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Articles 1 - 5 of 5
Full-Text Articles in Engineering
Analyzing Evolution Of Rare Events Through Social Media Data, Xiaoyu Lu
Analyzing Evolution Of Rare Events Through Social Media Data, Xiaoyu Lu
Dissertations
Recently, some researchers have attempted to find a relationship between the evolution of rare events and temporal-spatial patterns of social media activities. Their studies verify that the relationship exists in both time and spatial domains. However, few of those studies can accurately deduce a time point when social media activities are most highly affected by a rare event because producing an accurate temporal pattern of social media during the evolution of a rare event is very difficult. This work expands the current studies along three directions. Firstly, we focus on the intensity of information volume and propose an innovative clustering …
Blind Separation For Intermittent Sources Via Sparse Dictionary Learning, Annan Dong
Blind Separation For Intermittent Sources Via Sparse Dictionary Learning, Annan Dong
Dissertations
Radio frequency sources are observed at a fusion center via sensor measurements made over slow flat-fading channels. The number of sources may be larger than the number of sensors, but their activity is sparse and intermittent with bursty transmission patterns. To account for this, sources are modeled as hidden Markov models with known or unknown parameters. The problem of blind source estimation in the absence of channel state information is tackled via a novel algorithm, consisting of a dictionary learning (DL) stage and a per-source stochastic filtering (PSF) stage. The two stages work in tandem, with the latter operating on …
Probabilistic Spiking Neural Networks : Supervised, Unsupervised And Adversarial Trainings, Alireza Bagheri
Probabilistic Spiking Neural Networks : Supervised, Unsupervised And Adversarial Trainings, Alireza Bagheri
Dissertations
Spiking Neural Networks (SNNs), or third-generation neural networks, are networks of computation units, called neurons, in which each neuron with internal analogue dynamics receives as input and produces as output spiking, that is, binary sparse, signals. In contrast, second-generation neural networks, termed as Artificial Neural Networks (ANNs), rely on simple static non-linear neurons that are known to be energy-intensive, hindering their implementations on energy-limited processors such as mobile devices. The sparse event-based characteristics of SNNs for information transmission and encoding have made them more feasible for highly energy-efficient neuromorphic computing architectures. The most existing training algorithms for SNNs are based …
Supercapacitors With Gate Electrodes, Tazima Selim Chowdhury
Supercapacitors With Gate Electrodes, Tazima Selim Chowdhury
Dissertations
A new approach to improve the capacitance of supercapacitors (SC) is proposed in this study. A typical SC is composed of an anode and a cathode; a separator in between them assures an unintentional discharge of the capacitor. The study focuses on a family of structured separators, either electronically active or passive which are called gates. An active structured separator layer has been fabricated and analyzed. The structured separator has characteristics of electrical diode and is fabricated out of functionalized carbon nanotubes (CNT). Improvement of the overall capacitance of SC, equipped with either active or passive structured separators demonstrated a …
Epitaxial Growth Of Iii-Nitride Nanostructures And Their Optoelectronic Applications, Moab Rajan Philip
Epitaxial Growth Of Iii-Nitride Nanostructures And Their Optoelectronic Applications, Moab Rajan Philip
Dissertations
Light-emitting diodes (LEDs) using III-nitride nanowire heterostructures have been intensively studied as promising candidates for future phosphor-free solid-state lighting and full-color displays. Compared to conventional GaN-based planar LEDs, III-nitride nanowire LEDs exhibit numerous advantages including greatly reduced dislocation densities, polarization fields, and quantum-confined Stark effect due to the effective lateral stress relaxation, promising high efficiency full-color LEDs. Beside these advantages, however, several factors have been identified as the limiting factors for further enhancing the nanowire LED quantum efficiency and light output power. Some of the most probable causes have been identified as due to the lack of carrier confinement in …