• Title/Summary/Keyword: Information Processing Theory

검색결과 603건 처리시간 0.019초

An Abnormal Breakpoint Data Positioning Method of Wireless Sensor Network Based on Signal Reconstruction

  • Zhijie Liu
    • Journal of Information Processing Systems
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    • 제19권3호
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    • pp.377-384
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    • 2023
  • The existence of abnormal breakpoint data leads to poor channel balance in wireless sensor networks (WSN). To enhance the communication quality of WSNs, a method for positioning abnormal breakpoint data in WSNs on the basis of signal reconstruction is studied. The WSN signal is collected using compressed sensing theory; the common part of the associated data set is mined by exchanging common information among the cluster head nodes, and the independent parts are updated within each cluster head node. To solve the non-convergence problem in the distributed computing, the approximate term is introduced into the optimization objective function to make the sub-optimization problem strictly convex. And the decompressed sensing signal reconstruction problem is addressed by the alternating direction multiplier method to realize the distributed signal reconstruction of WSNs. Based on the reconstructed WSN signal, the abnormal breakpoint data is located according to the characteristic information of the cross-power spectrum. The proposed method can accurately acquire and reconstruct the signal, reduce the bit error rate during signal transmission, and enhance the communication quality of the experimental object.

헬스 케어를 위한 RDMS 설계 (Design of Rough Set Theory Based Disease Monitoring System for Healthcare)

  • 이병관;정은희
    • 한국통신학회논문지
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    • 제38C권12호
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    • pp.1095-1105
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    • 2013
  • 본 논문에서는 헬스 케어 시스템에서 효율적으로 질병을 관리할 수 있는 RDMS(Rough Set Theory based Disease Monitoring System)을 제안한다. RDMS는 DCM(Data Collection Module), RDRGM(RST based Disease Rule Generation Module), HMM(Healthcare Monitoring Module)로 구성된다. DCM은 바이오센서로부터 환자의 생체 정보를 수집하고, 데이터 처리 절차에 따라 RDMS DB에 저장한다. RDRGM은 RST의 코어와 속성의 지지율을 이용하여 질병 규칙을 생성한다. HMM은 DCM에 의해 수집된 환자 정보를 이용하여 환자의 질병에 대한 위험지수뿐만 아니라 질병에 대한 합병증에 관한 위험지수까지 분석함으로써 환자의 질병을 예측하고, 환자의 위험지수에 따라 환자, 주치의 등에 시각화된 환자의 정보를 전달한다. 또한, RDRGM에 의해 생성된 규칙들에 따라 환자의 의료정보, 현재의 환자건강상태, 환자 가족력 등을 비교분석하여 환자의 질병을 예측하고, 예측결과에 따라 환자 맞춤형 의료 서비스와 의료 정보를 신속하고 신뢰성 있게 제공할 수 있다.

지식기반신경망에서 은닉노드삽입을 이용한 영역이론정련화 (Theory Refinements in Knowledge-based Artificial Neural Networks by Adding Hidden Nodes)

  • 심동희
    • 한국정보처리학회논문지
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    • 제3권7호
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    • pp.1773-1780
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    • 1996
  • 인공지능의 기호적 방법과 수치적 방법을 결합한 지식기반신경망은 다른 기계 학 습모델보다 우수한 성능을 나타내고 있다. 그러나 지식기반신경망은 신경망으로 형성 된 후 동적으로 그 구조를 변경할 수 없어서 영역이론정련화 기능을 갖추지 못하였다. 지식기반신경망의 이러한 단점을 보완하기 위하여 TopGen 알고리즘이 제안되었으나 삽입된 은닉노드를 모두 입력 노드에 연결한 점, 빔탐색을 이용한 등의 문제를 안고 있다. 본 논문에서는 TopGen의 문제점을 해소하기 위하여 은닉 노드를 다음 하위계층 의 노드에 링크 시켰으며, 역추적을 허용한 언덕 오르기를 이용하는 알고리즘을 설계 하였다.

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조직구성원의 지식통합 역량에 대한 선행 요인과 지식창출 효과에 관한 연구: 융합 지향 조직을 중심으로 (Antecedents of Employees' Knowledge Integration Capability and Its Effects on Knowledge Creation: Focused on Convergence-Oriented Organizations)

  • 홍진원;서우종
    • 지식경영연구
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    • 제15권4호
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    • pp.105-126
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    • 2014
  • Knowledge integration is becoming a primary function of improving organizational capabilities and performance in today's convergence paradigm. The knowledge integration capability of employees has increasingly been regarded as a critical source for developing new products and services. This study investigates the influential factors of employees' knowledge integration capability and its effects. A theoretical research model was developed based on the socio-technical perspective and information processing theory. The model includes teamwork quality, expertise, IT support, and knowledge complexity as the primary influential factors of employees' knowledge integration capability. A large-scale survey was conducted for gathering data (a total of 316 samples from 141 organizations) to test the proposed model. The test results of the hypotheses show that expertise and knowledge complexity are the significant influential factors of employees' knowledge integration capability, and also the capability has a positive effect on the knowledge creation performance of employees. Our findings contribute to the development of initiatives for promoting employees' knowledge integration capability, especially in knowledge intensive organizations focusing on convergence products and services.

An Evaluative Study of the Operational Safety of High-Speed Railway Stations Based on IEM-Fuzzy Comprehensive Assessment Theory

  • Wang, Li;Jin, Chunling;Xu, Chongqi
    • Journal of Information Processing Systems
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    • 제16권5호
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    • pp.1064-1073
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    • 2020
  • The general situation of system composition and safety management of high-speed railway terminal is investigated and a comprehensive evaluation index system of operational security is established on the basis of railway laws and regulations and previous research results to evaluate the operational security management of the high-speed railway terminal objectively and scientifically. Index weight is determined by introducing interval eigenvalue method (IEM), which aims to reduce the dependence of judgment matrix on consistency test and improve judgment accuracy. Operational security status of a high-speed railway terminal in northwest China is analyzed using the traditional model of fuzzy comprehensive evaluation, and a general technique idea and references for the operational security evaluation of the high-speed railway terminal are provided. IEM is introduced to determine the weight of each index, overcomes shortcomings of traditional analytic hierarchy process (AHP) method, and improves the accuracy and scientificity of the comprehensive evaluation. Risk factors, such as terrorist attacks, bad weather, and building fires, are intentionally avoided in the selection of evaluation indicators due to the complexity of risk factors in the operation of high-speed railway passenger stations and limitation of the length of the paper. However, such risk factors should be considered in the follow-up studies.

Classroom Roll-Call System Based on ResNet Networks

  • Zhu, Jinlong;Yu, Fanhua;Liu, Guangjie;Sun, Mingyu;Zhao, Dong;Geng, Qingtian;Su, Jinbo
    • Journal of Information Processing Systems
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    • 제16권5호
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    • pp.1145-1157
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    • 2020
  • A convolution neural networks (CNNs) has demonstrated outstanding performance compared to other algorithms in the field of face recognition. Regarding the over-fitting problem of CNN, researchers have proposed a residual network to ease the training for recognition accuracy improvement. In this study, a novel face recognition model based on game theory for call-over in the classroom was proposed. In the proposed scheme, an image with multiple faces was used as input, and the residual network identified each face with a confidence score to form a list of student identities. Face tracking of the same identity or low confidence were determined to be the optimisation objective, with the game participants set formed from the student identity list. Game theory optimises the authentication strategy according to the confidence value and identity set to improve recognition accuracy. We observed that there exists an optimal mapping relation between face and identity to avoid multiple faces associated with one identity in the proposed scheme and that the proposed game-based scheme can reduce the error rate, as compared to the existing schemes with deeper neural network.

평균장 이론을 이용한 전량화분석 문제의 최적화 (Quantification Analysis Problem using Mean Field Theory in Neural Network)

  • 조광수
    • 한국정보처리학회논문지
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    • 제2권3호
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    • pp.417-424
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    • 1995
  • 본 논문에서는 정량화(Quantification) 문제를 MFT(Mean Field Theroy)를 통해서 해결하는 기법을 제안한다. 통계학에서 중요한 문제의 하나인 정량화 문제는 주어진 공간에서 대상들간의 유사성에 따라서 최적의 상태를 갖도록 하는 문제이다. 평균장 접근 방법에 기초한 한개의 변수로 표현되는 확률적 시뮬레이티드 아닐링을 제안하고 정량화 문제를 패널티(penalty) 파라메타 항을 첨가한 비한정된 최적화 문제로 변형하 여 MFT를 적용하였다. 또한 연속변수를 갖는 신경회로망에서 실제 값을 계산하는 것 보다 평균장 접근방법으로 계산하는것이 더 빠르게 계산될 수 있음을 확인하였다. 본 논문에서 제안한 방법이 실험결과 해석적인 방법보다 좋은 정량적 결과를 보였다.

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지식기반인공신경망에서 관련있는 입력노드만 연계된 은닉노드를 이용한 여역이론정련화 (Theory Refinement using Hidden Nodes Connected from Relevant Input Nodes in Knowledge-based Artificial Neural Network)

  • 심동희
    • 한국정보처리학회논문지
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    • 제4권11호
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    • pp.2780-2785
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    • 1997
  • 지식기반인공신경 망은 다른 기계학습알고리즘보다 우수한 성능을 나타내지만 인공신경망으로 형성된 후 동적으로 그 구조를 변경할 수 없어서 영역이론정련화 기능을 갖추지 못하였다. 지식기반인공신경망의 이러한 단점을 보완하기 위하여 TopGen 알고리즘이 제안되었으나 삽입된 은닉노드를 모든 입력 노드에 연결한 점, 빔탐색을 이용한 점 등의 문제를 안고 있다. 본 논문에서는 TopGen의 문제점을 해소하기 위하여 은닉노드를 입력 노드 중 관계가 깊은 일부의 노드에만 링크시켰으며, 역추적을 허용한 언덕오르기를 이용하는 알고리즘을 설계 하였다.

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Mukbang's Foodcasting beyond Korea's Borders: A Study Focusing on OTT Platforms

  • Lim, Jia
    • Journal of Information Processing Systems
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    • 제18권4호
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    • pp.470-479
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    • 2022
  • Mukbang is a type of foodcasting where a host records or streams their eating rituals for audience consumption in live format. With origins in South Korea via the online broadcast genre found on Afreeca TV in the mid-2000s, the phenomenon has since found global popularity. Its development as a full-fledged genre is based on a communication culture that invites people to a meal rather than to talk to one another; viewers watch in silence as a host consumes a copious number of dishes from Korean gastronomy to fast food to other ethnic cuisine on display. An invitation to eat means the beginning of a public relationship that quickly turns to a private shared experience. This study analyzes several Mukbang video postings and makes use of Linden's culture approach model to provide a view toward a number of cross-cultural connections by Koreans and non-Korean audiences. Prior to the study, 10 Korean eating shows were selected and used as standard models. Korean Mukbang mainly consists of eating behavior and ASMR, with very few storytelling or narrative devices utilized by its creators. For this reason, eating shows make a very private connection. In other ways, this paper shows how 28 Mukbang-related YouTube contents selected by Ranker were evolving and examined through notions of acculturation and reception theory.

객체지향 이론을 적용한 멀티미디어 데이터 처리 (Multimedia data processing using object-orient theory)

  • 김홍섭
    • 한국컴퓨터정보학회논문지
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    • 제5권2호
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    • pp.1-6
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    • 2000
  • 인터넷이 확장되고 멀티미디어의 통합 기술이 발전함에 따라 다양한 방식으로 정보를 표현하고 제공함으로써 컴퓨터 사용자들은 다양한 형태의 데이터를 접하게 된다. 개발자의 관점에서 볼 때 데이터의 처리는 여러 가지 문제를 야기할 수 있다. 사운드, 이미지, 영상 등 다양한 매체와, 같은 매체라도 서로 다른 자료구조로 인한 상호 호환성 문제는 개발자에게 더 많은 작업을 필요로 한다. 최근 대두되고 있는 객체지향 개발방법론은 이런 문제를 효율적이고 효과적으로 해결할 수 있는 기반을 제시한다. 본 고에서는 객체지향 이론의 핵심개념인 상속성과 다형성을 적용하여 효과적으로 멀티미디어 데이터를 처리하는 방법을 제시하고 게임 프로그램 개발에 적용한 그 구현 예를 제안하였다.

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