Local polynomial modeling of time-varying autoregressive models with application to time-frequency analysis of event-related EEG

This paper proposes a new local polynomial modeling (LPM) method for identification of time-varying autoregressive (TVAR) models and applies it to time-frequency analysis (TFA) of event-related electroencephalogram (ER-EEG). The LPM method models the TVAR coefficients locally by polynomials and estimates the polynomial coefficients using weighted least-squares with a window having a certain bandwidth. A data-driven variable bandwidth selection method is developed to determine the optimal bandwidth that minimizes the mean squared error. The resultant time-varying power spectral density estimation of the signal is capable of achieving both high time resolution and high frequency resolution in the time-frequency domain, making it a powerful TFA technique for nonstationary biomedical signals like ER-EEG. Experimental results on synthesized signals and real EEG data show that the LPM method can achieve a more accurate and complete time-frequency representation of the signal. © 2006 IEEE.published_or_final_versio

Local polynomial modelling of time-varying autoregressive processes and its application to the analysis of event-related electroencephalogram

This paper proposes a new method for identification of time-varying autoregressive (TVAR) models based on local polynomial modeling (LPM) and applies it to investigate the dynamic spectral information of event-related electroencephalogram (EEG). The proposed method models the TVAR coefficients locally by polynomials and estimates those using least-squares estimation with a kernel having a certain bandwidth. A data-driven variable bandwidth selection method is developed to obtain the optimal bandwidth, which minimizes the mean squared error (MSE). Simulation results show that the LPM-based TVAR identification method outperforms conventional methods for different scenarios. The advantages of the LPM method make it a useful high-resolution timefrequency analysis (TFA) technique for nonstationary biomedical signals like EEG. Experimental results show that the LPM method can reveal more meaningful time-frequency characteristics than wavelet transform. ©2010 IEEE.published_or_final_versionThe IEEE International Symposium on Circuits and Systems (ISCAS 2010), Paris, France, 30 May-2 June 2010. In Proceedings of ISCAS, 2010, p. 3124-312

Modeling and identification of gene regulatory networks: A Granger causality approach

It is of increasing interest in systems biology to discover gene regulatory networks (GRNs) from time-series genomic data, i.e., to explore the interactions among a large number of genes and gene products over time. Currently, one common approach is based on Granger causality, which models the time-series genomic data as a vector autoregressive (VAR) process and estimates the GRNs from the VAR coefficient matrix. The main challenge for identification of VAR models is the high dimensionality of genes and limited number of time points, which results in statistically inefficient solution and high computational complexity. Therefore, fast and efficient variable selection techniques are highly desirable. In this paper, an introductory review of identification methods and variable selection techniques for VAR models in learning the GRNs will be presented. Furthermore, a dynamic VAR (DVAR) model, which accounts for dynamic GRNs changing with time during the experimental cycle, and its identification methods are introduced. © 2010 IEEE.published_or_final_versionThe 9th International Conference on Machine Learning and Cybernetics (ICMLC 2010), Qingdao, China, 11-14 July 2010. In Proceedings of the 9th ICMLC, 2010, v. 6, p. 3073-307

On the design and implementation of a high definition multi-view intelligent video surveillance system

This paper proposes a distributed architecture for high definition (HD) multi-view video surveillance system. It adopts a modular design where multiple intelligent Internet Protocol (IP)-based video surveillance cameras are connected to a local video server. Each server is equipped with storage and optional graphics processing units (GPUs) for supporting high-level video analytics and processing algorithms such as real-time decoding and tracking for the video captured. The servers are connected to the IP network for supporting distributed processing and remote data access. The DSP-based surveillance camera is equipped with realtime algorithms for streaming compressed videos to the server and performing simple video analytics functions. We also developed video analytics algorithms for security monitoring. Both publicly available data set and real video data that are captured under indoor and outdoor scenarios are used to validate our algorithms. Experimental results show that our distributed system can support real-time video applications with high definition resolution.published_or_final_versio

Time-varying correlation coefficients estimation and its application to dynamic connectivity analysis of fMRI

Exploration of the dynamics of functional brain connectivity based on the correlation coefficients of functional magnetic resonance imaging (fMRI) data is important for understanding the brain mechanisms. Because fMRI data are time-varying in nature, the functional connectivity shows substantial fluctuations and dynamic characteristics. However, an effective method for estimating time-varying functional connectivity is lacking, which is mainly due to the difficulty in choosing an appropriate window to localize the time-varying correlation coefficients (TVCC). This paper introduces a novel method for adaptively estimating the TVCC of non-stationary signals and studies its application to infer dynamic functional connectivity of fMRI data in a visual task. The proposed method employs a sliding window having a certain bandwidth to estimate the TVCC locally and the window bandwidths are selected adaptively by a local plug-in rule to minimize the mean squared error. The results show that the functional connectivity changes in the visual task are transient, which suggests that simply assuming sustained connectivity changes during task period might not be sufficient to capture dynamic connectivity changes induced by tasks.published_or_final_versio

On the Hardware/Software Design and Implementation of a High Definition Multiview Video Surveillance System

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Advancement of the annual traffic census in Hong Kong

This paper summarises the process, findings and recommendations of a recently completed joint university consultancy project that reviewed the annual traffic census (ATC) in Hong Kong. The results of a survey that assessed the usefulness of the census report are presented, together with an overview of the existing traffic data collection process and traffic detection equipment. Areas for improvement are then identified, including the sampling strategies for the collection of vehicle classification and occupancy data, the procedure for the development of group scaling factors, the method for the selection of core and coverage stations, the approaches to developing growth factors and traffic flow estimation, the presentation method and database structure of the census framework, and the manpower requirements. Based on these identified areas, a new computer program is developed to integrate all of the tasks of the census report and to produce the results in CD-ROM format. Finally, concluding remarks are given together with recommendations for further study.published_or_final_versio

Structural basis for oligomerization and glycosaminoglycan binding of CCL5 and CCL3.

CC chemokine ligand 5 (CCL5) and CCL3 are critical for immune surveillance and inflammation. Consequently, they are linked to the pathogenesis of many inflammatory conditions and are therapeutic targets. Oligomerization and glycosaminoglycan (GAG) binding of CCL5 and CCL3 are vital for the functions of these chemokines. Our structural and biophysical analyses of human CCL5 reveal that CCL5 oligomerization is a polymerization process in which CCL5 forms rod-shaped, double-helical oligomers. This CCL5 structure explains mutational data and offers a unified mechanism for CCL3, CCL4, and CCL5 assembly into high-molecular-weight, polydisperse oligomers. A conserved, positively charged BBXB motif is key for the binding of CC chemokines to GAG. However, this motif is partially buried when CCL3, CCL4, and CCL5 are oligomerized; thus, the mechanism by which GAG binds these chemokine oligomers has been elusive. Our structures of GAG-bound CCL5 and CCL3 oligomers reveal that these chemokine oligomers have distinct GAG-binding mechanisms. The CCL5 oligomer uses another positively charged and fully exposed motif, KKWVR, in GAG binding. However, residues from two partially buried BBXB motifs along with other residues combine to form a GAG-binding groove in the CCL3 oligomer. The N termini of CC chemokines are shown to be involved in receptor binding and oligomerization. We also report an alternative CCL3 oligomer structure that reveals how conformational changes in CCL3 N termini profoundly alter its surface properties and dimer-dimer interactions to affect GAG binding and oligomerization. Such complexity in oligomerization and GAG binding enables intricate, physiologically relevant regulation of CC chemokine functions

Efficient Implementation and Design of A New Single-Channel Electrooculography-based Human-Machine Interface System

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Differential Effects of Concomitant Use of Vitamins C and E on Trophoblast Apoptosis and Autophagy between Normoxia and Hypoxia-Reoxygenation

Concomitant supplementation of vitamins C and E during pregnancy has been reportedly associated with low birth weight, the premature rupture of membranes and fetal loss or perinatal death in women at risk for preeclampsia; however, the cause is unknown. We surmise that hypoxia-reoxygenation (HR) within the intervillous space due to abnormal placentation is the mechanism and hypothesize that concomitant administration of aforementioned vitamin antioxidants detrimentally affects trophoblast cells during HR.Using villous explants, concomitant administration of 50 microM of vitamins C and E was observed to reduce apoptotic and autophagic changes in the trophoblast layer at normoxia (8% oxygen) but to cause more prominent apoptosis and autophagy during HR. Furthermore, increased levels of Bcl-2 and Bcl-xL in association with a decrease in the autophagy-related protein LC3-II were noted in cytotrophoblastic cells treated with vitamins C and E under standard culture conditions. In contrast, vitamin treatment decreased Bcl-2 and Bcl-xL as well as increased mitochondrial Bak and cytosolic LC3-II in cytotrophoblasts subjected to HR.Our results indicate that concomitant administration of vitamins C and E has differential effects on the changes of apoptosis, autophagy and the expression of Bcl-2 family of proteins in the trophoblasts between normoxia and HR. These changes may probably lead to the impairment of placental function and suboptimal growth of the fetus