• Title/Summary/Keyword: information expression

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Derivations of Single Hypothetical Don't-Care Minterms Using the Quasi Quine-McCluskey Method

  • Kim, Eungi
    • Journal of Korea Society of Industrial Information Systems
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    • v.18 no.1
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    • pp.25-35
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    • 2013
  • Automatically deriving only individual don't-care minterms that can effectively reduce a Boolean logic expressions are being investigated. Don't-care conditions play an important role in optimizing logic design. The type of unknown don't-care minterms that can always reduce the number of product terms in Boolean expression are referred as single hypothetical don't-care (S-HDC) minterms. This paper describes the Quasi Quine-McCluskey method that systematically derives S-HDC minterms. For the most part, this method is similar to the original Quine-McCluskey method in deriving the prime implicants. However, the Quasi Quine-McCluskey method further derives S-HDC minterms by applying so-called a combinatorial comparison operation. Upon completion of the procedure, the designer can review generated S-HDC minterms to test its appropriateness for a particular application.

Mobile Video Telephony Service Adoption : A Value-based Approach

  • Park, Jong-Sung;Lee, Jung-Hoon;Woo, Hyeok-Jun
    • Journal of Information Technology Applications and Management
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    • v.17 no.2
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    • pp.111-132
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    • 2010
  • Korean telecommunications industry has a large scale market and boasts on high service quality and high technologies enough to provide the mobile video telephony service(the VTS) satisfactorily. For many years, Korean telecommunications companies have been investing enormous amount of money to advertise their VTS widely and to allow their customers to change their cell phones for the 3G(the third generation) devices indispensable for the VTS. However, despite their efforts, the VTS adoption rate in Korea is very low as of January, 2010 and it seems that customers seldom feel the necessity to use. From this viewpoint, it becomes necessary to identify antecedents influencing the intention to use for the VTS empirically. For this purpose, we have proposed several hypotheses from the perspective of the Value-based Adoption Model(VAM). We conducted a survey and found the several factors which influence the value perception of VTS.

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Wavelet-Based Fuzzy Modeling Using a DNA Coding Method (DNA 코딩 기법을 이용한 웨이브렛 기반 퍼지 모델링)

  • Lee, Yeun-Woo;Yu, Jin-Young;Joo, Young-Hoon;Park, Jin-Bae
    • Proceedings of the KIEE Conference
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    • 2003.07d
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    • pp.2040-2042
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    • 2003
  • In this paper, we propose a new method about wavelet-based fuzzy modeling using a DNA coding method. DNA coding techniques is known that expression of knowledge is various than Genetic Algorithm(GA) usually by made optimization technique because done base in structure of biologic DNA and optimization performance is superior. The reposed method make fuzzy system model in wavelet transform and equivalence relation after identification with coefficient of wavelet transform using a DNA coding techniques. Also, can get fuzzy model effectively of nonlinear system using advantage of strong wavelet transform about function that have sudden change. In this paper, in order to demonstrate the superiority of the proposed method compared with GA.

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Interaction using Speech and a Virtual Stick in a CAVE

  • Fujishiro, Kanzan;Takahashi, Hiroki;Nakajima, Masayuki
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 1999.06a
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    • pp.207-212
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    • 1999
  • In VEs (virtual environments) such as a CAVE system, there are three important operations : executive command decision, object selection and 3-D (three-dimensional) pointing. It is necessary to implement these operations in VEs intuitively and accessibly. In CAVE, it is possible for examines to walk and change their viewpoints freely. Then, the input devices which have excellent portability and rich expression are desired. Speech input satisfies both requirements. It is, however, very difficult for the speech input to indicate an exact point in 3-D space. Therefore, an extendable virtual stick is employed and it supports speech input. This paper proposes a user friendly interface using speech and a virtual stick in CAVE system. In this paper, several applications appropriate for the proposed interface are developed. Some problems are pointed out from the applications.

Basic Implementation of Multi Input CNN for Face Recognition (얼굴인식을 위한 다중입력 CNN의 기본 구현)

  • Cheema, Usman;Moon, Seungbin
    • Annual Conference of KIPS
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    • 2019.10a
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    • pp.1002-1003
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    • 2019
  • Face recognition is an extensively researched area of computer vision. Visible, infrared, thermal, and 3D modalities have been used against various challenges of face recognition such as illumination, pose, expression, partial information, and disguise. In this paper we present a multi-modal approach to face recognition using convolutional neural networks. We use visible and thermal face images as two separate inputs to a multi-input deep learning network for face recognition. The experiments are performed on IRIS visible and thermal face database and high face verification rates are achieved.

Face Recognition Using Feature Information and Neural Network

  • Chung, Jae-Mo;Bae, Hyeon;Kim, Sung-Shin
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.55.2-55
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    • 2001
  • The statistical analysis of the feature extraction and the neural networks are proposed to recognize a human face. In the preprocessing step, the normalized skin color map with Gaussian functions is employed to extract the region efface candidate. The feature information in the region of face candidate is used to detect a face region. In the recognition step, as a tested, the 360 images of 30 persons are trained by the backpropagation algorithm. The images of each person are obtained from the various direction, pose, and facial expression, Input variables of the neural networks are the feature information that comes from the eigenface spaces. The simulation results of 30 persons show that the proposed method yields high recognition rates.

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An Improved PSO Algorithm for the Classification of Multiple Power Quality Disturbances

  • Zhao, Liquan;Long, Yan
    • Journal of Information Processing Systems
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    • v.15 no.1
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    • pp.116-126
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    • 2019
  • In this paper, an improved one-against-one support vector machine algorithm is used to classify multiple power quality disturbances. To solve the problem of parameter selection, an improved particle swarm optimization algorithm is proposed to optimize the parameters of the support vector machine. By proposing a new inertia weight expression, the particle swarm optimization algorithm can effectively conduct a global search at the outset and effectively search locally later in a study, which improves the overall classification accuracy. The experimental results show that the improved particle swarm optimization method is more accurate than a grid search algorithm optimization and other improved particle swarm optimizations with regard to its classification of multiple power quality disturbances. Furthermore, the number of support vectors is reduced.

Real-time Dehazing Algorithm using Haze Modeling Expression (안개 모델링 식을 이용한 실시간 안개제거 알고리즘)

  • Lee, Jae-Won;Hong, Sung-Hoon
    • Annual Conference of KIPS
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    • 2013.05a
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    • pp.350-352
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    • 2013
  • 야외에서 촬영된 영상은 안개나 연무 등에 의한 화질 저하가 나타난다. 이를 해결하기 위하여 안개제거를 위한 여러 장의 영상, 추가정보를 이용하는 안개제거 방법과 한 장의 영상을 이용한 안개제거 방법들이 제안되어왔다. 본 논문에서는 한 장의 영상에서 안개나 연기를 제거하여 가시성이 향상된 영상을 제공하는 방법을 제안한다. 이를 위하여 본 논문에서는 안개영상 모델에 대한 2차원 방정식 풀이를 통해 원 영상에 안개가 어느 정도의 비율로 섞여있는지를 나타내는 전달률(transmission rate)을 계산하고, 계산된 전달률을 이용하여 안개가 제거된 영상을 구한다. 제안된 방식은 기존 방법들과 달리 필터를 사용하지 않고 화소단위의 연산만을 사용하므로 후광효과가 발생하지 않고, 연산량이 매우 적어 실시간 처리가 가능하다.

Expression Power Anlaysis among the Existing Event Represent Methods based on Event Representation Components (이벤트 표현 구성요소 기반의 기존 이벤트 표현 방법들의 표현력 분석)

  • Seong, Cheol-Je;Kim, Changhwa;Park, Soo-Hyun
    • Annual Conference of KIPS
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    • 2013.11a
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    • pp.361-364
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    • 2013
  • 이벤트란 객체 상태 변화에 따른 상황 변화를 의미한다. 이벤트를 표현할 때 어떤 요소들을 표현하느냐에 따라 유추할 수 있는 정보 내용이 각각 달라진다. 본 논문은 일반적인 이벤트 표현을 위해 필요한 구성요소들을 제안하고 이 구성요소들을 기반으로 기존에 제안된 이벤트 표현 방법들을 분석 비교한다. 본 논문에서 제안한 이벤트 표현 구성요소들은 표현력 측면에서 이벤트 표현 방법들을 분석하고 비교하는데 타당한 기준이 될 수 있고 향 후 이벤트를 표현하거나 추론하는 방법 혹은 언어를 개발하는데 필수적인 요소가 될 수 있다. 또한 논문에서 제시한 기존 이벤트 표현 방법 분석과 비교는 사용자가 이벤트 표현 방법을 선택하는데 있어 좋은 가이드라인이 될 수 있다.

Dimensionality Reduction of RNA-Seq Data

  • Al-Turaiki, Isra
    • International Journal of Computer Science & Network Security
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    • v.21 no.3
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    • pp.31-36
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    • 2021
  • RNA sequencing (RNA-Seq) is a technology that facilitates transcriptome analysis using next-generation sequencing (NSG) tools. Information on the quantity and sequences of RNA is vital to relate our genomes to functional protein expression. RNA-Seq data are characterized as being high-dimensional in that the number of variables (i.e., transcripts) far exceeds the number of observations (e.g., experiments). Given the wide range of dimensionality reduction techniques, it is not clear which is best for RNA-Seq data analysis. In this paper, we study the effect of three dimensionality reduction techniques to improve the classification of the RNA-Seq dataset. In particular, we use PCA, SVD, and SOM to obtain a reduced feature space. We built nine classification models for a cancer dataset and compared their performance. Our experimental results indicate that better classification performance is obtained with PCA and SOM. Overall, the combinations PCA+KNN, SOM+RF, and SOM+KNN produce preferred results.