Support Vector Machines for Speech Recognition

Hidden Markov models (HMM) with Gaussian mixture observation densities are the dominant approach in speech recognition. These systems typically use a representational model for acoustic modeling which can often be prone to overfitting and does not translate to improved discrimination. We propose a new paradigm centered on principles of structural risk minimization using a discriminative framework for speech recognition based on support vector machines (SVMs). SVMs have the ability to simultaneously optimize the representational and discriminative ability of the acoustic classifiers. We have developed the first SVM-based large vocabulary speech recognition system that improves performance over traditional HMM-based systems. This hybrid system achieves a state-of-the-art word error rate of 10.6% on a continuous alphadigit task ? a 10% improvement relative to an HMM system. On SWITCHBOARD, a large vocabulary task, the system improves performance over a traditional HMM system from 41.6% word error rate to 40.6%. This dissertation discusses several practical issues that arise when SVMs are incorporated into the hybrid system

Power Bounded Computing on Current & Emerging HPC Systems

Power has become a critical constraint for the evolution of large scale High Performance Computing (HPC) systems and commercial data centers. This constraint spans almost every level of computing technologies, from IC chips all the way up to data centers due to physical, technical, and economic reasons. To cope with this reality, it is necessary to understand how available or permissible power impacts the design and performance of emergent computer systems. For this reason, we propose power bounded computing and corresponding technologies to optimize performance on HPC systems with limited power budgets. We have multiple research objectives in this dissertation. They center on the understanding of the interaction between performance, power bounds, and a hierarchical power management strategy. First, we develop heuristics and application aware power allocation methods to improve application performance on a single node. Second, we develop algorithms to coordinate power across nodes and components based on application characteristic and power budget on a cluster. Third, we investigate performance interference induced by hardware and power contentions, and propose a contention aware job scheduling to maximize system throughput under given power budgets for node sharing system. Fourth, we extend to GPU-accelerated systems and workloads and develop an online dynamic performance & power approach to meet both performance requirement and power efficiency. Power bounded computing improves performance scalability and power efficiency and decreases operation costs of HPC systems and data centers. This dissertation opens up several new ways for research in power bounded computing to address the power challenges in HPC systems. The proposed power and resource management techniques provide new directions and guidelines to green exscale computing and other computing systems

Effective interprocess communication (IPC) in a real-time transputer network

The thesis describes the design and implementation of an interprocess communication (IPC) mechanism within a real-time distributed operating system kernel (RT-DOS) which is designed for a transputer-based network. The requirements of real-time operating systems are examined and existing design and implementation strategies are described. Particular attention is paid to one of the object-oriented techniques although it is concluded that these techniques are not feasible for the chosen implementation platform. Studies of a number of existing operating systems are reported. The choices for various aspects of operating system design and their influence on the IPC mechanism to be used are elucidated. The actual design choices are related to the real-time requirements and the implementation that has been adopted is described. [Continues.

Cloud Computing cost and energy optimization through Federated Cloud SoS

2017 Fall.Includes bibliographical references.The two most significant differentiators amongst contemporary Cloud Computing service providers have increased green energy use and datacenter resource utilization. This work addresses these two issues from a system's architectural optimization viewpoint. The proposed approach herein, allows multiple cloud providers to utilize their individual computing resources in three ways by: (1) cutting the number of datacenters needed, (2) scheduling available datacenter grid energy via aggregators to reduce costs and power outages, and lastly by (3) utilizing, where appropriate, more renewable and carbon-free energy sources. Altogether our proposed approach creates an alternative paradigm for a Federated Cloud SoS approach. The proposed paradigm employs a novel control methodology that is tuned to obtain both financial and environmental advantages. It also supports dynamic expansion and contraction of computing capabilities for handling sudden variations in service demand as well as for maximizing usage of time varying green energy supplies. Herein we analyze the core SoS requirements, concept synthesis, and functional architecture with an eye on avoiding inadvertent cascading conditions. We suggest a physical architecture that diminishes unwanted outcomes while encouraging desirable results. Finally, in our approach, the constituent cloud services retain their independent ownership, objectives, funding, and sustainability means. This work analyzes the core SoS requirements, concept synthesis, and functional architecture. It suggests a physical structure that simulates the primary SoS emergent behavior to diminish unwanted outcomes while encouraging desirable results. The report will analyze optimal computing generation methods, optimal energy utilization for computing generation as well as a procedure for building optimal datacenters using a unique hardware computing system design based on the openCompute community as an illustrative collaboration platform. Finally, the research concludes with security features cloud federation requires to support to protect its constituents, its constituents tenants and itself from security risks

Automatic Summarization

It has now been 50 years since the publication of Luhn’s seminal paper on automatic summarization. During these years the practical need for automatic summarization has become increasingly urgent and numerous papers have been published on the topic. As a result, it has become harder to find a single reference that gives an overview of past efforts or a complete view of summarization tasks and necessary system components. This article attempts to fill this void by providing a comprehensive overview of research in summarization, including the more traditional efforts in sentence extraction as well as the most novel recent approaches for determining important content, for domain and genre specific summarization and for evaluation of summarization. We also discuss the challenges that remain open, in particular the need for language generation and deeper semantic understanding of language that would be necessary for future advances in the field

A Methodology For Measuring Resilience in a Satellite-Based Communication Network

According to Presidential Policy Directive 21, increasing resilience of critical infrastructures is not only desired, but United States policy. Communications infrastructures are one such critical infrastructure. The purpose of this research is to develop a methodology for measuring resilience in satellite communication systems for use as a key criterion in the selection and acquisition of new satellite architectures, in accordance with the National Security Space Strategy. The base methodology utilized in this thesis is Extreme Event Modeling implemented through the use of Bi-Level Programming with monotonically nonlinear continuous and mixed integer variables. This model differs from previous efforts applied to other critical infrastructures in that it captures the temporal component associated with multiple events, as well as the repairs, or reconstitution, of infrastructure components. Furthermore, a heuristic based upon a ratio of impact to cost and local searches is developed to solve the resulting continuous bi-level problem

Multi-Agent Systems

A multi-agent system (MAS) is a system composed of multiple interacting intelligent agents. Multi-agent systems can be used to solve problems which are difficult or impossible for an individual agent or monolithic system to solve. Agent systems are open and extensible systems that allow for the deployment of autonomous and proactive software components. Multi-agent systems have been brought up and used in several application domains

Consumer behaviour in voice based interactions

The following technological trends have occurred in parallel and together positioned and enabled the execution of my research: (a) The field of consumer behaviour that focuses on intuitive judgment and perception biases has developed significantly in recent years, (b) Speech and voice technologies have reached a commercial stage, and (c) The Big Data boom and other proprietary data that are owned by large corporates have located the industry in a better position than traditional academic bodies in terms of research capabilities. These global developments have created the opportunity to conduct this research which aims to explore the relationship between voice and speech attributes and consumer behaviour in the context of telephone based call centre interactions. The access to call centre recordings and their derivative analysis has enhanced this research with the unique experience of a practitioner rather than being limited to an at arm’s length theoretical analysis. The research questions aim to identify voice and speech attributes that affect (positively or negatively) customer satisfaction levels, and ways in which a company can utilize these attributes to change the way its call centre staff operate. The research methodology is based on a qualitative survey through which I collected data from a real-world call centre (auditory observation), and a triangulation of this data with that of a focus group session. The data went through a correlation test through a sample survey and a synthesis that processes the research findings into theoretical, published literature. Following these research insights, I have developed a Hidden Forces Model which is based on the findings arising from the research. This model offers an alternative way to operate call centres considering adjustments in social interaction by the service staff in order to impact and optimise customer satisfaction for the benefit of the company

Nuclear Power

The world of the twenty first century is an energy consuming society. Due to increasing population and living standards, each year the world requires more energy and new efficient systems for delivering it. Furthermore, the new systems must be inherently safe and environmentally benign. These realities of today's world are among the reasons that lead to serious interest in deploying nuclear power as a sustainable energy source. Today's nuclear reactors are safe and highly efficient energy systems that offer electricity and a multitude of co-generation energy products ranging from potable water to heat for industrial applications. The goal of the book is to show the current state-of-the-art in the covered technical areas as well as to demonstrate how general engineering principles and methods can be applied to nuclear power systems