• Title/Summary/Keyword: Online update

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A Study on the DB-IR Integration: Per-Document Basis Online Index Maintenance

  • Jin, Du-Seok;Jung, Hoe-Kyung
    • Journal of information and communication convergence engineering
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    • v.7 no.3
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    • pp.275-280
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    • 2009
  • While database(DB) and information retrieval(IR) have been developed independently, there have been emerging requirements that both data management and efficient text retrieval should be supported simultaneously in an information system such as health care, customer support, XML data management, and digital libraries. The great divide between DB and IR has caused different manners in index maintenance for newly arriving documents. While DB has extended its SQL layer to cope with text fields due to lack of intact mechanism to build IR-like index, IR usually treats a block of new documents as a logical unit of index maintenance since it has no concept of integrity constraint. However, In the DB-IR integrations, a transaction on adding or updating a document should include maintenance of the posting lists accompanied by the document. Although DB-IR integration has been budded in the research filed, the issue will remain difficult and rewarding areas for a while. One of the primary reasons is lack of efficient online transactional index maintenance. In this paper, performance of a few strategies for per-document basis transactional index maintenance - direct index update, pulsing auxiliary index and posting segmentation index - will be evaluated. The result shows that the pulsing auxiliary strategy and posting segmentation indexing scheme, can be a challenging candidates for text field indexing in DB-IR integration.

Robust Online Object Tracking via Convolutional Neural Network (합성곱 신경망을 통한 강건한 온라인 객체 추적)

  • Gil, Jong In;Kim, Manbae
    • Journal of Broadcast Engineering
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    • v.23 no.2
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    • pp.186-196
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    • 2018
  • In this paper, we propose an on-line tracking method using convolutional neural network (CNN) for tracking object. It is well known that a large number of training samples are needed to train the model offline. To solve this problem, we use an untrained model and update the model by collecting training samples online directly from the test sequences. While conventional methods have been used to learn models by training samples offline, we demonstrate that a small group of samples are sufficient for online object tracking. In addition, we define a loss function containing color information, and prevent the model from being trained by wrong training samples. Experiments validate that tracking performance is equivalent to four comparative methods or outperforms them.

A Method on the Learning Speed Improvement of the Online Error Backpropagation Algorithm in Speech Processing (음성처리에서 온라인 오류역전파 알고리즘의 학습속도 향상방법)

  • 이태승;이백영;황병원
    • The Journal of the Acoustical Society of Korea
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    • v.21 no.5
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    • pp.430-437
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    • 2002
  • Having a variety of good characteristics against other pattern recognition techniques, the multilayer perceptron (MLP) has been widely used in speech recognition and speaker recognition. But, it is known that the error backpropagation (EBP) algorithm that MLP uses in learning has the defect that requires restricts long learning time, and it restricts severely the applications like speaker recognition and speaker adaptation requiring real time processing. Because the learning data for pattern recognition contain high redundancy, in order to increase the learning speed it is very effective to use the online-based learning methods, which update the weight vector of the MLP by the pattern. A typical online EBP algorithm applies the fixed learning rate for each update of the weight vector. Though a large amount of speedup with the online EBP can be obtained by choosing the appropriate fixed rate, firing the rate leads to the problem that the algorithm cannot respond effectively to different learning phases as the phases change and the number of patterns contributing to learning decreases. To solve this problem, this paper proposes a Changing rate and Omitting patterns in Instant Learning (COIL) method to apply the variable rate and the only patterns necessary to the learning phase when the phases come to change. In this paper, experimentations are conducted for speaker verification and speech recognition, and results are presented to verify the performance of the COIL.

Synergetics based damage detection of frame structures using piezoceramic patches

  • Hong, Xiaobin;Ruan, Jiaobiao;Liu, Guixiong;Wang, Tao;Li, Youyong;Song, Gangbing
    • Smart Structures and Systems
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    • v.17 no.2
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    • pp.167-194
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    • 2016
  • This paper investigates the Synergetics based Damage Detection Method (SDDM) for frame structures by using surface-bonded PZT (Lead Zirconate Titanate) patches. After analyzing the mechanism of pattern recognition from Synergetics, the operating framework with cooperation-competition-update process of SDDM was proposed. First, the dynamic identification equation of structural conditions was established and the adjoint vector (AV) set of original vector (OV) set was obtained by Generalized Inverse Matrix (GIM).Then, the order parameter equation and its evolution process were deduced through the strict mathematics ratiocination. Moreover, in order to complete online structural condition update feature, the iterative update algorithm was presented. Subsequently, the pathway in which SDDM was realized through the modified Synergetic Neural Network (SNN) was introduced and its assessment indices were confirmed. Finally, the experimental platform with a two-story frame structure was set up. The performances of the proposed methodology were tested for damage identifications by loosening various screw nuts group scenarios. The experiments were conducted in different damage degrees, the disturbance environment and the noisy environment, respectively. The results show the feasibility of SDDM using piezoceramic sensors and actuators, and demonstrate a strong ability of anti-disturbance and anti-noise in frame structure applications. This proposed approach can be extended to the similar structures for damage identification.

Adaptive Keystroke Authentication Method for Online Test (온라인 시험을 위한 적응적 키보드 인증방법)

  • Ko, Joo-Young;Shim, Jae-Chang;Kim, Hyen-Ki
    • Journal of Korea Multimedia Society
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    • v.11 no.8
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    • pp.1129-1137
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    • 2008
  • E-learning as a new education trend is being applied not only to cyber school but also various education fields such as employee training for companies or interactive learning for consumers. Users of the E-learning can take online tests individually anywhere, to evaluate their achievement level. Because users who are taking the online tests may show their own IDs or passwords to others, the possibility of cheating is very high. Therefore, it is very important to authenticate the users. In this paper, we propose an adaptive-keyboard authentication method which depends on user behavior patterns through the use of IDs and passwords. This method does not need any additional devices or special effort. An adaptive method to update patterns in which IDs and passwords are entered was previously suggested and this new method has proved to be better than previous methods through simulations and implementation.

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An Efficient Method to Update Character Moving Directions for Massively Multi-player Online FPS Games (대규모 온라인 FPS 게임을 위한 효율적인 캐릭터 방향 갱신 기법)

  • Lim, Jong-Min;Lee, Dong-Woo;Kim, Youngsik
    • Journal of Korea Game Society
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    • v.14 no.5
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    • pp.35-42
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    • 2014
  • In the market of First Person Shooter (FPS) games, Massively Multi-player Online FPS games (MMOFPS) like 'PlanetSide 2' have been popular recently. Dead reckoning has been widely used in order to mitigate the network traffic overload for the game server with hundreds or thousands of people. This paper proposes the efficient analytical method to calculate the tolerable threshold angle of moving direction, which is one of the most important factors for character status updating when dead reckoning is used in MMOFPS games. The experimental results with game testers shows that the proposed method minimizes the position error for character moving and provides natural direction updates of characters.

A Fast-Loaming Algorithm for MLP in Pattern Recognition (패턴인식의 MLP 고속학습 알고리즘)

  • Lee, Tae-Seung;Choi, Ho-Jin
    • Journal of KIISE:Computing Practices and Letters
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    • v.8 no.3
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    • pp.344-355
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    • 2002
  • Having a variety of good characteristics against other pattern recognition techniques, Multilayer Perceptron (MLP) has been used in wide applications. But, it is known that Error Backpropagation (EBP) algorithm which MLP uses in learning has a defect that requires relatively long leaning time. Because learning data in pattern recognition contain abundant redundancies, in order to increase learning speed it is very effective to use online-based teaming methods, which update parameters of MLP pattern by pattern. Typical online EBP algorithm applies fixed learning rate for each update of parameters. Though a large amount of speedup with online EBP can be obtained by choosing an appropriate fixed rate, fixing the rate leads to the problem that the algorithm cannot respond effectively to different leaning phases as the phases change and the learning pattern areas vary. To solve this problem, this paper defines learning as three phases and proposes a Instant Learning by Varying Rate and Skipping (ILVRS) method to reflect only necessary patterns when learning phases change. The basic concept of ILVRS is as follows. To discriminate and use necessary patterns which change as learning proceeds, (1) ILVRS uses a variable learning rate which is an error calculated from each pattern and is suppressed within a proper range, and (2) ILVRS bypasses unnecessary patterns in loaming phases. In this paper, an experimentation is conducted for speaker verification as an application of pattern recognition, and the results are presented to verify the performance of ILVRS.

Infrastructure for Network Applications based on Multi-Platform (멀티 플랫폼 기반 네트워크 응용을 위한 기반 구조)

  • 김진덕;진교홍
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2002.11a
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    • pp.677-681
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    • 2002
  • Several multi-user online applications which are operated by the existing fixed terminals(PC) are being changed into online application based on multi-platform operated by the several PC, PDA and mobile phones to perform concurrent works due to the popularization of mobile devices recently. This paper proposed the infrastructure for network applications based on multi-platform. We also proposed the methods of consistency control based on multi-platform, update propagation protocols among diverse clients which take the asymmetry of computing power and network bandwidth among each client into account. Moreover, we implemented a chatting application based on multi-platform and it showed the proposed infrastructure and methods perform well.

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A Study on Distributed OCSP for minimizing the load of OCSP Server based on PKI (PKI환경의 OCSP서버 부하 감소를 위한 OCSP 분산 기법)

  • Ko, Hoon;Jang, Eui-Jin;Shin, Yong-Tae
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.13 no.6
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    • pp.97-106
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    • 2003
  • The important factor in Public-Key Infrastructure is the authentication to correspondent. We receive the digital certificate for authentication between each other, and then we check the existence of validity on the certificate by Certification Revocation List(CRL). But, To use CRL is the scheme used in offline status. So, it is impossible to refer to the latest information and the CRL scheme which is used after downloading is variously unsuitable to getting bigger of the CRL size as time goes on. Therefore, we prefer OCSP(Online Certificate Status Protocol) used in online to CRL used in offline. Consequently, we propose the scheme which provides the request of fast verification in case of requesting the verification on the certificate by owning the same update information to Certificate Registry and distributed OCSP.

Website Quality, E-satisfaction, and E-loyalty of Users Based on The Virtual Distribution Channel

  • PANDJAITAN, Dorothy R.H.;Mahrinasari, MS.;HADIANTO, Bram
    • Journal of Distribution Science
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    • v.19 no.7
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    • pp.113-121
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    • 2021
  • Purpose: Technology induces the virtual distribution channel to exist, especially for booking a room online. This situation, indeed, provides an alternative for the customers to book based on their budget through digital platforms. One platform offering competitive prices is virtual hotel operators, such as Airbnb, OYO, RedDoorz, and Airy Rooms. Preferably, after using their platform, the user should be satisfied and loyal. Hence, this investigation aims to prove some associations. The first is between e-satisfaction and e-loyalty. The second is between website quality and e-satisfaction. The final is between website quality and e-loyalty. Research design, data, and methodology: This study is quantitatively designed with the sample of 350 users of the virtual hotel operator applications in Bandar Lampung: Airbnb, OYO, RedDoorz, and Airy, as the samples. Therefore, by denoting this sample size, the structural equation model based on covariance is utilized to examine the three hypotheses proposed. Also, to get the responses, this study uses a survey through a questionnaire. Result: This investigation demonstrates the positive relationship between e-satisfaction and e-loyalty. Additionally, website quality positively associates with e-satisfaction and e-loyalty. Conclusion: The virtual hotel operators must have the superiority on their website-based application to update the information based on the room availability and price, ensure online transaction safety, and facilitate its utilization to maintain long-term satisfaction and loyalty virtually.