• Title/Summary/Keyword: statistical signal processing

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Long-Term Arrival Time Estimation Model Based on Service Time (버스의 정차시간을 고려한 장기 도착시간 예측 모델)

  • Park, Chul Young;Kim, Hong Geun;Shin, Chang Sun;Cho, Yong Yun;Park, Jang Woo
    • KIPS Transactions on Computer and Communication Systems
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    • v.6 no.7
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    • pp.297-306
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    • 2017
  • Citizens want more accurate forecast information using Bus Information System. However, most bus information systems that use an average based short-term prediction algorithm include many errors because they do not consider the effects of the traffic flow, signal period, and halting time. In this paper, we try to improve the precision of forecast information by analyzing the influencing factors of the error, thereby making the convenience of the citizens. We analyzed the influence factors of the error using BIS data. It is shown in the analyzed data that the effects of the time characteristics and geographical conditions are mixed, and that effects on halting time and passes speed is different. Therefore, the halt time is constructed using Generalized Additive Model with explanatory variable such as hour, GPS coordinate and number of routes, and we used Hidden Markov Model to construct a pattern considering the influence of traffic flow on the unit section. As a result of the pattern construction, accurate real-time forecasting and long-term prediction of route travel time were possible. Finally, it is shown that this model is suitable for travel time prediction through statistical test between observed data and predicted data. As a result of this paper, we can provide more precise forecast information to the citizens, and we think that long-term forecasting can play an important role in decision making such as route scheduling.

Pharmacological Functional Magnetic Resonance Imaging of Cloropidol on Motor Task (운동과제에 대한 클로피도그렐의 약리적 뇌자기공명영상)

  • Chang, Yong-Min
    • Investigative Magnetic Resonance Imaging
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    • v.16 no.2
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    • pp.136-141
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    • 2012
  • Purpose : To investigate the pharmacologic modulation of motor task-dependent physiologic responses by antiplatelet agent, clopidogrel, during hand motor tasks in healthy subjects. Materials and Methods: Ten healthy, right-handed subjects underwent three functional magnetic resonance (fMRI) sessions: one before drug administration, one after high dose drug administration and one after reaching drug steady state. For the motor task fMRI, finger flexion-extension movements were performed. Blood oxygenation level dependent (BOLD) contrast was collected for each subject using a 3.0 T VHi (GE Healthcare, Milwaukee, USA) scanner. $T2^*$-weighted echo planar imaging was used for fMRI acquisition. The fMRI data processing and statistical analyses were carried out using SPM2. Results: Second-level analysis revealed significant increases in the extent of activation in the contralateral motor cortex including primary motor area (M1) after drug administration. The number of activated voxels in motor cortex was 173 without drug administration and the number increased to 1049 for high dose condition and 673 for steady-state condition respectively. However, there was no significant difference in the magnitude of BOLD signal change in terms of peak T value. Conclusion: The current results suggest that cerebral motor activity can be modulated by clopidogrel in healthy subjects and that fMRI is highly senstive to evidence such changes.

An Image Separation Scheme using Independent Component Analysis and Expectation-Maximization (독립성분 분석과 E-M을 이용한 혼합영상의 분리 기법)

  • 오범진;김성수;유정웅
    • Journal of KIISE:Information Networking
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    • v.30 no.1
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    • pp.24-29
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    • 2003
  • In this paper, a new method for the mixed image separation is presented using the independent component analysis, the innovation process, and the expectation-maximization. In general, the independent component analysis (ICA) is one of the widely used statistical signal processing schemes, which represents the information from observations as a set of random variables in the from of linear combinations of another statistically independent component variables. In various useful applications, ICA provides a more meaningful representation of the data than the principal component analysis through the transformation of the data to be quasi-orthogonal to each other. which can be utilized in linear projection.. However, it has been known that ICA does not establish good performance in source separation by itself. Thus, in order to overcome this limitation, there have been many techniques that are designed to reinforce the good properties of ICA, which improves the mixed image separation. Unfortunately, the innovation process still needs to be studied since it yields inconsistent innovation process that is attached to the ICA, the expectation and maximization process is added. The results presented in this paper show that the proposed improves the image separation as presented in experiments.

Performance Enhancement of Differential Power Analysis Attack with Signal Companding Methods (신호 압신법을 이용한 차분전력분석 공격성능 향상)

  • Ryoo, Jeong-Choon;Han, Dong-Guk;Kim, Sung-Kyoung;Kim, Hee-Seok;Kim, Tae-Hyun;Lee, Sang-Jin
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.18 no.2
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    • pp.39-47
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    • 2008
  • Among previous Side Channel Analysis (SCA) methods, Differential Power Analysis (DPA) based on the statistical characteristics of collected signals has been known as an efficient attack for uncovering secret key of cryptosystems. However, the attack performance of this method is affected very much by the temporal misalignment and noise of collected side channel signals. In this paper, we propose a new method to surmount the noise problem in DPA. The performance of the proposed method is then evaluated while analyzing the power consumption signals of Micro-controller chips during a DES operation. Its performance is then compared to that of the original DPA in the time and frequency domains. When we compare the experimental results with respect to the needed number of traces to uncover the secret key, our proposed method shows the performance enhancement 33% in the time domain and 50% in the frequency domain.

Analysis of statistical characteristics of bistatic reverberation in the east sea (동해 해역에서 양상태 잔향음 통계적 특징 분석)

  • Yeom, Su-Hyeon;Yoon, Seunghyun;Yang, Haesang;Seong, Woojae
    • The Journal of the Acoustical Society of Korea
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    • v.41 no.4
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    • pp.435-445
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    • 2022
  • In this study, the reverberation of a bistatic sonar operated in southeastern coast in the East Sea in July 2020 was analyzed. The reverberation sensor data were collected through an LFM sound source towed by a research vessel and a horizontal line array receiver 1 km to 5 km away from it. The reverberation sensor data was analyzed by various methods including geo-plot after signal processing. Through this, it was confirmed that the angle reflected from the sound source through the scatterer to the receiver has a dominant influence on the distribution of the reverberation sound, and the probability distribution characteristics of bistatic sonar reverberation varies for each beam. In addition, parametric factors of K distribution and Rayleigh distribution were estimated from the sample through moment method estimation. Using the Kolmogorov-Smirnov test at the confidence level of 0.05, the distribution probability of the data was analyzed. As a result, it could be observed that the reverberation follows a Rayleigh probability distribution, and it could be estimated that this was the effect of a low reverberation to noise ratio.