• Title/Summary/Keyword: Long Tail

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A Study on Sigma Level and Its Calculation (시그마 수준과 계산 방법에 대한 고찰)

  • 박준오;박성현
    • Journal of Korean Society for Quality Management
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    • v.31 no.2
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    • pp.194-204
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    • 2003
  • It is very important to understand and interpret the meaning of the sigma level correctly through the Six Sigma project. Especially, the confusion over the relation between sigma level from the short-term point of view and defective proportion or DPMO from the long-term point of view may make a big gap between expected results of the Six Sigma project and real results in the field. The one-tail approximation is commonly used to calculate the sigma level both in most literatures introducing Six Sigma and actual cases of the Six Sigma project. Since the one-tail approximation undervalues the sigma level of the fields such as business and service of which the sigma level is generally low, however. there can be misleading results of the explanation of the sigma level and inappropriate project evaluation. This paper describes the relation between sigma level and defective proportion in detail and clears the difference between the one-tail and two-tail approximation.

Review of Application Models According to the Classification of Asymptotic Tail Distribution (근사 꼬리분포의 유형별 적용 모형 고찰)

  • Choi, Sung-Woon
    • Proceedings of the Safety Management and Science Conference
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    • 2010.11a
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    • pp.35-39
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    • 2010
  • The research classifies three types of asymptotic tail distributions such as long(heavy, thick) tailed distribution, medium tailed distribution and short(light, thin) tailed distribution. The extreme value distributions(EVD) classified in this paper can be used in SPC(Statistical Process Control) control chart and reliability engineering.

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LONG-TIME BEHAVIOR FOR SEMILINEAR DEGENERATE PARABOLIC EQUATIONS ON ℝN

  • Cung, The Anh;Le, Thi Thuy
    • Communications of the Korean Mathematical Society
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    • v.28 no.4
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    • pp.751-766
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    • 2013
  • We study the existence and long-time behavior of solutions to the following semilinear degenerate parabolic equation on $\mathbb{R}^N$: $$\frac{{\partial}u}{{\partial}t}-div({\sigma}(x){\nabla}u+{\lambda}u+f(u)=g(x)$$, under a new condition concerning a variable non-negative diffusivity ${\sigma}({\cdot})$. Some essential difficulty caused by the lack of compactness of Sobolev embeddings is overcome here by exploiting the tail-estimates method.

Image Classification using Class-Balanced Loss (Class-Balanced Loss를 이용한 이미지 분류)

  • Jihee Park;Wonjun Hwang
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2022.11a
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    • pp.164-166
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    • 2022
  • Long-tail problem은 class 별로 sample의 개수에 차이가 있어 성능에 안 좋은 영향을 미치는 것을 말한다. 본 논문에서는 cost-sensitive learning 중 Class-Balanced Loss를 이용해 성능을 개선하여 Long-tail problem을 해결하려고 한다. 먼저, balanced data set과 imbalanced data set의 성능 차이를 살펴보도록 할 것이다. 그 후, Class-Balanced Loss를 3가지 버전으로 이용해 그 성능을 측정하고 분석해 볼 것이다.

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A Case of Rapunzel Syndrome

  • Kim, Joon Sung;Nam, Chang Woo
    • Pediatric Gastroenterology, Hepatology & Nutrition
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    • v.16 no.2
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    • pp.127-130
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    • 2013
  • Rapunzel syndrome refers to a very rare condition in which swallowed hair forms a gastric trichobezoar that has a long tail extending into the small bowel. We describe a case of Rapunzel syndrome in an 8-year-old girl who presented with abdominal mass, epigastric pain and vomiting. Abdominal computed tomography scan showed a markedly dilated stomach filled with coarse heterogeneous materials. Upper gastrointestinal endoscopy revealed a huge hairy ball with a tail extending through the pylorus. We performed a surgical laparotomy and successfully removed a huge trichobezoar with a long tail extending into the middle portion of jejunum. Psychiatric consultation with review showed her past history of trichotillomania and trichophagia 4 years ago. But her parents denied further psychiatric therapy and she was lost to the follow-up. Rapunzel syndrome should be included in the differential diagnosis in children with chronic abdominal pain and trichophagia.

CLOSURE PROPERTY AND TAIL PROBABILITY ASYMPTOTICS FOR RANDOMLY WEIGHTED SUMS OF DEPENDENT RANDOM VARIABLES WITH HEAVY TAILS

  • Dindiene, Lina;Leipus, Remigijus;Siaulys, Jonas
    • Journal of the Korean Mathematical Society
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    • v.54 no.6
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    • pp.1879-1903
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    • 2017
  • In this paper we study the closure property and probability tail asymptotics for randomly weighted sums $S^{\Theta}_n={\Theta}_1X_1+{\cdots}+{\Theta}_nX_n$ for long-tailed random variables $X_1,{\ldots},X_n$ and positive bounded random weights ${\Theta}_1,{\ldots},{\Theta}_n$ under similar dependence structure as in [26]. In particular, we study the case where the distribution of random vector ($X_1,{\ldots},X_n$) is generated by an absolutely continuous copula.

Generating and Controlling an Interlinking Network of Technical Terms to Enhance Data Utilization (데이터 활용률 제고를 위한 기술 용어의 상호 네트워크 생성과 통제)

  • Jeong, Do-Heon
    • Journal of the Korean Society for information Management
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    • v.35 no.1
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    • pp.157-182
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    • 2018
  • As data management and processing techniques have been developed rapidly in the era of big data, nowadays a lot of business companies and researchers have been interested in long tail data which were ignored in the past. This study proposes methods for generating and controlling a network of technical terms based on text mining technique to enhance data utilization in the distribution of long tail theory. Especially, an edit distance technique of text mining has given us efficient methods to automatically create an interlinking network of technical terms in the scholarly field. We have also used linked open data system to gather experimental data to improve data utilization and proposed effective methods to use data of LOD systems and algorithm to recognize patterns of terms. Finally, the performance evaluation test of the network of technical terms has shown that the proposed methods were useful to enhance the rate of data utilization.

Geometric and Semantic Improvement for Unbiased Scene Graph Generation

  • Ruhui Zhang;Pengcheng Xu;Kang Kang;You Yang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.10
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    • pp.2643-2657
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    • 2023
  • Scene graphs are structured representations that can clearly convey objects and the relationships between them, but are often heavily biased due to the highly skewed, long-tailed relational labeling in the dataset. Indeed, the visual world itself and its descriptions are biased. Therefore, Unbiased Scene Graph Generation (USGG) prefers to train models to eliminate long-tail effects as much as possible, rather than altering the dataset directly. To this end, we propose Geometric and Semantic Improvement (GSI) for USGG to mitigate this issue. First, to fully exploit the feature information in the images, geometric dimension and semantic dimension enhancement modules are designed. The geometric module is designed from the perspective that the position information between neighboring object pairs will affect each other, which can improve the recall rate of the overall relationship in the dataset. The semantic module further processes the embedded word vector, which can enhance the acquisition of semantic information. Then, to improve the recall rate of the tail data, the Class Balanced Seesaw Loss (CBSLoss) is designed for the tail data. The recall rate of the prediction is improved by penalizing the body or tail relations that are judged incorrectly in the dataset. The experimental findings demonstrate that the GSI method performs better than mainstream models in terms of the mean Recall@K (mR@K) metric in three tasks. The long-tailed imbalance in the Visual Genome 150 (VG150) dataset is addressed better using the GSI method than by most of the existing methods.

Post-transcriptional and translational regulation of mRNA-like long non-coding RNAs by microRNAs in early developmental stages of zebrafish embryos

  • Lee, Kyung-Tae;Nam, Jin-Wu
    • BMB Reports
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    • v.50 no.4
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    • pp.226-231
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    • 2017
  • At the post-transcriptional and translational levels, microRNA (miRNA) represses protein-coding genes via seed pairing to the 3' untranslated regions (UTRs) of mRNA. Although working models of miRNA-mediated gene silencing are successfully established using miRNA transfections and knockouts, the regulatory interaction between miRNA and long non-coding RNA (lncRNA) remain unknown. In particular, how the mRNA-resembling lncRNAs with 5' cap, 3' poly(A)-tail, or coding features, are regulated by miRNA is yet to be examined. We therefore investigated the functional interaction between miRNAs and lncRNAs with/without those features, in miRNA-transfected early zebrafish embryos. We observed that the greatest determinants of the miRNA-mediated silencing of lncRNAs were the 5' cap and 3' poly(A)-tails in lncRNAs, at both the post-transcriptional and translational levels. The lncRNAs confirmed to contain 5' cap, 3' poly(A)-tail, and the canonical miRNA target sites, were observed to be repressed in the level of both RNA and ribosome-protected fragment, while those with the miRNA target sites and without 5' cap and 3' poly(A)-tail, were not robustly repressed by miRNA introduction, thus suggesting a role as a miRNA-decoy.