• Title/Summary/Keyword: False Errors

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An Effective Method for Approximating the Euclidean Distance in High-Dimensional Space (고차원 공간에서 유클리드 거리의 효과적인 근사 방안)

  • Jeong, Seung-Do;Kim, Sang-Wook;Kim, Ki-Dong;Choi, Byung-Uk
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.42 no.5
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    • pp.69-78
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    • 2005
  • It is crucial to compute the Euclidean distance between two vectors efficiently in high dimensional space for multimedia information retrieval. In this paper, we propose an effective method for approximating the Euclidean distance between two high-dimensional vectors. For this approximation, a previous method, which simply employs norms of two vectors, has been proposed. This method, however, ignores the angle between two vectors in approximation, and thus suffers from large approximation errors. Our method introduces an additional vector called a reference vector for estimating the angle between the two vectors, and approximates the Euclidean distance accurately by using the estimated angle. This makes the approximation errors reduced significantly compared with the previous method. Also, we formally prove that the value approximated by our method is always smaller than the actual Euclidean distance. This implies that our method does not incur any false dismissal in multimedia information retrieval. Finally, we verify the superiority of the proposed method via performance evaluation with extensive experiments.

An efficient method and performance analysis for burst synchronization/error detection using cyclic codes (순환코드를 이용한 효율적인 동기/에러 검출 방법 및 성능분석)

  • 최양호
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.21 no.8
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    • pp.2013-2022
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    • 1996
  • Cyclic Codes can be used for burs(or time slot) synchronization as well as error detection as that the overhead bits of the burst, which would be nessary to seperate burst synchronization and error detection systems, may be eliminated. In this paper a new method for combined burst synchronization and error detection is proposed which requires CRC decoding once only, while the previous method which inspects channel error after searching for burst synchronization requeires CRC decoding twice. The proposed method has the advantage of simple implementation and reducing processing time over the previous one, still showing the same detection perfdormance. It may occur that a burst different from the actually transmitted one is falsely accepted in the presence of channel errors. The exact expression for the false acceptance probability is newly presented through a simple derivation basied on the fact that it is determined by channel errors but not by detection methods.

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Evaluation of a Solar Flare Forecast Model with Value Score

  • Park, Jongyeob;Moon, Yong-Jae;Lee, Kangjin;Lee, Jaejin
    • The Bulletin of The Korean Astronomical Society
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    • v.41 no.1
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    • pp.80.1-80.1
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    • 2016
  • There are probabilistic forecast models for solar flare occurrence, which can be evaluated by various skill scores (e.g. accuracy, critical success index, heidek skill score, and true skill score). Since these skill scores assume that two types of forecast errors (i.e. false alarm and miss) are equal or constant, which does not take into account different situations of users, they may be unrealistic. In this study, we make an evaluation of a probabilistic flare forecast model [Lee et al., 2012] which use sunspot groups and its area changes as a proxy of flux emergence. We calculate daily solar flare probabilities from 2011 to 2014 using this model. The skill scores are computed through contingency tables as a function of forecast probability, which corresponds to the maximum skill score depending on flare class and type of a skill score. We use a value score with cost/loss ratio, relative importance between the two types of forecast errors. The forecast probability (y) is linearly changed with the cost/loss ratio (x) in the form of y=ax+b: a=0.88; b=0 (C), a=1.2; b=-0.05(M), a=1.29; b=-0.02(X). We find that the forecast model has an effective range of cost/loss ratio for each class flare: 0.536-0.853(C), 0.147-0.334(M), and 0.023-0.072(X). We expect that this study would provide a guideline to determine the probability threshold and the cost/loss ratio for space weather forecast.

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A Study on the Reverse-Power-Flow Phenomenon due to Transformer Wiring Types in Distribution System (배전계통에서 변압기 결선에 의한 역 조류현상에 관한 연구)

  • Shin, Dong-Yeol;Ha, Bok-Nam;Jung, Won-Wook;Cha, Han-Ju
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.22 no.9
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    • pp.111-119
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    • 2008
  • As the penetration of distributed generation systems is recently high, there have been metering errors, trips of protective devices in KEPCO distribution systems including an occurrence of false fault-indicator in distribution automation system. The cause of malfunctions was the reverse-power-flow phenomenon due to transformer wiring types. By the effect of the reverse-power-flow, each of phase's fundamental currents was added by about 3 times on the neutral line. A new method based on the analysis of the reverse-power-flow is proposed in this paper. Fault currents on each section were analyzed by the proposed method, and the effect of types of transformer wiring was examined experimentally. In order to reduce the malfunctions due to the reverse-power-flow, controlling the zero-sequence impedance of transformer was designed and verified by using PSCAD/EMTDC software.

Analysis of online parenting community posts on expanded newborn screening for metabolic disorders using topic modeling: a quantitative content analysis (토픽 모델링을 활용한 광범위 선천성 대사이상 신생아 선별검사 관련 온라인 육아 커뮤니티 게시 글 분석: 계량적 내용분석 연구)

  • Myeong Seon Lee;Hyun-Sook Chung;Jin Sun Kim
    • Women's Health Nursing
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    • v.29 no.1
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    • pp.20-31
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    • 2023
  • Purpose: As more newborns have received expanded newborn screening (NBS) for metabolic disorders, the overall number of false-positive results has increased. The purpose of this study was to explore the psychological impacts experienced by mothers related to the NBS process. Methods: An online parenting community in Korea was selected, and questions regarding NBS were collected using web crawling for the period from October 2018 to August 2021. In total, 634 posts were analyzed. The collected unstructured text data were preprocessed, and keyword analysis, topic modeling, and visualization were performed. Results: Of 1,057 words extracted from posts, the top keyword based on 'term frequency-inverse document frequency' values was "hypothyroidism," followed by "discharge," "close examination," "thyroid-stimulating hormone levels," and "jaundice." The top keyword based on the simple frequency of appearance was "XXX hospital," followed by "close examination," "discharge," "breastfeeding," "hypothyroidism," and "professor." As a result of LDA topic modeling, posts related to inborn errors of metabolism (IEMs) were classified into four main themes: "confirmatory tests of IEMs," "mother and newborn with thyroid function problems," "retests of IEMs," and "feeding related to IEMs." Mothers experienced substantial frustration, stress, and anxiety when they received positive NBS results. Conclusion: The online parenting community played an important role in acquiring and sharing information, as well as psychological support related to NBS in newborn mothers. Nurses can use this study's findings to develop timely and evidence-based information for parents whose children receive positive NBS results to reduce the negative psychological impact.

Sub-word Based Offline Handwritten Farsi Word Recognition Using Recurrent Neural Network

  • Ghadikolaie, Mohammad Fazel Younessy;Kabir, Ehsanolah;Razzazi, Farbod
    • ETRI Journal
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    • v.38 no.4
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    • pp.703-713
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    • 2016
  • In this paper, we present a segmentation-based method for offline Farsi handwritten word recognition. Although most segmentation-based systems suffer from segmentation errors within the first stages of recognition, using the inherent features of the Farsi writing script, we have segmented the words into sub-words. Instead of using a single complex classifier with many (N) output classes, we have created N simple recurrent neural network classifiers, each having only true/false outputs with the ability to recognize sub-words. Through the extraction of the number of sub-words in each word, and labeling the position of each sub-word (beginning/middle/end), many of the sub-word classifiers can be pruned, and a few remaining sub-word classifiers can be evaluated during the sub-word recognition stage. The candidate sub-words are then joined together and the closest word from the lexicon is chosen. The proposed method was evaluated using the Iranshahr database, which consists of 17,000 samples of Iranian handwritten city names. The results show the high recognition accuracy of the proposed method.

Comparison of methods for the proportion of true null hypotheses in microarray studies

  • Kang, Joonsung
    • Communications for Statistical Applications and Methods
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    • v.27 no.1
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    • pp.141-148
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    • 2020
  • We consider estimating the proportion of true null hypotheses in multiple testing problems. A traditional multiple testing rate, family-wise error rate is too conservative and old to control type I error in multiple testing setups; however, false discovery rate (FDR) has received significant attention in many research areas such as GWAS data, FMRI data, and signal processing. Identify differentially expressed genes in microarray studies involves estimating the proportion of true null hypotheses in FDR procedures. However, we need to account for unknown dependence structures among genes in microarray data in order to estimate the proportion of true null hypothesis since the genuine dependence structure of microarray data is unknown. We compare various procedures in simulation data and real microarray data. We consider a hidden Markov model for simulated data with dependency. Cai procedure (2007) and a sliding linear model procedure (2011) have a relatively smaller bias and standard errors, being more proper for estimating the proportion of true null hypotheses in simulated data under various setups. Real data analysis shows that 5 estimation procedures among 9 procedures have almost similar values of the estimated proportion of true null hypotheses in microarray data.

Efficient Hybrid Transactional Memory Scheme using Near-optimal Retry Computation and Sophisticated Memory Management in Multi-core Environment

  • Jang, Yeon-Woo;Kang, Moon-Hwan;Chang, Jae-Woo
    • Journal of Information Processing Systems
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    • v.14 no.2
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    • pp.499-509
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    • 2018
  • Recently, hybrid transactional memory (HyTM) has gained much interest from researchers because it combines the advantages of hardware transactional memory (HTM) and software transactional memory (STM). To provide the concurrency control of transactions, the existing HyTM-based studies use a bloom filter. However, they fail to overcome the typical false positive errors of a bloom filter. Though the existing studies use a global lock, the efficiency of global lock-based memory allocation is significantly low in multi-core environment. In this paper, we propose an efficient hybrid transactional memory scheme using near-optimal retry computation and sophisticated memory management in order to efficiently process transactions in multi-core environment. First, we propose a near-optimal retry computation algorithm that provides an efficient HTM configuration using machine learning algorithms, according to the characteristic of a given workload. Second, we provide an efficient concurrency control for transactions in different environments by using a sophisticated bloom filter. Third, we propose a memory management scheme being optimized for the CPU cache line, in order to provide a fast transaction processing. Finally, it is shown from our performance evaluation that our HyTM scheme achieves up to 2.5 times better performance by using the Stanford transactional applications for multi-processing (STAMP) benchmarks than the state-of-the-art algorithms.

Analysis of Users' Satisfaction Utility for Precipitation Probabilistic Forecast Using Collective Value Score (그룹 가치스코어 모형을 활용한 강수확률예보의 사용자 만족도 효용 분석)

  • Yoon, Seung Chul;Lee, Ki-Kwang
    • Korean Management Science Review
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    • v.32 no.4
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    • pp.97-108
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    • 2015
  • This study proposes a mathematical model to estimate the economic value of weather forecast service, among which the precipitation forecast service is focused. The value is calculated in terms of users' satisfaction or dissatisfaction resulted from the users' decisions made by using the precipitation probabilistic forecasts and thresholds. The satisfaction values can be quantified by the traditional value score model, which shows the scaled utility values relative to the perfect forecast information. This paper extends the value score concept to a collective value score model which is defined as a weighted sum of users' satisfaction based on threshold distribution in a group of the users. The proposed collective value score model is applied to the picnic scenario by using four hypothetical sets of probabilistic forecasts, i.e., under-confident, over-confident, under-forecast and over-forecast. The application results show that under-confident type of forecasts outperforms the others as a measure of the maximum collective value regardless of users' dissatisfaction patterns caused by two types of forecast errors, e.g., miss and false alarm.

An Efficient 3-D Deinterlacing Algorithm by Detecting Accurate Motions Using Adaptive-Thresholded Values (적응적인 임계값을 적용한 정확한 움직임 검출과 이를 이용한 효율적인 3-D 디인터레이싱 알고리즘)

  • Cho, Dae-Rim;Song, Jin-Mo;Lee, Dong-Ho
    • Journal of Korea Multimedia Society
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    • v.13 no.11
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    • pp.1610-1620
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    • 2010
  • This paper proposes a motion-adaptive 3-D deinterlacing algorithm based on an adaptive-thresholded motion detection and an interpolation method using binary patterns to compensate motion missing and false motion errors. For efficient motion detection, we adaptively decided a threshold value according to the complexity of image. Many edge-based interpolation algorithms have been proposed to improve the subjective quality. Recently, to efficiently interpolate low angle edge and line, a method using predefined binary patterns has been proposed. In this paper, we propose an improved method by modifying the binary patterns. Simulation results have shown that the proposed method provides better performance than the existing methods.