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Transmission Control Protocol (TCP), a reliable stream delivery transport protocol performs well in wired network compared to the multi-hop wireless network. The multi-hop wireless networks have several distinct features like dynamic self-configuration and self-healing ability remains integrated with wireless internet that enhances its capability. The TCP implementation in multi-hop wireless network...
Floating Content (FC) has recently been proposed as an attractive application for mobile networks, such as VANETs, to operate opportunistic and distributed content sharing over a given geographic area, namely Anchor Zone (AZ). FC performances are tightly dependent on the AZ size, which in literature is classically chosen by the node that generates the floating message. In the present work, we propose...
Small world characteristics (SWC) have been observed and studied in a wide range of disciplines such as social, biological, electrical and computer networks. However, the significance of SWC in wireless sensor network (WSN) applications has hitherto not been investigated. This work investigates the significance of introducing SWC in a conventional WSN for improving the accuracy of WSN node localization...
It is proposed that both digital and analog predistortion (DPD, APD) be used to cancel intermodulation distortion (IMD) in a dual band transmitter. DPD reduces IMDs near the carrier frequencies whereas APD cancels IMDs located at multiples of the carrier frequency separation. It is shown that linearization using memoryless basis waveforms provides cancellation of the dominant IMD modes when the two...
HTTP-based adaptive streaming (HAS) has recently been widely deployed on the Internet. In the HAS approach, a video content is encoded at multiple bitrates and the encoded video content is segmented into small parts of fixed durations. The HAS client requests a video segment, and stores it in the playout buffer. Many studies have shown a robust rate adaptation algorithm is critical to ensuring quality-of-experience...
Position sensorless vector control drives in the rotor-flux-oriented reference frame require precise estimation of rotor flux. A few open-loop rotor flux estimation methods are quite popular. However, the performance of these estimators is quite poor when the inverter switching frequency is quite low as in case of high power drives or when the ratio of switching frequency to maximum fundamental frequency...
The Fundamental PWM Excitation (FPE) is a recent sensorless motor control method in the electrical drive system which uses the current derivative measurement to estimate the rotor position. However, parasitic effects arising from the IGBT switches cause high frequency oscillation in current, so the current derivative estimation cannot be made until these high frequency oscillations die down. In this...
Modern Cloud computing environments are rapidly evolving, leading to a growing adoption of dynamic pricing for virtual resources and of speedier deployment tools and to the emergence of hybrid Cloud scenarios. These trends suggest the opportunity to investigate a new generation of Cloud-based IT services, capable of adapting to changes in their operating conditions and deployment environment by dynamically...
Kernel density estimation is a popular method for identifying crime hotspots for the purpose of data-driven policing. However, computing a kernel density estimate is computationally intensive for large crime datasets, and the quality of the resulting estimate depends heavily on parameters that are difficult to set manually. Inspired by methods from image processing, we propose a novel way for performing...
Given the rapid change in processor architecture in the past years, there is a driving necessity to assess processor performance for a high performance computation workload. Assessing performance for a given workload is important to understand the correlation between architecture parameters and the workload performance. A given workload can be categorized as memory bound, compute bound, or in between...
Design of robust autopilots along with actuator dynamics compensation continues to be a challenging task. Few works are available in the literature to address this issue. In this work an attempt has been made to design a robust roll autopilot using the technique of uncertainty and disturbance estimator, assuming ideal actuator. Further, considering a second order actuator, three methods have been...
In system identification, the more data is collected, the more accurate model is obtained. However, under limited communication bandwidth or computational resources, it is sometimes difficult to collect and store all the measured data, so it is desired to collect and store only useful data for improving model accuracy. This paper focuses on Lebesgue sampling, which uses thresholds on signal level...
Cooperative multi-AUV localization has the potential to outperform single-AUV localization, by taking advantage of data sharing among the team members. Unlike terrestrial communication links, underwater communication links have many issues pertaining to the channel stability and bandwidth, and therefore a decentralized localization is preferred. However this opens up new challenges to team members...
One of the central problems in machine learning and pattern recognition is how to deal with high-dimensional data either for visualization or for classification and clustering. Most of dimensionality reduction technologies, designed to cope with the curse of dimensionality, are based on Euclidean distance metric. In this work, we propose an unsupervised nonlinear dimensionality reduction method which...
Analog-to-information converters and Compressed Sampling (CS) sensor front-ends try to only extract the relevant, information-bearing elements of an incoming data stream. Information extraction and recognition tasks can run directly on the compressed data stream without needing full signal reconstruction. The accuracy of the extracted information or classification is strongly determined by the front-end...
Sufficient dimension reduction (SDR) is a popular framework for supervised dimension reduction, aiming at reducing the dimensionality of input data while information on output data is maximally maintained. On the other hand, in many recent supervised classification learning tasks, it is conceivable that the balance of samples in each class varies between the training and testing phases. Such a phenomenon,...
This paper analyzes the performance of passive time delay estimation with bandpass signals and generalizes the results of Weiss and Weinstein by considering a more general bandpass signal model with a parameter that allows for increasing the mean-squared bandwidth of the bandpass signal with respect to conventional flat bandpass signals. Analysis of the modified Ziv-Zakai lower bound shows (i) performance...
We introduce POSTAL, a new range-free positioning protocol for mobile ad hoc networks (MANETs) that eliminates the need of constantly flooding the whole network with positioning information. The proposed protocol is based on regions of interest which are connected components of the MANET spanning a beacon (or reference) node and one or more nodes interested in estimating their position. These regions...
A probabilistic power flow method considering variable bandwidth kernel density estimation (VKDE) for traction substation loads of high-speed railways is proposed. A variable bandwidth kernel density estimator, which varies the bandwidths to minimize mean squared errors at different estimation points, is adopted to model traction substation loads of high-speed railways. The traction substation loads...
The paper introduces a novel method for distance estimation based on an OFDM signal combined with the Zadoff-Chu sequences. By exploiting the properties of these sequences, it is possible to evaluate the distance between two active nodes with a very good precision and accuracy. The technique effectiveness is demonstrated by measuring the distance between a single transmitter and a synchronized receiver...
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