Computer Sciences Commons^™

Simple Analytic Performance Models For Streaming Data Applications Deployed On Diverse Architectures, Jonathan C. Beard, Roger D. Chamberlain, Mark A. Franklin

All Computer Science and Engineering Research

Modern hardware is inherently heterogeneous. With heterogeneity comes multiple abstraction layers that hide underlying complex systems. While hidden, this complexity makes quantitative performance modeling a difficult task. Designers of high-performance streaming applications for heterogeneous systems must contend with unpredictable and often non-generalizable models to predict performance of a particular application and hardware mapping. This paper outlines a computationally simple approach that can be used to model the overall throughput and buffering needs of a streaming application on heterogeneous hardware. The model presented is based upon a hybrid maximum flow and decomposed discrete queueing model. The utility of the model is …

Efficient Parallel Real-Time Upsampling Of Ultrasound Vectors, William D. Richard Ph.D.

All Computer Science and Engineering Research

Upsampling is required prior to the summation step in most receive digital beamforming implementations to produce an accurate summed RF line or vector. This is true in both annular and linear array systems where receive echos are digitized first and then time delayed in the digital domain to achieve proper signal alignment. The efficient, parallel, real-time upsampling circuit presented here produces M upsampled values per ADC clock, where M is the desired upsampling factor. A circuit implementation that upsamples by a factor of M=4 is presented as an example of the more general technique.

Ewa Model With Recency Effect And Limited Memory, Hang Xie

All Computer Science and Engineering Research

Game theory is an important field in economics; it studies how people make decisions amid conflict and cooperation. Various experiments have been carried to study the way people play those games, and economists study those data for various purposes. There has been a rise of need for using artificial agents to simulate the game, since we could save the cost of hiring human subjects for the experiments, and we could gain more control over the experiment settings.

Kernel Density Metric Learning, Yujie He, Wenlin Chen, Yixin Chen

All Computer Science and Engineering Research

This paper introduces a supervised metric learning algorithm, called kernel density metric learning (KDML), which is easy to use and provides nonlinear, probability-based distance measures. KDML constructs a direct nonlinear mapping from the original input space into a feature space based on kernel density estimation. The nonlinear mapping in KDML embodies established distance measures between probability density functions, and leads to correct classification on datasets for which linear metric learning methods would fail. Existing metric learning algorithms, such as large margin nearest neighbors (LMNN), can then be applied to the KDML features to learn a Mahalanobis distance. We also propose …

Self-Adapting Mac Layer For Wireless Sensor Networks, Mo Sha, Meng Xu, Chenyang Lu, Linh T.X. Phan, Tae-Suk Kim, Taerim Park

All Computer Science and Engineering Research

The integration of wireless sensors with mobile phones is gaining momentum as an enabling platform for numerous emerging applications. These mobile systems face dynamic environments where both application requirements and ambient wireless conditions change frequently. Despite the existence of many MAC protocols however, none can provide optimal performance along multiple dimensions, in particular when the conditions are frequently changing. Instead of pursuing a one-MAC-fit all approach we present a Self-Adapting MAC Layer (SAML) comprising (1) a Reconfigurable MAC Architecture (RMA) that can switch to different MAC protocols at run time and (2) a learning-based MAC Selection Engine that selects the …

Walkcompass: Finding Walking Direction Leveraging Smartphone's Inertial Sensors, Nirupam Roy

Theses and Dissertations

Determining moving direction with smartphone's inertial sensors is a well known problem in the field of location service. Compass alone cannot solve this problem because smartphone's compass cannot achieve high accuracy. Moreover GPS is not suitable in indoor scenario. Another well known approach is dead-reckoning but dead-reckoning needs to know phones initial orientation and over time it keeps accumulating errors and after some time the estimation becomes to noisy to use. To overcome these limitations, we propose a solution called WalkCompass which is specially designed for pedestrians keeping in mind the variation of force during normal human walk. Therefore the …

Multi-Label Segmentation Propagation For Materials Science Images Incorporating Topology And Interactivity, Jarrell Waggoner

Theses and Dissertations

Segmentation propagation is the problem of transferring the segmentation of an image to a neighboring image in a sequence. This problem is of particular importance to materials science, where the accurate segmentation of a series of 2D serial-sectioned images of multiple, contiguous 3D structures has important applications. Such structures may have prior-known shape, appearance, and/or topology among the underlying structures which can be considered to improve segmentation accuracy. For example, some materials images may have structures with a specific shape or appearance in each serial section slice, which only changes minimally from slice to slice; and some materials may exhibit …

Quasinovo: Algorithms For De Novo Peptide Sequencing, James Paul Cleveland

Theses and Dissertations

High-throughput proteomics analysis involves the rapid identification and characterization of large sets of proteins in complex biological samples. Tandem mass spectrometry (MS/MS) has become the leading approach for the experimental identification of proteins. Accurate analysis of the data produced is a computationally challenging process that relies on a complex understanding of molecular dynamics, signal processing, and pattern classification. In this work we address these modeling and classification problems, and introduce an additional data-driven evolutionary information source into the analysis pipeline.

The particular problem being solved is peptide sequencing via MS/MS. The objective in solving this problem is to decipher the …

Scanner: An Efficient And Accurate Trimming Tool For Illumina Next Generation Sequencing Reads, Xiang Zhou

All Computer Science and Engineering Research

Recent advances in High-Throughput Sequencing (HTS) technology have greatly facilitated the researches in bioinformatics field. With the ultra-high sequencing speed and improved base-calling accuracy, Illumina Genome Analyzer is currently the most widely used platform in the field. To use the raw reads generated from the sequencing machine, the 3’ adapter sequence attached to the real read in the process of ligation needs to be correctly trimmed. This is often done by some inhouse scripts or different packages with various parameters. They either use the Smith-Waterman algorithm or search for an exact match of the 3’ adapter sequence. In this report, …

Adding Data Parallelism To Streaming Pipelines For Throughput Optimization, Peng Li, Kunal Agrawal, Jeremy Buhler, Roger D. Chamberlain

All Computer Science and Engineering Research

The streaming model is a popular model for writing high-throughput parallel applications. A streaming application is represented by a graph of computation stages that communicate with each other via FIFO channels. In this report, we consider the problem of mapping streaming pipelines — streaming applications where the graph is a linear chain — in order to maximize throughput. In a parallel setting, subsets of stages, called components can be mapped onto different computing resources. The through-put of an application is determined by the throughput of the slowest component. Therefore, if some stage is much slower than others, then it may …

Real-Time Multi-Core Virtual Machine Scheduling In Xen, Sisu Xi, Meng Xu, Chenyang Lu, Linh T.X. Phan, Christopher Gill, Olga Sokolsky, Insup Lee

All Computer Science and Engineering Research

Recent years have witnessed two major trends in the development of complex real-time systems. First, to reduce cost and enhance flexibility, multiple systems are sharing common computing platforms via virtualization technology, instead of being deployed separately on physically isolated hosts. Second, multicore processors are increasingly being used in real-time systems. The integration of real-time systems as virtual machines (VMs) atop common multicore platforms raises significant new research challenges in meeting the real-time performance requirements of multiple systems.

Parallel Real-Time Scheduling Of Dags, Abusayeed Saifullah, David Ferry, Jing Li, Kunal Agrawal, Chenyang Lu, Christopher Gill

All Computer Science and Engineering Research

Recently, multi-core processors have become mainstream in processor design. To take full advantage of multi-core processing, computation-intensive real-time systems must exploit intra-task parallelism. In this paper, we address the open problem of real-time scheduling for a general model of deterministic parallel tasks, where each task is represented as a directed acyclic graph (DAG) with nodes having arbitrary execution requirements. We prove processor-speed augmentation bounds for both preemptive and non-preemptive real-time scheduling for general DAG tasks on multi-core processors. We first decompose each DAG into sequential tasks with their own release times and deadlines. Then we prove that these decomposed tasks …

Neural Network-Based Adaptive Event-Triggered Control Of Affine Nonlinear Discrete Time Systems With Unknown Internal Dynamics, Avimanyu Sahoo, Hao Xu, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, the design of a neural network (NN) based adaptive model-based event-triggered control of an uncertain single input single output (SISO) nonlinear discrete time system in affine form is presented. The controller uses an adaptive estimator consisting of a single-layer NN not only to approximate the internal dynamics of an affine nonlinear discrete-time system but also to provide an estimate of the state vector during inter event interval. The NN weights of the adaptive NN estimator are tuned in a aperiodic manner at the event trigger instants unlike periodic updates in standard adaptive neural network (NN) control. A …

Design, Construction And Load Testing Of The Pat Daly Road Bridge In Washington County, Mo, With Internal Glass Fiber Reinforced Polymers Reinforcement, Zhibin Lin, Mostafa Fakharifar, Chenglin Wu, Genda Chen, Wesley James Bevans, Arun Vijay Kumar Gunasekaran, Sahra Sedigh

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The overarching goal of this project is to deploy and assess an innovative corrosion-free bridge construction technology for long-term performance of new and existing bridges. The research objective of this project is to conduct a comprehensive study (instrumentation, construction, both laboratory and field evaluation) of a rapidly constructed and durable, three-span bridge with cast-in-place cladding steel reinforced concrete substructure and precast concrete decks/girders reinforced with glass fiber reinforced polymers (GFRP). The bridge has one conventional concrete-girder span, one conventional steel-girder span, and one innovative concrete box-girder span. The conventional concrete and steel girders were used to demonstrate the effective use …

Determining The Benefit Of Human Input In Human-In-The-Loop Robotic Systems, Christine Elizabeth Bringes

USF Tampa Graduate Theses and Dissertations

This work analyzes human-in-the-loop robotic systems to determine where human input can be most beneficial to a collaborative task. This is accomplished by implementing a pick-and-place task using a human-in-the-loop robotic system and determining which segments of the task, when replaced by human guidance, provide the most improvement to overall task performance and require the least cognitive effort.

The first experiment entails implementing a pick and place task on a commercial robotic arm. Initially, we look at a pick-and-place task that is segmented into two main areas: coarse approach towards a goal object and fine pick motion. For the fine …

Efficient And Private Processing Of Analytical Queries In Scientific Datasets, Anand Kumar

USF Tampa Graduate Theses and Dissertations

Large amount of data is generated by applications used in basic-science research and development applications. The size of data introduces great challenges in storage, analysis and preserving privacy. This dissertation proposes novel techniques to efficiently analyze the data and reduce storage space requirements through a data compression technique while preserving privacy and providing data security.

We present an efficient technique to compute an analytical query called spatial distance histogram (SDH) using spatiotemporal properties of the data. Special spatiotemporal properties present in the data are exploited to process SDH efficiently on the fly. General purpose graphics processing units (GPGPU or just …

A Robust Rgb-D Slam System For 3d Environment With Planar Surfaces, Po-Chang Su

Theses and Dissertations--Electrical and Computer Engineering

Simultaneous localization and mapping is the technique to construct a 3D map of unknown environment. With the increasing popularity of RGB-depth (RGB-D) sensors such as the Microsoft Kinect, there have been much research on capturing and reconstructing 3D environments using a movable RGB-D sensor. The key process behind these kinds of simultaneous location and mapping (SLAM) systems is the iterative closest point or ICP algorithm, which is an iterative algorithm that can estimate the rigid movement of the camera based on the captured 3D point clouds. While ICP is a well-studied algorithm, it is problematic when it is used in …

The Root Cause Of Failure In Complex It Projects: Complexity Itself, Kaitlynn M. Whitney, Charles B. Daniels

Engineering Management & Systems Engineering Faculty Publications

Increased demand for better technology and perpetual global expansion continue to provide developers with many project opportunities for success, as well as failure. While no industry is immune from project failure, the Information Technology (IT) industry is shown to be more susceptible to risk and failure than those of other industries. Agile project management, which facilitates adaptation to changing circumstances and alleviates rigid formal controls, has become more popular in the software development industry though is not entirely compatible with traditional project management approaches.In this paper we will examine the primary causes of IT project management failure stated in modern …

Detecting Semantic Method Clones In Java Code Using Method Ioe-Behavior, Rochelle Elva

Electronic Theses and Dissertations

The determination of semantic equivalence is an undecidable problem; however, this dissertation shows that a reasonable approximation can be obtained using a combination of static and dynamic analysis. This study investigates the detection of functional duplicates, referred to as semantic method clones (SMCs), in Java code. My algorithm extends the input-output notion of observable behavior, used in related work [1, 2], to include the effects of the method. The latter property refers to the persistent changes to the heap, brought about by the execution of the method. To differentiate this from the typical input-output behavior used by other researchers, I …

Active Learning With Unreliable Annotations, Liyue Zhao

Electronic Theses and Dissertations

With the proliferation of social media, gathering data has became cheaper and easier than before. However, this data can not be used for supervised machine learning without labels. Asking experts to annotate sufficient data for training is both expensive and time-consuming. Current techniques provide two solutions to reducing the cost and providing sufficient labels: crowdsourcing and active learning. Crowdsourcing, which outsources tasks to a distributed group of people, can be used to provide a large quantity of labels but controlling the quality of labels is hard. Active learning, which requires experts to annotate a subset of the most informative or …

An Exploration Of Unmanned Aerial Vehicle Direct Manipulation Through 3d Spatial Interaction, Kevin Pfeil

Electronic Theses and Dissertations

We present an exploration that surveys the strengths and weaknesses of various 3D spatial interaction techniques, in the context of directly manipulating an Unmanned Aerial Vehicle (UAV). Particularly, a study of touch- and device- free interfaces in this domain is provided. 3D spatial interaction can be achieved using hand-held motion control devices such as the Nintendo Wiimote, but computer vision systems offer a different and perhaps more natural method. In general, 3D user interfaces (3DUI) enable a user to interact with a system on a more robust and potentially more meaningful scale. We discuss the design and development of various …

A Compiler-Based Framework For Automatic Extraction Of Program Skeletons For Exascale Hardware/Software Co-Design, Amruth Rudraiah Dakshinamurthy

Electronic Theses and Dissertations

The design of high-performance computing architectures requires performance analysis of largescale parallel applications to derive various parameters concerning hardware design and software development. The process of performance analysis and benchmarking an application can be done in several ways with varying degrees of fidelity. One of the most cost-effective ways is to do a coarse-grained study of large-scale parallel applications through the use of program skeletons. The concept of a “program skeleton” that we discuss in this paper is an abstracted program that is derived from a larger program where source code that is determined to be irrelevant is removed for …

Discriminative Dictionary Learning With Spatial Constraints, Muhammad Nazar Khan

Electronic Theses and Dissertations

In this thesis, we investigate the use of dictionary learning for discriminative tasks on natural images. Our contributions can be summarized as follows: • We introduce discriminative deviation based learning to achieve principled handling of the reconstruction-discrimination tradeoff that is inherent to discriminative dictionary learning. • Since natural images obey a strong smoothness prior, we show how spatial smoothness constraints can be incorporated into the learning formulation by embedding dictionary learning into Conditional Random Field (CRF) learning. We demonstrate that such smoothness constraints can lead to state-of-the-art performance for pixel-classification tasks. • Finally, we lay down the foundations of super-latent …

Using Freebase, An Automatically Generated Dictionary, And A Classifier To Identify A Person's Profession In Tweets, Abraham Hall

Electronic Theses and Dissertations

Algorithms for classifying pre-tagged person entities in tweets into one of eight profession categories are presented. A classifier using a semi-supervised learning algorithm that takes into consideration the local context surrounding the entity in the tweet, hash tag information, and topic signature scores is described. In addition to the classifier, this research investigates two dictionaries containing the professions of persons. These two dictionaries are used in their own classification algorithms which are independent of the classifier. The method for creating the first dictionary dynamically from the web and the algorithm that accesses this dictionary to classify a person into one …

Automatically Acquiring A Semantic Network Of Related Concepts, Sean Szumlanski

Electronic Theses and Dissertations

We describe the automatic acquisition of a semantic network in which over 7,500 of the most frequently occurring nouns in the English language are linked to their semantically related concepts in the WordNet noun ontology. Relatedness between nouns is discovered automatically from lexical co-occurrence in Wikipedia texts using a novel adaptation of an information theoretic inspired measure. Our algorithm then capitalizes on salient sense clustering among these semantic associates to automatically disambiguate them to their corresponding WordNet noun senses (i.e., concepts). The resultant concept-to-concept associations, stemming from 7,593 target nouns, with 17,104 distinct senses among them, constitute a large-scale semantic …

Regret Based Robust Solutions For Uncertain Markov Decision Processes, Asrar Ahmed, Pradeep Reddy Varakantham, Yossiri Adulyasak, Patrick Jaillet

Research Collection School Of Computing and Information Systems

In this paper, we seek robust policies for uncertain Markov Decision Processes (MDPs). Most robust optimization approaches for these problems have focussed on the computation of maximin policies which maximize the value corresponding to the worst realization of the uncertainty. Recent work has proposed minimax regret as a suitable alternative to the maximin objective for robust optimization. However, existing algorithms for handling minimax regret are restricted to models with uncertainty over rewards only. We provide algorithms that employ sampling to improve across multiple dimensions: (a) Handle uncertainties over both transition and reward models; (b) Dependence of model uncertainties across state, …

Current-Mode Quadrature Oscillator Based On Cccdtas With Noninteractive Dual-Current Control For Both Condition Of Oscillation And Frequency Of Oscillation, Adirek Jantakun, Winai Jaikla

Turkish Journal of Electrical Engineering and Computer Sciences

The realization of 2 current-mode quadrature oscillators using current-controlled current differencing transconductance amplifiers (CCCDTAs) and grounded capacitors is presented. The proposed oscillators can provide 2 sinusoidal output currents with a 90° phase difference. They enable noninteractive dual-current control for both the condition of oscillation and the frequency ofi oscillation. The high-output impedances of the configurations enable the circuit to be cascaded without additional current buffers. The use of only grounded capacitors is ideal for integration. The circuit performances are depicted through PSpice simulations; they show good agreement to theoretical anticipation.

Ssr Mitigation With Sssc Thanks To Fuzzy Control, Seyed Mohammad Hassan Hosseini, Hadi Samadzadeh, Javad Olamaei, Murtaza Farsadi

Turkish Journal of Electrical Engineering and Computer Sciences

This paper deals with the capability of a static synchronous series compensator (SSSC) to attenuate the subsynchronous resonance (SSR). Two well-known controllers are designed, namely a conventional damping controller (CDC) and fuzzy logic damping controller (FLDC). These 2 damping controllers are added to a main control loop of a SSSC operating as a SSR damping controller. It should be noted that, to optimize the parameters of the CDC, a versatile optimization technique is implemented, namely particle swarm optimization (PSO). A comprehensive comparison between the 2 control methods is carried out for different operational conditions. To observe the superior performance of …

Automatic Detection Of Abnormal Behavior In Computing Systems, James Frank Roberts

Theses and Dissertations--Computer Science

I present RAACD, a software suite that detects misbehaving computers in large computing systems and presents information about those machines to the system administrator. I build this system using preexisting anomaly detection techniques. I evaluate my methods using simple synthesized data, real data containing coerced abnormal behavior, and real data containing naturally occurring abnormal behavior. I find that the system adequately detects abnormal behavior and significantly reduces the amount of uninteresting computer health data presented to a system administrator.

Information Security Challenge Of Qr Codes, Nik Thompson, Kevin Lee

Journal of Digital Forensics, Security and Law

The discipline of information security must adapt to new technologies and methods of interaction with those technologies. New technologies present both challenges and opportunities for the security professional, especially for areas such as digital forensics. Challenges can be in the form of new devices such as smartphones or new methods of sharing information, such as social networks. One such rapidly emerging interaction technology is the use of Quick Response (QR) codes. These offer a physical mechanism for quick access to Web sites for advertising and social interaction. This paper argues that the common implementation of QR codes potentially presents security …