• Title/Summary/Keyword: science network

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Wild Image Object Detection using a Pretrained Convolutional Neural Network

  • Park, Sejin;Moon, Young Shik
    • IEIE Transactions on Smart Processing and Computing
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    • v.3 no.6
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    • pp.366-371
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    • 2014
  • This paper reports a machine learning approach for image object detection. Object detection and localization in a wild image, such as a STL-10 image dataset, is very difficult to implement using the traditional computer vision method. A convolutional neural network is a good approach for such wild image object detection. This paper presents an object detection application using a convolutional neural network with pretrained feature vector. This is a very simple and well organized hierarchical object abstraction model.

The Application of Network Theory to Subway Transportation in Seoul, Korea

  • 김채복;김학수;김성인
    • Journal of the Korean Operations Research and Management Science Society
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    • v.14 no.2
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    • pp.81-81
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    • 1989
  • Network approach is used to find the shortest paths and transportation time between the subway stations in Seoul, Korea. Because of transfer stations, we reconstruct the subway network to compute the shortest routes and corresponding transportation times. The reconstructed network is useful to obtain desired information because it can handle the transfer time between tracks. Time and route information about the subway system is obtained and it will be displayed in the subway guide board at each station. Then, all passengers can have the information of shortest route to a destination and corresponding transportation time.

On the Design of Statistical Software in the Network Environment

  • Han, Beom-Soo;Ahn, Jeong-Yong;Han, Kyung-Soo
    • Communications for Statistical Applications and Methods
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    • v.9 no.1
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    • pp.167-174
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    • 2002
  • Computer network provides a powerful infrastructure for information sharing and the development of the statistical software with new concepts. In this paper, we discuss the design concepts of the statistical software in the network environment.

A Study on The Optimization Method of The Initial Weights in Single Layer Perceptron

  • Cho, Yong-Jun;Lee, Yong-Goo
    • Journal of the Korean Data and Information Science Society
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    • v.15 no.2
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    • pp.331-337
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    • 2004
  • In the analysis of massive volume data, a neural network model is a useful tool. To implement the Neural network model, it is important to select initial value. Since the initial values are generally used as random value in the neural network, the convergent performance and the prediction rate of model are not stable. To overcome the drawback a possible method use samples randomly selected from the whole data set. That is, coefficients estimated by logistic regression based on the samples are the initial values.

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Arabic Text Recognition with Harakat Using Deep Learning

  • Ashwag, Maghraby;Esraa, Samkari
    • International Journal of Computer Science & Network Security
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    • v.23 no.1
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    • pp.41-46
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    • 2023
  • Because of the significant role that harakat plays in Arabic text, this paper used deep learning to extract Arabic text with its harakat from an image. Convolutional neural networks and recurrent neural network algorithms were applied to the dataset, which contained 110 images, each representing one word. The results showed the ability to extract some letters with harakat.

Complex Regulatory Network of MicroRNAs, Transcription Factors, Gene Alterations in Adrenocortical Cancer

  • Zhang, Bo;Xu, Zhi-Wen;Wang, Kun-Hao;Lu, Tian-Cheng;Du, Ye
    • Asian Pacific Journal of Cancer Prevention
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    • v.14 no.4
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    • pp.2265-2268
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    • 2013
  • Several lines of evidence indicate that cancer is a multistep process. To survey the mechanisms involving gene alteration and miRNAs in adrenocortical cancer, we focused on transcriptional factors as a point of penetration to build a regulatory network. We derived three level networks: differentially expressed; related; and global. A topology network ws then set up for development of adrenocortical cancer. In this network, we found that some pathways with differentially expressed elements (genetic and miRNA) showed some self-adaption relations, such as EGFR. The differentially expressed elements partially uncovered mechanistic changes for adrenocortical cancer which should guide medical researchers to further achieve pertinent research.

Korean Restaurant Reservation System Model Using Hybrid Code Network (Hybrid Code Network를 이용한 한국어 식당 예약 시스템 모델)

  • Lee, Dong-Yub;Hur, Yun-A;Lim, Heui-Seok
    • Proceedings of The KACE
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    • 2017.08a
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    • pp.57-59
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    • 2017
  • 대화 시스템(dialogue system)은 텍스트나 음성을 통해 다양한 분야에서 특정한 목적을 수행할 수 있는 시스템이다. 대화 시스템을 구현하기 위한 방법으로 인공 신경망(neural network)을 기반으로한 end-to-end learning 방식이 제안되었다. End-to-end learning 방식을 이용한 식당 예약 시스템 모델의 학습을 위해 페이스북은 영어로 이루어진 식당 예약에 관련된 학습 대화 데이터셋(The 6 dialog bAbI tasks)을 구축하였다. 하지만 end-to-end learning 방식의 학습은 많은 학습 데이터가 필요하다는 단점이 존재하는데, 액션 템플릿(action template)의 정의를 통해 도메인 지식을 표현함으로써 일반적인 end-to-end learning 방식보다 적은 학습량으로 좋은 성능의 모델을 학습할 수 있는 Hybrid Code Network 구조를 제안한 연구가 있다. 본 논문에서는 Hybrid Code Network 구조를 이용하여 한국어 식당 예약 시스템을 구축할 수 있는 방법을 제안하고, 한국어로 이루어진 식당 예약에 관련한 학습 대화 데이터를 구축하는 방법을 제안한다.

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A Divided Scheduling Method based on Structural Characteristics in Wireless

  • Yoshino, Yuriko;Hashimoto, Masafumi;Wakamiya, Naoki
    • Journal of Multimedia Information System
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    • v.3 no.4
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    • pp.149-154
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    • 2016
  • Wireless mesh networks (WMNs) are used for metropolitan area network that requires high network throughput for handling many users. TDMA-based access is a common solution for this problem and several scheduling methods have been proposed. However, existing heuristic methods have room for improvement at network throughput although they are low complexity. In this paper, we propose a novel divided scheduling method based on structural characteristics in order to improve network throughput in WMNs. It separately schedules neighbor links of gateways and that of the other links by different scheduling algorithms. Simulation-based evaluations show that our proposal improves up to 14% of network throughput compared with conventional scheduling algorithm script.

Pareto RBF network ensemble using multi-objective evolutionary computation

  • Kondo, Nobuhiko;Hatanaka, Toshiharu;Uosaki, Katsuji
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.925-930
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    • 2005
  • In this paper, evolutionary multi-objective selection method of RBF networks structure is considered. The candidates of RBF network structure are encoded into the chromosomes in GAs. Then, they evolve toward Pareto-optimal front defined by several objective functions concerning with model accuracy and model complexity. An ensemble network constructed by such Pareto-optimal models is also considered in this paper. Some numerical simulation results indicate that the ensemble network is much robust for the case of existence of outliers or lack of data, than one selected in the sense of information criteria.

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Performance Analysis of Routing Protocols for Ad-Hoc Network (Ad-Hoc Network 환경을 위한 라우팅 프로토콜의 성능 비교)

  • So, Su-Hwan;Kim, Sung-Ho;Lee, Jae-Dong
    • Proceedings of the Korea Information Processing Society Conference
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    • 2005.05a
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    • pp.1389-1392
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    • 2005
  • Ad-Hoc Network 기술은 차세대 네트워크로 부각되고 있으며 IETF (Internet Engineering Task Force) MANET (Mobile Ad-Hoc Network) 워킹그룹에서 표준화 작업이 이루어지고 있다. Ad-Hoc Network 에서 라우팅은 중요한 요소이다. 다양한 서비스를 제공하기 위해서는 잘 정의된 라우팅 기법이 필요하다. 본 논문에서는 기존에 연구되고 있는 Ad-Hoc 라우팅 프로토콜 중 (AODV, PAODV, TORA, DSR, DSDV) 프로토콜들을 NS 시뮬레이터를 이용하여 동작과 성능을 비교 분석하여, Ad-Hoc 라우팅 프로토콜 중 가장 적합한 라우팅 프로토콜을 제시한다.

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