeon, Hyoung-Goo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.5C
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    • pp.556-564
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    • 2007
  • This paper proposes an efficient scheme to track a time variant channel induced by multi-path Rayleigh fading in mobile MIMO-OFDM systems with null sub-carriers. The proposed adaptive channel tracking scheme removes in the frequency domain the interfering signals of the other transmit (Tx) antennas by using a predicted channel frequency response before starting the channel estimation. Time domain channel estimation is then performed to reduce the additive white Gaussian noise (AWGN). The simulation results show that the proposed method is better than the conventional channel tracking method [3] in time varying channel environments. At a Doppler frequency of 300 Hz and bit error rates (BER) of 10-3, signal-to-noise power ratio (Eb/N0) gains of about 2.5 dB are achieved relative to the conventional channel tracking method [3]. At a Doppler frequency of 600 Hz, the performance difference between the proposed method and conventional one becomes much larger.

Interframe Coding of 3-D Medical Image Using Warping Prediction (Warping을 이용한 움직임 보상을 통한 3차원 의료 영상의 압축)

  • So, Yun-Sung;Cho, Hyun-Duck;Kim, Jong-Hyo;Ra, Jong-Beom
    • Journal of Biomedical Engineering Research
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    • v.18 no.3
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    • pp.223-231
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    • 1997
  • In this paper, an interframe coding method for volumetric medical images is proposed. By treating interslice variations as the motion of bones or tissues, we use the motion compensation (MC) technique to predict the current frame from the previous frame. Instead of a block matching algorithm (BMA), which is the most common motion estimation (ME) algorithm in video coding, image warping with biolinear transformation has been suggested to predict complex interslice object variation in medical images. When an object disappears between slices, however, warping prediction has poor performance. In order to overcome this drawback, an overlapped block motion compensation (OBMC) technique is combined with carping prediction. Motion compensated residual images are then encoded by using an embedded zerotree wavelet (EZW) coder with small modification for consistent quality of reconstructed images. The experimental results show that the interframe coding suing warping prediction provides better performance compared with interframe coding, and the OBMC scheme gives some additional improvement over the warping-only MC method.

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Short-term Power Consumption Forecasting Based on IoT Power Meter with LSTM and GRU Deep Learning (LSTM과 GRU 딥러닝 IoT 파워미터 기반의 단기 전력사용량 예측)

  • Lee, Seon-Min;Sun, Young-Ghyu;Lee, Jiyoung;Lee, Donggu;Cho, Eun-Il;Park, Dae-Hyun;Kim, Yong-Bum;Sim, Isaac;Kim, Jin-Young
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.19 no.5
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    • pp.79-85
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    • 2019
  • In this paper, we propose a short-term power forecasting method by applying Long Short Term Memory (LSTM) and Gated Recurrent Unit (GRU) neural network to Internet of Things (IoT) power meter. We analyze performance based on real power consumption data of households. Mean absolute error (MAE), mean absolute percentage error (MAPE), mean percentage error (MPE), mean squared error (MSE), and root mean squared error (RMSE) are used as performance evaluation indexes. The experimental results show that the GRU-based model improves the performance by 4.52% in the MAPE and 5.59% in the MPE compared to the LSTM-based model.

A study of age estimation from occluded images (가림이 있는 얼굴 영상의 나이 인식 연구)

  • Choi, Sung Eun
    • Journal of Platform Technology
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    • v.10 no.3
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    • pp.44-50
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    • 2022
  • Research on facial age estimation is being actively conducted because it is used in various application fields. Facial images taken in various environments often have occlusions, and there is a problem in that performance of age estimation is degraded. Therefore, we propose age estimation method by creating an occluded part using image extrapolation technology to improve the age estimation performance of an occluded face image. In order to confirm the effect of occlusion in the image on the age estimation performance, an image with occlusion is generated using a mask image. The occluded part of facial image is restored using SpiralNet, which is one of the image extrapolation techniques, and it is a method to create an occluded part while crossing the edge of an image. Experimental results show that age estimation performance of occluded facial image is significantly degraded. It was confirmed that the age estimation performance is improved when using a face image with reconstructed occlusions using SpiralNet by experiments.