• Title/Summary/Keyword: improving accuracy

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The Current State and the Development Direction of the Studies on Improving of Broadcasting Language (방송언어 개선 연구의 현황과 발전 방향)

  • CHO, TAE-RIN
    • Korean Linguistics
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    • v.74
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    • pp.169-197
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    • 2017
  • The purpose of this paper is to seek the development direction of the studies on improving of broadcasting language, by examining the fruits and the limitations of existing research. Firstly, this paper makes sure that the study on improving of broadcasting language is one of the subtypes of study on broadcasting language. Then the current state of the studies on improving of broadcasting language is analyzed by genre, problem, and assessment standard. According to this analysis, existing research is concentrated too much in certain genres such as current affairs and news, but also in certain problems such as accuracy or publicness infractions. Finally, this paper concludes by suggesting three development directions of the future studies on improving of broadcasting language as follows: (1) Accuracy or publicness related problems need no more studies on themselves but continuous and systematic monitoring and institutional device. (2) We need more interest and research on language used in certain genres such as TV home shopping and commercial break. (3) Fairness or soundness related problems need more studies on themselves, because the judgement or assessment standard of these problems is not only difficult to find out, but also in need of viewer and listener awareness investigation and social agreement procedure.

New D/A Design Method for Improving Accuracy in High-Performance Test Equipment (고성능 장비의 정밀도 향상을 위한 새로운 D/A 설계기법)

  • Kim, Hyung-Jung;Chae, Soo-Yong
    • Proceedings of the KIPE Conference
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    • 2018.07a
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    • pp.308-309
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    • 2018
  • This paper proposes new D/A(Digital to Analog) Design method for improving accuracy in high-performance test equipment. The proposed new D/A design can improve accuracy of the equipment even with low-resolution D/A converters. The validity of proposed D/A design is verified by analysis and experiment.

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Improving Image Fingerprint Matching Accuracy Based on a Power Mask (파워마스크를 이용한 영상 핑거프린트 정합 성능 개선)

  • Seo, Jin Soo
    • Journal of Korea Multimedia Society
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    • v.23 no.1
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    • pp.8-14
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    • 2020
  • For a reliable fingerprinting system, improving fingerprint matching accuracy is crucial. In this paper, we try to improve a binary image fingerprint matching performance by utilizing auxiliary information, power mask, which is obtained while constructing fingerprint DB. The power mask is an expected robustness of each fingerprint bit. A caveat of the power mask is the increased storage cost of the fingerprint DB. This paper mitigates the problem by reducing the size of the power mask utilizing spatial correlation of an image. Experiments on a publicly-available image dataset confirmed that the power mask is effective in improving fingerprint matching accuracy.

Oil Spill Detection from RADARSAT-2 SAR Image Using Non-Local Means Filter

  • Kim, Daeseong;Jung, Hyung-Sup
    • Korean Journal of Remote Sensing
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    • v.33 no.1
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    • pp.61-67
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    • 2017
  • The detection of oil spills using radar image has been studied extensively. However, most of the proposed techniques have been focused on improving detection accuracy through the advancement of algorithms. In this study, research has been conducted to improve the accuracy of oil spill detection by improving the quality of radar images, which are used as input data to detect oil spills. Thresholding algorithms were used to measure the image improvement both before and after processing. The overall accuracy increased by approximately 16%, the producer accuracy increased by 40%, and the user accuracy increased by 1.5%. The kappa coefficient also increased significantly, from 0.48 to 0.92.

Improving the Three-Dimensional Printability of Potato Starch Loaded onto Food Ink

  • Yourim Oh;Seungmin Lee;Nam Keun Lee;Jin-Kyu Rhee
    • Journal of Microbiology and Biotechnology
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    • v.34 no.4
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    • pp.891-901
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    • 2024
  • This study focuses on improving the 3D printability of pea protein with the help of food inks designed for jet-type 3D printers. Initially, the food ink base was formulated using nanocellulose-alginate with a gradient of native potato starch and its 3D printability was evaluated. The 3D-printed structures using only candidates for the food ink base formulated with or without potato starch exhibited dimensional accuracy exceeding 95% on both the X and Y axes. However, the accuracy of stacking on the Z-axis was significantly affected by the ink composition. Food ink with 1% potato starch closely matched the CAD design, with an accuracy of approximately 99% on the Z-axis. Potato starch enhanced the stacking of 3D-printed structures by improving the electrostatic repulsion, viscoelasticity, and thixotropic behavior of the food ink base. The 3D printability of pea protein was evaluated using the selected food ink base, showing a 46% improvement in dimensional accuracy on the Z-axis compared to the control group printed with a food ink base lacking potato starch. These findings suggest that starch can serve as an additive support for high-resolution 3D jet-type printing of food ink material.

Validation Data Augmentation for Improving the Grading Accuracy of Diabetic Macular Edema using Deep Learning (딥러닝을 이용한 당뇨성황반부종 등급 분류의 정확도 개선을 위한 검증 데이터 증강 기법)

  • Lee, Tae Soo
    • Journal of Biomedical Engineering Research
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    • v.40 no.2
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    • pp.48-54
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    • 2019
  • This paper proposed a method of validation data augmentation for improving the grading accuracy of diabetic macular edema (DME) using deep learning. The data augmentation technique is basically applied in order to secure diversity of data by transforming one image to several images through random translation, rotation, scaling and reflection in preparation of input data of the deep neural network (DNN). In this paper, we apply this technique in the validation process of the trained DNN, and improve the grading accuracy by combining the classification results of the augmented images. To verify the effectiveness, 1,200 retinal images of Messidor dataset was divided into training and validation data at the ratio 7:3. By applying random augmentation to 359 validation data, $1.61{\pm}0.55%$ accuracy improvement was achieved in the case of six times augmentation (N=6). This simple method has shown that the accuracy can be improved in the N range from 2 to 6 with the correlation coefficient of 0.5667. Therefore, it is expected to help improve the diagnostic accuracy of DME with the grading information provided by the proposed DNN.

Parallel Algorithm of Improved FunkSVD Based on Spark

  • Yue, Xiaochen;Liu, Qicheng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.5
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    • pp.1649-1665
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    • 2021
  • In view of the low accuracy of the traditional FunkSVD algorithm, and in order to improve the computational efficiency of the algorithm, this paper proposes a parallel algorithm of improved FunkSVD based on Spark (SP-FD). Using RMSProp algorithm to improve the traditional FunkSVD algorithm. The improved FunkSVD algorithm can not only solve the problem of decreased accuracy caused by iterative oscillations but also alleviate the impact of data sparseness on the accuracy of the algorithm, thereby achieving the effect of improving the accuracy of the algorithm. And using the Spark big data computing framework to realize the parallelization of the improved algorithm, to use RDD for iterative calculation, and to store calculation data in the iterative process in distributed memory to speed up the iteration. The Cartesian product operation in the improved FunkSVD algorithm is divided into blocks to realize parallel calculation, thereby improving the calculation speed of the algorithm. Experiments on three standard data sets in terms of accuracy, execution time, and speedup show that the SP-FD algorithm not only improves the recommendation accuracy, shortens the calculation interval compared to the traditional FunkSVD and several other algorithms but also shows good parallel performance in a cluster environment with multiple nodes. The analysis of experimental results shows that the SP-FD algorithm improves the accuracy and parallel computing capability of the algorithm, which is better than the traditional FunkSVD algorithm.

A Study on Improving Prediction Accuracy by Modeling Multiple Similar Time Series (다중 유사 시계열 모델링 방법을 통한 예측정확도 개선에 관한 연구)

  • Cho, Young-Hee;Lee, Gye-Sung
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.10 no.6
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    • pp.137-143
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    • 2010
  • A method for improving prediction accuracy through processing time series data has been studied in this research. We have designed techniques to model multiple similar time series data and avoided the shortcomings of single prediction model. We predicted the future changes by effective rules derived from these models. The methods for testing prediction accuracy consists of three types: fixed interval, sliding, and cumulative method. Among the three, cumulative method produced the highest accuracy.

Corrective machining Algorithm for Improving the Motion Accuracy of Hydrostatic Table (유정압테이블의 정밀도향상을 위한 수정가공 알고리즘)

  • 박천홍;이찬홍;이후상
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1997.10a
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    • pp.380-384
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    • 1997
  • For improving the motion accuracy of hydrostatic table, corrective machining algorithm is proposed in this paper. The algorithm consists of three main processes. Reverse analysis is performed firstly to estimate rail profile from measured linear and angular motion error, in the algorithm. For the next step, correctwe machining information is decided as referring to the estimating rail profile. Finally, motion errors on correctively machined rail are analized by using motion error analysls method proposed in the previous paper. These processes can be rtcrated if the analized motion errors are worse than target accuracy. In order to verify the validity of the algorithm theoretically, motion errors by the estimated rail after corrective machining are compared with motion errors by true rail assumed as the measured value. Estimated motion errors show good agreement with assumed values, and it is confirmed that the algorithm IS effective to acquire the corrective machming information to improve the accuracy of hydrostatic table.

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Improving Accuracy of Measurement of Rigid Body Motion by Using Transfer Matrix (전달 행렬을 이용한 강체 운동 측정의 정확도 개선)

  • 고강호;국형석
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2002.05a
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    • pp.253-259
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    • 2002
  • The rigid body characteristics (value of mass, Position of center of mass, moments and products of inertia) of mechanical systems can be identified from FRF data or vibration spectra of rigid body motion. Therefore the accuracy of rigid body characteristics is connected directly with the accuracy of measured data for rigid body motions. In this paper, a method of improving accuracy of measurement of rigid body motion is presented. Applying rigid body theory, ail translational and rotational displacements at a tentative point on the rigid body are calculated using the measured translational displacements for several points and transfer matrix. Then the estimated displacements for the identical points are calculated using the 6 displacements of the tentative Point and transfer matrix. By using correlation coefficient between measured and estimated displacements, we can detect the existence of errors that are contained in a certain measured displacement. Consequently, the improved rigid body motion with respect to a tentative point can be obtained by eliminating the contaminated data.

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