• 제목/요약/키워드: Random extraction

검색결과 202건 처리시간 0.026초

랜덤 변환 로고를 사용한 워터마킹과 견고성 (Robustness of Watermarking Using Random Dot Image Transformed with a Logo)

  • 이인정
    • 한국산업정보학회:학술대회논문집
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    • 한국산업정보학회 2003년도 추계공동학술대회
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    • pp.729-732
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    • 2003
  • In this paper, the transformed logo image is used as a watermark image, then the extraction rate is good when the logo image is transformed into randomly distribute Image domain. The robustness is good resist of clipping and noise.

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블록 움직임벡터 기반의 움직임 객체 추출 (Moving Object Extraction Based on Block Motion Vectors)

  • 김동욱;김호준
    • 한국정보통신학회논문지
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    • 제10권8호
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    • pp.1373-1379
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    • 2006
  • 움직임 객체의 추출은 비디오 서비스 등에서 주요한 연구목적 중의 하나이다. 본 논문은 블록 움직임 벡터를 이용하여 움직임 객체를 추출하는 새로운 기법을 제시한다. 이를 위하여, 1) 사후 확률 밀도와 Gibbs 랜덤필드의 이용하여 블록 움직임 벡터를 결정하고, 2) 2-D 히스토그램을 바탕으로 전역 움직임을 구하고, 3) 경계 블록 분할 단계를 통해 객체 추출을 달성한다. 제안된 알고리듬은 특히 압축된 비디오 신호의 움직임 객체에 특히 유용하게 이용될 수 있다. 제안된 알고리듬을 여러 가지 영상에 적용한 결과 양호한 결과를 얻을 수 있었다.

배전기기 고장률 추출에 관한 연구 (A Study on Failure Rate Extraction of Power Distribution System Equipment)

  • 문종필;김재철;이희태;추철민;안재민
    • 한국조명전기설비학회:학술대회논문집
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    • 한국조명전기설비학회 2007년도 춘계학술대회 논문집
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    • pp.366-368
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    • 2007
  • In this paper, the Time-varying Failure Rate (TFR) of power distribution system equipment is extracted from the recorded failure data of Korea Electric Power Corporation (KEPCO). For TFR extraction, it is used that the fault data accumulated by KEPCO during 10 years. The TFR is approximated to bathtub curve using the exponential (random failure) and Weibull (aging failure) distribution function. In addition, Kaplan-Meier estimation is applied to TFR extraction because of incomplete failure data of KEPCO. Finally, Probability plot and regression analysis is applied. It is presented that the extracted TFR is more effective and useful than Mean Failure Rate (MFR) through the comparison between TFR and MFR.

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Extracting meeting location from seminar and conference announcement in English

  • Kim, Anatoliy;Choi, Dong-Hyun;Choi, Key-Sun
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2011년도 한국컴퓨터종합학술대회논문집 Vol.38 No.1(C)
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    • pp.258-261
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    • 2011
  • Living in the age of information people face problems related to information overload. Information is easy to produce, store and distribute through various communication channels, one of which is emails. With the appearance of the mobile devices, such as smart phones and tabs, people can have access to email inbox at any moment of time from everywhere. In this paper we present information extraction system with a specific goal of extracting meeting location from the announcement of seminar or conference. We apply a machine learning method (conditional random fields, CRF), train the system using annotated corpus of seminar and conference announcements and validate results by applying various extracted correction rules and patterns. Furthermore, we normalize extracted location, and reference using geo-coding databases, OpenStreetMap and Wikipedia resources to determine real geographical coordinates.

메타데이터를 활용한 기록물 자동분류 성능 요소 비교 (Comparison of Performance Factors for Automatic Classification of Records Utilizing Metadata)

  • 김영범;장우권
    • 정보관리학회지
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    • 제40권3호
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    • pp.99-118
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    • 2023
  • 이 연구의 목적은 기록물의 맥락정보를 담고 있는 메타데이터를 활용하여 기록물 자동분류 과정에서의 성능요소를 파악하는데 있다. 연구를 위해 2022년 중앙행정기관 원문정보 약 97,064건을 수집하였다.수집한 데이터를 대상으로 다양한 분류 알고리즘과 데이터선정방법, 문헌표현기법을 적용하고 그 결과를 비교하여 기록물 자동 분류를 위한 최적의 성능요소를 파악하고자 하였다. 연구 결과 분류 알고리즘으로는 Random Forest가, 문헌표현기법으로는 TF 기법이 가장 높은 성능을 보였으며, 단위과제의 최소데이터 수량은 성능에 미치는 영향이 미미하였고 자질은 성능변화에 명확한 영향을 미친다는 것이 확인되었다.

Application of ChatGPT text extraction model in analyzing rhetorical principles of COVID-19 pandemic information on a question-and-answer community

  • Hyunwoo Moon;Beom Jun Bae;Sangwon Bae
    • International journal of advanced smart convergence
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    • 제13권2호
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    • pp.205-213
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    • 2024
  • This study uses a large language model (LLM) to identify Aristotle's rhetorical principles (ethos, pathos, and logos) in COVID-19 information on Naver Knowledge-iN, South Korea's leading question-and-answer community. The research analyzed the differences of these rhetorical elements in the most upvoted answers with random answers. A total of 193 answer pairs were randomly selected, with 135 pairs for training and 58 for testing. These answers were then coded in line with the rhetorical principles to refine GPT 3.5-based models. The models achieved F1 scores of .88 (ethos), .81 (pathos), and .69 (logos). Subsequent analysis of 128 new answer pairs revealed that logos, particularly factual information and logical reasoning, was more frequently used in the most upvoted answers than the random answers, whereas there were no differences in ethos and pathos between the answer groups. The results suggest that health information consumers value information including logos while ethos and pathos were not associated with consumers' preference for health information. By utilizing an LLM for the analysis of persuasive content, which has been typically conducted manually with much labor and time, this study not only demonstrates the feasibility of using an LLM for latent content but also contributes to expanding the horizon in the field of AI text extraction.

A Clustering Approach for Feature Selection in Microarray Data Classification Using Random Forest

  • Aydadenta, Husna;Adiwijaya, Adiwijaya
    • Journal of Information Processing Systems
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    • 제14권5호
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    • pp.1167-1175
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    • 2018
  • Microarray data plays an essential role in diagnosing and detecting cancer. Microarray analysis allows the examination of levels of gene expression in specific cell samples, where thousands of genes can be analyzed simultaneously. However, microarray data have very little sample data and high data dimensionality. Therefore, to classify microarray data, a dimensional reduction process is required. Dimensional reduction can eliminate redundancy of data; thus, features used in classification are features that only have a high correlation with their class. There are two types of dimensional reduction, namely feature selection and feature extraction. In this paper, we used k-means algorithm as the clustering approach for feature selection. The proposed approach can be used to categorize features that have the same characteristics in one cluster, so that redundancy in microarray data is removed. The result of clustering is ranked using the Relief algorithm such that the best scoring element for each cluster is obtained. All best elements of each cluster are selected and used as features in the classification process. Next, the Random Forest algorithm is used. Based on the simulation, the accuracy of the proposed approach for each dataset, namely Colon, Lung Cancer, and Prostate Tumor, achieved 85.87%, 98.9%, and 89% accuracy, respectively. The accuracy of the proposed approach is therefore higher than the approach using Random Forest without clustering.

Extraction of the mode shapes of a segmented ship model with a hydroelastic response

  • Kim, Yooil;Ahn, In-Gyu;Park, Sung-Gun
    • International Journal of Naval Architecture and Ocean Engineering
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    • 제7권6호
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    • pp.979-994
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    • 2015
  • The mode shapes of a segmented hull model towed in a model basin were predicted using both the Proper Orthogonal Decomposition (POD) and cross random decrement technique. The proper orthogonal decomposition, which is also known as Karhunen-Loeve decomposition, is an emerging technology as a useful signal processing technique in structural dynamics. The technique is based on the fact that the eigenvectors of a spatial coherence matrix become the mode shapes of the system under free and randomly excited forced vibration conditions. Taking advantage of the simplicity of POD, efforts have been made to reveal the mode shapes of vibrating flexible hull under random wave excitation. First, the segmented hull model of a 400 K ore carrier with 3 flexible connections was towed in a model basin under different sea states and the time histories of the vertical bending moment at three different locations were measured. The measured response time histories were processed using the proper orthogonal decomposition, eventually to obtain both the first and second vertical vibration modes of the flexible hull. A comparison of the obtained mode shapes with those obtained using the cross random decrement technique showed excellent correspondence between the two results.

RIE 공정을 이용한 유기발광다이오드의 광 산란층 제작 (Fabrication of Scattering Layer for Light Extraction Efficiency of OLEDs)

  • 배은정;장은비;최근수;서가은;장승미;박영욱
    • 반도체디스플레이기술학회지
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    • 제21권1호
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    • pp.95-102
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    • 2022
  • Since the organic light-emitting diodes (OLEDs) have been widely investigated as next-generation displays, it has been successfully commercialized as a flexible and rollable display. However, there is still wide room and demand to improve the device characteristics such as power efficiency and lifetime. To solve this issue, there has been a wide research effort, and among them, the internal and the external light extraction techniques have been attracted in this research field by its fascinating characteristic of material independence. In this study, a micro-nano composite structured external light extraction layer was demonstrated. A reactive ion etching (RIE) process was performed on the surfaces of hexagonally packed hemisphere micro-lens array (MLA) and randomly distributed sphere diffusing films to form micro-nano composite structures. Random nanostructures of different sizes were fabricated by controlling the processing time of the O2 / CHF3 plasma. The fabricated device using a micro-nano composite external light extraction layer showed 1.38X improved external quantum efficiency compared to the reference device. The results prove that the external light extraction efficiency is improved by applying the micro-nano composite structure on conventional MLA fabricated through a simple process.

3-D MRF를 이용한 동영상 내의 이동 물체의 형상과 움직임 추출 (The Shape and Movement Extraction of the Moving Object in Image Sequences Using 3-D Markov Random Fields)

  • 송효섭;양윤모
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2001년도 봄 학술발표논문집 Vol.28 No.1 (B)
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    • pp.553-555
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    • 2001
  • Markov Random Fields(MRF) 모델은 영상 분할 및 복원 등에 주로 사용되는 확률적 영상모델이다. 본 논문에서는 MRF 모델을 3차원으로 확장하여 분할을 위한 선 필드 모델(Line Field Model)과 움직임 검출을 위한 움직임 필드 모델(Motion Field Model)을 도입하여 동영상 내에서 움직이는 물체의 형상과 움직임을 추정한다. 제안된 방법을 이용하여 한국어 수화 동작에서 손의 형상과 이동방향을 검출하였다. 그 결과 optical flow를 사용하는 방법에 비해서 이동 방향이 왜곡되는 것을 방지하여 보다 정확한 이동 방향을 검출할 수 있었다. 또한 영상 추출의 경우에 있어서도 형상의 윤곽면과 내부가 하나의 라벨(label)로 묶이기 때문에 보다 깨끗한 영상을 추출할 수 있었다.

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