• Title/Summary/Keyword: threshold approach

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The Late Take-off Phenomenon in the Diffusion of Telecommunication Services : Focused on the Fax Markets (통신서비스의 늦은 수요 확산 현상에 관한 연구 : Fax 서비스를 중심으로)

  • 임병락;최문기;박명철
    • Journal of the Korean Operations Research and Management Science Society
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    • v.27 no.2
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    • pp.81-96
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    • 2002
  • Telecommunication services are distinctive in that their adoptions are influenced by network effect resulting in 'the late take-off phenomenon' and the 'critical mass' problem. In this paper we examined, so called, 'the late take-off phenomenon' in the diffusion process of telecommunication services. We compared the parameters of the diffusion process of consumer durables with those of fax services in the US and Korea. By analyzing the parameters of a new diffusion model based on the threshold model proposed by Markus, we found that 'the late take-off phenomenon' resulted from the low heterogeneity of the threshold distribution for the potential adopters. A simulation approach was proposed for the theoretical implication of the 'critical mass' problem in the start-up telecommunications services.

Image coding using blocked zerotree

  • Lee, Jin-Ho;Nam, In-Gil;Park, Sang-Ho
    • Journal of Korea Society of Industrial Information Systems
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    • v.6 no.1
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    • pp.39-47
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    • 2001
  • A blocked zerotree coding algorithm for compression of subband image is proposed. Significance of blocks with respect to a certain threshold are coded with a set of transition rules for the significance of blocks. Significant blocks are quantized by vector quantization. The basic idea for this coding approach are: 1) Subband images are coded by blocks, 2) Important blocks based on the significance of blocks are coded and quantized, 3) Multiband codebook which is composed of sub-codebooks dedicated for each threshold and subband level is adapted to produce good reproduction vectors for vector quantization. The compression results are similar to Shapiro's zerotree coding even though ours are obtained without entropy coding of bit streams from blocked zerotree encoder. If an entropy coding is applied to the bitstream, PSNR will be improved.

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Noise suppressor Using Psychoacoustic Model and Wavelet Packet Transform (심리음향 모델과 웨이블릿 패킷 변환을 이용한 잡음제거기)

  • Kim, Mi-Seon;Kim, Young-Ju;Lee, In-Sung
    • Proceedings of the IEEK Conference
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    • 2006.06a
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    • pp.345-346
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    • 2006
  • In this paper, we propose the noise suppressor with the psychoacoustic model and wavelet packet transform. The objective of the scheme is to enhance speech corrupted by colored or non-stationary noise. If corrupted noise is colored, subband approach would be more efficient than whole band one. To avoid serious residual noise and speech distortion, we must adjust the Wavelet Coefficient threshold. In this paper, the subband is designed matching with the critical band. And WCT is adapted by noise masking threshold(NMT) and segmental signal to noise ratio(seg_SNR). Consequently this work improve the PESQ-MOS about 0.23 in the case of coded speech.

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A Simple Approach of Improving Back-Propagation Algorithm

  • Zhu, H.;Eguchi, K.;Tabata, T.;Sun, N.
    • Proceedings of the IEEK Conference
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    • 2000.07b
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    • pp.1041-1044
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    • 2000
  • The enhancement to the back-propagation algorithm presented in this paper has resulted from the need to extract sparsely connected networks from networks employing product terms. The enhancement works in conjunction with the back-propagation weight update process, so that the actions of weight zeroing and weight stimulation enhance each other. It is shown that the error measure, can also be interpreted as rate of weight change (as opposed to ${\Delta}W_{ij}$), and consequently used to determine when weights have reached a stable state. Weights judged to be stable are then compared to a zero weight threshold. Should they fall below this threshold, then the weight in question is zeroed. Simulation of such a system is shown to return improved learning rates and reduce network connection requirements, with respect to the optimal network solution, trained using the normal back-propagation algorithm for Multi-Layer Perceptron (MLP), Higher Order Neural Network (HONN) and Sigma-Pi networks.

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Intelligent Intrusion Detection Systems Using the Asymmetric costs of Errors in Data Mining (데이터 마이닝의 비대칭 오류비용을 이용한 지능형 침입탐지시스템 개발)

  • Hong, Tae-Ho;Kim, Jin-Wan
    • The Journal of Information Systems
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    • v.15 no.4
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    • pp.211-224
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    • 2006
  • This study investigates the application of data mining techniques such as artificial neural networks, rough sets, and induction teaming to the intrusion detection systems. To maximize the effectiveness of data mining for intrusion detection systems, we introduced the asymmetric costs with false positive errors and false negative errors. And we present a method for intrusion detection systems to utilize the asymmetric costs of errors in data mining. The results of our empirical experiment show our intrusion detection model provides high accuracy in intrusion detection. In addition the approach using the asymmetric costs of errors in rough sets and neural networks is effective according to the change of threshold value. We found the threshold has most important role of intrusion detection model for decreasing the costs, which result from false negative errors.

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A Robust Background Subtraction Algorithm for Dynamic Scenes based on Multiple Interval Pixel Sampling (다중 구간 샘플링에 기반한 동적 배경 영상에 강건한 배경 제거 알고리즘)

  • Lee, Haeng-Ki;Choi, Young Kyu
    • Journal of the Semiconductor & Display Technology
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    • v.19 no.2
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    • pp.31-36
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    • 2020
  • Most of the background subtraction algorithms show good performance in static scenes. In the case of dynamic scenes, they frequently cause false alarm to "temporal clutter", a repetitive motion within a certain area. In this paper, we propose a robust technique for the multiple interval pixel sampling (MIS) algorithm to handle highly dynamic scenes. An adaptive threshold scheme is used to suppress false alarms in low-confidence regions. We also utilize multiple background models in the foreground segmentation process to handle repetitive background movements. Experimental results revealed that our approach works well in handling various temporal clutters.

An E-Mail Recommendation System using Semi-Automatic Method (반자동 방식을 이용한 이메일 추천 시스템)

  • Jeong, Ok-Ran;Jo, Dong-Seop
    • Proceedings of the KIEE Conference
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    • 2003.11c
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    • pp.604-607
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    • 2003
  • Most recommendation systems recommend the products or other information satisfying preferences of users on the basis of the users' previous profile information and other information related to product searches and purchase of users visiting web sites. This study aims to apply these application categories to e-mail more necessary to users. The E-Mail System has the strong personality so that there will be some problems even if e-mails are automatically classified by category through the learning on the basis of the personal rules. In consideration with this aspect, we need the semi-automatic system enabling both automatic classification and recommendation method to enhance the satisfaction of users. Accordingly, this paper uses two approaches as the solution against the misclassification that the users consider as the accuracy of classification itself using the dynamic threshold in Bayesian Learning Algorithm and the second one is the methodological approach using the recommendation agent enabling the users to make the final decision.

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A Study on Classifications of Useful Customer Reviews by Applying Text Mining Approach (텍스트 마이닝을 활용한 고객 리뷰의 유용성 지수 개선에 관한 연구)

  • Lee, Hong Joo
    • Journal of Information Technology Services
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    • v.14 no.4
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    • pp.159-169
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    • 2015
  • Customer reviews are one of the important sources for purchase decision makings in online stores. Online stores have tried to provide useful reviews in product pages to customers. To assess the usefulness of customer reviews before other users have voted enough on the reviews, diverse aspects of reviews were utilized in prevous studies. Style and semantic information were utilized in many studies. This study aims to test diverse alogrithms and datasets for identifying a proper classification method and threshold to classify useful reviews. In particular, most researches utilized ratio type helpfulness index as Amazon.com used. However, there is another type of usefulness index utilized in TripAdviser.com or Yelp.com, count type helpfulness index. There was no proper threshold to classify useful reviews yet for count type helpfulness index. This study used reivews and their usefulness votes on restaurnats from Yelp.com to devise diverse datasets and applied text mining approaches to classify useful reviews. Random Forest, SVM, and GLMNET showed the greater values of accuracy than other approaches.

A Method for Optimal Binarization using Bit-plane Pattern (비트평면 패턴을 이용한 최적 이진화 방법)

  • Kim, Ha-Sik;Kim, Kang;Cho, Kyung-Sik;Jeon, Jong-Sik
    • Journal of the Korea Society of Computer and Information
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    • v.6 no.4
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    • pp.1-5
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    • 2001
  • A new approach for determining global threshold value for image binarization is proposed in this paper. In the proposed algorithm, bit-plane information which involve the shapes of original image is used for dividing image into two parts object and background, and then compared each average values. Optimal threshold value are selected in center of two averages. Proposed method is relatively simple but robust and achieved good results in continuous tone images and document image.

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Practical Revision for Implementing the Distributing Security-Mediated PKI

  • Yang Jong-Phil;Shim Mi-Sun;Rhee Kyung Hyune
    • Journal of Korea Multimedia Society
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    • v.8 no.12
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    • pp.1638-1648
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    • 2005
  • The SEM approach to PKl offers several advantages, such as immediate revocation of users' signing ability without CRLs and compatibility with the standard RSA. However, it has a weakness against denial of service attack caused by breaking down or being compromised. G. Vanrenen et al. proposed a distributed SEM approach to overcome the weaknesses. However, it does not provide the desirable properties such as instant availability and immunity against denial of service attack, due to inadequate usage of threshold cryptography and proactive secret sharing. In this paper, we point out its structural contradictions and propose a modified version of distributed SEM approach.

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