Computer Sciences Commons^™

Static Extraction Of Dataflow Communication For Security, Laurentiu Radu Vanciu

Wayne State University Dissertations

The cost of security vulnerabilities in widely-deployed code such as mobile applications is high. As a result, many companies are using Architectural Risk Analysis (ARA) to find security vulnerabilities before releasing their applications. The existing analyses are focused on finding local coding bugs such as a hard-coded password, rather than architectural flaws such as bypassing the authentication component. During ARA, to find vulnerabilities that are architectural flaws, security architects use a forest-level view of the runtime architecture instead of reading the code. Unfortunately, such a view is often missing from the documentation or is inconsistent with the code.

This thesis …

Software Power Analysis And Optimization For Power-Aware Multicore Systems, Shinan Wang

Wayne State University Dissertations

Among all the factors in sustainable computing, power dissipation and energy consumption, arguably speaking, are fundamental aspects of modern computer systems. Different from performance metric, power dissipation is not easy to measure because hardware instrumentation is usually required. Yet as an indispensable component of a computer system, software becomes a major factor affecting power dissipation besides hardware energy-efficiency and power states. With detailed information on resource usage and power dissipation of an application/software, software developers will be able to leverage algorithms and implementations in order to produce power-efficient solutions. Hardware instrumentation, despite its accuracy, is costly and complicated to set …

In-Network Processing For Mission-Criticalwireless Networked Sensing And Control: A Real-Time, Efficiency, And Resiliency Perspective, Qiao Xiang

Wayne State University Dissertations

As wireless cyber-physical systems (WCPS) are increasingly being deployed in mission-critical applications, it becomes imperative that we consider application QoS requirements in in-network processing (INP). In this dissertation, we explore the potentials of two INP methods, packet packing and network coding, on improving network performance while satisfying application QoS requirements. We find that not only can these two techniques increase the

energy efficiency, reliability, and throughput of WCPS while satisfying QoS requirements of applications in a relatively static environment, but also they can provide low cost proactive protection against transient node failures in a more dynamic wireless environment.

We first …

On Ranked Approximate Matching Of Large Attributed Graphs, Mohammad Shafkat Amin

Wayne State University Dissertations

Many emerging database applications entail sophisticated graph based query manipulation, predominantly evident in large-scale

scientific applications. To access the information embedded in

graphs, efficient graph matching tools and algorithms have become of prime importance. Although the prohibitively expensive time

complexity associated with exact sub-graph isomorphism techniques has limited its efficacy in the application domain, approximate yet efficient graph matching techniques have received much attention due to their pragmatic applicability. Since public domain databases are noisy and incomplete in nature, inexact graph matching techniques have proven to be more promising in terms of inferring knowledge from numerous structural data repositories.

Contemporary …

Interference Modeling And Control In Wireless Networks, Xin Che

Wayne State University Dissertations

With the successful commercialization of IEEE802.11 standard, wireless networks have become a tight-knit of our daily life. As wireless networks are increasingly applied to real- time and mission-critical tasks, how to ensuring real-time, reliable data delivery emerges as an important problem. However, wireless communication is subject to various dynamics and uncertainties due to the broadcast nature of wireless signal. In particular, co-channel interfer- ence not only reduces the reliability and throughput of wireless networks, it also increases the variability and uncertainty in data communication [64, 80, 77].

A basis of interference control is the interference model which \emph{predicts} whether a …

Teak: A Novel Computational And Gui Software Pipeline For Reconstructing Biological Networks, Detecting Activated Biological Subnetworks, And Querying Biological Networks., Thair Judeh

Wayne State University Dissertations

As high-throughput gene expression data becomes cheaper and cheaper, researchers are faced with a deluge of data from which biological insights need to be extracted and mined since the rate of data accumulation far exceeds the rate of data analysis. There is a need for computational frameworks to bridge the gap and assist researchers in their tasks. The Topology Enrichment Analysis frameworK (TEAK) is an open source GUI and software pipeline that seeks to be one of many tools that fills in this gap and consists of three major modules. The first module, the Gene Set Cultural Algorithm, de novo …

Energy Efficiency Analysis And Optimization For Mobile Platforms, Grace Metri

Wayne State University Dissertations

The introduction of mobile devices changed the landscape of computing. Gradually, these devices are replacing traditional personal computer (PCs) to become the devices of choice for entertainment, connectivity, and productivity. There are currently at least 45.5 million people in the United States who own a mobile device, and that number is expected to increase to 1.5 billion by 2015.

Users of mobile devices expect and mandate that their mobile devices have maximized performance while consuming minimal possible power. However, due to the battery size constraints, the amount of energy stored in these devices is limited and is only growing by …

Algorithms And Tools For Computational Analysis Of Human Transcriptome Using Rna-Seq, Nan Deng

Wayne State University Dissertations

Alternative splicing plays a key role in regulating gene expression, and more than 90% of human genes are alternatively spliced through different types of alternative splicing. Dysregulated alternative splicing events have been linked to a number of human diseases. Recently, high-throughput RNA-Seq technologies have provided unprecedented opportunities to better characterize and understand transcriptomes, in particular useful for the detection of splicing variants between healthy and diseased human transcriptomes.

We have developed two novel algorithms and tools and a computational workflow to interrogate human transcriptomes between healthy and diseased conditions. The first is a read count-based Expectation-Maximization (EM) algorithm and tool, …

Building A Scalable And High-Performance Key-Value Store System, Yuehai Xu

Wayne State University Dissertations

Contemporary web sites can store and process very large amounts of data. To provide timely service to their users, they have adopted key-value (KV) stores, which is a simple but effective caching infrastructure atop the conventional databases that store these data, to boost performance. Examples are Facebook, Twitter and Amazon. As yet little is known about the realistic workloads outside of the companies that operate them, this dissertation work provides a detailed workload study on Facebook's Memcached, which is one of the world's largest KV deployment. We analyze the Memcached workload from the perspective of server-side performance, request composition, caching …

The Design, Analysis, & Application Of Multi-Modal Real-Time Embedded Systems, Masud Ahmed

Wayne State University Dissertations

For many hand-held computing devices (e.g., smartphones), multiple operational modes are preferred because of their flexibility. In addition to their designated purposes, some of these devices provide a platform for different types of services, which include rendering of high-quality multimedia. Upon such devices, temporal isolation among co-executing applications is very important to ensure that each application receives an acceptable level of quality-of-service. In order to provide strong guarantees on services, multimedia applications and real-time control systems maintain timing constraints in the form of deadlines for recurring tasks. A flexible real-time multi-modal system will ideally provide system designers the option to …

Selection Of Step Size For Total Variation Minimization In Ct, Anna N. Yeboah

College of Graduate Studies: Theses & Dissertations

Medical image reconstruction by total variation minimization is a newly developed area in computed tomography (CT). In compressed sensing literature, it hasbeen shown that signals with sparse representations in an orthonormal basis may be reconstructed via l1-minimization. Furthermore, if an image can be approximately modeled to be piecewise constant, then its gradient is sparse. The application of l1-minimization to a sparse gradient, known as total variation minimization, may then be used to recover the image. In this paper, the steepest descent method is employed to update the approximation of the image. We propose a way to estimate an optimal step …

Design Requirements For Generating Deceptive Content To Protect Document Repositories, Ben Whitham

Australian Information Warfare and Security Conference

For nearly 30 years, fake digital documents have been used to identify external intruders and malicious insider threats. Unfortunately, while fake files hold potential to assist in data theft detection, there is little evidence of their application outside of niche organisations and academic institutions. The barrier to wider adoption appears to be the difficulty in constructing deceptive content. The current generation of solutions principally: (1) use unrealistic random data; (2) output heavily formatted or specialised content, that is difficult to apply to other environments; (3) require users to manually build the content, which is not scalable, or (4) employ an …

A User-Oriented Network Forensic Analyser: The Design Of A High-Level Protocol Analyser, D Joy, F Li, N L. Clarke, S M. Furnell

Australian Digital Forensics Conference

Network forensics is becoming an increasingly important tool in the investigation of cyber and computer-assisted crimes. Unfortunately, whilst much effort has been undertaken in developing computer forensic file system analysers (e.g. Encase and FTK), such focus has not been given to Network Forensic Analysis Tools (NFATs). The single biggest barrier to effective NFATs is the handling of large volumes of low-level traffic and being able to exact and interpret forensic artefacts and their context – for example, being able extract and render application-level objects (such as emails, web pages and documents) from the low-level TCP/IP traffic but also understand how …

Carelessness And Affect In An Intelligent Tutoring System For Mathematics, Maria Ofelia Z. San Pedro, Ryan S.J.D Baker, Ma. Mercedes T. Rodrigo

Department of Information Systems & Computer Science Faculty Publications

We investigate the relationship between students’ affect and their frequency of careless errors while using an Intelligent Tutoring System for middle school mathematics. A student is said to have committed a careless error when the student’s answer is wrong despite knowing the skill required to provide the correct answer. We operationalize the probability that an error is careless through the use of an automated detector, developed using educational data mining, which infers the probability that an error involves carelessness rather than not knowing the relevant skill. This detector is then applied to log data produced by high-school students in the …

A Mobile Authoring Tool For Ar Content Generation Using Images As Annotations, Ma. Mercedes T. Rodrigo

Department of Information Systems & Computer Science Faculty Publications

Augmented Reality (AR) is a technology that allows the superimposition of virtual objects onto the real world environment. Various fields, such as education, medicine, and architecture, have started adapting AR technology. However, developing AR applications, along with their contents, requires a specific skillset, which limits the number of AR-based applications that can be developed. Various authoring tools are available for desktop systems to ease the development of AR applications and content, yet only few attempts have been made to develop these kinds of tools for mobile systems. This paper describes a mobile application that allows users to author content for …

Distributed Local Trust Propagation Model And Its Cloud-Based Implementation, Dharan Kumar Reddy Althuru

Browse all Theses and Dissertations

World Wide Web has grown rapidly in the last two decades with user generated content and interactions. Trust plays an important role in providing personalized content recommendations and in improving our confidence in various online interactions. We review trust propagation models in the context of social networks, semantic web, and recommender systems. With an objective to make trust propagation models more flexible, we propose several extensions to the trust propagation models that can be implemented as configurable parameters in the system. We implement Local Partial Order Trust (LPOT) model that considers trust as well as distrust ratings and perform evaluation …

Combating Integrity Attacks In Industrial Control Systems, Chad Arnold

Browse all Theses and Dissertations

Industrial Control Systems are vulnerable to integrity attacks because of connectivity to the external Internet and trusted internal networking components that can become compromised. Integrity attacks can be modeled, analyzed, and sometimes remedied by exploiting properties of physical devices and reasoning about the trust worthiness of ICS communication components.

Industrial control systems (ICS) monitor and control the processes of public utility that society depends on - the electric power grid, oil and gas pipelines, transportation, and water facilities. Attacks that impact the operations of these critical assets could have devastating consequences. The complexity and desire to interconnect ICS components have …

A Novel Synergistic Model Fusing Electroencephalography And Functional Magnetic Resonance Imaging For Modeling Brain Activities, Konstantinos Michalopoulos

Browse all Theses and Dissertations

Study of the human brain is an important and very active area of research. Unraveling the way the human brain works would allow us to better understand, predict and prevent brain related diseases that affect a significant part of the population. Studying the brain response to certain input stimuli can help us determine the involved brain areas and understand the mechanisms that characterize behavioral and psychological traits.

In this research work two methods used for the monitoring of brain activities, Electroencephalography (EEG) and functional Magnetic Resonance (fMRI) have been studied for their fusion, in an attempt to bridge together the …

Automated Complexity-Sensitive Image Fusion, Brian Patrick Jackson

Browse all Theses and Dissertations

To construct a complete representation of a scene with environmental obstacles such as fog, smoke, darkness, or textural homogeneity, multisensor video streams captured in diferent modalities are considered. A computational method for automatically fusing multimodal image streams into a highly informative and unified stream is proposed. The method consists of the following steps: 1. Image registration is performed to align video frames in the visible band over time, adapting to the nonplanarity of the scene by automatically subdividing the image domain into regions approximating planar patches

2. Wavelet coefficients are computed for each of the input frames in each modality …

The Properties Of Property Alignment On The Semantic Web, Michelle Andreen Cheatham

Browse all Theses and Dissertations

Ontology alignment is an important step in enabling computers to query and reason across the many linked datasets on the semantic web. This is a difficult challenge because the ontologies underlying different linked datasets can vary in terms of subject area coverage, level of abstraction, ontology modeling philosophy, and even language. The alignment approach presented here centers on string similarity metrics. Nearly all ontology alignment systems use a string similarity metric in one form or another, but it seems that the choice of a particular metric is often arbitrary. We begin this dissertation with the most comprehensive survey to date …

An Evolutionary Approximation To Contrastive Divergence In Convolutional Restricted Boltzmann Machines, Ryan R. Mccoppin

Browse all Theses and Dissertations

Deep learning is an emerging area in machine learning that exploits multi-layered neural networks to extract invariant relationships from large data sets. Deep learning uses layers of non-linear transformations to represent data in abstract and discrete forms. Several different architectures have been developed over the past few years specifically to process images including the Convolutional Restricted Boltzmann Machine. The Boltzmann Machine is trained using contrastive divergence, a depth-first gradient based training algorithm. Gradient based training methods have no guarantee of reaching an optimal solution and tend to search a limited region of the solution space. In this thesis, we present …

What Machines Understand About Personality Words After Reading The News, Eric David Moyer

Browse all Theses and Dissertations

Vector-based lexical semantics is a powerful technique that still has many undiscovered applications. In this thesis I apply a vector-space lexical-semantic model newly developed by Mikolov et. al. trained on skip-grams to the lexical hypothesis in personality psychology. The method produces interpretable dimensions that are consistent across several sets of descriptive personality words. The dimensions include ones for conflict and positive and negative evaluation. However they are more descriptive of word usage semantics than of the characteristics of the thing described and thus do not include a recognizable component of the 5 factor model in their first 14 dimensions. They …

Mining Privacy Settings To Find Optimal Privacy-Utility Tradeoffs For Social Network Services, Shumin Guo

Browse all Theses and Dissertations

Privacy has been a big concern for users of social network services (SNS). On recent criticism about privacy protection, most SNS now provide fine privacy controls, allowing users to set visibility levels for almost every profile item. However, this also creates a number of difficulties for users. First, SNS providers often set most items by default to the highest visibility to improve the utility of social network, which may conflict with users' intention. It is often formidable for a user to fine-tune tens of privacy settings towards the user desired settings. Second, tuning privacy settings involves an intricate tradeoff between …

Automatic Identification Of Interestingness In Biomedical Literature, Gaurish Anand

Browse all Theses and Dissertations

This thesis presents research on automatically identifying interestingness in a graph of semantic predications. Interestingness represents a subjective quality of information that represents its value in meeting a user's known or unknown retrieval needs. The perception of information as interesting requires a level of utility for the user as well as a balance between significant novelty and sufficient familiarity. It can also be influenced by additional factors such as unexpectedness or serendipity with recent experiences. The ability to identify interesting information facilitates the development of user-centered retrieval, especially in information semantic summarization and iterative, step-wise searching such as in discovery …

Personalizing Software Development Practice Using Mastery-Based Coaching, Chris Boesch, Sandra Boesch

Research Collection School Of Computing and Information Systems

The authors previously developed a system to facilitate the self-directed learning and practicing of software languages in Singapore. One of the goals of this self-directed learning was to enable the development of student mentors who would then be able to assist other students during classroom sessions. Building on this work, the authors extended the platform to support personalized coaching with the goals of further enabling and preparing students to mentor their peers. This paper covers the challenges, insights, and features that were developed in order to develop and deploy this mastery-based coaching feature.

A Decision Framework For Optimal Pairing Of Wind And Demand Response Resources, C. Lindsay Anderson, Judith Cardell

Engineering: Faculty Publications

Day-ahead electricity markets do not readily accommodate power from intermittent resources such as wind because of the scheduling difficulties presented by the uncertainty and variability in these resources. Numerous entities have developed methods to improve wind forecasting and thereby reduce the uncertainty in a day-ahead schedule for wind power generation. This paper introduces a decision framework for addressing the inevitable remaining variability resulting from imperfect forecasts. The framework uses a paired resource, such as demand response, gas turbine, or storage, to mitigate the generation scheduling errors due to wind forecast error. The methodology determines the cost-effective percentage, or adjustment factor, …

Hybrid Power System Options For Off-Grid Rural Electrification In Northern Kenya, June M. Lukuyu, Judith Cardell

Engineering: Faculty Publications

For domestic consumers in the rural areas of northern Kenya, as in other developing countries, the typical source of electrical supply is diesel generators. However, diesel generators are associated with both CO2 emissions, which adversely affect the environment and increase diesel fuel prices, which inflate the prices of consumer goods. The Kenya government has taken steps towards addressing this issue by proposing The Hybrid Mini-Grid Project, which involves the installation of 3 MW of wind and solar energy systems in facilities with existing diesel generators. However, this project has not yet been implemented. As a contribution to this effort, this …

Yeast Pheromone Pathway Modeling Using Petri Nets, Stephen D. Scott, Abhishek Majumdar, Jitender S. Deogun, Steven D. Harris

School of Computing: Conference and Workshop Papers

Background: Our environment is composed of biological components of varying magnitude. The relationships between the different biological elements can be represented as a biological network. The process of mating in S. cerevisiae is initiated by secretion of pheromone by one of the cells. Our interest lies in one particular question: how does a cell dynamically adapt the pathway to continue mating under severe environmental changes or under mutation (which might result in the loss of functionality of some proteins known to participate in the pheromone pathway). Our work attempts to answer this question. To achieve this, we first propose a …

A Comparison Of A Campus Cluster And Open Science Grid Platforms For Protein- Guided Assembly Using Pegasus Workflow Management System, Natasha Pavlovikj, Kevin Begcy, Sairam Behera, Malachy Campbell, Harkamal Walia, Jitender S. Deogun

School of Computing: Conference and Workshop Papers

Scientific workflows are a useful tool for managing large and complex computational tasks. Due to its intensive resource requirements, the scientific workflows are often executed on distributed platforms, including campus clusters, grids and clouds. In this paper we build a scientific workflow for blast2cap3, the protein-guided assembly, using the Pegasus Workflow Management System (Pegasus WMS). The modularity of blast2cap3 allows us to decompose the existing serial approach on multiple tasks, some of which can be run in parallel. Afterwards, this workflow is deployed on two distributed execution platforms: Sandhills, the University of Nebraska Campus Cluster, and the Open Science …

Transforming Web Tables To A Relational Database, David W. Embley, George Nagy, Sharad C. Seth

School of Computing: Conference and Workshop Papers

HTML tables represent a significant fraction of web data. The often complex headers of such tables are determined accurately using their indexing property. Isolated headers are factored to extract category hierarchies. Web tables are then transformed into a canonical form and imported into a relational database. The proposed processing allows for the formulation of arbitrary SQL queries over the collection of induced relational tables.