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Articles 1 - 13 of 13
Full-Text Articles in Engineering
A Parallel Direct Method For Finite Element Electromagnetic Computations Based On Domain Decomposition, Javad Moshfegh
A Parallel Direct Method For Finite Element Electromagnetic Computations Based On Domain Decomposition, Javad Moshfegh
Doctoral Dissertations
High performance parallel computing and direct (factorization-based) solution methods have been the two main trends in electromagnetic computations in recent years. When time-harmonic (frequency-domain) Maxwell's equation are directly discretized with the Finite Element Method (FEM) or other Partial Differential Equation (PDE) methods, the resulting linear system of equations is sparse and indefinite, thus harder to efficiently factorize serially or in parallel than alternative methods e.g. integral equation solutions, that result in dense linear systems. State-of-the-art sparse matrix direct solvers such as MUMPS and PARDISO don't scale favorably, have low parallel efficiency and high memory footprint. This work introduces a new …
Service Competition And Data-Centric Protocols For Internet Access, Thiago Teixeira
Service Competition And Data-Centric Protocols For Internet Access, Thiago Teixeira
Doctoral Dissertations
The Internet evolved in many aspects, from the application to the physical layers. However, the evolution of the Internet access technologies, most visible in dense urban scenarios, is not easily noticeable in sparsely populated and rural areas. In the United States, for example, the FCC identified that 50% of the census blocks have access to up to two broadband providers; however, these providers do not necessarily compete. Additionally, due to the methodology of the study, there is evidence that the number of actual customers without broadband access is higher since the FCC considers the entire block to have broadband if …
Time-Difference Circuits: Methodology, Design, And Digital Realization, Shuo Li
Time-Difference Circuits: Methodology, Design, And Digital Realization, Shuo Li
Doctoral Dissertations
This thesis presents innovations for a special class of circuits called Time Difference (TD) circuits. We introduce a signal processing methodology with TD signals that alters the target signal from a magnitude perspective to time interval between two time events and systematically organizes the primary TD functions abstracted from existing TD circuits and systems. The TD circuits draw attention from a broad range of application fields. In addition, highly evolved complementary metal-oxide-semiconductor (CMOS) technology suffers from various problems related to voltage and current amplitude signal processing methods. Compared to traditional analog and digital circuits, TD circuits bring several compelling features: …
Stealthy Parametric Hardware Trojans In Vlsi Circuits, Samaneh Ghandali
Stealthy Parametric Hardware Trojans In Vlsi Circuits, Samaneh Ghandali
Doctoral Dissertations
Over the last decade, hardware Trojans have gained increasing attention in academia, industry and by government agencies. In order to design reliable countermeasures, it is crucial to understand how hardware Trojans can be built in practice. This is an area that has received relatively scant treatment in the literature. In this thesis, we examine how particularly stealthy parametric Trojans can be introduced to VLSI circuits. Parametric Trojans do not require any additional logic and are purely based on subtle manipulations on the sub-transistor level to modify the parameters of few transistors which makes them very hard to detect. We introduce …
Function And Dissipation In Finite State Automata - From Computing To Intelligence And Back, Natesh Ganesh
Function And Dissipation In Finite State Automata - From Computing To Intelligence And Back, Natesh Ganesh
Doctoral Dissertations
Society has benefited from the technological revolution and the tremendous growth in computing powered by Moore's law. However, we are fast approaching the ultimate physical limits in terms of both device sizes and the associated energy dissipation. It is important to characterize these limits in a physically grounded and implementation-agnostic manner, in order to capture the fundamental energy dissipation costs associated with performing computing operations with classical information in nano-scale quantum systems. It is also necessary to identify and understand the effect of quantum in-distinguishability, noise, and device variability on these dissipation limits. Identifying these parameters is crucial to designing …
Feature Space Modeling For Accurate And Efficient Learning From Non-Stationary Data, Ayesha Akter
Feature Space Modeling For Accurate And Efficient Learning From Non-Stationary Data, Ayesha Akter
Doctoral Dissertations
A non-stationary dataset is one whose statistical properties such as the mean, variance, correlation, probability distribution, etc. change over a specific interval of time. On the contrary, a stationary dataset is one whose statistical properties remain constant over time. Apart from the volatile statistical properties, non-stationary data poses other challenges such as time and memory management due to the limitation of computational resources mostly caused by the recent advancements in data collection technologies which generate a variety of data at an alarming pace and volume. Additionally, when the collected data is complex, managing data complexity, emerging from its dimensionality and …
Sparsity In Machine Learning: An Information Selecting Perspective, Siwei Feng
Sparsity In Machine Learning: An Information Selecting Perspective, Siwei Feng
Doctoral Dissertations
Today we are living in a world awash with data. Large volumes of data are acquired, analyzed and applied to tasks through machine learning algorithms in nearly every area of science, business, and industry. For example, medical scientists analyze the gene expression data from a single specimen to learn the underlying causes of disease (e.g. cancer) and choose the best treatment; retailers can know more about customers' shopping habits from retail data to adjust their business strategies to better appeal to customers; suppliers can enhance supply chain success through supply chain systems built on knowledge sharing. However, it is also …
Improving And Understanding Data Quality In Large-Scale Data Systems, Xiaolan Wang
Improving And Understanding Data Quality In Large-Scale Data Systems, Xiaolan Wang
Doctoral Dissertations
Systems and applications rely heavily on data, which makes data quality a critical factor for their function. In turn, low quality data can be incredibly costly and disruptive, leading to loss of revenue, incorrect conclusions, and misguided policy decisions. Improving data quality is far more than purging datasets of errors; it is more important to improve the processes that produce the data, to collect good data sources that are used for generating the data, and to truly understand the quality of the data. Therefore, the objective of this thesis is to improve and understand data quality from the above aspects. …
Modeling Temporal Structures In Time-Varying Networks, Kun Tu
Modeling Temporal Structures In Time-Varying Networks, Kun Tu
Doctoral Dissertations
A dynamic network is a network whose structure changes because of the emergence and disappearance of node or edges. It can be used to study complex systems where individuals in a system are represented as nodes and their relations/interactions are represented as edges. Studying dynamic network structures helps to better understand changes in relationships. Considerable work has been conducted on learning network structure. However, due to the complexity of dynamic networks, there is considerable room for improvement to obtain better analysis results. This thesis studies different aspects of characteristic and dynamics of a network, focusing on their application in link …
Sequence Design Via Semidefinite Programming Relaxation And Randomized Projection, Dian Mo
Sequence Design Via Semidefinite Programming Relaxation And Randomized Projection, Dian Mo
Doctoral Dissertations
Wideband is a booming technology in the field of wireless communications. The receivers in wideband communication systems are expected to cover a very wide spectrum and adaptively extract the parts of interest. The literature has focused on mixing the input spectrum to baseband using a pseudorandom sequence modulation and recovering the received signals from linearly independent measurements by parallel branches to mitigate the pressures from required extreme high sampling frequency. However, a pseudorandom sequence provides no rejection for the strong interferers received together with weak signals from distant sources. The interferers cause significant distortion due to the nonlinearity of the …
Fundamental Limits Of Covert Communication In Packet Channels, Ramin Soltani
Fundamental Limits Of Covert Communication In Packet Channels, Ramin Soltani
Doctoral Dissertations
This dissertation focuses on covert communication in channels where the communication takes place by the transmission of packets. Consider a channel where authorized transmitter Jack sends packets to authorized receiver Steve according to a Poisson process with rate $\lambda$ packets per second for a time period $T$. Jack's transmitted packet visit Alice, Willie, Bob and Steve, respectively. Suppose that covert transmitter Alice wishes to communicate information to covert receiver Bob without being detected by a watchful adversary Willie. We consider three sets of assumptions for this channel. For each set of assumptions, we present a technique for establishing covert communication …
Volumetric Error Compensation For Industrial Robots And Machine Tools, Le Ma
Volumetric Error Compensation For Industrial Robots And Machine Tools, Le Ma
Doctoral Dissertations
“A more efficient and increasingly popular volumetric error compensation method for machine tools is to compute compensation tables in axis space with tool tip volumetric measurements. However, machine tools have high-order geometric errors and some workspace is not reachable by measurement devices, the compensation method suffers a curve-fitting challenge, overfitting measurements in measured space and losing accuracy around and out of the measured space. Paper I presents a novel method that aims to uniformly interpolate and extrapolate the compensation tables throughout the entire workspace. By using a uniform constraint to bound the tool tip error slopes, an optimal model with …
Neuroengineering Of Clustering Algorithms, Leonardo Enzo Brito Da Silva
Neuroengineering Of Clustering Algorithms, Leonardo Enzo Brito Da Silva
Doctoral Dissertations
"Cluster analysis can be broadly divided into multivariate data visualization, clustering algorithms, and cluster validation. This dissertation contributes neural network-based techniques to perform all three unsupervised learning tasks. Particularly, the first paper provides a comprehensive review on adaptive resonance theory (ART) models for engineering applications and provides context for the four subsequent papers. These papers are devoted to enhancements of ART-based clustering algorithms from (a) a practical perspective by exploiting the visual assessment of cluster tendency (VAT) sorting algorithm as a preprocessor for ART offline training, thus mitigating ordering effects; and (b) an engineering perspective by designing a family of …