• 제목/요약/키워드: extraction techniques

검색결과 899건 처리시간 0.031초

Blockchain-Enabled Decentralized Clustering for Enhanced Decision Support in the Coffee Supply Chain

  • Keo Ratanak;Muhammad Firdaus;Kyung-Hyune Rhee
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2023년도 추계학술발표대회
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    • pp.260-263
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    • 2023
  • Considering the growth of blockchain technology, the research aims to transform the efficiency of recommending optimal coffee suppliers within the complex supply chain network. This transformation relies on the extraction of vital transactional data and insights from stakeholders, facilitated by the dynamic interaction between the application interface (e.g., Rest API) and the blockchain network. These extracted data are then subjected to advanced data processing techniques and harnessed through machine learning methodologies to establish a robust recommendation system. This innovative approach seeks to empower users with informed decision-making abilities, thereby enhancing operational efficiency in identifying the most suitable coffee supplier for each customer. Furthermore, the research employs data visualization techniques to illustrate intricate clustering patterns generated by the K-Means algorithm, providing a visual dimension to the study's evaluation.

Deep Learning Method for Identification and Selection of Relevant Features

  • Vejendla Lakshman
    • International Journal of Computer Science & Network Security
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    • 제24권5호
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    • pp.212-216
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    • 2024
  • Feature Selection have turned into the main point of investigations particularly in bioinformatics where there are numerous applications. Deep learning technique is a useful asset to choose features, anyway not all calculations are on an equivalent balance with regards to selection of relevant features. To be sure, numerous techniques have been proposed to select multiple features using deep learning techniques. Because of the deep learning, neural systems have profited a gigantic top recovery in the previous couple of years. Anyway neural systems are blackbox models and not many endeavors have been made so as to examine the fundamental procedure. In this proposed work a new calculations so as to do feature selection with deep learning systems is introduced. To evaluate our outcomes, we create relapse and grouping issues which enable us to think about every calculation on various fronts: exhibitions, calculation time and limitations. The outcomes acquired are truly encouraging since we figure out how to accomplish our objective by outperforming irregular backwoods exhibitions for each situation. The results prove that the proposed method exhibits better performance than the traditional methods.

A note on the distance distribution paradigm for Mosaab-metric to process segmented genomes of influenza virus

  • Daoud, Mosaab
    • Genomics & Informatics
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    • 제18권1호
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    • pp.7.1-7.7
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    • 2020
  • In this paper, we present few technical notes about the distance distribution paradigm for Mosaab-metric using 1, 2, and 3 grams feature extraction techniques to analyze composite data points in high dimensional feature spaces. This technical analysis will help the specialist in bioinformatics and biotechnology to deeply explore the biodiversity of influenza virus genome as a composite data point. Various technical examples are presented in this paper, in addition, the integrated statistical learning pipeline to process segmented genomes of influenza virus is illustrated as sequential-parallel computational pipeline.

SVE와 Bioventing 기술을 이용한 유류 오염토양의 복원 (SVE & Bioventing Techniques for the Treatment of Hydrocarbon)

  • 김무훈;강순기;조미영;정우성;박덕신
    • 한국지하수토양환경학회:학술대회논문집
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    • 한국지하수토양환경학회 2000년도 창립총회 및 춘계학술발표회
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    • pp.137-140
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    • 2000
  • The purpose of this study is to see the effect of SVE (Soil Vapor Extraction) and Bioventing (biostimulation) hydrocarbon contaminated areas. The removal rate of VOC for three weeks were 17.43 kg on 3.6 ㎥/hr at steady-state. In the application of Bioventing, every flow rate were tested, and it was found that 4.0 ㎥/hr were adequate for best control of the system. At this stage, the addition of microbial agent accelerated the biodegradation of the hydrocarbon.

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반도체 EDS공정에서의 패턴인식기법을 이용한 불량 유형 자동 분류 방법 연구 (Automatic classification of failure patterns in semiconductor EDS Test using pattern recognition)

  • 한영신;황미영;이칠기
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2003년도 하계종합학술대회 논문집 II
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    • pp.703-706
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    • 2003
  • Yield enhancement in semiconductor fabrication is important. It is ideal to prevent all the failures. However, when a failure occurs, it is important to quickly specify the cause stage and take countermeasure. The automatic method of failure pattern extraction from fail bit map provides reduced time to analysis and facilitates yield enhancement. This paper describes the techniques to automatically classifies a failure pattern using a fail bit map, a new simple schema which facilitates the failure analysis.

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임플란트식립을 위한 치조제증대술 (Alveolar ridge augmentation for implant placement)

  • 유상준
    • 대한치과의사협회지
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    • 제57권12호
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    • pp.768-777
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    • 2019
  • Alveolar bone resorption are unpredictable and always occur after tooth extraction. Such bone resorption causes insufficient alveolar ridge which make implant placement difficult. There are many techniques to increase the alveolar ridge. Representative procedures include ridge split, guided bone regeneration, bone graft using autogenous block bone, and alveolar distraction. In each procedure, there are indications and complications. Depending on the shape and the width of bone defects, we can choose procedures for horizontal bone augmentation and vertical bone augmentation.

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A Study on a Motion Recognition from Moving Images with Camera Works

  • Murakami, Shin-ichi;Tomohiko-Shindoh
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 1998년도 Proceedings of International Workshop on Advanced Image Technology
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    • pp.35-40
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    • 1998
  • This paper describes an automatic recognition method of contents in moving images. The recognition process is carried out by the following two steps. At first, camera works in moving images are analyzed and moving objects are extracted from the moving images. Next, the motion of the object is recognized by pre-procured knowledge. These techniques will be applied to a construction of an efficient image database.

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서명자동검정을 위한 개인별 특징 세트 선택 (Customised feature set selection for automatic signature verification)

  • 배영래;조동욱;김지영
    • 한국통신학회논문지
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    • 제21권7호
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    • pp.1642-1653
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    • 1996
  • This paper covers feature extraction for automatic handwritten signature verification. Several major feature selection techniques are investigated from a practical perspective to realise an optimal signature verification system, and customised feature set selection based on set-on-set distance measurement is presented. The experimental results have proved the proposed methods to be efficient, offering considerably improved verification performance compared to conventional methods. Also, they dramatically reduce the processing complexity in the verification system.

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