• The Journal of the Acoustical Society of Korea
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• v.20 no.3
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• pp.56-62
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• 2001

In this paper, we adopt a missing data theory to speech recognition. It can be used in order to maintain high performance of speech recognizer when the missing data occurs. In general, hidden Markov model (HMM) is used as a stochastic classifier for speech recognition task. Acoustic events are represented by continuous probability density function in continuous density HMM(CDHMM). The missing data theory has an advantage that can be easily applicable to this CDHMM. A marginalization method is used for processing missing data because it has small complexity and is easy to apply to automatic speech recognition (ASR). Also, a spectral subtraction is used for detecting missing data. If the difference between the energy of speech and that of background noise is below given threshold value, we determine that missing has occurred. We propose a new method that examines the reliability of detected missing data using voicing probability. The voicing probability is used to find voiced frames. It is used to process the missing data in voiced region that has more redundant information than consonants. The experimental results showed that our method improves performance than baseline system that uses spectral subtraction method only. In 452 words isolated word recognition experiment, the proposed method using the voicing probability reduced the average word error rate by 12％ in a typical noise situation.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.7
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• pp.1003-1010
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• 2013

In this paper, TCP/IP based Machine-to-Machine (M2M) communication uses CDMA/GSM network for data communication. This communication method is widely used by offshore moored buoy for data transmission back to the system server. Due to weather and signal coverage, the TCP/IP M2M communication often experiences transmission failure and causing data losses in the server. Data losses are undesired especially for meteorological and oceanographic analysis. This paper discusses a software approach to minimize M2M data losses by handling transmission failure and re-attempt which meant to transmit the data for recovery. This implementation was tested for its performance on a meteorological buoy placed offshore.

• Journal of Broadcast Engineering
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• v.3 no.2
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• pp.138-145
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• 1998

최근 ATM(Asynchronous Transfer Mode) 네트워크를 비롯한 많은 데이터 전송 기술이 등장하였고, 이를 이용하여 동영상을 전달하는 연구가 진행되고 있다. 그러나 이러한 연구들은 대부분 동영상 데이터의 스트리밍에 주안점을 두고 있기 때문에, ATM 네트워크 기반으로 손실없는 방송 제작 환경을 구축하기 위해서는 에러가 발생하더라도 고속으로 복원할 수 있는 알고리즘이 필요하다. 본 논문에서는 ATM 네트워크 상에서 방송 제작 품질로 압축된 동영상을 TCP(Transport Control Protocol) 기반으로 전송하는 경우에 대하여 연구하였다. 실제 데이터의 송수신에는 잡음으로 인한 ATM 셀의 손실이 발생하게되는데, ATM 셀의 손실로 인한 패킷의 손실은 송신측의 재전송과 재전송 타임 아웃을 유발하므로 전송 성능에 지대한 영향을 미친다. 본 논문에서는 손실된 패킷의 연속적인 재전송을 통하여, 재전송 시간의 단축과 송신측 재전송 타임 아웃의 제거된 고속의 손실 복구 알고리즘을 제안하였고, 그 성능을 기존의 알고리즘과 비교하였다. 또한, 본 논문에서는 영상을 전송하는 과정에서 데이터 수신 버퍼의 오버플로우가 발생하지 않도록 충분한 버퍼 크기를 계산하는 방법에 관해서도 고찰하였다. 특히, 방송 제작 품질의 화질을 처리하는 경우에 대한 시스템 모델링을 하였고, 이 모델에 대하여 오버플로우를 일정 수준 이하로 낮추기 위한 수신 버퍼의 크기를 결정하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.6B
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• pp.867-874
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• 2010

Since high packet losses occur in multi-hop transmission of wireless sensor networks, reliable data transmission is required. Especially, in case of event-driven data, a loss recovery mechanism should be provided for lost packets. Because retransmission for lost packets is requested to a node that caches the packets, the caching node should maintains all of data for transmission in its buffer. However, nodes of wireless sensor networks have limited resources. Thus, both a loss recovery mechanism and a buffer management technique are provided for reliable data transmission in wireless sensor networks. In this paper, we propose a buffer management technique at a caching position determined by a loss recovery mechanism. The caching position of data is determined according to desirable reliability for the data. In addition, we validate the performance of the proposed method through computer simulations.

• Journal of the Korea Convergence Society
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• v.11 no.3
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• pp.1-7
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• 2020

This paper introduces two different techniques for dealing with incomplete data and algorithms for learning this data. The first method is to process the incomplete data by assigning the missing value with equal probability that the missing variable can have, and learn this data with the SVM. This technique ensures that the higher the frequency of missing for any variable, the higher the entropy so that it is not selected in the decision tree. This method is characterized by ignoring all remaining information in the missing variable and assigning a new value. On the other hand, the new method is to calculate the entropy probability from the remaining information except the missing value and use it as an estimate of the missing variable. In other words, using a lot of information that is not lost from incomplete learning data to recover some missing information and learn using deep learning. These two methods measure performance by selecting one variable in turn from the training data and iteratively comparing the results of different measurements with varying proportions of data lost in the variable.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.357-359
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• 1998

무선 통신 환경에서 기지국 안테나를 떠난 전파가 수신안테나에 도달하는 과정 중에 발생하는 전파 손실은 매우 복잡한 비선형 함수이다. 본 논문에서는 신경회로망을 사용한 전파 손실 모델을 제안하고, 3차원 지형 데이터를 이용하여 전파 환경을 반영할 수 있는 특징을 추출하여 이를 신경회로망에 적용함으로써 전파손실 예측모델을 생성하는 방법을 소개한다. 각 필드 측정 데이터에 대한 특징 값을 이용하여 신경회로망을 학습하여 예측모델을 완성한다. 또한, 서울 도심 지역의 실제 PCS 서비스 환경에 대한 실험결과를 통해 제안하는 모델의 우수성을 보인다.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04a
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• pp.328-330
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• 2001

무선 인터넷 환경하에서 신뢰성이 보장되어야 할 데이터의 전송이나 음성 데이터의 전송시에 혼잡으로 인한 손실이 발생했을 때, 라우터나 스위치에서의 손실을 네트웍 레이어에서 직접 복구를 함으로서 양단에서의 손실을 극소화함은 물론 지연시간을 최소화하여, 멀티미디어 데이터의 재생시에 치명적으로 작용할 수 있는 Jitter의 발생을 줄이며 네트웍 레이어에서의 손실을 최소화함으로써 무선 링크를 통한 복구 횟수를 줄여서 신뢰성 향상 및 전반적인 모바일 네트웍의 성능을 향상시킬 수 있는 방법을 제시하고 이에 대한 시뮬레이션을 통해 그 성능을 입증하도록 하겠다.

• Journal of KIISE:Information Networking
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• v.28 no.3
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• pp.389-405
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• 2001

In these days, we have increasing demands on the real-time services, especially for the multimedia data transmission in both of wired and wireless environments and thus efficient and stable ways of transmitting realtime data are needs. Although RTP is widely used for internet-based realtime applications, it cannot avoid packet losses, due to the use of UDP stack and its underlying layers. In the case of mobile computing applications, the packet losses are more frequent and consecutive because of the limited bandwidth. In this paper, we first statistically analyze the characteristics of packet losses in the wired and wireless communications, based on Gilbert model, and a new packet recovery scheme for realtime data transmission is presented. To reflect the transmission characteristics of the present network environment, our scheme makes the sender to dynamically adjust the amount of redundant information, using the current packet loss characteristic parameters reported by the receiver. Additionally, we use relatively large and discontinuous offset values, which enables us to recover from both of the random and consecutive packet losses. Due to these characteristics, our scheme is suitable for the mobile computing environment where packet loss rates are relatively high and varies rapidly in a wide range. Since our scheme is based on the analytic model form statistics, it can also be used for other network environments. We have implemented the scheme with Mobile IP and RTP/RTCP protocols to experimentally verify its efficiency.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.4
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• pp.601-608
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• 2023

Mobile robots are widely used in industries because mobile robots perform tasks in various environments. In order to carry out tasks, determining the precise location of the robot in real-time is important due to the need for path generation and obstacle detection. In particular, when mobile robots autonomously navigate in indoor environments and carry out assigned tasks within pre-determined areas, highly precise positioning performance is required. However, mobile robots frequently experience data missing in wireless communication environments. The robots need to rely on predictive techniques to autonomously determine the mobile robot positions and continue performing mobile robot tasks. In this paper, we propose an extended Kalman filter-based algorithm to enhance the accuracy of mobile robot localization and address the issue of data missing. Trilateration algorithm relies on measurements taken at that moment, resulting in inaccurate localization performance. In contrast, the proposed algorithm uses residual values of predicted measurements in data missing environments, making precise mobile robot position estimation. We conducted simulations in terms of data missing to verify the superior performance of the proposed algorithm.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.2076-2077
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• 2009

본 논문은 시간 지연 및 데이터 손실이 존재하는 양방향 원격 조작 시스템의 안정성을 확보하기 위해 에너지 제한 알고리즘을 적용한다. 다양한 실험 결과, 자유 공간 실험에서는 단방향 2.5 초까지의 시변 시간 지연(variable time delay), 벽 접촉 실험에서는 단방향 0.3 초까지의 시변 시간 지연에 대해 전체 시스템이 안정적으로 거동하는 것을 확인하였다. 또한 데이터 손실 발생 시 이전 데이터를 유지하는 방법을 이용하여 에너지 제한 알고리즘을 적용하면 90%까지의 데이터 손실이 발생할 경우에도 시스템의 안정성을 보장할 수 있음을 확인하였다.