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Articles 61 - 90 of 129
Full-Text Articles in Computer Engineering
Modeling Pedestrian Behavior In Video, Paul Scovanner
Modeling Pedestrian Behavior In Video, Paul Scovanner
Electronic Theses and Dissertations
The purpose of this dissertation is to address the problem of predicting pedestrian movement and behavior in and among crowds. Specifically, we will focus on an agent based approach where pedestrians are treated individually and parameters for an energy model are trained by real world video data. These learned pedestrian models are useful in applications such as tracking, simulation, and artificial intelligence. The applications of this method are explored and experimental results show that our trained pedestrian motion model is beneficial for predicting unseen or lost tracks as well as guiding appearance based tracking algorithms. The method we have developed …
Patterns Of Motion: Discovery And Generalized Representation, Imran Saleemi
Patterns Of Motion: Discovery And Generalized Representation, Imran Saleemi
Electronic Theses and Dissertations
In this dissertation, we address the problem of discovery and representation of motion patterns in a variety of scenarios, commonly encountered in vision applications. The overarching goal is to devise a generic representation, that captures any kind of object motion observable in video sequences. Such motion is a significant source of information typically employed for diverse applications such as tracking, anomaly detection, and action and event recognition. We present statistical frameworks for representation of motion characteristics of objects, learned from tracks or optical flow, for static as well as moving cameras, and propose algorithms for their application to a variety …
Resource Banking An Energy-Efficient, Run-Time Adaptive Processor Design Technique, Jacob Staples
Resource Banking An Energy-Efficient, Run-Time Adaptive Processor Design Technique, Jacob Staples
Electronic Theses and Dissertations
From the earliest and simplest scalar computation engines to modern superscalar out-oforder processors, the evolution of computational machinery during the past century has largely been driven by a single goal: performance. In today’s world of cheap, billion-plus transistor count processors and with an exploding market in mobile computing, a design landscape has emerged where energy efficiency, arguably more than any other single metric, determines the viability of a processor for a given application. The historical emphasis on performance has left modern processors bloated and over provisioned for everyday tasks in the hope that during computationally intensive periods some performance improvement …
Measuring And Improving Internet Video Quality Of Experience, Mukundan Venkataraman Iyengar
Measuring And Improving Internet Video Quality Of Experience, Mukundan Venkataraman Iyengar
Electronic Theses and Dissertations
Streaming multimedia content over the IP-network is poised to be the dominant Internet traffic for the coming decade, predicted to account for more than 91% of all consumer traffic in the coming years. Streaming multimedia content ranges from Internet television (IPTV), video on demand (VoD), peer-to-peer streaming, and 3D television over IP to name a few. Widespread acceptance, growth, and subscriber retention are contingent upon network providers assuring superior Quality of Experience (QoE) on top of todays Internet. This work presents the first empirical understanding of Internet’s video-QoE capabilities, and tools and protocols to efficiently infer and improve them. To …
Towards Calibration Of Optical Flow Of Crowd Videos Using Observed Trajectories, Iman K. Elbadramany
Towards Calibration Of Optical Flow Of Crowd Videos Using Observed Trajectories, Iman K. Elbadramany
Electronic Theses and Dissertations
The need exists for finding a quantitative method for validating crowd simulations. One approach is to use optical flow of videos of real crowds to obtain velocities that can be used for comparison to simulations. Optical flow, in turn, needs to be calibrated to be useful. It is essential to show that optical flow velocities obtained from crowd videos can be mapped into the spatially averaged velocities of the observed trajectories of crowd members, and to quantify the extent of the correlation of the results. This research investigates methods to uncover the best conditions for a good correlation between optical …
A Sustainable Autonomic Architecture For Organically Reconfigurable Computing Systems, Rashad S. Oreifej
A Sustainable Autonomic Architecture For Organically Reconfigurable Computing Systems, Rashad S. Oreifej
Electronic Theses and Dissertations
A Sustainable Autonomic Architecture for Organically Reconfigurable Computing System based on SRAM Field Programmable Gate Arrays (FPGAs) is proposed, modeled analytically, simulated, prototyped, and measured. Low-level organic elements are analyzed and designed to achieve novel self-monitoring, self-diagnosis, and self-repair organic properties. The prototype of a 2-D spatial gradient Sobel video edge-detection organic system use-case developed on a XC4VSX35 Xilinx Virtex-4 Video Starter Kit is presented. Experimental results demonstrate the applicability of the proposed architecture and provide the infrastructure to quantify the performance and overcome fault-handling limitations. Dynamic online autonomous functionality restoration after a malfunction or functionality shift due to changing …
An Adaptive Modular Redundancy Technique To Self-Regulate Availability, Area, And Energy Consumption In Mission-Critical Applications, Rawad N. Al-Haddad
An Adaptive Modular Redundancy Technique To Self-Regulate Availability, Area, And Energy Consumption In Mission-Critical Applications, Rawad N. Al-Haddad
Electronic Theses and Dissertations
As reconfigurable devices' capacities and the complexity of applications that use them increase, the need for self-reliance of deployed systems becomes increasingly prominent. A Sustainable Modular Adaptive Redundancy Technique (SMART) composed of a dual-layered organic system is proposed, analyzed, implemented, and experimentally evaluated. SMART relies upon a variety of self-regulating properties to control availability, energy consumption, and area used, in dynamically-changing environments that require high degree of adaptation. The hardware layer is implemented on a Xilinx Virtex-4 Field Programmable Gate Array (FPGA) to provide self-repair using a novel approach called a Reconfigurable Adaptive Redundancy System (RARS). The software layer supervises …
Analyzing Instructtion Based Cache Replacement Policies, Ping Xiang
Analyzing Instructtion Based Cache Replacement Policies, Ping Xiang
Electronic Theses and Dissertations
The increasing speed gap between microprocessors and off-chip DRAM makes last-level caches (LLCs) a critical component for computer performance. Multi core processors aggravate the problem since multiple processor cores compete for the LLC. As a result, LLCs typically consume a significant amount of the die area and effective utilization of LLCs is mandatory for both performance and power efficiency. We present a novel replacement policy for last-level caches (LLCs). The fundamental observation is to view LLCs as a shared resource among multiple address streams with each stream being generated by a static memory access instruction. The management of LLCs in …
Episodic Memory Model For Embodied Conversational Agents, Miguel Elvir
Episodic Memory Model For Embodied Conversational Agents, Miguel Elvir
Electronic Theses and Dissertations
Embodied Conversational Agents (ECA) form part of a range of virtual characters whose intended purpose include engaging in natural conversations with human users. While works in literature are ripe with descriptions of attempts at producing viable ECA architectures, few authors have addressed the role of episodic memory models in conversational agents. This form of memory, which provides a sense of autobiographic record-keeping in humans, has only recently been peripherally integrated into dialog management tools for ECAs. In our work, we propose to take a closer look at the shared characteristics of episodic memory models in recent examples from the field. …
Improving Performance And Programmer Productivity For I/O-Intensive High Performance Computing Applications, Saba Sehrish
Improving Performance And Programmer Productivity For I/O-Intensive High Performance Computing Applications, Saba Sehrish
Electronic Theses and Dissertations
Due to the explosive growth in the size of scientific data sets, data-intensive computing is an emerging trend in computational science. HPC applications are generating and processing large amount of data ranging from terabytes (TB) to petabytes (PB). This new trend of growth in data for HPC applications has imposed challenges as to what is an appropriate parallel programming framework to efficiently process large data sets. In this work, we study the applicability of two programming models (MPI/MPI-IO and MapReduce) to a variety of I/O-intensive HPC applications ranging from simulations to analytics. We identify several performance and programmer productivity related …
Contextualizing Observational Data For Modeling Human Performance, Viet Trinh
Contextualizing Observational Data For Modeling Human Performance, Viet Trinh
Electronic Theses and Dissertations
This research focuses on the ability to contextualize observed human behaviors in efforts to automate the process of tactical human performance modeling through learning from observations. This effort to contextualize human behavior is aimed at minimizing the role and involvement of the knowledge engineers required in building intelligent Context-based Reasoning (CxBR) agents. More specifically, the goal is to automatically discover the context in which a human actor is situated when performing a mission to facilitate the learning of such CxBR models. This research is derived from the contextualization problem left behind in Fernlund's research on using the Genetic Context Learner …
An Architecture For High-Performance Privacy-Preserving And Distributed Data Mining, James Secretan
An Architecture For High-Performance Privacy-Preserving And Distributed Data Mining, James Secretan
Electronic Theses and Dissertations
This dissertation discusses the development of an architecture and associated techniques to support Privacy Preserving and Distributed Data Mining. The field of Distributed Data Mining (DDM) attempts to solve the challenges inherent in coordinating data mining tasks with databases that are geographically distributed, through the application of parallel algorithms and grid computing concepts. The closely related field of Privacy Preserving Data Mining (PPDM) adds the dimension of privacy to the problem, trying to find ways that organizations can collaborate to mine their databases collectively, while at the same time preserving the privacy of their records. Developing data mining algorithms for …
Scalable And Efficient Outlier Detection In Large Distributed Data Sets With Mixed-Type Attributes, Anna Koufakou
Scalable And Efficient Outlier Detection In Large Distributed Data Sets With Mixed-Type Attributes, Anna Koufakou
Electronic Theses and Dissertations
An important problem that appears often when analyzing data involves identifying irregular or abnormal data points called outliers. This problem broadly arises under two scenarios: when outliers are to be removed from the data before analysis, and when useful information or knowledge can be extracted by the outliers themselves. Outlier Detection in the context of the second scenario is a research field that has attracted significant attention in a broad range of useful applications. For example, in credit card transaction data, outliers might indicate potential fraud; in network traffic data, outliers might represent potential intrusion attempts. The basis of deciding …
Falconet: Force-Feedback Approach For Learning From Coaching And Observation Using Natural And Experiential Training, Gary Stein
Electronic Theses and Dissertations
Building an intelligent agent model from scratch is a difficult task. Thus, it would be preferable to have an automated process perform this task. There have been many manual and automatic techniques, however, each of these has various issues with obtaining, organizing, or making use of the data. Additionally, it can be difficult to get perfect data or, once the data is obtained, impractical to get a human subject to explain why some action was performed. Because of these problems, machine learning from observation emerged to produce agent models based on observational data. Learning from observation uses unobtrusive and purely …
Variable Resolution & Dimensional Mapping For 3d Model Optimization, Joseph Venezia
Variable Resolution & Dimensional Mapping For 3d Model Optimization, Joseph Venezia
Electronic Theses and Dissertations
Three-dimensional computer models, especially geospatial architectural data sets, can be visualized in the same way humans experience the world, providing a realistic, interactive experience. Scene familiarization, architectural analysis, scientific visualization, and many other applications would benefit from finely detailed, high resolution, 3D models. Automated methods to construct these 3D models traditionally has produced data sets that are often low fidelity or inaccurate; otherwise, they are initially highly detailed, but are very labor and time intensive to construct. Such data sets are often not practical for common real-time usage and are not easily updated. This thesis proposes Variable Resolution & Dimensional …
Dynamic Task Allocation In Mobile Robot Systems Using Utility Funtions, Scott Vander Weide
Dynamic Task Allocation In Mobile Robot Systems Using Utility Funtions, Scott Vander Weide
Electronic Theses and Dissertations
We define a novel algorithm based on utility functions for dynamically allocating tasks to mobile robots in a multi-robot system. The algorithm attempts to maximize the performance of the mobile robot while minimizing inter-robot communications. The algorithm takes into consideration the proximity of the mobile robot to the task, the priority of the task, the capability required by the task, the capabilities of the mobile robot, and the rarity of the capability within the population of mobile robots. We evaluate the proposed algorithm in a simulation study and compare it to alternative approaches, including the contract net protocol, an approach …
Optimizing Dynamic Logic Realizations For Partial Reconfiguration Of Field Programmable Gate Arrays, Matthew Parris
Optimizing Dynamic Logic Realizations For Partial Reconfiguration Of Field Programmable Gate Arrays, Matthew Parris
Electronic Theses and Dissertations
Many digital logic applications can take advantage of the reconfiguration capability of Field Programmable Gate Arrays (FPGAs) to dynamically patch design flaws, recover from faults, or time-multiplex between functions. Partial reconfiguration is the process by which a user modifies one or more modules residing on the FPGA device independently of the others. Partial Reconfiguration reduces the granularity of reconfiguration to be a set of columns or rectangular region of the device. Decreasing the granularity of reconfiguration results in reduced configuration filesizes and, thus, reduced configuration times. When compared to one bitstream of a non-partial reconfiguration implementation, smaller modules resulting in …
Sustainable Fault-Handling Of Reconfigurable Logic Using Throughput-Driven Assessment, Carthik Sharma
Sustainable Fault-Handling Of Reconfigurable Logic Using Throughput-Driven Assessment, Carthik Sharma
Electronic Theses and Dissertations
A sustainable Evolvable Hardware (EH) system is developed for SRAM-based reconfigurable Field Programmable Gate Arrays (FPGAs) using outlier detection and group testing-based assessment principles. The fault diagnosis methods presented herein leverage throughput-driven, relative fitness assessment to maintain resource viability autonomously. Group testing-based techniques are developed for adaptive input-driven fault isolation in FPGAs, without the need for exhaustive testing or coding-based evaluation. The techniques maintain the device operational, and when possible generate validated outputs throughout the repair process. Adaptive fault isolation methods based on discrepancy-enabled pair-wise comparisons are developed. By observing the discrepancy characteristics of multiple Concurrent Error Detection (CED) configurations, …
A Competitive Reconfiguration Approach To Autonomous Fault Handling Using Genetic Algorithms, Kening Zhang
A Competitive Reconfiguration Approach To Autonomous Fault Handling Using Genetic Algorithms, Kening Zhang
Electronic Theses and Dissertations
In this dissertation, a novel self-repair approach based on Consensus Based Evaluation (CBE) for autonomous repair of SRAM-based Field Programmable Gate Arrays (FPGAs) is developed, evaluated, and refined. An initial population of functionally identical (same input-output behavior), yet physically distinct (alternative design or place-and-route realization) FPGA configurations is produced at design time. During run-time, the CBE approach ranks these alternative configurations after evaluating their discrepancy relative to the consensus formed by the population. Through runtime competition, faults in the logical resources become occluded from the visibility of subsequent FPGA operations. Meanwhile, offspring formed through crossover and mutation of faulty and …
A Reinforcement Learning Technique For Enhancing Human Behavior Models In A Context-Based Architecture, David Aihe
A Reinforcement Learning Technique For Enhancing Human Behavior Models In A Context-Based Architecture, David Aihe
Electronic Theses and Dissertations
A reinforcement-learning technique for enhancing human behavior models in a context-based learning architecture is presented. Prior to the introduction of this technique, human models built and developed in a Context-Based reasoning framework lacked learning capabilities. As such, their performance and quality of behavior was always limited by what the subject matter expert whose knowledge is modeled was able to articulate or demonstrate. Results from experiments performed show that subject matter experts are prone to making errors and at times they lack information on situations that are inherently necessary for the human models to behave appropriately and optimally in those situations. …
An Adaptive Multiobjective Evolutionary Approach To Optimize Artmap Neural Networks, Assem Kaylani
An Adaptive Multiobjective Evolutionary Approach To Optimize Artmap Neural Networks, Assem Kaylani
Electronic Theses and Dissertations
This dissertation deals with the evolutionary optimization of ART neural network architectures. ART (adaptive resonance theory) was introduced by a Grossberg in 1976. In the last 20 years (1987-2007) a number of ART neural network architectures were introduced into the literature (Fuzzy ARTMAP (1992), Gaussian ARTMAP (1996 and 1997) and Ellipsoidal ARTMAP (2001)). In this dissertation, we focus on the evolutionary optimization of ART neural network architectures with the intent of optimizing the size and the generalization performance of the ART neural network. A number of researchers have focused on the evolutionary optimization of neural networks, but no research has …
Metadata And Data Management In High Performance File And Storage Systems, Peng Gu
Metadata And Data Management In High Performance File And Storage Systems, Peng Gu
Electronic Theses and Dissertations
With the advent of emerging "e-Science" applications, today's scientific research increasingly relies on petascale-and-beyond computing over large data sets of the same magnitude. While the computational power of supercomputers has recently entered the era of petascale, the performance of their storage system is far lagged behind by many orders of magnitude. This places an imperative demand on revolutionizing their underlying I/O systems, on which the management of both metadata and data is deemed to have significant performance implications. Prefetching/caching and data locality awareness optimizations, as conventional and effective management techniques for metadata and data I/O performance enhancement, still play their …
Delay Sensitive Routing For Real Time Traffic Over Ad-Hoc Networks, Dipika Darshana
Delay Sensitive Routing For Real Time Traffic Over Ad-Hoc Networks, Dipika Darshana
Electronic Theses and Dissertations
Wireless ad hoc network consists of inexpensive nodes that form a mobile communication network. Due to limitations of the transmission range, the nodes rely on each other to forward packets such that messages can be delivered across the network. The selection of the path along which a packet is forwarded from the source node to the destination node is done by the routing algorithm. Most commonly used routing algorithms, though effective for non-real time applications, cannot handle real-time applications that require strict delay bounds on packet delivery. In this thesis, we propose a routing protocol that ensures timely delivery of …
A Hybrid Routing Protocol For Communications Among Nodes Withhigh Relative Speed In Wireless Mesh Networks, Nikolaos Peppas
A Hybrid Routing Protocol For Communications Among Nodes Withhigh Relative Speed In Wireless Mesh Networks, Nikolaos Peppas
Electronic Theses and Dissertations
Wireless mesh networks (WMN) is a new promising wireless technology which uses already available hardware and software components. This thesis proposes a routing algorithm for military applications. More specifically, a specialized scenario consisting of a network of flying Unmanned Aerial Vehicles (UAVs) executing reconnaissance missions is investigated. The proposed routing algorithm is hybrid in nature and uses both reactive and proactive routing characteristics to transmit information. Through simulations run on a specially built stand alone simulator, based on Java, packet overhead, delivery ratio and latency metrics were monitored with respect to varying number of nodes, node density and mobility. The …
A Neat Approach To Genetic Programming, Adelein Rodriguez
A Neat Approach To Genetic Programming, Adelein Rodriguez
Electronic Theses and Dissertations
The evolution of explicitly represented topologies such as graphs involves devising methods for mutating, comparing and combining structures in meaningful ways and identifying and maintaining the necessary topological diversity. Research has been conducted in the area of the evolution of trees in genetic programming and of neural networks and some of these problems have been addressed independently by the different research communities. In the domain of neural networks, NEAT (Neuroevolution of Augmenting Topologies) has shown to be a successful method for evolving increasingly complex networks. This system's success is based on three interrelated elements: speciation, marking of historical information in …
Congestion Avoidance And Fairness In Wireless Sensor Networks, Mohammad Ahmad
Congestion Avoidance And Fairness In Wireless Sensor Networks, Mohammad Ahmad
Electronic Theses and Dissertations
Sensor network congestion avoidance and control primarily aims to reduce packet drops while maintaining fair bandwidth allocation to existing network flows. The design of a congestion control algorithm suited for all types of applications in sensor networks is a challenging task due to the application-specific nature of these networks. With numerous sensors transmitting data simultaneously to one or more base stations (also called sinks), sensor nodes located near the base station will most likely experience congestion and packet loss. In this thesis, we propose a novel distributed congestion avoidance algorithm which calculates the ratio of the number of downstream and …
Collaborative Context-Based Reasoning, Gilbert Barrett
Collaborative Context-Based Reasoning, Gilbert Barrett
Electronic Theses and Dissertations
This dissertation explores modeling collaborative behavior, based on Joint Intentions Theory (JIT), in Context-Based Reasoning (CxBR). Context-Based Reasoning is one of several contextual reasoning paradigms. And, Joint Intentions Theory is the definitive semantic framework for collaborative behaviors. In order to formalize collaborative behaviors in CxBR based on JIT, CxBR is first described in terms of the more popular Belief, Desire, and Intention (BDI) model. Once this description is established JIT is used as a basis for the formalism for collaborative behavior in CxBR. The hypothesis of this dissertation is that this formalism allows for effective collaborative behaviors in CxBR. Additionally, …
Eino: An Intelligent Tutor For The University Of Central Florida Infinity Web Applets, James Hollister
Eino: An Intelligent Tutor For The University Of Central Florida Infinity Web Applets, James Hollister
Electronic Theses and Dissertations
This study investigated the various methods involved in creating an intelligent tutor for the University of Central Florida Infinity Web Applets (UCF Infinity Web Applets). After conducting research into various methods, two major methods emerged and they are: solving the problem for the student and helping the student when they become stymied and unable to solve the problem. A storyboard was created to show the interactions of the student and system along with a list of features that were desired to be included in the tutoring system. From the storyboard and list of features, an architecture was created to handle …
Learning Human Behavior From Observation For Gaming Applications, Christopher Moriarty
Learning Human Behavior From Observation For Gaming Applications, Christopher Moriarty
Electronic Theses and Dissertations
The gaming industry has reached a point where improving graphics has only a small effect on how much a player will enjoy a game. One focus has turned to adding more humanlike characteristics into computer game agents. Machine learning techniques are being used scarcely in games, although they do offer powerful means for creating humanlike behaviors in agents. The first person shooter (FPS), Quake 2, is an open source game that offers a multi-agent environment to create game agents (bots) in. This work attempts to combine neural networks with a modeling paradigm known as context based reasoning (CxBR) to create …
Design And Implementation Of A Hardware Level Content Networking Front End Device, Jeremy Layne Buboltz
Design And Implementation Of A Hardware Level Content Networking Front End Device, Jeremy Layne Buboltz
Electronic Theses and Dissertations
The bandwidth and speed of network connections are continually increasing. The speed increase in network technology is set to soon outpace the speed increase in CMOS technology. This asymmetrical growth is beginning to causing software applications that once worked with then current levels of network traffic to flounder under the new high data rates. Processes that were once executed in software now have to be executed, partially if not wholly in hardware. One such application that could benefit from hardware implementation is high layer routing. By allowing a network device to peer into higher layers of the OSI model, the …