Passive IP devices like SIP based surveillance camera, need to be secured due to the private info... more Passive IP devices like SIP based surveillance camera, need to be secured due to the private information that it may transmit. This paper proposes an architecture to secure the information that the device could access in peer-to-peer overlay networks. This architecture provides the security mechanism for authentication, authorization and audit (AAA). It combines the security features of Authentication Servers with SIP architecture to provide AAA Service to registered users needing access to passive IP devices. Dynamic password for authenticating the access of the passive devices managed by the authentication server could be also applied to enhance the security features of devices.
2005 13th IEEE International Conference on Networks Jointly held with the 2005 IEEE 7th Malaysia International Conf on Communic
... topof the transport layer, SIP can support many new services including multimedia communicati... more ... topof the transport layer, SIP can support many new services including multimedia communications and presence ... SIP COMMUNICATIONS AND SERVICES A three-layer SIP-based service architecture with a call ... The following table (Table.l) gives a review of securjty issues in all ...
This paper presents a novel video-on-demand (VoD) streaming scheme using rateless coding in peer-... more This paper presents a novel video-on-demand (VoD) streaming scheme using rateless coding in peer-to-peer networks. The proposed scheme (called rVoD) efficiently supports user free interactivity and resilient video streaming over lossy networks. In rVoD, videos are divided into small blocks. Partial information of each block is stored at every peer's local storage using rateless codes after it has been played. Unlike previous works based on caching of some blocks at every peer, in our scheme, every user stores the partial complete-video content so that any VCR operations such as random seeking do not break the connections between it and its children but also between it and its parents. The experiment results show that the proposed scheme has better performance in terms of server stress, latency and overhead compared to a recently proposed VMesh system [1].
Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques, 1993
ABSTRACT:A closed-loop or recurrent neural network was taught to generate output discharges to re... more ABSTRACT:A closed-loop or recurrent neural network was taught to generate output discharges to reproduce the prototypical activations in agonist and antagonist muscles which produce the displacement of a limb about a single joint. By introducing a generalized decrease in the excitability of the pre-output layer in the network, the network made the displacement more slowly and also showed an inability to maintain a repetitive movement. These concepts can be applied to the human nervous system in the understanding of the physical basis of movement and its disorders. It is suggested that a movement represents the output of a closed-loop network, such as the cortical-basal ganglia-thalamic-cortical motor loop, which iterates repetitively to its end point or attractor. The model provides an explanation of how the state of thalamic inhibition seen in Parkinson's disease physically may produce bradykinesia and the inability to maintain a repetitive movement.
Traditionally, time series data augmentation has primarily focused on improving the architecture ... more Traditionally, time series data augmentation has primarily focused on improving the architecture of Generative Adversarial Network (GAN), with the aim of closely matching the original data distribution while also preserving the dynamic behavior of the original data. However, even state-of-the-art GAN models like TimeGAN fall short in preserving the temporal dynamics present in the original time series due to the absence of first-order difference information. To address this limitation, this study proposes a novel process for generating multivariate time series data. The proposed process comprises four essential modules: a) the GAN module for generating multivariate time series data, b) the sampling module for preserving the first-order difference distribution, c) the smoothing module for refining the generated data, and d) an evaluation module using the Kolmogorov-Smirnov Test (KS-test) and Hilbert-Schmidt Independence Criterion (HSIC), along with other metrics to test the synthetic...
In recent years, big data produced by the Internet of Things has enabled new kinds of useful appl... more In recent years, big data produced by the Internet of Things has enabled new kinds of useful applications. One such application is monitoring a fleet of vehicles in real time to predict their remaining useful life. The consensus self-organized models (COSMO) approach is an example of a predictive maintenance system. The present work proposes a novel Internet of Things based architecture for predictive maintenance that consists of three primary nodes: the vehicle node, the server leader node, and the root node, which enable on-board vehicle data processing, heavy-duty data processing, and fleet administration, respectively. A minimally viable prototype of the proposed architecture was implemented and deployed to a local bus garage in Gatineau, Canada. The present work proposes improved consensus self-organized models (ICOSMO), a fleet-wide unsupervised dynamic sensor selection algorithm. To analyze the performance of ICOSMO, a fleet simulation was implemented. The J1939 data gathered...
2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583)
The most important characteristics required in dynamic systems modeling using neural networks are... more The most important characteristics required in dynamic systems modeling using neural networks are fast convergence and generalization capability. To achieve these, this paper presents an approach to nonlinear state-space modeling using recurrent multilayer perceptrons (RMLP) trained with the unscented Kalman filter (UKF). The recently proposed UKF, which is proper to state-space representation, offers not only fast convergence but also derivative-free
The wavelet transform is a very effective signal analysis tool for many problems for which Fourie... more The wavelet transform is a very effective signal analysis tool for many problems for which Fourier based methods have been inapplicable, expensive for real-time applications, or can only be applied with difficulty. The discrete wavelet transform can be implemented in VLSI more efficiently than the FFT. A single chip implementation is described.
Passive IP devices like SIP based surveillance camera, need to be secured due to the private info... more Passive IP devices like SIP based surveillance camera, need to be secured due to the private information that it may transmit. This paper proposes an architecture to secure the information that the device could access in peer-to-peer overlay networks. This architecture provides the security mechanism for authentication, authorization and audit (AAA). It combines the security features of Authentication Servers with SIP architecture to provide AAA Service to registered users needing access to passive IP devices. Dynamic password for authenticating the access of the passive devices managed by the authentication server could be also applied to enhance the security features of devices.
2005 13th IEEE International Conference on Networks Jointly held with the 2005 IEEE 7th Malaysia International Conf on Communic
... topof the transport layer, SIP can support many new services including multimedia communicati... more ... topof the transport layer, SIP can support many new services including multimedia communications and presence ... SIP COMMUNICATIONS AND SERVICES A three-layer SIP-based service architecture with a call ... The following table (Table.l) gives a review of securjty issues in all ...
This paper presents a novel video-on-demand (VoD) streaming scheme using rateless coding in peer-... more This paper presents a novel video-on-demand (VoD) streaming scheme using rateless coding in peer-to-peer networks. The proposed scheme (called rVoD) efficiently supports user free interactivity and resilient video streaming over lossy networks. In rVoD, videos are divided into small blocks. Partial information of each block is stored at every peer's local storage using rateless codes after it has been played. Unlike previous works based on caching of some blocks at every peer, in our scheme, every user stores the partial complete-video content so that any VCR operations such as random seeking do not break the connections between it and its children but also between it and its parents. The experiment results show that the proposed scheme has better performance in terms of server stress, latency and overhead compared to a recently proposed VMesh system [1].
Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques, 1993
ABSTRACT:A closed-loop or recurrent neural network was taught to generate output discharges to re... more ABSTRACT:A closed-loop or recurrent neural network was taught to generate output discharges to reproduce the prototypical activations in agonist and antagonist muscles which produce the displacement of a limb about a single joint. By introducing a generalized decrease in the excitability of the pre-output layer in the network, the network made the displacement more slowly and also showed an inability to maintain a repetitive movement. These concepts can be applied to the human nervous system in the understanding of the physical basis of movement and its disorders. It is suggested that a movement represents the output of a closed-loop network, such as the cortical-basal ganglia-thalamic-cortical motor loop, which iterates repetitively to its end point or attractor. The model provides an explanation of how the state of thalamic inhibition seen in Parkinson's disease physically may produce bradykinesia and the inability to maintain a repetitive movement.
Traditionally, time series data augmentation has primarily focused on improving the architecture ... more Traditionally, time series data augmentation has primarily focused on improving the architecture of Generative Adversarial Network (GAN), with the aim of closely matching the original data distribution while also preserving the dynamic behavior of the original data. However, even state-of-the-art GAN models like TimeGAN fall short in preserving the temporal dynamics present in the original time series due to the absence of first-order difference information. To address this limitation, this study proposes a novel process for generating multivariate time series data. The proposed process comprises four essential modules: a) the GAN module for generating multivariate time series data, b) the sampling module for preserving the first-order difference distribution, c) the smoothing module for refining the generated data, and d) an evaluation module using the Kolmogorov-Smirnov Test (KS-test) and Hilbert-Schmidt Independence Criterion (HSIC), along with other metrics to test the synthetic...
In recent years, big data produced by the Internet of Things has enabled new kinds of useful appl... more In recent years, big data produced by the Internet of Things has enabled new kinds of useful applications. One such application is monitoring a fleet of vehicles in real time to predict their remaining useful life. The consensus self-organized models (COSMO) approach is an example of a predictive maintenance system. The present work proposes a novel Internet of Things based architecture for predictive maintenance that consists of three primary nodes: the vehicle node, the server leader node, and the root node, which enable on-board vehicle data processing, heavy-duty data processing, and fleet administration, respectively. A minimally viable prototype of the proposed architecture was implemented and deployed to a local bus garage in Gatineau, Canada. The present work proposes improved consensus self-organized models (ICOSMO), a fleet-wide unsupervised dynamic sensor selection algorithm. To analyze the performance of ICOSMO, a fleet simulation was implemented. The J1939 data gathered...
2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583)
The most important characteristics required in dynamic systems modeling using neural networks are... more The most important characteristics required in dynamic systems modeling using neural networks are fast convergence and generalization capability. To achieve these, this paper presents an approach to nonlinear state-space modeling using recurrent multilayer perceptrons (RMLP) trained with the unscented Kalman filter (UKF). The recently proposed UKF, which is proper to state-space representation, offers not only fast convergence but also derivative-free
The wavelet transform is a very effective signal analysis tool for many problems for which Fourie... more The wavelet transform is a very effective signal analysis tool for many problems for which Fourier based methods have been inapplicable, expensive for real-time applications, or can only be applied with difficulty. The discrete wavelet transform can be implemented in VLSI more efficiently than the FFT. A single chip implementation is described.
Uploads
Papers by Tet Yeap