Physical Sciences and Mathematics Commons^™

A Comparative Study On Machine Learning Algorithms For Network Defense, Abdinur Ali, Yen-Hung Hu, Chung-Chu (George) Hsieh, Mushtaq Khan

Virginia Journal of Science

Network security specialists use machine learning algorithms to detect computer network attacks and prevent unauthorized access to their networks. Traditionally, signature and anomaly detection techniques have been used for network defense. However, detection techniques must adapt to keep pace with continuously changing security attacks. Therefore, machine learning algorithms always learn from experience and are appropriate tools for this adaptation. In this paper, ten machine learning algorithms were trained with the KDD99 dataset with labels, then they were tested with different dataset without labels. The researchers investigate the speed and the efficiency of these machine learning algorithms in terms of several …

Efficient Machine Learning Approach For Optimizing Scientific Computing Applications On Emerging Hpc Architectures, Kamesh Arumugam Karunanithi

Computer Science Theses & Dissertations

Efficient parallel implementations of scientific applications on multi-core CPUs with accelerators such as GPUs and Xeon Phis is challenging. This requires - exploiting the data parallel architecture of the accelerator along with the vector pipelines of modern x86 CPU architectures, load balancing, and efficient memory transfer between different devices. It is relatively easy to meet these requirements for highly-structured scientific applications. In contrast, a number of scientific and engineering applications are unstructured. Getting performance on accelerators for these applications is extremely challenging because many of these applications employ irregular algorithms which exhibit data-dependent control-flow and irregular memory accesses. Furthermore, these …

Sensys: A Smartphone-Based Framework For Its Applications, Abdulla Ahmed Alasaadi

Computer Science Theses & Dissertations

Intelligent transportation systems (ITS) use different methods to collect and process traffic data. Conventional techniques suffer from different challenges, like the high installation and maintenance cost, connectivity and communication problems, and the limited set of data. The recent massive spread of smartphones among drivers encouraged the ITS community to use them to solve ITS challenges.

Using smartphones in ITS is gaining an increasing interest among researchers and developers. Typically, the set of sensors that comes with smartphones is utilized to develop tools and services in order to enhance safety and driving experience. GPS, cameras, Bluetooth, inertial sensors and other embedded …

Computational Modeling For Abnormal Brain Tissue Segmentation, Brain Tumor Tracking, And Grading, Syed Mohammad Shamin Reza

Electrical & Computer Engineering Theses & Dissertations

This dissertation proposes novel texture feature-based computational models for quantitative analysis of abnormal tissues in two neurological disorders: brain tumor and stroke. Brain tumors are the cells with uncontrolled growth in the brain tissues and one of the major causes of death due to cancer. On the other hand, brain strokes occur due to the sudden interruption of the blood supply which damages the normal brain tissues and frequently causes death or persistent disability. Clinical management of these brain tumors and stroke lesions critically depends on robust quantitative analysis using different imaging modalities including Magnetic Resonance (MR) and Digital Pathology …

Modeling Energy Consumption Of High-Performance Applications On Heterogeneous Computing Platforms, Gary D. Lawson Jr.

Computational Modeling & Simulation Engineering Theses & Dissertations

Achieving Exascale computing is one of the current leading challenges in High Performance Computing (HPC). Obtaining this next level of performance will allow more complex simulations to be run on larger datasets and offer researchers better tools for data processing and analysis. In the dawn of Big Data, the need for supercomputers will only increase. However, these systems are costly to maintain because power is expensive. Thus, a better understanding of power and energy consumption is required such that future hardware can benefit.

Available power models accurately capture the relationship to the number of cores and clock-rate, however the relationship …

Methodology To Perform Cyber Lethality Assessment, Matthew W. Zurasky

Engineering Management & Systems Engineering Theses & Dissertations

The Naval Surface Warfare Center, Dahlgren Division (NSWCDD) Lethality and Effectiveness Branch is the Navy’s subject matter experts (SME) on target vulnerability, weapon lethality, and weapon effectiveness. Branch personnel currently exercise expertise in the kinetic and directed energy weapon domains. When the Navy develops weapons in the kinetic and directed energy domains, there are clear and well established procedures and methodologies for performing target characterization that support weapon-target pairing. Algorithms exist to describe the likelihood of damage effects. It is natural that in the paradigm shift to cyberspace warfare that the Branch provide these same services to the warfighter in …

Multi-Material Mesh Representation Of Anatomical Structures For Deep Brain Stimulation Planning, Tanweer Rashid

Computational Modeling & Simulation Engineering Theses & Dissertations

The Dual Contouring algorithm (DC) is a grid-based process used to generate surface meshes from volumetric data. However, DC is unable to guarantee 2-manifold and watertight meshes due to the fact that it produces only one vertex for each grid cube. We present a modified Dual Contouring algorithm that is capable of overcoming this limitation. The proposed method decomposes an ambiguous grid cube into a set of tetrahedral cells and uses novel polygon generation rules that produce 2-manifold and watertight surface meshes with good-quality triangles. These meshes, being watertight and 2-manifold, are geometrically correct, and therefore can be used to …

Algorithms For Constructing Vehicle Trajectories In Urban Networks Using Inertial Sensors Data From Mobile Devices, Umana Ahmed

Computational Modeling & Simulation Engineering Theses & Dissertations

Vehicle trajectories are an important source of information for estimating traffic flow characteristics. Lately, several studies have focused on identifying a vehicle’s trajectory in traffic network using data from mobile devices. However, these studies predominantly employed GPS coordinate information for tracking a vehicle’s speed and position in the transportation network. Considering the known limitations of GPS, such as, connectivity issues at urban canyons and underpasses, low precision of localization, high power consumption of device while GPS is in use, this research focuses on developing alternate methods for identifying a vehicle’s trajectory at an intersection and at a urban grid network …

Multi-Gpu Accelerated High-Fidelity Simulations Of Beam-Beam Effects In Particle Colliders, Naga Sai Ravi Teja Majeti

Computer Science Theses & Dissertations

Numerical simulation of beam-beam effects in particle colliders are crucial in understanding and the design of future machines such as electron-ion colliders (JLEIC), linac-ring machines (eRHIC) or LHeC. These simulations model the non-linear collision dynamics of two counter rotating beams in particle colliders for millions of turns. In particular, at each turn, the algorithm simulates the collision of two directed beams propagating at different speeds with different number of bunches each. This leads to non-pair-wise collisions of beams with different number of bunches that results in an increase in the computational load proportional to the number of bunches in the …

Itsblue: A Distributed Bluetooth-Based Framework For Intelligent Transportation Systems, Ahmed Awad Alghamdi

Computer Science Theses & Dissertations

Inefficiency in transportation networks is having an expanding impact, at a variety of levels. Transportation authorities expect increases in delay hours and in fuel consumption and, consequently, the total cost of congestion. Nowadays, Intelligent Transportation Systems (ITS) have become a necessity in order to alleviate the expensive consequences of the rapid demand on transportation networks. Since the middle of last century, ITS have played a significant role in road safety and comfort enhancements. However, the majority of state of the art ITS are suffering from several drawbacks, among them high deployment costs and complexity of maintenance.

Over the last decade, …

Finite Element Modeling Driven By Health Care And Aerospace Applications, Fotios Drakopoulos

Computer Science Theses & Dissertations

This thesis concerns the development, analysis, and computer implementation of mesh generation algorithms encountered in finite element modeling in health care and aerospace. The finite element method can reduce a continuous system to a discrete idealization that can be solved in the same manner as a discrete system, provided the continuum is discretized into a finite number of simple geometric shapes (e.g., triangles in two dimensions or tetrahedrons in three dimensions).

In health care, namely anatomic modeling, a discretization of the biological object is essential to compute tissue deformation for physics-based simulations. This thesis proposes an efficient procedure to convert …

Speech Based Machine Learning Models For Emotional State Recognition And Ptsd Detection, Debrup Banerjee

Electrical & Computer Engineering Theses & Dissertations

Recognition of emotional state and diagnosis of trauma related illnesses such as posttraumatic stress disorder (PTSD) using speech signals have been active research topics over the past decade. A typical emotion recognition system consists of three components: speech segmentation, feature extraction and emotion identification. Various speech features have been developed for emotional state recognition which can be divided into three categories, namely, excitation, vocal tract and prosodic. However, the capabilities of different feature categories and advanced machine learning techniques have not been fully explored for emotion recognition and PTSD diagnosis. For PTSD assessment, clinical diagnosis through structured interviews is a …

Scalable And Fully Distributed Localization In Large-Scale Sensor Networks, Miao Jin, Su Xia, Hongyi Wu, Xianfeng David Gu

Electrical & Computer Engineering Faculty Publications

This work proposes a novel connectivity-based localization algorithm, well suitable for large-scale sensor networks with complex shapes and a non-uniform nodal distribution. In contrast to current state-of-the-art connectivity-based localization methods, the proposed algorithm is highly scalable with linear computation and communication costs with respect to the size of the network; and fully distributed where each node only needs the information of its neighbors without cumbersome partitioning and merging process. The algorithm is theoretically guaranteed and numerically stable. Moreover, the algorithm can be readily extended to the localization of networks with a one-hop transmission range distance measurement, and the propagation of …

Granting Personhood For Sentient Non-Human Animals And Sentient Artificial Intelligences: A Demonstrative Argument, Jeremiah Meadows

Virginias Collegiate Honors Council Conference

While the subject of personhood has been exhaustively debated regarding the unborn, personhood for sentient animals and artificial intelligences is a concept that is rarely deliberated. Humanity has learned that there are multiple animal species which are very similar to humans in their self-awareness, emotional capacity, and free will. These traits have been partially developed for artificial intelligences as well, and those characteristics will evolve alongside human and technological development. As stratified societies emerged, there have been multiple occurrences where individuals were deemed lesser but then later acquired equal standing. Dr. Daniel Wilson, roboticist, wrote in his novel Robopocalypse, “It …

A Predictor Analysis Framework For Surface Radiation Budget Reprocessing Using Design Of Experiments, Patricia Allison Quigley

Engineering Management & Systems Engineering Theses & Dissertations

Earth’s Radiation Budget (ERB) is an accounting of all incoming energy from the sun and outgoing energy reflected and radiated to space by earth’s surface and atmosphere. The National Aeronautics and Space Administration (NASA)/Global Energy and Water Cycle Experiment (GEWEX) Surface Radiation Budget (SRB) project produces and archives long-term datasets representative of this energy exchange system on a global scale. The data are comprised of the longwave and shortwave radiative components of the system and is algorithmically derived from satellite and atmospheric assimilation products, and acquired atmospheric data. It is stored as 3-hourly, daily, monthly/3-hourly, and monthly averages of 1°x1° …

Role Of Requirements Engineering In Software Project’S Success, Sujatha Alla

Engineering Management & Systems Engineering Theses & Dissertations

Despite considerable time and resources spent on the initiation phase of software projects, discrepancies often exist between formal project documentation, customer requirements, and final project specifications. Such discrepancies in the requirements management process can have a very negative impact on final project outcomes. A Business Requirements Document (BRD) constitutes the formal software requirements documentation, which typically includes stakeholders’ needs and expectations and project scope while providing a clear project roadmap and project plan. According to IEEE standards, a BRD should be a structured document that includes specific elements such as functional and technical requirements while incorporating certain traits such as …

Detecting Agitation Onset In Individuals With Dementia Using Smart Phone Sensors, Christianne Fowler, Ajay Gupta, Kurt Maly, Karen Karlowicz, Maheedhar Gunnam, Rohila Gudipati, Mahesh Kukunooru, Rahul Rachamalla

Nursing Faculty Publications

Individuals living with dementia (ILWD) often experience problematic agitated behaviors, this occurs in up to 80% of ILWD. These behaviors lead to stress for caregivers and increased frequency of institutionalization. There are many proven methods to intervene during agitated behavior outburst and the earlier these methods are used the better the results. Technology has been used successfully to monitor many aspects of health monitoring for older adults. Technology is now being investigated to evaluate the effectiveness of predicting the onset of problem behaviors, especially escalating agitation in ILWD. Off the shelf technology, smart watches and android phones, are being tested …

Simulations Of Coherent Synchrotron Radiation On Parallel Hybrid Gpu/Cpu Platform, B. Terzić, K. Arumugam, D. Duffin, A. Godunov, T. Islam, D. Ranjan, S. Sangam, Mohammad Zubair

Physics Faculty Publications

Coherent synchrotron radiation (CSR) is an effect of self-interaction of an electron bunch as it traverses a curved path. It can cause a significant emittance degradation, as well as fragmentation and microbunching. Numerical simulations of the 2D/3D CSR effects have been extremely challenging due to computational bottlenecks associated with calculating retarded potentials via integrating over the history of the bunch. We present a new high-performance 2D, particle-in-cell code which uses massively parallel multicore GPU/GPU platforms to alleviate computational bottlenecks. The code formulates the CSR problem from first principles by using the retarded scalar and vector potentials to compute the self-interaction …

Gender Difference And Employees' Cybersecurity Behaviors, Mohd Anwar, Wu He, Ivan Ash, Xiaohong Yuan, Ling Li, Li Xu

Information Technology & Decision Sciences Faculty Publications

Security breaches are prevalent in organizations and many of the breaches are attributed to human errors. As a result, the organizations need to increase their employees' security awareness and their capabilities to engage in safe cybersecurity behaviors. Many different psychological and social factors affect employees' cybersecurity behaviors. An important research question to explore is to what extent gender plays a role in mediating the factors that affect cybersecurity beliefs and behaviors of employees. In this vein, we conducted a cross-sectional survey study among employees of diverse organizations. We used structural equation modelling to assess the effect of gender as a …

Error Aggregation In The Reengineering Process From 3d Scanning To Printing, Jennifer G. Michaeli, Matthew C. Degroff, Roman C. Roxas

Engineering Technology Faculty Publications

This work aims to study the aggregation of dimensional errors in the reengineering processes using 3D scanning and printing without initial design drawings. A 57-tooth spur gear is used as an example to facilitate the discussion. Two approaches are investigated. The first one builds the gear model based upon measurement taken from a caliper, and the second approach uses a 3D scanner to collect geometry data. Dimensional errors in each stage of these two approaches are investigated. Particular attention is paid to the geometry data flow in the reengineering process from data acquisition and editing to model construction. Recommendations are …

Power Budgets For Cubesat Radios To Support Ground Communications And Inter-Satellite Links, Otilia Popescu

Engineering Technology Faculty Publications

CubeSats are a class of pico-satellites that have emerged over the past decade as a cost-effective alternative to the traditional large satellites to provide space experimentation capabilities to universities and other types of small enterprises, which otherwise would be unable to carry them out due to cost constraints. An important consideration when planning CubeSat missions is the power budget required by the radio communication subsystem, which enables a CubeSat to exchange information with ground stations and/or other CubeSats in orbit. The power that a CubeSat can dedicate to the communication subsystem is limited by the hard constraints on the total …

Efficient Core Utilization In A Hybrid Parallel Delaunay Meshing Algorithm On Distributed-Memory Cluster, Daming Feng, Andrey N. Chernikov, Nikos P. Chrisochoides

Computer Science Faculty Publications

Most of the current supercomputer architectures consist of clusters of nodes that are used by many clients (users). A user wants his/her job submitted in the job queue to be scheduled promptly. However, the resource sharing and job scheduling policies that are used in the scheduling system to manage the jobs are usually beyond the control of users. Therefore, in order to reduce the waiting time of their jobs, it is becoming more and more crucial for the users to consider how to implement the algorithms that are suitable to the system scheduling policies and are able to effectively and …

Deep Models For Engagement Assessment With Scarce Label Information, Feng Li, Guangfan Zhang, Wei Wang, Roger Xu, Tom Schnell, Jonathan Wen, Frederic Mckenzie, Jiang Li

Electrical & Computer Engineering Faculty Publications

Task engagement is defined as loadings on energetic arousal (affect), task motivation, and concentration (cognition) [1]. It is usually challenging and expensive to label cognitive state data, and traditional computational models trained with limited label information for engagement assessment do not perform well because of overfitting. In this paper, we proposed two deep models (i.e., a deep classifier and a deep autoencoder) for engagement assessment with scarce label information. We recruited 15 pilots to conduct a 4-h flight simulation from Seattle to Chicago and recorded their electroencephalograph (EEG) signals during the simulation. Experts carefully examined the EEG signals and labeled …

Industrial Wireless Sensor Networks 2016, Qindong Sun, Schancang Li, Shanshan Zhao, Hongjian Sun, Li Xu, Arumugam Nallamathan

Information Technology & Decision Sciences Faculty Publications

The industrial wireless sensor network (IWSN) is the next frontier in the Industrial Internet of Things (IIoT), which is able to help industrial organizations to gain competitive advantages in industrial manufacturing markets by increasing productivity, reducing the costs, developing new products and services, and deploying new business models.

Semantic Inference On Clinical Documents: Combining Machine Learning Algorithms With An Inference Engine For Effective Clinical Diagnosis And Treatment, Shuo Yang, Ran Wei, Jingzhi Guo, Lida Xu

Information Technology & Decision Sciences Faculty Publications

Clinical practice calls for reliable diagnosis and optimized treatment. However, human errors in health care remain a severe issue even in industrialized countries. The application of clinical decision support systems (CDSS) casts light on this problem. However, given the great improvement in CDSS over the past several years, challenges to their wide-scale application are still present, including: 1) decision making of CDSS is complicated by the complexity of the data regarding human physiology and pathology, which could render the whole process more time-consuming by loading big data related to patients; and 2) information incompatibility among different health information systems (HIS) …

Qos Recommendation In Cloud Services, Xianrong Zheng, Li Da Xu, Sheng Chai

Information Technology & Decision Sciences Faculty Publications

As cloud computing becomes increasingly popular, cloud providers compete to offer the same or similar services over the Internet. Quality of service (QoS), which describes how well a service is performed, is an important differentiator among functionally equivalent services. It can help a firm to satisfy and win its customers. As a result, how to assist cloud providers to promote their services and cloud consumers to identify services that meet their QoS requirements becomes an important problem. In this paper, we argue for QoS-based cloud service recommendation, and propose a collaborative filtering approach using the Spearman coefficient to recommend cloud …

Long-Term Simulations Of Beam-Beam Dynamics On Gpus, B. Terzić, K. Arumugam, R. Majeti, C. Cotnoir, M. Stefani, D. Ranjan, A. Godunov, V. Morozov, H. Zhang, F. Lin, Y. Roblin, E. Nissen, T. Satogata

Physics Faculty Publications

Future machines such as the electron-ion colliders (JLEIC), linac-ring machines (eRHIC) or LHeC are particularly sensitive to beam-beam effects. This is the limiting factor for long-term stability and high luminosity reach. The complexity of the non-linear dynamics makes it challenging to perform such simulations which require millions of turns. Until recently, most of the methods used linear approximations and/or tracking for a limited number of turns. We have developed a framework which exploits a massively parallel Graphical Processing Units (GPU) architecture to allow for tracking millions of turns in a sympletic way up to an arbitrary order and colliding them …

Teaching Hands-On Cyber Defense Labs To Middle School And High School Students: Our Experience From Gencyber Camps, Peng Jiang, Xin Tian, Chunsheng Xin, Wu He

Electrical & Computer Engineering Faculty Publications

With the high demand of the nation for next generation cybersecurity experts, it is important to design and provide hands-on labs for students at the K-12 level in order to increase their interest in cybersecurity and enhance their confidence in learning cybersecurity skills at the young age. This poster reports some preliminary analysis results from the 2016 GenCyber summer camp held at Old Dominion University (ODU), which is part of a nationwide grant program funded by the National Security Agency (NSA) and the National Science Foundation (NSF). This poster also demonstrates the design of three hands-on labs which have been …

Sensitivity Analysis Method To Address User Disparities In The Analytic Hierarchy Process, Marie Ivanco, Gene Hou, Jennifer Michaeli

Mechanical & Aerospace Engineering Faculty Publications

Decision makers often face complex problems, which can seldom be addressed well without the use of structured analytical models. Mathematical models have been developed to streamline and facilitate decision making activities, and among these, the Analytic Hierarchy Process (AHP) constitutes one of the most utilized multi-criteria decision analysis methods. While AHP has been thoroughly researched and applied, the method still shows limitations in terms of addressing user profile disparities. A novel sensitivity analysis method based on local partial derivatives is presented here to address these limitations. This new methodology informs AHP users of which pairwise comparisons most impact the derived …

Human-Intelligence/Machine-Intelligence Decision Governance: An Analysis From Ontological Point Of View, Faisal Mahmud, Teddy Steven Cotter

Engineering Management & Systems Engineering Faculty Publications

The increasing CPU power and memory capacity of computers, and now computing appliances, in the 21st century has allowed accelerated integration of artificial intelligence (AI) into organizational processes and everyday life. Artificial intelligence can now be found in a wide range of organizational processes including medical diagnosis, automated stock trading, integrated robotic production systems, telecommunications routing systems, and automobile fuzzy logic controllers. Self-driving automobiles are just the latest extension of AI. This thrust of AI into organizations and everyday life rests on the AI community’s unstated assumption that “…every aspect of human learning and intelligence could be so precisely described …