• Title/Summary/Keyword: Data Labeling

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A Slice Information Based Labeling Algorithm for 3-D Volume Data (Slice 정보에 기반한 3차원 볼륨 데이터의 레이블링 알고리즘)

  • 최익환;최현주;이병일;최흥국
    • Journal of KIISE:Software and Applications
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    • v.31 no.7
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    • pp.922-928
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    • 2004
  • We propose a new 3 dimensional labeling method based on slice information for the volume data. This method is named SIL (Slice Information based Labeling). Compare to the conventional algorithms, it has advantages that the use of memory is efficient and it Is possible to combine with a variety of 2 dimensional labeling algorithms for finding an appropriate labeling algorithm to its application. In this study, we applied SIL to confocal microscopy images of cervix cancer cell and compared the results of labeling. According to the measurement, we found that the speed of Sd combined with, CCCL (Contour based Connected Component Labeling) is almost 2 times higher than that of other methods. In conclusion, considering that the performance of labeling depends on a kind of image, we obtained that the proposed method provide better result for the confocal microscopy cell volume data.

A Circle Labeling Scheme without Re-labeling for Dynamically Updatable XML Data (동적으로 갱신가능한 XML 데이터에서 레이블 재작성하지 않는 원형 레이블링 방법)

  • Kim, Jin-Young;Park, Seog
    • Journal of KIISE:Databases
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    • v.36 no.2
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    • pp.150-167
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    • 2009
  • XML has become the new standard for storing, exchanging, and publishing of data over both the internet and the ubiquitous data stream environment. As demand for efficiency in handling XML document grows, labeling scheme has become an important topic in data storage. Recently proposed labeling schemes reflect the dynamic XML environment, which itself provides motivation for the discovery of an efficient labeling scheme. However, previous proposed labeling schemes have several problems: 1) An insertion of a new node into the XML document triggers re-labeling of pre-existing nodes. 2) They need larger memory space to store total label. etc. In this paper, we introduce a new labeling scheme called a Circle Labeling Scheme. In CLS, XML documents are represented in a circular form, and efficient storage of labels is supported by the use of concepts Rotation Number and Parent Circle/Child Circle. The concept of Radius is applied to support inclusion of new nodes at arbitrary positions in the tree. This eliminates the need for re-labeling existing nodes and the need to increase label length, and mitigates conflict with existing labels. A detailed experimental study demonstrates efficiency of CLS.

Effect on self-enhancement of deep-learning inference by repeated training of false detection cases in tunnel accident image detection (터널 내 돌발상황 오탐지 영상의 반복 학습을 통한 딥러닝 추론 성능의 자가 성장 효과)

  • Lee, Kyu Beom;Shin, Hyu Soung
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.21 no.3
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    • pp.419-432
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    • 2019
  • Most of deep learning model training was proceeded by supervised learning, which is to train labeling data composed by inputs and corresponding outputs. Labeling data was directly generated manually, so labeling accuracy of data is relatively high. However, it requires heavy efforts in securing data because of cost and time. Additionally, the main goal of supervised learning is to improve detection performance for 'True Positive' data but not to reduce occurrence of 'False Positive' data. In this paper, the occurrence of unpredictable 'False Positive' appears by trained modes with labeling data and 'True Positive' data in monitoring of deep learning-based CCTV accident detection system, which is under operation at a tunnel monitoring center. Those types of 'False Positive' to 'fire' or 'person' objects were frequently taking place for lights of working vehicle, reflecting sunlight at tunnel entrance, long black feature which occurs to the part of lane or car, etc. To solve this problem, a deep learning model was developed by simultaneously training the 'False Positive' data generated in the field and the labeling data. As a result, in comparison with the model that was trained only by the existing labeling data, the re-inference performance with respect to the labeling data was improved. In addition, re-inference of the 'False Positive' data shows that the number of 'False Positive' for the persons were more reduced in case of training model including many 'False Positive' data. By training of the 'False Positive' data, the capability of field application of the deep learning model was improved automatically.

Efficient Access Control Labeling for Secure Query Processing on Dynamic XML Data Streams (동적 XML 데이타 스트링의 안전한 질의 처리를 위한 효율적인 접근제어 레이블링)

  • An, Dong-Chan;Park, Seog
    • Journal of KIISE:Databases
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    • v.36 no.3
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    • pp.180-188
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    • 2009
  • Recently, the needs for an efficient and secure access control method of dynamic XML data in a ubiquitous data streams environment have become an active research area. In this paper, we proposed an improved role-based prime number labeling scheme for an efficient and secure access control labeling method in dynamic XML data streams. And we point out the limitations of existing access control and labeling schemes for XML data assuming that documents are frequently updated. The improved labeling method where labels are encoded ancestor-descendant and sibling relationships between nodes but need not to be regenerated when the document is updated. Our improved role-based prime number labeling scheme supports an infinite number of updates and guarantees the arbitrary nodes insertion at arbitrary position of the XML tree without label collisions. Also we implemented an efficient access control using a role-based prime number labeling. Finally, we have shown that our approach is an efficient and secure through experiments.

Recognition of Nutrition Labeling of Korean Restaurants among Adults in Gyeonggi-do Area (경기 일부지역 거주 성인의 한식당 영양표시에 대한 인식)

  • Pak, Hee-Ok;Sohn, Chun-Young
    • The Korean Journal of Food And Nutrition
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    • v.26 no.4
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    • pp.663-669
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    • 2013
  • The aim of this study is to highlight the importance of the correct food choices and nutrition management through nutrition labeling and provide basic data for building a nutrition labeling system for Korean restaurants. In the study, a survey was conducted from February 5th to February 27th in 2010 involving adults over the age of 20 living in part of the Gyeonggi-do area. The data was used to analyze the general characteristics, the awareness of nutrition labeling and the nutrition labeling contents by using the SPSS 18.0 package program. Among the 268 people surveyed, the total number of women was greater (60.4%) than men (39.6%). The perception of the necessity of nutrition labeling was a relatively high score of 3.99 on a 1 to 5 scale and the motivation to utilize nutrition labeling scored 3.89. The study found that females perceived nutrition labeling to be more important than did the males. In addition, the perception varied according to the level of education and age. In conclusion, since customers have a high demand for nutrition labeling in Korean restaurants and are motivated to utilize labeling when eating-out is relatively strong, labeling would be a good educational tool for leading a healthy food life. Furthermore, since the study found that differences occur between nutrition labeling contents or nutrients according to general characteristics, food service companies might be able to gain benefits through differentiated nutrition labeling that is catered for their main customers.

Labeling and Customer Loyalty: Mediating Effects of Brand-related Constructs

  • Gulzira, Zheltauova;Han, Sang-Lin
    • Asia Marketing Journal
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    • v.20 no.4
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    • pp.65-94
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    • 2019
  • The purpose of this study was to analyze the brand loyalty formation by positive labeling. Affecting such factors as involvement, self-image, community engagement, preference, and choice cutback, positive labeling can be seen as one of psychological factors that shapes consumer's behavior and their decision. This study was carried out because little research was done to examine the influence of positive labeling toward brand loyalty, and also to find out the benefits that consumers can get from being labeled in positive terms. Data were collected through survey questionnaire and 151 usable responses were used. Following a series of pretests and confirmatory factor analysis helped to purify measures and verify the psychometric properties of the scale. Structural equation modeling with AMOS was used for testing of research hypotheses. The result of data analysis demonstrated the positive relationship between labeling and brand loyalty, i.e. positive labeling indirectly leads to consumers' loyalty toward a brand. Findings revealed significant relationship between involvement and emotional attachment, as well as the relationship between community engagement and choice cutback. The results gave support for the hypothesis of moderating effect of buzz on the relationship between involvement and emotional attachment, even though the hypothesis of moderating effect of distinction was rejected. Taking Apple's rivalry strategy as initial point, this study highlights the role of labeling in creating social identity. The study attempts to show the positive consequences of labeling strategy for firms that seeks ways of good competition without engaging into conflicts.

Design of Fusion Multilabeling System Controlled by Wi-Fi Signals (Wi-Fi신호로 제어되는 융합형 다중라벨기 설계)

  • Lim, Joong-Soo
    • Journal of the Korea Convergence Society
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    • v.6 no.1
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    • pp.1-5
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    • 2015
  • In this paper, we describe the design of a fusion labeling system which is controlled by the Wi-Fi signals. The Current labeling system which is used in the industry is designed to work independently on the production line not connected with internet network services. For such reasons, it is very inconvenient for the labeling system to transfer such labeling data of the production line to the server computer. We propose a labeling system connected to the Wi-Fi service being able to send real-time transmission of labeling data. This system can supply the labeling data of production line to the server computer in realtime and improve the production quality than the existing system.

The effects of labeling gap and susceptibility artifacts in pCASL perfusion MRI (pCASL 관류 영상에서 표지 간격과 자화감수성 인공물이 영상에 미치는 영향)

  • Kim, Seong-Hu
    • Journal of the Korean Society of Radiology
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    • v.9 no.4
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    • pp.213-217
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    • 2015
  • To report problems found in a patient who has implemented stent implantation and then conducted a perfusion MRI using ASL(Arterial Spin Labeling), in order to suggest a solution to them. The perfusion MRI was conducted, using pCASL among ASL methods. Data from pCASL(Pseudo Continuous Arterial Spin Labeling) was acquired together with the structural image simply by changing position(labeling gap 15 mm, 170 mm) of the labeling pulse to avoid stent. Data was processed through the ASLtbx. When perfusion MRI was acquired using pCASL, it showed that the position of the conventional labeling pulse (labeling gap 24 mm) was overlapped with that of stent, which made signal intensity in right brain tissue appear as if it were void. When the labeling pulse was positioned (labeling gap 15 mm) to avoid stent, high signal intensity images were acquired. In labeling pulse (labeling gap 170 mm), the signal intensity was more reduced due to relaxation before labeled blood arrived at the imaging slice. pCASL can be stably repeated measurements because it does not use a contrast agent. And it should be selected with the appropriate image acquisition parameters for the high quality image.

An Analysis of the methods to alleviate the cost of data labeling in Deep learning (딥 러닝에서 Labeling 부담을 줄이기 위한 연구분석)

  • Han, Seokmin
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.1
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    • pp.545-550
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    • 2022
  • In Deep Learning method, it is well known that it requires large amount of data to train the deep neural network. And it also requires the labeling of each data to fully train the neural network, which means that experts should spend lots of time to provide the labeling. To alleviate the problem of time-consuming labeling process, some methods have been suggested such as weak-supervised method, one-shot learning, self-supervised, suggestive learning, and so on. In this manuscript, those methods are analyzed and its possible future direction of the research is suggested.

Recognition and Use of Nutrition Labeling According to Age Groups of Housewives in Siheung, Gyeonggi Province (경기도 시흥지역 주부들의 연령에 따른 영양표시 인식과 이용실태)

  • Keum-Ok Lee;Wookyoun Cho
    • Journal of the Korean Society of Food Culture
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    • v.38 no.6
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    • pp.373-380
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    • 2023
  • In this study, 294 housewives in Siheung, Gyeonggi-do, were surveyed to evaluate the differences in the recognition and use of nutrition labeling according to age and to present data for nutrition education. The younger the age, the more aware the consumer was of the information on the nutrition label. Housewives who were younger than 60 years were more likely to check the nutrition labels. The lower the age, the higher the reliance on the nutritional labeling content of the food, and the higher the recognition level of nutritional labeling. It was found that the lower the age, the easier it was for the consumer to understand the nutritional labeling. Among housewives in their 30s and younger, 89.5 percent said they believed checking nutrition labels would help their health. In the younger age group knowledge and information on nutrition labeling was acquired from the internet, and in the older age group, knowledge was acquired from television, radio, and newspapers. Research conducted on housewives in other regions in the future could provide more detailed information suitable for the population of each region. This would serve as data for nutrition education on the recognition and use of nutrition labeling for a healthy diet.